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The copyright of this thesis rests with the University of Cape Town. No quotation from it or information derivedCape from it is to be published without full acknowledgement of theof source. The thesis is to be used for private study or non-commercial research purposes only.

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SELECTIVE ISOLATION AND CHARACTERISATION OF

INDIGENOUS ACTINOBACTERIA, WITH PARTICULAR EMPHASIS

ON THE GENUS Amycolatopsis

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Gareth John Everest

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Thesis presented for the Degree of Doctor of Philosophy in the Department of Molecular and Cell

Biology, Faculty of Science, University of Cape Town, South Africa.

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Table of Contents

Acknowledgments 5 List of Abbreviations 6 Abstract 10 Chapter 1 13 Introduction Chapter 2 89 Actinobacterial isolation and preliminary identification, antibiotic screening and extraction Town Chapter 3 123 Identification and characterisation of isolated actinobacteria Chapter 4 Cape 175 The use of gyrB and recN gene sequences in the phylogenetic analysis of the genus Amycolatopsis of Chapter 5 213 General discussion Appendices 221

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Acknowledgements

First and foremost I would like to thank my supervisor Dr Paul Meyers for his continued support, guidance and encouragement throughout this project. His enthusiasm towards research is contagious and has most certainly rubbed off during the five years under his supervision, something for which I will always be in his debt.

I am also grateful to the National Research Foundation and the University Scholarships Committee

(UCT) for financial support throughout my studies, without which it would have been difficult for me to have reached this point.

Town My thanks must also go out to all those who in some way or another contributed to the work in this thesis: to Di James and Bruna Galvão for DNA sequencing; Miranda Waldron for her assistance with scanning electron microscopy; Jerome Diedericks forCape collecting the soil sample from which I performed the isolation and Professor J. P. Euzébyof and Professor Dr H. G. Trüper for assistance with deriving the species names for four of my strains.

Further thanks must be said to all my past and present lab mates – Andrew, Bronwyn, Darren, Henrique, Iulia, Jeff, Marilize,University Saeed and all the Honours students who have passed through the lab, for all their help with experiments, opinions and interpretation of results and for making the time spent in the lab mostly fun and always memorable.

Last, but certainly by no means least, a big thank you to my mother, father and brother for all their love and support throughout my studies at UCT and for putting up with me over the years, I’m sure it wasn’t always easy.

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List of Abbreviations

7H9 - Middlebrook 7H9 (agar/broth) A - adenine (DNA base) ACD - albumin-dextrose-catalase ADRA - amplified DNA restriction analysis AFLP - amplified fragment length polymorphism ANI - average nucleotide identity ARDRA - amplified ribosomal DNA restriction analysis Ala - alanine A-site - aminoacyl site on the ribosome ATCC - American Type Culture Collection ATP - adenosine triphosphate Town bp - base pairs (DNA) BLAST - basic local alignment search tool blastn - nucleotide BLAST Cape C - cytosine (DNA base) CAS - cerium (IV) ammoniumof sulphate cm - centimeters CZ - Czapek solution (agar/broth) DAP - diaminopimelic acid DDH - DNA-DNA hybridisation DGGE - denaturing gradient gel electrophoresis DMSO - University dimethyl sulfoxide DNA - deoxyribonucleic acid DOI - 2-deoxy scyllo inosose DOTS - directly observed treatment, short course DPG - diphosphatidylglycerol DSMZ - Deutsche Sammlung von Mikroorganismen und Zellkulturen dNTP - deoxyribonucleotide triphosphate EDTA - ethylenediamine tetraacetic acid e.g. - exempli gratia, “for the sake of example” (for example) 7 etc - et cetera, “and the rest” or “so forth” Fig - figure fMET - formylmethionine (proteinogenic amino acid) g - grams G - guanine (DNA base) GBDP - genomic BLAST distance phylogeny gly - glycerol h - hours HGT - horizontal gene transfer HIV - human immunodeficiency virus HPLC - high performance liquid chromatography I - inosine (nucleoside) i.e. - id est, “it is” or “that is (to say)” ISP - International Streptomyces Project Town ITS - internally transcribed spacer I.U. - International Unit kb - kilobase pairs (103 bp) (DNA)Cape km - kilometers of km2 - square kilometers KRCA - Kenilworth Racecourse conservation area KZN - Kwa-Zulu Natal Province l - liter LB - Luria-Bertani (agar/broth) m - University meters M - molar MALDI-TOF - matrix-assisted laser desorption/ionization – time-of-flight Mb - megabase pairs (106 bp) (DNA) MC - modified Czapek solution (agar/broth) MDR - multidrug-resistant mg - milligrams min - minutes ml - milliliters MLSA - multilocus sequence analysis 8 mm - millimeters mm2 - square millimeters mM - millimolar MRSA - methicillin-resistant Staphylococcus aureus MTT - thiazolyl blue tetrazolium bromide ng - nanograms nm - nanometers nt - nucleotides (DNA) OD - optical density PBP - penicillin binding proteins PC - phosphatidylcholine PCR - polymerase chain reaction PE - phosphatidylethanolamine PG - phosphatidylglycerol Town PI - phosphatidylinositol PIMs - phosphatidylinositol mannosides PME - phosphatidylmethylethanolamineCape RAPD - randomly amplified ofpolymorphic DNA Rf - retention factor RFLP - restriction fragment length polymorphism RNA - ribonucleic acid mRNA - messenger RNA rRNA - ribosomal RNA tRNA - University transfer RNA rpm - revolutions per minute s - seconds Sac. - Saccharopolyspora Sal. - Salinispora SCFA - short chain fatty acids SE - soil extract (agar) SEM - scanning electron microscopy Ser - serine sp. - species (singular) 9 sp. nov. - species nova, “new species” spp. - species (plural) Sta. - Streptoalloteichus subsp. - subspecies T - thymine (DNA base)

TA - annealing temperature TAE - tris-acetate EDTA buffer TE - tris-HCl/EDTA buffer TB - tuberculosis TLC - thin layer chromatography

Tm - melting temperature U - units UV - ultraviolet V - volts Town vs - versus v/v - volume for volume WHO - World Health OrganizationCape w/v - weight for volume of XDR - extensively drug-resistant x g - times gravity (g-force – relative centrifugal force) YEME - yeast extract malt extract (agar/broth) °C - degrees Celsius > - “greater than” or “more than” ≥ - University “greater than or equal to” µg - micrograms µl - microliters µM - micromolar λ - phage Lambda

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Abstract

A soil sample collected from within the fynbos-rich area that is surrounded by the horseracing track at Kenilworth Racecourse, Cape Town, served as the source for the isolation of filamentous actinobacteria. The sampling area is known to contain a wide range of biodiversity, including endemic and endangered plant species. A total of 112 bacterial strains were initially isolated and, following morphological examination and de-replication, 64 strains were presumptively identified as filamentous actinobacteria and screened for their ability to produce antibiotics active against Mycobacterium aurum A+, a non-pathogenic, fast growing mycobacterium with a similar antibiotic susceptibility profile to that of Mycobacterium tuberculosis. Moderate to very strong antimycobacterial activity was recorded for 31 isolates and all were identified to belong to the genus Streptomyces, based on a rapid identification method. Based solely on morphological examination, a further 17 isolates were noted as interesting and selected for preliminaryTown identification as well. Eight of these morphologically interesting isolates were identified to belong to the genus Streptomyces, with three being identified as Amycolatopsis, three as belonging to members of the family Micromonosporaceae, one to the genus Nocardia, oneCape to Gordonia , Nocardia or Skermania and one to either Kribbella or Nocardioides. The nine isolates with the highest antimycobacterial activity were further screened for activity against Escherichiaof coli and Staphylococcus aureus, subjected to antibiotic extraction and attempts were made to partially purify the active compounds. Only a weakly active compound from one of the Streptomyces strains was successfully isolated by column chromatography.

The genera to which the top nine antibiotic producing strains belong, as well as the genera to which the strains identified as Universitynon-Streptomyces by the rapid molecular identification method belong, were definitively determined by BLAST analysis of their 16S rRNA gene sequences. The closest relatives were determined by 16S rRNA gene and gyrB gene based phylogenetic analyses. All strains were subjected to physiological characterisation to allow them to be differentiated from the most closely related type strains with validly-published names. Three strains belonging to the genus Amycolatopsis were shown to be distinct from all closely related type species by gyrB sequence analysis, with DNA-DNA hybridisation and physiological differences confirming this. The single Kribbella isolate was shown to be distinct by DNA-DNA hybridisation. Two strains belonging to the genus Micromonospora showed a high level of similarity to each other and could not be 11 differentiated. However, they showed a high number of physiological differences to the closely related type strain of Micromonospora olivasterospora and are likely to be distinct from this species. Two isolated Nocardia strains seem likely to represent novel species, showing multiple physiological differences from their respective relatives (‘Nocardia rhamnosiphila’, Nocardia flavorosea, Nocardia carnea, Nocardia sienata, Nocardia testacea, Nocardia fluminea, Nocardia cummidelens, Nocardia salmonicida and Nocardia soli), but DNA-DNA hybridisation will be required to determine if they are new species. The nine antibiotic producing Streptomyces isolates were only subjected to basic physiological comparisons. Six of these strains may belong to the same new species. The single Verrucosispora strain showed physiological differences from its closest relative, Verrucosispora gifhornensis, but DNA-DNA hybridisation will be needed to distinguish between these strains.

Owing to its potential for antibiotic production, the genus Amycolatopsis was further investigated and Amycolatopsis type strains were screened for the presence of Town antibiotic biosynthetic genes. It was noted that Amycolatopsis strains sharing similar antibiotic biosynthetic potential were phylogenetically related. Partial gyrB gene sequences (>1 kb) were obtained from 34 type strains with validly-published names and four laboratory strains.Cape Partial recN gene sequences were obtained from 31 of these type strains and the four laboratoryof strains. Phylogenetic trees were constructed to determine the effectiveness of using the gyrB and recN genes to predict taxonomic relationships within the genus. The use of gyrB and recN gene sequence analysis as an alternative to DNA-DNA hybridisation was also assessed for distinguishing closely related species. The gyrB and recN gene based phylogeny mostly confirmed the conventional 16S rRNA gene-based phylogeny and thus provides additional support for certain of these 16S rRNA gene-based phylogenetic groupings. The gyrB gene, however, seemsUniversity to be more suited to phylogenetic studies than the recN gene within this genus. Although pairwise gyrB or recN gene sequence similarity cannot be used to predict the DNA relatedness between type strains, the genetic distances can be used as a means to assess quickly whether an isolate is likely to represent a new species in the genus Amycolatopsis. In particular, a gyrB genetic distance of >0.02 or a recN genetic distance of >0.04 between two Amycolatopsis strains is proposed to provide a good indication that they belong to different species (and that polyphasic taxonomic characterisation of the unknown strain is worth undertaking).

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CHAPTER 1

INTRODUCTIONTown

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Contents

1.1 Bacterial Taxonomy 17 1.1.1 The development of the taxonomy of bacteria 17 1.1.2 Polyphasic taxonomy 18 1.1.2.1 Classical characteristics 18 1.1.2.2 Chemotaxonomy 19 1.1.2.3 Molecular methods 22 1.1.2.3.1 “Gold standard” methods 22 1.1.2.3.2 Indirect methods 25 1.1.2.3.3 Direct methods 28

1.1.2.3.3.1 Comparative sequence analysis 28 1.1.2.3.3.1.1 Genes used in analysis Town 29 1.1.2.3.3.1.2 Horizontal gene transfer (HGT) 32

1.1.2.3.3.1.3 Multilocus sequence analysis (MLSA) 33 1.1.2.3.3.2 Whole genome basedCape methods 33 1.1.2.3.4 Non genomic molecularof methods 36 1.1.3 Future prospects 37

1.2 Actinobacteria 38 1.2.1 Importance of actinobacteria 40 1.2.2 Isolation and characterisation 44 1.2.3 DescriptionUniversity of selected genera 47 1.2.3.1 The genus Amycolatopsis 47 1.2.3.2 The genus Kribbella 49 1.2.3.3 The genus Micromonospora 50 1.2.3.4 The genus Nocardia 52 1.2.3.5 The genus Streptomyces 54 1.2.3.6 The genus Verrucosispora 58

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1.3 Antibiotics 59 1.3.1 A brief history of antibiotics 59 1.3.2 Sources of antibiotics 61 1.3.3 Mechanisms of action 62 1.3.3.1 Inhibition of cell wall synthesis 62 1.3.3.2 Inhibition of DNA and RNA synthesis 63 1.3.3.3 Inhibition of protein synthesis 64 1.3.3.4 Other sites of inhibition 65 1.3.4 Antibiotic resistance 65 1.3.4.1 Mechanisms of resistance 67 1.3.4.1.1 Reduced intracellular concentration of antibiotic 67 1.3.4.1.2 Inactivation of antibiotic 68 1.3.4.1.3 Alteration of target sites 68 1.3.4.2 Sources of antibiotic resistance and contributingTown factors 69 1.3.4.3 Infectious diseases and antibiotic resistance 72 1.3.4.3.1 Tuberculosis 73 1.3.4.4 Implications of antibiotic resistanceCape and potential solutions 75 of 1.4 Aims of this study 77

1.5 References 78

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CHAPTER 1

INTRODUCTION

1.1 Bacterial taxonomy

With man’s insatiable quest for knowledge and the desire to obtain an understanding of all around him, comes the need to collate this information in some way. Taxonomy is the branch of science that deals with the classification of organisms on the basis of their evolutionary relationships and is a means of organising the vast array of knowledge about these organisms in a logical way. This allows us to make informed decisions about one organism, based on its classification and the information known about other related organisms (Prescott et al., 2002d; Sohier et al., 2008).

1.1.1 The development of the taxonomy of bacteriaTown Originally, prokaryotic taxonomy was based on the use of the classical characteristics, simply borrowed from botanical and zoological classification systems, which include morphology, motility, biochemistry, physiology and ecology (Woese, 1994; Busse et al., 1996; Prescott et al., 2002d; Richter & Rosselló-Móra, 2009; Staley, 2009). Cape However, it was soon realised that these characteristics were too simple and variable to accuratelyof classify bacteria and the need for a natural classification system, which finds the relationships between organisms, was recognised. Despite the recognition of the need for this type of classification system, the technology was not available at the time (1950’s) to allow the establishment of such a system (Woese, 1994).

After a period where the concern with the classification of bacteria wavered somewhat and interests moved more into the University study of biochemical pathways and molecular and genetic mechanisms (providing little to no information on the evolution of bacteria), the sequencing of numerous molecules (e.g. insulin, fibrinopeptide, haemoglobin and cytochrome c) had began (late 1950’s to early 1960’s). This saw the development of the methods that had great potential to assist in the identification of the relationships between organisms. Despite this development, initially very few used this molecular sequence data for determining phylogenetic relationships, but rather only as a means to identify misclassified species. An increased interest in bacterial ecology lead to a resurgence in the interests in determining the relationships between organisms, as there was now an implicit need to know the natural relationships between organisms and hence their phylogeny (Woese, 1994). 18

The 1960’s and 1970’s saw the introduction of molecular characterisation methods, like DNA-DNA hybridisation (DDH) and DNA base composition, and later (late 1970’s to early 1980’s) the introduction of protein and RNA sequencing (most importantly 16S rRNA genes) into taxonomy (Richter & Rosselló-Móra, 2009; Staley, 2009). Numerous methods to determine the chemotaxonomic characteristics of bacteria were developed in the 1980’s and introduced as part of the standard taxonomic characterisation (Wayne et al., 1987; Busse et al., 1996). The increased use of these methods allowed for a natural classification scheme to be identified and allowed for the objective determination of organisms’ evolutionary relationships (Embley & Stackebrandt, 1994; Stackebrandt & Goebel, 1994).

1.1.2 Polyphasic taxonomy Since the realisation that the classification of bacteria based on a limited set of simple characteristics was not adequate to correctly classify them (Woese, 1994), with resultsTown often varying depending on the characteristics that were used (Prescott et al., 2002d), the combination of many different characteristics was seen as the best way to obtain a true representation of the relatedness of bacteria (Busse et al., 1996; Ludwig, 2007). This approach is known as a polyphasic classification scheme and is currently used to characterise bacteria, incorporatingCape phenotypic, chemotaxonomic and genotypic characteristics (Embley & Stackebrandt,of 1994; Busse et al., 1996; Prescott et al., 2002d; Coenye et al., 2005; Gevers et al., 2005; Ludwig, 2007).

1.1.2.1 Classical characteristics In the early days of bacterial taxonomy, classifications were based exclusively on morphological and physiological data (Busse et al., 1996; Embley & Stackebrandt, 1994; Prescott et al., 2002d), with a certain set of phenotypicUniversity attributes being characteristic of a particular species or taxonomic group (Staley, 2009). These so-called classical characteristics still form an important part of bacterial classification and provide us with a means to differentiate and identify bacteria (Prescott et al., 2002d).

Morphological characteristics Perhaps one of the earliest characteristics used in the classification of bacteria, morphology is generally fairly easy to study and can be used as a coarse guide of phylogenetic relatedness (Woese, 1994), as structural features are reliant on the expression of multiple genes and are mostly 19 independent of environmental changes (Prescott et al., 2002d). Multiple different morphological features can be studied and include: colony morphology and colour, staining behaviour of cells, cell morphology (size and shape), types of inclusion bodies, the presence of fruiting bodies, motility, the presence of flagella or cilia, the presence of spores or endospores, as well as spore morphology and location (Busse et al., 1996; Prescott et al., 2002d).

Physiological characteristics Determination of the physiological and metabolic characteristics of a bacterium provides a vast array of information, as the results are a reflection of the presence or absence of multiple enzymes and transport proteins. These are themselves gene products and therefore the tests provide an indirect analysis of the underlying microbial genome (Prescott et al., 2002d). There are a wide range of physiological tests that are routinely performed to characterise bacteria, with the determination of growth parameters (pH, temperature and salinity tolerance), the ability to degrade a range of different substrates, the ability to utilise various carbon and nitrogen sources,Town the production of secondary metabolites and tolerance of metabolic inhibitors or antibiotics being just a few examples (Busse et al., 1996; Prescott et al., 2002d). The specific tests used depend on the genus being characterised. Cape Ecological characteristics of Characteristics which affect the relationship between a bacterium and its environment are ecological in nature and often provide taxonomically relevant information, with multiple differences in ecological characteristics often being present between closely related organisms (Prescott et al., 2002d). Important ecological characteristics can include disease-causing ability, life cycle patterns, the nature of the relationships with symbionts and the preference for certain habitats (Prescott et al., 2002d; Gevers et al., 2005;University Staley, 2009).

1.1.2.2 Chemotaxonomy It has been demonstrated that the comparison of various chemotaxonomic markers serves as a reliable method to identify phylogenetic relationships between organisms (Komagata & Suzuki, 1987; Busse et al., 1996). In fact, the validity of many of the previously classified taxa (whose classification was based mainly on morphology) was called into question when chemotaxonomic data were considered, as many contained members differing greatly in their chemical composition. As a result, many strains were re-classified into new genera (Embley & Stackebrandt, 1994). It was also concluded by the ad hoc committee on the reconciliation of approaches to bacterial systematics 20 that substantial chemotaxonomic data are required to support the creation of new taxa (there should be consistency between members in the same families) (Wayne et al., 1987).

The cell can be seen as a collection of multiple chemical substances, many of which are common to certain groups of bacteria and are coded for by highly regulated enzymatic systems in the cell, which are sufficiently stable to be used as taxonomic markers. The analysis of these important cellular components forms the basis of chemotaxonomy (Komagata & Suzuki, 1987).

Cellular fatty acids Located mainly in the cytoplasmic and outer membranes (as components of phospholipids and lipopolysaccharides in Gram negative bacteria and phospholipids and lipoteichoic acids in Gram positive bacteria (Busse et al., 1996)), fatty acids form one of the most essential components of cellular lipids (Komagata & Suzuki, 1987). The presence and relative abundance of various types of fatty acids are analysed and a comparison with reference strains is Townmade for both classification and identification purposes (Huys et al., 1994; Busse et al., 1996). Certain fatty acid profiles or the detection of a specific fatty acid can be characteristic of a particular phylogenetic group (Komagata & Suzuki, 1987; Busse et al., 1996) and may even beCape able to differentiate between closely related species (Huys et al., 1994). One important factorof to take into account when comparing fatty acid profiles with databases for identification and classification is that the fatty acid composition is highly dependent on the growth conditions and therefore the cells need to be grown under standardised conditions to allow for meaningful comparisons to be made (Busse et al., 1996).

Mycolic acids Forming a characteristicUniversity lipid component of some genera of coryneform bacteria, mycolic acids are long chain 2-alkyl-3-hydroxy fatty acids that can be used to distinguish the limited number of genera known to contain them (including Corynebacterium, Dietzia, Gordonia, Mycobacterium, Nocardia, Rhodococcus, Turicella and Tsukamurella) from those that lack mycolic acids (Komagata & Suzuki, 1987; Busse et al., 1996). Furthermore the number of carbon atoms making up the mycolic acid molecule allows differentiation within the mycolic acid containing genera and certain types are characteristic of different genera (Busse et al., 1996). The analysis of mycolic acids is usually combined with other characterisations as the analysis only provides useful information for a limited number of genera (Busse et al., 1996).

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Respiratory isoprenoid quinones A constituent of both cytoplasmic and mitochondrial membranes, respiratory isoprenoid quinones play an important role in the electron transport chain and their analysis for bacterial characterisation is based on identifying the type of quinone, the length if the isoprenoid side chain as well as the number of saturated isoprenoid units. The presence of different types of quinones (or combinations thereof) are characteristic of different classes of bacteria, with the analysis of the side chains (both length and level of saturation) providing more important information for identification and differentiation. For example, only menaquinones are known to be present in Gram positive bacteria (with the level of saturation of the side chains allowing more detailed differentiation), while members of the α-, β- and γ-subclasses of Proteobacteria contain ubiquinones, with the δ- and ε- subclasses containing ubiquinones and menaquinones (Busse et al., 1996).

Polar lipids Polar lipids usually consist of a polar group linked to two fatty acids,Town and form the main constituents of bacterial membranes. There are many different types of polar lipids found in bacterial membranes, with the phospholipids being the most common, but polar lipids containing ornithine or serine and glycolipids lacking phosphorus are also present.Cape The presence of a single polar lipid or a particular combination can be characteristic of certain taxa, with there being five recognised phospholipid patterns (PI-V) that are used for the description and differentiation of Gram positive bacteria. Identification of the different lipids is achieved by comparing their Rf values and staining behaviour (after separation by thin-layer chromatography (TLC)) with that of references. However, the interpretation of the polar lipid profile can often be difficult to achieve (Busse et al., 1996).

Peptidoglycan analysis University Diamino acids form an essential component of the peptidoglycan layer in bacterial cell walls and are usually found at position 3 in the peptide stem. Although there is not much variation in the type of diamino acid present in the Gram negative bacteria (where meso-diaminopimelic acid (DAP) is the only diamino acid present), there is a fair amount of variation amongst Gram positive bacteria. The diamino acids that can be detected include meso- (DL-) and LL-DAP, L-ornithine, L-lysine and L- 2,4-diaminobutyric acid while D-ornithine may be present in the interpeptide bridge. Knowing what type of diamino acid is present provides important information for the classification of Gram positive bacteria, but offers little help for that of Gram negative bacteria (Komagata & Suzuki, 1987; Busse et al., 1996). 22

Whole cell sugars In addition to the presence of glucosamine and muramic acid in the peptidoglycan layer of the bacterial cell wall, there are also various kinds of sugars present (Komagata & Suzuki, 1987). Comparisons of the sugar components of the cell wall often provide valuable information for the classification and identification of bacteria (Komagata & Suzuki, 1987) and have been widely used to describe Gram positive bacteria (Busse et al., 1996). Certain groups of bacteria have different characteristic whole cell sugar patterns, an example being the filamentous actinobacteria for which there are five recognised sugar patterns (including one with no diagnostic sugars). However, there are some taxa that have no uniform sugar pattern (Komagata & Suzuki, 1987; Busse et al., 1996).

The presence of sugars is identified by differential staining and comparisons of their Rf values after TLC separation with those of reference standards. The identification of unusual sugars is often difficult to achieve due to the lack of suitable standards for comparison (Busse et al., 1996).

1.1.2.3 Molecular methods Town It was agreed by the ad hoc committee on the reconciliation of approaches to bacterial systematics (Wayne et al., 1987) that the complete DNA sequence of organisms should be used as the reference for determining their evolutionary relationships, with Capeorganisms that diverged early in evolutionary history experiencing greater genetic drift than thoseof that diverged later. The study of genes, as well as the proteins which they encode, can therefore provide considerable information about the relatedness of organisms and has thus become very important in bacterial taxonomy (Embley & Stackebrandt, 1994; Prescott et al., 2002d). Initially, before the advent of rapid DNA sequencing, this was achieved by using indirect methods, where the nucleotide sequence of the DNAs was not determined, but information was nevertheless provided on the level of DNA relatedness between the organisms being compared.University This progressed to the use of direct sequencing methods, which involve determining the actual DNA sequence, thereby providing far more detailed information on the phylogenetic relatedness between the organisms being compared (Ludwig, 2007). The increased use of molecular methods in bacterial taxonomy can be viewed as “a logical development that allows a more objective assessment of both genetic and epigenetic characters” (Embley & Stackebrandt, 1994).

1.1.2.3.1 “Gold standard” methods The best procedures available to assess DNA similarity are methods of DDH, which have been used since the 1970’s to determine relatedness amongst prokaryotes (Wayne et al., 1987; Coenye et al., 23

2005; Gevers et al., 2005; Goris et al., 2007; Sohier et al., 2008). Differences in the melting temperatures (Tm) of the DNAs are used in conjunction with hybridisation to further establish relatedness (Wayne et al., 1987; Stackebrandt & Goebel, 1994; Ludwig, 2007). Values of about

70% DNA relatedness (with less than 5°C difference in the Tms of the individual DNAs) are used as the cut off to determine whether strains belong to the same genomic species, with the additional requirement that the strains be phenotypically distinct (Wayne et al., 1987; Stackebrandt & Goebel, 1994; Stackebrandt & Ebers, 2006; Ludwig, 2007; Richter & Rosselló-Móra, 2009; Staley, 2009).

With the advent of rapid sequencing came the introduction of 16S rRNA gene sequence similarity as an additional means to assess the genomic relatedness of bacteria (Stackebrandt & Goebel, 1994; Stackebrandt et al., 2002). This development can be seen as a “major milestone in the concomitant ‘evolution’ of systematics and methods for characterisation” (Ludwig, 2007). The 16S rRNA molecule is ubiquitous, highly conserved and essential for the survival of the bacterium, as it is essential for protein synthesis (Embley & Stackebrandt, 1994; GürtlerTown & Stanisich, 1996; Rintala et al., 2001; Gevers et al., 2005; Lanoot et al., 2005a; Ludwig, 2007). It is thus an ideal source of evolutionary information (Lanoot et al., 2005a; Ludwig, 2007), with the evolution of the molecule accurately reflecting that of the organism as well (EmbleyCape & Stackebrandt, 1994; Konstantinidis & Tiedje, 2007). Currently, analysis based on theof 16S rRNA gene sequence forms the ‘backbone’ of bacterial taxonomy (Ludwig, 2007) with nearly every species’ phylogenetic analysis being based on a 16S rRNA gene sequence (Fox et al., 1992; Busse et al., 1996; Stackebrandt & Ebers, 2006). With the ever increasing number of sequences being deposited in public databases, it is unlikely that any other gene will catch up in terms of volume to that of the 16S rRNA gene (>400 000 sequences) (Konstantinidis & Tiedje, 2007; Ludwig, 2007). University Strains that have more than 70% DNA relatedness by DDH will usually possess greater than 97% 16S-rRNA gene sequence similarity (Gevers et al., 2005; Sohier et al., 2008), with most of the variability occurring in certain hypervariable regions (Stackebrandt & Goebel, 1994). This 97% threshold was based on the comparison of DDH values and 16S rRNA gene sequence similarities for a limited dataset (Stackebrandt & Goebel, 1994) and this conservative estimate was used by researchers for over a decade as a guide to determine when DDH experiments were needed to delineate species (Stackebrandt & Ebers, 2006). Stackebrandt & Ebers (2006) subsequently updated the dataset and, upon re-evaluation, found that the 97% threshold is far too low and recommended 24 the value above which DDH needs to be performed be adjusted to 98.7-99% 16S rRNA gene sequence similarity.

A study performed by Keswani & Whitman (2001) showed that the 16S rRNA gene sequence similarity can be used to predict the extent of DDH through the formulation of a logarithmic equation (ln(-lnD) = 0.53(ln(-lnS)) + 2.201, where D is the extent of DDH and S the 16S rRNA sequence similarity). However, if the rRNA of the organism possesses nonultrametric properties (in that the sequence does not accurately reflect the true evolutionary distance), other methods of inferring relationships may be more appropriate (the method can still be used as long as these factors are taken into account). This has far reaching consequences, as it allows the estimation of DDH values from easily-obtained 16S-rRNA gene sequences without actually having to perform the laborious DDH experiment (Keswani & Whitman, 2001). Despite its promise, this method has not been adopted.

Although both the 16S-rRNA gene sequencing and DDH methods Townare used as “the gold standards” for taxonomic delineation (Gianninò et al., 2003; Zeigler, 2003; Zeigler, 2005; Stackebrandt & Ebers, 2006; Ludwig, 2007), they both have certain drawbacks. Results obtained in DDH studies can be affected by numerous parameters in the Cape hybridisation experiment, including: DNA concentrations, purity and size of the DNA fragments;of incubation temperatures; the presence of differing RNA levels and by the method itself (Yoon & Park, 2000; Stackebrandt & Ebers, 2006; Goris et al., 2007; Ludwig, 2007). Reproducibility is thus its main problem (Keswani & Whitman, 2001; Zeigler, 2003; Zeigler, 2005) as well as the fact that no database can be generated from the results, owing to the comparative nature of the experiment (Gevers et al., 2005; Stackebrandt & Ebers, 2006; Goris et al., 2007; Ludwig, 2007; Richter & Rosselló-Móra, 2009). The whole process of performing the hybridisationUniversity experiment is time consuming and labour intensive (Busse et al., 1996; Gevers et al., 2005; Goris et al., 2007) with most laboratories not performing the studies themselves but instead relying on the services of specialised laboratories (Stackebrandt & Ebers, 2006). Furthermore, DDH can only be used to assess the relationships between closely related species but cannot be used to assess those between distantly related organisms (Keswani & Whitman, 2001). Conversely, the highly conserved nature of the 16S rRNA molecule results in it having a low taxonomic resolution (Gevers et al., 2005; Konstantinidis & Tiedje, 2007), meaning that 16S rRNA gene sequence comparisons do not allow closely related species to be distinguished (Keswani & Whitman, 2001). However, 16S-rRNA gene sequence analysis is very useful for genus level identification or for the comparison between distantly related species within a genus (Fox et al., 25

1992; Stackebrandt & Goebel, 1994; Busse et al., 1996; Gianninò et al., 2003; Santos & Ochman, 2004; Lanoot et al., 2005a; Park & Kilbane, 2006; Staley, 2009).

1.1.2.3.2 Indirect methods Before the technological advancements that allowed for researchers to be able to perform large scale sequencing and comparisons of nucleic acids; numerous methods were developed that indirectly allowed for the assessment of the underlying genomic similarity between organisms. These methods can be either pattern based techniques, where differences in the genomes are determined through the generation and visualisation of different sized DNA fragments, or can be a means to measure the nucleic acid composition and similarity (Ludwig, 2007).

Numerous methodologies have been developed that further capitalise on the 16S rRNA molecule, without requiring for it to be sequenced, thus making these methods quicker and easier to perform. These methods mainly employ the use of restriction endonucleaseTown digestions to produce characteristic fragment patterns that are used to identify and classify organisms. Despite the multitude of methods utilising the 16S rRNA gene, they also cannot distinguish between closely related organisms. Thus the development of alternativeCape methods that make use of other genes or gene products to assess the entire genome relatedness,of and hence phylogeny, were encouraged (Stackebrandt et al., 2002). The ad hoc committee stated that these methods should be quantitative and that their results should be able to be substantiated by DDH (Stackebrandt et al., 2002).

Genomic Guanine + Cytosine content The determination of the guanine + cytosine (G + C) content of the genome was one of the first classical methods used toUniversity characterise genomes and classify taxa (Busse et al., 1996; Ludwig, 2007). Despite the method providing no phylogenetic information, being limited to confirming an assignment to a particular taxon, it is an important characteristic that is still used in the description of taxonomic units today (Ludwig, 2007). The acceptable variation in G + C content within a species is ≤5%, with that of a genus being no more than 10% (Busse et al., 1996). Organisms having different G + C contents can be safely assumed to be different, however identical or very similar levels of G + C content cannot be used alone to characterise strains as belonging to closely related taxa as unrelated taxonomic groups can share the same G + C content (Busse et al., 1996; Ludwig, 2007).

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DNA-rRNA hybridisation Somewhat similar to DDH experiments described earlier, this method was used to clarify the relationships of many different bacteria and to demonstrate both the close relationships between certain groups as well as the heterogeneity within the groups (Busse et al., 1996). The method involves the probing of single stranded DNA that is fixed to a membrane with the labelled 16S rRNA of a reference strain. It allows the determination of how closely related the two strains are and can rapidly and reliably identify unknown strains (Busse et al., 1996). Despite its usefulness, this technique has largely been replaced by gene sequencing (Busse et al., 1996; Ludwig, 2007).

Restriction fragment length polymorphism (RFLP) Digestion of the genomic DNA with various restriction endonucleases, or combinations thereof, can be used to generate a complex pattern of restriction fragments that can be analysed and used to differentiate between closely related strains, be they in the same genus or even belonging to the same species (Busse et al., 1996; Ludwig, 2007). Although this techniqueTown has the ability to differentiate strains, with different patterns representing different organisms, it cannot be used to identify them, as strains sharing the same RFLP pattern may differ substantially in the primary sequences of the fragments (Ludwig, 2007). The RFLP type techniquesCape have been surpassed by DNA sequencing (Ludwig, 2007), despite being sensitive methodsof to quickly and accurately differentiate strains (Sohier et al., 2008).

The RFLP technique is often performed on PCR amplified DNA fragments to produce patterns that are far less complex (and thus easier to analyse than those of genomic DNA), with this modified version often being referred to as amplified DNA restriction analysis (ADRA) (Ludwig, 2007). Amplified ribosomal DNAUniversity restriction analysis (ARDRA) is one of the most common forms of the ADRA method (Ludwig, 2007), where the 16S rRNA gene is amplified and then digested with numerous restriction endonucleases and the resulting fragment patterns are visually analysed (Heyndrickx et al., 1996). This allows the differentiation between organisms and allows for them to be identified to the species level (Heyndrickx et al., 1996; Cook & Meyers, 2003).

Amplified fragment length polymorphism (AFLP) This method involves PCR amplification of restriction endonuclease digested genomic DNA. After the DNA has been digested, the fragments are ligated onto linkers or adaptors that contain targets for PCR primers. PCR amplification is then performed on the ligated restriction fragments using 27 primers with additional bases at their 3’ ends that will extend into the fragment. The extra bases at the 3’ end of the primer reduces the number of linkers the primer can effectively bind to, as the additional bases will need to be complimentary to the restriction fragment as well. Only the fragments that are complementary to the 3’ end of the primers will be amplified. This results in the production of a distinct pattern that can be used for differentiation between even very closely related strains (Vos et al., 1995; Ludwig, 2007).

Random amplification of polymorphic DNA (RAPD) Random sections of the genome can be amplified by performing PCR reactions with either a single PCR primer or mixture of PCR primers with relatively low stringency to generate a characteristic fragment pattern indicating the polymorphism of the DNA (Busse et al., 1996; Ludwig, 2007). RAPD methods have been used to produce genomic fingerprints of organisms and have been shown to have a high discriminatory power, serving to aid in the identification and differentiation of organisms (Busse et al., 1996; Roberts & Crawford, 2000). This methodTown is particularly useful in the examination of complex genomes (Roberts & Crawford, 2000) and has been used in the identification of streptomycetes and other filamentous actinobacteria (Rintala et al., 2001). The fingerprints obtained by RAPD are also highly reproducibleCape and the major products can be successfully utilised as genome probes (Roberts of& Crawford, 2000).

Denaturing gradient gel electrophoresis (DGGE) By performing gel electrophoresis of DNA fragments in the presence of a gradient of a denaturing agent, the degree of migration of the fragments will depend not on their size, but rather on the primary sequence of each fragment, as the point in the gradient at which the fragment will denature and therefore stop migratingUniversity will depend on its base composition (Busse et al., 1996; Ludwig, 2007). This method can therefore be used to rapidly assess the complexity of a sample that is comprised of a mixture of different DNA fragments of the same size that would migrate as a single band under normal gel electrophoresis conditions (Ludwig, 2007). The main use of this technique is therefore in the area of microbial ecology, where it is able to differentiate between the different microorganisms in an environmental sample, thereby saving time and resources by negating the need to clone and sequence the environmentally amplified 16S rRNA genes in order to determine the composition of the sample (Busse et al., 1996; Ludwig, 2007). Performing DGGE analysis on the PCR amplified 16S internally transcribed spacer (ITS) region has been shown to have a high resolution for differentiating closely related Streptomyces species (Park & Kilbane, 2006). This method could 28 potentially be combined with other indirect molecular methods (mentioned previously) to allow the determination of whether or not two strains are in fact the same organism.

1.1.2.3.3 Direct methods Unlike the indirect methods detailed above, the direct molecular methods provide a far greater amount of phylogenetic information as they rely on the knowledge of the primary sequence of the DNA concerned and consequently allow for a far greater level of analysis. It was thanks to the advancement of molecular sequencing technology that allowed for these methods to gain ground in taxonomy, with comparative sequence analysis being the most widely used direct method (Ludwig, 2007). Initially analysis was limited to the 16S rRNA gene. However, as the cost of sequencing has decreased, other genes have also been sequenced and included in phylogenetic analyses, with the sequencing subsequently being extended to the sequencing of whole genomes themselves (Coenye et al., 2005; Ludwig, 2007, Sohier et al., 2008; Bolshoy & Volkovich, 2009). The first genome to be sequenced was that of Haemophilus influenzae, which was completedTown in 1995.

1.1.2.3.3.1 Comparative sequence analysis The analysis of the sequences of conserved macromoleculesCape is currently standard practice and forms the basis of bacterial taxonomy, allowing rapid andof accurate identification as well as classification of bacteria (Coenye et al., 2005; Ludwig, 2007). This method was introduced before the comparison of whole genomes was possible and is still widely used, as it is presently not practical (in terms of time and money) to sequence the entire genome of every strain in the study set. This method reduces the amount of analysis needed by only analysing a subset of genes that are thought to represent the whole genome relatedness, while still providing adequate taxonomic information. University With regard to this method, Zeigler (2003) proposed the use of various protein encoding genes to predict genome relatedness, as the sequences of these genes (much like that of the 16S rRNA gene) change slowly over time and can therefore be used to assess phylogeny. Similarly, Santos & Ochman (2004) suggested a set of such genes that could be used to determine the phylogeny. For this type of method, the ad hoc committee recommended the use of at least five housekeeping genes to produce a significant amount of information to allow accurate phylogenetic classification (Stackebrandt et al., 2002; Coenye et al., 2005). However Zeigler (2003) suggested that this is unnecessary and that fewer, well selected genes are capable of producing results with equal or perhaps even greater power than those produced by DDH (Zeigler, 2003; Coenye et al., 2005). 29

1.1.2.3.3.1.1 Genes used in analysis Suitable genes include those that are widely distributed amongst bacteria and have orthologous sequences present in many free living bacteria (Stackebrandt et al., 2002; Zeigler, 2003), but each “gene set” must be unique to each genome, to prevent paralogues from confusing the analysis. The genes should also be of a size that provides sufficient evolutionary information, yet allows them to be sequenced relatively easily and the sequences should precisely and accurately predict the whole genome relatedness between pairs of strains (Zeigler, 2003). Apart from the 16S rRNA gene, there are a variety of housekeeping genes that are used to determine the phylogenetic relationships amongst bacteria. There are many different studies that have suggested sets of genes that may be appropriate, however there is often very little consensus between sets (Santos & Ochman, 2004).

16S rRNA variable regions and ITS region To try and combat the problem associated with the 16S rRNA sequence (in that it is highly conserved), the comparison of its hypervariable regions (StackebrandtTown & Goebel, 1994; Mehling et al., 1995; Kataoka et al., 1997) or of the 16S-23S ribosomal ITS region (Gürtler & Stanisich, 1996; Stackebrandt et al., 2002; Gianninò et al., 2003) have been proposed as alternatives to try and classify closely related species. Cape of Kataoka et al. (1997) showed that comparison of the variable α region (V6) of the 16S rRNA gene was adequate to identify members of the Streptomyces group to the species level, with the results comparing well with those obtained from DDH and sequence analysis of the whole 16S rRNA gene. Despite this, many arguments oppose the use of these variable regions (Stackebrandt & Goebel, 1994) due to the fact that some changes do occur outside of the variable regions and, by omitting these sequences, valuableUniversity information is lost, thus making the use of these regions statistically unsound. Furthermore the location of these variable regions is taxon specific and as a result may be difficult to isolate for novel species (Stackebrandt & Goebel, 1994). The highly variable nature of these regions also presents a drawback to their use in taxonomy: the multiple mutations occurring may hide the number of evolutionary events that actually occurred, possibly making classification difficult (Stackebrandt & Goebel, 1994). Therefore the use of these variable regions may be better in conjunction with other methods used to distinguish between closely related species. The Kataoka et al. (1997) method has not been adopted in Streptomyces taxonomy. The use of the 16S-23S spacer region seems more promising, as there is considerable variation in both the sequence and the length of this region amongst species. The presence of multiple copies of 30 the rRNA operon in many bacteria increases the likelihood of variation not only between species and genera, but also between strains (Gürtler & Stanisich, 1996; Gianninò et al., 2003). One possible drawback is the need for a highly conserved region to be present in the flanking 16S and 23S rRNA gene sequences appropriate for the design of primers to allow amplification of the spacer (Gürtler & Stanisich, 1996).

Even so, Salazar et al. (2000) demonstrated that the polymorphisms of the 16S-23S spacer sequence can be utilised to successfully discriminate between species belonging to the genus Saccharomonospora, while Park and Kilbane (2006) performed DGGE analysis on the ITS regions to differentiate between closely related Streptomyces species and between strains of the same species, finding that the resolving power was far greater than that of the 16S rRNA gene. gyrB The DNA gyrase β-subunit encoding gene, gyrB, has been extensivelyTown used in bacterial phylogeny. The gene has been used to discriminate between closely related strains belonging to the genus Pseudomonas, to group strains of the genus Acinetobacter and to classify Micromonospora strains, with the results being consistent with those of DDHCape (Kasai et al. , 2000). The differentiation of closely related species in the genus Fusobacteriumof is also possible by gyrB sequence analysis (Jin et al., 2004) and differentiation of many of the members of the Mycobacterium tuberculosis complex (MBTC) is attainable by gyrB–RFLP analysis (Chimara et al., 2004). More recently the gyrB gene has been successfully used to support the 16S-rRNA gene-based phylogenetic groupings in the actinobacterial genera Gordonia, Nocardiopsis, Amycolatopsis, Nocardia and Kribbella (Shen et al., 2006; le Roes et al., 2008; Yang et al., 2008; Everest & Meyers, 2009; Takeda et al., 2010; Kirby et al., 2010). Owing to theUniversity faster evolution rate of protein encoding genes like gyrB, they are able to provide a far higher resolution than that of the 16S rRNA gene and are therefore more useful to resolve closely related species (Volokhov et al., 2007). rpoB The rpoB gene, encoding the β-subunit of bacterial RNA polymerase, has emerged as a gene with great potential to be used as a phylogenetic marker. Owing to its evolutionarily ancient origin (Adékambi et al., 2008), it has been used in phylogenetic studies of both bacteria and archaea, with even partial rpoB sequences allowing the accurate identification of enteric bacteria (with better resolution than 16S rRNA gene analysis) (Mollet et al., 1997). The rpoB sequence has also been 31 demonstrated as a good alternative marker for phylogenetic studies of Mycoplasma species (Kim et al., 2003a) and was used to confirm the placement of Coxiella burnetii amongst the Proteobacteria (Mollet et al., 1998). The RpoB amino acid sequence is capable of resolving the higher taxonomic levels, such as domain or phylum, whilst the nucleic acid sequence allows resolution at the species and sub-species level (Volokhov et al., 2007; Adékambi et al., 2008). In general, the rpoB based phylogenetic analyses agree with those based on the 16S rRNA gene, but rpoB phylogenetic trees show an increased robustness, marked by higher levels of bootstrap support (Adékambi et al., 2008). recN A study of the ability of various protein encoding genes to meet all the requirements of a universal marker gene and to accurately reflect the level of genome similarity between pairs of strains found that recN, encoding a recombination and repair protein, showed the greatest potential to predict overall genome relatedness (Zeigler, 2003). Within the genus Geobacillus, the recN gene was found to have a higher resolving power than that of the 16S rRNA gene Townfor the assignment of strains to lower order taxa (genus, species and sub-species), but lower resolution for the assignment to higher order taxa (above family level) (Zeigler, 2005). Despite this, the genome identity estimated by the predictive model was higher than the actual identity Capecalculated by DDH, with values showing the greatest difference when very closely or distantlyof related sequences were compared. Thus it appears that the recN analysis method cannot be used alone to assign strains to species within the genus Geobacillus, although it does show great promise as a method for initial organisation into possible taxa (Zeigler, 2005).

Similar results were found within the family ‘Leuconostocaceae’, where recN phylogenetic analysis showed high resolutionUniversity and strong bootstrap support for the groupings within each of the three genera belonging to the family, but showed poor support for their unity as a family (Arahal et al., 2008). The ability to predict the level of genome similarity (and thus species identity) from the recN sequence alone within this family was also limited, but it could be used in some instances to classify strains to a species when the recN similarities were below the 84-96% sequence similarity uncertainty threshold (Arahal et al., 2008).

Other genes A few of the other genes that have been used in bacterial phylogenetic analyses include those encoding ribonuclease P (RNase P), the β-subunit of ATP-synthase, glutamine synthetase, elongation 32 factor Tu, a heat shock protein – Hsp65 (Yoon & Park, 2000), secA1 (Zelazny et al., 2005), dnaA, dnaK and rpoC genes (Arahal et al., 2008).

1.1.2.3.3.1.2 Horizontal gene transfer (HGT) Bacteria have the ability to exchange genetic material between cells through numerous mechanisms, a process which is commonly referred to as HGT (Gribaldo & Brochier, 2009). HGT can be considered as one of the most important factors that shape the bacterial genome (Philippe & Douady, 2003). This process potentially can have huge implications for the phylogenetic analysis of bacteria and therefore the importance and consequences of HGT have been extensively debated (Philippe & Douady, 2003; Coenye et al., 2005). Recombination events can lead to the replacement of the vertically inherited genes with foreign DNA that has been horizontally acquired and thereby erase any useful phylogenetic information for that particular gene (Philippe & Douady, 2003; Staley, 2009). The result is that phylogenies constructed based on genes that have undergone HGT are often flawed and organisms that are in fact not that closely related, Town now appear to be more so, as demonstrated in Fig 1.1.1. Incongruence between phylogenetic trees based on different genes is therefore one way to detect that HGT has occurred in the gene that is producing the inconsistent grouping, as is the detection of deviations in the sequenceCape composition, or anomalies in the sequence similarities (Philippe & Douady, 2003; Gribaldoof & Brochier, 2009).

University

Figure 1.1.1 Diagrammatic representation of the impact of HGT on phylogenetic trees. The broken lines represent a tree showing the true evolutionary relationships among the organisms 1 – 6, with the solid line representing a tree that shows the relationships as determined from one homologous gene. (A) The gene used was inherited vertically and therefore the tree represents the actual evolutionary history of the organisms, with a close relationship between organisms 3 and 4. (B) The gene used to construct the tree underwent HGT from an ancestor of organism 5 to an ancestor of organism 4, making them appear closely related. The phylogeny based on this gene is therefore not congruent with the actual phylogeny of the organisms. Taken from Gribaldo & Brochier (2009).

It has been reported that all genes within the genome are subject to HGT and recombination events, with the actual number of events for each gene being unknown. However, many genes still offer 33 good phylogenetic signals as they do not undergo recombination frequently enough to distort the phylogeny (Konstantinidis & Tiedje, 2007). The fact that HGT does not affect all genes to an equal extent (Gribaldo & Brochier, 2009) has lead to the development of three theoretical categories of genes: the hard core set, comprising genes that never undergo HGT events (or occurring at levels that are not detectable) and can be used to reveal the ‘true phylogeny’; the soft core set, which undergo few HGT events, making them able to reveal phylogeny on the small and intermediate evolutionary scale; and the shell genes, that undergo frequent HGT events and offer poor phylogenetic information (Philippe & Douady, 2003; Coenye et al., 2005).

1.1.2.3.3.1.3 Multilocus sequence analysis (MLSA) It has been widely questioned whether the use of a single marker gene can adequately reflect the true phylogenetic relatedness of bacteria, due to the possibility of HGT or variations in the rate of mutation of the gene compared to that of the whole genome (Coenye et al., 2005; Gevers et al., 2005; Konstantinidis & Tiedje, 2007; Ludwig, 2007; Gribaldo & Brochier,Town 2009). The use of a set of genes in the phylogenetic analysis of bacteria has been proposed as a way to more accurately assess their relatedness, by providing a more representative picture of the phylogeny (Konstantinidis et al., 2006; Ludwig, 2007). Typically a set of Cape six to eight genes is used in the analysis (Konstantinidis et al., 2006; Konstantinidis & Tiedje,of 2007), however it has been proposed that fewer (as few as three), well selected genes can still offer an accurate determination of the phylogenetic relationships (Konstantinidis et al., 2006). A wide range of different genes has been used in different studies. Such genes should ideally be characterised as being ubiquitous, have not undergone recombination, not be linked on the genome and be present in a single copy (Gevers et al., 2005). MLSA is highly reproducible and allows for the generation of a cumulative database for future comparisons and has beenUniversity shown to be highly effective at delineating closely related species, as well as having good intra-species discriminatory power (Rong et al., 2009).

1.1.2.3.3.2 Whole genome based methods The comparison of the sequences of entire genomes can be considered as the best way to accurately and definitively determine the relatedness of bacteria (Coenye et al., 2005; Konstantinidis & Tiedje, 2007; Sohier et al., 2008), as it is generally accepted that the bacterial genome holds all the information relating to its taxonomic affiliation (Wayne et al., 1987; Goris et al., 2007; Bolshoy & Volkovich, 2009). Until fairly recently, the sequencing of the entire genome was not possible (Goris et al., 2007). However, with the advances in sequencing technology more and more bacterial 34 genomes have been sequenced (Sohier et al., 2008; Staley, 2009) and GenBank recently reached the milestone of 1000 prokaryotic genomes sequence (October 2009). The increase in the number of whole genome sequences has consequently led to the development of numerous methods whereby these genomic sequences can be analysed and used to classify bacteria and to determine their phylogenetic relationships (Coenye et al., 2005; Sohier et al., 2008). Fig 1.1.2 shows a comparison of the taxonomic resolution of some of these and other taxonomic methods.

Town

Cape of Figure 1.1.2 Representation of the taxonomic resolution of selected methods in bacterial taxonomy. Resolutions were determine by Coenye et al. (2005) from published data and may therefore be regarded as speculative, requiring confirmation. Adapted from Coenye et al. (2005).

Average nucleotide identity (ANI) The calculation of the ANIUniversity between the conserved genes in sequenced genomes has been shown to be a strong measure of the genetic and evolutionary distance between the compared organisms (Goris et al., 2007), with the results showing a clear correlation with both 16S rRNA gene sequence similarity and DDH results (Goris et al., 2007; Konstantinidis & Tiedje, 2007). The method shows great potential to be used in bacterial taxonomy because of its precision and simplicity (Konstantinidis & Tiedje, 2007), the fact that it is not affected by HGT or variation in the rate of recombination of different genes and because it shows resolution at the sub-species level (Goris et al., 2007). Studies have shown that the 70% DDH cut off point used to delineate bacterial species corresponds to 95% ANI when all genes are compared (Goris et al., 2007; Konstantinidis & Tiedje, 2007; Richter & Rosselló-Móra, 2009), with the corresponding ANI value dropping to 85% when 35 only the protein encoding portion of the genomes is analysed (Goris et al., 2007). Thus ANI has the potential to replace cumbersome DDH experiments where there are whole genome sequences available (Goris et al., 2007; Richter & Rosselló-Móra, 2009).

Gene content Comparison of gene content is a novel method whereby the genomes are regarded as a “bag of genes” and the contents of these “bags” are compared to each other (Coenye et al., 2005). This method relies on the fact that the genomes will have a number of orthologous genes in common, with this number depending on their evolutionary distance, as the number of these shared genes will decrease rapidly as the organisms evolve (Coenye et al., 2005; Bolshoy & Volkovich, 2009). It has been reported that HGT does not cause bias in trees constructed based on gene content and they usually correspond well with 16S rRNA gene trees (Coenye et al., 2005).

Gene order Town The conservation of gene order in genomes can be used to determine the relationships between organisms. However, there can be very little conservation between the gene orders when the average identity between the protein sequences of orthologuesCape in the genomes is below 50%. In these cases, the actual presence of a gene is more preservedof than the order. Gene order can be lost relatively quickly due to intragenomic rearrangements and thus it is only capable of distinguishing between closely related organisms, having a poor resolution for inferring the more distant phylogenetic relationships between organisms (Coenye et al., 2005).

Presence or absence analysis The presence or absenceUniversity of specific molecular features in a genome (like families of protein encoding genes) has also been used to deduce the relationships between taxa. Protein folds, or protein families that have the same basic molecular shape but perhaps different amino acid sequences, are thought to be ideal markers for use in this method, as they can be seen as “fundamental molecular units” that are utilised by organisms. The conserved insertions and deletions (indels) or signature sequences in proteins are other molecular features that can be used for analysis, with distinct taxonomic groupings being based on the presence or absence of these shared features. Results obtained with these presence-or-absence analyses are similar to those of 16S rRNA gene sequence analyses (Coenye et al., 2005).

36

Other methods Genome blast distance phylogeny (GBDP) is based on the pairwise comparison of the whole genome of organisms and produces a distance matrix, with the phylogeny then being inferred from this matrix. Metabolic pathway reaction content comparison evaluates reaction pathways between organisms and trees are constructed based on the enzyme and reaction contents of these pathways reconstructed from the annotated genomic sequences. Both of these methods appear congruent with 16S rRNA gene based sequence analysis (Coenye et al., 2005). Nucleotide composition comparison makes use of biases in nucleotide composition (e.g. dinucleotide relative abundance) of the genomes to determine their relatedness, with the nucleotide frequencies generally being more similar between closely related organisms (Coenye et al., 2005). Similarly the oligonucleotide frequencies within a genome can be used to circumscribe species (Richter & Rosselló-Móra, 2009) as well as to classify and phylogenetically sort organisms (Takahashi et al., 2009). The topologies of the trees for species with similar G + C contents are consistent with those based on homologous genes at both the species and family level. The length of the oligonucleotide needed to resolveTown the relationships however, depends on the GC group as well as the phylogenetic level you wish to resolve (Takahashi et al., 2009). The comparison of gene length amongst orthologues has also been proposed as a useful method for taxonomic analysis, with results correlatingCape with the tree of life based on 16S rRNA gene sequence similarity (Bolshoy & Volkovich, of 2009). The determination of the percentage of conserved DNA between two genomes (like ANI) has been shown to correspond with DDH results and can therefore be used as an alternative to classify species, with the 70% DDH cut off correlating to 69% conserved DNA over the whole genome or 79% over the protein coding portion (Goris et al., 2007).

1.1.2.3.4 Non genomic Universitymolecular methods Besides the genomic based approaches, other molecular methods capitalising on cellular biomarkers are frequently used in taxonomic studies. These include the use of high performance liquid chromatography (HPLC), matrix-assisted laser desorption/ionisation time-of-flight (MALDI-TOF) mass spectroscopy and electrophoresis with UV detection.

HPLC based approaches make use of the analysis of secondary metabolite profiles to classify and identify organisms and have been used to successfully group certain fungal strains (Hansen et al., 2005). This approach could potentially be useful in the classification of bacteria that produce complex secondary metabolites (like the filamentous actinobacteria). MALDI-TOF on the other 37 hand can be used to rapidly classify bacteria to the genus, species or strain level based on the identification of certain protein biomarkers from its protein profile (Lay, 2000). When differentiating between spores of the genus Bacillus, protein profiling was shown to have more discriminating power than 16S rRNA gene sequence analysis and more accuracy than metabolic profiling, with the results obtained being similar to those of DDH (Dickinson et al., 2004). Furthermore this approach requires little to no processing of the cultures prior to analysis, but the experimental conditions must be carefully controlled to allow reproducibility (Lay, 2000). Short chain fatty acids (SCFA) have been routinely used in taxonomic studies of anaerobic bacteria and capillary electrophoresis with UV detection is one method that can be used to produce electropherograms of microbes, allowing the presence or absence of certain taxonomically interesting SCFA to be determined, thus facilitating classification of these organisms (Arellano et al., 1997).

Even though the methods just described are more rapid and lessTown laborious than genome based approaches, they are unlikely to be widely utilised in taxonomical studies as not all researchers have access to the highly costly equipment required to perform them. This is particularly the case for those in the developing world. Cape of 1.1.3 Future prospects Although at present there is still no one universal method that can be applied to conclusively classify organisms, it is clear that the introduction of the use of molecular methods in bacterial taxonomy revolutionised the field in that it allowed the assessment of true relatedness – genome similarity. The best approach to conclusively classify bacteria would be to compare their entire genome sequences. However, this is not yetUniversity possible for the vast majority of bacterial taxa and thus a combination of other methods that indirectly measure the genome similarity must be performed. Of all of the methods available to the modern bacterial taxonomist, DDH and 16S rRNA gene sequence analysis are the most widely accepted. However, the comparison of just a few conserved genes seems a promising alternative to DDH for illuminating the relationships between organisms, as it provide a representation of the entire genome similarity.

The comparison of the sequences of protein encoding genes, like gyrB, was one of the most recently introduced methods and it seems to have great potential to become a widely utilised technique for the classification of bacteria, possibly even allowing for the indirect determination of genome similarity. 38

Despite not being absolutely accurate, it can be used to give the researcher an idea of the genome similarity and allows the decision of whether or not to pursue further research on a strain. Given this potential, a great deal more research must be conducted into utilising these genes as phylogenetic tools.

As the cost of genome sequencing decreases and its speed and accuracy increase, more genomes will be made available for public use and, as such, the whole genome based approaches will most likely dominate the future of bacterial taxonomy. However, despite these future prospects, presently there are not sufficient genome sequences available to allow the widespread use of whole genome analysis in bacterial taxonomy and researchers will therefore continue to develop sequencing-based methods that provide a representation of whole genome sequence relatedness.

Town 1.2 Actinobacteria

The name actinomycete is commonly used to refer to the filamentous members of the order Actinomycetales, but this reference has become lessCape popular in recent years (with actinobacteria becoming increasingly used) (Ward & Bora, 2006). The word actinomycete is derived from Greek and means “ray-fungus”, and stems from the historicalof confusion of these bacteria with fungi, which they closely resemble in morphology (Lechevalier & Lechevalier, 1981). Actinomycetes are a diverse group, however they do share many characteristics and can generally be described as being Gram positive, aerobic bacteria that produce branching filamentous hyphae, that may either remain stable or fragment into smaller subunits, and form asexual spores (Lechevalier & Lechevalier, 1981; Prescott et al., 2002e). Many actinomycetes form aerial mycelium that bear spores known as conidia or conidiospores, whichUniversity may be located on the ends of filaments or inside sporangia and are then called sporangiospores (Prescott et al., 2002e). Phylogenetically, the order Actinomycetales belongs to the class Actinobacteria along with four other orders (Acidimicrobiales, Bifidobacteriales, Coriobacteriales and Rubrobacterales), with the description of a fifth (Euzebyales) in press (Kurahashi et al., 2010). All actinobacterial genomes are marked by a high G + C content (more than 50%) (Stackebrandt et al., 1997; Prescott et al., 2002e). Within the order Actinomycetales there are 13 sub-orders, which encompass 42 families (Zhi et al., 2009). The relatedness of the class Actinobacteria within the domain Bacteria is indicated in Fig 1.2.1 (A), with the interclass relatedness of the actinobacteria being depicted in Fig 1.2.1 (B). 39

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Cape Figure 1.2.1 Phylogenetic position of and interclass relatedness in the phylum Actinobacteria. (A) Dendrogram indicating the phylogenetic position of the class Actinobacteria within the domain Bacteria based on 16S rRNA gene sequences. Rooting was performed using the Archaea sequences.of The scale bar indicates 10 nucleotide substitutions per 100 nucleotides. Figure taken from Stackebrandt et al. (1997). (B) Phylogenetic tree showing the interclass relatedness of the members of the class Actinobacteria based on 16S rRNA gene sequences. The new taxa which have been described since the proposed hierarchic classification of Stackebrandt et al. (1997) are indicated in bold. The scale bar represents 2 nucleotide substitutions per 100 nucleotides. Figure adapted from Zhi et al. (2009).

Actinobacteria are widely distributed in nature and occur in both marine and terrestrial habitats (Lechevalier & Lechevalier,University 1981; Goodfellow & Williams, 1983; Prescott et al., 2002e). The sources from which these organisms have been isolated encompass a hugely varied range of temperatures, pH, salinity, pressure as well as geographical locations. Furthermore, actinobacteria have been shown to be endophytic or symbiotic in nature, having been isolated from within the tissues of healthy plants and shown to be present in just about all vascular plants (Hasegawa et al., 2006; Ryan et al., 2008), the guts of various termite species (Watanabe et al., 2003; Kurtböke & French, 2007) and from specialized glands in multiple insect species (Kaltenpoth et al., 2006). They have also been isolated from numerous species of marine sponge (Zhang et al., 2006; Gandhimathi et al., 2008; Xin et al., 2008) and from within the organs of a puffer fish (Wu et al., 2005). 40

Actinobacteria are also of significant medical and industrial importance, responsible for causing disease as well as producing a wide range of bioactive secondary metabolites, including antibiotics and useful enzymes. They are even used in the treatment of raw sewage, being found to be present in activated sludge and have been shown to remove phthalate esters, prevent defloculation and to have demulsification ability (assisting in the separation of emulsions). However, they may also be responsible for producing thick foams that clog pipes (Lechevalier & Lechevalier, 1981; Goodfellow & Williams, 1983; Prescott et al., 2002e).

1.2.1 Importance of actinobacteria Owing to their wide distribution and saprophytic nature, filamentous actinobacteria play an important ecological role by degrading a wide range of organic compounds and thus assist in decomposition and nutrient cycling in natural environments (Lechevalier & Lechevalier, 1981; Goodfellow & Williams, 1983; Mincer et al., 2002; Prescott et al.Town, 2002e; González et al., 2005; Hasegawa et al., 2006). The role of actinobacteria in soil has been widely studied and they have been shown to play an important part in the degradation of complex organic material like cellulose, chitin, hemicellulose, keratin, lignin, lignocellulose and pectin, as well as in the removal of many compounds like petroleum, hydrocarbons, herbicidesCape and pesticides, thereby not only assisting in decomposition but also in decontamination of soilsof (Goodfellow & Williams, 1983; Mincer et al., 2002; González et al., 2005; Jayasinghe & Parkinson, 2008). Furthermore, actinobacteria have been shown to have an antagonistic effect on fungi in the soil (Jayasinghe & Parkinson, 2008) and can thus potentially assist in the prevention of pathogenic fungal infections of plants (Goodfellow & Williams, 1983). Many actinobacteria have also been shown to form a more intimate association with plants, often colonizing the internal tissues and residing as endophytes where they provide a host of benefits to the plantUniversity (Coombs & Franco, 2003; Hasegawa et al., 2006; Ryan et al., 2008). It is thought that many of the endophytic strains provide the host plant with an advantage by producing beneficial secondary metabolites. These can include antimicrobial or insecticidal molecules (Coombs & Franco, 2003; Hasegawa et al., 2006), plant growth promoters (Hasegawa et al., 2006; Ryan et al., 2008) or essential vitamins (Ryan et al., 2008). Perhaps simply by occupying the spaces between the plant cells, the endophytes reduce or prevent infection by removing the niche that could otherwise be occupied by the pathogens. Alternatively the actinobacteria may assist in enhancing the uptake and improving the cycling of minerals and nutrients, like nitrate and phosphate (Ryan et al., 2008). Actinobacteria can also be found to be present as a component of lichens, where they form 41 part of a symbiotic relationship with other microorganisms including fungi, green algae and cyanobacteria (González et al., 2005).

Just as many different plants form symbiotic relationships with actinobacteria, many different insect species are known to form symbiotic relationships with them. Possibly the best known example of this is the relationship between the leaf cutter ants and actinobacterial species. The ants harvest leaves which they use as a substrate to cultivate specific species of fungi as their main food source. The ants maintain the fungal garden and prevent pathogens from infecting and devastating their food source by also cultivating a mutualistic actinobacterium that produces antifungal antibiotics to prevent pathogen invasion. The ants house the single actinobacterial strain (typically belonging to the genus Pseudonocardia), which is vertically transferred from the parent colony to the new nests by the founding queen, in structures on their cuticle (Zhang et al., 2007). The European beewolf makes use of Streptomyces species, which are cultivated in specialized antennal glands of the female and secreted into the brood cell, to protect their offspring’s cocoonsTown from being infected by bacterial or fungal pathogens (Kaltenpoth et al., 2006). Another type of insect with a mutualistic association with actinobacteria is the termite, whose guts have been found to contain actinobacteria associated with the absorptive epithelia. These actinobacteria haveCape the ability to degrade the wood that makes up the main food source of the termites (Watanabeof et al., 2003; Kurtböke & French, 2007).

Like their terrestrial counterparts, aquatic actinobacteria play an important role in nutrient turnover in both fresh water and marine environments. They form an integral part of the microflora, playing a role in the degradation of alginates, cellulose, chitin and lignin and have been implicated in the decay of submerged wood as well as the decomposition of oil and other hydrocarbon contaminants (Goodfellow & Williams,University 1983). Within the oceans actinobacteria are known to form a part of a wide range of ecosystems, from the sea surface microlayer, to the water column, marine snow (macro-aggregates), sediment and even in association with free swimming marine organisms, as well as other marine fauna like sponges (Lam, 2006; Ward & Bora, 2006). The tetrodotoxin found in the organs of the puffer fish (Fugu rubripes) has in fact been shown to be produced by a symbiotic actinobacterium living in the organs of the fish (Wu et al., 2005). Similarly, many of secondary metabolites produced by marine sponges are now thought be of actinobacterial origin, owing to them forming a major component of the symbiotic bacteria associated with sponges, often accounting for between 40 and 60% of the biomass volume of the sponge (Ward & Bora, 2006; Zhang et al., 2006; Gandhimathi et al., 2008; Xin et al., 2008). Actinobacteria are also responsible for degradation of 42 the rubber joints in both water and sewage pipes and for damage to timber foundation piles (Lechevalier & Lechevalier, 1981; Goodfellow & Williams, 1983).

Perhaps the best known characteristic of the filamentous actinobacteria is their potential to produce a wide range of secondary metabolites, most notably antibiotics. A vast majority of the antibiotics on the market today are of actinobacterial origin (Lazzarini et al., 2000; Mincer et al., 2002; Prescott et al., 2002e), with members of the genus Streptomyces being the champion antibiotic producers, responsible for nearly half of these molecules (Anderson & Wellington, 2001; Watve et al., 2001; Busti et al., 2006; Marinelli, 2009). The other so called ‘rare actinomycetes’ are responsible for producing around 16% of the antimicrobials (Lazzarini et al., 2000). The genera that are regarded as being rare are those that are considered to be less exploited and include, but are not limited to, the genera Actinomadura, Actinoplanes, Amycolatopsis, Dactylosporangium, Kibdelosporangium, Microbispora, Micromonospora, Planobispora, Planomonospora and Streptosporangium (Lazzarini et al., 2000). The anti-infective producing ability of the genus StreptomycesTown is followed, with regard to the number of producing strains, by that of members of the families Micromonosporaceae (mainly the genera Micromonospora and Actinoplanes), Pseudonocardiaceae (mainly Amycolatopsis, Saccharopolyspora and Saccharothrix), ThermomonosporaceaeCape (mainly Actinomadura), Nocardiaceae and Streptosporangiaceae (mainlyof Streptosporangium ) (Lazzarini et al., 2000). The other bioactive secondary metabolites they produce include anti-cancer drugs, immunosuppressive agents as well as vitamins, industrially useful enzymes and pigments. Table 1.2.1 lists some of the useful secondary metabolites that are produced by the actinobacteria. Fig 1.2.2 shows the distribution of the producing strains among the ‘rare’ genera.

Although they produce Universitynumerous antimicrobial compounds, the actinobacteria may also be harmful, with some causing diseases in humans, animals and plants. Many species are simply opportunistic pathogens, while others are causative agents of specific diseases. Human diseases or ailments that can be attributed to actinobacteria include abscesses, actinomycoses, allergic pneumonias, leprosy, mycetomas, nocardiosis, paratuberculosis, streptothricosis and tuberculosis (TB) (Kutzner, 1981; Lechevalier & Lechevalier, 1981; Goodfellow & Williams, 1983; Williams et al., 1989; Chun & Goodfellow, 1995; Prescott et al., 2002e). The formation of scab of potatoes and other root vegetables as well as soil rot, wilt, leaf spot and canker are plant diseases caused by actinobacteria (Kutzner, 1981; Lechevalier & Lechevalier, 1981; Goodfellow & Williams, 1983; Williams et al., 1989; Coombs & Franco, 2003; Hasegawa et al., 2006;). 43

Table 1.2.1 Bioactive secondary metabolites produced by actinobacteria Molecule Compound Class Producing Organism Reference Acarbose Enzyme inhibitora Actinoplanes sp. Demain, 2000 Actinomycins Polyketide antibiotic Streptomyces spp. Marinelli, 2009 Avermectins Antihelminticsb Streptomyces spp. Demain, 2000 Clavulanic acid Enzyme inhibitorc Streptomyces clavuligerus Marinelli, 2009 Dethymicin Immunosuppressive Amycolatopsis japonica Wink et al., 2003 Erythromycin Macrolide antibiotic Saccharopolyspora erythraea Pelaéz, 2006 Gentamicin Aminoglycoside antibiotic Micromonospora echinospora, Cross, 1981; Micromonospora purpurea and Wagman & Micromonospora sagamiensis Weinstein, 1980 Octacosamicin Polyketide antifungal Amycolatopsis azurea Wink et al., 2003 Proteases Enzymed Nocardiopsis spp. Mehta at al., 2006 Proximicin A Antitumor Verrucosispora spp. Williams, 2008 Rifamycin Ansamycin antibiotic Amycolatopsis mediterranei, Bala et al., 2004; Amycolatopsis rifamycinica and Wink et al., 2003 Amycolatopsis sulphurea Salinisporamide A Antitumor Salinispora tropica Lam, 2006; Williams, 2008 Tacrolimus Immunosuppressive Streptomyces tsukubaenis Kino et al., 1987 TownTanaka et al., 1997 Vitamin B12 Vitamin Propionibacterium shermanii Demain, 2000 (cyanocobalamin) Vancomycin Glycopeptide antibiotic Amycolatopsis orientalis Pelaéz, 2006; Wink et al., 2003 Xylanases Enzymee Streptomyces spp. and Beg et al., 2001 ThermomonosporaCape curvata a – intestinal glucosidase inhibitor used for the treatment of diabetes; b – used for the treatment of parasitic worms; c – β-lactamase inhibitor; d – one of the most important groups of industrially used enzymes; e – used industrially and as a food additive and processing agent of

Nocardioides 2.6% Streptosporangiaceae 6% University Nocardia 11% Micromonosporaceae 38.1% Genera incertae sedis 13.3%

Thermomonosporaceae 14% Pseudonocardiaceae 15%

Figure 1.2.2 Distribution of the bioactive secondary metabolite producing strains amongst the rare filamentous actinobacteria for compounds described between 1900 and 2000. Data include 1578 producers of bioactive compounds as described in the Antibiotic Literature Database, which contains information on all the compounds described from 1900 onwards. Reproduced from Lazzarini et al. (2000). 44

1.2.2 Isolation and characterisation The wide distribution of actinobacteria makes their isolation generally fairly easy to achieve, provided that certain methods are followed to prevent them from being overgrown by other bacteria. Filamentous actinobacteria are generally slower growing than most other bacteria, with doubling times being around two to three hours (or longer) as compared to Escherichia coli which doubles every 20 minutes (Lechevalier & Lechevalier, 1981). Isolation plates can therefore easily become overgrown with non-actinobacteria, making any attempted isolation difficult to achieve. To solve this problem, various antibiotics can be incorporated into the isolation plates to limit as much as possible the growth of non-actinobacteria. The plates can thus be incubated for an extended period to allow the actinobacteria to establish themselves. The pre-treatment of the sample with dry heat or microwaves may also help to remove the vegetatively growing bacteria and thereby favour the isolation of the spore forming actinobacteria (Goodfellow & Williams, 1983). The isolation of actinobacteria with motile spores (like actinoplanetes) can be targetedTown by using baiting procedures, where suitable bait (hair, pollen, snakeskin, etc) is used to attract the spores from within a suspension. The spores germinate on the bait floating at the surface and the individual colonies are then aseptically removed and plated (Bland & Couch, 1981; Goodfellow & Williams, 1983). Although most genera of actinobacteria can be cultivatedCape in the lab, many are never isolated when generalized isolation procedures are performed.of The genus Streptomyces, which is thought to dominate most habitats, is by far the most commonly isolated, with the isolation of many of the other actinobacterial genera (particularly the ‘rare’ genera) being more of a challenge to achieve.

For this specific reason, multiple different selective media have been developed in an attempt to favour the growth of particular genera by the inclusion of different inhibitory molecules or alternative nutrient sources.University Altering the pH and salinity or providing complex or unusual carbon sources can be effective in targeting species or genera capable of growing under the unusual conditions (Goodfellow & Williams, 1983). Specific isolation media exist for the isolation of members of the genus Amycolatopsis, which include multiple antibiotics and unusual carbon sources (Tan et al., 2006). Multiple different media are also available for the selective isolation of nocardiae and rhodococci (Goodfellow & Minnikin, 1981). The inclusion of natural extracts (leaf, pollen, soil, etc) into the media can be helpful in isolating targeted actinobacteria, such as plant endophytes for example. The use of soil-extract media, which contain only the nutrients that were extracted from soil, has been shown to allow the growth of actinobacteria that are unable to grow on any other media containing rich nutrient sources (Hamaki et al., 2005). The use of this type of medium 45

(containing only naturally extracted nutrients at extremely low levels) may be the only means by which the growth of “unculturable” strains can be achieved. To further favour the isolation of specific rarer actinobacteria, actinophages specific for Streptomyces or other untargeted genera can be included in the preparation process to remove even more of the competition and increase the chances of isolating the desired actinobacteria (Kurtböke & Williams, 1991).

The conditions under which isolation is performed can also be adjusted to favour the growth of specific genera. For instance, to isolate thermophilic or thermotolerant species the incubations can be performed at a higher temperature or alternatively at a low temperature to favour psychrophiles (Goodfellow & Williams, 1983). Mimicking the natural environmental conditions can be another way to favour growth of fastidious actinobacteria. This has been achieved by inoculating a “diffusion chamber” (comprised of a washer housing an agar block between two semi permeable membranes) with an environmental sample and then incubating it in the natural environment, allowing free diffusion of chemicals in and out of the chamber, butTown restricting the movement of bacteria (Gavrish et al., 2008). Alternatively the diffusion chamber can be used as “trap” to allow in situ cultivation of filamentous actinobacterial strains by placing a sterile chamber in the environment and allowing the filamentous actinobacteria to penetrateCape into the chamber through the semi- permeable membrane and grow on the agar insideof (Gavrish et al., 2008).

Once the actinobacteria have been isolated, they are characterised to allow them to be correctly identified, with this characterisation usually taking on a polyphasic approach, including many of the methods described in the previous section of this chapter. The use of numerical taxonomy amongst filamentous actinobacteria was introduced in the 1960’s with great success, at the time being the method of choice for definingUniversity poorly classified strains (Goodfellow, 1988). However, numerical taxonomy is no longer widely used in actinobacterial taxonomy, largely owing to the success of the molecular taxonomic methods. Extensive morphological examination of filamentous actinobacteria is required to accurately describe a species, with all aspects of the colonial morphology (macroscopic and microscopic) being examined. The colonies are studied for the formation of substrate mycelium, which may be branched or rudimentary and either stable or fragmenting, with the shape and motility of the fragments being an important feature. The formation of aerial mycelium is another key feature, with many genera being characterised by a lack of aerial mycelium production (like Micromonospora). The morphology of the spores is another important characteristic, with the length and morphology of spore chains and spore surface ornamentation offering differential information. 46

The formation of sporangia or any other sporing structures should also be noted along with the motility of the spores. The colours of the substrate and aerial mycelia can also assist in classification of certain genera (Cross, 1989; Lechevalier, 1989; Williams et al., 1989).

Physiological characterisation encompasses a wide range of different features. The ability to grow under different conditions (temperature, pH and salinity) is usually tested. The metabolic capabilities are investigated by determining the ability of strains to utilise a range of sole carbon and nitrogen sources or to produce acid from carbohydrates. Enzymatic activity is another important feature and is determined by performing degradation tests with a wide range of substrates (casein, chitin, starch, xylan, etc). The production of diffusible pigments and melanin may also be diagnostic features. The antibiotic susceptibility and growth in the presence of inhibitory compounds can also be determined, as can the exhibition of antimicrobial activity against a range of different test organisms (Williams et al., 1989). Town The determination of the chemotaxonomic characteristics of actinobacteria allows for differentiation between many of the genera and therefore can provide vital information for identification and classification of an unknown isolate to a particular genus.Cape The diagnostic sugars and isomer of DAP that are present in the cell wall are the most widelyof determined chemotaxonomic characters. The presence or absence of mycolic acids is another characteristic that can be used to differentiate genera. The menaquinone and phospholipid profiles may also be of diagnostic value, as can the fatty acid profile. Although routinely performed, most of these chemotaxonomic characters do not offer much resolution below the genus level (mainly being used to confirm genus assignments from 16S-rRNA gene sequence analysis) and are therefore considered to be somewhat outdated by many researchers (Kutzner, 1981; Lechevalier,University 1989; Williams et al., 1989; Embley & Stackebrandt, 1994).

The current genotypic characterisation of actinobacteria is largely based on 16S rRNA gene sequence analysis and DDH, with almost all taxonomic assignments being based on the 16S rRNA gene. Despite this, the sequences of many other genes are becoming increasingly used in phylogenetic analysis and for species differentiation. The gyrB gene is perhaps the most widely used alternative marker gene, having been used in the genera Amycolatopsis (Everest & Meyers, 2009), Gordonia (Shen et al., 2006; le Roes et al., 2008), Kribbella (Kirby et al., 2010), Micromonospora (Kasai et al., 2000), Mycobacterium (Chimera et al., 2004), Nocardia (Takeda et al., 2010) and Nocardiopsis (Yang et al., 2008). The gyrB gene was also used to help prove that a strain (assigned 47 to the genus Smaragdicoccus) represents a novel lineage within the suborder Corynebacterineae (Adachi et al., 2007). Furthermore MLSA, which uses multiple marker genes, has been used within the actinobacteria in an attempt to obtain a better representation of phylogenetic relationships (Rong et al., 2009; Rong & Huang, 2010).

1.2.3 Descriptions of selected genera 1.2.3.1 The genus Amycolatopsis Originally created to accommodate species that had been misclassified to the genus Nocardia, the genus Amycolatopsis was proposed by Lechevalier et al. (1986) and contains nocardioform actinomycetes that lack mycolic acids and have a type IV cell wall (containing meso-DAP, arabinose and xylose; rhamnose may be present) (Tan et al., 2006). The genus presently contains 41 species with validly-published names, with Amycolatopsis orientalis ATCC 19795T as the type species. Amycolatopsis is the largest genus belonging to the family PseudonocardiaceaeTown, which contains 15 other genera (12 of which contain three or fewer species) and has Pseudonocardia (with 32 members) as the type genus (Euzéby, 2010). Cape Amycolatopsis strains are non-motile, aerobic, Gram positive, non-acid fast, catalase positive actinobacteria that form branching vegetative hyphaeof that tend to fragment into squarish subunits. Some Amycolatopsis species produce aerial mycelium. When formed, the aerial hyphae may fragment into chains of squarish to oval fragments. The formation of endospores, sheaths, synnemata, sporangia or sclerotia is not observed. Colonies are usually rough, flat and irregularly shaped with convoluted borders and the vegetative mycelia can take on a range of colours from cream to orange to yellow-brown. The aerial mycelia, when present, can be white to cream to yellow-brown in colour.University If diffusible pigments are produced they generally take on a yellow to brown colour. The phospholipid profile contains phosphatidylethanolamine (PE) with or without phosphatidylmethylethanolamine (PME) and variable amounts of phosphatidylinositol mannosides (PIMs), phosphatidylinositol (PI) and diphosphatidylglycerol (DPG) (phospholipid pattern type PII sensu Lechevalier et al., 1977). The fatty acid profile contains a complex mix of iso- and anteiso- saturated fatty acids. The predominant menaquinones are MK-9(H2, H4) and mycolic acids are not produced (Lechevalier et al., 1986; Henssen et al., 1987; Mertz & Yao, 1993; Lee & Hah, 2001; Majumdar et al., 2006; Tan et al., 2006; Ding et al., 2007).

48

Although the genus only contained 10 species with validly-published names within the first 13 years after its creation, the subsequent decade has seen the description of triple that number, with strains being isolated from a wide range of sources including soil (the most common source), fresh water and clinical sources – both human and animal (Ding et al., 2007). A possible explanation for this increased interest in this genus is the need for the discovery of new antimicrobial compounds, for the production of which members of this genus are particularly well known. A derivative of the rifamycin group of antibiotics (ansamycin type antibiotics), rifampicin, is widely used for the treatment of TB. Rifamycins are produced by Amycolatopsis mediterranei, Amycolatopsis rifamycinica and Amycolatopsis sulphurea. The latter species also produces the tetracycline antibiotic chelocardin (Labeda, 1995; Wink et al., 2003; Bala et al., 2004; Tan et al., 2006). A. mediterranei is also known to produce the ansamycin type antibiotics homorifamycin and kanglemycin A, as well as an ansamycin-related antibiotic, proansamycin B-M1, and an intermediate of ansamycin biosynthesis, protorifamycin (Wink et al., 2003). The clinically important glycopeptide antibiotic vancomycin is produced by A. orientalis, whichTown is also known to produce another glycopeptide antibiotic, orienticin, as well as the macrocyclic antibiotic, quartromicin. The vancomycin-like antibiotic, avoparcin, used agriculturally in animal feeds as a growth promoter, is produced by Amycolatopsis coloradensis (Labeda, 1995;Cape Wink et al. , 2003). of Other species that are known to produce antimicrobials include: Amycolatopsis alba – produces a glycopeptide antibiotic related to vancomycin; Amycolatopsis azurea – azureomycin (glycopeptide) and octacosamicin (antifungal polyketide); Amycolatopsis balhimycina – balhimycin (glycopeptide); Amycolatopsis decaplanina – decaplanin (glycopeptide); Amycolatopsis keratiniphila subsp. nogabecina – nogabecin (glycopeptide); Amycolatopsis lurida – benzanthrin (quinone) and ristocetin/resistomycin University (glycopeptide); Amycolatopsis plumensis – shows activity against selected Gram-positive and -negative bacteria and certain fungi; Amycolatopsis tolypomycina – tolypomycin (ansamycin); Amycolatopsis vancoresmycina – homorifamycin (ansamycin) and vancoresmycin (polyketide) (Henssen et al., 1987; Mertz & Yao, 1993; Labeda, 1995; Wink et al., 2003; Wink et al., 2004; Saintpierre-Bonaccio et al., 2005). Amycolatopsis benzoatilytica, a human clinical isolate, does not appear to produce any antimicrobial activity. However, unlike all other Amycolatopsis species, this species does metabolize aromatic compounds like m-hydroxybenzoate (Majumdar et al., 2006).

49

The classification of members of this genus relies heavily on chemotaxonomic and physiological characteristics, with the use of 16S rRNA gene sequence analysis being the main source of phylogenetic information and DDH being performed to differentiate closely related species. By analysing the 16S rRNA genes of multiple Amycolatopsis type strains and comparing the alignments with the sequences of other genera, Tan et al. (2006) identified a section of the gene that was unique to members of the genus and subsequently designed a primer (AMY2) that can be used in conjunction with a previously published 16S rRNA gene probe (ATOP of McVeigh et al. (1994)) to generate a 435nt 16S rRNA gene PCR product that is exclusively amplified from Amycolatopsis strains. This primer pair allows for the rapid determination of whether an isolate belongs to the genus Amycolatopsis or not (Tan et al., 2006). The use of the gyrB gene has recently been shown to be useful in the phylogeny of this genus, showing improved resolution over the 16S rRNA gene and can even assist in predicting if an isolate is likely to represent a novel species (Everest & Meyers, 2009). The description of this gyrB work is included in Chapter 4 of this study, as is the examination of the use of the recN gene as a tool in the phylogeny ofTown the genus Amycolatopsis.

1.2.3.2 The genus Kribbella Belonging to the family Nocardioidaceae, the genus KribbellaCape was proposed by Park et al. (1999) as the result of the reclassification of two strains fromof the genus Nocardioides and can be described as accommodating nocardioform actinomycetes with LL-DAP in their cell walls. The family presently contains six genera (Actinopolymorpha, Aeromicrobium, Jiangella, Kribbella, Marmoricola and Nocardioides). The type genus of the family (and most speciated) is Nocardioides, which contains 46 species with validly-published names. Kribbella is the second largest genus in the family with 16 species, with the type species being Kribbella flavida NBRC 14399T (Euzéby, 2010). University Kribbellae are Gram positive to Gram variable, non-motile, aerobic actinobacteria which are non- acid fast and catalase-, oxidase- and urease positive. The genus is characterised by nocardioform growth, in that their extensively branched vegetative mycelia, which penetrate into the agar, often fragment into rod-shaped or coccoid elements. The aerial mycelium fragments into short to elongated rod-shaped elements. Colonies usually have a lichenous shape with irregular edges and appear pasty. Chemotaxonomic features include a cell wall of chemotype I, with no diagnostic whole cell-sugars, but with mannose and ribose being present in many species. Mycolic acids are not present and the predominant menaquinone is MK-9(H4). The major phospholipid is phosphatidylcholine (PC) (phospholipid pattern type PIII sensu Lechevalier et al., 1977), while the 50 fatty acid profile contains large amounts of branched iso- and anteiso-fatty acids (Park et al., 1999; Li et al., 2006; Carlsohn et al., 2007).

Despite the majority of Kribbella species being isolated from soil samples from diverse geographical locations, strains have also been isolated from patinas on rock surfaces in the catacombs of St. Callistus in Rome (Urzì et al., 2008), the root nodules of the blue lupine (Lupinus angustifolius) (Trujillo et al., 2006b) and from scab lesions on a potato tuber (Song et al., 2004), indicating that they are not limited to a single ecological niche (Trujillo et al., 2006b). Although the genus is not well known for the production of antimicrobial compounds, two members do exhibit such activity. Kribbella sandramycini (Park et al., 1999) produces sandramycin, which is effective against selected Gram positive bacteria and shows moderate antitumor activity (Matson & Bush, 1989). Kribbella antibiotica has been shown to exhibit antifungal activity (Li et al., 2004).

Phylogenetic classification of Kribbella species has largely been basedTown on the sequence of the 16S rRNA gene, however Kirby et al. (2010) recently examined the use of gyrB gene sequences in the phylogenetic analysis of the genus and showed that gyrB based trees showed improved resolution over the 16S rRNA based trees. Furthermore, type strainsCape could be distinguished by calculating the gyrB based genetic distance between strains, therebyof allowing an assessment of the potential novelty of new isolates prior to performing full polyphasic characterisation.

1.2.3.3 The genus Micromonospora The genus Micromonospora was proposed in 1923 by Ørskov and belongs to the family Micromonosporaceae along with 21 other genera (the majority of which only contain one or two species) (Euzéby, 2010;University Zhi et al., 2009). The genus can be readily distinguished from the other members of its family based on a combination of morphological and chemotaxonomic characters (Cross, 1981; Koch et al., 1996a). It is the type genus of its family (as well as the most speciated) and currently contains 42 members, with Micromonospora chalcea ATCC 12452T being the type species (Euzéby, 2010).

Micromonosporae are Gram positive, non-acid fast and form well-developed, branched, septate mycelia that do not fragment. Aerial mycelia are not produced and the non-motile spores are formed singly on the substrate mycelium. The spores can be spherical, oval or ellipsoidal in shape and are borne sessile or on short or long sporophores and have surface ornamentations that have previously 51 been described as smooth, rough, warty or blunt spiny based on transmission electron microscopy. However, the use of scanning electron microscopy (SEM) has revealed that most spores have a blunt spiny ornamentation and therefore spore ornamentation is of little use for differentiation (Kawamoto, 1989). Colonies usually appear pale yellow or light orange in colour on agar medium, becoming orange, red, brown, blue-green or purple and taking on a progressively darker colour with maturation and the production of brown-black, green-black or black spores. The colonies often become mucoid upon sporulation. Despite the production of characteristic diffusible pigments by certain species, the mycelial pigmentation is not considered to be a diagnostic feature of the genus (Cross, 1981; Kawamoto, 1989; Koch et al., 1996a).

The cell walls of Micromonospora strains contain meso-DAP with glycine (type II cell wall) and have xylose and arabinose present in the whole cell sugar pattern (pattern D). Members of the genus contain a complex mixture of saturated iso- and anteiso-fatty acids, with unsaturated or 10-methyl fatty acids present in some strains. Similarly, the menaquinone profileTown is fairly complex, containing varying amounts of tetra-, hexa- and/or octa-hydrogenated menaquinones with 9, 10, and/or 12 isoprene units, but MK-10(H4) and MK-10(H6) are the major components in many strains. Mycolic acids are not produced and the predominant phospholipidsCape include PE, PI and PIMs (phospholipid pattern type PII) (Cross, 1981; Kawamoto, 1989;of Koch et al., 1996a).

Members of this genus have been isolated from a wide range of sources and are thought to occur in low numbers in soils, but more frequently in aquatic habitats, including fresh and salt water sources (lake, river and deep sea sediments; water samples; beach sand and rice paddy soils to name a few) (Cross, 1981; Kawamoto, 1989). Micromonosporae have also been isolated from the root nodules (Garcia et al., 2010; TrujilloUniversity et al., 2006a), as well as the leaves of plants (Kirby & Meyers, 2010). Many Micromonospora strains were isolated as producers of aminoglycoside type antibiotics (Kasai et al., 2000) with gentamicin (produced by Micromonospora echinospora) being the most well know example (Cross, 1981). The discovery of antibiotic-producing micromonosporae sparked the widespread isolation and screening of members of this genus, resulting in the discovery of producers of just about every class of antibiotic (Wagman & Weinstein, 1980). Besides the strains that have the ability to produce antibiotics, this genus also contains other interesting members, some of which are capable of degrading natural rubber (Kasai et al., 2000) and surviving in water contaminated with radon, a radioactive by-product of uranium mining (Trujillo et al., 2005).

52

Analysis of the 16S rRNA gene sequences of members of the genus by Koch et al. (1996b) showed that the Micromonospora strains form a “phylogenetically tight genus” and confirmed the taxonomic status of the species with validly-published names, but questioned the assignments of some of the strains as sub-species, suggesting that extensive DDH experiments would be needed to resolve this. Kasai et al. (2000) made use of the gyrB gene to assess the intrageneric relationships between Micromonospora strains and found that, although the members still formed a coherent cluster, the phylogenetic groupings based on the gyrB gene were different to those based on the 16S rRNA gene. By performing multiple DDH experiments, they showed that gyrB-based phylogenetic analysis provides a more accurate representation of the phylogeny within the genus than that of the 16S rRNA gene. This study resulted in the reclassification of many of the strains (Kasai et al., 2000). The study also indicated that the evolutionary rate of the 16S rRNA gene was not uniform within the genus due to different selective pressures, possibly influenced by the 16S rRNA binding aminoglycoside antibiotics produced by many strains (Kasai et al., 2000). Town 1.2.3.4 The genus Nocardia This genus belongs to the family Nocardiaceae, which initially only contained four other genera, Micropolyspora (whose standing is currently uncertainCape – the type strain and all but one strain (of which a nomenclatular change has not been validlyof published) have be transferred to other genera), Rhodococcus, Smaragdicoccus and Williamsia. However, the proposal of Zhi et al. (2009) has seen the inclusion of the three genera of the family Gordoniaceae (Gordonia, Millisia and Skermania) into an emended family, retaining the name Nocardiaceae and with the genus Nocardia remaining as the type genus (Euzéby, 2010). Numerous species that were initially classified as belonging to the genus Nocardia, based mainly on morphological characteristics have been transferred to other genera, including, AmycolataUniversity (now Pseudonocardia ), Amycolatopsis, Rhodococcus and Saccharopolyspora (Goodfellow & Lechevalier, 1989; Euzéby, 2010). The genus currently contains 90 members with validly-published names, with Nocardia asteroides ATCC 19247T being the type species (Euzéby, 2010).

The nocardiae are Gram-positive to Gram-variable, aerobic bacteria, with an aerobic respiratory type of metabolism and are catalase positive. One of the few constant morphological features of this genus is the tendency of the aerial and substrate mycelia, which can be either rudimentary or extensively branched, to fragment into rod-shaped to coccoid elements that are non-motile. The aerial hyphae, which are always produced, may mature into short to long chains of conidia which are 53 non-motile. The colonies will often appear chalky in texture, but may appear smooth when no visible aerial mycelia are present. A wide range of cell pigment colours may be produced (brown, grey, off-white, orange, peach, pink, purple, red, tan or yellow), however Nocardia colonies are usually orange to pink to brown in colour, with diffusible pigments being an undistinguished brown to yellow in colour, if present at all. Aerial mycelia range in colour from white to grey to orange- pink (Goodfellow & Minnikin, 1981; Goodfellow & Lechevalier, 1989).

Chemotaxonomically the genus is defined as containing meso-DAP with arabinose and galactose as the diagnostic sugars in the cell wall and thus has a cell wall chemotype IV and a whole cell sugar pattern type A. The characteristic phospholipid pattern is type PII, which consists of DPG, PE (taxonomically significant), PI and PIMs. The fatty acid profile contains straight-chain, unsaturated and tuberculostearic acids (type IV fatty acid pattern). The predominant menaquinones are MK-

8(H4) or MK-9(H2). Mycolic acids are present and contain 40-60 carbon atoms (Goodfellow & Minnikin, 1981; Goodfellow & Lechevalier, 1989; Chun & Goodfellow,Town 1995).

Nocardia strains are considered to be widespread and abundant in soil (Goodfellow & Minnikin, 1981; Goodfellow & Lechevalier, 1989) and, althoughCape some have been isolated from soil, a larger number have been isolated from clinical samples.of Some strains are pathogenic to humans and other animals and are thought to be largely opportunistic pathogens (Goodfellow & Lechevalier, 1989; Chun & Goodfellow, 1995). Two diseases in humans that are caused by Nocardia infection include actinomycete mycetoma, mainly attributed to Nocardia brasiliensis and Nocardia transvalensis, and nocardiosis, attributed to N. asteroides, Nocardia farcinica and Nocardia nova (Chun & Goodfellow, 1995). University The genus was originally defined based on chemotaxonomic characteristics (Goodfellow & Lechevalier, 1989), with DDH, phage sensitivity and antibiotic susceptibility data also being considered. However, the introduction of 16S rRNA gene sequence analysis allowed for determination of the phylogenetic relationships between strains (Chun & Goodfellow, 1995). Clinical isolates can be rapidly identified to the genus Nocardia by the use of genus specific 16S rRNA gene PCR primers (Laurent et al., 1999) and strains can be differentiated by performing RFLP analysis on a 439nt fragment amplified from the 65 kDa heat shock protein gene (Steingrube et al., 1995). The use of gyrB gene sequence analysis in the genus was recently examined by Takeda et al. (2010) who analyzed the partial sequences from 56 type strains and showed that the gene can 54 accurately predict phylogeny and offers a higher discriminatory power than the 16S rRNA gene, with the gyrB sequences being approximately 3.6 times more divergent than that of the 16S rRNA gene sequences. Currently there are 143 publicly available gyrB gene sequences for Nocardia strains (in GenBank as of 2 February 2010), which will undoubtedly prove to be useful in the phylogenetic analysis of the members of this genus in future.

1.2.3.5 The genus Streptomyces Proposed by Waksman and Henrici in 1943, the genus Streptomyces is the type genus of the family Streptomycetaceae, and currently contains well over 550 species, with the type species of this genus being Streptomyces albus ATCC 25426T (Euzéby, 2010). There has been much debate around the classification of species within this genus and the other genera in the family, with the result being that multiple strains have been transferred to and from the genus Streptomyces over the years. The family presently only contains two other genera, namely KitasatosporaTown (originally Kitasatosporia), which was transferred to the genus Streptomyces by Wellington et al. (1992) but was subsequently revived by Zhang et al. in 1997, and Streptacidiphilus, which was established in 2003 by Kim et al. (2003b) to accommodate an acidophilic actinobacterium (Anderson & Wellington, 2001; Euzéby, 2010). The genera Actinopycnidium, Actinosporangium,Cape Chainia, Elytrosporangium, Kitasatoa and Microellobosporia were all transferred to the genusof Streptomyces as a result of numerical taxonomic analysis of phenotypic traits of members of the Streptomycetaceae family (Anderson & Wellington, 2001). The genus Streptoverticillium, which was in fact created to accommodate strains that were initially classified as Streptomyces but showed a characteristic “whorl” formation (Kutzner, 1981), was virtually identical to the genus Streptomyces (with the only detectable differences being the formation of this barbed-wire like aerial mycelium and differences in DNA-RNA pairing). It was therefore decided that itUniversity should be considered a synonym of Streptomyces (Witt & Stackebrandt, 1990; Anderson & Wellington, 2001). The genera Kineosporia and Sporichthya share many chemotaxonomic characteristics with the genus Streptomyces and were therefore incorporated into this genus, but have been subsequently reinstated as separate genera, belonging to the families Kineosporiaceae and Sporichthyaceae, respectively, based on 16S-rRNA gene analysis (Anderson & Wellington, 2001).

The discovery of the production of antibiotics by streptomycetes in the 1940’s saw widespread screening programs being initiated by pharmaceutical companies, with the producers of the novel compounds often being described as new species and patented, resulting in the overspeciation of the 55 genus (the number of species increasing from about 40 to over 3000, many of which were synonyms). As a result, many attempts were made to try and correctly classify the streptomycetes. The use of morphological features (like spore mass colour, spore chain morphology and spore surface ornamentation) were introduced, but were found to be insufficient to allow reliable classification. The International Streptomyces Project (ISP), initiated in 1964, saw the development of a defined set of criteria that could be used for the phenotypic characterisation of isolates, allowing for accurate identification and serving as a framework for the development of a classification scheme. Chemotaxonomic analysis, which was considered to be less subjective than morphology, genetically stable and uniform within taxa, was introduced in the 1970’s and helped to refine the identification and classification of streptomycetes. Numerous numerical taxonomic studies, using varying amounts of data, were conducted on the members of Streptomyces and related genera in the 1960’s – 1980’s, with the resulting classification distributing the strains into multiple major and minor clusters. The members of the minor clusters were considered to belong to the same species, while the major clusters were regarded as species-groups, containingTown multiple sub-groups of species. The development and implementation of molecular characterisation lead to further revision of the classification. These advancements in the methods used for taxonomic classification have resulted in many modifications to the genus Streptomyces and theCape family Streptomycetaceae , some of which have been mentioned above (Kutzner, 1981; of Williams et al., 1989; Goodfellow et al., 1992; Anderson & Wellington, 2001; Lanoot et al. (2002, 2004, 2005b); Rong et al., 2009; Rong & Huang, 2010).

The streptomycetes are Gram-positive, non-acid fast, catalase positive, aerobic organisms that are classed as chemo-organotrophic, with an aerobic respiratory type of metabolism. They are non- fastidious, being able toUniversity utilise a wide range of carbon and nitrogen sources without the requirement for vitamins or growth factors. Extensively branched vegetative mycelia are produced and rarely fragment. Aerial mycelia are produced as the colonies age and the formation of cross walls in the multinucleated aerial filaments (sporophores) results in the development of chains of three or more non-motile spores (conidia). Some species may form sclerotia, pycnidia-, sporangia- or synnemata- like structures. The morphology of the spore chains can be defined as straight to flexuous (Rectiflexibiles), hooks, loops or coils with one or two turns (Retinaculiaperti) or spirals (Spirales). The spore surface ornamentation (as seen by SEM) borne on the spore sheath can be hairy, rugose, smooth, spiny or warty. Colonies are discrete and lichenous, leathery or butyrous and may initially appear to have a smooth surface, but become floccose, granular, powdery or velvety upon the 56 development of the aerial mycelium. A wide variety of pigments is produced and results in the many vivid colours of the substrate and aerial mycelia, with many strains also producing diffusible pigments that are pH indicators. The colour of the mature aerial mycelium (spore mass) is a widely used taxonomic feature and is often used to group strains into “sections”, “series” or “colour- groups”. The colours are recognized as being blue, grey, green, red, violet, white or yellow, however some strains are difficult to place into one of these defined colour groups and can be described as having a “mixed colour” (i.e. blue-green). The colour of the substrate mycelium may often be affected by the medium, pH and age of the culture and therefore may not be as useful as the spore mass colour. Similarly the colour of diffusible pigments may be useful in classification, but it should be noted that chemically different pigments may have the same colour (Kutzner, 1981; Williams et al., 1989; Anderson & Wellington, 2001).

A key chemotaxonomic feature of the streptomycetes is the presence of LL-DAP and glycine in the cell wall (cell wall type I) and the absence of any diagnostic sugarsTown in the whole cell sugar pattern. Strains lack mycolic acids and the predominant menaquinones are hexa- or octa-hydrogenated with nine isoprene units. The fatty acid profile contains major amounts of saturated iso- and anteiso-fatty acids. The cell membranes have a phospholipid profileCape consisting of phosphatidylglycerol (PG), PE, PI and PIMs (phospholipid pattern type PII) (Kutzner,of 1981; Williams et al., 1989; Anderson & Wellington, 2001).

Despite the vast numbers that have been isolated from soils, streptomycetes are thought to be widely distributed in both terrestrial and aquatic habitats (Kutzner, 1981; Williams et al., 1989). This is exemplified by the isolation of strains from many different sources all around the world. Some of these isolation sources University include: compost and manure heaps; fodder; fresh water (river and lake) samples and sediments; deep sea sediments (Kutzner, 1981); the leaves, roots and stems (as endophytes) of various plants (Hasegawa et al., 2006); marine organisms such as sponges (Ganghimathi et al., 2008; Xin et al., 2008); the guts of termites (Watanabe et al., 2003); diseased plants as well as human and animal clinical samples (Kutzner, 1981; Williams et al., 1989).

One of the most well known plant diseases caused by streptomycetes is common scab that affects potatoes and taproot vegetables and can be attributed to Streptomyces scabies (Kutzner, 1981; Williams et al., 1989; Hammerschmidt, 2007), Streptomyces acidiscabies, Streptomyces turgidiscabies, Streptomyces europaeiscabiei or Streptomyces stelliscabiei (St-Onge et al., 2008). 57

The disease occurs in dry, neutral to alkaline soils in many of the world’s potato producing countries and is marked by the formation of deep or superficial lesions on the tubers (Williams et al., 1989). These can be attributed to the production of toxins called thaxtomins by the infecting streptomycetes, which cause necrosis of the tissue of the tubers (Hammerschmidt, 2007; St-Onge et al., 2008). Similarly, russet scab is a form of scab that results in a brown roughening of the skin, but occurring in wet soils (Williams et al., 1989). Soil rot of sweet potatoes is caused by Streptomyces ipomoea (occurring under similar conditions to those of common scab), which results in dwarfing of the plants, with the root system being poorly developed and often entirely rotten, as well as the formation of pits or cavities on the tubers (Kutzner, 1981).

Streptomycetes that have been isolated from humans include: Streptomyces somaliensis and Streptomyces sudanensis (Quintana et al., 2008), known human pathogens that cause actinomycetoma (now known simply as mycetoma), which is a granulomatous infection of subcutaneous tissues; Streptomyces willmorei which has been isolatedTown from streptothricosis of the liver; strains of S. albus from dental caries, pulmonary streptothricosis and blood samples; and Streptomyces griseus and Streptomyces violaceoruber which have frequently been isolated from clinical samples, with there being evidence of the former’sCape ability to cause infection (Kutzner, 1981; Williams et al., 1989). Strains belonging to S. griseusof have also been seen to cause infections in cats as well as mycetomas in captive bottlenose dolphins (Williams et al., 1989). A strain of S. albus was found in the blood of a sick cow (Kutzner, 1981).

Terrestrial streptomycetes are considered to be saprophytes and play an important role in the decomposition of plant matter as well as natural polymers, thereby contributing to nutrient turn-over and cycling (Williams etUniversity al., 1989). There has been much debate about the strains found in aquatic sources around whether they are true aquatic streptomycetes or simply occur as a result of wash in from terrestrial sources, surviving as spores (Kutzner, 1981; Williams et al., 1989; Ward & Bora, 2006; Williams, 2008). However it is now believed that these organisms do in fact truly form a part of the microflora of aquatic habitats, actively contributing to the decomposition of organic matter (Kutzner, 1981; Williams, 2008). The development of earthy tastes and odours in reservoirs and water supplies has been attributed to the production of geosmin and methylisoborneol by streptomycetes (Kutzner, 1981) and provides further evidence that the strains are in fact growing in the water, as these secondary metabolites are produced after hyphal growth and not by spores (Williams et al., 1989). 58

The most recent advances in the taxonomy of the genus include the use of alternative marker genes, like the housekeeping genes gyrB and rpoB, in MLSA applications to differentiate strains (Rong et al., 2009; Rong & Huang, 2010) and to construct phylogenetic trees. Three Streptomyces genomes have been sequenced, namely, Streptomyces avermitilis MA-4680T (9.0256 Mb is size), Streptomyces coelicolor A3(2) (8.6675 Mb) and Streptomyces griseus subsp. griseus NBRC 13350 (8.5459 Mb).

1.2.3.6 The genus Verrucosispora The genus Verrucosispora was established by Rheims et al. (1998) to accommodate a strain that was found to belong to the family Micromonosporaceae based on a combination of morphological, physiological, chemotaxonomic and phylogenetic characteristics. However, it possessed features sufficiently different from the genera associated with the family to warrant the formation of a new genus. There are currently only two Verrucosispora species with Townvalidly-published names, with a third, ‘Verrucosispora sediminis’, currently in press (Dai et al., 2010). The type species is Verrucosispora gifhornensis DSM 44337T (Euzéby, 2010).

Verrucosispora strains are Gram positive, non-acid Cape fast and aerobic, with branching hyphae that form a well developed septate mycelium and showof sparse to no aerial mycelium formation. The singular spores are borne sessile or on short or long sporophores from the substrate mycelium, are non-motile and possess a warty surface appearance which becomes hairy upon aging. The colonies appear yellow to orange in colour, with diffusible pigments showing similar colours, if produced. The cell walls contain meso-DAP and glycine (type II cell wall) and the whole cell sugars include mannose and xylose, but exclude arabinose. The major fatty acids include iso-C15:0, iso-C16:0 and anteiso-C17:0. The predominantUniversity menaquinone is tetra-hydrogenated with 9 isoprene units, however minor amounts of MK-9(H2), MK-9(H6) and MK-10(H4) may be present. The phospholipid profile contains PE, DPG, PIMs and phosphatidylserine (PS) (phospholipid pattern type PII) (Rheims et al., 1998; Liao et al., 2009).

Members of this genus, like others of its family, seem to be found predominantly in aquatic habitats, with all published species being isolated from aquatic sources: V. gifhornensis from a peat bog (Rheims et al., 1998), Verrucosispora lutea from mangrove sediment (Liao et al., 2009) and ‘V. sediminis’ from deep sea sediment from the South China Sea (Dai et al., 2010). Furthermore, many unpublished strains have been isolated from marine samples (Ward & Bora, 2006; Williams, 2008). 59

The genus also possesses the ability to produce antimicrobial agents, with the potent polycyclic polyketide antibiotic abyssomicin C (which inhibits folic acid biosynthesis in Gram-positive bacteria) being produced by a Verrucosispora strain (Riedlinger et al., 2004; Lam, 2006; Williams, 2008). The broth of ‘V. sediminis’ also showed potent antimicrobial activity (Dai et al., 2010). However, neither V. gifhornensis nor V. lutea exhibits any antimicrobial activity (Rheims et al., 1998; Liao et al., 2009).

1.3 Antibiotics

The word antibiotic (meaning “against life”) was first used by Selman Waksman in 1942 to describe molecules that were produced by microorganisms that inhibit the growth of other microbes. This definition, as he stated it, referred solely to natural products or to molecules that were derived from natural products and excluded all synthetically produced molecules.Town These man-made compounds are known as antibacterial or antimicrobial agents, however nowadays both are often referred to as antibiotics (Levy, 1998; Peláez, 2006; Yoneyama & Katsumata, 2006; Marinelli, 2009). Cape Antibiotics are small molecules, which enter the bacterial cell and, through various interactions, kill, or prevent the cell from growing. Hence they exertof their action as one of two effects: bactericidal or bacteriostatic, respectively (Yoneyama & Katsumata, 2006). Antibiotics belong to the larger group of microbially produced compounds known as secondary metabolites (Marinelli, 2009) and, as such, are multifunctional molecules which have been speculated to have a role in intercellular signalling amongst different bacteria in nature. Many antibiotics have the ability to modulate bacterial transcription at low concentrations,University but it is at higher concentrations that they exert the antibacterial effects (Davies, 2009).

1.3.1 A brief history of antibiotics For centuries man has used natural products to treat infection and disease (Lindblad, 2008; Davies, 2009; Herbs2000, 2009). Despite the apparent lack of understanding behind why the substances provided the curative effects, there was a multitude of herbal medicines and folk cures passed down from one generation to another (Forrest, 1982; Herbs2000, 2009). Various herbs and plants (which we now know to possess antibacterial qualities) were used widely by the Chinese, Egyptians, Romans and Greeks as wound dressings, as were certain minerals like copper and mercury (Forrest, 60

1982; Lindblad, 2008; Herbs2000, 2009). The use of honey to dress and vinegar as an antiseptic to clean wounds was also fairly common throughout history (Forrest, 1982; Lindblad, 2008). As far back as 4000 years ago, the ancient Egyptians used moulds to cure surface infections, a feat which has been replicated by numerous cultures since then (Wainright, 1989).

Despite the widespread use of natural products, it was not until the late 19th and early 20th century when scientists began to actively research these substances in an attempt to identify the cause of their healing abilities. With this research came the identification of numerous possible antimicrobial substances, but many were ultimately abandoned due to toxicity or other undesirable effects (Herbs2000, 2009). This includes Paul Elrich’s Salvarsan, which was introduced in 1910 to treat syphilis but was later replaced by penicillin (Yarnell, 2005). Chemists did however manage to synthesize the sulfonamides (sulfa drugs), which were therapeutically introduced in 1935 (Powers, 2004) and made a huge impact on the treatment of infections (Butler & Buss, 2006; Yoneyama & Katsumata, 2006). Town

It was not until 1928 when Alexander Fleming made the chance discovery of the inhibition of a Staphylococcus strain by a contaminating mould, whichCape subsequently lead to the identification and clinical use of penicillin, that things started of to look up for natural products. Soon after the introduction of penicillin in 1941, came the discovery of streptomycin, isolated from S. griseus by Selman Waksman in 1944, which became the first effective treatment for TB (Davies, 2009). Following these discoveries, much research was conducted into microbial natural products and the following 20 – 30 years lead to the discovery of virtually all of the classes of antibiotics used today (Butler & Buss, 2006). This period (1940-1970) is thus widely referred to as “the golden age” of antibiotics (Overby & Barrett,University 2005; Yoneyama & Katsumata, 2006; Marinelli, 2009) and delivered the aminoglycosides, ansamycins (rifamycins), β-lactams (penicillins and cephalosporins), glycopeptides, macrolides and tetracyclines amongst others (Chu et al., 1996; Powers, 2004; Projan & Shales, 2004; Butler & Buss, 2006; Yoneyama & Katsumata, 2006; Marinelli, 2009).

Following this period of mass antibiotic discovery was a period where the number of new molecules discovered dropped substantially and there was a scale-back by major pharmaceutical companies in the field of antibiotic drug discovery. In fact the only new classes of molecules that have been launched since 1970 are the pseudomonic acids in 1985, oxazolidinones in 2000 and lipopeptides in 2003 (with only the oxazolidinones also having a novel mode of action). However, multiple 61 derivatives from the known classes of compound have been generated (Powers, 2004; Projan & Shales, 2004; Norrby et al., 2005; Overbye & Barrett, 2005; Butler & Buss, 2006; Peláez, 2006; Marinelli, 2009).

1.3.2 Sources of antibiotics A major proportion (~80%) of the antibiotic classes known today were isolated as or derived from natural products (Overby & Barrett, 2005; Butler & Buss, 2006; Harvey, 2007), with a few classes being completely synthetic (Overby & Barrett, 2005; Butler & Buss, 2006; Peláez, 2006). Of the natural product derived classes, a vast majority of them are of a microbial origin (Busti et al., 2006; Peláez, 2006). Other sources contributing to the pool of natural products include multiple plant species and various marine invertebrates (Peláez, 2006). The microbial taxa that are best known for their ability to produce secondary metabolites, like antibiotics, include the filamentous actinobacteria, fungi, cyanobacteria and myxobacteria (Peláez, 2006).Town Medicinal chemistry is further responsible for improving and diversifying many of the natural products that were initially found to have antibacterial activity (Powers, 2004; Projan & Shales, 2004; Peláez, 2006; Harvey, 2007; Marinelli, 2009). The manipulation of the actual genetic pathways involved in the production of the antibiotic molecule or feeding of the producing strain Capewith modified versions of precursor molecules required for the synthesis of the antibiotic, has ofalso resulted in the formation of derivatives or even altogether novel molecules (Butler & Buss, 2006; Sosio & Donadio, 2006; Yoneyama & Katsumata, 2006; Harvey, 2007).

It should be noted that of the antibiotic producing microbes, the filamentous actinobacteria are the most important group, with an estimate of close to half of all natural bioactive molecules being derived from them (LazzariniUniversity et al., 2000; Lam, 2006; Williams, 2008; Marinelli, 2009). Furthermore, 80% of all antibiotics that originated between 1955 and 1962 were isolated from the actinobacteria (Watve et al., 2001), with the genus Streptomyces being by far the most prolific producer (Lazzarini et al., 2000; Anderson & Wellington, 2001; Watve et al., 2001; Busti et al., 2006; Marinelli, 2009). As such, many drug discovery programs have been focused on actinobacteria (Lam, 2006; Williams, 2008), particularly streptomycetes. However, the search has also been extended to other genera that are less commonly isolated (Lazzarini et al., 2000; Marinelli, 2009). Although terrestrial actinobacteria have been widely exploited in the past (Williams, 2008), their marine counterparts are now also being investigated and it appears that they too can provide a vast source of novel antibiotics (Lam, 2006; Williams, 2008). 62

1.3.3 Mechanisms of action Although there are multiple structural classes of antibiotics, each with a wide variety of structures, there are only a few mechanisms by which they exert their antibacterial activity (Yoneyama & Katsumata, 2006). All the mechanisms involve interference with production of the major cellular components required for the bacteria to multiply and survive (Levy, 1998). Fig 1.3.1 represents a diagrammatic summary of these targets.

Town

Cape of

Figure 1.3.1 Antibiotic target sites. PBP, penicillin binding protein; DHP, dihydropteroate; DHF, dihydrofolate; THF, tetrahydrofolate. Taken from Yoneyama & Katsumata (2006).

1.3.3.1 Inhibition ofUniversity cell wall synthesis The bacterial cell wall serves as a means to protect the cell from lysis (Prescott et al., 2002a; Yoneyama & Katsumata, 2006). In Gram positive bacteria the cell wall is composed mainly of a thick layer of peptidoglycan and forms a rigid outermost barrier (Prescott et al., 2002a; Yoneyama & Katsumata, 2006), whereas in Gram negative bacteria the cell wall generally consists of only a thin layer of peptidoglycan that is surrounded by an outer membrane (Prescott et al., 2002a). The rigid peptidoglycan layer is a polymer that consists of strands composed of alternating N- acetylglucosamine and N-acetylmuramic acid residues with attached peptide chains (Prescott et al., 2002a). Cross linking of the strands occurs by the action of transglycosidase and transpeptidase 63 enzymes (Yoneyama & Katsumata, 2006) and results in the formation of a dense interconnected network (Prescott et al., 2002a).

The bifunctional enzymes that are responsible for the formation of the cross links between the strands are the target sites for the β-lactam type antibiotics like the penicillins and cephalosporins (Chu et al., 1996; Yoneyama & Katsumata, 2006). The antibiotics bind to the transpeptidase and acylate the active site, causing the inactivation of the enzyme, which as a result is referred to as a penicillin-binding protein (PBP) (Chu et al., 1996; Yoneyama & Katsumata, 2006). Similarly the phosphoglycolipid antibiotic moenomycin A inhibits the formation of cross links in the cell wall, however it does so through the inhibition of the transglycosylation step, a feat which is unique to this compound (Baizman et al., 2000; Piddock, 1998). An alternative strategy is applied by the glycopeptide antibiotic vancomycin, which binds to the terminal D-Ala-D-Ala moiety of the pentapeptide side chain attached to the N-acetylmuramic acid of the peptidoglycan strands. This then prevents the transglycosylation reaction from being performed Townand results in prevention of cell wall biosynthesis (Chu et al., 1996; Piddock, 1998; Yoneyama & Katsumata, 2006). By preventing the formation of the cross links between the polysaccharide strands, glycopeptide antibiotics weaken the overall structure of the peptidoglycan layer andCape ultimately render the bacteria vulnerable to osmotic lysis. of

1.3.3.2 Inhibition of DNA and RNA synthesis The replication of DNA is a cellular process that is critically important for all organisms and involves the interplay of multiple enzymes including topoisomerases, polymerases and helicases (Prescott et al., 2002b; Yoneyama & Katsumata, 2006). The bacterial chromosome, which is present in a supercoiled state inUniversity the cell, undergoes changes in structure during the replication process. The topoisomerases are responsible for the conversion between the different topological forms (Yoneyama & Katsumata, 2006), relieving the tension in the DNA strands that are generated as they are unwound and rewound by helicases (Prescott et al., 2002b). Replication of the unwound DNA is performed by DNA polymerases (Prescott et al., 2002b). The transcription of the genetic material from DNA to mRNA is somewhat simpler than DNA replication; however, it is another very important process for the survival of all organisms (Yoneyama & Katsumata, 2006).

The quinolone antibiotics like nalidixic acid, norfloxacin and ciprofloxacin, target the type II topoisomerase DNA gyrase, and through stabilization of the enzyme complex, cause a shift of the 64 equilibrium in the gyrase catalytic reaction. This results in an accumulation of the cleaved DNA complex (Yoneyama & Katsumata, 2006). The quinolones are also implicated in the inhibition of DNA topoisomerase IV, another type II topoisomerase, their primary target in Gram positive bacteria like Staphylococcus aureus. However, this enzyme is a secondary target in most Gram negative bacteria (Piddock, 1998). The ansamycin antibiotic rifampicin inhibits transcription through the inhibition of the RNA polymerase by binding to the β-subunit of the enzyme at an allosteric site (Piddock, 1998; Yoneyama & Katsumata, 2006). The essential nature of DNA and RNA synthesis for survival of all organisms, as well as the involvement of multiple steps in the process, makes these ideal cellular mechanisms to be targeted by antibiotic molecules.

1.3.3.3 Inhibition of protein synthesis Yet another vitally important cellular function is the synthesis of proteins. This process is carried out by the ribosomes, which in prokaryotes consist of a 30S and a 50STown subunit which combine to form the complete 70S ribosome (Prescott et al., 2002c; Yoneyama & Katsumata, 2006). The complex process of protein synthesis starts with initiation, where the mRNA, ribosomal subunits and fMET- tRNA (both bound by initiation factors) come together to form the ribosome complex; elongation of the polypeptide chain then occurs, where amino acidsCape are added in a stepwise fashion in the three phases that make up each elongation cycle (aidedof by elongation factors): aminoacyl tRNA binding, the transpeptidation reaction and translocation; followed by termination, where the ribosome recognizes the stop codon in its aminoacyl site (A-site), hydrolyses the peptide free from the tRNA and dissociates from the mRNA (Prescott et al., 2002c).

The aminoglycoside antibiotics act by binding to the A-site of the ribosome (present within the 30S subunit) and thereby preventUniversity the synthesis of proteins by blocking the elongation step (Durante- Mangoni et al., 2009). The same mechanism of action is exhibited by the broad-spectrum tetracycline antibiotics (Chu et al., 1996). Macrolide antibiotics bind to the 50S ribosomal subunit and cause dissociation of the peptidal-tRNA from the ribosome during the translocation phase of elongation (Chu et al., 1996). The synthetic oxazolidinone antibiotics (linezolid and eperezolid) also bind to the 50S ribosomal subunit; however they appear to act in the prevention of initiation of protein synthesis (Chu et al., 1996; Piddock, 1998). Antibacterial peptides have also been identified that exert their action through the inhibition of protein synthesis (Piddock, 1998), one by interacting with the elongation factor Tu and thereby preventing the binding of aminoacylated tRNA (Chu, et al., 1996). The highly complex nature of protein synthesis provides multiple opportunities for 65 antibiotics to exert their effect, exemplified by the range of targets acted upon by the agents mentioned here.

1.3.3.4 Other sites of inhibition Other mechanisms of action are perhaps not exploited as much as those stated above, but can be just as effective at inhibiting bacterial cell growth and survival. Many of these potential alternative targets are widespread amongst all organisms and therefore molecules targeting them often require additional research to ensure their safety.

Interfering with a metabolic pathway that is responsible for the production of an essential metabolite is a powerful way of rendering an organism unable to grow or perhaps even survive. The inhibition of folic acid biosynthesis is one such mechanism. The lack of this biosynthetic pathway in human metabolism makes it an ideal pathway to be targeted for antibiotic inhibitionTown (Prescott et al., 2002f). The maintenance of the integrity of the cell membrane, including the outer membrane of Gram- negatives, is essential to the survival of the cell. Cationic peptides like the polymyxins (cyclic peptides with attached fatty acid chains) attack the cell membranes of bacteria by disrupting the membrane organization and result in an increased membraneCape permeability causing the death of the cell (Piddock, 1998; Yoneyama & Katsumata, 2006).of

1.3.4 Antibiotic resistance The introduction of antibiotics as therapeutic agents for the treatment of infections saw a drop in the number of deaths caused by infectious diseases and even lead to many clinicians believing that we had won the war on bacterial infections (Cohen, 1992; Chu et al., 1996; Yoneyama & Katsumata, 2006). This however wasUniversity not the case, as soon after the release of these “wonder drugs”, came the problem of antibiotic resistance. In fact resistance to most of the antibiotic drugs has been observed within four years of their approval, with resistance to many developing within less than a year of their introduction. In some cases, resistance was recorded even before the antibiotics were release for clinical use (Overbye & Barrett, 2005; Yoneyama & Katsumata, 2006). For example, resistance to penicillin was noted a few years after its introduction in 1942, resistance to streptomycin was detected a year after its discovery in 1944 (Davies, 1994; Yoneyama & Katsumata, 2006), while resistance to linezolid was experienced during the clinical trials of the antibiotic (Overbye & Barrett, 2005). 66

Antibiotic resistance can either be intrinsic or acquired. Intrinsic resistance is inherent in the nature of the organism itself and thus the resistance is due to its genetic make up. Examples being the resistance of Pseudomonas aeruginosa to many types of antibiotics due to the low permeability of its cell envelope. Acquired resistance on the other hand, results from the bacteria obtaining genes or genetic elements that allow them to overcome the action of the antibiotic. This acquired resistance can be as a result of either random mutation that results in a change that affords the bacteria enhanced fitness or due to the uptake of genetic material containing resistance genes (Levy, 1998; Yoneyama & Katsumata, 2006; Mulvey & Simor, 2009).

Random mutations that confer resistance are a rare event, but can arise during antibiotic treatment, which is how M. tuberculosis becomes resistant to isoniazid and rifampicin. The uptake of resistance genes, often present on transferable segments of DNA like plasmids, transposons or integrons, is more likely to be the cause of the resistance. Plasmids are able to replicate independently of the bacterial chromosome and are usually responsibleTown for carrying multiple resistance genes and genes that may improve fitness or virulence. Transposons are segments of DNA that contain genes (often antibiotic resistance genes) and elements that allow these genes to replicate and transpose or jump into the chromosomeCape or onto plasmids. An integron is a DNA element that can capture genes from plasmidsof or the chromosome and, although they are not themselves mobile, are often carried by plasmids or transposons. The main ways in which these genetic elements are transferred between bacteria are: conjugation, transformation and transduction. For the latter two mechanisms to result in resistance, the genes that are received need to be stably incorporated into the chromosome or a plasmid (Davies, 1994; Levy, 1998; Mulvey & Simor, 2009).

Bacteria are often resistantUniversity to multiple different antibiotics, the genes of which are often transferred together and afford multidrug resistance to the recipients (Levy, 1998). As a result, a bacterium that is resistant to one antibiotic has a higher chance of being resistant to other antibiotics than that of a sensitive bacterium (Gould, 2008). This development of multidrug resistance is a major problem. The problem is further intensified by the development of antimicrobial resistance in other organisms including fungi, parasites, particularly those causing malaria, and viruses, most notably HIV (Norrby, 2005).

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1.3.4.1 Mechanisms of resistance Despite the multitude of antibiotic molecules and the wide range of their targets within the cell, there are only a few mechanisms by which bacteria overcome the actions of these antibiotics (Fig 1.3.2).

Town

Figure 1.3.2 Antibiotic resistance mechanisms. Modified from Yoneyama & Katsumata (2006). Cape of 1.3.4.1.1 Reduced intracellular concentration of antibiotic For an antibiotic to be effective it firstly needs to get into the cell and accumulate to a high enough concentration to cause the desired inhibition. Thus by preventing the antibiotic from entering the cell or by actively removing it from the cell, the molecule is not allowed to accumulate and cause its inhibitory effect (Mulvey & Simor, 2009). This is generally achieved by one of two mechanisms: permeability barriers thatUniversity prevents access or by the development of efflux pumps to actively remove the antibiotics (Levy, 1998; Yoneyama & Katsumata, 2006; Mulvey & Simor, 2009).

The outer membrane of the Gram negative bacterial cell acts as a permeability barrier, with the movement of essential molecules (as well as antibiotics) through the membrane being achieved with the assistance of outer membrane proteins or porins (Mulvey & Simor, 2009). Modifications of the structure of these porins (by mutation) or the loss of certain porins altogether, can result in the prevention of movement of antibiotics into the cell. This mechanism is thought to contribute to the resistance of P. aeruginosa and other Gram negatives to the aminoglycosides and the β-lactams (Chu et al., 1996; Yoneyama & Katsumata, 2006; Mulvey & Simor, 2009). 68

Antibiotic efflux pumps are present in a wide range of both Gram-negative and -positive bacteria and may be able to export a single antibiotic or multiple antibiotics (Mulvey & Simor, 2009). These efflux pumps can either be primary transporters, using the energy from ATP hydrolysis to power the transport, or secondary transporters, which use the proton (or sodium ion) motive force to pump the antibiotics from the cell (Yoneyama & Katsumata, 2006). Resistance of many staphylococci to macrolides and type B streptogramins is mediated by efflux pumps, as is the resistance to tetracycline and its structural analogues (Chu et al., 1996).

1.3.4.1.2 Inactivation of antibiotics Instead of preventing the antibiotic from entering the cell, an alternative mechanism of resistance is to destroy the antibiotic or modify it in such a way that it can no longer bind to its target in the cell (Levy, 1998; Yoneyama & Katsumata, 2006; Mulvey & Simor, 2009). This is one of the most common mechanisms of resistance and is commonly achieved by the acquisition of genes which encode the antibiotic-modifying enzymes (Davies, 1994; YoneyamaTown & Katsumata, 2006; Mulvey & Simor, 2009).

Perhaps the best known example of enzymatic inactivationCape (responsible for resistance in a wide range of bacteria) is that of the hydrolytic cleavageof of the β-lactam ring in penicillins, cephalosporins and carbapenems by the β-lactamase enzymes, rendering the antibiotics unable to bind their target PBP’s (Neu, 1992; Yoneyama & Katsumata, 2006; Mulvey & Simor, 2009). Resistance to the aminoglycosides can also be achieved by enzymatic inactivation, involving covalent modification by the action of various aminoglycoside modifying enzymes, lowering the affinity of the antibiotics for their rRNA target (Neu, 1992; Yoneyama & Katsumata, 2006; Durante-Mangoni et al., 2009). University 1.3.4.1.3 Alteration of target sites Once inside the cell the antibiotic needs to bind to its target site before it can exert its antibacterial effect. Preventing this is achieved by two means, either modification of the target site so that it can no longer be bound by the antibiotic (Mulvey & Simor, 2009), or over production of the target molecule to dilute out the effect of the antibiotic (Levy, 1998; Yoneyama & Katsumata, 2006). The most common means by which alteration of the target is achieved is by obtaining new genes (from plasmids or transposons) that encode enzymes that carry out the modifications. However, it can also result from mutations in the genes encoding the targets, resulting in modified versions that have a lower affinity for, or no longer bind, the antibiotic (Yoneyama & Katsumata, 2006). 69

An example of enzymatic modification of the target is seen in S. aureus in its resistance to erythromycin and other macrolide, lincosamide and streptogramin B antibiotics. Resistance is mediated by a methyltransferase which is responsible for the mono- or dimethylation of a specific adenine residue on the 23S rRNA, resulting in reduced affinity for the antibiotic without affecting protein synthesis (Neu, 1992; Chu et al., 1996; Yoneyama & Katsumata, 2006). The resistance of many species of Acinetobacter, Klebsiella and Pseudomonas to aminoglycosides is also achieved by the methylation of the ribosome (16S rRNA within the 30S subunit), resulting in its reduced affinity for the antibiotic (Durante-Mangoni et al., 2009). The acquired resistance to the glycopeptide vancomycin is as a result of the enzymatic reprogramming of the peptidoglycan terminus from D- Ala-D-Ala to either D-Ala-D-lactate, which produces high level resistance (1000-fold drop in affinity for vancomycin) or to D-Ala-D-Ser, which results in low level resistance (Neu, 1992; Chu et al., 1996; Yoneyama & Katsumata, 2006).

Resistance to isoniazid (and structurally related antibiotics) in MycobacteriumTown smegmatis and other clinically isolated mycobacteria can be attributed to mutations that occur upstream of the gene inhA (coding for the fatty acid synthase InhA), which results in the creation of a stronger promoter and/or an improved ribosome binding site. This presumablyCape leads to the overexpression of this target, thereby titrating the antibiotic (Heym & Cole, 1997).of

1.3.4.2 Sources of antibiotic resistance and contributing factors There has been much debate over the cause of antibiotic resistance, however it can be surmised that many of the factors implicated possibly had some role to play in the development of antibacterial resistance, however small they may be. First and foremost it should be noted that the antibiotics themselves are the mainUniversity causative agent in antibiotic resistance. They place selective pressure on bacteria and promote survival of the resistant strains, which will then be able to proliferate in the absence of the competition of the sensitive strains that would otherwise have limited their growth. Antibiotic use thus promotes the development of a pool of resistance genes that can then potentially be transferred to the sensitive strains. The lack of competition may also result in the resistant, non pathogenic bystanders becoming disease agents themselves. The antibiotics are thus “self-defeating” molecules and promote their own ineffectiveness (Cohen, 1992; Levy, 1998; Mulvey & Simor, 2009; Overbye & Barrett, 2005; Projan & Shales, 2004). The bacteria themselves are another major contributing factor to antibiotic resistance. Having such a short life span allows for rapid evolution to take place which, when coupled with the frequent exchange of genetic material and the vast 70 biochemical versatility of bacteria, makes the development of resistance a somewhat simple feat. The development of antibiotic resistance in bacteria can in fact be thought of in terms of Le Chatelier’s principle (if a stress is applied to a system, the system will react in a way to reduce that stress) in that it is a response to reduce the stress that was placed on the bacteria by the antibiotic (Hamilton-Miller, 2004).

Currently there is a substantial pool of antibiotic resistance genes present in nature (Davies, 1994) which is the most likely source of the resistance determinants that are present in pathogenic bacteria (Yoneyama & Katsumata, 2006). But what are the sources of these genes? Perhaps the most obvious source is the organisms that are producing the antibiotics (Davies, 1994). These organisms would obviously have to have some sort of mechanism whereby they protect themselves from the action of the antibiotic they are producing to allow its production to be of any benefit to them. A notable example is the presence of the same mechanism of aminoglycoside resistance, through methylation of the ribosome, being present in the producingTown strains and in the unrelated aminoglycoside resistant pathogenic bacteria (Durante-Magoni et al., 2009; Gould, 2008). Similarly the mechanism of resistance to erythromycin present in S. aureus, is the same as the self-protection mechanism present in erythromycin producers (YoneyamaCape & Katsumata, 2006). The producing strains however are not the only source of resistanceof genes, as it has been proposed that many housekeeping genes are able to evolve into antibiotic resistance genes, which is thought to have been how the aminoglycoside modifying enzymes arose from the sugar kinases and acetyltransferases (Davies, 1994). Random mutations that arise during treatment can often result in development of resistance or may even strengthen the existing resistance, however these are generally rare events (Levy, 1998; Mulvey & Simor, 2009). The antibiotic may also cause the inductive expression of a latent chromosomal geneUniversity resulting in the development of resistance (Neu, 1992). Alternatively the genes may simply be those that are naturally occurring and happen to confer antibiotic resistance as well, an example being the efflux pump of P. aeruginosa which happens to be able to export antibiotics and as such confers intrinsic antibiotic resistance (Yoneyama & Katsumata, 2006). All of these genes make up the pool which other bacteria may draw upon when they are exposed to antibiotics (Davies, 1994).

There are numerous factors that have been thought to have contributed to the widespread prevalence of antibiotic resistance, most notably being the overuse or misuse of antibiotics. The first culprit responsible for this overuse is the doctors, who frequently prescribe antibiotics to patients who do 71 not need them, often because they are demanded by the patients (over 80% of doctors admit to prescribing antibiotics against their better judgment) or as a result of an improper initial diagnosis. This unnecessarily increases the exposure of bacteria to antibiotics and serves no purpose other than promoting the spread of antibiotic resistance. Fig 1.3.3 is a cartoon parodying the overuse of antibiotics by doctors. The next culprit is the patient who often misuses the antibiotics, even if they have been correctly prescribed. Most commonly patients do not complete the full course of the antibiotic and often use the leftovers to self medicate. This is particularly damaging as it exposes the bacteria to low level concentrations of the antibiotics and greatly enhances the development of resistance. The fact that many antibiotics are available over the counter in many countries further compounds this problem of misuse (Levy, 1998; Powers, 2004).

Town

Cape of

Figure 1.3.3 “Don’t forget to take a handful of our complimentary antibiotics on your way out.” (Levy, 1998).

The current trend to include antibiotics and antiseptics in commonly used household items is another factor contributing to theUniversity development of antibiotic resistance. The inclusion of antibiotics in items like toothpastes, soaps, lotions, detergents and impregnation into items like toys, clothes, mattresses and cutting boards has been a point of much debate, with many believing it to be totally unnecessary and serving only to select for resistance in the household. Some go so far as to say that this trend could lead to our homes becoming much like our hospitals – a haven for resistant bacteria (Levy, 1998; Kerr & Venter, 2001).

The use of antimicrobials in agriculture has long been thought to be a factor leading to the development of antibiotic resistance. Antibiotics are commonly used in animal husbandry to promote growth and prevent disease. This results in the long term exposure of bacteria to low doses 72 of antibiotics – a perfect recipe for the development of resistance. The resistant bacteria are thought to then be spread to people who handle the animals and work with their carcasses (Neu, 1992; Levy, 1998; Yoneyama & Katsumata, 2006). Another common use of antibiotics in agriculture is in the prevention of bacterial infections in orchards, where acres of fruit trees are sprayed with aerosol antibiotics. The problem here is the antibiotic can linger on the fruit and promote the growth of resistant strains that are spread when the fruit is processed. The spray also spreads further than just the targeted trees, becoming diluted in the environment and further promoting the development of resistance (Levy, 1998).

All the factors mentioned above add to the development of antibiotic resistance, however there are also many factors that contribute to the spread of the already resistant organisms. Medical or surgical equipment as well as the health care workers themselves have been implicated in the spread of resistant bacteria within a hospital or even between different hospitals (Mulvey & Simor, 2009). The increased amounts of both international travel and trade have furtherTown contributed to the spread of these resistant organisms, by the infected persons or contaminated goods, to countries all over the world (Cohen, 1992; Levy, 1998). Changes in social behaviour as well as economic changes have also contributed to the increase in resistance (Cohen, 1992).Cape of 1.3.4.3 Infectious diseases affected by antibiotic resistance The introduction of the use of antibiotics in the 1930’s can be considered to be one of the, if not the most important, measures which lead to the effective control of bacterial infections. Despite the widespread use and success of antibiotics, bacterial infections are still the second leading cause of death in industrialized nations (Butler & Buss, 2006), a fact that can be attributed to the development and spread of antibioticUniversity resistance (something we should have anticipated from the start (Hamilton- Miller, 2004)). The current situation sees the rate of development of resistance far outpacing that of new drug discovery (Butler & Buss, 2006), and could see a situation where we are faced with bacteria that are untreatable with all of the available antibiotics (Cohen, 1992; Mulvey & Simor, 2009). Usually the first thing that comes to mind when one thinks of antibiotic resistance are the nosocomial or hospital-acquired infections, which have received much of the focus of antibiotic resistance. Methicillin-resistant S. aureus (MRSA), which has been present in hospitals around the world for decades and has been responsible for multiple epidemics that are notoriously difficult to control, is one of the most well known resistant infections (Cohen, 1992).

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1.3.4.3.1 Tuberculosis One of the most dangerous infectious diseases that have been affected by antibiotic resistance is TB, which in 1993 was the first ever disease to be declared a public health emergency by the World Heath Organization (WHO) (BD, 2009). TB is caused by the bacterium M. tuberculosis and primarily infects the lungs, resulting in pulmonary TB, but can spread to other parts of the body including the brain, kidneys and the spine (CDC, 2009; Rodrigues et al., 2007; WHO, 2007). Treatment usually includes a two month initial intensive phase, where patients are administered isoniazid, rifampicin, pyrazinamide and ethambutol or streptomycin, which is followed by a four month continuation phase, consisting of isoniazid and rifampicin (Heym & Cole, 1997). Treatment is often administered as part of the WHO TB control strategy known as directly observed treatment, short course (DOTS). The programme aims to prevent patients from defaulting on their treatment (Noeske & Nguenko, 2002; WHO, 2007), which in South Africa usually occurs in about 15% of patients (Singh et al., 2007). Town The emergence of resistant and more importantly multidrug-resistant (MDR) TB poses a great threat to the global TB control program (Noeske & Nguenko, 2002). MDR-TB was first noticed in the late 1980’s (Heym & Cole, 1997) and is defined as strainsCape that are resistant to at least isoniazid and rifampicin, two of the front line drugs (Noeske of& Nguenko, 2002; Rodrigues et al., 2007; Singh et al., 2007; WHO, 2007) and is a growing public health problem worldwide (Cohen, 1992; Duncan & Barry, 2004; Andrews et al., 2007; Martins et al., 2009). Treatment for MDR-TB involves the use of various second line drugs, including capreomycin, cycloserine, ethionamide, kanamycin and the fluoroquinolones (Heyme & Cole, 1997), which require a much longer treatment period, are more expensive, complicated (due to drug toxicity) and often ineffective (Gandhi et al., 2006; Andrews et al., 2007; Rodrigues et Universityal., 2007; Martins et al. , 2009). The cost of treating an MDR-TB infection can be as much as 1400 times higher than that of a drug-sensitive TB infection, with the treatment lasting for up to two years (Bateman, 2006). Even more worrying is the recent emergence of cases of extensively drug-resistant (XDR) TB that have been reported world wide (Andrews et al., 2007; Martins et al., 2009). This form of TB is noted to be resistant to isoniazid, rifampicin, fluoroquinolones and at least one of the injectable second line drugs: amikacin, capreomycin or kanamycin (Gandhi et al., 2006; Andrews et al., 2007; Singh et al., 2007; CDC, 2009). Due to the high level of resistance in XDR-TB, there are not many treatment options available, and owing to the final diagnosis taking between six and 16 weeks (meaning patients often do not receive the correct treatment initially) the outcome is generally not a very good one (CDC, 2009). The severity of 74

XDR-TB can be seen in the very high mortality rate (>98%) that occurred during an outbreak at Tugela Ferry hospital in KwaZulu-Natal (KZN) province, South Africa in 2006. All but one of the infected patients died within 25 days of diagnosis (Bateman, 2006; Andrews et al., 2007; Singh et al., 2007).

The worldwide problem of TB is further compounded by the ever increasing incidence of HIV infections, which together form a lethal combination (WHO, 2007) with the one promoting the progression of the other (Andrews et al., 2007; Goldfeld & Ellner, 2007). An HIV infection hastens the natural course of TB and makes it more likely for a person to develop a new active TB infection or for a latent infection to progress to an active one (Andrews et al., 2007; Goldfeld & Ellner, 2007). In fact HIV positive persons are over five times more likely to develop an active TB infection than those that are HIV negative (Gandhi et al., 2006). Furthermore TB hastens the development of HIV, by activating cells harbouring latent HIV infections, promoting viral replication and increasing the drop in CD4 T cell counts (Goldfeld & Ellner, 2007). Therefore it Townis not surprising that the leading cause of death amongst HIV infected persons is TB (Duncan & Barry, 2004; Gandhi et al., 2006; WHO, 2007; CDC, 2009). Cape The WHO estimated that in 2005 over 1.6 millionof people worldwide died as a result of TB infections, with the highest incidence rate being in sub-Saharan Africa, at 343 cases per 100 000 people, nearly double that of South-East Asia (WHO, 2007). South Africa is one of the countries in sub-Saharan Africa that is particularly badly effected by TB, with about 250 000 new cases being reported each year (Bateman, 2006; Andrews et al., 2007). The Western Cape Province is the hardest hit, having an incidence rate that is up to three times higher than that of the rest of the country (Weyer et al., 1995).University The high prevalence of HIV in Africa can be considered the leading cause of a rise in the incidence of TB in the region since 1990 (Gandhi et al., 2006; WHO, 2007). This is illustrated by the fact that 80% of the patients with new TB infections in KZN are also HIV positive (Bateman, 2006; Gandhi, 2006) and all the Tugela Ferry XDR-TB patients for which the HIV status was also known were HIV positive (Andrews et al., 2007; Singh et al., 2007).

Resistance in TB threatens public health like no other disease, especially given its deadly relationship with HIV. We therefore desperately need new drugs to be developed to help combat its spread if we are to avoid the potentially devastating consequences.

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1.3.5 Implications of antibiotic resistance and potential solutions In the past the problem of antibiotic resistance was pretty much thought to be of no consequence as there were always new antibiotics coming onto the market to counteract any resistance that had developed (Neu, 1992; Hamilton-Miller, 2004). The situation has however now changed and the problem of resistance and its implications are realized for what they really are: dire and far reaching (Powers, 2004).

One of the most obvious solutions to the problem of antibiotic resistance would be to simply develop new antibiotics effective against resistant strains. This is however easier said than done, evident in the fact that only three new classes of drugs have been released since the 1970’s (Butler & Buss, 2006). Despite the difficulty associated with new drug discovery, ongoing antibiotic research could potentially provide us with a solution. A return to natural product screening should be the first move, as natural products have been very successful (Overbye Town & Barrett, 2005; Peláez, 2006; Harvey, 2007). A very large proportion of these natural products originated from the filamentous actinobacteria (Lazzarini et al., 2000; Mincer et al., 2002; Overbye & Barrett, 2005; Busti et al., 2006; Lam, 2006; Marinelli, 2009), making this group an ideal source in which to continue the search. The screening of underexploited environments,Cape like the sea, as well as focusing on the rarer genera of producing organisms, could provide of the previously undiscovered chemical diversity we need (Busti et al., 2006; Lam, 2006; Peláez, 2006; Williams, 2008; Marinelli, 2009). Focusing on previously unculturable strains may also provide us with novel bioactive metabolites (Busti et al., 2006), as might the use of genome mining to identify unexpressed or “cryptic” biosynthetic pathways that can be induced through altering the culture conditions in favour of expression (Peláez, 2006; Gulder & Moore, 2009; Marinelli, 2009), or by cloning the appropriate genes into another host for expression (Harvey,University 2007).

The generation of new antibiotics can also be achieved by modification of the compounds we already have to render novel structures, something which has been performed extensively in the past with great success (Butler & Buss, 2006; Peláez, 2006; Sosio & Donadio, 2006; Harvey, 2007). The use of combinatorial biosynthesis and other modern genetic techniques can allow for the generation of “unnatural” types of natural products and create even further novel chemical structures (Sosio & Donadio, 2006; Harvey, 2007; Gulder & Moore, 2009). Advances in this field could very well be the source of completely novel bioactive molecules that perform well against resistant strains.

76

The next most obvious solution to the resistance problem is to simply inhibit the resistance mechanisms and thereby allow the currently available antibiotics to remain effective. This can include synergistic action of a second molecule that inhibits the antibiotic resistance mechanism, allowing the antibiotic to exert its effect (Hamilton-Miller, 2004; Levy, 1998; Nuotio, 2009; Peláez, 2006).

Perhaps the best option available to combat the development and spread of antibiotic resistance is to try and better utilise the currently available antibiotics which should ultimately lead to their reduced use and will thereby effectively reduce the selective pressure for antibiotic resistance (Cohen, 1992; Levy, 1998; Hamilton-Miller, 2004). This can be achieved by the proper use of antibiotics by patients as well as doctors (Levy, 1998). Combination therapy, that is the use of multiple antibiotics with different mechanisms of action in the same patient, will also help to reduce the development of resistance. However, this is a slightly more expensive treatment option with a higher risk of allergic reaction (Cohen, 1992). The development of better delivery systemsTown for the antibiotics could further reduce the selective pressure for antibiotic resistance because by delivering them directly to the source of the infection, the antibiotic will be present there at a higher concentration which will reduce the overall length of treatment and will also limitCape the exposure of the rest of the body to the antibiotic (Duncan & Barry, 2004). of

Another effective means to reduce the antibiotic use is to find alternatives to antibiotics (Hamilton- Miller, 2004). This is particularly important in agriculture and animal husbandry, where low doses of antibiotic are used for extended periods (Cohen, 1992; Levy, 1998). Alternative treatments to antibiotic therapy should also try to be used for minor conditions like acne (Levy, 1998). Some other ideas of possible alternativesUniversity to antibiotic treatment include the utilisation of probiotics to prevent infection (Sleator, 2009), phage therapy, impeding the virulence mechanisms themselves instead of acting against the whole organism or the use of complementary and alternative medicine practices (Hamilton-Miller, 2004).

Measures to prevent the spread of infection are perhaps our best option, as by preventing the infections we remove the need for the use of antibiotics in the first place (Cohen, 1992). The use of vaccinations and immunizations is another way to prevent the spread of infections and should ideally be developed for those infections that are particularly difficult to treat (Cohen, 1992; Hamilton- Miller, 2004). 77

The high level of antibiotic resistance coupled with the current lack of new antibiotics, not to mention the scale back in antibiotic drug discovery by many pharmaceutical companies, has left a rather large gap in the market. The current drugs we have to treat bacterial infections are dwindling due to this threat of ever encroaching resistance to these drugs and unless something is done to remedy the situation we will rapidly approach an era that will resemble that of the pre antibiotic age.

1.4 Aims of this study

South Africa is well known for its biodiversity, particularly its floral diversity, with the Cape Floral Kingdom making up the smallest yet richest of the world’s six floral kingdoms. The Cape Floral Kingdom contains over 1300 species per 10 000km2, more than triple that of the Amazon Rainforest (Maneveldt, 2009). This area is populated with a wide variety of fynbos plant species, many of which are endemic to the area, as well as many associated animal and insect species, many of which are also endemic. Soil collected from a fynbos-rich area was Town used for isolating filamentous actinobacteria, with the intention of characterising novel species. This formed the first major focus of this study, with particular emphasis being placed on the isolation of strains belonging to the genus Amycolatopsis. Cape

The actinobacteria are well known for their abilityof to produce antimicrobials, many of which are active against M. tuberculosis, and are therefore a potential source from which to isolate much needed, novel antitubercular drugs. Thus the second focus of this study was the screening of the isolated actinobacterial strains for antibiotics active against Mycobacterium aurum A+, a non- pathogenic species with a similar antibiotic susceptibility profile to that of M. tuberculosis (Chung et al., 1995). Isolation and partial purification of the antimicrobial molecules were attempted from those strains showing strongUniversity inhibitory activity.

Many members belonging to the genus Amycolatopsis have the ability to produce antimicrobial compounds and therefore this genus could be of great interest in antibiotic screening programmes. To date, the phylogenetic analysis of the genus has been exclusively based on 16S rRNA gene sequences and, although phenotypic differences can be used to differentiate species, DDH is often required to resolve the relationships of the more closely related species. For this reason the final aim of this study was to assess the feasibility of using partial gyrB and recN gene sequences as alternatives for phylogenetic analysis, as well as for resolving species relationships within the genus 78

Amycolatopsis, i.e. predicting whether strains belong to different genomic species from gyrB and recN genetic distances.

1.5 References:

Adachi, K., Katsuta, A., Matsuda, S., Peng, X., Misawa, N., Shizuri, Y., Kroppenstedt, R. M., Yokota, A. & Kasai, H. (2007). Smaragdicoccus niigatensis gen. nov., sp. nov., a novel member of the suborder Corynebacterineae. Int J Syst Evol Microbiol 57, 297-301.

Adékambi, T., Drancourt, M. & Raoult, D. (2008). The rpoB gene as a toll for clinical microbiologists. Trends Microbiol 17, 37-45.

Anderson, A. S. & Wellington, E. M. H. (2001). The taxonomy of Streptomyces and related genera. Int J Syst Evol Microbiol 51, 797-814.

Andrews, J. R., Shah, N. S., Gandhi, N., Moll, T. & Friedland, G. (2007). Multidrug-resistant and extensively drug- resistant tuberculosis: implications for the HIV epidemic and antiretroviral therapy rollout in South Africa. J Infect Dis 196, S482-S490.

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Contents

2.1 Summary 92 2.2 Introduction 93 2.3 Materials and methods 97 2.3.1 Sample collection 97 2.3.2 Isolation 97 2.3.3 Screening for antimicrobial activity 99 2.3.4 Preliminary identification 100 2.3.4.1 Genomic DNA extraction 100 2.3.4.2 16S rRNA gene amplification 100 2.3.4.3 Rapid molecular identification Town 100 2.3.4.4 Amycolatopsis genus specific PCR 101 2.3.5 Antibiotic extraction 101 2.3.5.1 PCR screening for antibiotic biosyntheticCape potential 101 2.3.5.2 Determination of extraction solvent 102 2.3.5.2.1 Small scale solventof extraction 102 2.3.5.2.2 Bioautography 102 2.3.5.3 Purification of antibacterial compounds 103 2.3.5.3.1 Large scale solvent extraction 103 2.3.5.3.2 Thin layer chromatography 103 2.3.5.3.3 Partial purification of compounds by column University chromatography 104 2.4 Results 104 2.4.1 Isolated actinobacteria 105 2.4.2 Screening for antibiotic activity 105 2.4.3 Preliminary identification 109 2.4.4 Antibiotic extraction 111 2.5 Discussion 115 2.6 References 121

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2.1 Summary

A soil sample collected from within the fynbos-rich area that is surrounded by the horseracing track at Kenilworth Racecourse, Cape Town, served as the source for the isolation of filamentous actinobacteria. The sampling area is known to contain a wide range of biodiversity, including endemic and endangered plant species. A total of 112 bacterial strains were initially isolated and, following morphological examination and de-replication, 64 strains were presumptively identified as actinobacteria and screened for their ability to produce antibioticsTown active against M. aurum A+, a non-pathogenic, fast growing mycobacterium with a similar antibiotic susceptibility profile to that of M. tuberculosis. Moderate to very strong antimycobacterial activity was recorded for 31 isolates and all were identified to belong to the genus StreptomycesCape, based on a rapid identification method. Based solely on morphological examination, aof further 17 isolates were noted as interesting and selected for preliminary identification as well. Eight of these morphologically interesting isolates were identified to belong to the genus Streptomyces, with three being identified as Amycolatopsis, three as belonging to members of the family Micromonosporaceae, one to the genus Nocardia, one to Gordonia, Nocardia or Skermania and one to either Kribbella or Nocardioides. The nine isolates with the highest antimycobacterial activity were further screened for activity against E. coli and S. aureus, subjected to antibioticUniversity extraction and attempts were made to partially purify the active compounds. Only a weakly active compound from one of the Streptomyces strains was successfully isolated by column chromatography.

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2.2 Introduction

Most of the antibiotic drugs on the market today originate from natural sources, being produced by various groups of microorganisms (Knight et al., 2003; Busti et al., 2006). The filamentous actinobacteria are by far the most prolific antibiotic-producing group of microbes, responsible for the production of more than half of all antimicrobial molecules (Lazzarini et al., 2000; Busti et al., 2006; Lam, 2006). With the current state of antibiotic resistance, there is a desperate need for the discovery of new antibiotics to treat the increasing number of resistant organisms (Thomson et al., 2004).

The most commonly isolated actinobacteria from soil belong to the genus Streptomyces, the members of which are well known for their ability to produce numerous antibiotics, accounting for about 45% of all known antibiotics and about 80% of actinobacterial products (Lazzarini et al., 2000). As a result, this genus has been heavily exploited as a sourceTown of antimicrobial agents in the past (Watve et al., 2001; Busti et al., 2006). Due to this, it is highly likely that any streptomycete isolated from soil will belong to a known species and therefore the chances of discovering a novel antibacterial compound from it are extremely low (BustiCape et al., 2006). The isolation of the rarer, non-Streptomyces genera increases the chance of isolating novel species and along with them novel compounds (Lazzarini et al., 2000). The use ofof previously unexploited sources, particularly those which are known to contain high levels of biodiversity will undoubtedly increase the chance of isolating novel strains (Knight et al., 2003).

South Africa is well known as a rich source of biodiversity and contains eight biomes that play host to over 19 000 different flowering plant species. The Cape Floral Kingdom contains, amongst others, the fynbos biomeUniversity (pronounced “fane-boss”) which forms a crescent shaped area that spans the region from Nieuwoudtville (360km north of Cape Town) to Port Elizabeth, some 770km eastwards along the coastline. The area between Port Elizabeth and Grahamstown is also known to contain fynbos, however it consists of only small patches containing a low number of species that are located in high altitude areas and are therefore excluded from the biome by many botanists. Maps of South Africa and the fynbos biome are shown in Fig 2.2.1. Despite the fynbos area only accounting for 6% of the total land area of South Africa (approximately 90 000km2), it contains more than half of the known plant species found in the whole of Southern Africa. In fact this floral kingdom is the richest of all six known kingdoms, containing over 1300 species per 10 000km2, despite being the 94 smallest in area. This is more than triple that of the South American rainforests, which only contain 400 species per 10 000km2 (Manning, 2003; Branch & Jennings, 2008; Maneveldt, 2009).

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Figure 2.2.1 Maps of South Africa (top) and the fynbos biome (bottom). In the upper map the province names are capitalised, cities are show in black, national parks in green and tourist attractions (and rivers) in blue, with the area known as the garden route being boxed; adapted from www.sa-venues.com. In the lower map, the area comprising the fynbos biome is shaded in green; taken from www.itmonline.org. 95

Many fynbos plants are woody and can be described as sclerophyllous, having hard leathery leaves as well as microphyllous, having small leaves, a feature which earned them their name – fynbos means “fine bush” in Dutch. The fynbos biome contains 950 different genera and over 9000 plant species, 70% of which are endemic to the region. The predominant species found in the region are the ericas (of which 600 species are found in this region, with only 26 in the rest of the world), proteas and restios, while the most speciated family is the family Asteraceae (daisy family) with just under 1000 species, over 600 of which are endemic (Manning, 2003; Branch & Jennings, 2008; Maneveldt, 2009).

The biodiversity within the fynbos biome is not limited to that of the floral species – a multitude of animals is also associated with the biome, many of which are also endemic to the region. The area supports a host of smaller mammals, including the Cape Hyrax or dassie, Chacma baboon, mongooses, mice and small buck species (klipspringers and grysbok), but it does not have the nutrient richness to support the needs of herds of larger mammals. Town Birds play an important role in pollination of fynbos and the six bird species that are endemic to the south-western Cape are all associated with fynbos. Many butterfly and other insect species, like ants, are supported by fynbos. The diversity of reptiles and amphibians is not particularlyCape great within the fynbos biome, however many species that are found there are endemic orof threatened. Close to half of the frog species found in the Cape are endemic to this region. Many of these frogs are associated with fynbos and can only be found in specific fynbos areas. Many endemic, rare and/or threatened or endangered species of fish can also be found within the estuaries or river systems of the fynbos biome, most notably the Olifants River system (Baard & de Villiers, 2000; Branch & Jennings, 2008; Maneveldt, 2009).

Located within the well-developedUniversity southern suburbs of Cape Town is Kenilworth Racecourse (Fig 2.3.1), the oldest horseracing course in South Africa and with it the Kenilworth Racecourse Conservation Area (KRCA), situated in the centre of the racing track (infield). The area was established in 1882 and comprises approximately 52 hectares of natural vegetation with nine natural seasonal wetlands, making it the largest such area within the southern suburbs of Cape Town. The KRCA is considered to be “the best example of” as well as “the most valuable piece of Cape sand plain fynbos remaining” (KRCA, 2009) within the Cape Peninsula, while the wetlands are thought to be among those of the highest quality in the south-western Cape. The area is thought to contain more than 283 indigenous plant species, many of which are endemic (two species of which are thought to be extinct in the wild) including some 20 Red Data Book species (those that are 96 threatened with extinction). A further 61 exotic and invasive floral species are also found on the site, bringing the total to over 340, with the result that it has been said that “no other single urban, natural vegetation remnant on our planet comes close in terms of sheer plant species numbers, relative to physical area” (KRCA, 2009). As with most fynbos areas, the site plays host to a wide range of animal species as well. There are over 79 bird species that are known to reside or frequent the area, two of which (the Peregrine falcon and the Marsh owl) are considered to be rare. The KRCA is home to a population of the critically endangered Micro frog, Microbatrachella capensis, which is the smallest amphibian in South Africa (no larger than a thumb nail), as well as the most endangered lowland amphibian. This endangered frog can only be found in four sub-populations from Betty’s Bay (approximately 20km north-west along the coast from Hermanus) to Cape Agulhas (with a total combined area of less than 10km2) with the KRCA population being the only known remaining population on the Cape Flats area of Cape Town. There are a further 12 frog species found at the site, many of which are endangered and all are endemic to the Cape. Furthermore, at least eight mammal species and 17 reptile species have been found to reside in Townthe KRCA (Baard & de Villiers, 2000; Hitchcock, 2005; Turner, 2006; Branch & Jennings, 2008; KRCA, 2009). This area is therefore a real “gold mine” of biological diversity (despite being located within a highly populated urban area), which has never been screened for actinobacterialCape diversity. This unique ecological site is thus an excellent source for the isolation of novelof actinobacteria.

Even though there have been extensive screening programmes for novel actinobacteria that focus on terrestrial environments, this source is by no means exhausted, evident by the fact that novel strains are readily isolated from terrestrial environments. However, the rate of re-discovery of known strains is increasing (Lam, 2006; Lam, 2007). The use of selective culturing techniques as well as collecting samples fromUniversity unique or unusual ecological niches increases the likelihood of isolating novel actinobacteria from terrestrial sources. It is also believed that only about 1% of all microorganisms can be cultivated under current laboratory conditions and therefore there is a huge section of the microbial population that remains to be isolated (Hamaki et al., 2005). The use of alternative media and isolation procedures can be useful in the isolation of these so called unculturable strains and may thereby also increase the chances of isolating novel actinobacteria (Goodfellow & Williams, 1983; Hamaki et al., 2005).

The aim of this part of the study was to isolate novel actinobacteria from a soil sample collected from within the KRCA. The isolations were performed on general as well as specific isolation media in 97 the hope of isolating members of the rare genera, including the genus Amycolatopsis. Isolates were initially chosen based on gross colony morphology and were all screened for antimycobacterial activity (against the non-pathogenic M. aurum A+). Those exhibiting moderate to very strong inhibitory activity, as well as those that showed unusual colony morphologies, were identified to the genus level (or to a small group of genera) using the rapid molecular identification method of Cook & Meyers (2003). The nine isolates with the highest antimycobacterial activity were further screened for activity against representative Gram-positive and -negative bacteria in an attempt to determine the specificity of the produced compound(s).

2.3 Materials and methods 2.3.1 Sample collection A surface soil sample was collected by Mr Jerome Diedericks, theTown track manager at Kenilworth Racecourse, approximately 10m from the dirt service road (leading from the quarantine station) which is located in the lower left hand corner of the South Eastern quadrant of the KRCA, within the centre of the horse racing track. An aerial view of theCape racecourse is shown in Fig 2.3.1, with the approximate location of the sampling site indicatedof by the white arrow.

2.3.2 Isolation The collected soil sample was initially pre-treated with dry heat to reduce the number of vegetative bacteria present. The sample was ground with a mortar in a pestle before being heated in a 60°C oven for 1h in a sterile glass Petri dish. The sample was cooled to room temperature and approximately 1g of theUniversity treated soil was added to 10ml of sterile distilled water and agitated by vortexing for 1min. The soil was allowed to settle and the supernatant serially diluted to 10-4 in sterile distilled water, with 100µl of each dilution being spread onto each of the isolation plates in duplicate.

The media used for the isolations were: Czapek solution (CZ) agar (Atlas, 2004); Difco Middlebrook 7H9 agar supplemented with 10mM glucose (albumin-dextrose-catalase (ADC) supplement omitted) (Becton Dickinson); Modified Czapek solution (MC) agar (Nonomura & Ohara, 1971); Amycolatopsis selective media SM1, SM2 and SM3 (Tan et al., 2006); Soil extract (SE) agar (Hamaki et al., 2005) adjusted to pH 6, 7 or 8; and yeast extract-malt extract agar (ISP 2 or YEME) 98

(Shirling & Gottlieb, 1966). The soil extract used in the SE medium was prepared as described by Hamaki et al. (2005) using soil from the same location as that from which the isolation sample was obtained. The Amycolatopsis selective media were prepared as described, but without the inclusion of nystatin in SM1 and SM2 or nystatin and novobiocin in SM3. All isolation plates contained cycloheximide (50µg/ml) and nalidixic acid (10µg/ml) and were incubated at 30˚C. Plates were incubated for a total of 35 days with colonies being sub-cultured at regular intervals.

Town

Cape of

Figure 2.3.1 Aerial photograph of Kenilworth Racecourse. The KRCA constitutes the majority of the area located in the centre of and between the tracks as well as the area on the outside of the back straight leading into the first turn, located on the eastern corner of the property. The white arrow indicates the approximate location from which the soil sample used for the isolation of actinobacteria was obtained. The finish post is located in the vicinity of F; GS indicates the grand stand; KC indicated theUniversity Kenilworth Centre shopping complex adjacent to the racecourse; Q indicates the horse quarantine station. As a point of scale reference, the central straight leading to the finish post is approximately 30m wide, with the home straight (as you come round the turn to the finishing post) of the outermost track being 350m in length. Photo courtesy of Steve McCurrach.

Isolates were selected based on their colony morphology and sub-cultured using sterile toothpicks onto the same media (without antibiotics) from which they were isolated. Subcultured isolates were incubated at 30°C for 7 days. Isolates were named with a letter corresponding to the medium from which they were isolated and numbered chronologically as they were sub-cultured: C – CZ; H – 7H9; S1 – SM1; S2 – SM2; S3 – SM3; SE(6) – SE at pH 6; SE(7) – SE at pH 7; SE(8) – SE at pH 8; 99

M – MC; Y – YEME. Isolates were re-examined on the sub-cultured plates and, when necessary, were re-streaked to obtain pure cultures. Those isolates not appearing to be actinobacteria were discarded. Strains isolated from SE agar plates were transferred to YEME agar to allow for better growth and examination. All isolates were grown on YEME agar to allow a standardised morphological comparison. Gram stains were performed on isolates that could not be clearly identified as actinobacteria. All isolates were maintained on agar plates. Spore stocks were made by suspending 2 – 3 loopfuls of spores or cell mass (when no sporulation was noted) in 50% (v/v) sterile glycerol and stored at -20°C. Once the isolates had been grown in broth cultures, further glycerol broth stocks were made (containing 15% (v/v) glycerol) and stored at -70°C.

2.3.3 Screening for antimicrobial activity Antimicrobial activity was determined by performing standard agar overlays. Actinobacterial isolates were stab inoculated with sterile toothpicks onto 7H9 supplementedTown with 10mM glucose (ADC supplement omitted), MC, MC with glycerol as the carbon source (MC-gly) and YEME agar. Four isolates were inoculated per plate and the plates were incubated at 30°C for 9 days. All isolates were tested against M. aurum A+, with the top nine producers also being tested against E. coli ATCC 25922 and S. aureus ATCC 25923. The test bacteria Capewere grown in 10ml Luria-Bertani (LB) broth (Sambrook et al., 1989) incubated at 37°C overof night (approximately 18h) with shaking. Cultures were Gram stained to check for contamination and the optical density at 600nm (OD600) was determined using a Beckman DU-530 spectrophotometer. Each stab inoculated plate was overlaid with 6ml of sloppy LB agar (0.7% w/v agar) containing the predetermined volume of test bacterium. To ensure reproducibility, the volume of test bacterium added to each overlay was calculated such that OD600 × volume to be added (in µl) = 160 for M. aurum and S. aureus and 4 for E. coli. The determined volume wasUniversity added to molten sloppy LB agar at about 55°C, vortexed and poured onto the stab inoculated plate and swirled to cover the entire area of the plate up to the edge of the actinobacterial colonies. The agar was allowed to solidify, the plates inverted and incubated at 37°C for 48h for M. aurum and 24h for E. coli and S. aureus. The area of the zone of inhibition, in mm2, was calculated by first determining the total area of inhibition and subtracting from it the area of the actinobacterial colony. The level of activity was assessed as follows: <100mm2 – very weak; 100- 1000mm2 – weak; 1001-2000mm2 – moderate; 2001-3000mm2 – strong; >3000mm2 – very strong. Where necessary, strains were retested individually.

100

2.3.4 Preliminary identification 2.3.4.1 Genomic DNA extraction Isolates were inoculated into 10ml of YEME broth in 100ml Erlenmeyer flasks from either a spore stock or from a heavy loopful of spores or cell mass from a plate and incubated at 30°C with shaking until sufficient growth was noted (3-7 days). Gram stains were performed to check for contamination and cells were harvested by centrifugation. Genomic DNA was extracted as per the method of Wang et al. (1996), with modifications to the lysis buffer to increase the lysozyme concentration to 20mg/ml and to include Proteinase K (0.2mg/ml). The lysozyme digestion was performed overnight and the treatment with RNase A was also performed overnight. The DNA was redissolved in 50µl of 10mM Tris-HCl, 1mM EDTA (TE) buffer at pH 7.8, the concentration measured using a NanodropTM spectrophotometer (model ND-1000) and stored at 4°C.

2.3.4.2 16S rRNA gene amplification Town The 16S rRNA gene was amplified from the genomic DNA of isolates by the polymerase chain reaction (PCR). Reactions were performed in a Techne TC-512 thermal cycler in 50µl reaction volumes containing 2 or 4mM MgCl2, 150µM of eachCape dNTP, 0.5 µM of each primer, 0.5U Super- Therm Taq polymerase (JMR Holdings, USA) and 500ng of template DNA. The primers used were the universal bacterial primers F1 (5’-AGAGTTTGATCITGGCTCAG-3’)of and R5 (5’- ACGGITACCTTGTTACGACTT-3’) (I = inosine), which were adapted from primers fD1 and rP2, respectively (Weisburg et al., 1991). The PCR programme consisted of an initial denaturation at 96°C for 2min, followed by 30 cycles of denaturation at 96°C for 45s, annealing at 56-60°C for 30s and extension at 72°C for 2min, with a final extension at 72°C for 5min. The PCR products were electrophoresed alongsideUniversity a PstI digestion of λ DNA, serving as a molecular size marker, on 0.8% (w/v) agarose gels containing 0.8µg/ml ethidium bromide in 1 × TAE buffer (Sambrook et al., 1989) at 100V. Gels were visualised on a GelDoc XR System (BioRad).

2.3.4.3 Rapid molecular identification To allow identification of the genus or small group of genera to which the isolated actinobacteria belonged, the PCR amplified 16S rRNA genes were subjected to single restriction endonuclease digestions as per Cook & Meyers (2003). Initial digestion was performed with MboI and VspI (isoschizomers of Sau3AI and AsnI, respectively), with the subsequent digestions being performed as determined from the method of Cook & Meyers (2003). Digestions were performed in 20µl reaction 101 volumes containing 2U of the restriction endonuclease, 2µl of the appropriate buffer and 6-10µl of the 16S rRNA gene PCR product and incubated at 37°C over night. Reactions were stopped by the addition of 2µl of 6 × tracking dye (Sambrook et al., 1989) and the DNA was electrophoresed alongside an undigested 16S rRNA gene control and a λ-PstI size marker on 1.5% (w/v) agarose gels as described in section 2.3.4.2.

2.3.4.4 Amycolatopsis genus specific PCR Screening for the amplification of an Amycolatopsis specific 16S rRNA gene product was performed in 25µl reaction volumes containing 5% DMSO, 3mM MgCl2, 150µM of each dNTP, 0.5µM of each primer and 0.5U Super-Therm Taq polymerase (JMR Holdings, USA) (modified from Tan et al., 2006). The primers AMY2 (5’-GGTGTGGGCGACATCCACGTTGT-3’) and ATOP (5’- GTATCGCAGCCCTCTGTACCAGC-3’) amplify a product of 435nt in size (Tan et al., 2006). The PCR reactions were performed in a Techne TC-512 thermal cycler usingTown a protocol comprised of an initial denaturation at 95°C for 5min, followed by 25 cycles of denaturation at 95°C for 1min, annealing at 65°C for 1min and elongation at 72°C for 1min, with a final elongation step at 72°C for 10min (Tan et al., 2006). The PCR products were electrophoresed alongside a λ-PstI size marker on 1.2% (w/v) agarose gels as described in section 2.3.4.2Cape. of 2.3.5 Antibiotic extraction 2.3.5.1 PCR screening for antibiotic biosynthetic potential Strains were screened for the presence of biosynthetic genes involved in production of the core structures of ansamycin (3-amino-5-hydroxy-benzoic acid synthase gene), glycopeptide (oxyB gene) and Type-II (aromatic) Universitypolyketide (ketosynthase alpha and ketosynthase beta tandem gene pair) type antibiotics using the primer sets ANSA, Foxy/Roxy and ARO-PKS, respectively (Wood et al., 2007).

The PCR reactions were performed in 50µl reaction volumes containing 2mM MgCl2, 150µM of each dNTP, 0.5µM of each primer, 0.5U Super-Therm Taq polymerase (JMR Holdings, USA) and 500ng of template DNA. The PCR programme consisted of an initial denaturation step at 96°C for 2min, followed by 30 cycles of denaturation at 96°C for 45s, annealing at 56°C (ANSA primers), 60°C (Foxy/Roxy primers) or 64°C (ARO-PKS primers) for 30s and extension at 72°C for 2min, with a final extension at 72°C for 5min (Wood et al., 2007). A Techne TC-512 thermal cycler was used to perform the PCR reactions and the products were electrophoresed as described in section 2.3.4.2. 102

2.3.5.2 Determination of extraction solvent 2.3.5.2.1 Small scale solvent extraction Each antibiotic-producing strain was grown in 10ml of YEME broth in a 100ml Erlenmeyer flask at 30°C with shaking until sufficient growth was noticed (2-3 days). This culture was used as the seed culture to inoculate 100ml of YEME broth in a 1l Erlenmeyer flask and was incubated at 30°C for 7 days with shaking to allow production of the antibiotic compound(s). The culture was then filtered through a coffee filter (size 102, House of Coffees) to remove the cell mass. The culture filtrate was subsequently divided into four fractions of approximately 25ml each in sterile 100ml blue top bottles. One fraction was freeze dried to serve as the control to determine whether the antibiotic was produced in the culture. Equal volumes (25ml) of chloroform, ethyl acetate or hexane were added to each of the three remaining fractions of the culture filtrate, the mixtures were shaken vigorously for 10min, followed by agitation on an orbital shaker at 85rpm for 30min before being left to stand at 4°C overnight. The bottles were vigorously shaken again for 5minTown before being left to reach room temperature and for the solvent and aqueous layers to separate. The solvent layers were removed, placed in glass beakers and left to evaporate in a fume cupboard before being redissolved in the same solvent used for the extraction, such that the extracts were now approximately 50 times concentrated. The cell mass left in the coffee filter was dried by firstlyCape squeezing out as much broth as possible and subsequently blotting on paper towel to further removeof as much residual broth as possible. The filter was then torn open and allowed to air dry for 10min on more paper towel before the cell mass was removed and placed in a sterile bottle. The cell mass was then extracted with 10ml of methanol as described for the broth fractions, with the exception that centrifugation was used if the cells did not adequately separate from the solvent. All extracts were stored in Eppendorf tubes at -20°C. To determine the optimal solvent for extraction of each antibiotic and to determine whether the compound was locatedUniversity in the broth or retained in the cells, all solvent extracts were tested for antimycobacterial activity by spot test bioautography (Betina, 1973). To perform the spot tests, 5µl of each extract was spotted onto a silica TLC plate (Merck 1.05554.0001) that had been divided into a grid of 1.5cm by 1.5cm blocks and dried in a fume cupboard. Bioautography against M. aurum A+ was performed on the prepared TLC plate. Tests were repeated using 10µl of the extracts if weak or doubtful activity was initially recorded.

2.3.5.2.2 Bioautography A culture of the test bacterium (E. coli, M. aurum or S. aureus) was grown by inoculating 10ml of LB broth in a universal with a loopful of bacteria, vortexing to distribute the culture and incubating 103 at 37°C overnight with shaking. A Gram stain was performed to ensure the purity of the culture.

The OD600 of the culture was determined and subsequently diluted with sterile LB broth such that the

OD600 was 0.5. Sterile non-absorbent cotton wool was used to dab the diluted culture onto the prepared TLC plate, which was then incubated in a sealed plastic container containing moist paper towel for 24h at 37°C. After incubation, the plates were dabbed with a 0.25% solution of thiazolyl blue tetrazolium bromide (MTT) (Sigma; M2128) that was prepared in phosphate buffered saline

(1.78g Na2HPO4; 8.50g NaCl; 1l distilled water; pH 7.3) and incubated again at 37°C for 1-2h to allow the colour change to occur. MTT changes from yellow to blue in the presence of actively respiring cells (as a result of the reduction of the MTT to the insoluble formazan derivative). Images of the plates were digitally captured before fading of the colour on the TLC plate occurred.

2.3.5.3 Purification of antibacterial compounds 2.3.5.3.1 Large scale solvent extraction Town Once the optimal solvent of extraction was determined, cultures were grown and filtered as described before (section 2.3.5.2.1), with the exception that the entire volume of the culture filtrate was extracted with an equal volume (100ml) of the predetermined solvent, with the cell mass also being extracted with the same solvent. Spot test bioautographyCape against M. aurum A+ was performed to ensure that the compound had been produced andof effectively extracted before performing TLC to separate the active compound(s) from the other molecules.

2.3.5.3.2 Thin layer chromatography For TLC, 10µl of the sample or extract containing the active compound was spotted 1.5cm from the bottom of a silica TLC plate that was 10cm in length (width varied depending on the number of samples tested) and placedUniversity in a fume cupboard to allow the solvent to evaporate. The appropriate solvent system was placed in a glass beaker covered with aluminium foil (forming the TLC chamber) and left for 30min to allow saturation of the atmosphere with the solvent prior to performing the chromatography. Sufficient solvent was added so that at least 0.5cm of the TLC plate was immersed in the solvent system. Plates were placed in the chamber and allowed to develop until the solvent front was 1cm from the top of the TLC plate (30 – 45min). The plates were then removed and the solvent allowed to evaporate in a fume cupboard before bioautography was performed to determine the location of the active compound(s) (section 2.3.5.2.2).

104

2.3.5.3.3 Partial purification of compounds by column chromatography A silica gel column was prepared by packing a clean 10ml glass pipette with silica gel 60 (Merck; 1.07734.2500) that was suspended in the appropriate solvent system as determined by TLC. The column was washed with 30ml (three column volumes) of the solvent system before 500µl of the crude solvent extract was applied and run into the column. A thin layer of acid purified sand (BDH, BB330945E) was applied to the top of the packed silica to prevent the disruption of the silica bed upon the addition of more solvent to the column. An initial 10ml fraction was collected to contain the dead volume of the column, followed by 15 fractions of 2ml each and a final fraction of 10ml. All fractions were evaporated in a fume cupboard and redissolved in the original solvent of extraction to 25 times concentrated and tested for activity by performing spot test bioautography against M. aurum A+. Fractions shown to contain activity were tested for purity by performing TLC and dabbing the chromatogram with cerium (IV) ammonium sulphate (CAS) (63g of Ce(NH4)SO4 initially dissolved in 500ml of 1M H2SO4 and made up to a final volume of 1l with deionised water). The CAS-treated chromatogram was heated slowly at 110°C toTown reveal the number of organic compounds present (appearing as brown spots) to correlate with the bioautography results to reveal the location of the active compound(s). Cape of 2.4 Results

A total of 112 strains was initially sub-cultured from the isolation plates and re-examined for colony morphology typical of filamentous actinobacteria. The SE agar plates combined showed the highest number of isolates at 37 (17 from pH 6, 11 from pH 7 and 9 from pH 8), with YEME producing the next highest number of isolates at 27. 7H9 agar produced 18 isolates, while there were 16 strains isolated from SM3 agar,University 6 from MC agar and 4 each from SM1 and CZ agars. No strains were isolated from SM2 agar. The vast majority of the isolates were obtained from the undiluted sample (73), with less than half that amount coming from the 10-1 dilution (28) and even fewer from the 10-2 and 10-3 dilutions (8 and 3 respectively), while none were isolated from the 10-4 dilution.

Strains growing on the SE agar plates all appeared to be very similar, growing as sparse, feathery grey colonies that appeared to be only comprised of spores on the surface of the agar. These strains were therefore transferred to YEME agar plates to encourage more profuse growth and allow for their morphology to be more effectively examined. Similarly, all other isolates were also transferred 105 to YEME agar plates to allow more effective (and standardised) comparisons between the isolates. Strains that appeared to be non-actinobacteria (mucoid) were discarded, while others that did not appear hard, leathery or powdery (the broad morphological description of filamentous actinobacteria) were further examined by Gram staining to determine whether they were likely actinomycete strains. Strains that were most likely duplicates (marked by the exact same colony morphology and pigmentation) were also excluded from further study.

2.4.1 Isolated actinobacteria The examination of the colony morphology of all 112 isolates and Gram staining of selected strains allowed for the removal of close to half the total number of strains. All 64 of the presumptive filamentous actinobacteria isolated in this study are listed in Table 2.4.1 along with a brief colony description and details of the incubation time, medium and dilution they were isolated from. Town Based solely on their morphological appearance, 17 isolates were selected as interesting and were therefore earmarked for further study and preliminarily identified using a molecular identification method (Cook & Meyers, 2003). These isolates all had morphological features that are not commonly associated with the genus StreptomycesCape (fragmenting mycelia or absence of aerial mycelium), showed unusual colours (pink, orange)of or sparse growth, and are therefore more likely to belong to rare and less exploited genera.

2.4.2 Screening for antibiotic activity A total of 63 presumptive filamentous actinobacterial isolates were tested for antibacterial activity against M. aurum A+ onUniversity different media. Strain Y11 was selected as morphologically interesting, but was not screened for antimicrobial activity as it failed to grow from any of the prepared stock cultures. The results of the overlay experiments performed on 7H9 and YEME agar are shown in Table 2.4.2. All the strains that showed very strong activity (>3000mm2) against M. aurum are indicated in bold. Most strains produced no activity against M. aurum on MC or MC-gly agar and the results for these media are therefore not included in Table 2.4.2. The results for the strains that did show activity on these two media are shown in Table 2.4.3. 106

Table 2.4.1 Isolation details of presumptive filamentous actinobacterial isolates Isolation Day of Isolation Day of Strain$ Colony Description


Dilution Strain$ Colony Description


Dilution Medium Sub-culture Medium Sub-culture C2 CZ Pink smooth SM with white flaky AM 18 100 SE(6)16 SE pH 6 Grey to green powdery AM, yellow DP 21 100 H1 7H9 Dusty/dirty grey powdery AM 10 10-2 SE(7)1 SE pH 7 Light orange SM with white flaky AM 10 10-2 H2 7H9 Grey powdery AM 10 10-1 SE(7)2 SE pH 7 White to light grey AM 10 10-1 H3 7H9 Dark grey powdery AM 10 10-1 SE(7)3 SE pH 7 White SM with grey to brown AM 10 10-1 H7 7H9 White AM 10 100 SE(7)5 SE pH 7 Grey to green SM, no AM, brown DP 10 100 H10 7H9 Dark grey powdery AM with white patches 16 10-1 SE(7)7 SE pH 7 Cream SM, white to dark grey AM 10 100 H13 7H9 Brown to dark grey powdery AM 16 100 SE(7)8 SE pH 7 Light grey SM, white AM 10 100 H14 7H9 Greenish grey powdery AM 16 100 SE(8)1 SE pH 8 White SM, dark grey AM, SL 10 10-2 H17 7H9 Beige/cream SM, white AM 21 10-1 SE(8)3 SE pH 8 Dark brown SM, white AM, brown DP, SPT 10 100 H18 7H9 Beige SM, cream AM 21 100 SE(8)4 SE pH 8 Pale pink to colourless SM, lacking AM 10 100 S1.3 SM1 Cream to brown SM, white AM, brown DP, SPT 21 100 SE(8)6 SE pH 8 Cream to white SM, grey AM 18 100 S1.4 SM1 Cream SM, SPT 21 100 SE(8)7 SE pH 8Town Dark grey AM 18 100 S3.2 SM3 Cream SM, grey AM 7 10-1 SE(8)9 SE pH 8 White to cream SM, light grey AM 21 100 S3.3 SM3 Powdery grey AM 7 100 Y1 YEME White AM becoming grey on the edges 7 10-1 S3.4 SM3 Dull cream SM, white AM 7 100 Y2 YEME White to grey AM 7 10-1 S3.5 SM3 White powdery AM 7 100 Y3 YEME Grey AM 7 10-1 S3.6 SM3 Brown SM, white AM, brown DP, SPT 10 10-2 CapeY4 YEME Cream SM with wrinkly texture, lacking AM 7 100 S3.8 SM3 Colourless SM, white AM 10 100 Y5 YEME White to grey AM 7 100 S3.10 SM3 White SM, star shaped, showing very weak growth 16 10-1 of Y6 YEME Yellow to pink SM, lacking AM 7 100 S3.11 SM3 Yellowish to cream SM, white to brown AM 16 100 Y7 YEME White powdery AM 7 100 S3.15 SM3 Beige to yellow cream SM, white AM 21 10-2 Y8 YEME White flaky AM 7 100 SE(6)1 SE pH 6 Grey powdery AM becoming darker on the edges 10 10-1 Y9 YEME White AM becoming grey to green 7 100 SE(6)2 SE pH 6 Greenish grey SM, lacking AM 10 10-1 Y10 YEME Pale grey AM 7 100 SE(6)3 SE pH 6 Black SM, very hard colony texture 10 100 Y11 YEME Orange to pink SM, grey AM 10 10-3 SE(6)5 SE pH 6 White to brown AM, SL 10 100 Y12 YEME Pink to red SM, white AM 10 10-2 SE(6)6 SE pH 6 White to cream SM, grey AM 10 100 Y13 YEME Light orange SM, becoming darker on the edges 10 10-1 SE(6)7 SE pH 6 Cream SM, white AM 10 100 Y16 YEME Cream SM, white AM 10 100 SE(6)9 SE pH 6 Orange SM, white to grey AM University10 10 0 Y17 YEME Cream SM, white to grey AM 10 100 SE(6)11 SE pH 6 White SM, grey AM 10 100 Y21 YEME Light orange SM, becoming black on tips 16 100 SE(6)13 SE pH 6 Cream SM, white AM, shows very weak growth 16 10-1 Y22 YEME Orange SM, becoming black on tips 18 100 SE(6)14 SE pH 6 Cream SM, lacking AM 16 100 Y23 YEME Pale to medium grey AM 18 100 SE(6)15 SE pH 6 White SM with a crumbly texture 16 100 Y25 YEME Orange brown SM, becoming black and mucoid 21 10-3 $ Strains indicated in bold are those that were deemed to be interesting based on their colony morphology.


AM, aerial mycelium; DP, diffusible pigment; SL, secreting liquid from AM; SPT, colony holds its shape but has a soft, paste like texture; SM, substrate mycelium. 107

Table 2.4.2 Antimicrobial activity of presumptive filamentous actinobacterial isolates against M. aurum A+ on 7H9 agar and YEME agar Strain Medium AM$ Inhibition


Activity Strain Medium AM$ Inhibition


Activity Strain Medium AM$ Inhibition


Activity C2 7H9 + 0 NA SE(6)1 7H9 + 0 NA SE(8)6 7H9 + 0 NA YEME – 0 NA YEME – 1206 M YEME – 1582 M H1 7H9 + 0 NA SE(6)2 7H9 – 0 NA SE(8)7 7H9 + 0 NA YEME – 1786 M YEME – 864 W YEME – 1695 M H2 7H9 + 0 NA SE(6)3 7H9 + 0 NA SE(8)9 7H9 + 587 W YEME – 1868 M YEME + 0 NA YEME – 0 NA H3 7H9 + 0 NA SE(6)5 7H9 + 0 NA Y1 7H9 + 4220 VS YEME – 1441 M YEME + 3893 VS YEME + 3517 VS H7 7H9 + 0 NA SE(6)6 7H9 + 829 W Y2 7H9 + 3287 VS YEME – 2156 S YEME – 979 W YEME + 1143 M H10 7H9 + 0 NA SE(6)7 7H9 + 1713 M Y3 7H9 + 0 NA YEME – 1184 M YEME – 1306 M YEME + 1762 M H13 7H9 + 301 W SE(6)9 7H9 + 0 NA Y4 7H9 + 0 NA YEME + 1684 M YEME + 829 W YEME – 680 W H14 7H9 + 219 W SE(6)11 7H9 + 1884 Town M Y5 7H9 + 2731 S YEME + 1055 M YEME + 3325 VS YEME + 844 W H17 7H9 – 0 NA SE(6)13 7H9 + 0 NA Y6 7H9 + 0 NA YEME – 3266 VS YEME – 0 NA YEME – 596 W H18 7H9 + 0 NA SE(6)14 7H9 + 668 W Y7 7H9 + 668 W YEME – 1343 M YEME – 176 W YEME – 794 W S1.3 7H9 + 301 W SE(6)15 7H9 + Cape 59 VW Y8 7H9 + 1356 M YEME + 0 NA YEME + 250 W YEME + 922 W S1.4 7H9 + 0 NA SE(6)16 7H9 + 0 NA Y9 7H9 + 0 NA YEME + 0 NA YEME of + 0 NA YEME – 2884 S S3.2 7H9 + 0 NA SE(7)1 7H9 + 0 NA Y10 7H9 + 0 NA YEME + 3287 VS YEME + 0 NA YEME + 650 W S3.3 7H9 + 1582 M SE(7)2 7H9 + 0 NA Y12 7H9 – 13 VW YEME + 3517 VS YEME – 2508 S YEME – 190 W S3.4 7H9 + 3102 VS SE(7)3 7H9 + 3517 VS Y13 7H9 – 0 NA YEME + 2904 S YEME + 2135 S YEME – 0 NA S3.5 7H9 + 0 NA SE(7)5 7H9 + 234 W Y16 7H9 – 0 NA YEME + 3306 VS YEME – 0 NA YEME + 2176 S S3.6 7H9 + 0 NA SE(7)7 7H9 + 0 NA Y17 7H9 + 0 NA YEME + 0 NA University YEME – 0 NA YEME – 816 W S3.8 7H9 + 2712 S SE(7)8 7H9 + 0 NA Y21 7H9 – 0 NA YEME + 436 W YEME – 2423 S YEME – 125 W S3.10 7H9 + 1865 M SE(8)1 7H9 – 523 W Y22 7H9 – 0 NA YEME + 0 NA YEME + 1123 M YEME – 0 NA S3.11 7H9 + 0 NA SE(8)3 7H9 + 432 W Y23 7H9 + 0 NA YEME – 978 W YEME + 84 VW YEME + 1714 M S3.15 7H9 – 0 NA SE(8)4 7H9 + 330 W Y25 7H9 – 0 NA YEME – 0 NA YEME – 480 W YEME – 0 NA $ Production of aerial mycelium: +, produced; –, not produced.


Area of the zone of inhibition measured in mm2. Antibacterial activity: NA, no activity; VW, very weak; W, weak; M, moderate; S, strong; VS, very strong. All strains showing very strong activity are indicated in bold. 108

Table 2.4.3 Antimicrobial activity of presumptive filamentous actinobacterial isolates against M. aurum A+ on MC agar and MC-gly agar Strain Medium AM$ Inhibition


Activity Strain Medium AM$ Inhibition


Activity S1.3 MC + 100 W SE(6)11 MC + 1236 M MC-gly + 0 NA MC-gly + 1243 M S3.2 MC + 1217 M SE(7)3 MC + 1481 M MC-gly + 1070 M MC-gly + 1372 M S3.3 MC + 1205 M Y1 MC + 1469 M MC-gly + 1243 M MC-gly + 888 W S3.4 MC + 1633 M Y3 MC + 0 NA MC-gly + 2433 S MC-gly + 1356 M S3.5 MC + 1346 M Y7 MC + 0 NA MC-gly + 1236 M MC-gly + 536 W S3.6 MC + 0 NA Y8 MC + 0 NA MC-gly + 687 W MC-gly + 1481 M $ Production of aerial mycelium: +, produced; –, not produced.


Area of the zone of inhibition measured in mm2. Antibacterial activity: NA, no activity; W, weak; M, moderate; S, strong. Town

Table 2.4.4 Antimicrobial activity of presumptive filamentous actinobacterial isolates against E. coli and S. aureus. 7H9 MC MC-gly YEME Strain Test Organism AM$ Inhibition


Activity AM$ Inhibition


CapeActivity AM$ Inhibition


Activity AM$ Inhibition


Activity H17 E. coli + 0 NA – 0 NA – 0 NA – 0 NA S. aureus + 0 NA + 0 NA + 0 NA – 0 NA S3.2 E. coli + 0 NA + 0of NA + 0 NA + 0 NA S. aureus + 895 W + 0 NA + 699 W + 574 W S3.3 E. coli + 0 NA – 0 NA – 0 NA – 0 NA S. aureus – 2425 S – 1251 M – 1228 M – 1291 M S3.5 E. coli + 148 W + 0 NA + 100 W + 0 NA S. aureus + 668 W + 200 W + 7 VW + 3700 VS SE(6)5 E. coli + 0 NA – 0 NA – 0 NA + 0 NA S. aureus + 0 NA – 0 NA – 0 NA + 0 NA SE(6)11 E. coli + 0 NA + 0 NA + 0 NA + 0 NA S. aureus + 1105 M + 1010 M + 1249 M + 0 NA SE(7)3 E. coli + 0 University NA + 0 NA + 38 VW + 0 NA S. aureus + 953 W + 294 W + 699 W + 0 NA Y1 E. coli + 0 NA + 0 NA + 0 NA + 0 NA S. aureus + 1130 M + 146 W + 699 W – 695 W Y2 E. coli + 0 NA – 0 NA + 0 NA – 0 NA S. aureus + 0 NA – 0 NA + 0 NA + 0 NA $ Production of aerial mycelium: +, produced; –, not produced.


Area of the zone of inhibition measured in mm2. Antibacterial activity: NA, no activity; VW, very weak; W, weak; M, moderate; S, strong; VS, very strong. Strain showing very strong activity is indicated in bold. 109

In most cases the level of antimycobacterial activity that was recorded depended on the media on which the isolates were grown, often with activity being noted for only one of the media. A few strains did, however, show activity on multiple media, but the activity on one medium was often markedly higher than on the others. Only 11 strains (17.5%) showed no activity against M. aurum on any of the media tested and 19 strains (30%) showed only very weak or weak activity. Moderate activity was recorded for 16 strains (25.5%) on at least one of the media types, with strong and very strong activity being recorded for 7 and 10 strains, respectively (11% and 16%).

The nine strains that exhibited the strongest activity against M. aurum were screened for activity against E. coli and S. aureus (Table 2.4.4). These nine strains were chosen as candidates for antibiotic extraction and purification, as well as for preliminary identification to the genus level, along with 22 of the other isolates that showed moderate, strong or very strong antimycobacterial activity (Table 2.4.2). Strain S3.4, which showed very strong antimycobacterial activity, failed to grow for any subsequent antibiotic evaluations and could not be Town resurrected from stock cultures. Therefore no further work could be performed on this strain. Similarly, strain H14, which showed moderate activity against M. aurum, could not be grown from any of the stock cultures. Of the nine strains showing the greatest antimycobacterial activity,Cape three (H17, SE(6)5 and Y2) showed no activity against either E. coli or S. aureus (Tableof 2.4.4 ). Two strains (S3.5 and SE(7)3) showed weak activity on 7H9 or MC-gly agar and very weak activity on MC-gly agar against E. coli, with the remaining seven isolates showing no activity against E. coli on any of the tested media (Table 2.4.4). All but three strains showed activity, ranging from very weak to very strong, against S. aureus, with most showing activity on more than one media type. Despite this, it can be seen that one of the media types showed a markedly higher level of activity than the others (inhibition zones of double the size on the other media).University

2.4.3 Preliminary identification All but one of the isolates (H14) that exhibited moderate to very strong antibacterial activity and all those selected based on colony morphology were preliminarily identified to the genus level using the rapid molecular identification method of Cook & Meyers (2003). The proposed genus identity of each of the tested isolates is listed in Table 2.4.5, with those being found to be non-Streptomyces indicated in bold.

110

Table 2.4.5 Preliminary genus identity of filamentous actinobacterial isolates

Strain Activity$ Possible Genus Assignment Ref

Strain Activity$ Possible Genus Assignment Ref

Y1 VS (4220) Streptomyces or Sporichthya T1(4b) H10 M (1184) Streptomyces T1(5b) SE(6)5 VS (3893) Streptomyces or Sporichthya T1(4b) SE(8)1 M (1123) Streptomyces or Sporichthya T1(4b) S3.3 VS (3517) Streptomyces or Sporichthya T1(4b) C2 SBIM Gordonia, Nocardia or Skermania T1(6b) SE(7)3 VS (3517) Streptomyces or Sporichthya T1(4b) H13 SBIM Streptomyces or Sporichthya T1(4b) SE(6)11 VS (3325) Streptomyces or Sporichthya T1(4b) S1.3 SBIM Amycolatopsis, Pseudonocardia or T4(11b) S3.5 VS (3306) Streptomyces or Sporichthya T1(4b) Saccharopolyspora S3.2 VS (3287) Streptomyces or Sporichthya T1(4b) S1.4 SBIM Kribbella or Nocardioides T3(7a) Y2 VS (3287) Streptomyces T1(5b) S3.6 SBIM Amycolatopsis, Pseudonocardia or T4(11b) H17 VS (3266) Streptomyces or Sporichthya T1(4b) Saccharopolyspora S3.4 VS (3102) Streptomyces or Sporichthya T1(4b) S3.10 SBIM Streptomyces T1(5b) Y9 S (2884) Streptomyces or Sporichthya T1(4b) S3.11 SBIM Streptomyces T1(5b) Y5 S (2731) Streptomyces or Sporichthya T1(4b) S3.15 SBIM Streptomyces or Sporichthya T1(4b) S3.8 S (2712) Streptomyces T1(5b) SE(6)9 SBIM Streptomyces T1(5b) SE(7)2 S (2508) Streptomyces or Sporichthya T1(4b) SE(6)13 SBIM Streptomyces or Sporichthya T1(4b) SE(7)8 S (2423) Streptomyces or Sporichthya T1(4b) SE(7)1 SBIM Nocardia T4(4b) Y16 S (2175) Streptomyces T1(5b) SE(8)3 SBIM Amycolatopsis, Pseudonocardia or T4(11b) H7 S (2156) Streptomyces or Sporichthya T1(4b) Saccharopolyspora H2 M (1868) Streptomyces or Sporichthya T1(4b) Y11 SBIM Streptomyces or Sporichthya T1(4b) H1 M (1786) Streptomyces Y13 SBIM TownStreptomyces or Sporichthya T1(4b) Y3 M (1760) Streptomyces or Sporichthya T1(4b) Y21 SBIM Actinoplanes, Couchioplanes, T3(4b) SE(6)7 M (1713) Streptomyces T1(5b) Micromonospora, Pilimelia, Y23 M (1713) Streptomyces or Sporichthya T1(4b) Verrucosispora or Virgisporangium SE(8)7 M (1695) Streptomyces or Sporichthya T1(4b) Y22 SBIM Actinoplanes, Couchioplanes, T3(4b) SE(8)6 M (1583) Streptomyces T1(5b) Micromonospora, Pilimelia, Y8 M (1481) Streptomyces or Sporichthya T1(4b) Cape Verrucosispora or Virgisporangium H3 M (1441) Streptomyces T1(5b) Y25 SBIM Actinoplanes, Couchioplanes, T3(4b) H18 M (1343) Streptomyces T1(5b)of Micromonospora, Pilimelia, SE(6)1 M (1206) Streptomyces or Sporichthya T1(4b) Verrucosispora or Virgisporangium $ Level of antimycobacterial activity with the area of the largest inhibition zone in parentheses (mm2); M, moderate; S, strong; SBIM, selected based on interesting colony morphology; VS, very strong.
Reference to the table (T) and subsequent step (in parentheses) in that table that represents the terminal restriction digest allowing genus assignment as per the method of Cook & Meyers (2003). Non-Streptomyces isolates are indicated in bold.

All the isolates that were chosen based on antibiotic producing ability and close to half of those chosen based on colonyUniversity morphology (8 out of 17) were found to belong to the genus Streptomyces or to either the genus Streptomyces or Sporichthya. In cases of the latter situation, the strains can be assumed to belong to the genus Streptomyces based on their morphology being inconsistent with that of Sporichthya (which does not produce substrate mycelium) (Cook & Meyers, 2003). The other 9 of the 17 morphologically interesting isolates were found to belong to rarer genera of actinobacteria. One isolate was identified as belonging to the genus Nocardia, one as possibly belonging to Gordonia, Nocardia or Skermania; another to either the genus Kribbella or Nocardioides; three as belonging to one of six genera belonging to the family Micromonosporaceae and three as belonging to either Amycolatopsis, Pseudonocardia or Saccharopolyspora. The latter three isolates were each presumptively identified as belonging to the genus Amycolatopsis by virtue of the amplification of 111 the characteristic 435nt PCR product when screened with the Amycolatopsis genus specific 16S- rRNA gene PCR primers AMY2 and ATOP (Tan et al., 2006). All the isolates that were thought to be non-Streptomyces were selected for further analysis, while no further work was performed on the eight morphologically interesting isolates that appeared to belong to the genus Streptomyces.

2.4.4 Antibiotic extraction The nine Streptomyces isolates that were shown to have very strong antibacterial activity against M. aurum A+ were selected for antibiotic extraction and purification. The strains were also screened for the presence of the biosynthetic genes involved in the production of ansamycin, aromatic polyketide and glycopeptide type antibiotics. Positive amplification was obtained for the ARO-PKS primer set, which has been shown to amplify both the ketosynthase α-β gene pair as well as genes involved in the synthesis of spore pigments (Wood et al., 2007). Solvent extractions were performed on the broth and cell fractions of the cultures of the nine Streptomyces strainsTown to determine the optimal solvent for extraction as well as the location (in the broth or cell mass) of the antibacterial compound(s). The use of spot test bioautography against M. aurum A+ allowed for the identification of the solvent containing the active compound as illustrated in Fig 2.4.1 which shows the results for strains SE(6)5 and SE(6)11. The extract of strain SE(6)5Cape was by far the most effective of all the extractions performed as, after evaporation ofof the solvent used to extract the cell mass, large quantities of a yellow powder (assumed to be the active compound) were left behind. This was the only strain from which such a powder was noted after extraction.

Once the crude extracts of the antibacterial compounds were obtained, TLC was performed using solvent systems comprising of various pairwise combinations of different solvents in different ratios, in order to determine theUniversity optimal system that would allow adequate separation of the compounds present in the crude extract. Bioautography against M. aurum A+ was performed (on the developed TLC plates) to determine whether the solvent systems allowed separation of the active compound(s) and to determine their Rf values. Fig 2.4.2 shows the results from bioautography on the chromatograms of strains SE(6)5 and SE(6)11. The solvents that allowed for extraction of the antibacterial compounds from the cultures of the selected actinobacteria, the solvent systems that allowed adequate resolution of these compounds and the Rf values of each of the antimycobacterial compounds in the crude extracts are listed in Table 2.4.6.

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Figure 2.4.1 Spot test bioautography of the solvent extracts of Streptomyces cultures against the test bacterium M. aurum A+. A. Spot test of the small-scale solvent extractions of strain SE(6)5 to determine optimal solvent for extraction of activity. 1, methanol extract of the cell mass; 2, chloroform extract of the broth fraction; 3, ethyl acetate extract of the broth fraction; 4, hexane extract of the broth fraction. B. Spot test of the large scale solvent extraction of strain SE(6)5 with ethyl acetate. 1, extract of the broth fraction; 2, extract of the cell mass. C. Spot test of the small-scale solvent extractions of strain SE(6)11 to determine the optimal solvent for extraction of activity. 1, chloroform extract of broth fraction; 2, ethyl acetate extract of the broth fraction; 3, hexane extract of the brothTown fraction; 4, methanol extract of the cell mass. D. Spot test of the large scale solvent extraction of strain SE(6)11 with chloroform. 1, extract of the broth fraction; 2, extract of the cell mass.

In all cases, the active compounds were found to be locatedCape within the cells and only small amounts excreted into the culture broth. The majority of ofthe compounds were most effectively extracted with chloroform, with ethyl acetate proving most effective for two of the strains. Hexane did not effectively extract the compounds from any of the cultures tested, only weakly extracting the activity from one strain. To later allow for the purification of the active compound, the optimal Rf value (as determined by TLC) should be around 0.5, which will allow for the separation of the active compound from most of the unwanted compounds co-extracted during solvent extraction. Eight of the strains were subjectedUniversity to TLC and for seven of them the most active compounds were separated such that their Rf values were around 0.5, except for SE(6)5, for which the Rf value of the compound could not be lowered below 0.7 with the solvent systems that were tested. Despite multiple attempts, the active compound of S3.3 could not be moved from the origin. Similarly, active compounds from strains S3.2, S3.5, SE(6)11 and Y2 could not be moved from the origin. However, the most active compound from each of these strains was effectively resolved. In addition to the unresolved compound (at the origin) from strain SE(6)11, an additional three resolved compounds were detected, with the second strongest activity being noted from the compound running just below the most active compound (appearing as a “tail” from the most active spot). 113

Town

Figure 2.4.2 M. aurum bioautography of the thin layer chromatograms of the solvent extracts from actinobacterial strains. A. TLC of the ethyl acetate extract of the cell mass of strain SE(6)5 using the solvent system comprising 100% isopropanol. The arrowhead indicates the active spot with the correspondingCape R value being indicated alongside. The f line marked as Or indicates the origin, while the line marked SF shows the solvent front. B. TLC of the chloroform extract of the cell mass from strain SE(6)11 using the solventof system comprising of chloroform:acetone (80:20) (v/v). The arrowheads indicate the active spots with their corresponding Rf values being indicated alongside. The line marked as Or indicates the origin, while the line marked SF shows the solvent front.

The solvent systems that were determined by TLC bioautography to separate the compounds were used as the mobile phase on silica columns to attempt to partially purify the active compounds for further analysis. The identification of the fraction(s) that contained the active compound was achieved by spot test bioautographyUniversity against M. aurum. Column chromatography was performed on six of the top antibiotic producing strains (H17, S3.2, SE(6)5, SE(6)11, SE(7)3 and Y2). Only one fraction collected from the column purification of one of the strains (SE(6)11) was ever found to contain activity, despite at least two attempted column purifications of the active compound from each of the six strains. The initial 10ml fraction collected from the column of strain SE(6)11 was found to contain activity, with none of the other collected fractions showing any activity. Upon repeating and collecting 2ml fractions from the start of the run, the activity was found to be present in the fourth 2ml fraction, again with no activity being detected in any of the other 30 collected fractions. Furthermore, even when twenty fractions of 10ml were collected, only the initial fraction was found to contain any activity. 114

Table 2.4.6 Summary of the antibiotic extraction information from the top antibiotic producing actinobacterial strains Fraction No of Extraction Solvent System Resolving R value(s) of Active Strain Containing Compounds f Solvent$ Compound Compound(s)


Activity Detected H17 Cell mass Chloroform Chloroform:Ethyl Acetate (80:20) 1 0.4 Ethyl Acetate (w) S3.2 Cell mass Chloroform Chloroform:Ethyl Acetate (70:30) 2 0.545 0.0 S3.3 Cell mass Chloroform Not resolved ND ND S3.5 Cell mass Chloroform Chloroform:Ethyl Acetate (80:20) 2 0.48 0.0 SE(6)5 Cell mass Ethyl Acetate Isopropanol (100%) 1 0.7 Broth (w)

SE(6)11 Cell mass Chloroform Chloroform:Acetone (80:20) 4 0.56 Ethyl Acetate (w) 04 Hexane (w) 0.9 0.0

SE(7)3 Cell mass Chloroform Chloroform:Ethyl Acetate (80:20) 2 0.44 0.1 Y1 Cell mass Chloroform ND ND ND Y2 Cell mass Ethyl Acetate Chloroform:Ethyl Acetate (80:20)Town 2 0.41 Chloroform (w) 0.0

$


The first listed solvent was used for the extraction; The Rf values are listed in order of decreasing activity as measured by the size of the active spot. ND, not determined; w, weak activity as assessed by bioautography. Cape

The purity of the active fraction collected for SE(6)11of was assessed by TLC using bioautography and CAS staining (Fig 2.4.3). As can be seen, the fraction apparently only contained one compound and can therefore be said to be moderately pure. Unfortunately the partially-purified active compound appeared to be only one of the weakly active compounds produced by strain SE(6)11 and the most active compound (with an Rf of 0.56 in Fig 2.4.2 B) could not be eluted from the column. Bioautography performedUniversity with S. aureus and E. coli revealed that this compound had activity against S. aureus, but not against E. coli. TLC bioautography of the crude extract of SE(6)11 against these two test organisms further revealed that no activity was detected against E. coli, while only the compounds with Rf values of 0.9 and 0.0 had activity against S. aureus. Time did not permit any further work on the purified compound.

115

Town

Figure 2.4.3 Thin layer chromatograms of the active column fraction collected from strain SE(6)11. A. Bioautography of the TLC plate against M. aurum. 1, column fraction; 2, chloroformCape extract of the cell mass (crude extract). The arrowheads indicate the active compounds with their corresponding Rf values being indicated alongside. The line marked Or indicates the origin, while the line SF shows the solvent front. B. CAS staining of the TLC plate. 1, column fraction; 2 chloroform extract of the cell mass (crude extract).of The arrowheads indicate the organic compounds with their corresponding Rf values being indicated alongside. The line marked Or indicates the origin, while the line SF shows the solvent front.

2.5 Discussion The aim of this part University of the study was to isolate filamentous actinobacteria (preferably non- streptomycetes) from soil, to screen these strains for antimicrobial activity and attempt to partially purify the active compounds. The 64 presumptive filamentous actinobacteria that were isolated were distributed across most of the isolation media that were used in the study, with MC and SM2 agar being the only media from which no actinobacterial strains were isolated. The use of selective media was very effective, with large numbers of strains being isolated on the SE agars as well as on SM3 agar. Altogether the selective media accounted for more than half of the isolated actinobacteria. As expected, the conventional isolation media proved to be successful, with 29 strains being isolated altogether from 7H9, CZ and YEME. The majority of the actinobacteria that were identified in this 116 study were found to belong to the genus Streptomyces (38 of 47 strains – 81%) by the rapid molecular identification method of Cook and Meyers (2003).

Medium SM1 showed the greatest selectivity for non-streptomycetes, with both actinobacterial strains isolated from it being found to belong to rarer genera, one of which was shown to belong to the genus Amycolatopsis (for which the medium was designed to select). Similarly, the only actinobacterial strain isolated from CZ agar was found to belong to one of the genera Gordonia, Nocardia or Skermania. The soil extract agars were the source of two rare genera, Amycolatopsis and Nocardia. A third Amycolatopsis strain was isolated from SM3 agar and was the only non- streptomycete found on this medium type. Three of the strains isolated from YEME were identified to belong to one of six of the genera within the family Micromonosporaceae. The finding that the majority of the isolates belonged to the genus Streptomyces is not surprising, since it is known that streptomycetes are one of the easiest groups to isolate from soil and are thought to be the most abundant actinobacteria present in terrestrial habitats. FurthermoreTown it should be noted that the so-called selective media were in fact not that selective, allowing the growth of many of the non-targeted genera. Cape Unfortunately it appears that relatively low numbersof of the rare filamentous actinobacterial genera were isolated from the collected sample, accounting for only 14% of the total strains. However, when only the strains selected based on interesting morphology are considered, this proportion increases significantly to 50%. Possible explanations as to why so few of the rare genera were isolated could be found in the actual isolation procedures or the media themselves, not being optimal or ideal for the isolation of these genera but targeted for the isolation of Streptomyces strains. On the other hand, this lack of Universityrare genera could simply be due to the fact that there are none of these genera present in this particular soil sample. An obvious solution to the former would be to use alternative pretreatment methods or to use an untreated sample, to allow the full isolation potential of the soil sample to be realised. Furthermore, the use of morhological criteria seems to be useful and therefore could be applied when initially selecting strains from the isolation plates to increase the relative proportion of the rare genera.

When looking for novel antibiotic compounds, it would obviously be best to screen for activity against the actual pathogen against which the antibiotics will be used (Peláez, 2006). In the case of the search for antitubercular antibiotics, however, it is not feasible to routinely screen all strains for 117 activity against M. tuberculosis, due to its very slow growth rate and pathogenic nature. For these reasons the fast growing, non-pathogenic M. aurum A+, which has been reported to have a similar antibiotic susceptibility profile to that of M. tuberculosis (Chung et al., 1995) was used as a substitute test organism in screening for antimycobacterial compounds.

The overlay experiments showed that 81% of the strains exhibited at least some antimicrobial activity against M. aurum A+, with over 50% of strains showing moderate to very strong activity. All of the strains that produced zones of inhibition of more than 1000mm2 against M. aurum were identified to belong to the genus Streptomyces, which is not surprising considering members of this genus are the most well known antibiotic producers of all the actinobacterial genera. Although three strains were shown to belong to the genus Amycolatopsis, which is known to contain many antibiotic producing strains (Lazzarini et al., 2000; Wink et al., 2003; Tan et al., 2006), only weak activity was recorded for these strains (inhibition zones of 301, 437 and 687mm2) against M. aurum A+. Similarly, of the three strains belonging to the family MicromonosporaceaeTown, only one (Y21) was shown to have weak antimycobacterial activity (125mm2) despite members of this family (most notably the genus Micromonospora) being the second most prolific producers of antibiotics after the streptomycetes (Lazzarini et al., 2000). It should be Capenoted however that the lack of activity against the M. aurum A+ does not mean that the strains ofdo not produces antibiotics, but simply none that are active against this organism.

Most of the antimicrobial activity that was recorded was from isolates that had been grown on YEME agar, with far fewer of those grown on 7H9 agar showing activity (Table 2.4.2). When grown on MC and MC-gly agar, the majority of isolates did not produce much activity. However, of the two media, MC-glyUniversity supported slightly better antibiotic production, marked by larger zones of inhibition on this medium for seven strains compared to that on MC agar, on which five showed larger zones (Table 2.4.3). This being said, only two strains showed higher antibiotic activity on MC-gly agar than any other test medium (with strain S3.6 only showing activity on this medium) and none showed higher activity on MC agar. Furthermore, the antimicrobial activity was usually limited to one media type, with some strains producing very strong activity on one medium, but no activity on any of the others. There were some strains that produced activity on multiple media types, however one always produced higher activity than the others and often resulted in zones of inhibition double the size of the next best medium.

118

The recording of the majority of the antimycobacterial activity on YEME agar was somewhat surprising, considering the richness of this medium and the fact that many secondary metabolites are often only produced in response to starvation conditions (Martin & Demain, 1980; Tormo et al., 2003). A possible explanation for this could be that the strains, which generally grew very well on this medium, had exhausted all of the nutrients (carbon and nitrogen sources) before the end of the incubation period and, owing to the presence of more cell mass, produced higher levels of antimicrobial compounds and therefore showed higher activity as well. Furthermore, YEME contains no added phosphate and therefore also avoids the potential problem of phosphate inhibition of antibiotic production. The growth of strains in nutrient poor or nutrient limiting media or in media using carbon sources other than glucose, have been shown to improve the production of secondary metabolites (Tormo et al., 2003), with the inhibition of antibiotic production by many Streptomyces species being attributed to catabolite repression by glucose as well as the presence of extracellular phosphate (Hurley & Bialek, 1974; Martin & Demain, 1980). This is somewhat substantiated by the findings in this study, where some isolates (13 strains, 25% of producers)Town produced the highest level of activity on 7H9 agar (which contains limited levels of carbon and nitrogen) and that in most cases the activity on MC-gly agar (containing glycerol as the carbon source) was slightly higher than that noted on standard MC agar, which contains glucose asCape the carbon source. However the number of strains showing stronger activity on these nutrientof limiting media were miniscule in comparison with those noted for the rich medium YEME agar (37 strains, 71% of producers), with only two strains (S3.6 and Y8, 4% of producers) showing higher activity on the MC agars (more specifically MC-gly) as compared to YEME agar (Tables 2.4.2 and 2.4.3).

To try and determine the specificity of the antibacterial compounds produced by the top nine anti-M. aurum actinobacteria, theyUniversity were screened for activity against E. coli, as a representative Gram negative bacterium and S. aureus, as a representative Gram positive bacterium. Although these two bacteria were used here as a guide for specificity, the compounds produced may in fact be able to inhibit a wide range of other bacteria and therefore cannot be said to be specific based solely on these findings. Three strains (H17, SE(6)3 and Y2) were shown to have no activity against either of these test bacteria on any of the four media tested, which would suggest that the compounds they produce are potentially specific to mycobacteria and therefore worthy of further study. Four isolates (S3.2, S3.3, SE(6)11 and Y1) were found to only inhibit M. aurum and S. aureus (with the activities ranging from weak to strong) indicating that the compounds they produce may act specifically on Gram positive bacteria. Two strains (S3.5 and SE(7)3) were shown to be able to inhibit both E. coli 119 and S. aureus (but with the former being only weakly inhibited and much stronger inhibition being seen for the latter).

Interestingly, strains SE(6)11 and SE(7)3 showed no activity against S. aureus on YEME agar despite showing moderate and weak activity, respectively, on all other media types against this test bacterium. Furthermore, the activity against E. coli that was shown by strain SE(7)3 was only present when grown on MC-gly agar (with SE(6)11 being unable to inhibit E. coli on any medium). These findings suggest that different compounds are being produced on the different media and that there are compounds being produced by these strains on YEME agar that act against mycobacteria. An alternative explanation could be that YEME agar allows for the production of additional molecules that act in synergy with other molecules, thereby causing them to become specifically active against mycobacteria. Whatever the explanation, these findings certainly make these two strains worthy of further examination. Town Screening of the top nine antimicrobial producers for the presence of antibiotic biosynthetic genes involved in the synthesis of the core structures of different antibiotic classes, revealed only the presence of the ketosynthase α and ketosynthase β geneCape segment. These genes are required for the production of aromatic polyketide antibiotics. of This, however, does not mean that these strains produce these molecules as they may lack the genes required for the further processing of the molecules to produce the final antibiotic. The lack of amplification of the biosynthetic genes involved in the production of the other classes of antibiotics does not mean they do not produce that antibiotic either, as the primers may just not have been able to bind effectively to the target gene in that strain (Wood et al., 2007). The use of PCR screening may therefore underestimate the antibiotic producing ability simplyUniversity due to the wide range of genetic diversity that is present within the genes involved in the production of the antibiotics (Ayuso et al., 2005). It is therefore best to combine the PCR screening with the culture based techniques of antibiotic screening.

Despite active compounds being effectively extracted from all of the tested actinobacterial strains, not all of these compounds could be effectively resolved under the tested conditions. However, adequate separation was achieved for most of the extracts that were subjected to TLC. It was disappointing that none of the most active compounds could be purified by silica column chromatography, with only a weakly active compound from strain SE(6)11 being isolated from the column. This compound was also shown to be active against the Gram positive test organism S. 120 aureus. Although the collected fraction from SE(6)11 seemed to be pure, as only one spot was noted by CAS staining, the fraction may in fact contain other compounds not oxidised by the CAS. For this reason the fractions that were “purified” would need to be further screened to confirm their purity. The same can be said for all the active spots that were seen on all of the TLC bioautograms from all the extracts, however for the initial partial purifications that were attempted in this study, it was assumed that only one compound was present in each active spot.

In spite of the TLC experiments which showed that the active compounds could be separated using various solvents, silica gel column chromatography performed under the same conditions as the TLC experiments failed to elute the most active compounds, which could therefore not be purified. The reason for this failure of the column chromatography despite the success of the TLC is unknown. A possible explanation could be that the compounds degraded or lost activity while on the column or during the concentration steps. However, the compounds that were stored at -20°C, as well as a sample that was left at room temperature for the duration of the columnTown purification experiments (2-5 days) were still active. A possible solution to the problem would be to try different methods for the purification of the compounds (e.g. HPLC), or even a combination of different techniques. If all else fails, TLC could be performed and the active spot ofCape interest scraped off the TLC plate and eluted from the silica. However, this would be labourof intensive and somewhat impractical to obtain the quantities of the sample that would be required for further analysis.

Although the source of the soil sample for the isolation of filamentous actinobacteria was unique, in that it has never before been screened for actinobacteria and it comes from an area of high biodiversity, the vast majority of the strains that were isolated were found to belong to the genus Streptomyces, with onlyUniversity a small number belonging to the “rarer” and less often isolated genera. However, the Streptomyces strains may still prove to be unique, as despite being so commonly isolated, they do show a high level of biodiversity – as testified by the fact that there are over 500 known species. While novelty of strains is best when looking for novel antibiotics and non- Streptomyces strains have a higher likelihood of being novel (simply because they are less commonly isolated), the streptomycetes can still be an excellent source of antibiotics, with it being estimated that only about 3% of all the antimicrobials that can potentially be produced by the genus having been reported (Watve et al., 2001).

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2.6 References

Atlas, R. M. (2004). Handbook of Microbiological Media (3rd edition). Boca Raton, Fl: CRC Press.

Ayuso, A., Clark, D., González, I., Salazar, O., Anderson, A. & Genilloud, O. (2005). A novel actinomycete strain de-replication approach based on the polyketide synthase and nonribosomal peptide synthetase biosynthetic pathways. Appl Microbiol Biotechnol 67, 795-806.

Baard, E. H. W. & de Villiers, A. L. (2000). State of biodiversity: Western Cape Province, South Africa. Amphibians and reptiles. Western Cape State of Biodiversity 2000. (http://hdl.handle.net/1834/709)

Betina, V. (1973). Bioautography in paper and thin-layer chromatography and its scope in the antibiotic field. J Chromatogr 78, 41-51.

Branch, M & Jennings, G. (2008). City of Cape Town Nature Reserves: A network of amazing urban biodiversity. Cape Town, South Africa: City of Cape Town Environmental Resource Management Department. (Booklet available from www.capetown.gov.za/environment)

Busti, E., Monciardini, P., Cavaletti, L., Bamonte, R., Lazzarini, A., Sosio, M. & Donadio, S. (2006). Antibiotic- producing ability by representatives of a newly discovered lineage of actinomycetes. Microbiol 152, 675-683.

Chung, G. A. C., Aktar, Z., Jackson, S. & Duncan, K. (1995). High-throughput screen for detecting antimycobacterial agents. Antimicrob Agents Chemother 39, 2235-2238. Town

Cook, A. E. & Meyers, P. R. (2003). Rapid identification of filamentous actinomycetes to the genus level using genus- specific 16S rRNA gene restriction fragment patterns. Int J Syst Evol Microbiol 53, 1907-1915.

Goodfellow, M. & Williams, S. T. (1983). Ecology of actinomycetes. Ann Rev Microbiol 37, 189-216. Cape Hamaki, T., Suzuki, M., Fudou, R., Jojima, Y., Kajiura, T., Tabuchi, A., Sen, K. & Shibai, H. (2005). Isolation of novel bacteria and actinomycetes using soil-extract agar medium. J Biosci Bioeng 5, 485-492. of Hitchcock, A. (2005). Restoration Conservation at Kirstenbosch National Botanical Gardens. Poster presented at the first Global Partnership for Plant Conservation (October 2005). Accessed online November 2009. www.botanicgardens.ie/gspc/gppc/posters/kenilworth.htm

Hurley, L. H. & Bialek, D. (1974). Regulation of antibiotic production: catabolite inhibition and the dualistic effect of glucose on indolmycin production. J Antibiot (Tokyo) 27, 49-56.

Knight, V., Sanglier, J.-J., DiTullio, D., Braccili, S., Bonner, P., Waters, J., Hughes, D. & Zhang, L. (2003). Diversifying microbial natural products for drug discovery. Appl Microbiol Biotechnol 62, 446-458. University KRCA – Kenilworth Racecourse Conservation Area online. (2009). Accessed November 2009. www.krca.co.za

Lam, K. S. (2006). Discovery of novel metabolites from marine actinomycetes. Curr Opin Microbiol 9, 1-7.

Lam, K. S. (2007). New aspects of natural products in drug discovery. Trends Microbiol 15, 279-289.

Lazzarini, A., Cavaletti, L., Toppo, G. & Marinelli, F. (2000). Rare genera of actinomycetes as potential producers of new antibiotics. Antonie van Leeuwenhoek 78, 399-405.

Maneveldt, G. W. (2009). UWC’s enviro-facts guide to fynbos. Accessed November 2009. www.botany.uwc.ac.za/envfacts/fynbos

Manning, J. (2003). Photographic guide to the Wildflowers of South Africa. Pretoria, South Africa: Briza Publications.

Martin, J. F. & Demain, A. L. (1980). Control of antibiotic biosynthesis. Microbiol Rev 44, 230-251.

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Nonomura, H. & Ohara, Y. (1971). Distribution of actinomycetes in soil. VIII. Green spore group of Microtetraspora, its preferential isolation and taxonomic characteristics. J Ferment Technol 49, 1-7.

Peláez, F. (2006). The historical delivery of antibiotics from microbial natural products - Can history repeat? Biochem Pharmacol 71, 981-990.

Sambrook, J., Fritsch, E. F. & Maniatis, T. (1989). In Molecular Cloning, a laboratory manual, second edition. Cold Spring Harbor: Cold Spring Harbor Laboratory Press.

Shirling, E. B. & Gottlieb, D. (1966). Methods for characterization of Streptomyces species. Int J Syst Bacteriol 16, 313-340.

Tan, G. Y. A., Ward, A. C. & Goodfellow, M. (2006). Exploration of Amycolatopsis diversity in soil using genus- specific primers and novel selective media. Syst Appl Microbiol 29:7, 557-569.

Thomson, C. J., Power, E., Ruebsamen-Waigmann, H. & Labischinski, H. (2004). Antibacterial research and development in the 21st Century – an industry perspective of the challenges. Curr Opin Microbiol 7, 445-450.

Tormo, J.R., Garcίa, J.B., DeAntonio, M., Feliz, J., Mira, A., Dίez, M.T., Hernández, P. & Peláez, F. (2003). A method for the selection of production media for actinomycete strains based on their metabolite HPLC profiles. J Ind Microbiol Biotechnol 30, 582-588.

Turner, R. (2006). The Golden Oval: The Kenilworth Racecourse, a valuable lowland vegetation remnant. Veld & Flora 92, 140-150. Town

Wang, Y., Zhang, Z. & Ruan, J. (1996). A proposal to transfer Microbispora bispora (Lechevalier 1965) to a new genus, Thermobispora gen. nov., as Thermobispora bispora comb. nov. Int J Syst Bacteriol 46, 933-938.

Watve, M. G., Tickoo, R., Jog, M. M. & Bhole, B. D. (2001). How many antibiotics are produced by the genus Streptomyces? Arch Microbiol 176, 386-390. Cape

Weisburg, W. G., Barns, S. M., Pelletier, D. A. & Lane, D. J. (1991). 16S ribosomal DNA amplification for phylogenetic study. J Bacteriol 173, 697-703. of

Wink, J., Kroppenstedt, R. M., Ganguli, B. M., Nadkarni, S. R., Schumann, P., Seibert, G. & Stackenbrandt, E. (2003). Three new antibiotic producing species of the genus Amycolatopsis, Amycolatopsis balhimycina sp. nov., A. tolypomycina sp. nov., A. vancoresmycina sp. nov., and description of Amycolatopsis keratiniphila subsp. keratiniphila subsp. nov. and A. keratiniphila subsp. nogabecina subsp. nov. Syst Appl Microbiol 26, 38-46.

Wood, S. A., Kirby, B. M., Goodwin, C. M., Le Roes, M. & Meyers, P. R. (2007). PCR screening reveals unexpected antibiotic biosynthetic potential in Amycolatopsis sp. strain UM16. J Appl Microbiol 102, 245-253.

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IDENTIFICATION AND CHARACTERISATIONTown OF ISOLATED ACTINOBACTERIA

Cape of

University

The description of Kribbella hippodromi has been published in the International Journal of Systematic and Evolutionary Microbiology – Everest, G. J. & Meyers, P. R. (2008). Kribbella hippodromi sp. nov., isolated from soil from a racecourse in South Africa. Int J Syst Evol Microbiol 58, 443-446. 124

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Contents

3.1 Summary 126 3.2 Introduction 127 3.3 Materials and methods 128 3.3.1 Genotypic characterisation 128 3.3.1.1 16S rRNA gene amplification, sequencing and genus level identification 128 3.3.1.2 gyrB Amplification and sequencing 128 3.3.1.3 Phylogenetic analysis 129 3.3.2 Chemotaxonomic characterisation 130 3.3.3 Phenotypic characterisation Town 131 3.3.3.1 Morphological characterisation 131 3.3.3.1.1 Colony morphology and pigmentation 131 3.3.3.1.2 Scanning electron microscopy 131 3.3.3.2 Physiological characterisation Cape 131 3.3.3.3 DNA-DNA hybridisation of 133 3.4 Results 133 3.4.1 Genus determination 133 3.4.2 Characterisation of actinobacterial isolates 134 3.4.2.1 Isolates belonging to the genus Amycolatopsis 134 3.4.2.2 Isolate belonging to the genus Kribbella 141 3.4.2.3 IsolatesUniversity belonging to the genus Micromonospora 145 3.4.2.4 Isolates belonging to the genus Nocardia 150 3.4.2.5 Isolates belonging to the genus Streptomyces 157 3.4.2.6 Isolate belonging to the genus Verrucosispora 164 3.5 Discussion 167 3.6 References 171

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3.1 Summary

The genera to which the top nine antibiotic producing strains belong, as well as the genera to which the strains identified as non-Streptomyces by the rapid molecular identification method belong, were definitively determined by BLAST analysis of their 16S rRNA gene sequences. The closest relatives were determined by 16S rRNA gene and gyrB gene based phylogenetic analyses. All strains were subjected to physiological characterisation to allow them to be differentiated from the most closely related type strains with validly-published names. Three strainsTown belonging to the genus Amycolatopsis were shown to be distinct from all closely related type species by gyrB sequence analysis, with DDH and physiological differences confirming this. The single Kribbella isolate was shown to be distinct by DDH. Two strains belonging to the genus Micromonospora showed a high level of similarity to each other and could not be differentiated.Cape However, they showed a high number of physiological differences to theof closely related type strain Micromonospora olivasterospora and are likely to be distinct from this species. Two isolated Nocardia strains seem likely to represent novel species, showing multiple physiological differences from their respective relatives (‘Nocardia rhamnosiphila’, Nocardia flavorosea, Nocardia carnea, Nocardia sienata, Nocardia testacea, Nocardia fluminea, Nocardia cummidelens, Nocardia salmonicida and Nocardia soli), but DDH will be required to determine if they are new species. The nine antibiotic producing Streptomyces isolates wereUniversity only subjected to basic physiological comparisons. Six of these strains may belong to the same new species. The single Verrucosispora strain showed physiological differences from its closest relative, Verrucosispora gifhornensis, but DDH will be needed to distinguish between these strains.

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3.2 Introduction

The main focus of Chapter 2 was the isolation of filamentous actinomycetes from soil and screening them for antimicrobial activity against M. aurum A+, with the ultimate goal of identifying possible new antibiotics for the treatment of TB. Owing to the wide biodiversity of plant and animal species that can be found at the source from which the soil sample was obtained, it might be expected that a high level of diversity and novelty would be reflected at the microbial level and that rare and novel strains of actinomycetes might be isolated. The chances of isolating novel strains are thought to be increased if the source of the isolation is unexploited and contains a high level of biodiversity (Knight et al., 2003). The isolation of members of the less exploited actinobacterial genera will further increase the chances of isolating novel strains and with them novel antimicrobial compounds (Lazzarini et al., 2000). Hence the isolation of non-Streptomyces strains was favoured.

This chapter describes the identification and phenotypic Town characterisation of interesting actinobacterial isolates to determine if they belong to novel species. In order to allow a robust assessment of the characteristics of the actinobacterial strains, a polyphasic characterisation approach, making use of multiple different taxonomicCape positions, should be applied (Busse et al., 1996; Ludwig, 2007). Genotypic characterisation of the strains allows for a definitive genus level assignment to be made as well as for the closestof relatives to be identified, with the use of chemotaxonomic characters confirming the genus assignment and potentially being useful in the differentiation of the strain from related organisms. The physiological characteristics can then be used in combination to get a clearer idea of how similar or different the strains are from known species and of whether the strains represent potentially novel species. Ultimately DDH experiments may be needed to determine the species status of an isolate. Two strains sharing less than 70% DNA relatedness by DDH areUniversity considered to belong to separate genomic species as long as they are phenotypically different (Wayne et al., 1987).

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3.3 Materials and methods 3.3.1 Genotypic characterisation 3.3.1.1 16S rRNA gene amplification, sequencing and genus level identification The 16S rRNA gene was amplified by PCR as detailed in section 2.3.4.2. The amplified products were purified with either a Cleanmix kit (TA050CLN; Talent, Italy) or MSB® Spin PCRapace kit (Invitek, Germany) and quantified using a NanoDropTM spectrophotometer. PCR products were sequenced by dye termination reaction using the primers F1, F3, F5, R1, R3 and R5 (Table 3.3.1) to obtain nearly the full length of the 16S rRNA gene. Sequencing was performed as a service by GeneCare Genetics (Pty) Ltd (South Africa) and Macrogen (Seoul, South Korea). Sequence chromatograms were edited in Chromas version 2.01 (Technelysium) and the sequences assembled in DNAMAN version 5.2.9 (Lynnon BioSoft), with at least two overlapping sequences being used to confirm each sequence. Town Table 3.3.1 Primers used to sequence the 16S rRNA gene Primer Binding Position$ Primer Sequence


F1 8-27 5’-AGAGTTTGATCITGGCTCAG-3’ F3 517-536 5’-GCCAGCAGCCGCGGTAATAC-3’Cape F5 1053-1074 5’-GCATGGITGTCGTCAGCTCGTG-3’ R1 536-515 5’-GTATTACCGCGGCTGCTGGCAC-3’of R3 1074-1053 5’-CACGAGCTGACGACAICCAT-3’ R5 1512-1492 5’-ACGGITACCTTGTTACGACTT-3’ $ As per the E. coli numbering.


I, inosine

A standard nucleotide-nucleotide BLAST search (blastn) (Altschul et al., 1997) of the 16S rRNA gene sequence against Universitythe GenBank database allowed for the determination of the genus to which each isolate belonged.

3.3.1.2 gyrB Amplification and sequencing The primers used to amplify and sequence the gyrB genes are listed in Table 3.3.2. The 7G-gyrB-R (le Roes et al., 2008) and 7G-gyrB-F (Everest & Meyers, 2009) primers were designed from an alignment of thirteen gyrB sequences from strains belonging to seven genera. The GgyrB primers were described by le Roes et al. (2008). The gyrB gene was amplified from the Nocardia isolates using primers 7G-gyrB-F & 7G-gyrB-R, to produce a single 1504nt fragment. The gyrB gene from the Amycolatopsis isolates was amplified in two segments with a 266nt overlap, using two 129 combinations of primers: 7G-gyrB-F & GgyrB-R1 amplifying a 776nt fragment from the 5’-end and GgyrB-F1 & 7G-gyrB-R amplifying a 994nt fragment. Product sizes were all calculated based on the Streptomyces avermitilis MA-4680T gyrB sequence.

Table 3.3.2 Primers used to amplify and sequence the gyrB gene from selected filamentous actinobacterial isolates Primer Binding Position$ Primer Sequence


7G-gyrB-F 160-180 5’ - GTICGYAWVCGICCSGGHATGTAC - 3’ 7G-gyrB-R 1664–1641 5’- CCGTCVACRTCRGCRTCSGCCATS - 3’ GgyrB-F1 670-693 5’ - CARGARATGGCNTTCYTSAACAAG - 3’ GgyrB-R1 936-916 5’ - GTTCCAYTGCATSGCSABCTC - 3’ $ Based on the S. avermitilis MA-4680T gyrB sequence.


Using the standard ambiguity codes for nucleotides.

All PCR reactions were performed in 50µl volumes containing 4mM MgCl2, 150µM of each dNTP, 0.5µM of each primer, 0.5U Supertherm Taq polymerase (JMR Holdings,Town U.S.A.) and 500ng of genomic DNA in a Techne TC-512 thermal cycler. The PCR program consisted of an initial denaturation at 96°C for 2min, followed by 30 cycles of denaturation at 96°C for 45s, annealing at 56°C for 30s and extension at 72°C for 90s, followedCape by a final extension at 72°C for 5min. PCR products were electrophoresed alongside a λ-PstofI size marker on 0.8% (w/v) agarose gels containing ethidium bromide (0.8µg.ml-1) and visualized (GelDoc, BioRad). PCR products were purified using the MSB® Spin PCRapace kit (Invitek, Germany) or, when necessary, were excised from the gel under long-wave UV (365nm) and purified using a Cleanmix kit (TA050CLN; Talent). Products were sequenced as described above using the PCR primers in the sequencing reactions.

The gyrB sequence fromUniversity the Kribbella isolate was obtained by Bronwyn Kirby as part of the work for her PhD thesis and has been published (Kirby et al., 2010).

3.3.1.3 Phylogenetic analysis For isolates belonging to the genus Streptomyces, the 16S rRNA gene sequences of the type strains (Euzéby, 2010) of the top 25 hits identified in the BLAST search were downloaded from the GenBank database and used as references to construct individual phylogenetic trees. Strains with similar BLAST results were combined for analysis. A single tree was also constructed by combining all these reference strains and analyzed in combination with the individually constructed trees to determine the closest relatives of each isolate. The final tree was then constructed for all the isolates 130 using the refined consensus list of reference strains that were identified. For the non-Streptomyces isolates, the 16S rRNA gene sequences of all the type strains belonging to the same genus as the isolates were included as the references to construct the phylogenetic tree. If the genus contained less than five members, the 16S rRNA gene sequences of all type strains of that genus, as well as that of the type species plus at least one other member from each of the genera belonging to the same family were included in the phylogenetic analysis. All phylogenetic analyses were performed using MEGA version 4 (Tamura et al., 2007). Phylogenetic trees were constructed using the neighbour- joining (Saitou & Nei, 1987), minimum evolution and maximum parsimony (Takahashi & Nei, 2000) methods.

3.3.2 Chemotaxonomic characterisation Actinobacterial isolates were grown in 100ml of YEME broth in a 1l Erlenmeyer flask that was incubated for 3 days at 30°C with constant shaking. The cell mass wasTown collected by centrifugation at 10 000 x g for 10min and washed twice with 100ml of sterile distilled water. The washed cell pellets were then resuspended in 20ml of sterile distilled water and placed in 1l round-bottom flasks before being frozen in an ethanol bath and freeze dried overnight. Cape The isomer of DAP present in the cell wall wasof analysed by the method of Hasegawa et al. (1983) using approximately 10mg of the freeze dried cells. The whole cell sugar patterns were also determined as per the method of Hasegawa et al. (1983), using 100mg of freeze dried cells and a solvent system comprising ethyl acetate:pyridine:distilled water (100:35:25, v/v). Analyses were performed on cellulose TLC plates (Merck; 1.05552.0001) and included the relevant standards: 1% commercial DAP standard (Sigma; D1377-5G) and 0.1% (v/v) glycine standard for the DAP analysis; 1% (w/v) of University each of glucose, mannose and ribose standard and 1% (w/v) of each of galactose, arabinose and xylose standard for the whole cell sugar analysis. The phospholipid patterns were determined as described by Komagata & Suzuki (1987) and Minnikin et al. (1984) using freeze dried cells and silica TLC plates. Chromatography was performed in a TLC chamber containing approximately 80ml of the relevant solvent system and a wick made of Whatman no. 1 paper that had been set up 30min prior to chromatography to allow the atmosphere to become saturated with the solvents.

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3.3.3 Phenotypic characterisation 3.3.3.1 Morphological characterisation 3.3.3.1.1 Colony morphology and pigmentation All ISP media were prepared according to Shirling & Gottlieb (1966). The colours of the substrate and aerial mycelia were determined on inorganic salts-starch agar (ISP 4) or on YEME agar. The production of diffusible pigments and the determination of their pH sensitivity, along with that of the substrate mycelium, were determined on glycerol-asparagine agar (ISP 5). The production of melanin was determined on peptone-yeast extract iron agar (ISP 6) and tyrosine agar (ISP 7) after four days of incubation. All plates were incubated at 30°C for 14 days, unless stated otherwise.

3.3.3.1.2 Scanning electron microscopy Strains were streaked onto ISP 4 agar and incubated at 30ºC for 14 days. A plug of agar (approximately 1cm X 1cm) containing both substrate and aerial myceliumTown was cut from the plate with a sterile scalpel blade. The samples were fixed in 100mM sodium cacodylate buffer containing 2% (v/v) glutaraldehyde (pH 8.0) overnight, after which they were washed twice (30min each) in 100mM sodium cacodylate buffer (pH 8.0) without glutaraldehyde.Cape Post-fixing was performed in 100mM sodium cacodylate buffer (pH 8.0) containing 1.0% (v/v) osmium tetroxide for 2h before the samples were washed, once with 100mM sodiumof cacodylate buffer and twice with sterile distilled water (10min each). The fixed samples were dehydrated in an increasing ethanol gradient (30, 50, 70, 85, 95 and 100% ethanol, 10min each), being washed three times in 100% ethanol to ensure all water was removed before storage in 100% ethanol. All the preparation steps were performed at room temperature. Samples were critical point dried and sputter coated with gold palladium and viewed under a Leica Stereoscan 440i Scanning Electron Microscope (Electron Microscope Unit, University of Cape Town).University

3.3.3.2 Physiological characterisation All physiological tests were performed as described by Williams et al. (1989). All plates were incubated at 30°C for the recommended periods, unless otherwise stated. Growth in the presence of antibiotics was determined on Bennett’s medium (Atlas, 2004), containing the indicated concentration of compounds, after 7 days. Salt tolerance was tested on YEME agar, incubated for 14 days. Growth at differing pH’s and temperatures was determined on Bennett’s medium incubated for 14 days. Carbon source utilisation testing was performed as per the methods of Shirling & Gottlieb 132

(1966). All carbon sources were filter sterilized with AcetatePlus Cameo syringe filters with a pore size of 0.22µm (Osmonics) and tested at a concentration of 1% (w/v), with the exception of sodium acetate, sodium citrate and sodium succinate, which were tested at 0.1% (w/v). Nitrogen source utilisation tests were performed as per Williams et al. (1989). All nitrogen sources were filter sterilized and tested at a concentration of 0.1% (w/v). Modified carbon and nitrogen utilisation plates were prepared to allow for the growth of the Micromonospora strains that failed to grow on the standard utilisation test media and included yeast extract at a final concentration of 0.05% (w/v).

The ability to grow under anaerobic conditions was determined on ISP 9 with glucose as the sole carbon source and on ATCC medium 172 (www.atcc.org/Attachments/2915.pdf) with the N-Z amine type A being replaced with Casitone (Difco). Plates were incubated at 37°C for 21 days in an anaerobic chamber (model 1024, Forma Scientific) containing an atmosphere of H2/CO2/N2 (5:10:85). Before incubation, plates were opened inside the chamber for 5s, to remove all residual oxygen and then sealed in a plastic bag. Town

Physiological testing was performed on the closest relatives (as determined by 16S rRNA gene phylogenetic analysis) in parallel with that of all theCape non-Streptomyces isolates. The type strains tested in this study are listed in Table 3.3.3. Allof test plates were inoculated from growth on a YEME agar plate or with 2 loopfuls of culture grown in YEME broth (10ml YEME in a 100ml Erlenmeyer flask grown at 30°C for 3-5 days with shaking). Carbon and nitrogen source utilisation plates were inoculated with two 50µl volumes of washed inoculum, prepared from a YEME broth culture (grown at 30°C for 3-5 days with shaking) as described in Shirling & Gottlieb (1966). Gram stains were performed on all cultures to ensure their purity prior to the inoculation of the test plates. University Table 3.3.3 Details of actinobacteria type strains tested Strain Strain Number Source Amycolatopsis albidoflavus NRRL B-24149T USDA ARS Culture Collection Amycolatopsis echigonensis JCM 21831T Japan Collection of Microorganisms Amycolatopsis halotolerans NRRL B-24428T USDA ARS Culture Collection Amycolatopsis niigatensis JCM 21832T Japan Collection of Microorganisms Amycolatopsis rubida NRRL B-24150T USDA ARS Culture Collection Kribbella solani CIP 108508T Collection de l'Institut Pasteur Micromonospora olivasterospora NRRL 8178T USDA ARS Culture Collection Nocardia fluminea DSM 44489T German Collection of Microorganisms and Cell Cultures ‘Nocardia rhamnosiphila’ 202GMO Lab isolate (A. Cook) Verrucosispora gifhornensis DSM 44337T German Collection of Microorganisms and Cell Cultures

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3.3.3.3 DNA-DNA hybridisation For the DDH experiments, all strains were grown in YEME broth. A 1ml 15% glycerol stock was used to inoculate 10ml of medium in a 100ml Erlenmeyer flask and incubated at 30°C with constant shaking for 3 days. This starter culture was then added to a 250ml Erlenmeyer flask containing 20ml of medium and incubated as before. This second culture (approx 30ml) was then inoculated into 500ml of medium in a 5l Erlenmeyer flask and incubated at 30°C with constant shaking for 4 days. Gram staining and streaking for single colonies were performed at each step to check for contamination. The cell mass was harvested by centrifugation at 10 000 x g for 15min, resuspended in 50ml sterile distilled water and centrifuged again at 10 000 x g for 10min before being resuspended in 10-15ml of 50% isopropanol. The resuspended cell mass was stored in plastic Sterilin tubes sealed with Parafilm at 4°C prior to being couriered to Germany. DDH was performed as a service by the DSMZ (Deutsche Sammlung von Mikroorganismen und Zellkulturen) using the spectrophotometric method of De Ley et al. (1970) and incorporatingTown the modifications of Huss et al. (1983).

3.4 Results Cape 3.4.1 Genus determination of The top nine antibiotic producing strains and nine other non-Streptomyces isolates, selected for further study based on their interesting colony morphologies (section 2.4.3), had their 16S rRNA genes sequenced to allow for definitive genus level assignments to be made by blastn analysis (Table 3.4.1). University Table 3.4.1 Genus level assignments of the isolated actinobacteria based on 16S rRNA gene sequences Strain Genus Strain Genus C2 Nocardia SE(6)11 Streptomyces H17 Streptomyces SE(7)1 Nocardia S1.3 Amycolatopsis SE(7)3 Streptomyces S1.4 Kribbella SE(8)3 Amycolatopsis S3.2 Streptomyces Y1 Streptomyces S3.3 Streptomyces Y2 Streptomyces S3.5 Streptomyces Y21 Micromonospora S3.6 Amycolatopsis Y22 Micromonospora SE(6)5 Streptomyces Y25 Verrucosispora

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All isolates that were presumptively identified as belonging to the genus Streptomyces were shown by BLAST analysis to have been correctly assigned, as were the three isolates presumed to belong to the genus Amycolatopsis. The single isolate (SE(7)1) initially placed in the genus Nocardia by the rapid molecular identification method was also shown to be correctly assigned, with another isolate (C2), initially presumed to belong to one of Gordonia, Nocardia or Skermania, being identified as belonging to the genus Nocardia. Strain S1.4, preliminarily assigned to either the genus Kribbella or Nocardioides was shown to belong to Kribbella. Of the three isolates shown to belong to one of seven genera within the family Micromonosporaceae, two (Y21 & Y22) belong to the genus Micromonospora and the other (Y25) to the genus Verrucosispora.

The 16S rRNA gene sequences were not obtained from the morphologically interesting isolates that were presumed to belong to the genus Streptomyces. However, owing to the high level of accuracy with which the rapid molecular method identifies the members of this genus, it is reasonable to presume that the morphologically interesting isolates were correctly Townidentified.

3.4.2 Characterisation of actinobacterial isolates 3.4.2.1 Isolates belonging to the genus AmycolatopsisCape Three of the isolates that were selected based onof their interesting colony morphology and which were presumed to be Amycolatopsis due to the amplification of the characteristic 16S rRNA gene product with genus specific primers (Tan et al., 2006) were indeed found to belong to this genus. Phylogenetic analysis of strains S1.3, S3.6 and SE(8)3 was performed to determine their phylogenetic position within the genus. The 16S rRNA gene phylogenetic tree is included as Fig 3.4.1, with sub trees showing the phylogeny based on the gyrB gene and the gyrB-16S rRNA concatenated genes beingUniversity included in Fig 3.4.2 (the full trees can be seen in Appendix A and B respectively). In all trees the three isolates were found to cluster together and were most closely association with A. albidoflavus. The support for the association with A. albidoflavus was low in the 16S-rRNA gene tree (< 40%), but moderate (71%) in the gyrB tree. In the 16S rRNA gene based tree, A. halotolerans N4-6T, A. echigonensis LC2T, A. niigatensis LC11T, A. benzoatilytica DSM 43387T and A. rubida 13.4T formed part of the same clade, while in the other trees additional strains were found to be associated on the periphery of the cluster.

135

The 16S rRNA gene sequence similarity between strains S1.3 and S3.6 was 99.71% (over 1384nt), between strains S1.3 and SE(8)3 was 99.72% (1430nt) and between strains S3.6 and SE(8)3 was 99.86% (1384nt) by local alignment in DNAMAN, while the similarities to their closest relatives are indicated in Table 3.4.2.

Table 3.4.2 16S rRNA gene sequence similarity values between isolates S1.3, S3.6 and SE(8)3 and related Amycolatopsis type strains Strain S1.3 Strain S3.6 Strain SE(8)3 Similarity (%) Length (nt) Similarity (%) Length (nt) Similarity (%) Length (nt) A. albidoflavus 98.70 1457 98.20 1384 98.12 1433 A. benzoatilytica 94.46 1424 94.36 1383 94.46 1426 A. echigonensis 98.70 1455 98.63 1385 98.61 1433 A. halotolerans 98.76 1455 98.70 1384 98.67 1432 A. niigatensis 98.36 1458 98.41 1386 98.26 1434 A. rubida 97.58 1406 97.55 1384 97.29 1402

Morphologically strains S1.3, S3.6 and SE(8)3 are very similar,Town with the colonies appearing convoluted with raised centres on most media. The aerial mycelium appears white, whilst the vegetative mycelium appears cream-brown in colour, fragmenting into short branched hyphae in both liquid and agar cultures. A brown diffusible pigment is produced by all three isolates on most media and on ISP 5 is tan in colour, becoming yellowCape with the addition of acid and red upon the addition of base. Melanin is not produced on ISPof 6 or ISP 7.

The chemotaxonomic features of all three strains are identical and consistent with those of the members of the genus Amycolatopsis. The cell wall peptidoglycan was shown to contain meso-DAP, with arabinose, galactose and glucose present in the whole-cell hydrolysates (cell wall chemotype IV and a type A whole-cell sugar pattern; Lechevalier & Lechevalier, 1970). The predominant phospholipids are PE, PI,University PG and PIMs, corresponding to a type II phospholipid pattern (Lechevalier & Lechevalier, 1981).

All three strains grow between 20 and 37°C (but not at 45°C) and from pH 4.3 to 9. Both strains S1.3 and S3.6 are able to grow in the presence of up to 7% (w/v) NaCl (but not at 10% (w/v) NaCl), whilst strain SE(8)3 grows in the presence of up to 10% (w/v) NaCl. The ability to reduce nitrate to nitrite and produce H2S is shared by all three strains. 136

T *66 Amycolatopsis kentuckyensis NRRL B-24129 (AY183357) Amycolatopsis rifamycinica DSM 46095T (AY083603) Amycolatopsis lexingtonensis NRRL B-24131T (AY183358) T *89 Amycolatopsis pretoriensis NRRL B-24133 (AY183356) Amycolatopsis vancoresmycina DSM 44592T (AJ508240) 69 Amycolatopsis plumensis SBHS Strp1T (AY262825) *67 *80 Amycolatopsis tolypomycina DSM 44544T (AJ508241) 76 Amycolatopsis balhimycina DSM 44591T (AJ508239) Amycolatopsis mediterranei NRRL B-3240T (AY184424) Amycolatopsis australiensis GY048T (AY129753) Amycolatopsis saalfeldensis HKI0457T (DQ792500) Amycolatopsis rubida 13.4T (AF222022) Amycolatopsis benzoatilytica DSM 43387T (AY957506) *74 T * Amycolatopsis echigonensis LC2 (AB248535) T * Amycolatopsis niigatensis LC11 (AB248537) Amycolatopsis halotolerans N4-6T (DQ000196) Amycolatopsis albidoflavus IMSNU 22139T (AJ252832) Strain S1.3 Strain S3.6 *99 *61 Strain SE(8)3 T *90 Amycolatopsis alba DSM 44262 (AF051340) Amycolatopsis coloradensis DSM 44225T (AJ421142) Amycolatopsis azurea IMSNU 20053T (AJ400709)Town *96 T *99 Amycolatopsis orientalis IMSNU 20058 (AJ400711) * Amycolatopsis regifaucium GY080T (AY129760) 78 Amycolatopsis japonica DSM 44213T (AJ508236) Amycolatopsis decaplanina DSM 44594T ( AJ508237) Amycolatopsis keratiniphila subsp. nogabecetica DSM 44586T (AJ508238) AmycolatopsisCape keratiniphila subsp. keratiniphila DSM 44409T (AJ278496) 76 *53 Amycolatopsis lurida DSM 43134T (AJ577997) Amycolatopsisof ultiminotia RP-AC36T (FM177516) T 63 Amycolatopsis jejuensis N7-3 (DQ000200) T 62 Amycolatopsis sulphurea DSM 46092 (AF051343) 95 Amycolatopsis sacchari DSM 44468T (AF223354) Amycolatopsis minnesotensis 32U-2T (DQ076482) T *94 Amycolatopsis nigrescens CSC17-Ta-90 (DQ486888) T *100 Amycolatopsis marina MS392A (EU329845) Amycolatopsis palatopharyngis 1BDZT (AF479268) Amycolatopsis taiwanensis 0345M-7T (DQ160215) 58 T *100 Amycolatopsis eurytherma NT202 (AJ000285) *65 T University Amycolatopsis tucumanensis ABO (DQ886938) *100 Amycolatopsis methanolica IMSNU 20055T (AJ249135) *99 Amycolatopsis thermoflava N1165T (AF052390) Amycolatopsis fastidiosa IMSNU 20054T (AJ400710) Streptomyces avermitilis NCIMB 12804T (AF145223)

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Figure 3.4.1 Unrooted 16S rRNA gene phylogenetic tree showing the position of strains S1.3, S3.6, and SE(8)3 within the genus Amycolatopsis. The tree was constructed using the neighbour-joining method based on 1378nt of common sequence. The percentage bootstrap values of 1000 replications are shown at each node (only values above 50% are shown), with asterisks (*) indicating the clades that were conserved in all three tree drawing algorithms (section 3.3.1.3). Accession numbers are indicated in parentheses after the strain numbers. The scale bar indicates 1 nucleotide substitution per 100 nucleotides. Streptomyces avermitilis NCIMB 12804T was used as an outgroup.

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Strain S1.3 *100 A Strain S3.6 *71 Strain SE(8)3 Amycolatopsis albidoflavus NRRL B-24149T (EU822886) 86 Amycolatopsis rubida NRRL B-24150T (EU822911) Amycolatopsis echigonensis JCM 21831T (EU822892) 99 *100 Amycolatopsis niigatensis JCM 21832T (EU822905) *96 Amycolatopsis halotolerans NRRL B-24428T (EU822895) Amycolatopsis jejuensis NRRL B-24427T (EU822897)

*99 *51 Amycolatopsis sulphurea NRRL 2822T (EU822914) Amycolatopsis saalfeldensis DSM 44993T (EU822912)

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*65 Strain S3.6 Town B *100 Strain SE(8)3 62 Strain S1.3 60 Amycolatopsis albidoflavus AmycolatopsisCape echigonensis 72 *100 Amycolatopsis niigatensis 100 of Amycolatopsis rubida *97 Amycolatopsis halotolerans

Amycolatopsis jejuensis

*96 *97 Amycolatopsis sulphurea Amycolatopsis saalfeldensis

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Figure 3.4.2 Phylogenetic sub-trees showing the relationship of strains S1.3, S3.6 and SE(8)3 to the closely related members of the genus Amycolatopsis. The sub-trees show the phylogeny based on the gyrB gene (A) and the gyrB-16S rRNA concatenated genes (B). Both sub-trees are part of the full unrooted phylogenetic trees which include all 34 species for which there is a gyrB gene sequence (Appendix A and B). The trees were constructed using the neighbour- joining method based on 1292nt of gyrB sequence and 2642nt of gyrB-16S rRNA concatenated sequence, respectively, and S. avermitilis was used as the outgroup. The percentage bootstrap values of 1000 replications are shown at each node (only values above 50% are shown), with asterisks (*) indicating the clades that were conserved in all three tree drawing algorithms (section 3.3.1.3). The strain numbers indicated in A are the strains from which the gyrB genes were obtained, with the accession numbers indicated in parentheses. The 16S rRNA genes used in Fig 3.4.1 were joined to these gyrB genes to construct Fig 3.4.2 B. The scale bars indicate 10 (A) and 5 (B) nucleotide substitutions per 1000 nucleotides, respectively.

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Strain S1.3 has the ability to utilise adonitol, L(+)-arabinose, D(+)-cellobiose, D(–)-fructose, D(+)- galactose, D(+)-glucose, glycerol, myo-inositol, α-lactose, D(–)-mannitol, D(+)-mannose, D(–)- ribose, trehalose, sucrose and D(+)-xylose as sole carbon sources, showing weak growth on sodium acetate, sodium citrate and sodium succinate, but doubtful growth on maltose. The strain is unable to utilise dulcitol, inulin, D(+)-melezitose, melibiose, raffinose, L(+)-rhamnose, D(–)-salicin, D(–)- sorbitol or xylitol as sole carbon sources. DL-α-Amino-n-butyric acid, L-asparagine, L-histidine, L- methionine, L-phenylalanine, potassium nitrate, L-serine, L-threonine and L-valine are all utilised as sole nitrogen sources, with weak growth on L-cysteine. Strain S1.3 is unable to utilise L-4- hydroxyproline as a sole nitrogen source. Aesculin is hydrolysed whilst arbutin and starch are not. Casein, gelatin, hypoxanthine, Tween 80 and L-tyrosine are degraded and allantoin, urea and xanthine are only weakly degraded by strain S1.3. Adenine, cellulose, guanine and xylan are not degraded. Strain S1.3 is resistant to cephaloridine (100µg/ml), lincomycin hydrochloride (100µg/ml), oleandomycin phosphate (100µg/ml), penicillin G (10I.U./ml) and rifampicin (50µg/ml), but is sensitive to neomycin sulphate (50µg/ml), streptomycinTown sulphate (100µg/ml), tobramycin sulphate (50µg/ml) and vancomycin hydrochloride (50µg/ml).

Strain S3.6 utilises adonitol, L(+)-arabinose, D(+)-cellobiose,Cape D(–)-fructose, D(+)-galactose, D(+)- glucose, glycerol, myo-inositol, α-lactose, D(–)-mannitol,of D(+)-mannose, D(–)-ribose, salicin, sucrose, trehalose and D(+)-xylose as sole carbon sources, showing weak growth on sodium acetate, sodium citrate and sodium succinate. The strain is unable to utilise dulcitol, inulin, maltose, D(+)- melezitose, D(+)-melibiose, raffinose, L(+)-rhamnose, D-sorbitol or xylitol as sole carbon sources. DL-α-Amino-n-butyric acid, L-asparagine, L-histidine, L-methionine, L-phenylalanine, potassium nitrate, L-serine, L-threonine and L-valine are utilised as sole nitrogen sources, with only weak growth on L-cysteine. UniversityStrain S3.6 is unable to utilise L-4-hydroxyproline as a sole nitrogen source. Aesculin is hydrolysed, arbutin is weakly hydrolysed and starch is not hydrolysed by strain S3.6. Casein, gelatin, hypoxanthine, Tween 80, L-tyrosine and urea are degraded while adenine, allantoin and xanthine are weakly degraded and cellulose, guanine and xylan are not degraded. Strain S3.6 is resistant to cephaloridine (100µg/ml), lincomycin hydrochloride (100µg/ml), oleandomycin phosphate (100µg/ml), penicillin G (10I.U./ml) and rifampicin (50µg/ml), weakly resistant to tobramycin sulphate (50µg/ml), but is sensitive to neomycin sulphate (50µg/ml), streptomycin sulphate (100µg/ml) and vancomycin hydrochloride (50µg/ml).

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Strain SE(8)3 utilises adonitol, L(+)-arabinose, D(+)-cellobiose, D(–)-fructose, D(+)-galactose, D(+)-glucose, glycerol, myo-inositol, α-lactose, D(–)-mannitol, D(+)-mannose, D(–)-ribose, sucrose, trehalose and D(+)-xylose as sole carbon sources, showing weak growth on inulin, maltose, raffinose, sodium acetate, sodium citrate and sodium succinate, but doubtful growth on maltose. The strain is unable to utilise dulcitol, D(+)-melezitose, melibiose, L(+)-rhamnose, D(–)-salicin, D(–)- sorbitol or xylitol as sole carbon sources. DL-α-Amino-n-butyric acid, L-asparagine, L-histidine, L- methionine, L-phenylalanine, potassium nitrate, L-serine, L-threonine and L-valine are utilised as sole nitrogen sources, with weak growth on L-cysteine. Strain SE(8)3 is unable to utilise L-4- hydroxyproline as a sole nitrogen source. Aesculin is hydrolysed and arbutin is weakly hydrolysed, but starch is not hydrolysed. Allantoin, casein, gelatin, hypoxanthine, Tween 80 and L-tyrosine are degraded by strain SE(8)3, whilst urea is weakly degraded and adenine, cellulose, guanine, xanthine and xylan are not degraded. Strain SE(8)3 is resistant to cephaloridine (100µg/ml), lincomycin hydrochloride (100µg/ml), oleandomycin phosphate (100µg/ml), penicillin G (10I.U./ml) and rifampicin (50µg/ml), weakly resistant to tobramycin sulphate (50µg/ml),Town but sensitive to neomycin sulphate (50µg/ml), streptomycin sulphate (100µg/ml) and vancomycin hydrochloride (50µg/ml).

Comparison of the physiological characteristics of theCape three Amycolatopsis strains with those of their closest relatives shows that the three can be distinguishedof from each other and from the type strains of their phylogenetic neighbours (Table 3.4.3).

The likelihood of strains S1.3, S3.6 and SE(8)3 representing unique genomic species was assessed by calculating the gyrB based genetic distances between the strains and their closest relatives. This is a method that was developed as a part of this study, is presented in Chapter 4 and has been published (Everest & Meyers,University 2009). gyrB Genetic distance values between strain S3.6 and A. albidoflavus, A. echigonensis, A. halotolerans, A. niigatensis and A. rubida were 0.023, 0.04, 0.035, 0.04 and 0.036, respectively (0.051, 0.091, 0.066, 0.084 and 0.073 based on the 315nt variable segment (Everest & Meyers, 2009)), with the values between strains S1.3 or SE(8)3 and these type strains being identical to those for strain S3.6. All these values are above the 0.02 threshold proposed to be the cut-off for a novel species (Everest & Meyers, 2009), thereby suggesting that these strains should be recognised as novel species. DDH experiments confirmed this, with strain S3.6 sharing 22.7 ± 1.4% DNA relatedness with A. albidoflavus, 23.8 ± 3.4% with A. echigonensis, 34.4 ± 1.7% with A. halotolerans, 24.6 ± 1.8% with A. niigatensis and 25.0 ± 3.6% with A. rubida. The gyrB genetic distances between strains S1.3, S3.6 and SE(8)3 were zero, thus requiring DDH to 140

determine if they are separate genomic species. DDH revealed that strains S3.6 and S1.3 are distinct species, sharing only 12.8 ± 2.4 % genome similarity, that strains S3.6 and SE(8)3 are distinct species, sharing 9.8 ± 5.5% genome similarity and that strains SE(8)3 and S1.3 shared 67.9 ± 2.9 % genome similarity.

Table 3.4.3: Phenotypic differences between strains S1.3, S3.6, SE(8)3 and Amycolatopsis type strains Test S1.3 S3.6 SE(8)3 1 2 3 4 5 Growth at: 45°C – – – – + – + – pH 4.3 ++ ++ ++ + + (–) ++ + (–) + pH 5 ++ ++ ++ + + (–) ++ + (–) + 10 % (w/v) NaCl – – +w – +w – +w – Degradation of: Adenine – +w – – +w – +w – Allantoin +w +w + – – +w – – Gelatin + + + + + + + (–) +w Urea +w + +w – (+w) – (+) +w – (+) – (+) Xanthine +w +w – + + – (+) + + Hydrolysis of: Arbutin – +w +w – Town +w – + + Starch – – – – (+) – – – – Utilisation as sole carbon source: L(+)-Arabinose + ++ + + + – + +w Dulcitol – – – – +w – +w – Inulin – – +w – – – +w – Maltose – – +wCape – +w – +w +w D(+)-Melezitose – – – +w – – – – Raffinose – – +w +w +w +w +w – D(–)-Salicin – + of – – + – + +w D(–)-Sorbitol – – – – +w – +w – Resistance to: Neomycin sulphate (50µg/ml) – – – + – + – +w Streptomycin sulphate (100µg/ml) – – – +w – + – – Tobramycin sulphate (50µg/ml) – +w +w + – +w – – Vancomycin hydrochloride (50µg/ml) – – – +w – + – – 1, Amycolatopsis albidoflavus IMSNU 22139T (Lee & Hah, 2001); 2, Amycolatopsis echigonensis LC2T (Ding et al., 2007); 3, Amycolatopsis halotolerans N4-6T (Lee, 2006); 4, Amycolatopsis niigatensis LC11T (Ding et al., 2007); 5, Amycolatopsis rubida 13.4T (Huang et al., 2001). All data were determined in this study.University Conflicting data (obtained from published work) are indicated in parenthesis. Symbols: ++, strong positive; +, positive; +w, weak positive; –, negative.

The gyrB genetic distance data, confirmed by the DDH data, clearly indicated that strains S3.6 and S1.3 should be recognised as distinct genomic species. Although strain SE(8)3 might be considered to belong to the same species as strain S1.3 when the threshold value of 70% genome similarity is used to delineate bacterial species (Wayne et al., 1987), these strains do show phenotypic differences (Table 3.4.3) and are therefore proposed to be distinct species. Support is lent to this proposal by two of the phylogenetic trees (Fig 3.4.1 and Fig 3.4.2 B) in which strain SE(8)3 clusters with strain S3.6 (with moderate bootstrap values) rather than strain S1.3. 141

Strain S1.3 shows four clear phenotypic differences (excluding degrees of difference) from strain S3.6, seven from strain SE(8)3, at least seven differences (if data with conflicting results are excluded) from A. albidoflavus, nine from A. echigonensis, six from A. halotolerans, 11 from A. niigatensis and four from A. rubida. This strain is therefore proposed to represent the type strain of a novel species for which the name ‘Amycolatopsis circi’ sp. nov. is proposed (cir’ci. L. gen. n. circi of an oval course for races, Kenilworth Racecourse, Cape Town, Western Cape, South Africa).

Strain S3.6 shows four clear phenotypic differences from strain S1.3, seven from strain SE(8)3, at least nine differences from A. albidoflavus, eight from A. echigonensis, eight from A. halotolerans, nine from A. niigatensis and five from A. rubida. This strain is therefore proposed to represent the type strain of a novel species for which the name ‘Amycolatopsis hippodromi’ sp. nov. is proposed (hip.po'dro.mi. Gr. masc. n. hippodromos horse racecourse, N.L. gen. masc. n. hippodromi of/from a horse racecourse, Kenilworth, Cape Town, Western Cape, South Africa). Town Strain SE(8)3 shows seven clear phenotypic differences from strain S1.3 as well as strain S3.6, at least ten differences from A. albidoflavus, nine from A. echigonensis as well as A. halotolerans and eight from A. niigatensis and A. rubida. This strain isCape therefore proposed to represent the type strain of a novel species for which the name ‘Amycolatopsisof equina’ sp. nov. is proposed (e.qui'na. L. fem. adj. equina, relating to horses, isolated from a soil sample collected near a horse racing track, Kenilworth Racecourse, Cape Town, Western Cape, South Africa).

3.4.2.2 Isolate belonging to the genus Kribbella The single isolate found to belong to the genus Kribbella by blastn analysis was strain S1.4, which was initially shown to belongUniversity to either the genus Kribbella or Nocardioides by the rapid molecular identification method (section 2.4.3). The phylogenetic position of this strain within the genus Kribbella was assessed by constructing a 16S rRNA gene tree with all type strains of the genus (Fig 3.4.3). Strain S1.4 was found to be most closely related to Kribbella solani DSA1T (bootstrap value = 100%), with Kribbella aluminosa HKI0478T, Kribbella jejuensis HD9T and Kribbella swartbergensis HMC25T forming part of the same cluster with weak to moderate bootstrap support. These type strains’ 16S rRNA gene sequences are 99.57% (over 1388nt), 98.91% (1378nt), 98.42% (1388nt) and 97.63% (1390nt) similar to that of strain S1.4, respectively. When the phylogenetic tree was constructed based on the gyrB gene (Fig 3.4.4), a similar clustering was observed, but additional strains were introduced into the strain S1.4 cluster. K. solani was still the closest 142 phylogenetic relative, but Kribbella karoonensis Q41T joined the cluster, with Kribbella sandramycini DSM 18824T and Kribbella koreensis CIP 108301T clustering on the periphery, replacing K. swartbergensis, which was no longer part of the cluster.

T *70 Kribbella aluminosa HKI 0478 (EF126967) *70 Kribbella jejuensis HD9T (AY253866) *78 Kribbella swartbergensis HMC25T (AY995147) Kribbella solani DSA1T (AY253862) * *100 Strain S1.4 (EF472955) Kribbella karoonensis Q41T (AY995146) Kribbella flavida KACC 20248T (AY253863) Kribbella alba YIM 31075T (AY082062) Kribbella catacumbae BC631T (AM778575) Kribbella sancticallisti BC633T (AM778577) Kribbella koreensis LM 161T (Y09159) Town *89 Kribbella ginsengisoli Gsoil 001T (AB245391) Kribbella lupini LU14T (AJ811962) Kribbella yunnanensis YIM 30006T (AY082061) *84 Kribbella sandramycini ATCC 39419T (AF005020)Cape Kribbella antibiotica YIM 3153T (AY082063) of Nocardioides albus KCTC 9186T (AF004988)

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Figure 3.4.3 Unrooted 16S rRNA gene phylogenetic tree showing the position of strain S1.4 within the genus Kribbella. The tree was constructed using the neighbour-joining method based on 1362nt of 16S rRNA gene sequence. Values at each node are the percentage bootstrap values of 1000 replications (only values above 50% are shown), with asterisks (*) indicating the clades that were conserved in all three tree drawing algorithms (section 3.3.1.3). Accession numbers are indicated in parenthesis after the strain numbers. The scale bar indicates 1 nucleotide substitution per 100 nucleotides. Nocardioides albus KCTC 9186UniversityT was used as an outgroup.

Strain S1.4 is Gram positive and aerobic (unable to grow on ATCC medium 172 and ISP 9-glucose under anaerobic conditions). The colonies appear convoluted with irregular edges on most media and the vegetative mycelium appears cream in colour with highly branched hyphae that fragment in both liquid and agar cultures. The aerial mycelium appears white on ISP 4. No diffusible pigments are produced on any medium and melanin is not produced on ISP 6 or ISP 7.

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T 63 Kribbella jejuensis CIP 108509 (EU434818) Kribbella karoonensis Q41T (EU434816)

54 Kribbella aluminosa DSM 18824T (EU434807)

Kribbella solani CIP108508T (EU434813) *100 Strain S1.4 (EU434817)

Kribbella sandramycini DSM 15499T (EU434812)

Kribbella koreensis CIP 108301T (EU434810)

T 83 Kribbella catacumbae BC631 (FJ917358) Kribbella sancticallisti BC633T (FJ917357)

Kribbella alba DSM 15500T (EU434820) *68 Kribbella yunnanensis YIM 30006T (EU434815)

Kribbella flavida CIP 107494T (434809) 50 Kribbella lupini DSM 16683T (EU434811)

Kribbella antibiotica YIM 31530T (EU434819) Kribbella swartbergensis HMC25TownT (EU434808) Streptomyces avermitilis MA-4680T (NC_003155)

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Figure 3.4.4 Unrooted gyrB gene phylogenetic tree showing theCape position of strain S1.4 within the genus Kribbella. The tree was constructed using the neighbour-joining method based on 1105nt of gyrB gene sequence. Values at each node are the percentage bootstrap values of 1000 replications (onlyof values above 50% are shown), with asterisks (*) indicating the clades that were conserved in all three tree drawing algorithms (section 3.3.1.3). Accession numbers are indicated in parenthesis after the strain numbers. The scale bar indicates 2 nucleotide substitutions per 100 nucleotides. S. avermitilis MA-4680T was used as an outgroup.

The cell wall peptidoglycan contains LL-DAP and glycine, which corresponds to a cell wall chemotype I (LechevalierUniversity & Lechevalier, 1970). Only glucose, minor amounts of ribose and an unidentified sugar were found in the whole-cell hydrolysate.

Strain S1.4 is able to utilise adonitol, L(+)-arabinose, D(+)-cellobiose, D(–)-fructose, D(+)-galactose, D(+)-glucose, glycerol, myo-inositol, inulin, maltose, D(–)-mannitol, D(+)-mannose, D(+)- melezitose, melibiose, raffinose, L(+)-rhamnose, salicin, sucrose and trehalose as sole carbon sources, showing weak growth on sodium acetate, sodium citrate and sodium succinate and doubtful growth on α-lactose and D(+)-xylose. Strain S1.4 is unable to utilise xylitol as a sole carbon source. Strain S1.4 utilises L-arginine, L-asparagine, L-histidine, potassium nitrate and L-threonine as sole nitrogen sources, showing weak growth on DL-α-amino-n-butyric acid, L-cysteine, L-4- 144 hydroxyproline, L-serine and L-valine and doubtful growth on L-methionine and L-phenylalanine.

Nitrate is reduced to nitrite and H2S is produced. Aesculin and arbutin are hydrolysed, starch is weakly hydrolysed and pectin is not hydrolysed by strain S1.4. Adenine, casein, gelatin, hypoxanthine, Tween 80 and L-tyrosine are degraded, but allantoin, cellulose, guanine, urea, xanthine and xylan are not degraded. Strain S1.4 grows at 20–37°C, but not at 45°C, at pH 5–9 (weakly at pH 4.3) and in the presence of 5% (w/v) NaCl, with very weak growth at 6% (w/v) NaCl and no growth at 7% (w/v) NaCl. Strain S1.4 is resistant to lincomycin hydrochloride (100µg/ml), neomycin sulphate (50µg/ml), oleandomycin phosphate (100µg/ml), penicillin G (10I.U./ml), rifampicin (50µg/ml) and streptomycin sulphate (100µg/ml), but is sensitive to cephaloridine (100µg/ml), tobramycin sulphate (50µg/ml) and vancomycin hydrochloride (50µg/ml).

When compared with the physiological characteristics of the closely related Kribbella species with validly-published names, strain S1.4 has nine differences from K. solani, at least six from K. swartbergensis, 20 from K. jejuensis and seven from K. aluminosaTown (only clear differences were counted, i.e. “-” and “+”, and “-” and “+w”). A summary of the physiological differences between these strains is shown in Table 3.4.4. Cape DDH experiments between K. solani CIP 108508ofT and strain S1.4 indicated that these strains share only 40.4 ± 3.8% DNA relatedness, and thus represent two separate genomic species when the threshold value of 70% genome similarity is used to delineate bacterial species (Wayne et al., 1987). This data, in conjunction with the physiological differences, was sufficient to establish strain S1.4 as the type strain of a novel species, Kribbella hippodromi sp. nov. (Everest & Meyers, 2008).

University

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Table 3.4.4. Phenotypic differences between strain S1.4 and closely related Kribbella type strains Test S1.4 1$ 2 3 4 Growth at: 37°C + – + + + 45°C – – + – – pH 4.3 +w – ND – ND pH 9 + + + – – (9.5) 4% (w/v) NaCl + + +w – – 5% (w/v) NaCl + +w – – – 6% (w/v) NaCl +w – – – – Nitrate reduction + + + – – Degradation of: Adenine + + + – + Casein + + + – + Hypoxanthine + + + – (+*) + Tween 80 + + + – + L-Tyrosine + + + – + Urea – – NG + + Xanthine – – ND – + Hydrolysis of starch +w +w + – + Utilisation as sole carbon source : Adonitol + + ND – ND myo-Inositol ++ + +w Town – + Inulin ++ – – + ND α-Lactose – ++ +w + ND D(–)-Mannitol + + +w – + Mannose + + +w – ND Salicin + + ND – ND D(+)-Xylose – Cape ++ +w + + Utilisation as sole nitrogen source: DL-α-Amino-n-butyric acid +w + ND + ND L-4-Hydroxyproline +wof + ND + ND L-Methionine – + ND ND ND L-Phenylalanine – + ND ND ND L-Valine +w ++ ND ND ND Growth on ATCC medium 172 Aerobic + + ++ ++* ND Anaerobic – +w – +w* ND 1, Kribbella solani DSA1T (Song et al., 2004); 2, Kribbella swartbergensis HMC25T (Kirby et al., 2006); 3, Kribbella jejuensis HD9T (Song et al., 2004); 4, Kribbella aluminosa HKI 0478T (Carlsohn et al., 2007). $ data determined in this study. * data taken from Kirby et al. (2006). Conflicting data are indicated in Universityparenthesis. Symbols: ++, strong positive; +, positive; +w, weak positive; –, negative; ND, not determined; NG, no growth.

3.4.2.3 Isolates belonging to the genus Micromonospora Two isolates, Y21 and Y22, were selected for further characterisation because of their interesting colony morphology (orange colonies lacking aerial mycelium), and because they were identified as belonging to one of six genera within the family Micromonosporaceae. A blastn analysis of their 16S rRNA gene sequences showed that they belong to the genus Micromonospora. Their position within the genus was determined by constructing a phylogenetic tree with all the type strains from 146 this genus with validly-published names (Fig 3.4.5). Strains Y21 and Y22 are most closely related to each other, with Micromonospora olivasterospora DSM 43868T being their closest relative. The BLAST analysis revealed Micromonospora viridifaciens DSM 43909T as the closest hit, with Micromonospora auratinigra DSM 44815T following after M. olivasterospora. Although these two strains do not group with strains Y21 and Y22 in the tree, they were included in the phenotypic comparison. The 16S rRNA gene sequences of strains Y21 and Y22 are identical (over 1374nt), with that of strain Y21 being 98.99% similar to M. olivasterospora, 99.21% to M. viridifaciens and 98.92% to M. auratinigra (over 1387nt), whilst strain Y22 is 98.98%, 99.20%, and 98.84% similar to these type strains respectively (over 1374nt).

Morphologically strains Y21 and Y22 are very similar, the substrate mycelium of both appearing wrinkled and orange in colour, with the edges of the colony darkening and becoming slightly black upon aging. The substrate mycelium of strain Y21 is slightly lighter in colour than that of strain Y22, which is a deeper orange colour. Neither strain produces melaninTown on ISP 6 or ISP 7, nor any diffusible pigments. This is in contrast to their closest relative, M. olivasterospora, which produces a distinctive olive-green diffusible pigment on most media. M. olivasterospora has substrate mycelium that is light orange to cream in colour, but thisCape quickly becomes dark green. of Both strains Y21 and Y22 show chemotaxonomic characteristics that are consistent with their placement in the genus Micromonospora. The cell wall peptidoglycan of both strains contains meso- DAP and glycine and the whole-cell hydrolysates contain arabinose, glucose, ribose and xylose (cell wall chemotype II, type D whole-cell sugar pattern; Lechevalier & Lechevalier, 1970).

The conditions under whichUniversity the strains are able to grow are mostly common between strains Y21 and Y22, namely, growth at pH 5-10 and at 20-37°C, but not at 45°C. Strain Y21 is slightly more tolerant to salt, growing weakly at 3% (w/v) NaCl, while strain Y22 showed no growth above 2% (w/v) NaCl. These characteristics are similar to those of M. olivasterospora NRRL 8178T, which grows only weakly at 2% (w/v) NaCl (showing no growth at 3%) and grows under the same conditions of pH and temperature. However, it does not grow as well at 37°C as it does at 30°C, whereas strains Y21 and Y22 grow just as well at 37 °C as at 30°C (Y21) or better (Y22). 147

T *75 Micromonospora coriariae DSM 44875 (AJ784008) *54 Micromonospora endolithica DSM 44398T (AJ560635) Micromonospora chersina ATCC 53710T (X92628) Micromonospora inositola ATCC 21773T (X92610) Micromonospora fulviviridis DSM 43906T (X92620) Micromonospora inyonensis DSM 46123T (X92629) *97 Micromonospora sagamiensis DSM 43912T (X92624) Micromonospora rosaria ATCC 29337T (X29337) ‘Micromonospora tulbaghiae’ TVU1T (EU196562) *47 Micromonospora echinspora DSM43816T (X92607)

T 51 Micromonospora eburnea DSM 44814 (AB107231) Micromonospora narathiwatensis BTG4-1T (AB193559) Micromonospora nigra DSM 43818T (X92609) Micromonospora pallida DSM 43817T (x92608) Micromonospora viridifaciens DSM 43909T (X92623) Micromonospora echinaurantiaca DSM 43904T (X92618) Micromonospora peucetia DSM 43363T (X92603) Micromonospora echinofusca DSM 43913T (x92625) Micromonospora citrea DSM 43903T (X92617) Micromonospora coerulea ATCC 27008T (X92598) Micromonospora auratinigra DSM 44815T (AB159779) Town Micromonospora chaiyaphumensis MC5-1T (AB196710) ‘Micromonospora marina’ JSM1-1T (AB196712) Micromonospora aurantiaca ATCC 27029T (X92604) Micromonospora chalcea ATCC 12452T (X92594) Micromonospora purpureochromogenesCape DSM 43821 T (X92611) Micromonospora coxensis 2-30-b(28)T (AB241455) Micromonospora halophytica DSM 43171T (X92601) of T Micromonospora siamensis JCM 12769 (AB1936565)

T *83 Micromonospora carbonacea DSM 43168 (X92599) Micromonospora krabiensis MA-2T (AB196716) 59 Micromonospora matsumotoense IMSNU 220013T (AF152109) *65 Micromonospora rifamycinica AM105T (AY561829) Micromonospora mirobrigensis DSM 44830T (AJ626950) Micromonospora saelicesensis Lupac 09T (AJ783993) 53 T 90 Micromonospora chokoriensis 2-19(6) (AB241454) Micromonospora lupini Lupac 14NT (AJ783996) University Micromonospora pattaloongensis TJ2-2T (AB275607) *97 ‘Micromonospora pisi’ GUI 15T (AM944497) Micromonospora olivasterospora DSM 43868T (X92613) Strain Y21 *100 Strain Y22 Catellatospora citrea DSM 44097T (X93197)

0.005

Figure 3.4.5 Unrooted 16S rRNA gene phylogenetic tree showing the position of strains Y21 and Y22 within the genus Micromonospora. The tree was constructed using the neighbour-joining method based on 1365nt of common 16S rRNA gene sequence. Values at each node are the percentage bootstrap values of 1000 replications (only values above 50% are shown), with asterisks (*) indicating the clades that were conserved in all three tree drawing algorithms (section 3.3.1.3). Accession numbers are indicated in parenthesis after the strain numbers. The scale bar indicates 5 nucleotide substitutions per 1000 nucleotides. Catellatospora citrea DSM 44097T was used as an outgroup.

148

Strain Y21 is able to utilise D(+)-cellobiose, D(–)-fructose, D(+)-glucose, myo-inositol, maltose, D(+)-mannose, ribose, sorbitol, sucrose and trehalose as sole carbon sources, growing weakly on L(+)-arabinose, α-lactose, melibiose, sodium citrate, sodium succinate and D(+)-xylose. It is unable to utilise adonitol, glycerol, inulin, D(–)-mannitol, D(+)-melezitose, raffinose, L(+)-rhamnose, salicin or sodium acetate as sole carbon sources. L-Asparagine, L-methionine, potassium nitrate and L-serine are utilised as sole nitrogen sources by strain Y21, with weak growth occurring on L-4- hydroxyproline and L-valine. DL-α-Amino-n-butyric acid, L-cysteine, L-histidine, L-phenylalanine and L-threonine are not utilised as sole nitrogen sources. Nitrate is only weakly reduced to nitrite by strain Y21 and H2S is produced. Casein, gelatin, Tween 80 and L-tyrosine are degraded, whilst xylan is only weakly degraded and adenine, allantoin, cellulose, guanine, hypoxanthine, urea and xanthine are not degraded by strain Y21. Aesculin, arbutin and starch are all hydrolysed. Strain Y21 is weakly resistant to oleandomycin phosphate (100µg/ml) and penicillin G (10I.U./ml), but is sensitive to cephaloridine (100µg/ml), lincomycin hydrochloride (100µg/ml), neomycin sulphate (50µg/ml), rifampicin (50µg/ml), streptomycin sulphate (100µg/ml),Town tobramycin sulphate (50µg/ml) and vancomycin hydrochloride (50µg/ml).

Strain Y22 is able to utilise D(+)-glucose, maltose, sucrose,Cape trehalose and D(+)-xylose as sole carbon sources, growing weakly on L(+)-arabinose,of D(+)-cellobiose, D(–)-fructose, α-lactose, D(+)- mannose, melibiose, L(+)-rhamnose, ribose, salicin, sodium acetate and sorbitol. It is unable to utilise adonitol, glycerol, myo-inositol, inulin, D(–)-mannitol, D(+)-melezitose, raffinose, sodium citrate or sodium succinate as sole carbon sources. L-Asparagine, L-histidine, L-4-hydroxyproline, L-methionine, potassium nitrate and L-serine are utilised as sole nitrogen sources by strain Y22, however DL-α-amino-n-butyric acid, L-cysteine, L-phenylalanine, L-threonine and L-valine are not utilised as sole nitrogenUniversity sources. Nitrate is only weakly reduced to nitrite and H2S is produced. Casein, gelatin, Tween 80 and L-tyrosine are degraded, whilst xylan is only weakly degraded and adenine, allantoin, cellulose, guanine, hypoxanthine, urea and xanthine are not degraded by strain Y22. Aesculin, arbutin and starch are all hydrolysed. Strain Y22 is resistant to penicillin G (10I.U./ml) and weakly resistant to oleandomycin phosphate (100µg/ml), but is sensitive to cephaloridine (100µg/ml), lincomycin hydrochloride (100µg/ml), neomycin sulphate (50µg/ml), rifampicin (50µg/ml), streptomycin sulphate (100µg/ml), tobramycin sulphate (50µg/ml) and vancomycin hydrochloride (50µg/ml).

149

Interestingly, neither strains Y21 nor Y22 were able to grow on the standard carbon and nitrogen source utilisation test media (Shirling & Gottlieb, 1966; Williams et al., 1989), producing barely visible growth on all of the tested carbon and nitrogen sources. Due to this problem, the media were supplemented with yeast extract to a final concentration of 0.05% (w/v) to allow for the growth of both isolates. This was the lowest concentration of yeast extract at which both strains showed growth and clear differentiation could be made between the negative and positive controls. M. olivasterospora NRRL 8178T grew on the standard test media but, for the purposes of comparison, was also tested on the media that had been supplemented with 0.05% (w/v) yeast extract. It should be noted, however, that there was no difference between the carbon and nitrogen source utilisation of M. olivasterospora NRRL 8178T between the standard and the supplemented media.

The phenotypic differences between strains Y21, Y22 and related type species are shown in Table 3.4.5. There are nine differences between strains Y21 and Y22, with eight of these being differences in carbon or nitrogen source utilisation and the other being growth Townat 3% (w/v) NaCl. Both strains Y21 and Y22 have 17 differences to M. olivasterospora, with 12 of these differences being common to both strains Y21 and Y22 and two being differences in antibiotic resistance. The limited published data available for the other two comparedCape strains did not allow for a comprehensive comparison to be made. However, from the availableof data it can been seen that both strains Y21 and Y22 show three differences to M. viridifaciens, while strain Y21 shows six, and strain Y22 shows five differences to M. auratinigra. Furthermore, strains Y21 and Y22 show differences in colony colour and in the production of diffusible pigments to these species with validly-published names and have a different whole cell sugar pattern to that of M. viridifaciens (which lacks arabinose).

These data suggest thatUniversity strains Y21 and Y22 are different from their closest relative, M. olivasterospora. However, DDH will need to be performed to determine whether they are separate genomic species from M. olivasterospora (and from each other). A more detailed phenotypic analysis of the other two type strains (M. auratinigra and M. viridifaciens) will also need to be performed.

150

Table 3.4.5 Physiological differences between strains Y21, Y22 and related Micromonospora species. Test Y21 Y22 1$ 2 3 Cell wall sugars ara, glc, ara, glc, ara, glc, glc, rib & ara & xyl rib & xyl rib & xyl rib & xyl xyl Colour of substrate mycelium light dark orange to yellow to orange to orange orange green nut brown black Colour of diffusible pigments none none olive none brown Growth at: 3% (w/v) NaCl +w – – ND – pH 5 +w +w – ND ND

H2S production + + +w ND – Nitrate Reduction +w +w – ND – Degradation of: L-Tyrosine + + + ND – Xylan +w +w – ND ND Utilisation as sole carbon source: L(+)-Arabinose +w +w – +w + myo-Inositol + – – +w ND α-Lactose +w +w – ND + Mannitol – – – +w – D(+)-Melibiose +w +w – ND + Raffinose – – +wTown +w + L(+)-Rhamnose – +w – +w – Salicin – +w +w ND + Sodium acetate – +w – ND ND Sodium citrate +w – +w ND ND Sodium succinate +w – +w ND ND D(–)-Sorbitol + Cape +w – ND ND Utilisation as sole nitrogen source: L-Cysteine –of – +w ND ND L-Histidine – + + ND ND L-Methionine + + – ND ND L-Threonine – – + ND ND L-Valine +w – – ND ND Resistance to: Lincomycin hydrochloride (100µg/ml) – – +w ND ND Tobramycin sulphate (50µg/ml) – – + ND ND 1, Micromonospora olivasterospora DSM 43868T (Kawamoto et al., 1983); 2, Micromonospora viridifaciens DSM 43909T (Kroppenstedt et al., 2005); 3, Micromonospora auratinigra DSM 44815T (Thawai et al., 2004) $ Data determined in this study. Ara, arabinose; glc, glucose; rib, ribose; xyl, xylose. Symbols: +, positive; +w, weak positive; –, negative;University ND, no data available.

3.4.2.4 Isolates belonging to the genus Nocardia Isolates C2 and SE(7)1 were both shown to be non-streptomycetes by the rapid molecular identification method (section 2.4.3) and confirmed to belong to the genus Nocardia by performing blastn analysis (section 3.4.1). A phylogenetic tree was constructed with all the type strains of the genus Nocardia to determine the position of each isolate within the genus. Initially it was noted that strain C2 clustered with Nocardia flavorosea JCM 3332T, a species with which the lab strain ‘Nocardia rhamnosiphila’ 202GMOT (isolated by a fellow lab member) is also known to cluster. 151

This strain has been shown to be distinct from N. flavorosea by DDH and physiological characterisation (P. Meyers, personal communication) and was therefore included as a reference when constructing the phylogenetic tree. The phylogenetic position of the two isolates can be seen in Fig 3.4.6, which shows the clustering of each strain within its sub-tree (the whole-genus 16S rRNA gene tree is shown in Appendix C).

Based on the 16S rRNA gene, the closest relative of strain C2 was shown to be ‘N. rhamnosiphila’ with very high bootstrap support (95%), with N. flavorosea being the next closest relative. Nocardia carnea ATCC 6847T, followed by Nocardia sienata IFM 10088T and Nocardia testacea JCM 12235T, formed the next branchings respectively, with Nocardia speluncae N2-11T grouping on the periphery of all of these strains. This entire cluster grouped near the base of the Nocardia tree, on the periphery of the taxospace encompassed by all the other type strains with the exception of Nocardia pigrifrangens JCM 11884T, which formed the outermost Nocardia branch of the tree (Appendix C). Isolate SE(7)1 was most closely related to Nocardia Townfluminea DSM 44489T with low bootstrap support (< 40%), with both of these strains branching off the cluster defined by Nocardia cummidelens DSM 44490T, Nocardia salmonicida DSM 40472T and Nocardia soli DSM 44488T. The pairing of Nocardia coubleae OFN N11T and NocardiaCape ignorata IMMIB R-1434T branched off from these strains, with the entire cluster to whichof strain SE(7)1 belongs grouping within the centre of the Nocardia tree (Appendix C).

The phylogeny based on the gyrB gene is shown in Fig 3.4.7. Although somewhat different to the 16S rRNA gene tree, the grouping of strains into similar clusters was conserved in the gyrB gene based tree. Strain C2 still formed a close association with ‘N. rhamnosiphila’ with very high bootstrap support (100%),University however N. sienata and N. testacea were now the next most closely related strains and N. flavorosea grouped further away but remained in the same cluster. The association of the N. sienata-N. testacea pair with the strain C2-‘N. rhamnosiphila’ pair was supported by a very high bootstrap value (100%). For strain SE(7)1, the clustering between strains changed somewhat compared to the 16 rRNA gene tree, however there was still a close association of strain SE(7)1 to N cummidelens, N. salmonicida and N. soli, with N. alba forming a closer affiliation and N. fluminea now grouping on the periphery of all these strains. The bootstrap values for the branches in the strain SE(7)1 cluster were high (≥ 86%).

152

*95 Strain C2 A ‘Nocardia rhamnosiphila’ 202GMOT (EF418604)

Nocardia flavorosea JCM 3332T (Z46754) 71 Nocardia carnea ATCC 6847T ( X80602) Nocardia sienata IFM 10088T (AB121770) *99 Nocardia testacea JCM 12235T (AB192415) Nocardia speluncae N2-11T (AM422449)

0.002

T B *99 Nocardia cummidelens DSM 44490 (AF430052) *54 Nocardia soli DSM 44488T (AF430051)

98 Nocardia salmonicida DSM 40472T (AF430050) Strain SE(7)1 99 * Nocardia fluminea DSM 44489T (AF430053) Nocardia coubleae OFN N11T (DQ235688) * Town *99 Nocardia ignorata IMMIB R-1434T (AJ303008)

Nocardia jejuensis N3-2T (AY964666) 73 Nocardia alba YIM 30243T (AY222321) Nocardia ninae OFNCape 02.72T (DQ235687)

0.002 of Figure 3.4.6 Sub-trees of the unrooted 16S rRNA gene phylogenetic tree showing the position of strains C2 and SE(7)1 within the genus Nocardia. The two sub-trees showing the position of strains C2 (A) and SE(7)1 (B) within the genus forms part of the neighbour joining tree that was constructed with all type strains belonging to the genus Nocardia, based on 1277nt of common 16S rRNA gene sequence (Appendix C). Values at each node are the percentage bootstrap values of 1000 replications (only values above 50% are shown), with asterisks (*) indicating the clades that were conserved in all three tree drawing algorithms (section 3.3.1.3). Accession numbers are indicated in parenthesis after the strain numbers. The scale bars indicate 2 nucleotide substitutions per 1000 nucleotides.

University The 16S rRNA gene sequence similarity between strain C2 and its closest relative ‘N. rhamnosiphila’ is 99.93% (over 1463nt) and that to N. flavorosea is 99.24% (1454nt). The similarity of strain C2 to the other members of the cluster are 99.0% (1395nt) to N. carnea, 99.36% (1414nt) to N. sienata, 99.24% (1454nt) to N. testacea and 98.22% (1405nt) to N. speluncae. Strain SE(7)1 shows 16S rRNA gene sequence similarity values of 99.07% (over 1390nt) to its closest relative N. fluminea, 98.92% (1390nt) to N. salmonicida, 99.14% (1390nt) to both N. cummidelens and N. soli, with the similarity values to other members of the cluster being below 98.5% (>1300nt). 153

Strain C2 *100 A ‘Nocardia rhamnosiphila’ 202GMOT *100 Nocardia sienata IFM 10088T (AB450807) 97 *94 Nocardia testacea IFM 0937T (AB450810) Nocardia jinanensis DSM 45048T Nocardia flavorosea IFM 0851T (AB450787) *50 Nocardia carnea IFO 14403T (AB075569) 100 *100 *85 Nocardia speluncae DSM 45078T Nocardia pigrifrangens IFM 10533T (AB450800)

0.01

T *99 Nocardia cummidelens IFM 10176 (AB450783) B *90 Nocardia soli IFM 10177T (AB450808) *88 Nocardia salmonicida IFO 13393T (AB075568) *86 Strain SE(7)1 *100 Town Nocardia alba IFM 10588T (AB453918)

Nocardia fluminea IFM 10138T (AB450788) *79 Nocardia caishijiensis IFM 10344T (AB450775) *99 Nocardia ignorataCape IFM 10475 T (AB450790)

0.01 of Figure 3.4.7 Sub trees of the unrooted gyrB phylogenetic tree showing the relationship of strains C2 and SE(7)1 to members of the genus Nocardia. The two sub-trees showing the position of strains C2 (A) and SE(7)1 (B) within the genus form part of the neighbour joining tree that was constructed with the gyrB sequences of all Nocardia type strains for which gyrB sequences are available (Appendix D). The tree was based on 1147nt of common sequence and Streptomyces avermitilis MA-4680T (NC_003155) was used as an outgroup. Values at each node are the percentage bootstrap values of 1000 replications (only values above 50% are shown), with asterisks (*) indicating the clades that were conserved in all three tree drawing algorithms (section 3.3.1.3). Accession numbers of the sequences obtained from public databases are indicated in parenthesis after the strain numbers, with the others being determined by P. Meyers. The scale bars indicate 1 nucleotide substitution per 100 nucleotides. University

Both strains C2 and SE(7)1 show the same chemotaxonomic characteristics, with their cell wall peptidoglycan containing meso-DAP and arabinose, galactose, glucose and ribose being present in the whole-cell hydrolysates. This type IV cell wall and type A whole-cell sugar pattern is consistent with their placement in the genus Nocardia (Lechevalier & Lechevalier, 1970).

The colonies of strain C2 appear smooth and are light pink in colour, producing white to pink aerial mycelium and taking on a flakey appearance with age. The colonies are fairly flat, not rising very much above the surface of the agar. No diffusible pigments are produced, nor is melanin produced 154 on ISP 6 or ISP 7. The strain can grow at pH 5-10 (with better growth at pH 10 than at pH 7) but not at pH 4.3, at 20-37°C but not at 45°C and in the presence of up to 5% (w/v) NaCl.

Strain C2 can utilise D(+)-galactose, D(+)-glucose, L(+)-rhamnose and trehalose as sole carbon sources, but grows only weakly on dulcitol, glycerol, maltose, salicin, sodium acetate, sodium citrate and sodium succinate. Strain C2 is unable to utilise adonitol, L(+)-arabinose, D(+)-cellobiose, D(–)- fructose, myo-inositol, inulin, α-lactose, D(–)-mannitol, D(+)-mannose, D(+)-melezitose, melibiose, raffinose, D(–)-ribose, D(–)-sorbitol, sucrose, xylitol or D(+)-xylose as sole carbon sources. L-Asparagine, L-cysteine, L-histidine, L-methionine, potassium nitrate, L-serine and L-valine are used as sole nitrogen sources, with only weak growth occurring on L-threonine. DL-α-Amino-n- butyric acid, L-4-hydroxyproline and L-phenylalanine are not used as sole nitrogen sources. Tween 80 is weakly degraded, but strain C2 is unable to degrade allantoin, casein, cellulose, gelatin, guanine, hypoxanthine, L-tyrosine, urea, xanthine or xylan. The strain is unable to grow on adenine degradation plates. Aesculin and arbutin are hydrolyzed by strain TownC2 but starch is not. Nitrate is reduced to nitrite and H2S is not produced. Strain C2 is resistant to lincomycin hydrochloride (100µg/ml), oleandomycin phosphate (100µg/ml), penicillin G (10I.U./ml) and rifampicin (50µg/ml), but is sensitive to cephaloridine (100µg/ml),Cape neomycin sulphate (50µg/ml), streptomycin sulphate (100µg/ml), tobramycin sulphate (50µg/ml)of and vancomycin hydrochloride (50µg/ml).

Strain SE(7)1 produces colonies that are raised and initially appear to be smooth, with substrate mycelium that is slightly pink to orange in colour and aerial mycelium that is white. The colonies appear flakey upon aging. Melanin is not produced on ISP 6 or ISP 7 and diffusible pigments are not produced. Strain SE(7)1 can grow at pH 4.3-10 (optimum pH 9), 20-30°C (but not at 37°C) and in the presence of up to 4%University (w/v) NaCl.

Strain SE(7)1 utilises D(–)-fructose, D(+)-glucose and glycerol as sole carbon sources, but grows only weakly on maltose, D(+)-mannose, D(–)-ribose, salicin, sodium acetate, sodium succinate and trehalose. Strain SE(7)1 is unable to utilise adonitol, L(+)-arabinose, D(+)-cellobiose, dulcitol, D(+)- galactose, myo-inositol, inulin, α-lactose, D(–)-mannitol, D(+)-melezitose, melibiose, raffinose, L(+)-rhamnose, sodium citrate, D(–)-sorbitol, sucrose, xylitol or D(+)-xylose as sole carbon sources. L-Asparagine, L-histidine, potassium nitrate and L-valine are used as sole nitrogen sources, with only weak growth occurring on DL-α-amino-n-butyric acid, L-cysteine, L-methionine, L-phenylalanine, L-serine and L-threonine. L-4-Hydroxyproline is not used as a sole nitrogen 155 source. Strain SE(7)1 degrades urea, weakly degrades allantoin, gelatin and Tween 80, but is unable to degrade adenine, casein, cellulose, guanine, hypoxanthine, L-tyrosine, xanthine or xylan. Aesculin and arbutin are hydrolyzed but starch is not. Nitrate is reduced to nitrite by strain SE(7)1 and H2S is produced. Strain SE(7)1 is resistant to lincomycin hydrochloride (100µg/ml), oleandomycin phosphate (100µg/ml) and penicillin G (10I.U./ml), but is sensitive to cephaloridine (100µg/ml), neomycin sulphate (50µg/ml), rifampicin (50µg/ml), streptomycin sulphate (100µg/ml), tobramycin sulphate (50µg/ml) and vancomycin hydrochloride (50µg/ml).

Summaries of the physiological characteristics that allow differentiation of isolates C2 and SE(7)1 from their closest phylogenetic relatives are shown in Table 3.4.6 and Table 3.4.7, respectively. Strain C2 shows nine physiological differences to ‘N. rhamnosiphila’ based on the data determined in this study, 13 differences to N. flavorosea (with there being another six characters that have conflicting results), six differences to N. carnea (with an additional two characters having conflicting results), four differences to N. sienata and three differences to N. Towntestacea, based on limited data. Furthermore strain C2 is unable to grow on adenine degradation plates, while N. flavorosea, N. carnea, N. sienata and N. testacea grow on this medium, but fail to degrade the substrate. Strain SE(7)1 has 11 physiological differences to N. flumineaCape based on the results determined in this study for the type strain. Six differences are notedof to N. salmonicida, four to N. soli and two to N. cummidelens, however it should be noted that only a limited number of characters were compared to these type strains.

When the physiological data are considered, strain C2 may represent a novel species, however the high level of 16S rRNA gene sequence similarity (99.93%) to ‘N. rhamnosiphila’ is somewhat problematic. This valueUniversity is larger than that between it and any other strain in the cluster as well as being larger than that between ‘N. rhamnosiphila’ and its closest relative, the type strain of N. flavorosea (99.31%), or that of the closely related N. sienata and N. testacea (99.86%). It cannot be concluded based solely on the data presented that strain C2 is a distinct species from ‘N. rhamnosiphila’, but it appears highly likely to be distinct from all the other members of its cluster. It further appears that strain SE(7)1 is likely to represent a novel species, especially considering that the 16S rRNA gene sequence similarity to its closest relative or any other member in its clade is below that between any of the closely related validly published species. The 16S rRNA gene sequence similarity between N. coubleae and N. ignorata is 99.09% while that between N. cummidelens and N. soli is 100%, with equally high levels of similarity (>99%) having been noted 156 between many Nocardia species (Yassin et al., 2003). This, along with the physiological data, makes a strong case for the creation of a novel species to accommodate this strain. In both cases however (but especially for strain C2), DDH will need to be performed to determine the species status of each isolate from its closest related strains.

Table 3.4.6 Physiological characteristics allowing differentiation of strain C2 from related Nocardia species. Test C2 1$ 2 3 4 5 Substrate mycelium colour pale pink orange orange cream to pale orange to pink peach yellow brick Growth at: pH 4.3 – +w (–*) ND ND ND ND 45°C – – + (–*●) –● – + 7% (w/v) NaCl – +w ++* ND ND ND

H2S production – + ND ND ND ND Nitrate reduction + + – (+*) + ND ND Degradation of: Adenine NG NG – – – – Tween 80 +w – ND ND ND Urea – – – Town– (+) – – Hydrolysis of: Aesculin ++ ++ –● (+*) + ND ND Arbutin ++ + +*● –● ND ND Starch – – + (–*) + ND ND Utilisation as sole carbon source: Adonitol – – Cape + * – – – L(+)-Arabinose – – – + – – Dulcitol +w +w (–*) –* ND ND ND D(–)-Fructose – of +w (–*) +w* ND ND ND D(+)-Galactose ++ + ND + – – Maltose +w +w +w* ND – – D(–)-Mannitol – – +● – (+●) ND – D(+)-Mannose – +w ND ND + – D(+)-Melibiose – +w (–*) –* ND ND ND L(+)-Rhamnose + + –*● – – + D(–)-Ribose – +w (– *) ND ND ND ND Sodium citrate +w +w –* (+●) –● ND ND Sorbitol – – +● (–*) +● ND ND Xylitol University– – + w* ND ND ND Utilisation as sole nitrogen source: L-Methionine + + (–*) +w* ND ND ND L-Serine ++ ++ –* ND ND ND L-Threonine +w +w (–*) –* ND ND ND L-Valine + – –* ND ND ND Resistance to: Cephaloridine (100µg/ml) – – +w* ND ND ND Oleandomycin phosphate (100µg/ml) + + –* ND ND ND Rifampicin (50µg/ml) + + –* ND ND ND 1, ‘Nocardia rhamnosiphila’ 202GMO; 2, Nocardia flavorosea JCM 3332T (Chun et al., 1998); 3, Nocardia carnea ATCC 6847T (Goodfellow & Lechevalier, 1989) ; 4, Nocardia sienata IMF 10088T (Kageyama et al., 2004); 5, Nocardia testacea IMF 0937T (Kageyama et al., 2004). $ data determined in this study. * data determined by P. Meyers (personal communication). ● data determined by Maldonado et al. (2000).  data determined by Isik et al. (1999).  data determined by Chun et al. (1998). Conflicting data are indicated in parentheses. Symbols: ++, strong positive; +, positive; +w, weak positive; –, negative; ND, no data available; NG, no growth. 157

Table 3.4.7 Physiological characteristics allowing differentiation of strain SE(7)1 from related Nocardia species. Test SE(7)1 1$ 2 3 4 Diffusible pigments none brown none none none Substrate mycelium colour pink to cream to pink pale pink orange brown to orange pale orange Growth at: 20°C + – + + + pH 4.3 +w +w (–) – ND – 5 % (w/v) NaCl – + ND – ND

H2S production + – ND ND ND Degradation of: Allantoin +w – (+) ND ND ND Casein – + (–) – – – Gelatin +w – ND ND ND Tween 80 +w + – + – L-Tyrosine – – (+) – + – Urea + +w (–) + + + Utilisation as sole carbon source: D(–)-Mannitol – – – + – D(+)-Mannose +w – ND ND ND Raffinose – +w ND – ND L(+)-Rhamnose – + – – – Sodium acetate +w +w (–) + Town+ + Sodium citrate – – (+) – + – D(–)-Sorbitol – – – + – Sucrose – +w ND ND ND Utilisation as sole nitrogen source: L-Phenylalanine +w +w ND – ND Resistance to: Cape Cephaloridine (100µg/ml) – +w – ND – of (16µg/ml) (16µg/ml) 1, Nocardia fluminea DSM 44489T (Maldonado et al., 2000); 2, Nocardia cummidelens DSM 44490T (Maldonado et al., 2000); 3, Nocardia salmonicida DSM 40472T (Isik et al., 1999); 4, Nocardia soli DSM 44488T (Maldonado et al., 2000). $ data determined in this study. Conflicting data are indicated in parentheses. Symbols: +, positive; +w, weak positive; –, negative; ND, no data available.

3.4.2.5 Isolates belonging to the genus Streptomyces The preliminary assignmentUniversity of the top nine antibiotic producing actinomycete strains (section 2.4.2) to the genus Streptomyces by the rapid molecular identification method (section 2.4.3) was confirmed by performing blastn analysis on their 16S rRNA genes (section 3.4.1). Phylogenetic trees were constructed with the Streptomyces type strains found to be most similar by BLAST analysis to determine the closest relatives of each strain. A single phylogenetic tree was then constructed with all the isolates and the determined type strains (Fig 3.4.8). Strain H17 clustered with Streptomyces fumanus NBRC 13042T with low bootstrap support (41%), with Streptomyces brasiliensis NBRC 101283T, Streptomyces anandii NBRC 13438T and Streptomyces naganishii NRRL B-1816T forming the next nearest neighbours. Strains S3.2, S3.5 and SE(7)3 grouped together and formed a cluster with strains S3.3, SE(6)11 and Y1 with high bootstrap support (100%). 158

The closest relatives to these isolates were Streptomyces celluloflavus NBRC 13780T and Streptomyces kasugaensis M338-M1T which grouped together and formed the closest branch (78% bootstrap support). Strain SE(6)5 branched off from the cluster of Streptomyces diastaticus subsp. diastaticus NBRC 3714T, Streptomyces gougerotii NBRC 13043T, Streptomyces rutgersensis subsp. rutgersensis NBRC 3727T and Streptomyces intermedius DSM 40372T with moderate bootstrap support (73%). Streptomyces aureoverticillatus NBRC 12742T, followed by Streptomyces koyangensis VK-A60T formed the next two branches. Strain Y2 formed a monophyletic line on the periphery of Streptomyces catenulae DSM 40258T, Streptomyces misakiensis IFO 12891T and Streptomyces ramulosus NRRL B-2714T with high bootstrap support (91%).

Strain H17 and S. fumanus have a 16S rRNA gene sequence similarity of 98.86% (1400nt), with S. anandii and S. brasiliensis sharing 98.79% (1398 and 1400nt) sequence similarity with strain H17. S. naganishii, Streptomyces cinereospinus NBRC 15397T and Streptomyces coeruleofuscus NBRC 12757T show 98.14%, 97.93% and 97.86% 16S rRNA gene similarityTown to strain H17, respectively (1399nt). The similarity of strains H17 and SE(6)5 is 97.47%, with that of strain H17 to any other isolate being below 95.32%. The 16S rRNA gene sequences of strains S3.2, S3.5 and SE(7)3 are identical (1398nt), as are those of strains S3.3, SE(6)11Cape and Y1 (1336nt), whilst these groupings share 99.93% sequence identity (1338nt). Theof sequence similarity of these strains to both S. celluloflavus and S. kasugaensis ranges form 98.22 to 98.31% (over ≥ 1344nt). These strains are about 97.6% similar to strain Y2 and 95.3% similar to strains H17 and SE(6)5. Strain SE(6)5 shows a 16S rRNA gene sequence similarity of 98.99% (1382nt) to S. intermedius, 98.84% (1384nt) to S. diastaticus subsp. diastaticus, S. gougerotii and S. rutgersensis subsp. rutgersensis, 98.41% (1382nt) to S. koyangensis and 98.34% (1385nt) to S. aureoverticillatus. The 16S rRNA gene sequence similarity between strainUniversity Y2 and S. ramulosus is 99.51% (1427nt) and to both S. catenulae and S. misakiensis is 98.81%. Strain Y2 is about 96.5% similar to strains H17 and SE(6)5 and 97.6% similar to the other isolates.

Basic physiological characterisation was performed on all nine Streptomyces isolates and the results are presented in Table 3.4.8. Morphological examinations were also performed, including determination of the spore chain morphology and spore surface ornamentation by SEM, the results of which are presented in Table 3.4.9, with selected micrographs being shown in Fig 3.4.9.

159

Strain S3.2 *64 Strain SE(7)3

*100 Strain S3.5 Strain SE(6)11

*78 Strain S3.3 *64 Strain Y1

Streptomyces celluloflavus NBRC 13780T (AB184476)

*100 Streptomyces kasugaensis M338-M1T (AB024441)

Streptomyces mobaraensis NRRL B-3729T (DQ442528) *50 Streptomyces coerulescens NBRC 12758T (AB184122) 83 Streptomyces ehimensis KCTC 9727T (AY999834) *100 Streptomyces luteoverticillatus NBRC 3840T (AB184803)

Streptomyces varsoviensis NRRL B-3589T (DQ026653) *98 Streptomyces ardus NBRC 13430T (AB184864)

*90 Streptomyces stramineus NBRC 16131T (AB184720)

Strain Y2

Streptomyces ramulosus NRRL B-2714T (DQ026662) 91 T 73 Streptomyces catenulae DSM 40258Town (AJ621613) * *100 Streptomyces misakiensis IFO 12891T (AB217605)

Streptomyces flavofungini NBRC 13371T (AB184359)

* Strain H17 Streptomyces fumanus NBRC 13042T (AB184273) * Cape *81 Streptomyces brasiliensis NBRC 101283T (AB249981)

*91 T 99 of Streptomyces anandii NBRC 13438 (AB184402) *80 Streptomyces naganishii NRRL B-1816T (DQ442529)

Streptomyces cinereospinus NBRC 15397T (AB184648)

*93 Streptomyces coeruleofuscus NBRC 12757T (AB184840)

Streptomyces koyangensis VK-A60T (AY079156)

Streptomyces aureoverticillatus NBRC 12742T (AB249919)

Strain SE(6)5 56 Streptomyces intermedius DSM 40372T (Z76686) 73 University Streptomyces rutgersensis subsp. rutgersensis NBRC 3727T (AB184795) 92 Streptomyces diastaticus subsp. diastaticus NBRC 3714T (AB184785) *99 Streptomyces gougerotii NBRC 13043T (AB249982)

Streptosporangium roseum DSM 43021T (X89947)

0.01

Figure 3.4.8 Unrooted 16S rRNA gene phylogenetic tree showing the position of the top nine antibiotic producing strains amongst selected Streptomyces type strains. The tree was constructed using the neighbour-joining method, based on 1329nt of common 16S rRNA gene sequence. Values at each node are the percentage bootstrap values of 1000 replications (only values above 50% are shown), with asterisks (*) indicating the clades that were conserved in all three tree drawing algorithms (section 3.3.1.3). Accession numbers are indicated in parenthesis after the strain numbers. The scale bar indicates 1 nucleotide substitution per 100 nucleotides. Streptosporangium roseum DSM 43021T was used as an outgroup.

160

Table 3.4.8 Physiological characteristics of the Streptomyces isolates. Test S3.2 S3.5 SE(7)3 SE(6)11 S3.3 Y1 Y2 H17 SE(6)5

H2S Production +w – – – – – + + – Nitrate Reduction – + – – – – +w – +w Growth at: 2% (w/v) NaCl ++ ++ ++ +++ +++ +++ +++ ++ ++ 4% (w/v) NaCl ++ + ++ ++ ++ +++ + + + 7% (w/v) NaCl +w + + +w + ++ + +w – 37°C + ++ + + ++ ++ +w + + pH 4.3 + ++ ++ ++ + ++ + + ++ pH 9 ++ ++ ++ ++ ++ ++ +++ ++ ++ Degradation of: Adenine + + + + + + + – + Allantoin – +w – – + + +w – +w Casein + + + + + + + + + Cellulose – – – – – – – – – Gelatin + + + + + + + + + Guanine – – – – – – – – – Hypoxanthine + + + + + + + + + Tween 80 + + – + + + + + + L-Tyrosine + + + + + + + + + Urea – – – – + – +w – +w Xanthine +w + +w – – + – + + Xylan – – – – – Town – – – – Hydrolysis of: Aesculin ++ ++ ++ ++ ++ ++ – ++ + Arbutin + ++ ++ + + ++ – + + Starch + + + + + + + + + Pectin – – – – – – – + – Symbols: +++, growth stronger than the positive control; ++, strongly positiveCape (growth equal to the positive control); +, positive (growth but less than the positive control); +w, weakly positive; –, negative. of

Table 3.4.9 Morphological characteristics of the Streptomyces isolates. S3.2 S3.5 SE(7)3 SE(6)11 S3.3 Y1 Y2 H17 SE(6)5 Substrate white to yellow – yellow – brown to yellow – yellow – yellow – yellow – yellow – mycelium cream brown brown black brown brown brown brown brown Aerial white to white white to grey white to white grey white to grey to mycelium grey grey grey grey brown Spore chain SP RF RP SP RF RF RF SP SP morphology University Spore surface smooth smooth smooth smooth smooth smooth smooth smooth smooth ornamentation The spore chain morphologies and spore surface ornamentations were determined from growth on ISP 4, except for strain S3.5 which was determined from growth on YEME. Plates were incubated for 14 days at 30°C. Symbols: RF, Rectiflexibiles; RP, Retinaculiaperti; SP, Spirales

Comparisons of the physiological characteristics between the two closely related groups of strains (S3.2 and SE(6)11 group) revealed that, although they are very similar, they do show slight differences. Strain S3.5 shows three differences to both strains S3.2 and SE(7)3, but strains S3.2 and SE(7)3 show only two differences to each other, as do all the members of the SE(6)11 group. The 161 comparison between the groups showed that the strains have between one and four differences to each other. Strain Y2 shows between four and eight physiological differences to the strains of these two groups, which is as expected given its phylogenetic position in relation to them. Similarly strains H17 and SE(6)5 cluster away from these strains and show varying numbers of differences. They are clearly unrelated to strain Y2 or to any of the strains in the S3.2 and SE(6)11 groups. Strains H17 and SE(6)5 show seven phenotypic differences to each other and are clearly distinct by virtue of both their phylogenetic position and low level of 16S rRNA gene sequence similarity. Morphologically all the strains are fairly similar, showing no striking differences in colony colour or pigmentation. There are differences in spore chain morphology between closely related strains (in the S3.2 and SE(6)11 groups), but this is not uncommon between strains of the same cluster within the genus (Williams et al., 1989).

Town

Cape of

University

Figure 3.4.9 Scanning electron micrographs of selected Streptomyces isolates. A. The Spirales spore chains of strain H17. B. The Spirales spore chains of strain S3.2. C. The Retinaculiaperti spore chains of strain SE(7)3. D. The smooth spores of strain Y2 in Rectiflexibiles spore chains.

162

A summary of the physiological and morphological differences between the related strains and type strains are shown in Tables 3.4.10 and 3.4.11. As can be seen, limited data are available in the literature for the related type strains and therefore the likelihood of the isolates being separate based on physiological differences cannot be clearly determined. Based on this limited data, strain H17 shows no differences to S. fumanus, but shows four to S. brasiliensis. Strain SE(6)5 shows two differences to S. aureoverticillatus and three to S. intermedius and S. diastaticus subsp. diastaticus. Strain Y2 shows a single difference to each of S. ramulosus and S. catenulae with two differences noted to S. misakiensis. The six strains in the S3.2 cluster all show a single difference to S. celluloflavus, with two (and another with a variable result) to S. kasugaensis. More extensive phenotypic testing and DDH analysis needs to be performed on these type strains to allow for them to be definitively differentiated from the isolates. This being said, the isolates do share what for this genus can be considered to be fairly low levels of 16S rRNA gene sequence similarity to the type strains and therefore may in fact be separate species. Town

Table 3.4.10 Characters allowing differentiation of strains H17 and SE(6)5 from each other and their respective related Streptomyces type strains. Test H17 1 2 Cape SE(6)5 3 4 5  H2S production + + + – +* + +* Nitrate reduction – ND of –* +w –* – – Growth at 7% (w/v) NaCl +w + –* – +* –* – Degradation of: Adenine – ND ND + ND ND ND Allantoin – ND ND +w ND ND ND Urea – ND ND +w ND ND ND Xanthine + + –* + + + + Hydrolysis of: Arbutin + + – + + + + Pectin + ND –* – – – + 1, Streptomyces fumanus NBRC 13042T; 2, Streptomyces brasiliensis NBRC 10128T; 3, Streptomyces intermedius DSM 40372UniversityT; 4, Streptomyces aureoverticillatus NBRC 12742T; 5, Streptomyces diastaticus subsp. diastaticus NBRC 3714T. The data for all type strains were taken from Williams et al. (1989). * 70 – 85% of strains produce this result.  67% of strains produce this result.  53% of strains produce this result. Symbols: +, positive; +w, weak positive; –, negative; ND, no data available. 163

Table 3.4.11 Characters allowing differentiation of strains S3.2, S3.3, S3.5, SE(6)11, SE(7)3, Y1 and Y2 from each other and related Streptomyces type strains. Test S3.2 S3.5 SE(7)3 SE(6)11 S3.3 Y1 1 2 Y2 3 4 5 Colour of aerial mycelium white to white white to grey white to white yellow to olive grey grey grey white to grey grey grey greenish grey grey – yellow Colour of substrate mycelium white to yellow – yellow – brown to yellow – yellow – yellow – yellow – yellow – yellow – yellow – ND cream brown brown black brown brown brown brown brown to brown or brown

Town red – green

orange Spore chain morphology SP RF RP SP RF RF RF SP RF RP RP RF

H2S production +w – – – – – ND ND + ND ND ND Nitrate reduction – + – – – – ND + +w ND ND ND Growth at 7% (w/v) NaCl +w + + +w + ++ ND ND + + +* – Degradation of: Cape Allantoin – +w – – + + ND ND +w ND ND ND Gelatin + + + + of + + – + + ND ND ND Tween 80 + + – + + + ND ND + ND ND ND Urea – – – – + – ND ND +w ND ND – Xanthine +w + +w – – + ND ND – + +* +* Hydrolysis of: Aesculin ++ ++ ++ ++ ++ ++ + ND – ND ND ND Arbutin + ++ ++ + + ++ ND ND – ND ND – Starch + + + + + + + – + ND ND ND 1, Streptomyces celluloflavus NBRC 13780T; 2, Streptomyces kasugaensis M338-M1T (Hamada et al., 1995); 3, Streptomyces ramulosus NRRL B-2714T; 4, Streptomyces catenulae DSM 40258T; 5, Streptomyces misakiensis IFO 12891T. All data for the unreferenced type strains were taken fromUniversity Williams et al. (1989). * 11-89% of strains produce this result. Symbols: ++, strong positive; +, positive; +w, weak positive; –, negative; ND, no data available; RF, Rectiflexibiles; RP, Retinaculiaperti; SP, Spirales. 164

3.4.2.6 Isolate belonging to the genus Verrucosispora The third isolate (Y25) that was shown to belong to one of six genera within the family Micromonosporaceae by the rapid molecular identification method (section 2.4.3) was shown to belong to the genus Verrucosispora based on the results of blastn analysis (section 3.4.1). This genus currently only contains two species with validly-published names, with the description of a third (‘Verrucosispora sediminis’) in press. A phylogenetic tree was therefore constructed with all the type species plus at least one other species (where the genus contained multiple species) of all the genera within the family Micromonosporaceae. If the genus contained fewer than five species all were included as reference strains. The resulting phylogenetic tree (Fig 3.4.10) showed that strain Y25 is most closely related to Verrucosispora gifhornensis HR1-2T with both Verrucosispora lutea YIM 013T and ‘V. sediminis’ MS426T (which are most closely related to each other) clustering adjacent to this pair. Town The 16S rRNA gene sequence of strain Y25 is 99.86% similar (over 1379nt) to that of V. gifhornensis, with the similarities to V. lutea and ‘V. sediminis’ being 98.63% (1382nt) and 98.99% (1379nt), respectively. The similarity between V. gifhornensis and V. lutea or ‘V. sediminis’ is 98.31% (1417nt) and 98.89% (1437nt), respectively, Capewhile that between V. lutea and ‘V. sediminis’ is 98.44% (1411nt). Strain Y25 clustered withof V. gifhornensis with 100% bootstrap support (Fig 3.4.10) and is clearly associated with the genus Verrucosispora, the four strains of which clustered with very high bootstrap support (99%).

Strain Y25 was found to have meso-DAP and glycine present in the cell wall peptidoglycan and the whole-cell sugar pattern contained glucose, mannose, ribose and xylose. The strain thus has a cell wall chemotype II withUniversity no definable cell wall sugar pattern, as the only diagnostic sugar present is xylose (Lechevalier & Lechevalier, 1970). These chemotaxonomic characters are consistent with those of the genus Verrucosispora (Rheims et al., 1998).

The colonies of strain Y25 appear convoluted and have fairly irregular edges. The colour of the colonies is initially a dark orange, becoming increasingly darker upon aging, progressing from orange to red-brown and ultimately appearing black. The texture of the colony also changes with age. Initially the colonies are firm and slightly rubbery, but become softer with age and finally take on a mucoid texture. No visible aerial mycelium is produced and the substrate mycelium fragments in both solid and liquid culture. No diffusible pigments are produced on ISP 5, however an orange- 165 brown pigment is produced on YEME as well as on most other rich media. Melanin is not produced on ISP 6 or ISP 7. Growth occurs at 20, 30 and 37°C (but not at 45°C), at pH 7-10 (optimal at pH 9 and no growth at pH 5 or below) and in the presence of up to 4% (w/v) NaCl but not at 5% (w/v) NaCl.

Strain Y25 is able to utilise L(+)-arabinose, D(+)-cellobiose, D(+)-glucose, maltose, D(+)-mannose, salicin, sucrose, trehalose and D(+)-xylose as sole carbon sources, grows weakly on α-lactose and sodium acetate, but is unable to utilise adonitol, dulcitol, D(–)-fructose, D(+)-galactose, glycerol, myo-inositol, inulin, D(–)-mannitol, D(+)-melezitose, melibiose, raffinose, L(+)-rhamnose, D(–)- ribose, sodium citrate, sodium succinate, D(–)-sorbitol or xylitol as sole carbon sources. L-Asparagine, L-cysteine, L-histidine, L-4-hydroxyproline, L-methionine, L-phenylalanine, L- serine, L-threonine and L-valine are used as sole nitrogen sources, with weak growth occurring on potassium nitrate. Strain Y25 is unable to utilise DL-α-amino-n-butyric acid as a sole nitrogen source. Strain Y25 is able to degrade casein, gelatin, Tween 80 Town and L-tyrosine, weakly degrade xylan, but is unable to degrade adenine, allantoin, cellulose, guanine, hypoxanthine, urea or xanthine.

Aesculin and starch are hydrolyzed but arbutin is not. H2S is produced by strain Y25, but nitrate is not reduced to nitrite. Strain Y25 is resistant to cephaloridineCape (100µg/ml), oleandomycin phosphate (100µg/ml) and penicillin G (10I.U./ml), weaklyof resistant to lincomycin hydrochloride (100µg/ml) and sensitive to neomycin sulphate (50µg/ml), rifampicin (50µg/ml), streptomycin sulphate (100µg/ml), tobramycin sulphate (50µg/ml) and vancomycin hydrochloride (50µg/ml).

There are only five clear physiological differences between strain Y25 and V. gifhornensis, whilst there are 19 differences to V. lutea and 11 to ‘V. sediminis’, with there being chemotaxonomic differences noted to bothUniversity the latter two strains as well. These differences are shown in Table 3.4.12.

Based on the data presented, it is clear that strain Y25 does not to belong to either V. lutea or ‘V. sediminis’ by virtue of the significant number of physiological differences between them. However, its standing in relation to its closest relative, V. gifhornensis, is not that clear. The limited number of physiological differences between them makes it difficult to conclude if they represent distinct species and DDH experiments are required to determine if they do.

166

T *100 Verrucosispora gifhornensis HR1-2 (Y15523) *99 Strain Y25 Verrucosispora lutea YIM 013T (EF191199) *80 ‘Verrucosispora sediminsis’ MS426T (EU870859)

Catenuloplanes crispus JCM 9312T (AB024701)

*98 Catenuloplanes japonicus DSM 44102T (AJ865470) Asanoa ferruginea DSM44099T (X93199)

T 100 Asanoa iriomotensis TT 97-02 (AB112081) 52 Asanoa ishikariensis IMSNU 22004T (AJ294715)

Spirilliplanes yamanashiensis IFO 15828T (D63912) *64 Krasilnikovia cinnamomea 3-54(41)T (AB236956)

Pseudosporangium ferrugineum 3-44-a-19T (AB302183) *79 T *99 Couchioplanes caeruleus ssp. azureus IFO 13939 (D85478) *68 Couchioplanes caeruleus ssp. caeruleus IFO 13939T (D85479)

Polymorphospora ruber TT 97-42T (AB223089)

T *99 Micromonospora chalcea ATCC 12452 (X92594) Micromonospora echinspora DSM43816T (X92607)

Plantactinospora mayteni YIM 61359T (FJ214343)

Salinispora arenicola ATCC BAA-917T (AY040619) *100 Salinispora tropica CNB-440T (AY040617) Actinoplanes lobatus IFO 12513T (AB037006) Town *100 Actinoplanes philippinensis DSM 43019T (X93187)

T *100 Actinocatenispora sera KV-744 (AB263096) Actinocatenispora thailandica TT2-10T (AB107233) Pilimelia anulata DSM 43039T (X93189) *100 Pilimelia terevasa DSM 43040CapeT (X93190) T *100 Rugosimonospora acidiphila Delta1 (FM208261) Rugosimonospora africana Delta3ofT (FM208262) T *99 Dactylosporangium aurantiacum ATCC23491 (DAU58528) Dactylosporangium roseum DSM 43916T (X93194)

Planosporangium flavigriseum YIM 46034T (AM232832)

Virgisporangium ochraceum YU655-43T (AB006167)

*100 Virgisporangium aurantiacum YU438-5T (AB006169) Luedemannella flava 7-40(26)T (AB236959) 50 *100 Luedemannella helvata 3-9(24)T (AB236957)

Longispora albida K97-0003T (AB089241) University Hamadae tsunoense IMSNU 22005T (AF152110) Catellatospora bangladeshensis 2-70(23)T (AB200233)

*99 Catellatospora citrea DSM 44097T (X93197)

Catelliglobosispora koreensis LM042T (AF171700)

Saccharomonospora paurometabolica YIM90007T (AF540959)

0.01 Figure 3.4.10 Unrooted 16S rRNA gene phylogenetic tree showing the relationship of strain Y25 to that of members of the genus Verrucosispora and all other genera in the family Micromonosporaceae. The tree was constructed using the neighbour-joining method based on 1376nt of sequence. Values at each node are the percentage bootstrap values of 1000 replications (only values above 50% are shown), with asterisks (*) indicating the clades that were conserved in all three tree drawing algorithms (section 3.3.1.3). The type species of each genus is underlined. Accession numbers of the sequences are indicated in parentheses after the strain numbers. The scale bar indicates 1 nucleotide substitution per 100 nucleotides. Saccharomonospora paurometabolica YIM90007T was used as an outgroup.

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Table 3.4.12 Physiological characteristics allowing differentiation of strain Y25 from known Verrucosispora species Test Y25 1$ 2 3 Cell wall sugars glc, man, glc, man, glc & xyl glc, glcN & rib & xyl rib & xyl man Substrate mycelium colour orange to vivid yellow to orange to black orange orange brown Colour of diffusible pigments orange orange none none brown

H2S production + +w – – Nitrate reduction – – + + Growth at: 20°C + – + + 45°C – – + + 5% (w/v) NaCl – – + + 7% (w/v) NaCl – – + – Hydrolysis of: Aesculin + + – ND Arbutin – + ND – Degradation of: Casein + + – + Gelatin + + – ND L-Tyrosine + – ND ND Utilisation as sole carbon source: Town Dulcitol – – + ND D(–)-Fructose – +w + ND D(+)-Galactose – – + ND Glycerol – – + + D(+)-Melibiose – Cape– + + D(–)-Ribose – – + + Salicin + +w – + Sodium acetate +wof – ND ND Trehalose ++ + – + Utilisation as sole nitrogen source : L-Methionine + + – – L-Phenylalanine + + – – L-Valine + + – – 1, Verrucosispora gifhornensis HR1-2T (Rheims et al., 1998); 2, Verrucosispora lutea YIM 013T (Liao et al., 2009); 3, ‘Verrucosispora sediminis’ MS426T (Dai et al., 2010). $ Data determined in this study. glc, glucose; glcN, glucosamine; man, mannose; rib, ribose; xyl, xylose. Symbols: ++,University strong positive; +, positive; +w, weak positive; –, negative; ND, not determined.

3.5 Discussion

For the Amycolatopsis isolates S1.3, S3.6 and SE(8)3, the data presented clearly illustrate that they are all distinct from the type strains with validly-published names. Furthermore it is clear from the DDH analysis that strain S3.6 is distinct from the other two strains, with strains S1.3 and SE(8)3 showing a borderline DDH value. However, when considered in conjunction with the physiological data, it can be argued that these strains belong to separate species. It should also be noted that although 70% DNA relatedness by DDH is the value that has been used as the threshold for 168 distinguishing between species, it is not a clear-cut boundary and values within a 10% range either side of this value may in actual fact be considered to show that the strains belong to separate species, when viewed with the phenotypic data (Wayne et al., 1987; Stackebrandt & Goebel, 1994). Therefore DDH always needs to be supported by physiological evidence to warrant the creation of a new species (Wayne et al., 1987; Stackebrandt & Ebers, 2006). This is the case here where strains S1.3 and SE(8)3 can clearly be seen to be physiologically different.

Kribbella strain S1.4 was also shown to be a novel member of the genus Kribbella by virtue of the low DDH value to its closest phylogenetic relative and multiple physiological differences to related type strains and was subsequently published as such in the International Journal of Systematic and Evolutionary Microbiology as K. hippodromi (Everest & Meyers, 2008).

For the Micromonospora isolates Y21 and Y22, the data that were determined in this study are sufficient to show that these strains are most likely different fromTown the most closely related M. olivasterospora, owing to the large number of physiological differences found between them. However DDH will need to be performed to confirm this assumption, as they do share 16S rRNA gene sequence similarities of about 99%. Nevertheless,Cape it is not uncommon for different species to share even higher levels of 16S rRNA gene sequenceof similarity.

Strains Y21 and Y22 are also most likely different from both M auratinigra and M. viridifaciens, as there are notable differences within the limited data that are available for these published species, including components of the whole cell sugar patterns, carbon source utilisation and morphological differences. One would need to perform a far more detailed physiological analysis of these two type strains in order to allowUniversity for an accurate assessment of the novelty of strains Y21 and Y22. DDH would be needed in addition to physiological differences to differentiate strains Y21 and Y22 from both M. auratinigra and M. viridifaciens, as they share 16S rRNA gene sequence similarities above the 98.7% threshold, below which DDH is not required to be performed (Stackebrandt & Ebers, 2006). It should be noted that most of the groupings in Fig 3.4.5 show low levels of bootstrap support and therefore the clustering may in fact change with the addition of more strains into the tree.

For this reason the use of gyrB sequence analysis may be helpful, possibly resolving the problem of low bootstrap support and helping to improve the confidence of the phylogenetic clusterings. Unfortunately the gyrB gene could not be amplified from strains Y21 and Y22, however with the 169 increasing number of Micromonospora gyrB sequences becoming available (Kasai et al., 2000; Garcia et al., 2010; Kirby & Meyers, 2010), it may be possible to design new primers to amplify the gyrB gene from these two strains.

Although there are physiological differences between strains Y21 and Y22, their identical 16S rRNA gene sequences makes it seem unlikely that they represent different species and are most likely two strains belonging to the same species. However DDH will be needed to definitively determine the species status of these two isolates within the genus Micromonospora.

The high levels of 16S rRNA gene sequence similarity between the Nocardia strains C2 and SE(7)1 and their respective relatives are not unusual for members of this genus (Yassin et al., 2003). In fact the 16S rRNA genes of N. cummidelens and N. soli are identical, yet they are still considered to be separate species. The similarity of strain C2 to ‘N. rhamnosiphila’ is 99.93%, while the similarities to the other members in the cluster are all below 99.36%. For strainTown SE(7)1 the similarity to its closest relative N. fluminea is 99.07%, while that to N. cummidelens and N. soli is 99.14% with similarities to other cluster members being below 99%. Viewed in conjunction with the physiological and morphological differences to theirCape closest relatives, the isolates are likely to represent novel species within the genus, but DDHof will still be required to distinguish them as such. This is particularly true for strain C2.

Based on the limited data available for the Streptomyces isolates, it appears that strains S3.2, S3.5 and SE(7)3 are all strains of the same species. The same can be said for strains SE(6)11, S3.3 and Y1. It also seems likely that these two sub-groups may belong to the same species, as only two phenotypic differences Universityare noted between the sub-groups if the consensus result from each group is compared. The limited data available in the literature for the published type strains makes it difficult to draw conclusions as to the potential novelty of any of the isolates. Despite this, there are a few phenotypic differences between the isolates and some of their related type strains. However, these are insufficient to allow it to be concluded that they are distinct.

The 16S rRNA gene sequence similarities between any of the strains in the S3.2 cluster and their closest related type strains are well below 98.5%, which alone would suggest they are different from S. celluloflavus and S. kasugaensis (Stackebrandt & Ebers, 2006). All that is still required to show that they are a novel species are more physiological differences to the published type strains. 170

The other Streptomyces isolates, however, show varying levels of similarity to their closest relatives, with those for strain H17 being around 98.8%, strain SE(6)5 around 98.8 to 99%, whilst strain Y2 shows 99.51 and 98.81% to its closest related type strains. These values are not particularly high for this genus and many species share significantly higher levels of 16S rRNA gene similarity and are still considered to be separate species. Despite this, it is still likely that DDH will be required to differentiate these strains from the published species.

All this considered, along with the fact that these strains are known to produce highly active antibiotic compounds, they are all certainly worthy of further characterisation.

The 16S rRNA gene sequence similarity between strain Y25 and V. gifhornensis is fairly high when compared to that between other members of the genus. When viewed in conjunction with the five physiological differences found between the strains, it does not inspire the view that strain Y25 clearly represents a novel species. However, they are physiologicallyTown different and therefore may be different species. DDH would ultimately be needed to determine if strain Y25 is distinct from V. gifhornensis. The similarity between strain Y25 and the other two members of the genus is similar to those between the three type strains and therefore canCape be said to be separate from both V. lutea and ‘V. sediminis’. This is further supported by theof physiological data that shows that strain Y25 is significantly different from both of these species. In the end, DDH will be required to clearly identify the standing of strain Y25 within the genus.

As can be seen in most of the physiological difference tables presented here, there are multiple tests which show conflicting results between the different studies cited. This highlights the need for the use of standardised proceduresUniversity when testing strains and the need to conduct all of the relevant physiological testing in parallel. This will minimize the variability between experiments and ultimately allow for a more accurate assessment of the physiological uniqueness of isolated strains.

Although many of the isolated strains appear to be physiologically different from their closest relatives, the 16S rRNA gene sequence similarities of all but those strains in the Streptomyces S3.2 group are above the threshold value of 98.7% proposed to be the cut off above which DDH is mandatory to prove novelty (Stackebrandt & Ebers, 2006). For this reason none of these isolates can be said to novel without having first performed DDH to prove that they are distinct from their relatives. This is despite the fact that they may actually have 16S rRNA gene sequences similarities 171 that are not particularly high when compared to others within their genus. This mandatory requirement for DDH is particularly problematic for laboratories that are not able to perform these experiments themselves and can prove to be fairly costly to have done as a service. The fact that our laboratory is not able to perform DDH experiments spurred the search for alternative methods by which the genome similarity of closely related strains can be determined. The use of gene sequence based methods to predict genome similarity and/or to determine the novel species status of strains within the actinomycete genus Amycolatopsis is investigated in Chapter 4.

3.6 References

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Atlas, R. M. (2004). Handbook of Microbiological Media (3rd edition). Boca Raton, Fl: CRC Press. Town Busse, H.-J., Denner, E. B. M. & Lubitz, W. (1996). Classification and identification of bacteria: current approaches to an old problem. Overview of methods used in bacterial systematics. J Biotechnol 47, 3-38.

Carlsohn, M. R., Groth, I., Spröer, C., Schütze, B., Saluz, H.-P., Munder, T. and Stackebrandt, E. (2007). Kribbella aluminosa sp. nov., isolated from a medieval alum slate mine. Int J Syst Evol Microbiol 57, 1943-1947. Cape Chun, J., Seong, C.-N., Bae, K. S., Lee, K.-J., Kang, S.-O., Goodfellow, M. & Hah, Y. C. (1998). Nocardia flavorosea sp. nov. Int J Syst Bacteriol 48, 901-905. of Dai, H.-Q., Wang, J., Xin, Y.-H., Pei, G., Tang, S.-K., Ren, B., Ward, A., Ruan, J.-S., Li, W.-J. & Zhang, L.-Z. (2010). Verrucosispora sediminis sp. nov., a novel cyclodipeptide-producing actinomycete from the South China Sea. Int J Syst Evol Microbiol (In Press). doi: 10.1099/ijs.0.017053-0

De Ley, J., Cattoir, H., Reynaerts, A. (1970). The quantitative measurement of DNA hybridization from renaturation rates. Eur J Biochem 12, 133–142.

Ding, L., Hirose, T. & Yokota, A. (2007). Amycolatopsis echigonensis sp. nov. and Amycolatopsis niigatensis sp. nov., novel actinomycetes isolated from a filtration substrate. Int J Syst Evol Microbiol 57, 1747-1751. University Euzéby, J. P. (2010). List of Prokaryotic names with standing in nomenclature. Accessed November 2009 – February 2010. www.bacterio.cict.fr

Everest, G. J. & Meyers, P. R. (2008). Kribbella hippodromi sp. nov., isolated from soil from a racecourse in South Africa. Int J Syst Evol Microbiol 58, 443-446.

Everest, G. J. & Meyers, P. R. (2009). The use of gyrB sequence analysis in the phylogeny of the genus Amycolatopsis. Antonie van Leeuwenhoek 95(1), 1-11.

Garcia, L. C., Martínez-Molina, E. & Trujillo, M. E. (2010). Micromonospora pisi sp. nov., isolated from root nodules of Pisum sativum. Int J Syst Evol Microbiol 60, 331-337.

Goodfellow, M. & Lechevalier, M. P. (1989). Genus Nocardia Trevisan 1889, 9AL In Bergey’s Manual of Systematic Bacteriology, vol. 4, pp.2350-2361. Edited by S. T. Williams, M. E. Sharpe & J. G. Holt. Baltimore: Williams & Wilkins.

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Hasegawa, T., Takizawa, M. & Tanida, S. (1983). A rapid analysis for chemical grouping of aerobic actinomycetes. J Gen Appl Microbiol 29, 319-322.

Huang, Y., Qi, W., Lu, Z., Liu, Z. & Goodfellow, M. (2001). Amycolatopsis rubida sp. nov., a new Amycolatopsis species from soil. Int J Syst Evol Microbiol 51, 1093-1097.

Huss, V. A. R., Festl, H., Schleifer, K. H. (1983). Studies on the spectrophotometric determination of DNA hybridization from renaturation rates. Syst Appl Microbiol 4, 184–192.

Isik, K., Chun, J., Hah, Y. C. & Goodfellow, M. (1999). Nocardia salmonicida nom. rev., a fish pathogen. Int J Syst Bacteriol 49, 833-837.

Kageyama, A., Yazawa, K., Nishimura, K. & Mikami, Y. (2004). Nocardia testaceus sp. nov. and Nocardia senatus sp. nov., isolated from patients in Japan. Microbiol Immunol 48, 271-276.

Kasai, H., Tamura, T. & Harayama, S. (2000). Intrageneric relationships among Micromonospora species deduced from gyrB-based phylogeny and DNA relatedness. Int J Syst Evol Microbiol 50, 127-134.

Kawamoto, I., Yamamoto, M. & Nara, T. (1983). Micromonospora olivasterospora sp. nov. Int J Syst Bacteriol 33, 107-112.

Kirby, B. M., Everest, G. J. & Meyers, P. R. (2010). Phylogenetic analysis of theTown genus Kribbella based on the gyrB gene: proposal of a gyrB-sequence threshold for recognising new type strains of Kribbella. Antonie van Leeuwenhoek 97, 131-142.

Kirby, B. M., Le Roes, M. & Meyers, P. R (2006). Kribbella karoonensis sp. nov. and Kribbella swartbergensis sp. nov., isolated from soil from the Western Cape, South Africa. Int J Syst Evol Microbiol 56, 1097-1101. Cape Kirby, B. M. & Meyers, P. R. (2010). Micromonospora tulbaghiae sp. nov., isolated from the leaves of wild garlic, Tulbaghia violacea. Int J Syst Evol Microbiol (In Press). doi: 10.1099/ijs.0.013243-0 of Knight, V., Sanglier, J.-J., DiTullio, D., Braccili, S., Bonner, P., Waters, J., Hughes, D. & Zhang, L. (2003). Diversifying microbial natural products for drug discovery. Appl Microbiol Biotechnol 62, 446-458.

Komagata, K. & Suzuki, K. L. (1987). Lipid and cell-wall analysis in bacterial systematics. Methods Microbiol 19, 161-207.

Kroppenstedt, R. M., Mayilraj, S., Wink, J. M., Kallow, W., Schumann, P., Secondini, C. & Stackebrandt, E. (2005). Eight new species of the genus Micromonospora, Micromonospora citrea sp. nov., Micromonospora echinaurantiaca sp. nov., Micromonospora echinofusca sp. nov. Micromonospora fulviviridis sp. nov., Micromonospora inyonensis sp. nov., MicromonosporaUniversity peucetia sp. nov., Micromonospora sagamiensis sp. nov., and Micromonospora viridifaciens sp. nov. Syst Appl Microbiol 28, 328-339.

Liao, Z.-L., Tang, S.-K., Guo, L., Zhang, Y.-Q., Tian, X.-P., Jiang, C.-L., Xu, L.-H. & Li, W.-J. (2009). Verrucosispora lutea sp. nov., isolated from a mangrove sediment sample. Int J Syst Evol Microbiol 59, 2269-2273.

Lazzarini, A., Cavaletti, L., Toppo, G. & Marinelli, F. (2000). Rare genera of actinomycetes as potential producers of new antibiotics. Antonie van Leeuwenhoek 78, 399-405.

Lechevalier, H. A. & Lechevalier, M. P. (1981). Introduction to the order Actinomycetales. In: The Prokaryotes: a handbook on habitats, isolation and identification of bacteria, vol. 2, pp. 1915-1922. Edited by M. P. Starr, H. Stolp, H. G. Trüper, A. Balows, & H. G. Schlegel. Berlin, Germany: Springer-Verlag.

Lechevalier, M. P. and Lechevalier, H. (1970). Chemical composition as a criterion in the classification of aerobic actinomycetes. Int J Syst Bacteriol 20, 435-443.

Lee, S. D. (2006). Amycolatopsis jejuensis sp. nov. and Amycolatopsis halotolerans sp. nov., novel actinomycetes isolated from a natural cave. Int J Syst Evol Microbiol 56, 549-553. 173

Lee, S. D. & Hah, Y. C. (2001). Amycolatopsis albidoflavus sp. nov. Int J Syst Evol Microbiol 51, 645-650. le Roes, M., Goodwin, C. M., Meyers, P. R. (2008). Gordonia lacunae sp. nov. isolated from an estuary. Syst Appl Microbiol 31, 17-23.

Ludwig, W. (2007). Nucleic acid techniques in bacterial systematics and identification. Int J Food Microbiol 120, 225- 236.

Maldonado, L., Hookey, J. V., Ward, A. C. & Goodfellow, M. (2000). The Nocardia salmonicida clade, including descriptions of Nocardia cummidelens sp. nov., Nocardia fluminea sp. nov. and Nocardia soli sp. nov. Antonie van Leeuwenhoek 78, 367-377.

Minnikin, D. E., O’Donnell, A. G., Goodfellow, M., Alderson, G., Athalye, M., Schaal, A. & Parlett, J. H. (1984). An integrated procedure for the extraction of bacterial isoprenoid quinines and polar lipids. J Microbiol Methods 2, 233- 241.

Rheims, H., Schumann, P., Rohde, M. & Stackebrandt, E. (1998). Verrucosispora gifhornensis gen. nov., sp. nov., a new member of the actinobacterial family Micromonosporaceae. Int J Syst Bacteriol 48, 1119-1127.

Saitou, N. & Nei, M. (1987). The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 4, 406-425.

Shirling, E. B. and Gottlieb, D. (1966). Methods for characterization of Streptomyces species. Int J Syst Bacteriol 16, 313-340. Town

Song, J., Kim, B. Y., Hong, S. B., Cho, H. S., Sohn, K., Chun, J. & Suh, J. W. (2004). Kribbella solani sp. nov. and Kribbella jejuensis sp. nov., isolated from potato tuber and soil in Jeju, Korea. Int J Syst Evol Microbiol 54, 1345-1348.

Stackebrandt, E & Ebers, J. (2006). Taxonomic parameters revisited: tarnished gold standards. Microbiol Today 33, 152-155. Cape

Stackebrandt, E. & Goebel, B. M. (1994). Taxonomic note: a place for DNA-DNA reassociation and 16S rRNA sequence analysis in the present species definition in bacteriology.of Int J Syst Bacteriol 44, 846-849.

Takahashi, K. & Nei, M. (2000). Efficiencies of fast algorithms of phylogenetic inference under the criteria of maximum parsimony, minimum evolution, and maximum likelihood when a large number of sequences are used. Mol Biol Evol 17, 1251-1258.

Tamura, K., Dudley J., Nei, M. & Kumar, S. (2007). MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0. Mol Biol Evol 24, 1596-1599.

Tan, G. Y. A., Ward, A. C. & Goodfellow, M. (2006). Exploration of Amycolatopsis diversity in soil using genus- specific primers and novel selectiveUniversity media. Syst Appl Microbiol 29:7, 557-569.

Thawai, C., Tanasupawat, S., Itoh, T., Suwanborirux, K. & Kudo, T. (2004). Micromonospora aurantionigra sp. nov., isolated from a peat swamp forest in Thailand. Actinomycetologica 18, 8-14.

Wayne, L. G., Brenner, D. J., Colwell, R. R., Grimont, P. A. D., Kandler, O., Krichevsky, M. I., Moore, L. H., Moore, W. E. C., Murray, R. G. E., Stackebrandt, E., Starr, M. P. & Trüper, H. G. (1987). Report of the ad hoc committee on reconciliation of approaches to bacterial systematics. Int J Syst Bacteriol 37, 463-464.

Williams, S. T., Goodfellow, M. & Alderson, G. (1989). Genus Streptomyces Waksman and Henrici 1943, 339AL. In Bergey’s Manual of Systematic Bacteriology, vol. 4, pp. 2452-2492. Edited by S. T. Williams, M. E. Sharpe & J. G. Holt. Baltimore: Williams & Wilkins.

Yassin, A. F., Sträubler, B., Schumann, P. & Schaal, K. P. (2003). Nocardia puris sp. nov. Int J Syst Evol Microbiol 53, 1595-1599.

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CHAPTER 4

THE USE OF gyrB AND recNTown GENE SEQUENCES IN THE PHYLOGENETIC ANALYSIS OF THE GENUS Amycolatopsis Cape of

University

A section of this chapter has been published in the journal Antonie van Leeuwenhoek – Everest, G. J. & Meyers, P. R. (2009). The use of gyrB sequence analysis in the phylogeny of the genus Amycolatopsis. Antonie van Leeuwenhoek 95, 1-11. 176

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Contents

4.1 Summary 178 4.2 Introduction 179 4.3 Materials and methods 180 4.3.1 Bacterial strains and DNA extraction 180 4.3.2 PCR primers and primer design 180 4.3.2.1 Antibiotic biosynthetic primers 180 4.3.2.2 gyrB Gene primers 180 4.3.2.3 recN Gene primers 180 4.3.3 PCR amplification and gene sequencing 181 4.3.3.1 Antibiotic biosynthetic genes Town 181 4.3.3.2 gyrB Gene 182 4.3.3.3 recN Gene 182 4.3.3.4 BLAST analysis Cape 184 4.3.4 Phylogenetic and sequence analysis 184 4.4 Results of 184 4.4.1 Gene amplification 184 4.4.1.1 Antibiotic biosynthetic potential 184 4.4.1.2 gyrB Gene amplification 185 4.4.1.3 recN Gene amplification 185 4.4.2 PhylogeneticUniversity analysis 186 4.4.2.1 Distribution of antibiotic producers 186 4.4.2.2 gyrB-Gene based phylogeny 186 4.4.2.3 recN-Gene based phylogeny 188 4.4.2.4 Concatenated gyrB- and recN-gene based phylogeny 195 4.4.3 Sequence analysis 198 4.4.3.1 gyrB Gene analysis 198 4.4.3.2 recN Gene analysis 202 4.4.4 Evaluation of the gyrB and recN sequence analysis methods 205 4.5 Discussion 206 4.6 References 209 178

CHAPTER 4

THE USE OF gyrB AND recN GENE SEQUENCES IN THE PHYLOGENETIC ANALYSIS OF THE GENUS Amycolatopsis

4.1 Summary

Amycolatopsis type strains were screened for the presence of antibiotic biosynthetic genes. Partial gyrB gene sequences (>1kb) were obtained from 34 type strains with validly-published names and four laboratory strains. Partial recN gene sequences were obtained from 31 of these type strains and the four laboratory strains. Phylogenetic trees were constructed to determine the effectiveness of using the gyrB and recN genes to predict taxonomic relationships within the genus. The use of gyrB and recN gene sequence analysis as an alternative to DDH was Town also assessed for distinguishing closely related species. It was noted that Amycolatopsis strains sharing similar antibiotic biosynthetic potential were phylogenetically related. The gyrB- and recN-gene based phylogeny mostly confirmed the conventional 16S rRNA gene-basedCape phylogeny and thus provides additional support for certain of these 16S rRNA gene-basedof phylogenetic groupings. The gyrB gene, however, seems to be more suited to phylogenetic studies than the recN gene within this genus. Although pairwise gyrB or recN gene sequence similarity cannot be used to predict the DNA relatedness between type strains, the genetic distances can be used as a means to assess quickly whether an isolate is likely to represent a new species in the genus Amycolatopsis. In particular, a gyrB genetic distance of >0.02 or a recN genetic distance of >0.04 between two Amycolatopsis strains is proposed to provide a good indicationUniversity that they belong to different species (and that polyphasic taxonomic characterisation of the unknown strain is worth undertaking).

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4.2 Introduction

The genus Amycolatopsis belongs to the family Pseudonocardiaceae (Lechevalier et al., 1986) and contains 41 members (Euzéby, 2010), many of which are known antibiotic producers. Being one of the rarer antibiotic-producing actinobacterial genera, Amycolatopsis strains are an obvious point of interest for antibiotic drug discovery programs, especially given the desperate need for the discovery of new antibiotics to combat increasing bacterial antibiotic resistance.

Taxonomic delineation in this genus, as with most bacterial genera, relies greatly on 16S rRNA gene sequence analysis and DDH, which are still considered the “gold standards” for species delineation, despite having numerous short falls (Stackebrandt & Goebel, 1994; Zeigler, 2003). The development of alternative methods is therefore desirable, with the use of sequences of housekeeping genes having been suggested to complement the 16S rRNA gene sequence analysis for species level determination (Coenye et al., 2005). Furthermore it has been suggestedTown that the sequence analysis of such genes could be used to predict genome similarity and thereby possibly even replace the use of DDH altogether (Stackebrandt et al., 2002; Zeigler, 2003; Coenye et al., 2005). To this end, Zeigler (2003) proposed several housekeeping genes that mightCape be used for this purpose, with just one gene sequence potentially being sufficient to predict the entire genome similarity. of The DNA gyrase β-subunit encoding gene, gyrB, has been widely used in bacterial taxonomy to group strains and to discriminate or differentiate between closely related species, with the results being consistent with those of DDH (Kasai et al., 2000; Chimara et al., 2004; Jin et al., 2004). It has also been used to support phylogenetic groupings (Shen et al., 2006; le Roes et al., 2008; Takeda et al., 2010; Kirby et al., 2010). In the study of Zeigler (2003), the recN gene was found to have the highest potential to replaceUniversity DDH, and it has subsequently been shown to be useful in taxonomic delineations in the genus Geobacillus (Zeigler, 2005), the family ‘Leuconostocaceae’ (Arahal et al., 2008) and most recently the genus Streptococcus (Glazunova et al., 2010).

The aim of this part of the study were firstly to obtain partial gyrB and recN gene sequences from most of the members of the genus Amycolatopsis with validly-published names (all of the Risk Group 1 type strains available by the end of February 2009), secondly to compare the effectiveness of these genes to the 16S rRNA gene in assessing the phylogenetic relationships between type strains in this genus and thirdly to assess the potential of using gyrB or recN gene sequence analysis as a 180 tool to predict the DNA relatedness between type strains of Amycolatopsis to allow rapid assessment of whether environmental Amycolatopsis isolates are likely to represent new species.

4.3 Materials and methods 4.3.1 Bacterial strains and DNA extraction All Amycolatopsis strains used are included in Table 4.3.1. Strains were grown in YEME broth at 30°C for 3-5 days with shaking. Gram stains were performed to confirm the purity of all cultures. Genomic DNA was extracted as described in section 2.3.4.1.

4.3.2 PCR primers and primer design 4.3.2.1 Antibiotic biosynthetic primers Town The primers used to screen for antibiotic biosynthetic potential were described in section 2.3.5.1. In addition, screening for the presence of the 2-deoxy scyllo inosose (DOI) synthase gene, involved in the production of 2-deoxystreptamine-containing aminoglycoside antibiotics was carried out. The latter was achieved by using the primers DINOS-F (5’Cape – CTGMTSGCCGCSCTGCTSTTC – 3’) and DINOS-R (5’ – GGTAGCCSCGCTTGTTGTCGAAof – 3’), amplifying a fragment of 642nt in length. The DINOS primers were designed from the DOI synthase genes from M. echinospora ATCC 15835 (AY524043), Streptomyces kanamyceticus ATCC 12853T (AJ582817) and Streptoalloteichus tenebrarius ATCC 17920 (AJ579650) (primers were designed by Vishal Darji as part of his Honours project). M. echinospora or Sta. tenebrarius served as the positive control for the PCR reaction.

4.3.2.2 gyrB Gene primersUniversity The details of the gyrB gene primers used in this chapter are as described in section 3.3.1.2.

4.3.2.3 recN Gene primers The primers 7G-recN-F (5’-GAGACSGGNGCSGGYAAGACSATG-3’) and 7G-recN-R (5’- CCGACVCCSGCRTCVACYTCGTCG-3’) were designed based on ten recN gene sequences from seven genera: Frankia alni strain ACN14a (NC_008278), Frankia sp. strain CcI3 (CP000249), N. farcinica strain IFM 10152 (AP006618), Nocardioides sp. strain JS614 (CP000509), Sac. erythraea NRRL 2338T (AM420293), Sal. tropica strain CNB-440T (CP000667), Streptomyces arenae NRRL 181

2377T (sequence determined by Andrew Cook), S. avermitilis strain MA-4680T (AP005046), S. coelicolor strain A3(2) (AL939110) and Thermobifida fusca strain YX (NC_007333) (primers designed by P. Meyers).

Primers MS-recN-F1 (5’-GGYRCIGGCAAGACSATGGTGG-3’) and MS-recN-R5 (5’- ACYGCIGCCYIGCCGCCGAC-3’) were designed based on the recN gene sequences from eight members of the lass Actinobacteria: Mycobacterium avium subsp. paratuberculosis K-10 (NC_002944), Mycobacterium bovis AF2122/97 (BX248339), Mycobacterium leprae TN (AL583921), M. tuberculosis H37RvT (BX842577), M. tuberculosis CDC 1551 (NC_002755), a partial sequence from Nocardia brasiliensis ATCC 19296T (P. Meyers), S. avermitilis MA-4680T (AP005046) and S. coelicolor A3(2) (AL939110) (primers designed by P. Meyers).

Primer recN-R1455 (5’-GACICCSGCGTCGACCTCGTCG-3’) was designed based on the recN gene sequences of N. brasiliensis, Micromonospora aurantiaca andTown 17 Streptomyces sequences (primer designed by B. Kirby).

The primers Amy-recN-F1 (5’-AGGACRYSGARCTSRCCG-3’)Cape and Amy-recN-R1 (5’- CYTCSGAVGTGTCCATSS-3’) were designedof in this study based on 13 Amycolatopsis recN gene sequences from: A. alba, A. albidoflavus, A. echigonensis, A. jejuensis, A. keratiniphila subsp. keratiniphila, A. keratiniphila subsp. nogabecina, A. lurida, A. niigatensis, A. palatopharyngis, A. regifaucium, A. rubida, A. sulphurea and ‘Amycolatopsis umgeniensis’ (all determined in this study).

4.3.3 PCR amplification and gene sequencing 4.3.3.1 Antibiotic biosyntheticUniversity genes Screening for biosynthetic genes involved in the production of ansamycin, glycopeptide and Type-II (aromatic) polyketide antibiotics was performed as detailed in section 2.3.5.1. The PCR conditions and programme used for the screening of the presence of a DOI synthase gene were as described in section 2.3.5.1, using an annealing temperature of 56°C. Products were electrophoresed as described in section 2.3.4.2. Antibiotic biosynthetic gene products were purified and sequenced as described in section 3.3.1.1 using the original PCR primers in the sequencing reactions.

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4.3.3.2 gyrB Gene The gyrB genes were amplified from the Amycolatopsis type strains using the same PCR conditions and primer combinations described in section 3.3.1.2. Products were electrophoresed as described in section 2.3.4.2. The specific combination of primers used for each strain, as well as the modifications to the standard PCR reaction conditions, where applicable, are indicated in Table 4.3.1. Genes were purified and sequenced as described in section 3.3.1.1 using the original PCR primers in the sequencing reactions.

4.3.3.3 recN Gene The recN gene was amplified from most strains using the primers 7G-recN-F & 7G-recN-R, to produce a single 1363nt fragment (based on the S. avermitilis MA-4680T recN gene sequence). The primers MS-recN-F1 & recN-R1455 were used to amplify a 1382nt fragment of the gene from A. keratiniphila subsp. keratiniphila and the primers MS-recN-F1 & MS-recN-R5Town were used to amplify a 1373nt fragment of the gene from A. lurida. Primer Amy-recN-F1, used in conjunction with 7G- recN-R, and Amy-recN-R1, used with 7G-recN-F, should amplify fragments of 848nt and 933nt, respectively, from the recN gene (with a 418nt overlap). Cape All PCR reactions were performed in 50µl volumesof containing 500ng of genomic DNA, 2mM

MgCl2, 5-10% glycerol, 150µM of each dNTP, 0.5µM of each primer and 0.5U Supertherm Taq polymerase (JMR Holdings, USA) in a Techne TC-512 thermal cycler. In some cases, 1µg of DNA and 1µM of each primer were used. The PCR program consisted of an initial denaturation at 96°C for 2min, followed by 30 cycles of denaturation at 96°C for 45s, annealing at 56-68°C for 30s and extension at 72°C for 90s, followed by a final extension at 72°C for 5min. Products were electrophoresed as describedUniversity in section 2.3.4.2 . The specific amplification conditions for each strain are included in Table 4.3.1. Genes were purified and sequenced as described in section 3.3.1.1 using the original PCR primers in the sequencing reactions. Strains were screened for recN amplification with the Amy-recN primers in combination with 7G-recN primers using the conditions as described above and containing 5% glycerol with an annealing temperature of 56°C.

Where direct sequencing of the PCR products failed, they were cloned into the pJET1/blunt vector (GeneJET PCR cloning kit; Fermentas Life Sciences) and transformed into E. coli DH5α (Sambrook et al., 1989). Transformants were screened for the presence of a recN insert by performing colony PCR under the original amplification conditions. A single transformant shown to harbour a plasmid 183 containing the recN gene was then grown in 5ml of LB broth containing 100µg/ml of ampicillin at 37°C with shaking for 18h. The plasmid was extracted using an Invisorb Spin Plasmid Mini Two kit (Invitek, Germany). The recN gene was then amplified from the extracted plasmid DNA by PCR using the initial PCR conditions and sequenced as described. Those sequences obtained from cloned PCR products are indicated in Table 4.3.1.

Table 4.3.1 Amycolatopsis strains, gyrB primer combinations and recN PCR reaction conditions. recN PCR gyrB Strain Strain numbers reaction primer set*† conditions Amycolatopsis alba NRRL 18532T BF/BR 5% gly; 64°C Amycolatopsis albidoflavus NRRL B-24149T 7G/BR 3% gly; 60°C Amycolatopsis australiensis DSM 44671T BF/BR 10% gly; 56°C Amycolatopsis azurea NRRL 11412T BF/BR 5% gly; 60°C Amycolatopsis balhimycina NRRL B-24207T 7Ga 10% gly; 60°C Amycolatopsis coloradensis NRRL 3218T 7G/BF/BR 10% gly; 64°C Amycolatopsis decaplanina NRRL B-24209T 7G/BF/BR 3% gly; 56°C Amycolatopsis echigonensis JCM 21831T BF/BR 3% gly; 64°C Amycolatopsis eurytherma DSM 44348T Town7G NA Amycolatopsis fastidiosa NRRL B-16697T BF/BR NA Amycolatopsis halotolerans NRRL B-24428T 7Ga,d/BF 3% gly; 64°C Amycolatopsis japonica NRRL B-24138T 7Gb,d/BF/BR 3% gly; 60°C Amycolatopsis jejuensis NRRL B-24427T 7Gb,e/BF/BR 3% gly; 60°C Amycolatopsis keratiniphila subsp. keratiniphila NRRL B-24117T 7G/BR 5% gly; 60°C  Amycolatopsis keratiniphila subsp. nogabecina NRRLCape B-24206T 7G 3% gly; 64°C Amycolatopsis lurida NRRL 2430T 7Gb,d 10% gly; 60°C  Amycolatopsis mediterranei NRRL B-3240T BF/BR 3% gly; 60°C Amycolatopsis methanolica ofNRRL B-24139T 7Gc 5% gly; 64°C
Amycolatopsis minnesotensis NRRL B-24435T BF/BR 10% gly; 64°C  Amycolatopsis nigrescens DSM 44992T BF/BR 5% gly; 64°C  Amycolatopsis niigatensis JCM 21832T BF/BR 3% gly; 64°C Amycolatopsis orientalis NRRL 2450T 7G 3% gly; 56°C Amycolatopsis palatopharyngis DSM 44832T BF/BR 3% gly; 64°C Amycolatopsis plumensis NRRL B-24324T BF/BR 3% gly; 56°C  Amycolatopsis regifaucium DSM 45072T BF/BR 5% gly; 64°C Amycolatopsis rifamycinica DSM 46095T 7Gc,d/BF/BR 5% gly; 60°C Amycolatopsis rubida NRRL B-24150T BF/BR 3% gly; 60°C Amycolatopsis saalfeldensisUniversity DSM 44993T 7G/BR 10% gly; 60°C  Amycolatopsis sacchari DSM 44468T 7Ge 3% gly; 56°C Amycolatopsis sulphurea NRRL 2822T 7G 5% gly; 64°C  Amycolatopsis taiwanensis DSM 45107T BF/BR 5% gly; 64°C Amycolatopsis thermoflava NRRL B-24140T 7Gc,d/BF/BR 5% gly; 64°C
Amycolatopsis tolypomycina NRRL B-24205T 7G/BF/BR 10% gly; 64°C  Amycolatopsis vancoresmycina NRRL B-24208T BF/BR 0% gly; 60°C ‘Amycolatopsis circi’ S1.3T BF/BR 5% gly; 64°C
 ‘Amycolatosis equina’ SE(8)3T BF/BR 5% gly; 64°C
 ‘Amycolatopsis hippodromi’ S3.6T BF/BR 5% gly; 64°C
 ‘Amycolatopsis umgeniensis’ UM16T BF/BR 5% gly; 64°C * 7G – 7G-gyrB-F & 7G-gyrB-R; BF – 7G-gyrB-F & GgyrB-R1; BR – GgyrB-F1 & 7G-gyrB-R † 7G gyrB PCR conditions as modified from the standard conditions: a, 2.5% glycerol; b, 5% glycerol; c, 2% d e DMSO; , 60°C TA; , 64°C TA.  The recN genes from all strains except A. keratiniphila subsp. keratiniphila (MS-recN-F1 & recN-R1455) and A. lurida (MS-recN-F1 & MS-recN-R5) were amplified with the 7G-recN-F & 7G-recN-R primer combination. Conditions of glycerol (gly) and annealing temperature (°C) are indicated.  PCR products were cloned before sequencing. NA, no amplification was recorded.
1µg of DNA and 1µM of each primer was used in the reaction. 184

4.3.3.4 BLAST analysis The sequences of all the genes determined in this study were subjected to BLAST analysis (Altschul et al., 1997) to confirm their identity and to ensure that the intended genes had been amplified.

4.3.4 Phylogenetic and sequence analysis All phylogenetic analyses were performed using MEGA version 4 (Tamura et al., 2007). Phylogenetic trees were constructed using the neighbor-joining (Saitou & Nei, 1987), minimum evolution and maximum parsimony (Takahashi & Nei, 2000) methods. The concatenated gyrB-16S rRNA gene and recN-16S rRNA gene sequences were created by joining the 16S rRNA gene sequence to the 3’-end of the in-frame gyrB and recN gene sequences, respectively. The concatenated gyrB-recN-16S gene sequence was created by joining the 16S rRNA sequence to the 3’-end of the in-frame recN gene sequence, which was joined to the 3’-end of the in frame gyrB gene sequence. Sequence analysis was performed using DNAMAN. TheTown gyrB and recN genetic distances were calculated in MEGA, using Kimura’s 2-parameter model (Kimura, 1980). All plots were generated using SigmaPlot®, version 10.0.1 (Systat Software Inc). Cape

4.4 Results of 4.4.1 Gene amplification 4.4.1.1 Antibiotic biosynthetic potential PCR screening for antibiotic biosynthetic potential revealed the presence of antibiotic biosynthetic genes in all the Amycolatopsis type strains that are known antibiotic producers, as well as in several type strains that are notUniversity known to produce these antibiotics (which are all listed here). A key gene involved in the production of ansamycins (the 3-amino-5-hydroxy-benzoic acid synthase gene) was found in A. minnesotensis. The ketosynthase α-ketosynthase β tandem gene pair, which is essential for the production of aromatic polyketides, was detected in A. australiensis, A. azurea, A. balhimycina, A. decaplanina, A. echigonensis, A. fastidiosa, A. keratiniphila subsp. keratiniphila, A. lurida, A. minnesotensis, A. nigrescens, A. niigatensis, A. palatopharyngis, A. rifamycinica, A. rubida and A. thermoflava. The oxyB P450 monooxygenase, which is essential for the production of glycopeptides, was detected in A. decaplanina, A. japonica, A. regifaucium and A. tolypomycina. Amplification of the ketosynthase α-β gene pair was also recorded for ‘A. circi’ strain S1.3T, 185

‘A. equina’ strain SE(8)3T, ‘A. hippodromi’ strain S3.6T and ‘A. umgeniensis’ strain UM16T, with the latter also showing amplification of the oxyB gene. Amplification was noted from the DOI synthase gene PCR primers from A. balhimycina, A. keratiniphila subsp. keratiniphila, A. keratiniphila subsp. nogabecina, A. mediterranei, A. palatopharyngis, A. rifamycinica and A. sacchari, however, BLAST analysis of the sequences showed them to be non-specific amplification products and not biosynthetic genes.

4.4.1.2 gyrB Gene amplification The gyrB gene was amplified from genomic DNA of 34 Amycolatopsis type strains with validly- published names and four laboratory strains, using the primer combinations shown in Table 4.3.1. Approximately 1300-1400nt of gyrB gene sequence was obtained for each of the strains. BLAST searches showed that all the sequences were amplified from the gyrB gene and not from the paralogous gene, parE (Watanabe et al., 2001). Furthermore, an alignmentTown of parE gene sequences from two actinobacterial strains (S. avermitilis MA-4680T (NC_003155) and Streptomyces griseus subsp. griseus NBRC 13350 (NC_010572)), plus Bacteroides fragilis NCTC 9343 (CR626927) and Pseudomonas aeruginosa PAO1 (NC_002516) showed that the gyrB gene primers that were used are not sufficiently complementary to the parE gene to allowCape amplification of a product, or would not generate products of the correct sizes (data not shown).of

4.4.1.3 recN Gene amplification The recN gene was amplified from the genomic DNA of 32 Amycolatopsis type strains with validly- published names and four laboratory strains, using the PCR conditions shown in Table 4.3.1. Approximately 1200-1300nt of recN gene sequence was obtained for 35 strains of these 36 strains. The recN gene sequenceUniversity of A. methanolica could not be obtained due to sequencing problems with the initially amplified PCR products (which appeared to be mixed products) and the inability to obtain clones containing the recN gene product. The sequences of A. eurytherma and A. fastidiosa could not be determined as the gene failed to amplify with the primers that were used in this study. No amplification was obtained from the Amy-recN primers, used in combination with the 7G-recN primers, despite the 7G primers amplifying the gene from all but two strains and the Amy-recN primers having been designed from Amycolatopsis recN gene sequences.

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4.4.2 Phylogenetic analysis 4.4.2.1 Distribution of antibiotic producers A summary of the results of the biosynthetic gene screening performed in this study and Wood et al. (2007), along with the known biosynthetic capacity of the genus (Wink et al., 2003; Bala et al., 2004; Wink et al., 2004), is presented in the 16S rRNA gene-based phylogenetic tree of the entire genus (Fig 4.4.1). The results obtained support and extend the data presented by Wink et al. (2003) and Wood et al. (2007), which showed that Amycolatopsis type strains that produce, or have the potential to produce, a particular class of antibiotic are phylogenetically related. This is particularly evident for those possessing glycopeptide biosynthetic genes, with all but two of these strains clustering together and all the members of the cluster either producing, or apparently having the biosynthetic genes for the production of a glycopeptide. Similar clustering was noted for those strains possessing genes for the production of ansamycins. All but three of these strains grouped into the same cluster with only one known ansamycin producer not groupingTown in the cluster. However, there appears to be no phylogenetic clustering of the strains containing the aromatic polyketide biosynthetic genes, with these strains being scattered throughout the tree. Cape 4.4.2.2 gyrB-Gene based phylogeny Phylogenetic trees were constructed with the of 16S rRNA gene, gyrB gene and gyrB-16S rRNA concatenated gene sequences and are displayed as Figs 4.4.2, 4.4.3 and 4.4.4, respectively. Although the overall topologies of the 16S rRNA gene (Fig 4.4.2) and gyrB gene (Fig 4.4.3) trees were different, groups of closely related strains clustered in both trees (clusters A-E), which is consistent with results for the genera Gordonia (Shen et al., 2006), Kribbella (Kirby et al., 2010) and Micromonospora (KasaiUniversity et al., 2000). The gyrB gene tree (Fig 4.4.3) clearly showed a higher level of resolution than that of the 16S rRNA gene tree (Fig 4.4.2), marked by longer branch lengths between strains. The concatenated tree (Fig 4.4.4) closely resembled the gyrB gene tree (Fig 4.4.3) and also contained the conserved clustering (groups A-E) noted in the other two trees. The resolution of this tree was lower than that of the gyrB gene tree (Fig 4.4.3), but greater than that of the 16S rRNA gene tree (Fig 4.4.2). However, the number of bootstrap values greater than 90% increased from 9 for the 16S rRNA gene tree (Fig 4.4.2) to 17 for the gyrB gene tree (Fig 4.4.3) to 19 for the gyrB-16S rRNA gene tree (Fig 4.4.4) indicating increasing robustness of the gyrB and gyrB-16S rRNA gene tree topologies. 187

T *66 Amycolatopsis kentuckyensis NRRL B-24129 (AY183357) Amycolatopsis rifamycinica DSM 46095T (AY083603)  Amycolatopsis lexingtonensis NRRL B-24131T (AY183358) *88 Amycolatopsis pretoriensis NRRL B-24133T (AY183356) Ansamycin Amycolatopsis vancoresmycina DSM 44592T (AJ508240)  Producers 71 Amycolatopsis plumensis SBHS Strp1T (AY262825) 68 84 Amycolatopsis tolypomycina DSM 44544T (AJ508241)  *77 Amycolatopsis balhimycina DSM 44591T (AJ508239)  Amycolatopsis mediterranei NRRL B-3240T (AY184424)  Amycolatopsis australiensis GY048T (AY129753)  Amycolatopsis saalfeldensis HKI0457T (DQ792500) Amycolatopsis rubida 13.4T (AF222022)  Amycolatopsis benzoatilytica DSM 43387T (AY957506) 70 T  * Amycolatopsis echigonensis LC2 (AB248535) * Amycolatopsis niigatensis LC11T (AB248537)  Amycolatopsis halotolerans N4-6T (DQ000196) Amycolatopsis albidoflavus IMSNU 22139T (AJ252832) ‘Amycolatopsis circi’ S1.3T  ‘Amycolatopsis hippodromi’ S3.6T  *99 *61 ‘Amycolatopsis equina’ SE(8)3T  T 56 Amycolatopsis coloradensis DSM 44225 (AJ421142) 83 ‘Amycolatopsis umgeniensis’ UM16T (DQ110876)  T Town Amycolatopsis alba DSM 44262 (AF051340)  Amycolatopsis azurea IMSNU 20053T (AJ400709)  *97 T *99 Amycolatopsis orientalis IMSNU 20058 (AJ400711) 51 Amycolatopsis regifaucium GY080T (AY129760)  Glycopeptide 72 Producers Amycolatopsis japonica DSM 44213T (AJ508236)  Amycolatopsis decaplaninaCape DSM 44594 T ( AJ508237)  Amycolatopsis keratiniphila subsp. nogabecina DSM 44586T (AJ508238) T  76 Amycolatopsis keratiniphila subsp. keratiniphila DSM 44409 (AJ278496) of T *54 Amycolatopsis lurida DSM 43134 (AJ577997)  Amycolatopsis ultiminotia RP-AC36T (FM177516) Amycolatopsis jejuensis N7-3T (DQ000200) 63 *59 Amycolatopsis sulphurea DSM 46092T (AF051343)  96 Amycolatopsis sacchari DSM 44468T (AF223354) T  * Amycolatopsis minnesotensis 32U-2 (DQ076482)  *94 Amycolatopsis nigrescens CSC17-Ta-90T (DQ486888)  T *100 Amycolatopsis marina MS392A (EU329845) Amycolatopsis palatopharyngis 1BDZT (AF479268)  Amycolatopsis taiwanensis 0345M-7T (DQ160215) University60 T *99 Amycolatopsis eurytherma NT202 (AJ000285) *67 Amycolatopsis tucumanensis ABOT (DQ886938) *100 Amycolatopsis methanolica IMSNU 20055T (AJ249135) *100 Amycolatopsis thermoflava N1165T (AF052390)  Amycolatopsis fastidiosa IMSNU 20054T (AJ400710)  Streptomyces avermitilis NCIMB 12804T (AF145223)

0.01

Figure 4.4.1 Unrooted 16S rRNA gene phylogenetic tree of all members of the genus Amycolatopsis. The tree was constructed using the neighbor-joining method based on 1353nt of sequence. The percentage bootstrap values of 1000 replications are shown at each node (only values above 50% are shown), with asterisks (*) indicating the clades that were conserved in all three tree drawing algorithms (section 4.3.4). Accession numbers are indicated in parenthesis after the strain numbers. The scale bar indicates 1 nucleotide substitution per 100 nucleotides. S. avermitilis NCIMB 12804T was used as an outgroup. Symbols indicate species that have the potential to produce ansamycins (), aromatic (Type-II) polyketides () and glycopeptides () as well as strains that are known producers of ansamycins (), aromatic (Type- II) polyketides () and glycopeptides ( ). Glycopeptide and ansamycin producing clusters are indicated. 188

It should be noted that A. saalfeldensis clusters on the periphery of cluster C, while A. jejuensis and A. sulphurea cluster on the periphery of the taxospace of clusters A, B, C and D in the 16S rRNA gene tree (Fig 4.4.2), but are all associated with cluster B in the gyrB concatenated trees (Figs 4.4.3 & 4.4.4) (marked as cluster X, although they are not a coherent cluster). Furthermore, it should be noted that A. fastidiosa was consistently recovered on the periphery of the cluster defined by the other type strains of the genus in all the trees. Phylogenetic trees that were constructed based on only the variable third nucleotide position in the codons of the gyrB gene sequences closely resembled those based on the entire 1290nt gyrB gene sequence, with the exception that cluster C was split into two groups in the neighbor-joining tree (but was conserved with the other tree drawing algorithms) and A. palatopharyngis clustered with A. fastidiosa in all except the maximum parsimony tree, where it clustered outside of this strain (Appendices E-G).

4.4.2.3 recN-Gene based phylogeny Town Phylogenetic trees were constructed with the 16S rRNA gene, recN gene and recN-16S rRNA gene concatenated sequences and are displayed as Figs 4.4.5, 4.4.6 and 4.4.7, respectively. As was the case with the gyrB-gene based phylogeny, the overall topologies of the 16S rRNA gene (Fig 4.4.5) and recN gene (Fig 4.4.6) trees were different, but thereCape are groups of closely related strains that clustered in both trees (clusters A-C). These wereof the same clusters of strains noted in the gyrB-gene based trees. The recN gene tree (Fig 4.4.6) clearly showed a higher level of resolution than that of the 16S rRNA gene tree (Fig 4.4.5), evident by the longer branch lengths between strains. The concatenated tree (Fig 4.4.7) closely resembled the recN gene tree (Fig 4.4.6) and also contained the conserved clustering (groups A-C) noted in the other two trees. The resolution of this tree was lower than that of the recN gene tree (Fig 4.4.6), but greater than that of the 16S rRNA gene tree (Fig 4.4.5), as was the case Universityin the gyrB gene trees. The number of bootstrap values greater than 90% increased from 7 for the 16S rRNA gene tree (Fig 4.4.5) to 12 for the recN gene tree (Fig 4.4.6) to 14 for the recN-16S rRNA gene tree (Fig 4.4.7). Thus, the percentage increase in the number of bootstrap values ≥90% was lower in the recN trees than in the gyrB gene trees, but nevertheless still indicated an increasing robustness of the recN and recN-16S rRNA gene tree topologies compared to that of the 16S-rRNA gene tree.

As in the gyrB gene trees, A. jejuensis, A. saalfeldensis and A. sulphurea cluster on the periphery of the taxospace of clusters A, B and C in the 16S rRNA gene tree (Fig 4.4.5), but are associated with cluster B in the concatenated gene trees (Figs 4.4.6 & 4.4.7) (marked as cluster X on the trees). 189

T *89 Amycolatopsis orientalis IMSNU 20058 (AJ400711) *55 Amycolatopsis regifaucium GY080T (AY129760) * Amycolatopsis japonica DSM 44213T (AJ508236) Amycolatopsis decaplanina DSM 44594T ( AJ508237) 92 Amycolatopsis azurea IMSNU 20053T (AJ400709) Amycolatopsis lurida DSM 43134T (AJ577997) A T *97 Amycolatopsis keratiniphila subsp. keratiniphila DSM 44409 (AJ278496) Amycolatopsis keratiniphila subsp. nogabecina DSM 44586T (AJ508238) ‘Amycolatopsis umgeniensis’ UM16T (DQ110876)

T 94 Amycolatopsis alba DSM 44262 (AF051340) 68 Amycolatopsis coloradensis DSM 44225T (AJ421142) Amycolatopsis rubida 13.4T (AF222022) T *67 ‘Amycolatopsis hippodromi’ S3.6 *98 ‘Amycolatopsis equina’ SE(8)3T 99 ‘Amycolatopsis circi’ S1.3T Amycolatopsis albidoflavus IMSNU 22139T (AJ252832) B Amycolatopsis halotolerans N4-6T (DQ000196) 62 Amycolatopsis echigonensis LC2T (AB248535) 50 Amycolatopsis niigatensis LC11T (AB248537)Town Amycolatopsis saalfeldensis HKI0457T (DQ792500) Amycolatopsis australiensis GY048T (AY129753) T *55 Amycolatopsis balhimycina DSM 44591 (AJ508239) * T 62 Amycolatopsis mediterranei NRRL B-3240 (AY184424) Cape T Amycolatopsis rifamycinica DSM 46095 (AY083603) C 87 Amycolatopsis vancoresmycina DSM 44592T (AJ508240)

of T 74 62 Amycolatopsis plumensis SBHS Strp1 (AY262825) *84 Amycolatopsis tolypomycina DSM 44544T (AJ508241) Amycolatopsis minnesotensis 32U-2T (DQ076482) *93 Amycolatopsis nigrescens CSC17-Ta-90T (DQ486888) D 96 Amycolatopsis jejuensis N7-3T (DQ000200) Amycolatopsis sacchari DSM 44468T (AF223354) Amycolatopsis sulphurea DSM 46092T (AF051343) Amycolatopsis palatopharyngis 1BDZT (AF479268) University Amycolatopsis taiwanensis 0345M-7T (DQ160215) 54 Amycolatopsis eurytherma NT202T (AJ000285) *82 T E *100 Amycolatopsis methanolica IMSNU 20055 (AJ249135) *99 Amycolatopsis thermoflava N1165T (AF052390) Amycolatopsis fastidiosa IMSNU 20054T (AJ400710) Streptomyces avermitilis NCIMB 12804T (AF145223)

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Figure 4.4.2 Unrooted 16S rRNA gene phylogenetic tree for 34 validly published and four unpublished members of the genus Amycolatopsis for which there are gyrB gene sequences. The tree was constructed using the neighbor-joining method based on 1353nt of sequence. The percentage bootstrap values of 1000 replications are shown at each node (only values above 50% are shown), with asterisks (*) indicating the clades that were conserved in all tree drawing algorithms (section 4.3.4). Accession numbers are indicated in parenthesis after the strain numbers. The scale bar indicates 1 nucleotide substitution per 100 nucleotides. S. avermitilis NCIMB 12804T was used as an outgroup. Groups A-E indicate conserved clusters of strains.

190

T *100 Amycolatopsis keratiniphila subsp. keratiniphila NRRL B-24117 (EU822898) 73 Amycolatopsis keratiniphila subsp. nogabecina NRRL B-24206T (EU822899) Amycolatopsis decaplanina NRRL B-24209T (EU822891) 99 Amycolatopsis lurida NRRL 2430T (EU822900) * Amycolatopsis japonica NRRL B-24138T (EU822896) ‘Amycolatopsis umgeniensis’ UM16T A *55 Amycolatopsis alba NRRL 18532T (EU822885) *100 Amycolatopsis azurea NRRL 11412T (EU822888) 100 Amycolatopsis orientalis NRRL 2450T (EU822906) Amycolatopsis coloradensis NRRL 3218T (EU822890) 56 * Amycolatopsis regifaucium DSM 45072T (EU822909) Amycolatopsis australiensis DSM 44671T (EU822887) T *53 Amycolatopsis mediterranei NRRL B-3240 (EU822901) 100 Amycolatopsis rifamycinica DSM 46095T (EU822910) Amycolatopsis vancoresmycina NRRL B-24208T (EU822918) 100 73 C Amycolatopsis balhimycina NRRL B-24207T (EU822889) T *97 Amycolatopsis plumensis NRRL B-24324 (EU822908) *83 Amycolatopsis tolypomycina NRRL B-24205T (EU822917) Amycolatopsis saalfeldensis DSM 44993TownT (EU822912) T 52 Amycolatopsis jejuensis NRRL B-24427 (EU822897) X *99 Amycolatopsis sulphurea NRRL 2822T (EU822914) Amycolatopsis halotolerans NRRL B-24428T (EU822895) 99 Amycolatopsis rubida NRRL B-24150T (EU822911) 99 *93 Cape T *100 Amycolatopsis echigonensis JCM 21831 (EU822892) 86 Amycolatopsis niigatensis JCM 21832T (EU822905) Amycolatopsisof albidoflavus NRRL B-24149T (EU822886) B ‘Amycolatopsis circi’ S1.3T *71 ‘Amycolatopsis hippodromi’ S3.6T *100 ‘Amycolatopsis equina’ SE(8)3T T *74 Amycolatopsis minnesotensis NRRL B-24435 (EU822903) *62 Amycolatopsis nigrescens DSM 44992T (EU822904) D Amycolatopsis palatopharyngis DSM 44832T (EU822907) *97 Amycolatopsis sacchari DSM 44468T (EU822913) University Amycolatopsis taiwanensis DSM 45107T (EU822915) *97 Amycolatopsis methanolica NRRL B-24139T (EU822902) *96 T E *100 Amycolatopsis eurytherma DSM 44348 (EU822893) *98 Amycolatopsis thermoflava NRRL B-24140T (EU822916 Amycolatopsis fastidiosa NRRL B-16697T (EU822894) Streptomyces avermitilis MA-4680T (NC_003155)

0.05

Figure 4.4.3 Unrooted gyrB gene phylogenetic tree for 34 validly published and four unpublished members of the genus Amycolatopsis. The tree was constructed using the neighbor-joining method based on 1290nt of sequence. The percentage bootstrap values of 1000 replications are shown at each node (only values above 50% are shown), with asterisks (*) indicating the clades that were conserved in all tree drawing algorithms (section 4.3.4). Accession numbers are indicated in parenthesis after the strain numbers. The scale bar indicates 5 nucleotide substitutions per 100 nucleotides. S. avermitilis MA-4680T was used as an outgroup. Groups A-E and X indicate conserved clusters of strains. 191

*99 Amycolatopsis keratiniphila subsp. keratiniphila *64 Amycolatopsis keratiniphila subsp. nogabecina *56 Amycolatopsis decaplanina *99 Amycolatopsis lurida Amycolatopsis japonica *91 Amycolatopsis alba A Amycolatopsis azurea 10065 Amycolatopsis coloradensis *78 ‘Amycolatopsis umgeniensis’ Amycolatopsis orientalis 59 *75 Amycolatopsis regifaucium Amycolatopsis australiensis

*71 Amycolatopsis mediterranei *100 Amycolatopsis rifamycinica 100 96 Amycolatopsis vancoresmycina C Amycolatopsis balhimycina

*94 Amycolatopsis plumensis *95 Amycolatopsis tolypomycina Amycolatopsis saalfeldensis Town *98 Amycolatopsis jejuensis X *97 Amycolatopsis sulphurea Amycolatopsis halotolerans 97 Amycolatopsis rubida *99 100 *100 AmycolatopsisCape echigonensis 73 Amycolatopsis niigatensis 59 Amycolatopsisof albidoflavus B ‘Amycolatopsis circi’ 69 *100 ‘Amycolatopsis hippodromi’ *64 ‘Amycolatopsis equina’

*89 Amycolatopsis minnesotensis Amycolatopsis nigrescens D

95 Amycolatopsis palatopharyngis Amycolatopsis sacchari 66 Amycolatopsis taiwanensis *81 University Amycolatopsis eurytherma *99 E 100 Amycolatopsis methanolica 53 Amycolatopsis thermoflava Amycolatopsis fastidiosa Streptomyces avermitilis

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Figure 4.4.4 Unrooted phylogenetic tree based on the gyrB-16S rRNA concatenated gene sequence for 34 validly published and four unpublished members of the genus Amycolatopsis. The tree was constructed using the neighbor- joining method based on 2643nt of sequence. The percentage bootstrap values of 1000 replications are shown at each node (only values above 50% are shown), with asterisks (*) indicating the clades that were conserved in all tree drawing algorithms (section 4.3.4). Accession numbers of the sequences used are shown in Figs 4.4.2 and 4.4.3, respectively. The scale bar indicates 2 nucleotide substitutions per 100 nucleotides. An S. avermitilis MA-4680T 16S rRNA gene-gyrB gene concatenated sequence (AF145223 and NC_003155, respectively) was used as an outgroup. Groups A-E and X indicate conserved clusters of strains. 192

T *92 Amycolatopsis orientalis IMSNU 20058 (AJ400711) *58 Amycolatopsis regifaucium GY080T (AY129760) Amycolatopsis japonica DSM 44213T (AJ508236) Amycolatopsis decaplanina DSM 44594T ( AJ508237) Amycolatopsis lurida DSM 43134T (AJ577997) 89 Amycolatopsis keratiniphila subsp. keratiniphila DSM 44409T (AJ278496) A Amycolatopsis keratiniphila subsp. nogabecina DSM 44586T (AJ508238) *98 Amycolatopsis azurea IMSNU 20053T (AJ400709) ‘Amycolatopsis umgeniensis’ UM16T (DQ110876)

T 96 Amycolatopsis alba DSM 44262 (AF051340) 68 Amycolatopsis coloradensis DSM 44225T (AJ421142) Amycolatopsis rubida 13.4T ( AF222022)

T *64 ‘Amycolatopsis hippodromi’ S3.6 *99 ‘Amycolatopsis equina’ SE(8)3T 99 T ‘Amycolatopsis circi’ S1.3 B Amycolatopsis albidoflavus IMSNU 22139T (AJ252832) Amycolatopsis halotolerans N4-6TTown ( DQ000196) 59 Amycolatopsis echigonensis LC2T (AB248535) * Amycolatopsis niigatensis LC11T (AB248537) Amycolatopsis australiensis GY048T (AY129753) Amycolatopsis balhimycina DSM 44591T (AJ508239) * * * Cape T *63 Amycolatopsis mediterranei NRRL B-3240 (AY184424) Amycolatopsisof rifamycinica DSM 46095T (AY083603) C *84 Amycolatopsis vancoresmycina DSM 44592T (AJ508240)

T *71 Amycolatopsis plumensis SBHS Strp1 (AY262825)

*91 Amycolatopsis tolypomycina DSM 44544T (AJ508241) Amycolatopsis saalfeldensis HKI0457T (DQ792500) 56 Amycolatopsis sacchari DSM 44468T (AF223354) Amycolatopsis jejuensis N7-3T (DQ000200) *67 Amycolatopsis sulphurea DSM 46092T (AF051343) University Amycolatopsis minnesotensis 32U-2T (DQ076482) *94 Amycolatopsis nigrescens CSC17-Ta-90T (DQ486888) Amycolatopsis palatopharyngis 1BDZT (AF479268)

T 62 Amycolatopsis taiwanensis 0345M-7 (DQ160215) *80 Amycolatopsis thermoflava N1165T (AF052390) Streptomyces avermitilis NCIMB 12804T (AF145223)

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Figure 4.4.5 Unrooted 16S rRNA gene phylogenetic tree for 31 validly published and four unpublished members of the genus Amycolatopsis for which there are recN sequences. The tree was constructed using the neighbor-joining method based on 1356nt of sequence. The percentage bootstrap values of 1000 replications are shown at each node (only values above 50% are shown), with asterisks (*) indicating the clades that were conserved in all tree drawing algorithms (section 4.3.4). Accession numbers are indicated in parenthesis after the strain numbers. The scale bar indicates 1 nucleotide substitution per 100 nucleotides. S. avermitilis NCIMB 12804T was used as an outgroup. Groups A-C indicate conserved clusters of strains. 193

T *65 ‘Amycolatopsis circi’ S1.3 *100 ‘Amycolatopsis equina’ SE(8)3T 50 ‘Amycolatopsis hippodromi’ S3.6T Amycolatopsis albidoflavus NRRL B-24149T

T B *92 Amycolatopsis halotolerans NRRL B-24428

T 100 Amycolatopsis echigonensis JCM 21831 *100 Amycolatopsis niigatensis JCM 21832T *86 Amycolatopsis rubida NRRL B-24150T *99 Amycolatopsis jejuensis NRRL B-24427T *96 Amycolatopsis sulphurea NRRL 2822T X T *97 Amycolatopsis saalfeldensis DSM 44993 Amycolatopsis balhimycina NRRL B-24207T Amycolatopsis australiensis DSM 44671T 100 Amycolatopsis tolypomycina NRRL B-24205T Amycolatopsis mediterranei NRRL B-3240T *54 C T *97 Amycolatopsis rifamycinica DSM 46095 Amycolatopsis plumensisTown NRRL B-24324T * Amycolatopsis vancoresmycina NRRL B-24208T

T 77 Amycolatopsis orientalis NRRL 2450 Amycolatopsis regifaucium DSM 45072T Amycolatopsis coloradensis NRRL 3218T 100 ‘AmycolatopsisCape umgeniensis ’ UM16T

T 55 Amycolatopsis alba NRRL 18532 * of Amycolatopsis azurea NRRL 11412T A Amycolatopsis decaplanina NRRL B-24209T 51 Amycolatopsis lurida NRRL 2430T

T 73 Amycolatopsis japonica NRRL B-24138 T *100 Amycolatopsis keratiniphila subsp. nogabecina NRRL B-24206 *100 Amycolatopsis keratiniphila subsp. keratiniphila NRRL B-24117T Amycolatopsis nigrescens DSM 44992T Amycolatopsis thermoflava NRRL B-24140T *72University Amycolatopsis taiwanensis DSM 45107T 84 Y Amycolatopsis minnesotensis NRRL B-24435T *66 Amycolatopsis sacchari DSM 44468T Amycolatopsis palatopharyngis DSM 44832T Streptomyces avermitilis MA-4680T (BA000030)

0.05

Figure 4.4.6 Unrooted recN gene phylogenetic tree for 31 validly published and four unpublished members of the genus Amycolatopsis. The tree was constructed using the neighbor-joining method based on 1230nt of sequence. The percentage bootstrap values of 1000 replications are shown at each node (only values above 50% are shown), with asterisks (*) indicating the clades that were conserved in all tree drawing algorithms (section 4.3.4). The scale bar indicates 5 nucleotide substitutions per 100 nucleotides. S. avermitilis MA-4680T was used as an outgroup. Groups A-C, X and Y indicate conserved clusters of strains. 194

*94 Amycolatopsis albidoflavus Amycolatopsis halotolerans Amycolatopsis echigonensis *100 Amycolatopsis niigatensis B ‘Amycolatopsis hippodromi’ S3.6T 100 ‘Amycolatopsis circi’ S1.3T 100 T 56 63 ‘Amycolatopsis equina’ SE(8)3 Amycolatopsis rubida 100 Amycolatopsis jejuensis *92 Amycolatopsis sulphurea X

*99 Amycolatopsis saalfeldensis Amycolatopsis australiensis Amycolatopsis balhimycina 100 *80 Amycolatopsis mediterranei 63 Amycolatopsis rifamycinica C Amycolatopsis vancoresmycin *100 72 Amycolatopsis plumensis *60 Amycolatopsis tolypomycinaTown *99 Amycolatopsis orientalis Amycolatopsis regifaucium

*58 Amycolatopsis coloradensis * ‘Amycolatopsis umgeniensis’ UM16T 100 AmycolatopsisCape alba of Amycolatopsis azurea A * Amycolatopsis decaplanina 64 Amycolatopsis lurida

79 Amycolatopsis japonica Amycolatopsis keratiniphila subsp. nogabecina *100 *100 Amycolatopsis keartiniphila subsp. keratiniphila Amycolatopsis nigrescens Amycolatopsis minnesotensis 56 Amycolatopsis sacchari Y University92 Amycolatopsis taiwanensis 56 *74 Amycolatopsis thermoflava Amycolatopsis palatopharyngis Streptomyces avermitilis MA-4680T

0.02

Figure 4.4.7 Unrooted phylogenetic tree based on the recN-16S rRNA concatenated gene sequences for 31 validly published and four unpublished members of the genus Amycolatopsis. The tree was constructed using the neighbor- joining method based on 2586nt of sequence. The percentage bootstrap values of 1000 replications are shown at each node (only values above 50% are shown), with asterisks (*) indicating the clades that were conserved in all tree drawing algorithms (section 4.3.4). Accession numbers of the 16S rRNA gene sequences used are shown in Fig 4.4.5. The scale bar indicates 2 nucleotide substitutions per 100 nucleotides. An S. avermitilis MA-4680T recN-16S rRNA concatenated gene sequence (AF145223 and BA000030, respectively) was used as an outgroup. Groups A-C, X and Y indicate conserved clusters of strains. 195

Two of the strains from cluster E in the gyrB tree (A. eurytherma and A. methanolica), as well as A. fastidiosa, were not included in the recN gene phylogenetic analysis, which resulted in the formation of a new coherent grouping of strains which included the strains of cluster D of the gyrB-gene based trees and A. sacchari in both the recN-gene based trees. These strains are marked as cluster Y in Figs 4.4.6 and 4.4.7. When trees were constructed based on only the third nucleotide position of the codons in the recN gene sequences, the same clustering as in the full recN gene tree was recorded, except that A. saalfeldensis clustered on the periphery of cluster C and no longer formed part of cluster X associated with cluster B (Appendix H).

4.4.2.4 Concatenated gyrB- and recN-gene based phylogeny Phylogenetic trees were constructed with the gyrB-recN concatenated as well as the gyrB-recN-16S rRNA concatenated gene sequences and are displayed as Figs 4.4.8 and 4.4.9, respectively. Again, the overall topologies of the 16S rRNA gene (Fig 4.4.5) and gyrB-recNTown (Fig 4.4.8) and gyrB-recN- 16S rRNA (Fig 4.4.9) concatenated gene trees were different, but the same groups of closely related strains that cluster in all the other trees are formed in these concatenated gene trees (clusters A-C, X & Y – with A. palatopharyngis now grouping into cluster Y). The gyrB-recN concatenated gene tree (Fig 4.4.8) showed a higher level of resolution than thatCape of the 16S rRNA gene tree (Fig 4.4.5), as did the gyrB-recN-16S rRNA concatenated geneof tree (Fig 4.4.9). Both of these concatenated trees (Figs 4.4.8 & 4.4.9) almost exactly resembled each other and the recN gene tree (Fig 4.4.6) and all show similar levels of resolution. However, the resolution was slightly lower with the inclusion of the 16S rRNA gene (branch lengths are slightly shorter).

There are 15 bootstrap values that are greater than 90% in the gyrB-recN concatenated gene tree (Fig 4.4.8), whilst there are University16 in the gyrB-recN-16S rRNA concatenated gene tree (Fig 4.4.9). These numbers are higher than was recorded for either of the two recN-gene based trees, but lower than was recorded in the gyrB-gene based trees, indicating that they show intermediate robustness between the trees constructed with just one of these protein encoding genes and the 16S rRNA gene trees. This is interesting, considering that usually by increasing the length of the sequence that is used in the phylogenetic analysis, the robustness of the resulting tree topology is strengthened. However, this was not the case when the recN gene was added to gyrB (another protein coding gene), where the recN gene lowered the robustness of the tree topology. When trees were constructed based on only the third nucleotide position of the codons in the gyrB-recN concatenated gene sequence (Appendix I), the tree closely resembled that based on the entire gyrB-recN gene 196 sequence, however the number of bootstrap values above 90% dropped to only nine, compared to 15 in the tree based on the full gyrB-recN sequence.

T 64 ‘Amycolatopsis circi’ S1.3 100 ‘Amycolatopsis equina’ SE(8)3T ‘Amycolatopsis hippodromi’ S3.6T Amycolatopsis albidoflavus NRRL B-24149T 100 *63 Amycolatopsis halotolerans NRRL B-24428T B Amycolatopsis rubida NRRL B-24150T 75 Amycolatopsis echigonensis JCM 21831T * T *99 100 Amycolatopsis niigatensis JCM 21832 Amycolatopsis jejuensis NRRL B-24427T *99 Amycolatopsis sulphurea NRRL 2822T X Amycolatopsis saalfeldensis DSM 44993T *95 Amycolatopsis australiensis DSM 44671T

T *92 Amycolatopsis plumensis NRRL B-24324 Amycolatopsis tolypomycina NRRL B-24205T 100 *58 Amycolatopsis balhimycina NRRLTown B-24207T C T *99 62 Amycolatopsis vancoresmycina NRRL B-24208 Amycolatopsis mediterranei NRRL B-3240T *69 Amycolatopsis rifamycinica DSM 46095T

T *73 Amycolatopsis orientalis NRRL 2450 AmycolatopsisCape regifaucium DSM 45072T Amycolatopsis coloradensis NRRL 3218T * 100 ‘Amycolatopsisof umgeniensis’ UM16T

T *99 Amycolatopsis alba NRRL 18532 * T Amycolatopsis azurea NRRL 11412 A T 77 Amycolatopsis lurida NRRL 2430 Amycolatopsis decaplanina NRRL B-24209T 99 Amycolatopsis japonica NRRL B-24138T Amycolatopsis keratiniphila subsp. nogabecina NRRL B-24206T *99 *100 Amycolatopsis keratiniphila subsp. keratiniphila NRRL B-24117T University T *59 Amycolatopsis nigrescens DSM 44992 Amycolatopsis palatopharyngis DSM 44832T

T *96 Amycolatopsis minnesotensis NRRL B-24435 Amycolatopsis sacchari DSM 44468T Y 84 Amycolatopsis taiwanensis DSM 45107T 74 *64 Amycolatopsis thermoflava NRRL B-24140T Streptomyces avermitilis MA-4680T

0.05

Figure 4.4.8 Unrooted phylogenetic tree based on the gyrB-recN concatenated gene sequence for 31 validly published and four unpublished members of the genus Amycolatopsis. The tree was constructed using the neighbor-joining method based on 2520nt of sequence. The percentage bootstrap values of 1000 replications are shown at each node (only values above 50% are shown), with asterisks (*) indicating the clades that were conserved in all tree drawing algorithms (section

4.3.4). Accession numbers of the gyrB gene sequences used are shown in Fig 4.4.3. The scale bar indicates 5 nucleotide substitutions per 100 nucleotides. An S. avermitilis MA-4680T gyrB-recN concatenated gene sequence (NC_003155 and BA000030, respectively) was used as an outgroup. Groups A-C, X and Y indicate conserved clusters of strains. 197

T 68 ‘Amycolatopsis circi’ S1.3 100 ‘Amycolatopsis equina’ SE(8)3T ‘Amycolatopsis hippodromi’ S3.6T Amycolatopsis albidoflavus 100 *81 Amycolatopsis halotolerans B Amycolatopsis rubida 100 Amycolatopsis echigonensis * *100 Amycolatopsis niigatensis *100 Amycolatopsis jejuensis 65 Amycolatopsis sulphurea X *98 Amycolatopsis saalfeldensis Amycolatopsis australiensis

*98 Amycolatopsis plumensis Amycolatopsis tolypomycina *100 *51 Amycolatopsis balhimycina C *100 89 Amycolatopsis vancoresmycina Amycolatopsis mediterranei *82 Amycolatopsis rifamycinicaTown *97 Amycolatopsis orientalis Amycolatopsis regifaucium Amycolatopsis coloradensis *62 *100 ‘Amycolatopsis umgeniensis’ UM16T CapeAmycolatopsis alba 78 *98 of Amycolatopsis azurea A 83 Amycolatopsis lurida Amycolatopsis decaplanina 100 Amycolatopsis japonica Amycolatopsis keratiniphila subsp. nogabecina *100 *100 Amycolatopsis keratiniphila subsp. keratiniphila Amycolatopsis palatopharyngis Amycolatopsis minnesotensis 63 Amycolatopsis nigrescens University Y 59 Amycolatopsis sacchari Amycolatopsis taiwanensis *89 *95 Amycolatopsis thermoflava Streptomyces avermitilis

0.05

Figure 4.4.9 Unrooted phylogenetic tree based on the gyrB-recN-16S rRNA concatenated gene sequence for 31 validly published and four unpublished members of the genus Amycolatopsis. The tree was constructed using the neighbor- joining method based on 3873nt of sequence. The percentage bootstrap values of 1000 replications are shown at each node (only values above 50% are shown), with asterisks (*) indicating the clades that were conserved in all tree drawing algorithms (section 4.3.4). Accession numbers of the 16S rRNA and gyrB gene sequences used are shown in Figs 4.4.2 and 4.4.3, respectively. The scale bar indicates 5 nucleotide substitutions per 100 nucleotides. An S. avermitilis MA-4680T gyrB-recN-16S rRNA concatenated gene sequence (NC_003155-BA000030-AF145223) was used as an outgroup. Groups A-C, X and Y indicate the conserved clusters of strains. 198

4.4.3 Sequence analysis 4.4.3.1 gyrB Gene analysis The sequence similarities between the gyrB genes of all the pairs of strains for which DDH data are available were determined. Similarity values ranged from 79.50% (A. fastidiosa vs A. sulphurea) to 100% (between the strains ‘A. circi’, ‘A. equina’ and ‘A. hippodromi’), with 98.95% (A. echigonensis vs A. niigatensis) being the next highest similarity (Table 4.4.1). When compared to the corresponding 16S rRNA gene sequence similarities, the gyrB gene sequence similarities were lower, indicating that the gyrB gene comparisons are better able to resolve closely related strains than the 16S rRNA gene comparisons. The only exceptions were the A. echigonensis – A. niigatensis and A. eurytherma – A. methanolica pairs, where the gyrB gene sequence similarity was almost identical to the 16S rRNA gene sequence similarity and between the strains ‘A. circi’, ‘A. equina’ and ‘A. hippodromi’, where the gyrB gene similarity was higher than that of the 16S rRNA gene. Town When the pairwise gyrB gene sequence similarities were plotted against their corresponding DDH values, no linear relationship was found to exist between them (R2=0.0372), making the prediction of the DNA relatedness from the gyrB gene sequence similarityCape impossible (Fig 4.4.10). However the genetic distance based on the gyrB gene has been shown to differentiate effectively between strains within the genera Micromonospora (Kasai et al.,of 2000) and Kribbella (Kirby et al., 2010).

100

98

University96

94 sequence (%) similarity gyrB 92 xy += 642.950205.0 R2 = 0372.0

90 0 10 20 30 40 50 60 70 80 DNA relatedness (%)

Figure 4.4.10 Plot of gyrB gene sequence similarities against the DNA relatedness values for pairs of strains in the genus Amycolatopsis (data from Table 4.4.1). The line represents the best fit for the data, with its equation and R2 value being indicated. All published DDH values of 0 were omitted. 199

Table 4.4.1 Amycolatopsis gyrB gene sequence analysis data. gyrB 16S rRNA gyrB-based gyrB-based DNA Source sequence sequence genetic genetic Relatedness of DDH Strain Pair similarity similarity distance distance (%)* data (%) (%) (1290nt) (315nt) A. alba vs A. azurea 97.68 98.48 0.024 0.034 56 1 A. alba vs A. coloradensis 94.86 99.32 0.054 0.108 27 1 A. alba vs A. fastidiosa 81.28 94.12 0.206 0.337 0 1 A. alba vs A. lurida 95.60 98.40 0.046 0.066 24 1 A. alba vs A. mediterranei 91.65 98.16 0.089 0.176 25 1 A. alba vs A. orientalis 95.28 98.12 0.051 0.063 30 1 A. alba vs A. sulphurea 87.81 96.43 0.133 0.260 0 1 A. alba vs ‘A. umgeniensis’ 96.36 99.23 0.037 0.041 18.4 2 A. albidoflavus vs A. echigonensis 96.41 98.37 0.037 0.088 46.5 3 A. albidoflavus vs ‘A. hippodromi’ 97.81 98.2 0.023 0.051 22.7 4 A. albidoflavus vs A. niigatensis 96.36 98.85 0.037 0.088 33.6 3 A. azurea vs A. coloradensis 95.10 98.43 0.051 0.108 33 1 A. azurea vs A. decaplanina 96.41 99.11 0.038 0.063 55.7 5 A. azurea vs A. fastidiosa 81.84 94.46 0.201 0.332 0 1 A. azurea vs A. lurida 95.97 99.35 0.041 0.074 37 1 A. azurea vs A. mediterranei 92.08 97.88 0.085 0.184 0 1 A. azurea vs A. orientalis 95.71 98.68 0.045 0.070 19 1 A. azurea vs A. sulphurea 87.99 98.64 0.132 Town 0.270 0 1 A. balhimycina vs A. mediterranei 95.69 98.76 0.046 0.088 46 6 A. balhimycina vs A. tolypomycina 96.3 98.57 0.037 0.066 61 6 A. balhimycina vs A. vancoresmycina 95.61 98.14 0.046 0.081 53 6 ‘A. circi’ vs ‘A. equina’ 100 99.72 0.00 0.00 67.9 4 ‘A. circi’ vs ‘A. hippodromi’ 100 99.71 0.00 0.00 12.8 4 A. coloradensis vs A. fastidiosa 81.51 94.24 Cape 0.207 0.353 0 1 A. coloradensis vs A. lurida 95.09 98.78 0.051 0.092 37 1 A. coloradensis vs A. mediterranei 92.00 98.11of 0.085 0.155 0 1 A. coloradensis vs A. orientalis 95.04 98.56 0.050 0.077 0 1 A. coloradensis vs A. sulphurea 88.11 96.46 0.129 0.242 0 1 A. coloradensis vs ‘A. umgeniensis’ 96.35 99.52 0.037 0.084 16.2 2 A. decaplanina vs A. lurida 97.52 99.14 0.025 0.038 31.5 5 A. decaplanina vs A. orientalis 95.62 99.84 0.046 0.045 50.5 5 A. echigonensis vs ‘A. hippodromi’ 96.26 98.63 0.04 0.091 23.8 4 A. echigonensis vs A. niigatensis 98.95 98.98 0.011 0.017 60 3 A. echigonensis vs A. rubida 95.29 97.94 0.05 0.095 41.5 3 ‘A. equina’ vs ‘A. hippodromi’ 100 99.86 0.00 0.00 9.8 4 A. eurytherma vs A. methanolicaUniversity 98.84 98.76 0.011 0.024 60 7 A. fastidiosa vs A. lurida 82.27 94.17 0.197 0.327 0 1 A. fastidiosa vs A. mediterranei 83.30 93.98 0.186 0.307 11 1 A. fastidiosa vs A. orientalis 81.69 94.73 0.202 0.327 0 1 A. fastidiosa vs A. sulphurea 79.50 94.35 0.236 0.409 7 1 A. halotolerans vs ‘A. hippodromi’ 96.71 98.7 0.036 0.069 34.4 4 ‘A. hippodromi’ vs A. niigatensis 96.28 98.41 0.04 0.084 24.6 4 ‘A. hippodromi’ vs A. rubida 96.52 97.55 0.037 0.076 25 4 A. japonica vs A. keratiniphila subsp. 97.07 99.00 0.031 0.077 59.5 8 keratiniphila A. lurida vs A. mediterranei 91.81 97.63 0.089 0.155 6 1 A. lurida vs A. orientalis 95.14 98.63 0.049 0.059 44.9† 1,6,9,10 A. lurida vs A. sulphurea 88.12 96.53 0.129 0.242 0 1 A. mediterranei vs A. orientalis 92.38 97.53 0.081 0.143 0 1 A. mediterranei vs A. rifamycinica 97.39 98.77 0.028 0.031 40 11 A. mediterranei vs A. sulphurea 89.4 96.40 0.115 0.184 0 1

200

Table 4.4.1 continued gyrB 16S rRNA gyrB-based gyrB-based DNA Source sequence sequence genetic genetic Relatedness of DDH Strain Pair similarity similarity distance distance (%)* data (%) (%) (1290nt) (315nt) A. mediterranei vs A. tolypomycina 95.27 98.72 0.05 0.063 55 6 A. mediterranei vs A. vancoresmycina 97.09 98.31 0.030 0.027 54 6 A. methanolica vs A. thermoflava 98.67 99.73 0.013 0.027 21 12 A. niigatensis vs A. rubida 95.24 97.16 0.051 0.095 31.8 3 A. orientalis vs A. regifaucium 95.61 99.45 0.042 0.070 42.5 13 A. orientalis vs A. sulphurea 87.85 96.77 0.128 0.228 0 1 A. tolypomycina vs A. vancoresmycina 96.47 99.01 0.037 0.063 54 6 * Most DNA relatedness values were obtained from published DDH data.  1, Labeda, 1995; 2, Data obtained from Paul Meyers (personal communication); 3, Ding et al., 2007; 4, Data determined in this study; 5, Wink et al., 2004; 6, Wink et al., 2003; 7, Kim et al., 2002; 8, Al-Musallam et al., 2003; 9, Lechevalier et al., 1986; 10, Stackebrandt et al., 2004; 11, Bala et al., 2004; 12, Chun et al., 1999; 13, Tan et al., 2007. † average of 44 (Labeda, 1995), 44.5 (Wink et al., 2004), 46 (Lechevalier et al., 1986) and 45.2 (Stackebrandt et al., 2004)

The genetic distances between Amycolatopsis type strains based on the gyrB gene (1290nt) were calculated and are displayed in Table 4.4.1 (genetic distances between all strains are included in Appendix J). Values ranged from zero (between the strains ‘TownA. circi’, ‘A. equina’ and ‘A. hippodromi’), with 0.011 being the next lowest value (A. echigonensis vs A. niigatensis and A. eurytherma vs A. methanolica), to 0.236 (A. fastidiosa vs A. sulphurea), with 0.132 (A. alba vs A. sulphurea and A. coloradensis vs A. sulphurea) beingCape the largest genetic distance not involving A. fastidiosa (the values for which are all above 0.18).of Only six values fell below the 0.014 threshold value determined to correlate to 70% DNA relatedness within the genus Micromonospora (Kasai et al., 2000). Two of these were for members of cluster E, whilst four were for members of cluster B (Figs 4.4.2-4.4.9). There are however, 20 gyrB genetic distance values that fall below the 0.04 threshold proposed to distinguish species in the genus Kribbella (Kirby et al., 2010).

A genetic distance of >0.02University would be more appropriate to use as a threshold for predicting which strains are different species in the genus Amycolatopsis. There were only six data points below this value (Table 4.4.1 & Fig 4.4.11). The genetic distance between A. echigonensis and A. niigatensis, as well as A. eurytherma and A. methanolica, was 0.011 (98.95% and 98.84% gyrB gene sequence similarity, respectively), that between A. methanolica and A. thermoflava was 0.013 (98.67% sequence similarity) and the values between the strains ‘A. circi’, ‘A. equina’ and ‘A. hippodromi’ are all zero (100% sequence similarity). However, DDH experiments showed that they share only 60% (A. echigonensis vs A. niigatensis and A. eurytherma vs A. methanolica; Kim et al., 2002; Ding et al., 2007), 21% (A. methanolica vs A. thermoflava; Chun et al., 1999) and 67.9 ± 2.9%, 12.8 ± 2.4% and 9.8 ± 5.5% (‘A. circi’ vs ‘A. equina’, ‘A. circi’ vs ‘A. hippodromi’ and ‘A. equina’ vs ‘A. 201 hippodromi’, respectively) DNA relatedness. Along with phenotypic differences, these DNA relatedness values allowed the strains to be recognised as distinct genomic species.

100

80

60

40 DNA DNA relatedness (%)

20

0 0.00 0.02 0.04 0.06 Town0.08 0.10

gyrB-based genetic distance Figure 4.4.11 Plot of gyrB-based genetic distances against the DNA relatedness values for pairs of strains in the genus Amycolatopsis (data from Table 4.4.1). The horizontal dashed line shows the 70% DNA relatedness threshold, with the vertical dashed line showing the 0.02 gyrB genetic distance threshold proposed to determine whether DDH is required to delineate species. All published DDH values of 0 were omitted. Cape of

By analysis of a multiple sequence alignment with all 38 Amycolatopsis gyrB gene sequences, a 315nt segment, corresponding to positions 480–795bp of the S. avermitilis MA-4680T gyrB gene sequence (NC_003155), was identified that contains a higher level of variation than the remainder of the sequence. This region is located in the segment of the gene amplified using primers 7G-gyrB-F & GgyrB-R1, and can beUniversity identified after aligning with the S. avermitilis MA-4680T sequence. The genetic distances calculated based on this 315nt fragment (Appendix K) are somewhat higher than those based on the 1290nt section of the gene (Table 4.4.1), however they do allow for the A. eurytherma – A. methanolica and A. methanolica – A. thermoflava pairs to be better resolved, with the genetic distances being 0.024 and 0.027, respectively. When these genetic distances are plotted against the DDH values, the resulting plot (Appendix L) is very similar to that shown in Fig 4.4.11, except that there are now only four values below 0.02, three of which involve the strains ‘A. circi’, ‘A. equina’ and ‘A. hippodromi’ (which all have identical gyrB gene sequences) (Table 4.4.1). This supports the use of a gyrB genetic distance of >0.02 as a threshold to predict whether two 202

Amycolatopsis strains belong to the same species. For genetic distances of less than 0.02, DDH would need to be performed to determine whether the strains represent distinct genomic species.

4.4.3.2 recN Gene analysis The sequence similarities between the recN genes of all the pairs of strains for which DDH data are available were determined. Similarity values ranged from 34.18% (A. azurea vs A. mediterranei) to 99.76% (‘A. circi’ vs ‘A. equina’), with 98.59% (A. echigonensis vs A. niigatensis) being the next highest similarity not involving the three strains isolated in this study (Table 4.4.2). When compared to the corresponding 16S rRNA gene sequence similarities, the recN gene sequence similarities were, in almost all cases, lower. This, as was the case with the gyrB gene comparisons, shows that the recN genes are better able to resolve closely related strains than the 16S rRNA gene comparisons. The only exceptions were the A. echigonensis – A. niigatensis, ‘A. circi’ – ‘A. hippodromi’ and ‘A. equina’ – ‘A. hippodromi’ pairs, where the recN gene sequence similarityTown was almost identical to the 16S rRNA gene sequence similarity, and between the strains ‘A. circi’ and ‘A. equina’, where the recN gene similarity was higher than that of the 16S rRNA gene.

Cape Table 4.4.2 Amycolatopsis recN gene sequence analysis data. recN 16S rRNA recN-based DNA Source sequenceof sequence genetic Relatedness of DDH Strain Pair similarity similarity distance (%)* data (%) (%) (1290nt) A. alba vs A. azurea 94.67 98.48 0.056 56 1 A. alba vs A. coloradensis 92.57 99.32 0.08 27 1 A. alba vs A. lurida 92.25 98.40 0.084 24 1 A. alba vs A. mediterranei 80.71 98.16 0.22 25 1 A. alba vs A. orientalis 92.01 98.12 0.085 30 1 A. alba vs A. sulphurea 78.21 96.43 0.259 0 1 A. alba vs ‘A. umgeniensis’ 92.5 99.23 0.079 18.4 2 A. albidoflavus vs A.University echigonensis 94.43 98.37 0.056 46.5 3 A. albidoflavus vs ‘A. hippodromi’ 95.37 98.2 0.05 22.7 4 A. albidoflavus vs A. niigatensis 94.9 98.85 0.051 33.6 3 A. azurea vs A. coloradensis 91.56 98.43 0.087 33 1 A. azurea vs A. decaplanina 95.13 99.11 0.052 55.7 5 A. azurea vs A. lurida 92.5 99.35 0.075 37 1 A. azurea vs A. mediterranei 34.18 97.88 0.232 0 1 A. azurea vs A. orientalis 91.63 98.68 0.092 19 1 A. azurea vs A. sulphurea 77.98 98.64 0.26 0 1 A. balhimycina vs A. mediterranei 91.92 98.76 0.083 46 6 A. balhimycina vs A. tolypomycina 90.58 98.57 0.104 61 6 A. balhimycina vs A. vancoresmycina 91.95 98.14 0.087 53 6 ‘A. circi’ vs ‘A. equina’ 99.76 99.72 0.001 67.9 4 ‘A. circi’ vs ‘A. hippodromi’ 99.68 99.71 0.002 12.8 4 A. coloradensis vs A. lurida 91.41 98.78 0.093 37 1 A. coloradensis vs A. mediterranei 79.14 98.11 0.241 0 1 203

Table 4.4.2 cont recN 16S rRNA recN-based DNA Source sequence sequence genetic Relatedness of DDH Strain Pair similarity similarity distance (%)* data (%) (%) (1290nt) A. coloradensis vs A. orientalis 91.29 98.56 0.92 0 1 A. coloradensis vs A. sulphurea 76.48 96.46 0.284 0 1 A. coloradensis vs ‘A. umgeniensis’ 91.32 99.52 0.09 16.2 2 A. decaplanina vs A. lurida 94.77 99.14 0.56 31.5 5 A. decaplanina vs A. orientalis 92.03 99.84 0.085 50.5 5 A. echigonensis vs ‘A. hippodromi’ 94.69 98.63 0.053 23.8 4 A. echigonensis vs A. niigatensis 98.59 98.98 0.015 60 3 A. echigonensis vs A. rubida 94.95 97.94 0.052 41.5 3 ‘A. equina’ vs ‘A. hippodromi’ 99.53 99.86 0.003 9.8 4 A. halotolerans vs ‘A. hippodromi’ 95.67 98.7 0.047 34.4 4 ‘A. hippodromi’ vs A. niigatensis 94.92 98.41 0.051 24.6 4 ‘A. hippodromi’ vs A. rubida 95 97.55 0.053 25 4 A. japonica vs A. keratiniphila subsp. 95.98 99.00 0.041 59.5 7 keratiniphila A. lurida vs A. mediterranei 78.8 97.63 0.253 6 1 A. lurida vs A. orientalis 90.78 98.63 0.98 44.9† 1,6,8,9 A. lurida vs A. sulphurea 77.3 96.53 0.275 0 1 A. mediterranei vs A. orientalis 78.81 97.53 0.245Town 0 1 A. mediterranei vs A. rifamycinica 94.53 98.77 0.055 40 10 A. mediterranei vs A. sulphurea 81.64 96.40 0.209 0 1 A. mediterranei vs A. tolypomycina 92.68 98.72 0.073 55 6 A. mediterranei vs A. vancoresmycina 93.59 98.31 0.68 54 6 A. niigatensis vs A. rubida 95.24 Cape 97.16 0.048 31.8 3 A. orientalis vs A. regifaucium 93.17 99.45 0.72 42.5 11 A. orientalis vs A. sulphurea 77.11 96.77 0.271 0 1 A. tolypomycina vs A. vancoresmycina 92.77 of 99.01 0.76 54 6 * Most DNA relatedness values were obtained from published DDH data.  1, Labeda, 1995; 2, Data obtained from Paul Meyers (personal communication); 3, Ding et al., 2007; 4, Data determined in this study; 5, Wink et al., 2004; 6, Wink et al., 2003; 7, Al-Musallam et al., 2003; 8, Lechevalier et al., 1986; 9, Stackebrandt et al., 2004; 10, Bala et al., 2004; 11, Tan et al., 2007. † average of 44 (Labeda, 1995), 44.5 (Wink et al., 2004), 46 (Lechevalier et al., 1986) and 45.2 (Stackebrandt et al., 2004)

University When the pairwise recN gene sequence similarities were plotted against their corresponding DDH values, no linear relationship was found to exist between them (R2=0.0616), making the prediction of the DNA relatedness from the recN gene sequence similarity impossible (Fig 4.4.12). In fact, the predicted DDH values determined from the equation of the line of best fit drawn through the plotted values in Fig 4.4.12 varied greatly from the actual DDH values. In many instances there were huge discrepancies between the predicted and actual DDH values for different pairs of strains which showed similar levels of recN gene sequence similarity (Appendix M). Similarly, the equation provided by Zeigler (2003) was not effective at predicting the extent of DDH and greatly overestimated the level of genome similarity between the strains (Appendix M). 204

The genetic distances between Amycolatopsis type strains based on the recN gene (1230nt) were calculated and are displayed in Table 4.4.2 (genetic distances between all strains are included in Appendix N). Values ranged from 0.001 (‘A. circi’ vs ‘A. equina’), with 0.015 (A. echigonensis vs A. niigatensis) being the next lowest value not involving the three strains isolated in this study, to 0.98 (A. lurida vs A. orientalis). Only three values (those between ‘A. circi’, ‘A. equina’ and ‘A. hippodromi’) fell below the 0.014 gyrB threshold value determined to correlate to 70% DNA relatedness within the genus Micromonospora (Kasai et al., 2000). All were for members of cluster B (Figs 4.4.2-4.4.9). There are four genetic distance values (those between ‘A. circi’, ‘A. equina’ and ‘A. hippodromi’ and that between A. echigonensis vs A. niigatensis) that fall below the 0.02 threshold proposed for the gyrB gene and below the 0.04 gyrB threshold proposed to distinguish species in the genus Kribbella (Kirby et al., 2010).

100 Town

95

90 Cape 85 of sequence (%) similarity

recN 80 xy += 967.900622.0 R2 = 0616.0

75 0 10 20 30 40 50 60 70 80

DNA relatedness (%)

Figure 4.4.12 Plot of recN gene sequence similarities against the DNA relatedness values for pairs of strains in the genus Amycolatopsis (data from TableUniversity 4.4.2). The line represents the best fit for the data, with its equation and R2 value being indicated. All published DDH values of 0 were omitted.

A recN genetic distance of >0.04 would therefore be appropriate to use as a threshold for predicting which strains are different species in the genus Amycolatopsis. There were only four data points present that were below this value (Table 4.4.2 & Fig 4.4.13). The genetic distance between A. echigonensis and A. niigatensis was 0.015 (98.59% recN gene sequence similarity) and the values between the strains ‘A. circi’, ‘A. equina’ and ‘A. hippodromi’ were 0.001, 0.002 and 0.003 (99.76, 99.68 and 99.53% recN gene sequence similarity, respectively). However, DDH experiments showed them to be separate genomic species (60% DNA relatedness for A. echigonensis vs A. 205 niigatensis (Ding et al., 2007), 67.9 ± 2.9% for ‘A. circi’ vs ‘A. equina’, 12.8 ± 2.4% for ‘A. circi’ vs ‘A. hippodromi’ and 9.8 ± 5.5% for ‘A. equina’ vs ‘A. hippodromi’). Along with phenotypic differences, these DNA relatedness values allowed the strains to be recognised as distinct genomic species.

100

80

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40 DNA relatednessDNA (%) 20 Town

0 0.0 0.2 0.4 0.6 0.8 1.0 recN-based geneticCape distance Figure 4.4.13 Plot of recN-based genetic distances against the DNA relatedness values for pairs of strains in the genus Amycolatopsis (data from Table 4.4.2). The horizontal dashed line shows the 70% DNA relatedness threshold, with the vertical dashed line showing the 0.04 recN genetic distanceof threshold proposed to determine whether DDH is required to delineate species. All published DDH values of 0 were omitted.

Examination of a multiple sequence alignment of the recN genes from the 35 Amycolatopsis strains analyzed in this study revealed no highly variable regions throughout the length of the sequence (1230nt). Therefore thereUniversity is no hyper-variable region present in the section of the recN gene that was sequenced.

4.4.4 Evaluation of the gyrB and recN gene sequence analysis methods The effectiveness of the gyrB- and recN-based genetic distance methods were tested on the three Amycolatopsis strains isolated in this study, ‘A. circi’ strain S1.3T, ‘A. equina’ strain SE(8)3T and ‘A. hippodromi’ strain S3.6T, (sections 2.4.3 & 3.4.2.1) as well as another laboratory strain, ‘A. umgeniensis’ strain UM16T, isolated by Paul Meyers. The gyrB-based genetic distance values between ‘A. circi’, ‘A. equina’ and ‘A. hippodromi’ were zero, showing that they required DDH to distinguish them from each other. The gyrB-based genetic distance values to closely related type 206 strains were all above the 0.02 threshold that was proposed to distinguish species (section 3.4.2.1). Similarly the recN-based genetic distances were almost identical between the isolated strains (0.001, 0.002 and 0.003), but those between these strains and closely related type strains with validly- published names were all above the proposed 0.04 threshold (Table 4.4.2). DDH experiments between ‘A. hippodromi’ and the type strains with validly-published names confirmed them to be separate species, as did the DDH experiments between the three isolates (section 3.4.2.1, Tables 4.4.1 & 4.4.2). The same was the case for ‘A. umgeniensis’, where the gyrB- and recN-based genetic distances were above the 0.02 and 0.04 thresholds, respectively, to the two most closely related type strains, A. alba and A. coloradensis (Tables 4.4.1 & 4.4.2). DDH experiments confirmed ‘A. umgeniensis’ to be separate from these species, showing only 18.4% and 16.2% DNA relatedness to A. alba and A. coloradensis, respectively (Tables 4.4.1 & 4.4.2) (P. Meyers, personal communication). These data thereby support the use of genetic distances as a guide to species novelty in the genus Amycolatopsis. Town

4.5 Discussion Cape The screening for the presence of antibiotic biosynthetic genes revealed the presence of genes in many strains that were not known to possess themof and showed that strains possessing a particular biosynthetic gene, particularly for glycopeptide production (and to a lesser extent ansamycin production), tended to cluster together in the phylogenetic trees. Owing to this tendency, it may be possible to predict the antibiotic-production ability of a novel strain from its association in the 16S- rRNA gene tree. This would be particularly helpful, as it would give researchers an idea of the antibiotic production potential of the strain before it has even been screened for antibiotic activity. By identifying strains thatUniversity are more likely to be antibiotic producers, it allows for these strains to be given priority so that there is a higher chance of success in the discovery of antibiotic molecules.

From examination of the phylogenetic trees (Figs 4.4.2 – 4.4.9), it can be seen that both the gyrB and recN genes can be used to support the phylogenetic groupings obtained by the conventional 16S rRNA gene phylogenetic analysis, with most overall groupings being similar between the trees (clusters A-C, with D & E conserved in the gyrB-gene based trees and X & Y in the gyrB- and recN- gene based trees). The more distantly related strains however do show different clustering in the trees, which can be explained by the lower sequence conservation in the gyrB and recN gene 207 sequences than in the 16S rRNA gene sequences. Interestingly, the association of cluster X with cluster B in the gyrB- and recN-gene based trees shows improved bootstrap support over these strains’ association within the 16S rRNA gene trees.

The concatenation of the gyrB or recN gene sequences with the 16S rRNA gene sequences was useful in that it increased both the resolution and robustness of the constructed trees. However, it seems that the concatenation of the gyrB and recN gene sequences, with or without the 16S rRNA gene sequences, is not necessary for phylogenetic resolution within the genus Amycolatopsis, as the resolution of these gyrB-recN gene trees is about the same as those based on just one of these genes concatenated with the 16S rRNA gene. However, the confidence of the phylogenetic groupings in recN-gene based trees is lower than those in the trees excluding the recN gene. Thus despite the recN gene showing higher sequence variation than the 16S rRNA gene and producing trees that have groupings with higher bootstrap values, it seems that the gyrB gene is better suited for phylogenetic analysis within the genus, as it does exactly what the recN gene does,Town but the tree topologies are more robust and the sequences themselves are far more easily obtained.

Interestingly, the phylogeny of the three AmycolatopsisCape strains isolated in this study (S1.3, S3.6 and SE(8)3) is not adequately resolved using the gyrBof gene alone, as can be seen in Fig 4.4.3. This therefore indicates that the gyrB gene may not always be the best to resolve the very closely related strains within the genus, where the inclusion of alternative genes would then be favoured. This is demonstrated in Figs 4.4.8 & 4.4.9, where the concatenated genes did show a somewhat higher resolving power that the gyrB gene alone for these three isolates.

Despite the inability of Universitythe gyrB or recN gene sequence similarities to allow the prediction of DNA relatedness between pairs of strains, the calculation of genetic distances proved to be a useful way to assess quickly whether an isolate is worthy of full taxonomic characterisation. Pairs of strains that have a gyrB-based genetic distance of greater than 0.02 or a recN-based genetic distance of above 0.04 are likely to be different species, i.e. sharing a DNA relatedness of below 70% (Wayne et al., 1987) (Figs 4.4.11 & 4.4.13). Conversely, strains with genetic distances of less than 0.02 (gyrB-based) or 0.04 (recN-based) would need to be subjected to DDH experiments to assess the level of genomic similarity. It should also be noted that a gyrB gene sequence similarity of less than 98.95% (over >1000nt) could also be used as an indicator of which strains are likely to share less than 70% genome identity, as none of the type-strain pairs examined, except those involving ‘A. 208 circi’, ‘A. equina’ and ‘A. hippodromi’, share a gyrB gene sequence similarity of above 98.95%. Similarly a recN gene sequence similarity of 98.59% (over >1000nt) could be used to indicate novelty.

The varying threshold values of gyrB genetic distances used as the cut off for predicting novel species within the genera Amycolatopsis (0.02), Kribbella (0.04) and Micromonospora (0.014) are clear evidence that this gene undergoes varying rates of evolution within these respective genomes. Perhaps this is due to varying selective pressures placed on the different genera within the environment. Based on these data it can be presumed that the gyrB gene will undergo similarly different rates of evolution within the genomes of other bacterial genera. Therefore a single gyrB genetic distance threshold cannot be applied to all genera and this value will need to be calculated independently for each genus in which the method is applied. Similar conclusions cannot be drawn for the recN gene as this is the first study that made use of the recN based genetic distance to predict the novelty of actinobacterial strains. However, the fact that in theTown genus Amycolatopsis, the recN sequence similarity does not correlate with the DDH data as it does in other genera (Geobacillus, Streptococcus and members of the family ‘Leuconostocaceae’), would suggest that varying evolutionary rates are experienced for this gene as well.Cape of This study clearly revealed that the gyrB and recN genes are useful in phylogenetic studies amongst Amycolatopsis strains and that they both have a higher resolving power than the 16S rRNA gene. However, it seems that the gyrB gene is better suited of the two genes for phylogenetic analysis in this genus. The recN gene may prove to be of more use along with others genes in a MLSA type analysis. The calculation of the gyrB- or recN-based genetic distances between an isolated strain and other known type strainsUniversity can allow for its potential novelty to be quickly determined. However, it appears that the gyrB gene would be favoured for this approach, as the gyrB gene sequence can be obtained far more easily than that of the recN gene (due mainly to the difficulties associated with PCR amplification and sequencing of the recN gene). On the other hand, the recN-gene based method may be better suited to differentiate between the more closely related strains, as the gene is less conserved than that of the gyrB gene.

It is therefore proposed that a partial gyrB gene sequence should be determined from Amycolatopsis isolates and the genetic distance determined between these strains and their closest phylogenetic relatives (as assessed by 16S-rRNA gene phylogenetic analysis) to assess the potential novelty of the 209 strains prior to commencing polyphasic taxonomic characterisation. Furthermore the gyrB (particularly the 315nt variable fragment) and recN genes would be good candidates to be used in conjunction with other housekeeping gene sequences for possible future MLSA of members of this genus.

Based on the gyrB gene phylogenetic trees (Figs 4.4.3 & 4.4.4), as well as the genetic distance data presented, A. fastidiosa does not appear to belong in the genus Amycolatopsis as it consistently formed an outgroup in all of the neighbor-joining trees (clustering with S. avermitilis MA-4680T in the maximum parsimony trees, with both strains forming the outgroup) and has gyrB genetic distances significantly larger that those between any other pairs of type strains of the genus. In fact the genetic distance values involving A. fastidiosa are similar to those between S. avermitilis MA- 4680T and any Amycolatopsis type strain (Appendices J & K), which further suggests that this strain belongs to a different genus. Town Additional support for the need to reclassify A. fastidiosa was obtained after conducting a nucleotide-nucleotide BLAST search with the 16S rRNA gene sequence of the type strain of A. fastidiosa. The results contained strains of the generaCape Actinokineospora , Lechevalieria, Lentzea and Saccharothrix and a tree constructed with these strainsof (and Amycolatopsis type strains) revealed that A. fastidiosa grouped with the Actinokineospora strains and not with those of the genus Amycolatopsis (data not shown). A proposal to transfer this strain into the genus Actinokineospora as Actinokineospora fastidiosa comb. nov., is currently in press (Labeda et al., 2010).

4.6 References University

Al-Musallam, A. A., Al-Zarban, S. S., Fasasi, Y. A., Kroppenstedt, R. M. & Stackebrandt, E. (2003). Amycolatopsis keratiniphila sp. nov., a novel keratinolytic soil actinomycete from Kuwait. Int J Syst Evol Microbiol 53, 871-874.

Altschul, S. F., Madden, T. L., Schäffer, A. A., Zhang, J., Zhang, Z., Miller, W. & Lipman, D. J. (1997). Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acid Res 25, 3389-3402.

Arahal, D. R., Sánchez, E., Macián, M. C. & Garay, E. (2008). Value of recN sequences for species identification and as a phylogenetic marker within the family “Leuconostocaceae”. Int Microbiol 11, 33-39.

Bala, S., Khanna, R., Dadhwal, M., Prabagaran, S. R., Shivaji, S., Cullum, J. & Lal, R. (2004). Reclassification of Amycolatopsis mediterranei DSM 46095 as Amycolatopsis rifamycinica sp. nov. Int J Syst Evol Microbiol 54, 1145- 1149.

Chimara, E., Ferazoli, L. & Leão, S. C. (2004). Mycobacterium tuberculosis complex differentiation using gyrB- restriction fragment length polymorphism analysis. Mem Inst Oswaldo Cruz 99, 745-748. 210

Chun, J., Kim, S. B., Oh, Y. K., Seong, C.-N., Lee, D.-H., Bae, K. S., Lee, K.-J., Kang, S.-O., Hah, Y. C. & Goodfellow, M. (1999). Amycolatopsis thermoflava sp. nov., a novel soil actinomycetes from Hainan Island, China. Int J Syst Evol Microbiol 49, 1369-1373.

Coenye, T., Gevers, D., Van de Peer, Y., Vandamme, P. & Swings, J. (2005). Towards a prokaryotic genomic taxonomy. FEMS Microbiol Rev 29, 147-167.

Ding, L., Hirose, T. & Yokota, A. (2007). Amycolatopsis echigonensis sp. nov. and Amycolatopsis niigatensis sp. nov., novel actinomycetes isolated from filtration substrate. Int J Syst Evol Microbiol 57, 1747-1751.

Euzéby, J. P. (2010). List of Prokaryotic names with standing in nomenclature. Accessed November 2009 – February 2010. (http://www.bacterio.cict.fr/).

Glazunova, O. O., Raoult, D. & Roux, V. (2010). recN partial gene sequencing: a new tool for identification and phylogeny within the Streptococcus genus. Int J Syst Evol Microbiol (In Press) doi: 10.1099/ijs.0.018176-0.

Jin, J., Haga, T., Shinjo, T. & Goto, Y. (2004). Phylogenetic analysis of Fusobacterium necrophorum, Fusobacterium varium and Fusobacterium nucleatum based on gyrB gene sequences. J Vet Med Sci 66, 1243-1245.

Kasai, H., Tamura, T. & Harayama, S. (2000). Intrageneric relationships among Micromonospora species deduced from gyrB-based phylogeny and DNA relatedness. Int J Syst Evol Microbiol 50, 127-134.

Kim, B., Sahin, N., Tan, G. Y. A., Zakrzewska-Czerwinska, J. & Goodfellow,Town M. (2002). Amycolatopsis eurytherma sp. nov., a thermophilic actinomycetes isolated form soil. Int J Syst Evol Microbiol 52, 889-894.

Kimura, M. (1980). A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J Mol Evol 16, 111-120.

Kirby, B. M., Everest, G. J. & Meyers, P. R. (2010). PhylogeneticCape analysis of the genus Kribbella based on the gyrB gene: proposal of a gyrB-sequence threshold for recognising new type strains of Kribbella. Antonie van Leeuwenhoek 97, 131-142. of Labeda, D. P. (1995). Amycolatopsis coloradensis sp. nov., the avoparcin (LL-AV290)-producing strain. Int J Syst Bacteriol 45, 124-127.

Labeda, D. P., Price, N. P., Tan, G. Y. A., Goodfellow, M. & Klenk, H.-P. (2010). Emended description of the genus Actinokineospora Hasegawa 1988 and transfer of Amycolatopsis fastidiosa Henssen et al. 1987 as Actinokineospora fastidiosa comb. nov. Int J Syst Evol Microbiol (In Press) doi: 10.1099/ijs.0.016568-0.

Lechevalier, M. P., Prauser, H., Labeda, D. P. & Ruan, J. S. (1986). Two new genera of nocardioform actinomycetes: Amycolata gen. nov. and Amycolatopsis gen. nov. Int J Syst Bacteriol 36, 29-37. University le Roes, M., Goodwin, C. M. & Meyers, P. R. (2008). Gordonia lacunae sp. nov. isolated from an estuary. System Appl Microbiol 31, 17-23.

Saitou, N. & Nei, M. (1987). The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 4, 406-425.

Sambrook, J., Fritsch, E. F. & Maniatis, T. (1989). In Molecular Cloning, a laboratory manual, second edition. Cold Spring Harbor: Cold Spring Harbor Laboratory Press.

Shen, F.-T., Lu, H.-L., Lin, J.-L., Huang, W.-S., Arun, A.B. & Young, C.-C. (2006). Phylogenetic analysis of members of the metabolically diverse genus Gordonia based on proteins encoding the gyrB gene. Res Microbiol 157, 367-375.

Stackebrandt, E., Frederiksen, W., Garrity, G. M., Grimont, P. A. D., Kämpfer, P., Maiden, M. C. J., Nesme, X., Rosselló-Mora, R., Swings, J., Trüper, H. G., Vauterin, L.., Ward, A. C. & Whitman, W. B. (2002). Report of the ad hoc committee for the re-evaluation of the species definition in bacteriology. Int J Syst Evol Microbiol 52, 1043-1047. 211

Stackebrandt, E. & Goebel, B. M. (1994). Taxonomic note: a place for DNA-DNA reassociation and 16S rRNA sequence analysis in the present species definition in bacteriology. Int J Syst Bacteriol 44, 846-849.

Stackebrandt, E., Kroppenstedt, R. M., Wink, J. & Schumann, P. (2004). Reclassification of Amycolatopsis orientalis subsp. lurida Lechevalier et al. 1986 as Amycolatopsis lurida sp. nov., comb. nov. Int J Syst Evol Microbiol 54, 267-268.

Takahashi, K. & Nei, M. (2000). Efficiencies of fast algorithms of phylogenetic inference under the criteria of maximum parsimony, minimum evolution, and maximum likelihood when a large number of sequences are used. Mol Biol Evol 17, 1251-1258.

Takeda, K., Kang, Y., Yazawa, K., Gonoi, T. & Mikami, Y. (2010). Phylogenetic studies of genus Nocardia species based on gyrB gene analyses. J Med Microbiol 59, 165-171.

Tamura, K., Dudley J., Nei, M. & Kumar, S. (2007). MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0. Mol Biol Evol 24, 1596-1599.

Tan, G. Y. A., Robinson, S., Lacey, E., Brown, R., Kim, W. & Goodfellow, M. (2007). Amycolatopsis regifaucium sp. nov., a novel actinomycete that produces kigamicins. Int J Syst Evol Microbiol 57, 2562-2567.

Wayne, L. G., Brenner, D. J., Colwell, R. R., Grimont, P. A. D., Kandler, O., Krichevsky, M. I., Moore, L. H., Moore, W. E. C., Murray, R. G. E., Stackebrandt, E., Starr, M. P. & Trüper, H. G. (1987). Report of the ad hoc committee on reconciliation of approaches to bacterial systematics. Int J Syst BacteriolTown 37, 463-464.

Wink, J., Gandhi, J., Kroppenstedt, R.M., Seibert, G., Straubler, B., Schumann, P. & Stackebrandt, E. (2004). Amycolatopsis decaplanina sp. nov., a novel member of the genus with unusual morphology. Int J Syst Evol Microbiol 54, 235-239.

Wink, J., Kroppenstedt, R.M., Ganguli, B.M., Nadkarni, S.R.,Cape Schumann, P., Seibert, G. & Stackebrandt, E. (2003). Three new antibiotic producing species of the genus Amycolatopsis, Amycolatopsis balhimycina sp. nov., A. tolypomycina sp. nov., A. vancoresmycina sp. nov., and description of Amycolatopsis keratiniphila subsp. keratiniphila subsp. nov. and A. keratiniphila subsp. nogabecina subsp.of nov. System Appl Microbiol 26, 38-46.

Watanabe, K., Nelson, J.S., Harayama, S. & Kasai, H. (2001). ICB database: the gyrB database for identification and classification of bacteria. Nucleic Acids Res 29, 344-345.

Wood, S.A., Kirby, B.M., Goodwin, C.M., le Roes, M. & Meyers, P.R. (2007). PCR screening reveals unexpected antibiotic biosynthetic potential in Amycolatopsis sp. strain UM16. J Appl Microbiol 102, 245-253.

Zeigler, D. R. (2003). Gene sequences useful for predicting relatedness of whole genomes in bacteria. Int J Syst Evol Microbiol 53, 1893-1900. University Zeigler, D. R. (2005). Application of recN sequence similarity analysis to the identification of species within the bacterial genus Geobacillus. Int J Syst Evol Microbiol 55, 1171-1179.

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GENERAL DISCUSSIONTown

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CHAPTER 5

GENERAL DISCUSSION

The ever increasing incidence of antibiotic resistance amongst bacterial pathogens is becoming increasingly problematic and unless new molecules are found to combat these resistant pathogens, a state where we have no antibiotics to treat bacterial infections may well not be that far away. One disease whose treatment is particularly affected by resistance is TB, the worlds’ second leading cause of death by an infectious agent (Singh, 2004). This disease is prevalent all over the world, but occurs more frequently in developing nations (Rodrigues et al., 2007), with sub-Saharan Africa being one of the most badly affected areas (WHO, 2007). It is therefore obvious that a global priority should be the discovery of novel antibiotics to treat this as well as other infectiousTown diseases. Historically, natural sources, particularly microorganisms and more specifically actinobacteria, have been fruitful antibiotic providers (Watve et al., 2001; Peláez, 2006), with the genus Streptomyces being the focus of many discovery programs (Watve et al., 2001; Marinelli,Cape 2009). Thus the isolation of the “rarer” filamentous actinobacterial genera can be the aimof of future discovery programs as members of these rare genera may be a potential “treasure trove” of novel compounds. Although sampling from unexploited and unique environments, with a high level of biodiversity, will help maximize isolation of novel strains (Knight et al., 2003), this is not crucially important as novel strains are continually isolated, even from sources that have been routinely screened (e.g. soil).

The source of the actinobacterialUniversity isolations performed in this study was not unique, in that it was a soil sample, but the location from which it was obtained was unique as it has never before been screened for the presence of actinobacteria. The KRCA soil sample proved to contain many actinobacteria but, as with most soil habitats, the majority of the isolates belonged to the genus Streptomyces with a few non-Streptomyces strains (Amycolatopsis, Kribbella, Micromonospora, Nocardia and Verrucosispora) also being isolated. The novelty of the three Amycolatopsis and single Kribbella strain was confirmed by DDH, however, DDH is still needed to determine the novelty of the other isolates despite the physiological differences between them and their closest phylogenetic relatives suggesting that they represent new species. A few of the Streptomyces isolates also appear to be novel based on the low level of 16S rRNA gene sequence similarity and 216 physiological distinctness to their closest phylogenetic relatives. However, these Streptomyces isolates will require more extensive testing (including DDH) to prove them as novel.

The KRCA is an ideal source for the screening of novel actinobacteria as the site plays host to a wide range of biodiversity, as was detailed in Chapter 2 (section 2.2), with many of the species being endemic to the site and endangered. Thus there is a high probability that a similarly wide biodiversity and endemicity can be found at the microbial level. In order to maximize the potential of the site to provide novel strains, all the sources available should be exploited. This includes the multitude of indigenous plant species found in the area, where isolation can be performed from the surfaces of the leaves, stems and roots, or even from within them. The dams or the nine seasonal wetlands found at the KRCA can also serve as an isolation source, including sediment, aquatic plants or even the water itself. Furthermore, samples from the wetlands can be collected when they are in their dry and wet states, and examined for the presence of filamentous actinobacteria, to determine if the diversity changes with the changing environmental conditions. TheTown multiple insect species could also serve as an isolation source, as could soil samples collected from different sites within the area, perhaps around different indigenous plants. Thus there is a huge range of potential sources within the KRCA from which further actinobacterial isolationsCape can be performed, none of which has ever been screened before. of

The screening of the isolated strains for antibiotic production revealed that many strains showed inhibitory activity against the test strain M. aurum A+, which was used as a substitute for the pathogenic M. tuberculosis (Chung et al., 1995). All the strains showing moderate to very strong activity were identified as Streptomyces, which is unfortunate as the aim was to isolate the “rarer” antibiotic-producing genera,University but not unexpected. Attempts to purify the compounds produced by the most active strains were only partly successful, in that the conditions to separate the compounds by TLC were identified, but the compounds themselves could not be obtained by column chromatography. Only one of the multiple compounds produced by strain SE(6)11 was successfully isolated, however this was only a weakly active molecule. One of the compounds produced by strain SE(6)5 was perhaps the most interesting, as it showed the second strongest inhibition of M. aurum A+ and seemed to be extracted in large amounts from the cell mass (Chapter 2, section 2.4.4). This compound would be a prime candidate for further characterisation, including elemental analysis, mass spectrometry (to determine its molecular weight) and NMR analysis or X-ray crystallography to help determine its structure. These would however require that the compound be purified, 217 something which could not be done in this study. As a result, no information (structure or characteristics) on this or any of the other compounds produced by the Streptomyces isolates could be determined.

Perhaps alternative purification methods could be used to try and isolate the active compounds so as to further examine and identify the molecules. The use of ion-exchange or affinity chromatography (e.g. using HPLC) can be considered, or alternatively, large scale TLC can be applied. In the latter, silica of the desired active spots can be scraped from the plates after separation using the conditions already determined in this study and redissolved in the appropriate solvent for further analysis. The first two methods, however, will require more to be known about the molecules to allow for the conditions under which to perform the purification to be determined (i.e. the conditions needed to allow for the molecule to bind to the column and later be eluted). Furthermore the conditions under which the strains themselves are grown prior to the extraction of the antibiotics can be evaluated and perhaps modified so as to obtain maximal production of the desiredTown compounds. This could even result in the discovery of many more antibiotic compounds that were not produced under the culture conditions that were used in this study. Cape To maximize the potential of the antibiotic discoveryof from the actinobacteria that were isolated in this study, they could be further screened for activity against a host of other bacterial pathogens, including those that are resistant to antibiotics (e.g. MRSA, vancomycin resistant S. aureus or vancomycin resistant enterococci). The extended screening may just show that many of the filamentous actinobacteria which had no or low levels of activity against M. aurum A+ maybe more active against one or multiple other pathogenic strains or that those with activity against M. aurum A+ also inhibited otherUniversity bacteria. This might thus lead to the discovery of novel molecules for the treatment of these bacteria that would otherwise have gone undetected. Furthermore, the additional screening may discover molecules that are isolated more easily than those that have already been examined in this study.

Going hand in hand with the isolation of strains and screening for novel antibiotic compounds, comes the need to identify the strains and determine if they represent novel species. The 16S rRNA gene is the most widely used genetic marker for phylogenetic studies, with DDH often being required to prove novelty at the species level. Despite their wide use in taxonomy, both of these methods are known to have drawbacks and therefore there is a need for the development of novel 218 methods whereby the novelty of a strain can be assessed (Coenye et al., 2005). The sequences of certain housekeeping genes have been used to complement the 16S rRNA gene based phylogeny and have been suggested to be able to predict the level of genome relatedness (Stackebrandt et al., 2002; Coenye et al., 2005), with just one well selected gene potentially being able to replace DDH (Zeigler, 2003). This was shown to work well within the genera Geobacillus (Zeigler, 2005) and Streptococcus (Glazunova et al., 2010) based on the recN gene, while the gyrB gene has been shown to useful in assessing the phylogeny of many actinobacterial genera (Kasai et al., 2000; Shen et al., 2006; Kirby et al., 2010; Takeda et al., 2010).

The potential of these two genes to phylogenetically sort strains and to predict the level of DDH between them was therefore assessed within the genus Amycolatopsis, one of the “rarer” actinobacterial genera that is well known for producing antibiotics. This study was the first to investigate the usefulness of the recN gene in the phylogenetic analysis of an actinobacterial genus. The results showed that despite being useful in determining the Town phylogeny, neither gene could predict the level of DDH between strains. Therefore, Zeigler’s claim about the usefulness of the recN gene to predict the genomic relatedness is not true within the genus Amycolatopsis. Despite this, both genes were useful in that the calculation ofCape the genetic distances between pairs of strains allowed for the determination of whether an unknownof strain was potentially a novel species. The gyrB gene was slightly superior to that of the recN gene, mainly because its sequence is far more easily obtained. However, the recN gene may prove to be better to differentiate between closely related strains due to it being less conserved.

The next logical step in the evaluation of the gene based methods to assess species relationships would be to extend the UniversitygyrB analysis to a wider range of genera, ultimately including all the genera within the family Pseudonocardiaceae. Furthermore, the sequences of additional housekeeping genes (those that have been shown to be useful within other genera e.g. rpoB, dnaA or dnaK), could be determined and their potential to predict the level of DDH assessed along with their ability to determine phylogenetic relationships within the genus and ultimately the family. These sequences could then also be used in combination with the gyrB and recN genes to perform MLSA of the genus Amycolatopsis and get a more accurate representation of the true relatedness between strains. Again, this could also be extended to the entire family. This task (MLSA) will be aided somewhat by the availability of the genome sequences of Saccharomonospora viridis, which was published recently 219

(towards the end of 2009), and that of Saccharopolyspora erythraea (Oliynyk et al., 2007), both members of the family Pseudonocardiaceae.

The analysis of the antibiotic production potential of members of the genus Amycolatopsis could also be further expanded to include the screening for a range of other antibiotic classes. This could be done by using existing primers targeting specific genes in the production of other classes of antibiotics or by designing new primers to screen for specific antibiotic biosynthetic genes. Either way, this may just allow for the identification of cryptic or unexpressed antibiotic pathways within the genomes of the members of the genus and, although unlikely, may lead to the discovery of new molecules from within the already known biodiversity. Alternatively this approach may identify partial biosynthetic pathways within the genomes that contain unique tailoring enzymes that could be cloned and used to modify existing molecules, thereby generating new derivatives of antibiotics. Furthermore, this analysis would build on what has already been done in this study, in that it would expand the knowledge on the antibiotic production potential ofTown the genus and allow for the assessment of whether strains with particular biosynthetic potential form a phylogenetic cluster, like those with glycopeptide (and to a lesser extent ansamycin) biosynthetic genes do. Ultimately this will allow for researchers to more easily identify thoseCape Amycolatopsis isolates that are potential antibiotic producers and worthy of further screening.of

Although multiple non-Streptomyces strains were isolated in this study, with at least four being shown to be novel and others likely to be so, as well as strains showing strong antimycobacterial activity being identified, none of the antibiotic compounds could be purified, characterized and assessed for their potential in the treatment of TB. Similarly the goal of developing a gene based method to predict the levelUniversity of DDH between type strains within the genus Amycolatopsis was not met. However, the calculation of the gyrB- and recN-based genetic distance values was shown to provide a quick way to assess whether strains are likely to represent novel species, allowing strains that are worthy of full characterisation to be identified. Furthermore these genes were shown to have been useful in the phylogenetic analysis of the genus, showing a phylogenetically higher resolving power than the 16S rRNA gene and are particularly useful in assessing the relationships between closely related strains. This study has thus provided new, sequence-based tools in the taxonomy of the genus Amycolatopsis that should save researchers time in characterising environmental Amycolatopsis isolates by allowing them to select the strains that are most likely to represent new species. 220

References:

Chung, G. A. C., Aktar, Z., Jackson, S. & Duncan, K. (1995). High-throughput screen for detecting antimycobacterial agents. Antimicrob Agents Chemother 39, 2235-2238.

Coenye, T., Gevers, D., Van de Peer, Y., Vandamme, P. & Swings, J. (2005). Towards a prokaryotic genomic taxonomy. FEMS Microbiol Rev 29, 147-167.

Glazunova, O. O., Raoult, D. & Roux, V. (2010). recN partial gene sequencing: a new tool for identification and phylogeny within the Streptococcus genus. Int J Syst Evol Microbiol (In Press) DOI: 10.1099/ijs.0.018176-0

Kasai, H., Tamura, T. & Harayama, S. (2000). Intrageneric relationships among Micromonospora species deduced from gyrB-based phylogeny and DNA relatedness. Int J Syst Evol Microbiol 50, 127-134.

Kirby, B. M., Everest, G. J. & Meyers, P. R. (2010). Phylogenetic analysis of the genus Kribbella based on the gyrB gene: proposal of a gyrB-sequence threshold for recognising new type strains of Kribbella. Antonie van Leeuwenhoek 97, 131-142.

Knight, V., Sanglier, J.-J., DiTullio, D., Braccili, S., Bonner, P., Waters, J., Hughes, D. & Zhang, L. (2003). Diversifying microbial natural products for drug discovery. Appl Microbiol Biotechnol 62, 446-458.

Marinelli, F. (2009). Antibiotics and Streptomyces: the future of antibiotic discovery. Microbiol Tod 36, 20-23. Town Oliynyk, M., Samborskyy, M., Lester, J. B., Mironenko, T., Scott, N., Dickens, S., Haydock, S. F. & Leadlay, P. F. (2007). Complete genome sequence of the erythromycin-producing bacterium Saccharopolyspora erythraea NRRL23338. Nat Biotechnol 25, 447-453.

Peláez, F. (2006). The historical delivery of antibiotics from microbial natural products–Can history repeat? Biochem Pharmacol 71, 981-990. Cape

Rodrigues, P., Gomes, M. G. M. & Rebelo, C. (2007). Drug resistance in tuberculosis – a reinfection model. Theor Popul Biol 71, 196-212. of

Shen, F.-T., Lu, H.-L., Lin, J.-L., Huang, W.-S., Arun, A.B. & Young, C.-C. (2006). Phylogenetic analysis of members of the metabolically diverse genus Gordonia based on proteins encoding the gyrB gene. Res Microbiol 157, 367-375.

Singh, S. (2004). Focus on: Tropical diseases, tuberculosis. Curr Anaesth Crit Care 15, 165-171.

Stackebrandt, E., Frederiksen, W., Garrity, G. M., Grimont, P. A. D., Kämpfer, P., Maiden, M. C. J., Nesme, X., Rosselló-Mora, R., Swings, J., Trüper, H. G., Vauterin, L.., Ward, A. C. & Whitman, W. B. (2002). Report of the ad hoc committee for the re-evaluationUniversity of the species definition in bacteriology. Int J Syst Evol Microbiol 52, 1043-1047.

Takeda, K., Kang, Y., Yazawa, K., Gonoi, T. & Mikami, Y. (2010). Phylogenetic studies of genus Nocardia species based on gyrB gene analyses. J Med Microbiol (In Press). doi: 10.1099/jmm.0.011346-0

Watve, M. G., Tickoo, R., Jog, M. M. & Bhole, B. D. (2001). How many antibiotics are produced by the genus Streptomyces? Arch Microbiol 176, 386-390.

WHO – World Health Organization (2007). Tuberculosis Fact Sheet No 14. Accessed July 2009. www.who.int

Zeigler, D. R. (2003). Gene sequences useful for predicting relatedness of whole genomes in bacteria. Int J Syst Evol Microbiol 53, 1893-1900.

Zeigler, D. R. (2005). Application of recN sequence similarity analysis to the identification of species within the bacterial genus Geobacillus. Int J Syst Evol Microbiol 55, 1171-1179.

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T APPENDIX A *100 A. keratiniphila subsp. keratiniphila NRRL B-24117 (EU822898) 67 A. keratiniphila subsp. nogabecina NRRL B-24206 T (EU822899) Unrooted gyrB gene phylogenetic tree 97 A. decaplanina NRRL B-24209 T (EU822891) showing the position of strains S1.3, S3.6 and SE(8)3 amongst the 34 A. japonica NRRL B-24138 T (EU822896) *69 Amycolatopsis type strains for which A. lurida NRRL 2430 T (EU822900) gyrB sequences are available. The tree was constructed using the neighbour- *65 A. alba NRRL 18532 T (EU822885) joining method based on 1292nt of *100 A. azurea NRRL 11412 T (EU822888) common sequence. The percentage *100 bootstrap values of 1000 A. orientalis NRRL 2450 T (EU822906) replications are shown at each A. coloradensis NRRL 3218 T (EU822890) node (only values above 50% *52 T are shown), with asterisks (*) *67 A. regifaucium DSM 45072 (EU822909) indicating the clades that were A. australiensis DSM 44671 T (EU822887) conserved in all three tree drawing algorithms. Accession *56 A. mediterranei NRRL B-3240 T (EU822901) numbers are indicated in 100 A. rifamycinica DSM 46095 T (EU822910) parenthesis after the strain T 74 A. vancoresmycina NRRL B-24208 (EU822918) numbers. The scale bar *100 indicates 5 nucleotide A. balhimycina NRRL B-24207 T (EU822889) substitutions per 100 T nucleotides. S. *98 A. plumensis NRRL B-24324 (EU822908) T avermitilis MA-4680 *80 A. tolypomycina NRRL B-24205Town T (EU822917) was used as an A. saalfeldensis DSM 44993 T (EU822912) outgroup. T *51 A. jejuensis NRRL B-24427 (EU822897) *99 A. sulphurea NRRL 2822 T (EU822914) A. halotolerans Cape NRRL B-24428 T (EU822895) *96 T *100of A. echigonensis JCM 21831 (EU822892) *93 99 A. niigatensis JCM 21832T (EU822905)

T 86 A. rubida NRRL B-24150 (EU822911) A. albidoflavus NRRL B-24149 T (EU822886) Strain SE(8)3 *71 Strain S1.3 *100 Strain S3.6

T University*74 A. minnesotensis NRRL B-24435 (EU822903) *64 A. nigrescens DSM 44992 T (EU822904) A. palatopharyngis DSM 44832 T (EU822907) *96 A. sacchari DSM 44468 T (EU822913) A. taiwanensis DSM 45107 T (EU822915) *98 A. methanolica NRRL B-24139 T (EU822902) *98 T *100 A. eurytherma DSM 44348 (EU822893) *98 A. thermoflava NRRL B-24140 T (EU822916) A. fastidiosa NRRL B-16697 T (EU822894) Streptomyces avermitilis MA-4680 T (NC_003155)

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A PPENDIX B *100 A. keratiniphila subsp. keratiniphila Unrooted gyrB-16S rRNA concatenated gene 61 A. keratiniphila subsp. nogabecina phylogenetic tree showing the position of strains 59 S1.3, S3.6 and SE(8)3 amongst the 34 A. decaplanina 98 Amycolatopsis type strains for which gyrB A. lurida sequences are available. The tree was constructed 69 using the neighbour-joining method based on A. japonica 2642nt of common sequence. The percentage A. alba bootstrap values of 1000 replications are 100 *98 shown at each node (only values above A. azurea 50% are shown), with asterisks (*) A. coloradensis indicating the clades that were conserved in all three tree drawing algorithms. *58 A. orientalis Accession numbers of the 16S rRNA and *66 A. regifaucium gyrB genes are included in Fig 3.4.1 and Appendix A, respectively, along with the A. australiensis strain numbers. The scale bar indicates 2 nucleotide substitutions per 100 69 A. mediterranei 100 nucleotides. S. avermitilis was used as A. rifamycinica an outgroup. *100 92 A. vancoresmycina A. balhimycinaTown *95 A. plumensis

*98 A. tolypomycina

A. saalfeldensis *97 Cape A. jejuensis *96 A. sulphurea of *97 A. halotolerans 99 A. rubida 100 *100 A. echigonensis 72 A. niigatensis

60 A. albidoflavus 62 Strain S1.3

*100 Strain S3.6 University *65 Strain SE(8)3

*90 A. minnesotensis A. nigrescens

97 A. palatopharyngis

A. sacchari 72 *79 A. taiwanensis

*100 A. eurytherma

A. methanolica 100 54 A. thermoflava A. fastidiosa Streptomyces avermitilis

0.02 225

T APPENDIX C *96 Nocardia kruczakiae ATCC BAA-948 (DQ659909) *58 Nocardia veterana DSM 44445T (DQ659918) Nocardia cerradoensis Y9T (AF060790) 59 T Nocardia africana DSM 44491 (AY089701) 65 Unrooted 16S rRNA gene phylogenetic tree T Nocardia aobensis IFM 0372 (AB126876) showing the position of strains C2 and *63 Nocardia elegans IMMIB N-402T (AJ854058) SE(7)1 within the genus Nocardia. The tree Nocardia vaccinii ATCC 11092T (DQ659917) was constructed using the neighbour-joining * Nocardia vermiculata IFM 0391T (AB126873) Nocardia nova ATCC 33726T (DQ659911) method based on 1277nt of common Nocardia jiangxiensis 43401T (AY639902) sequence. The percentage bootstrap values *85 Nocardia miyunensis JCM 12860T (AY639901) of 1000 replications are shown at each node Nocardia acidivorans GW4-1778T (AM402972) Nocardia pseudobrasiliensis DSM 44290T (AF430042) (only values above 50% are shown), with Nocardia crassostreae JCM 10500T (AF430049) T asterisks (*) indicating the clades that were *99 Nocardia yamanashiensis IFM 0265 (AB092561) *58 T conserved in all three tree drawing Nocardia inohanensis DSM 44667 (DQ659908) Nocardia niigatensis DSM 44670T (DQ659910) algorithms. Accession numbers are indicated T *64 Nocardia concava IFM 0354 (AB126880) in parentheses after the strain numbers. The Nocardia seriolae JCM 3360T (DQ659915) scale bar indicates 1 nucleotide substitution Nocardia otitidiscaviarum ATCC 14629T (DQ659912) 73 Nocardia uniformis JCM 3224T (Z46752) per 100 nucleotides. S. avermitilis NCIMB Nocardia caishijiensis F829T (AF459443) T Nocardia vinacea JCM 10988T (DQ659919) 12804 was used as an outgroup. * T 63 Nocardia anaemiae IFM 0323 (AB162801) 72 Nocardia pseudovaccinii DSM 43406T (AF430046) T *99 Nocardia lijiangensis YIM 33378 (AY779043) 60 Nocardia polyresistens YIM 33361T (AY626158) Nocardia xishanensis JCM 12160T (AY333115) Nocardia exalbida IFM 0803T (AB187522) *99 Nocardia gamkensis CZH20T (DQ235272) Nocardia mexicana CIP 108295T (AY555577) T Town Nocardia alba YIM 30243 (AY222321) Nocardia ninae OFN 02.72T (DQ235687) Nocardia jejuensis N3-2T (AY964666) 73 T *99 Nocardia coubleae OFN N11 (DQ235688) * Nocardia ignorata IMMIB R-1434T (AJ303008)

Strain SE(7)1 99 * Nocardia fluminea DSM 44489T (AF430053) 98 Nocardia salmonicida DSM 40472T (AF430050) Cape T *54 Nocardia cummidelens DSM 44490 (AF430052) *99 Nocardia soli DSM 44488T (AF430051) T 80 Nocardia asteroides ATCC 19247 (DQ659898) Nocardiaof neocaledoniensis DSM 44717T (AY282603) Nocardia thailandica IFM 10145T (AB126874) Nocardia abscessus ATCC BAA-279T (DQ659895) T 52 Nocardia altamirensis DSM 44997 (EU006090) T 69 Nocardia brasiliensis ATCC 19296 (DQ659902) Nocardia iowensis NRRL 5646T (DQ925490) 71 Nocardia tenerifensis DSM 44704T (AJ556157) Nocardia takedensis DSM 44801T (AB158277) T *65 Nocardia transvalensis DSM43405 (X80609) *90 Nocardia wallacei ATCC 49873T (EU099357) Nocardia blacklockiae ATCC 700035T (EU099360) Nocardia harenae WS-26T (DQ282122) T *63 Nocardia araoensis IFM 0575 (AB108779) 73 Nocardia arthritidis DSM 44731T (DQ659896) University T 76 Nocardia beijingensis JCM 10666 (DQ659901) Nocardia amamiensis TT 00-78T (AB275164) *91 Nocardia pneumoniae IFM 0784T (AB108780) 58 Nocardia puris DSM 44599T (AB097455) Nocardia asiatica DSM 44668T (DQ659897) Nocardia farcinica ATCC 3318T (DQ659906) T 56 Nocardia higoensis IFM 10084 (AB108778) Nocardia shimofusensis IFM 10311T (AB108775) Nocardia cyriacigeorgica DSM 44484T (DQ659904) Nocardia brevicatena ATCC 15333T (DQ659903) *99 Nocardia paucivorans DSM 44386T (AF430041) Nocardia speluncae N2-11T (AM422449) T *99 Nocardia sienata IFM 10088 (AB121770) Nocardia testacea JCM 12235T (AB192415) T 71 Nocardia carnea ATCC 6847 (X80602) Nocardia flavorosea JCM 3332T (Z46754) Strain C2 *95 ‘Nocardia rhamnosiphila’ 202GMOT (EF418604) Nocardia pigrifrangens JCM 11884T (AF219974) Streptomyces avermitilis NCIMB 12804T (AF145223) 0.01 226

T APPENDIX D *73 Nocardia elegans IFM 10589 (AB450785) *98 Nocardia nova IFO 15556T (AB075571) T *99 Nocardia africana IFM 10147 (AB447399) Unrooted gyrB gene phylogenetic tree Nocardia cerradoensis IFM 10366T (AB450777) 100 T showing the position of strains C2 and *98 Nocardia aobensis DSM 44805 (EU484386) *100 T SE(7)1 within the genus Nocardia. The *74 Nocardia kruczakiae DSM 44877 (FJ765063) tree was constructed using the Nocardia veterana IFM 10086T (AB450816) Nocardia vermiculata IFM 0391T (AB450815) neighbour-joining method based on T *100 Nocardia miyunensis IFM 10632 (AB450794) 1147nt of common sequence. The T Nocardia vaccinii IFM 10284 (AB450814) percentage bootstrap values of 1000 Nocardia pseudobrasiliensis IFM 0624T (AB450802) replications are shown at each node 45 Nocardia transvalensis IFM 0333T (AB450812) T (only values above 50% are shown), *86 Nocardia otitidiscaviarum IFO 14405 (AB075570) with asterisks (*) indicating the clades Nocardia uniformis IFO 13702T (AB075560) Nocardia crassostreae IFM 10173T (AB450779) that were conserved in all three tree 67 Nocardia jejuensis NRRL B-24430T drawing algorithms. Accession numbers T *100 Nocardia yamanashiensis IFM 0265 (AB450819) 53 T are indicated in parentheses after the Nocardia inohanensis IFM 0092 (AB450791) strain numbers. The scale bar indicates 5 66 Nocardia niigatensis IFM 0833T (AB450796) T nucleotide substitutions per 100 *92 Nocardia concava IFM 0354 (AB450778) nucleotides. S. avermitilis MA-4680T *100 Nocardia seriolae IFM 0286T (AB450805) was used as an outgroup. Nocardia cyriacigeorgica IFM 10235T (AB450784) Nocardia xishanensis IFM 10549T (AB450818)

T *100 Nocardia brevicatena IFO 12119 (AB075567) Nocardia paucivorans IFM 10001T (AB450799) Nocardia pigrifrangens IFM 10533T (AB450800) *83 *100 Strain C2 T Town *100 ‘Nocardia rhamnosiphila’ 202GMO 100 Nocardia sienata IFM 10088T (AB450807) *94 Nocardia testacea IFM 0937T (AB450810) 97 T Nocardia jinanensis DSM 45048 Nocardia flavorosea IFM 0851T (AB450787) 50 T *100 Nocardia carnea IFO 14403 (AB075569) *85 Nocardia speluncae DSM 45078T CapeT *90 Nocardia brasiliensis IFO 14402 (AB014168) Nocardia tenerifensis DSM 44704T (FJ765062) Nocardiaof pseudovaccinii IFM 10376T (AB450803) Nocardia anaemiae IFM 0323T (AB447400) *100 Nocardia vinacea IFM 10175T (AB450817)

T *100 Nocardia araoensis IFM 0575 (AB450768) Nocardia beijingensis IFM 10174T (AB450772)

T *95 Nocardia abscessus IFM 10029 (AB447398) *67 T *98 Nocardia asiatica IFM 0245 (AB450770) Nocardia jiangxiensis IFM 10633T (AB450792)

T 100 Nocardia amamiensis DSM 45066 (FJ765061) 88 Nocardia pneumoniae IFM 0784T (AB450801) Nocardia arthritidis IFM 10035T (AB450769)

T *100 Nocardia exalbida IFM 0803 (AB447397) University *99 Nocardia gamkensis CZH20T T * 53 Nocardia farcinica IFO 15532 (AB014169) Nocardia puris IFM 10564T (AB450804) 88 Nocardia higoensis IFM 10084T (AB450789) *100 Nocardia shimofusensis IFM 10331T (AB450806)

T *98 Nocardia asteroides IFM 0319 (AB450771) 90 Nocardia neocaledoniensis IFM 10560T (AB450795) Nocardia thailandica IFM 10145T (AB450811)

T *99 Nocardia caishijiensis IFM 10344 (AB450775) 93 Nocardia ignorata IFM 10475T (AB450790)

T *77 Nocardia fluminea IFM 10138 (AB450788) Nocardia alba IFM 10588T (AB453918) *100 Strain SE(7)1 *86 Nocardia salmonicida IFO 13393T (AB075568) *88 T *90 Nocardia cummidelens IFM 10176 (AB450783) *99 Nocardia soli IFM 10177T (AB450808) Nocardia takedensis IFM 10572T (AB450809) Streptomyces avermitilis MA-4680T (NC_003155)

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APPENDIX E A. decaplanina NRRL B-24209T (EU822891)

T Unrooted gyrB gene phylogenetic tree 59 A. keratiniphila subsp. keratiniphila NRRL B-24117 (EU822898) for 34 validly published and four A. keratiniphila subsp. nogabecina NRRL B-24206T (EU822899) unpublished members of the genus A. lurida NRRL 2430T (EU822900) Amycolatopsis. The tree was constructed using the maximum parsimony method ‘ A. umgeniensis’ UM16T A based on the third nucleotide position of A. alba NRRL 18532T (EU822885) each codon of the sequence (1290nt). 70 The percentage bootstrap values of 1000 76 A. azurea NRRL 11412T (EU822888) replications are shown at each node 65 A. coloradensis NRRL 3218T (EU822890) (only values above 50% are shown). T Accession numbers are indicated in A. regifaucium DSM 45072 (EU822909) parenthesis after the strain numbers. The A. japonica NRRL B-24138T (EU822896) scale bar indicates 10 nucleotide T substitutions. S. avermitilis MA-4680T A. orientalis NRRL 2450 (EU822906) was used as an outgroup. Groups A-E A. mediterranei NRRL B-3240T (EU822901) indicate the conserved clusters of strains. A. rifamycinica DSM 46095T (EU822910) A. australiensis DSM 44671T (EU822887) A. vancoresmycina NRRL B-24208T (EU822918) C A. balhimycina NRRLTown B-24207T (EU822889) T 58 A. plumensis NRRL B-24324 (EU822908) 88 A. tolypomycina NRRL B-24205T (EU822917) A. sulphurea NRRL 2822T (EU822914) A. jejuensis NRRLCape B-24427T (EU822897) A. halotolerans NRRL B-24428T (EU822895) A. rubida NRRL B-24150T (EU822911) 95 56 of 96 A. echigonensis JCM 21831T (EU822892) T 55 A. niigatensis JCM 21832 (EU822905) B ‘A. hippodromi’ S3.6T A. albidoflavus NRRL B-24149T (EU822886) ‘A. cirsi’ S1.3T ‘A. equina’ SE(8)3T University A. saalfeldensis DSM 44993T (EU822912) A. minnesotensis NRRL B-24435T (EU822903) 71 A. nigrescens DSM 44992T (EU822904) D A. sacchari DSM 44468T (EU822913) A. taiwanensis DSM 45107T (EU822915) 71 A. methanolica NRRL B-24139T (EU822902) 56 T E 99 A. eurytherma DSM 44348 (EU822893) 72 A. thermoflava NRRL B-24140T (EU822916) A. fastidiosa NRRL B-16697T (EU822894) A. palatopharyngis DSM 44832T (EU822907) Streptomyces avermitilis MA-4680T (NC_003155)

10

228

APPENDIX F A. keratiniphila subsp. keratiniphila NRRL B-24117T (EU822898)

T Unrooted gyrB gene phylogenetic tree A. keratiniphila subsp. nogabecina NRRL B-24206 (EU822899) 71 for 34 validly published and four A. lurida NRRL 2430T (EU822900) unpublished members of the genus A. decaplanina NRRL B-24209T (EU822891) Amycolatopsis. The tree was constructed using the minimum evolution method A. japonica NRRL B-24138T (EU822896) based on the third nucleotide position of ‘A. umgeniensis’ UM16T each codon of the sequence (1290nt). A T The percentage bootstrap values of 1000 79 73 A. alba NRRL 18532 (EU822885) replications are shown at each node 88 A. azurea NRRL 11412T (EU822888) (only values above 50% are shown). T Accession numbers are indicated in A. coloradensis NRRL 3218 (EU822890) parenthesis after the strain numbers. The A. orientalis NRRL 2450T (EU822906) scale bar indicates 2 nucleotide T substitutions per 100 nucleotides. S. A. regifaucium DSM 45072 (EU822909) T avermitilis MA-4680 was used as an 99 A. plumensis NRRL B-24324T (EU822908) outgroup. Groups A-E indicate the 73 A. tolypomycina NRRL B-24205T (EU822917) conserved clusters of strains. A. balhimycina NRRL B-24207T (EU822889)

T 99 A. australiensis DSM 44671 (EU822887) C A. vancoresmycina NRRL B-24208TownT (EU822918) T 60 A. mediterranei NRRL B-3240 (EU822901) 55 A. rifamycinica DSM 46095T (EU822910) A. saalfeldensis DSM 44993T (EU822912) A. sulphurea NRRL 2822T (EU822914) 51 Cape A. jejuensis NRRL B-24427T (EU822897) 98 A.of echigonensis JCM 21831T (EU822892) 67 A. niigatensis JCM 21832T (EU822905) 67 A. halotolerans NRRL B-24428T (EU822895) 53 A. rubida NRRL B-24150T (EU822911) A. albidoflavus NRRL B-24149T (EU822886) B ‘A. cirsi’ S1.3T 65 ‘A. hippodromi’ S3.6T 69 University ‘A. equina’ SE(8)3T A. minnesotensis NRRL B-24435T (EU822903) 92 D A. nigrescens DSM 44992T (EU822904)

63 A. sacchari DSM 44468T (EU822913) A. taiwanensis DSM 45107T (EU822915) 90 A. methanolica NRRL B-24139T (EU822902) T E 99 A. eurytherma DSM 44348 (EU822893) 88 A. thermoflava NRRL B-24140T (EU822916) A. fastidiosa NRRL B-16697T (EU822894) A. palatopharyngis DSM 44832T (EU822907) Streptomyces avermitilis MA-4680T (NC_003155)

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APPENDIX G 55 A. keratiniphila subsp. keratiniphila NRRL B-24117T (EU822898) T Unrooted gyrB gene phylogenetic tree A. keratiniphila subsp. nogabecina NRRL B-24206 (EU822899) for 34 validly published and four 71 A. decaplanina NRRL B-24209T (EU822891) unpublished members of the genus A. lurida NRRL 2430T (EU822900) Amycolatopsis. The tree was constructed using the neighbor-joining method based ‘A. umgeniensis’ UM16T on the third nucleotide position of each A. alba NRRL 18532T (EU822885) codon of the sequence (1290nt). The 75 A percentage bootstrap values of 1000 82 A. azurea NRRL 11412T (EU822888) replications are shown at each node A. japonica NRRL B-24138T (EU822896) (only values above 50% are shown). 82 T Accession numbers are indicated in A. orientalis NRRL 2450 (EU822906) parenthesis after the strain numbers. The A. coloradensis NRRL 3218T (EU822890) scale bar indicates 2 nucleotide 50 T substitutions per 100 nucleotides. S. A. regifaucium DSM 45072 (EU822909) avermitilis MA-4680T was used as an A. australiensis DSM 44671T (EU822887) outgroup. Groups A-E indicate the A. rifamycinica DSM 46095T (EU822910) conserved clusters of strains. C1 A. mediterranei NRRL B-3240T (EU822901) 99 A. vancoresmycina NRRL B-24208T (EU822918) 99 A. plumensis NRRL B-24324T Town(EU822908) 71 A. tolypomycina NRRL B-24205T (EU822917) A. balhimycina NRRL B-24207T (EU822889) C2 A. saalfeldensis DSM 44993T (EU822912) A. sulphureaCape NRRL 2822T (EU822914) A. jejuensis NRRL B-24427T (EU822897) 55 A. halotolerans NRRL B-24428T (EU822895) 68 of 54 T 97 A. echigonensis JCM 21831 (EU822892) 61 A. niigatensis JCM 21832T (EU822905) A. rubida NRRL B-24150T (EU822911) 56 B A. albidoflavus NRRL B-24149T (EU822886) ‘A. equina’ SE(8)3T 55 ‘A. cirsi’ S1.3T 70 University ‘A. hippodromi’ S3.6T 88 A. minnesotensis NRRL B-24435T (EU822903) A. nigrescens DSM 44992T (EU822904) D

T 51 A. sacchari DSM 44468 (EU822913) A. taiwanensis DSM 45107T (EU822915) 93 A. methanolica NRRL B-24139T (EU822902) 50 T E 99 A. eurytherma DSM 44348 (EU822893) 90 A. thermoflava NRRL B-24140T (EU822916) A. fastidiosa NRRL B-16697T (EU822894) A. palatopharyngis DSM 44832T (EU822907) Streptomyces avermitilis MA-4680T (NC_003155)

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APPENDIX H

Unrooted recN gene phylogenetic tree for 31 T validly published and four unpublished 52 A. albidoflavus NRRL B-24149 members of the genus Amycolatopsis. The A. halotolerans NRRL B-24428T tree was constructed using the neighbor- T joining method based on the third nucleotide A. echigonensis JCM 21831 position of each codon of the sequence *100 A. niigatensis JCM 21832T (1230nt). The percentage bootstrap values of ‘A. equina’ SE(8)3T B 1000 replications are shown at each node 100 T (only values above 50% are shown). ‘A. circi’ S1.3 *100 The scale bar indicates 5 ‘A. hippodromi’ S3.6T nucleotide substitutions per 100 A. rubida NRRL B-24150T nucleotides. S. avermitilis 72 MA-4680T was used as an A. jejuensis NRRL B-24427T outgroup. Groups A-C and 94 A. sulphurea NRRL 2822T Y indicate the conserved clusters of strains. A. saalfeldensis DSM 44993T A. balhimycina NRRL B-24207T A. australiensis DSM 44671T *100 T 51 A. mediterranei NRRL B-3240 70 A. rifamycinica DSM 46095TownT C *92 A. vancoresmycin NRRL B-24208T A. plumensis NRRL B-24324T *86 A. tolypomycina NRRL B-24205T

T *95 Cape A. orientalis NRRL 2450 *68 A. regifaucium DSM 45072T of A. coloradensis NRRL 3218T

T *72 A. alba NRRL 18532 100 A. azurea NRRL 11412T 58 ‘A. umgeniensis’ UM16T A A. decaplanina NRRL B-24209T A. lurida NRRL 2430T A. japonica NRRL B-24138T A. keratinophila subsp. nogabecina NRRL B-24206T University *98 *99 A. keratiniphila subsp. keratiniphila NRRL B-24117T A. thermoflava NRRL B-24140T

T 53 A. minnesotensis NRRL B-24435 A. sacchari DSM 44468T Y A. nigrescens DSM 44992T A. taiwanensis DSM 45107T A. palatopharyngis DSM 44832T Streptomyces avermitilis MA-4680T (BA000030)

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APPENDIX I

T Unrooted gyrB-recN concatenated gene *100 A. keratinophila subsp. nogabecina NRRL B-24206 phylogenetic tree for 31 validly published 77 A. keratiniphila subsp. keratiniphila NRRL B-24117T and four unpublished members of the genus Amycolatopsis. The tree was constructed 93 A. japonica NRRL B-24138T using the neighbor-joining method based on A. decaplanina NRRL B-24209T the third nucleotide position of each codon of T the sequence (2520nt). The percentage A. lurida NRRL 2430 bootstrap values of 1000 replications are A. alba NRRL 18532T A shown at each node (only values above 50% A. azurea NRRL 11412T are shown). The scale bar indicates 5 65 nucleotide substitutions per 1000 A. regifaucium DSM 45072T nucleotides. S. avermitilis MA- T 100 A. coloradensis NRRL 3218 4680T was used as an outgroup. T Groups A-C, X and Y indicate the * ‘A. umgeniensis’ UM16 conserved clusters of strains. A. orientalis NRRL 2450T A. australiensis DSM 44671T

T *53 A. mediterranei NRRL B-3240 100 A. rifamycinica DSM 46095T

T 64 A. balhimycina NRRL B-24207 C 100 A. vancoresmycin NRRLTown B-24208T A. plumensis NRRL B-24324T *51 A. tolypomycina NRRL B-24205T A. saalfeldensis DSM 44993T A. sulphureaCape NRRL 2822T X *82 of A. jejuensis NRRL B-24427T T *98 *100 A. echigonensis JCM 21831 * A. niigatensis JCM 21832T *83 A. rubida NRRL B-24150T A. albidoflavus NRRL B-24149T 99 *71 A. halotolerans NRRL B-24428T B

T 52 ‘A. hippodromi’ S3.6

T 100 ‘A. circi’ S1.3 University 70 ‘A. equina’ SE(8)3T A. palatopharyngis DSM 44832T A. nigrescens DSM 44992T

T A. minnesotensis NRRL B-24435 Y A. thermoflava NRRL B-24140T 87 A. sacchari DSM 44468T A. taiwanensis DSM 45107T Streptomyces avermitilis MA-4680T

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PPENDIX

Amycolatopsis gyrB-based genetic distance matrix

Amycolatopsis genetic distance matrix based on 1290nt of gyrB gene sequence. Genetic distances were calculated in MEGA (version 4) using the Kimura 2-parameter model. J

[ 1] A. alba [14] A. keratiniphila subsp. keratiniphila [27] A. rubida [ 2] A. albidoflavus [15] A. keratiniphila subsp. nogabecina [28] A. saalfeldensis [ 3] A. australiensis [16] A. lurida [29] A. sacchari [ 4] A. azurea [17] A. mediterranei [30] A. sulphurea [ 5] A. balhimycina [18] A. methanolica [31] A. taiwanensis [ 6] A. coloradensis [19] A. minnesotensis [32] A. thermoflava [ 7] A. decaplanina [20] A. nigrescens [33] A. tolypomycina [ 8] A. echigonensis [21] A. niigatensis [34] A. vancoresmycina [ 9] A. eurytherma [22] A. orientalis [35] ‘A. circi’ S1.3T [10] A. fastidiosa [23] A. palatopharyngis [36] ‘A. equina’ SE(8)3T [11] A. halotolerans [24] A. plumensis [37] ‘A. hippodromi’ S3.6T [12] A. japonica [25] A. regifaucium [38] ‘A. umgeniensis’ UM16T [13] A. jejuensis [26] A. rifamycinica [39] Streptomyces avermitilis MA-4680T Town

[ 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 ] [ 1] [ 2] 0.103 [ 3] 0.086 0.099 [ 4] 0.024 0.102 0.087 [ 5] 0.104 0.099 0.062 0.103 [ 6] 0.054 0.101 0.086 0.051 0.103 [ 7] 0.038 0.104 0.085 0.038 0.103 0.051 [ 8] 0.111 0.037 0.110 0.108 0.100 0.107 0.111 Cape [ 9] 0.181 0.178 0.158 0.182 0.174 0.184 0.178 0.181 [10] 0.206 0.214 0.189 0.201 0.207 0.207 0.193 0.213 0.197 [11] 0.101 0.034 0.100 0.100 0.094 0.103 0.099 0.052 0.182 0.212 [12] 0.054 0.103 0.088 0.051 0.098 0.057 0.030 0.110 0.179 0.204 0.102 [13] 0.113 0.062 0.104 0.116 0.092 0.116 0.107 0.071 0.185 0.216 0.066 0.107 of [14] 0.038 0.105 0.086 0.037 0.101 0.047 0.016 0.111 0.172 0.196 0.097 0.031 0.111 [15] 0.041 0.107 0.087 0.041 0.102 0.051 0.019 0.113 0.172 0.196 0.098 0.031 0.114 0.005 [16] 0.046 0.107 0.088 0.041 0.105 0.051 0.025 0.116 0.175 0.197 0.107 0.031 0.115 0.021 0.023 [17] 0.089 0.099 0.046 0.085 0.046 0.085 0.086 0.110 0.170 0.186 0.092 0.081 0.096 0.087 0.088 0.089 [18] 0.186 0.187 0.159 0.185 0.180 0.185 0.181 0.189 0.011 0.195 0.191 0.182 0.192 0.175 0.177 0.178 0.176 [19] 0.194 0.185 0.168 0.191 0.166 0.186 0.182 0.180 0.161 0.208 0.187 0.179 0.188 0.181 0.183 0.180 0.174 0.162 [20] 0.179 0.179 0.159 0.179 0.159 0.173 0.176 0.188 0.160 0.210 0.175 0.173 0.195 0.171 0.170 0.177 0.167 0.161 0.123 [21] 0.114 0.037 0.111 0.111 0.102 0.110 0.114 0.011 0.182 0.216 0.053 0.115 0.072 0.112 0.116 0.116 0.114 0.190 0.179 0.183 [22] 0.051 0.104 0.092 0.045 0.099 0.050 0.046 0.111 0.175 0.202 0.104 0.051 0.110 0.045 0.046 0.049 0.081 0.178 0.183 0.170 0.114 [23] 0.223 0.234 0.214 0.219 0.218 0.220 0.219 0.235 0.198 0.238 0.234 0.212 0.236 0.213 0.216 0.219 0.211 0.197 0.198 0.174 0.233 0.212 [24] 0.098 0.089 0.059 0.097 0.036 0.092 0.095 0.103 0.168 0.199 0.088 0.089 0.092 0.098 0.099 0.096 0.050 0.175 0.162 0.156 0.106 0.091 0.217 [25] 0.053 0.095 0.080 0.047 0.090 0.041 0.048 0.104 0.173 0.189 0.091 0.051 0.107 0.049 0.051 0.046 0.066 0.176 0.187 0.173 0.106 0.042 0.218 0.079 [26] 0.079 0.092 0.044 0.075 0.048 0.078 0.075 0.101 0.164 0.191 0.087 0.075 0.090 0.077 0.078 0.080 0.028 0.171 0.175 0.167 0.105 0.075 0.214 0.044 0.066 [27] 0.117 0.039 0.107 0.112 0.110 0.108 0.112 0.050 0.190 0.217 0.043 0.115 0.073 0.112 0.114 0.120 0.105 0.197 0.176 0.177 0.051 0.114 0.236 0.099 0.106 0.103 [28] 0.118 0.088 0.093 0.119 0.097 0.107 0.108 0.103 0.175 0.215 0.087 0.112 0.094 0.109 0.112 0.113 0.093 0.177 0.182 0.164 0.102 0.106 0.220 0.101 0.103 0.093 0.090 [29] 0.173 0.175 0.165 0.170 0.169 0.173 0.163 0.176 0.123 0.212 0.170 0.164 0.170 0.161 0.163 0.165 0.172 0.122 0.144 0.174 0.178 0.167 0.187 0.164 0.163 0.163 0.184 0.172 [30] 0.133 0.087 0.117 0.132 0.112 0.129 0.122 0.099 0.190 0.236 0.083 0.126 0.084 0.124 0.123 0.129 0.115 0.196 0.194 0.181 0.098 0.128 0.235 0.111 0.118 0.105 0.091 0.103 0.195 [31] 0.221 0.208 0.199 0.223 0.225 0.218 0.213 0.217 0.130 0.235 0.217 0.216 0.214 0.215 0.214 0.218 0.215 0.133 0.182 0.178 0.214 0.221 0.218 0.212 0.217 0.213 0.213 0.207 0.150 0.215 [32] 0.182 0.179 0.159 0.183 0.176 0.185 0.179 0.182 0.002 0.197 0.183 0.180 0.187 0.173 0.173 0.176 0.171 0.013 0.162 0.161 0.183 0.176 0.199 0.170 0.173 0.165 0.191 0.177 0.124 0.192 0.133 [33] 0.089 0.085 0.053 0.090 0.037 0.083 0.087 0.092 0.169 0.195 0.078 0.082 0.082 0.090 0.091 0.090 0.050 0.176 0.161 0.158 0.096 0.087 0.216 0.019 0.074 0.041 0.089 0.095 0.162 0.100 0.210 0.171 [34] 0.079 0.087 0.043 0.080 0.046 0.081 0.081 0.092 0.156 0.177 0.081 0.078University 0.085 0.082 0.081 0.085 0.030 0.163 0.168 0.161 0.095 0.080 0.209 0.042 0.066 0.028 0.099 0.091 0.163 0.105 0.207 0.157 0.037 [35] 0.110 0.023 0.091 0.109 0.094 0.102 0.106 0.040 0.177 0.211 0.036 0.107 0.064 0.107 0.108 0.112 0.099 0.186 0.173 0.173 0.040 0.108 0.231 0.087 0.098 0.092 0.037 0.086 0.178 0.086 0.206 0.178 0.081 0.083 [36] 0.110 0.023 0.091 0.109 0.094 0.102 0.106 0.040 0.177 0.211 0.036 0.107 0.064 0.107 0.108 0.112 0.099 0.186 0.173 0.173 0.040 0.108 0.231 0.087 0.098 0.092 0.037 0.086 0.178 0.086 0.206 0.178 0.081 0.083 0.000 [37] 0.110 0.023 0.091 0.109 0.094 0.102 0.106 0.040 0.177 0.211 0.036 0.107 0.064 0.107 0.108 0.112 0.099 0.186 0.173 0.173 0.040 0.108 0.231 0.087 0.098 0.092 0.037 0.086 0.178 0.086 0.206 0.178 0.081 0.083 0.000 0.000 [38] 0.037 0.096 0.087 0.033 0.103 0.037 0.040 0.103 0.174 0.199 0.094 0.051 0.111 0.037 0.040 0.041 0.086 0.177 0.182 0.162 0.104 0.041 0.209 0.092 0.049 0.074 0.107 0.101 0.165 0.124 0.214 0.175 0.087 0.078 0.101 0.101 0.101 [39] 0.311 0.311 0.300 0.307 0.316 0.306 0.313 0.310 0.331 0.312 0.317 0.300 0.311 0.306 0.305 0.305 0.300 0.335 0.329 0.324 0.313 0.311 0.353 0.309 0.304 0.294 0.311 0.328 0.339 0.331 0.382 0.330 0.300 0.287 0.313 0.313 0.313 0.307

233 A

PPENDIX

Amycolatopsis gyrB-based genetic distance matrix

Amycolatopsis genetic distance matrix based on a 315nt segment of the gyrB gene sequence corresponding to positions 480–795bp of the Streptomyces avermitilis MA- 4680T gyrB sequence (NC_003155). Genetic distances were calculated in MEGA (version 4) using the Kimura 2-parameter model. K

[ 1] A. alba [14] A. keratiniphila subsp. keratiniphila [27] A. rubida [ 2] A. albidoflavus [15] A. keratiniphila subsp. nogabecina [28] A. saalfeldensis [ 3] A. australiensis [16] A. lurida [29] A. sacchari [ 4] A. azurea [17] A. mediterranei [30] A. sulphurea [ 5] A. balhimycina [18] A. methanolica [31] A. taiwanensis [ 6] A. coloradensis [19] A. minnesotensis [32] A. thermoflava [ 7] A. decaplanina [20] A. nigrescens [33] A. tolypomycina [ 8] A. echigonensis [21] A. niigatensis [34] A. vancoresmycina [ 9] A. eurytherma [22] A. orientalis [35] ‘A. circi’ S1.3T [10] A. fastidiosa [23] A. palatopharyngis [36] ‘A. equina’ SE(8)3T [11] A. halotolerans [24] A. plumensis [37] ‘A. hippodromi’ S3.6T [12] A. japonica [25] A. regifaucium [38] ‘A. umgeniensis’ UM16T [13] A. jejuensis [26] A. rifamycinica [39] Streptomyces avermitilis MA-4680T

Town

[ 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 ] [ 1] [ 2] 0.182 [ 3] 0.178 0.157 [ 4] 0.034 0.182 0.186 [ 5] 0.221 0.153 0.122 0.225 [ 6] 0.107 0.178 0.149 0.107 0.199 [ 7] 0.055 0.174 0.145 0.062 0.195 0.087 [ 8] 0.204 0.087 0.170 0.195 0.153 0.199 0.195 Cape [ 9] 0.320 0.316 0.291 0.336 0.337 0.325 0.301 0.311 [10] 0.336 0.368 0.317 0.331 0.357 0.351 0.306 0.352 0.360 [11] 0.199 0.069 0.161 0.204 0.149 0.195 0.178 0.114 0.327 0.362 [12] 0.096 0.161 0.145 0.103 0.162 0.106 0.076 0.191 0.320 0.346 0.166 [13] 0.208 0.110 0.166 0.221 0.118 0.208 0.195 0.125 0.306 0.347 0.122 0.191 of [14] 0.058 0.191 0.149 0.069 0.186 0.084 0.020 0.212 0.296 0.311 0.178 0.076 0.208 [15] 0.058 0.191 0.149 0.069 0.186 0.084 0.020 0.212 0.296 0.311 0.178 0.076 0.208 0.000 [16] 0.066 0.195 0.157 0.073 0.204 0.091 0.037 0.221 0.306 0.321 0.199 0.084 0.221 0.030 0.030 [17] 0.178 0.141 0.087 0.187 0.087 0.157 0.149 0.166 0.316 0.306 0.133 0.122 0.133 0.149 0.149 0.157 [18] 0.331 0.336 0.306 0.346 0.357 0.336 0.310 0.326 0.024 0.349 0.347 0.331 0.326 0.305 0.305 0.315 0.336 [19] 0.459 0.421 0.374 0.465 0.414 0.441 0.430 0.392 0.316 0.321 0.425 0.424 0.391 0.424 0.424 0.429 0.424 0.311 [20] 0.378 0.364 0.316 0.400 0.390 0.362 0.362 0.375 0.295 0.325 0.369 0.351 0.413 0.352 0.352 0.373 0.384 0.291 0.191 [21] 0.213 0.087 0.174 0.204 0.157 0.208 0.204 0.017 0.321 0.363 0.106 0.208 0.126 0.221 0.221 0.230 0.170 0.336 0.392 0.359 [22] 0.066 0.161 0.158 0.073 0.170 0.080 0.048 0.182 0.291 0.326 0.170 0.069 0.191 0.048 0.048 0.062 0.141 0.301 0.423 0.346 0.191 [23] 0.478 0.517 0.436 0.491 0.516 0.504 0.479 0.503 0.357 0.453 0.511 0.441 0.504 0.455 0.455 0.485 0.478 0.357 0.367 0.300 0.503 0.435 [24] 0.212 0.142 0.110 0.226 0.084 0.170 0.186 0.174 0.347 0.352 0.141 0.153 0.149 0.195 0.195 0.195 0.087 0.368 0.402 0.379 0.178 0.174 0.484 [25] 0.110 0.145 0.146 0.118 0.162 0.080 0.084 0.174 0.301 0.310 0.145 0.091 0.182 0.087 0.087 0.091 0.110 0.310 0.442 0.362 0.178 0.069 0.478 0.145 [26] 0.170 0.129 0.080 0.170 0.073 0.153 0.133 0.145 0.301 0.297 0.129 0.118 0.114 0.141 0.141 0.149 0.030 0.321 0.413 0.389 0.149 0.126 0.484 0.073 0.106 [27] 0.217 0.087 0.170 0.204 0.182 0.191 0.199 0.099 0.326 0.362 0.084 0.199 0.137 0.203 0.203 0.226 0.166 0.346 0.370 0.338 0.099 0.195 0.509 0.162 0.178 0.157 [28] 0.186 0.138 0.145 0.199 0.159 0.178 0.170 0.178 0.277 0.415 0.134 0.191 0.174 0.166 0.166 0.170 0.166 0.281 0.391 0.336 0.170 0.137 0.465 0.179 0.146 0.158 0.145 [29] 0.351 0.379 0.357 0.373 0.368 0.357 0.325 0.357 0.182 0.392 0.352 0.331 0.336 0.320 0.320 0.336 0.373 0.174 0.262 0.315 0.362 0.320 0.331 0.379 0.331 0.352 0.384 0.301 [30] 0.267 0.129 0.182 0.276 0.170 0.248 0.235 0.186 0.315 0.407 0.145 0.230 0.141 0.225 0.225 0.248 0.186 0.331 0.401 0.357 0.170 0.230 0.453 0.199 0.213 0.170 0.157 0.149 0.367 [31] 0.429 0.418 0.390 0.429 0.465 0.423 0.400 0.412 0.244 0.407 0.424 0.417 0.412 0.412 0.412 0.406 0.447 0.234 0.301 0.286 0.406 0.429 0.395 0.453 0.406 0.435 0.406 0.367 0.217 0.378 [32] 0.325 0.316 0.296 0.341 0.342 0.331 0.305 0.311 0.003 0.360 0.327 0.325 0.311 0.301 0.301 0.310 0.321 0.027 0.316 0.295 0.321 0.295 0.357 0.353 0.301 0.306 0.326 0.282 0.186 0.320 0.248 [33] 0.208 0.134 0.095 0.221 0.069 0.166 0.182 0.157 0.333 0.342 0.125 0.149 0.126 0.191 0.191 0.199 0.065 0.353 0.386 0.373 0.161 0.170 0.478 0.020 0.142 0.051 0.145 0.171 0.363 0.174 0.436 0.338 [34] 0.170 0.137 0.080 0.178 0.080 0.149 0.149 0.153 0.316 0.301 0.129 0.118University 0.129 0.149 0.149 0.157 0.027 0.336 0.412 0.373 0.158 0.126 0.478 0.080 0.103 0.034 0.170 0.158 0.373 0.199 0.447 0.321 0.065 [35] 0.204 0.051 0.122 0.204 0.141 0.170 0.178 0.091 0.316 0.351 0.069 0.174 0.114 0.195 0.195 0.208 0.137 0.336 0.374 0.316 0.084 0.170 0.491 0.126 0.145 0.129 0.076 0.130 0.368 0.125 0.389 0.316 0.118 0.126 [36] 0.204 0.051 0.122 0.204 0.141 0.170 0.178 0.091 0.316 0.351 0.069 0.174 0.114 0.195 0.195 0.208 0.137 0.336 0.374 0.316 0.084 0.170 0.491 0.126 0.145 0.129 0.076 0.130 0.368 0.125 0.389 0.316 0.118 0.126 0.000 [37] 0.204 0.051 0.122 0.204 0.141 0.170 0.178 0.091 0.316 0.351 0.069 0.174 0.114 0.195 0.195 0.208 0.137 0.336 0.374 0.316 0.084 0.170 0.491 0.126 0.145 0.129 0.076 0.130 0.368 0.125 0.389 0.316 0.118 0.126 0.000 0.000 [38] 0.041 0.170 0.161 0.048 0.217 0.084 0.041 0.191 0.300 0.305 0.162 0.088 0.212 0.041 0.041 0.059 0.161 0.310 0.435 0.336 0.200 0.062 0.459 0.195 0.095 0.153 0.186 0.166 0.341 0.235 0.395 0.305 0.191 0.153 0.174 0.174 0.174 [39] 0.529 0.503 0.465 0.536 0.536 0.503 0.509 0.522 0.579 0.505 0.543 0.471 0.503 0.503 0.503 0.496 0.477 0.585 0.465 0.471 0.529 0.523 0.544 0.510 0.516 0.459 0.490 0.556 0.595 0.563 0.614 0.572 0.492 0.465 0.529 0.529 0.529 0.509

234

APPENDIX L

Plot of the 315nt segment gyrB-based genetic distance values against the DNA relatedness values for pairs of strains in the genus Amycolatopsis (data from Table 4.4.1). The variable section corresponds to position 480-795bp of the Streptomyces avermitilis MA-4680T gyrB sequence (NC_003155). The horizontal dashed line shows the 70% DNA relatedness threshold, with the vertical dashed line showing the 0.02 gyrB genetic distance threshold proposed to determine whether DDH is required to delineate species. All published DDH values of 0 were omitted.

100

80

60

40 Town DNA relatednessDNA (%)

20 Cape 0 0.0 0.1 0.2of 0.3 0.4 gyrB-based genetic distance (315nt)

University

235

APPENDIX M

Table comparing the DNA relatedness values for pairs of Amycolatopsis strain, taken from published DDH data, against those predicted using the recN sequence similarity equation that was determined in Fig 4.4.12 and that of Zeigler (2003).

Zeigler’s recN DNA Predicted Predicted Strain Pairs sequence Relatedness DDH value DDH value similarity (%)* (%)† (%)$ A. alba vs A. azurea 94.67 56 59.5 83 A. alba vs A. coloradensis 92.57 27 25.8 78.3 A. alba vs A. lurida 92.25 24 20.6 77.6 A. alba vs A. mediterranei 80.71 25 -164.9 51.6 A. alba vs A. orientalis 92.01 30 16.8 77 A. alba vs A. sulphurea 78.21 0 -205.1 46 A. alba vs ‘A. umgeniensis’ 92.5 18.4 24.6 78 A. albidoflavus vs A. echigonensis 94.43 46.5 55.7 82.5 A. albidoflavus vs ‘A. hippodromi’ 95.37 22.7 70.8 84.6 A. albidoflavus vs A. niigatensis 94.9 33.6 63.2 83.5 A. azurea vs A. coloradensis 91.56 33 9.5 76 A. azurea vs A. decaplanina 95.13 55.7 66.9 84 A. azurea vs A. lurida 92.5 37 24.6 78 A. azurea vs A. mediterranei 34.18 0 -913 -53 A. azurea vs A. orientalis 91.63 19 Town 10.7 76.2 A. azurea vs A. sulphurea 77.98 0 -208.8 45.5 A. balhimycina vs A. mediterranei 91.92 46 15.3 76.8 A. balhimycina vs A. tolypomycina 90.58 61 -6.2 73.8 A. balhimycina vs A. vancoresmycina 91.95 53 15.8 76.9 ‘A. circi’ vs ‘A. equina’ 99.76 67.9 141.7 94.5 ‘A. circi’ vs ‘A. hippodromi’ 99.68Cape 12.8 140.1 94.3 A. coloradensis vs A. lurida 91.41 37 7.1 75.7 A. coloradensis vs A. mediterranei 79.14 0 -190.1 48.1 A. coloradensis vs A. orientalis of91.29 0 5.2 -11 A. coloradensis vs A. sulphurea 76.48 0 -232.9 42.1 A. coloradensis vs ‘A. umgeniensis’ 91.32 16.2 5.7 75.5 A. decaplanina vs A. lurida 94.77 31.5 61.1 83.2 A. decaplanina vs A. orientalis 92.03 50.5 17.1 77.1 A. echigonensis vs ‘A. hippodromi’ 94.69 23.8 59.9 83.1 A. echigonensis vs A. niigatensis 98.59 60 122.6 91.8 A. echigonensis vs A. rubida 94.95 41.5 64.0 83.6 ‘A. equina’ vs ‘A. hippodromi’ 99.53 9.8 137.7 93.9 A. halotolerans vs ‘A. hippodromi’ 95.67 34.4 75.6 85.3 ‘A. hippodromi’ vs A. niigatensisUniversity 94.92 24.6 63.6 83.6 ‘A. hippodromi’ vs A. rubida 95 25 64.8 83.8 A. japonica vs A. keratiniphila subsp. keratiniphila 95.98 59.5 80.6 86 A. lurida vs A. mediterranei 78.8 6 -195.6 47.3 A. lurida vs A. orientalis 90.78 44.9 -3 74.3 A. lurida vs A. sulphurea 77.3 0 -219.7 43.9 A. mediterranei vs A. orientalis 78.81 0 -195.5 47.3 A. mediterranei vs A. rifamycinica 94.53 40 57.3 82.7 A. mediterranei vs A. sulphurea 81.64 0 -150 53.7 A. mediterranei vs A. tolypomycina 92.68 55 27.5 78.5 A. mediterranei vs A. vancoresmycina 93.59 54 42.2 80.6 A. niigatensis vs A. rubida 95.24 31.8 68.7 84.3 A. orientalis vs A. regifaucium 93.17 42.5 35.4 79.6 A. orientalis vs A. sulphurea 77.11 0 -222.8 43.5 A. tolypomycina vs A. vancoresmycina 92.77 54 29 78.7 * taken from published DDH data referenced in Tables 4.4.1 & 4.4.2.  average of the published values † predicted from the equation in Fig 4.4.12: DDH = (recN similarity – 90.967) ÷ 0.0622 $ predicted from the equation of Zeigler (2003): DDH = –1.30+2.25(recN sequence identity) 236 A

PPENDIX

Amycolatopsis recN-based genetic distance matrix

Amycolatopsis genetic distance matrix based on 1230nt of recN gene sequence. Genetic distances were calculated in MEGA (version 4) using the Kimura 2-parameter model. N

[ 1] A. alba [13] A. keratiniphila subsp. nogabecina [25] A. saalfeldensis [ 2] A. albidoflavus [14] A. lurida [26] A. sacchari [ 3] A. australiensis [15] A. mediterranei [27] A. sulphurea [ 4] A. azurea [16] A. minnesotensis [28] A. taiwanensis [ 5] A. balhimycina [17] A. nigrescens [29] A. thermoflava [ 6] A. coloradensis [18] A. niigatensis [30] A. tolypomycina [ 7] A. decaplanina [19] A. orientalis [31] A. vancoresmycin [ 8] A. echigonensis [20] A. palatopharyngis [32] ‘A. circi’ S1.3T [ 9] A. halotolerans [21] A. plumensis [33] ‘A. equina’ SE(8)3T [10] A. japonica [22] A. regifaucium [34] ‘A. hippodromi’ S3.6T [11] A. jejuensis [23] A. rifamycinica [35] ‘A. umgeniensis’ UM16T [12] A. keratiniphila subsp. keratiniphila [24] A. rubida [36] Streptomyces avermitilis (AP005046)

Town

[ 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 ] [ 1] [ 2] 0.232 [ 3] 0.229 0.194 [ 4] 0.056 0.238 0.227 [ 5] 0.223 0.208 0.103 0.233 Cape [ 6] 0.079 0.244 0.240 0.087 0.247 [ 7] 0.058 0.235 0.238 0.051 0.238 0.081 [ 8] 0.240 0.056 0.201 0.245 0.218 0.249 0.241 [ 9] 0.235 0.034 0.197 0.239 0.215 0.248 0.240 0.053 [10] 0.077 0.238 0.238 0.075 0.236 0.093 0.054 0.244 0.242 of [11] 0.253 0.120 0.205 0.254 0.206 0.262 0.251 0.122 0.118 0.246 [12] 0.082 0.237 0.242 0.073 0.237 0.090 0.058 0.252 0.245 0.041 0.248 [13] 0.079 0.238 0.240 0.073 0.239 0.090 0.058 0.255 0.246 0.036 0.248 0.007 [14] 0.082 0.243 0.242 0.075 0.247 0.092 0.055 0.253 0.249 0.069 0.259 0.068 0.070 [15] 0.220 0.192 0.080 0.233 0.085 0.243 0.242 0.199 0.201 0.242 0.197 0.243 0.244 0.253 [16] 0.295 0.317 0.312 0.302 0.335 0.307 0.305 0.329 0.318 0.302 0.310 0.307 0.304 0.304 0.322 [17] 0.274 0.308 0.284 0.273 0.281 0.277 0.283 0.311 0.308 0.280 0.298 0.281 0.281 0.295 0.266 0.262 [18] 0.235 0.050 0.189 0.244 0.209 0.249 0.241 0.015 0.050 0.236 0.116 0.243 0.244 0.248 0.193 0.319 0.312 [19] 0.085 0.250 0.242 0.091 0.234 0.091 0.084 0.247 0.250 0.091 0.245 0.099 0.098 0.097 0.245 0.298 0.278 0.251 [20] 0.312 0.340 0.344 0.316 0.353 0.314 0.315 0.335 0.338 0.309 0.334 0.319 0.321 0.316 0.346 0.349 0.291 0.333 0.295 [21] 0.215 0.195 0.083 0.227 0.086 0.235 0.226 0.201 0.201 0.220 0.195 0.228 0.229 0.226 0.062 0.297 0.272 0.190 0.238 0.342 [22] 0.086 0.247 0.248 0.076 0.241 0.083 0.072 0.254 0.260 0.085 0.248 0.090 0.091 0.086 0.240 0.302 0.276 0.255 0.073 0.302 0.230 [23] 0.205 0.182 0.087 0.216 0.082 0.229 0.226 0.191 0.188 0.223 0.192 0.225 0.225 0.236 0.054 0.311 0.254 0.185 0.229 0.340 0.058 0.225 [24] 0.231 0.056 0.190 0.237 0.211 0.246 0.240 0.052 0.053 0.237 0.118 0.245 0.246 0.246 0.191 0.316 0.303 0.049 0.246 0.334 0.193 0.250 0.182 [25] 0.211 0.151 0.178 0.220 0.158 0.228 0.219 0.164 0.153 0.217 0.151 0.226 0.225 0.228 0.158 0.325 0.279 0.158 0.225 0.340 0.168 0.235 0.147 0.150 [26] 0.278 0.294 0.304 0.291 0.328 0.294 0.291 0.294 0.297 0.291 0.294 0.296 0.299 0.295 0.322 0.207 0.262 0.289 0.294 0.324 0.306 0.300 0.301 0.288 0.293 [27] 0.258 0.158 0.220 0.260 0.216 0.285 0.262 0.161 0.167 0.255 0.152 0.267 0.266 0.274 0.213 0.317 0.269 0.160 0.271 0.344 0.227 0.281 0.201 0.156 0.166 0.304 [28] 0.320 0.318 0.313 0.322 0.321 0.320 0.314 0.321 0.323 0.303 0.317 0.304 0.306 0.328 0.317 0.255 0.244 0.316 0.316 0.340 0.307 0.308 0.318 0.320 0.315 0.234 0.321 [29] 0.307 0.295 0.302 0.301 0.312 0.311 0.315 0.298 0.294 0.298 0.291 0.306 0.308 0.322 0.299 0.248 0.251 0.292 0.304 0.334 0.307 0.310 0.299 0.289 0.290 0.210 0.303 0.253 [30] 0.206 0.193 0.090 0.217 0.104 0.229 0.220 0.201 0.202 0.221 0.194 0.233 0.231 0.229 0.074 0.301 0.268 0.192 0.235 0.330 0.058 0.224 0.066 0.191 0.165 0.311 0.217 0.307 0.296 [31] 0.222 0.185 0.081 0.231 0.088 0.240 0.236 0.193 0.198 0.233 0.199 0.232University 0.231 0.246 0.069 0.302 0.267 0.180 0.243 0.333 0.062 0.242 0.069 0.192 0.170 0.301 0.220 0.298 0.299 0.076 [32] 0.234 0.047 0.190 0.236 0.210 0.248 0.238 0.050 0.044 0.236 0.117 0.244 0.245 0.243 0.197 0.316 0.308 0.049 0.251 0.343 0.196 0.252 0.188 0.050 0.149 0.280 0.150 0.315 0.287 0.193 0.194 [33] 0.235 0.048 0.191 0.237 0.212 0.249 0.239 0.051 0.045 0.237 0.118 0.245 0.246 0.244 0.198 0.317 0.310 0.050 0.252 0.344 0.197 0.253 0.189 0.051 0.150 0.281 0.151 0.316 0.288 0.194 0.195 0.001 [34] 0.235 0.050 0.191 0.237 0.212 0.249 0.239 0.053 0.047 0.237 0.118 0.245 0.246 0.244 0.198 0.319 0.310 0.051 0.252 0.345 0.197 0.253 0.189 0.053 0.150 0.283 0.151 0.317 0.289 0.194 0.195 0.002 0.003 [35] 0.079 0.257 0.244 0.086 0.247 0.090 0.078 0.260 0.251 0.095 0.259 0.098 0.099 0.091 0.245 0.316 0.290 0.258 0.088 0.314 0.238 0.098 0.226 0.253 0.230 0.303 0.278 0.335 0.328 0.229 0.248 0.258 0.259 0.259 [36] 0.533 0.512 0.521 0.547 0.514 0.571 0.544 0.528 0.522 0.532 0.505 0.523 0.524 0.556 0.510 0.511 0.509 0.519 0.548 0.546 0.517 0.556 0.520 0.518 0.490 0.496 0.513 0.545 0.510 0.511 0.513 0.504 0.506 0.507 0.55

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University