Molecular- and Culture- Based Approaches to Unraveling the Chemical Cross-Talk Between Delisea Pulchra and Ruegeria Strain R11

Molecular- and culture- based approaches to unraveling the chemical cross-talk between Delisea pulchra and Ruegeria strain R11

Rebecca Case

A thesis in fulfilment of the requirements for the degree of Doctor of Philosophy

School of Biotechnology and Biomolecular Sciences Faculty of Science The University of New South Wales Sydney, Australia

June, 2006 Originality Statement

‘I hereby declare that this submission is my own work and to the best of my knowledge it contains no materials previously published or written by another person, or substantial proportions of material which have been accepted for the award of any other degree or diploma at UNSW or any other educational institution, except where due acknowledgement is made in the thesis. Any contribution made to the research by others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis. I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project's design and conception or in style, presentation and linguistic expression is acknowledged.’

Signed ……………………………………………......

1 The [microbial] world is nature's most astonishing phenomenon. Nothing is impossible to it; the most improbable things commonly occur there. One who penetrates deeply into its mysteries is continually breathless with wonder. [They know] that anything can happen, and that the completely impossible often does.

C. J. Briejèr in Rachael Carson's Silent Spring

printed on recycled paper

2 Acknowledgements

Tack så mycket Staffan. It’s difficult to articulate the influence you've had on my life. Your trust in science, belief in me and the freedom you've allowed me has encouraged me to think creatively and have the courage to take risks in the lab. Luckily, it paid off for us, but more importantly you are my mentor. In finishing my PhD I feel the satisfaction of completion but also the loss of leaving my mentor and friend.

Ingela, the day we met has come to be one of those days in life you always remember because nothing was ever the same after that. The conversations we've had, and your hypothesis-driven approach to science, has molded my science. But more than this, you mentored me selflessly and gave me my independence.

Carola, your calmness, constancy and help in moments of crisis will forever be remembered with gratitude.

Thanks also to Peter for your enthusiasm and helpfulness with the Delisea part of my project. The interdisciplinary environment you and Staffan have created in the CMBB has been fantastic for my PhD.

A special thanks to Ford Doolittle and his lab for taking me in. The two major discoveries that changed the focus of my PhD (quorum sensing is laterally transferred and Ruegeria was a potential pathogen) were made during this time.

Thanks to Bill O'Sullivan for proof-reading my thesis. Thanks also to Adam and Evi for all the help with submission.

I want to thank all the other students that have worked on Delisea pulchra with me: Sharon Longford, Dacre England, Adrian Low, and Vickey Chen. Working with people who readily discuss ideas and pull together has made this project bearable at the worst of times and a lot of fun most of the time.

Laurel Crosby for the rpo chats and emails. Knowing there was another PhD student who thought we could use something other than 16S, convinced me to keep going when I thought my project would never take off.

3 Maurice, Flavia and Sacha, you guys have made my PhD. You've been through it all with me, laughter, rowr, tears and a whole lot of science talk. I'm really lucky to have found best friends at work.

Thanks to the 304 girls Kirsty, Niina, Megs, Anne, Maria, Ani, Kath, Barbara, Carola, Shaz, Vickey, Sach and Flavs. And the 304 boys who put up with us, Mike, Adrian, Torsten and Brendan. Also thanks to Adam, Mary, Greg, Evi, Nids, Ana-Maria, David, Johnny and Dhana for the comradery and science chats.

To my family I owe huge thanks. Especial my mum who’s done my ironing and countless other things for me while I'm writing up. Lucy who always makes us laugh and teaches me about determination. My siblings, especially Tina and Paul for their help in realizing certain goals during university. And Reshma, who listened tirelessly about my project and for making our home so friendly during the first few years of my PhD.

Thanks to Ruth and Godfrey for always being interested in my progress. The weekends in the mountains have been some of the most relaxing times over the last few years. Thanks especially for your help in making the decision to do my PhD.

Gina thanks for stimulating the other half of my brain and taking me out for a boogie when I needed it. Thanks especially for coming home when I needed you.

Yan, you have earned my unending gratitude over the last year. Your patience in teaching me bioinformatics and help throughout the writing process with proof-reading and discussing ideas has been invaluable. bisous

4 Abstract

Delisea pulchra is a red macroalga that produces furanones, a class of secondary metabolites that inhibit the growth and colonization of a range of micro- and macro- organisms. In bacteria, furanones specifically inhibit acyl homoserine lactone (AHL)- driven quorum sensing, which is known to regulate a variety of colonization and virulence traits. This thesis aims to unveil multiple aspects of the chemically mediated interactions between an alga and its bacterial flora.

It was demonstrated that the quorum sensing genetic machinery of bacteria is laterally transferred, making traditional 16S rRNA gene based-diversity techniques poorly suited to identify quorum sensing species. Previous studies had shown that AHL-producing bacteria belonging to the roseobacter clade can be readily isolated from D. pulchra. Because of this, it was decided to use a roseobacter epiphytic isolate from this alga, Ruegeria strain R11, to conduct a series of colonization experiments on furanone free and furanone producing D. pulchra. Furanones were shown to inhibit Ruegeria strain R11's colonization and infection of D. pulchra. In addition, it was demonstrated that Ruegeria strain R11 has temperature-regulated virulence, similar to what is seen for the coral pathogen Vibrio shiloi. Rising ocean temperatures may explain bleached D. pulchra specimens recently observed at Bare Island, Australia.

To assess whether quorum sensing is common within the roseobacter clade, cultured isolates from the Roseobacter, Ruegeria and Roseovarius genera were screened for AHL production. Half of the bacteria screened produced the quorum sensing signal molecules, AHLs. These AHLs were identified using an overlay of an AHL reporter strain in conjunction with thin layer chromatography (TLC). The prevalence of quorum sensing within the roseobacter clade, suggests that these species may occupy marine niches where cellular density is high (such as surface associated communities on substratum and marine eukaryotes).

Diversity studies in marine microbial communities require appropriate molecular markers. The 16S rRNA gene is the most commonly used marker for molecular microbial ecology studies. However, it has several limitations and shortcomings, to which attention has been drawn here. The rpoB gene is an alternate ‘housekeeping’ gene used in molecular microbial ecology. Therefore, the phylogenetic properties of these two genes were compared. At most taxonomic levels the 16S rRNA and rpoB

5 genes offer similar phylogenetic resolution. However, the 16S rRNA gene is unable to resolve relationships between strains at the subspecies level. This lack of resolving power is shown here to be a consequence of intragenomic heterogeneity.

6 List of Publications

In preparation

Case RJ, Chen WC, Holmström C, Dahllöf I, Kjelleberg S, (2006), A comparison of the diversity detected using 16S rDNA-DGGE and rpoB-DGGE using the newly designed 'universal' rpoB primers (in preparation)

Submitted

Case RJ, Longford S, Crocetti G, Tujula N, Steinberg P, Kjelleberg S, (2006), Pathogens, bleaching and chemical defense in seaweeds, Science, (submitted).

Case RJ, Labbate M, Kjelleberg S, (2006), Uncoupled LuxR-type proteins: Hierarchical regulation or simply eavesdropping? Environmental Microbiology, (submitted).

Holmström C, Case RJ, Baille H, Thompson L, Kjelleberg S, (2006), Gram-positive bacteria cultured from the surfaces of two red algae and a phylogenetic analysis of the bacteria associated with the red alga, Biofouling, (submitted).

In press

Case RJ, Boucher Y, Dahllöf I, Holmström C, Doolittle WF, Kjelleberg S. (2006) Comparing the 16S rRNA and rpoB genes as molecular markers for microbial ecology, Applied and Environmental Microbiology (submitted).

Published

Boucher Y, Douady CJ, Papke T, Walsh DA, Boudreau MER, Nesbø CL, Case RJ, Doolittle WF, (2003), Lateral transfer and the origins of prokaryotic groups. Annual Review in Genetics 37, 283-328.

7 List of Abbreviations

aa amino acid(s) AHL N-acyl homoserine lactones bp base pair(s) BLAST Basic Local Alignment Search Tool qC degrees Celsius d day(s) DGGE denaturing gradient gel electrophoresis DNA deoxyribonucleic acid dNTP deoxyribonucleotide triphosphate EDTA ethylene diamine tetraacetic acid, trisodium salt FISH fluorescent in situ hybridization g gram GFP green fluorescent protein GTR general time reversible h hour(s) HCl hydrochloric acid LGT lateral gene transfer l litre m milli (10-3) ȝ micro (10-6) M molar min minute(s) ML maximum likelihood MLSA multilocus sequence analysis NCBI National Centre for Biotechnology Information nm nanometres no. number NSS nine salts solution PCR polymerase chain reaction pmol picomole (10-9) RNA ribonucleic acid rpm revolutions per minute rpoB/RpoB the gene/protein encoding the RNA polymerase ȕ subunit

8 rRNA Ribosomal RNA s second(s) sp. species TBR tree bisection reconnection T-RFLP terminal restriction length polymorphism TLC thin layer chromatography UV ultraviolet VNSS V-medium modified from väätänen w/v weight per volume ratio

9 Table of Contents

Originality Statement ...... 1 Acknowledgements ...... 3 Abstract ...... 5 List of Publications ...... 7 List of Abbreviations ...... 8 Table of Contents ...... 10 Table of Figures ...... 14 Table of Tables...... 16

Chapter One 1 General Introduction...... 17 1.1 Acyl homoserine lactone (AHL) driven quorum sensing...... 17 1.2 Quorum sensing regulation of colonization and virulence traits in plant associated bacteria...... 21 1.2.1 Attachment and colonization...... 21 1.2.2 Symbiosis and infection ...... 24 1.3 Evolution fights back – quorum sensing inhibitors and mimics...... 27 1.4 Delisea pulchra ...... 30 1.4.1 Bacterial diseases of red algae...... 35 1.5 Molecular microbial ecology ...... 36 1.5.1 Measuring diversity...... 37 1.5.2 Community dynamics ...... 38 1.5.3 Linking function to diversity...... 39 1.6 Thesis aims and Chapter summary ...... 40 1.7 References ...... 42

Chapter Two 2 Finding quorum sensing bacteria in the environment: evolutionary implications for acyl homoserine lactone (AHL) – driven quorum sensing...... 63 2.1 Introduction...... 63 2.2 Methods ...... 65 2.2.1 Sequence retrieval and alignment ...... 65 2.2.2 Phylogenetic analyses ...... 65 2.3 Results and Discussion ...... 66

10 2.3.1 The role of lateral gene transfer (LGT) in the evolution of the LuxI- and LuxR-type protein families...... 66 2.3.2 Uncoupled LuxR-type proteins: regulation or simply eavesdropping?...... 71 2.3.3 The use of quorum sensing genes to identify quorum sensing species in the environment ...... 77 2.4 References ...... 79

Chapter Three 3 Delisea pulchra chemically defends itself against the novel intracellular pathogen, Ruegeria strain R11 ...... 84 3.1 Introduction...... 84 3.2 Methods ...... 87 3.2.1 Bacterial strains and media ...... 87 3.2.2 Furanone minimal inhibitory concentration (MIC) ...... 87 3.2.3 Flow cell experiments ...... 87 3.2.4 Microscopy of flow cells ...... 88 3.2.5 Delisea pulchra sampling...... 88 3.2.6 Growing Br+/- D. pulchra ...... 88 3.2.7 Colonization experiments ...... 89 3.2.8 Infection experiments...... 90 3.2.9 Microscopy of D. pulchra ...... 90 3.2.10 Re-isolation and identification of Ruegeria strain R11 ...... 90 3.2.10.1 DNA extraction...... 90 3.2.10.2 PCR of the 16S rRNA gene ...... 90 3.2.10.3 Sequencing the 16S rRNA gene...... 91 3.2.10.4 Sequence analysis...... 91 3.2.11 Catalyzed reporter deposition - fluorescence in situ hybridization (CARD-FISH) ...... 91 3.2.12 Microscopy of Br- D. pulchra stained by CARD-FISH...... 92 3.3 Results...... 93 3.4 Discussion ...... 99 3.4.1 Furanone inhibition of biofilm formation in Ruegeria strain R11 ...... 99 3.4.2 Furanone inhibition of virulence in Ruegeria strain R11 ...... 100 3.4.3 Koch's postulates...... 100 3.4.4 The importance of disease and global warming in marine ecology ...... 103 Acknowledgments ...... 103 3.5 References ...... 104

11 Chapter Four 4 Comparing the 16S rRNA and rpoB genes as molecular markers for microbial ecology ...... 111 4.1 Introduction...... 111 4.2 Materials and Methods ...... 114 4.2.1 Sequence retrieval and alignment ...... 114 4.2.2 Recoding of alignment positions displaying intragenomic heterogeneity 114 4.2.3 Mutational saturation analysis...... 114 4.2.4 Phylogenetic analyses ...... 115 4.2.5 Random taxon sampling analysis ...... 115 4.2.6 Determination of evolutionary rates across sites (sliding window analysis) 116 4.3 Results...... 117 4.3.1 rpoB and 16S rRNA gene copy number and intragenomic heterogeneity 117 4.3.2 Localization of intragenomic heterogeneity in the 16S rRNA molecule .. 117 4.3.3 Evolutionary characteristics of the rpoB and 16S rRNA genes...... 117 4.3.4 Comparing rpoB and 16S rRNA gene phylogenies ...... 126 4.4 Discussion ...... 131 4.4.1 Frequency and distribution of intragenomic heterogeneity between 16S rRNA gene copies ...... 131 4.4.2 Comparing the rpoB and 16S rRNA genes as phylogenetic markers..... 132 4.4.3 Establishing rpoB as an alternative gene marker for microbial ecology . 133 4.4.4 Alternative markers in molecular microbial ecology – the way forward .. 135 Acknowledgments ...... 136 4.5 References ...... 137

Chapter Five 5 Quorum sensing and phylogeny of the Roseobacter, Roseovarius and Ruegeria genera: chatterboxes of the oceans ...... 141 5.1 Introduction...... 141 5.2 Materials and methods ...... 144 5.2.1 Strains and media...... 144 5.2.2 DNA extraction...... 145 5.2.3 PCR of the 16S rRNA and rpoB genes...... 145 5.2.4 16S rRNA and rpoB gene sequencing...... 145 5.2.5 Phylogenetic analysis ...... 145

12 5.2.6 AHL streak assay...... 146 5.2.7 Extraction and characterization of AHLs produced by marine strains .... 146 5.3 Results...... 148 5.4 Discussion ...... 154 Acknowledgments ...... 156 5.5 References ...... 157

Chapter Six 6 General Discussion...... 165 6.1 The use of rpoB as a molecular marker in microbial ecology ...... 165 6.2 The novel pathogen Ruegeria strain R11, climate change and chemical defense against colonization and infection by Delisea pulchra...... 167 6.3 References ...... 171

7 Appendices ...... 175 7.1 Appendix 1...... 175 7.2 Appendix 2...... 176

13 Table of Figures

Chapter One Figure 1-1: Schematic diagram of the Vibrio fischeri quorum sensing paradigm, autoinduction (A) and quorum sensing without auto-induction (B)...... 19 Figure 1-2: Model of bacterial colonization and biofilm formation ...... 25 Figure 1-3: Schematic diagram of furanone antagonism of acyl homoserine lactone (AHL)-driven quorum sensing (A), AHL (B) and furanone (C) chemical structures...... 28 Figure 1-4: Description (A) and illustration of Delisea pulchra (B) from Harvey’s History of Australian Seaweeds (65) ...... 31 Figure 1-5: Light micrographs of Delisea pulchra from Dworjanyn et al. (47) ...... 33

Chapter Two Figure 2-1: Best maximum likelihood phylogenetic trees of LuxR transcription regulator (A) and LuxI AHL synthase (B)...... 68 Figure 2-2: Phylogenies of LuxR-type proteins in bacteria that lack complete quorum sensing circuits (bold) and nearest neighbours (A), Rhizobia and Agrobacterium LuxR- type proteins (B) and Pseudomonas and Burkholderia LuxR-type proteins (C)...... 73

Chapter Three Figure 3-1: Biofilm formation by Ruegeria strain R11...... 94 Figure 3-2: Three months old Delisea pulchra grown in artificial seawater without bromine (Br-) at 20°C (A), with bromine (Br+) at 20°C (B), Br- at 25°C (C) and Br+ at 25°C (D)...... 95 Figure 3-3: Intracellular bacteria visualized using CARD-FISH on three months old Delisea pulchra grown in artificial seawater without bromine (Br-)...... 96 Figure 3-4: Bleached Delisea pulchra collected from Bare Island, Sydney, Australia, in the late astral summer, February 2006...... 102

Chapter Four Figure 4-1: Mapping of the 16S rRNA positions for which intragenomic heterogeneity is observed among the 111 bacterial species analyzed...... 119 Figure 4-2: Evolutionary rate and intragenomic heterogeneity at specific sites across the length of bacterial RpoB protein and 16S rRNA gene...... 123 Figure 4-3: Comparison of the best maximum likelihood trees of the 16S rRNA gene and RpoB protein for the domain Bacteria...... 127

14 Figure 4-4: Evaluation of 16S rRNA and rpoB genes as phylogenetic markers at the subspecies level ...... 128

Chapter Five Figure 5-1: 16S rRNA gene phylogeny of the roseobacter clade...... 150 Figure 5-2: RpoB phylogeny of the roseobacter clade...... 151 Figure 5-3: Acylated homoserine lactones (AHLs) profiles on C18 reversed phase thin layer chromatography (TLC) with an overlay of the AHL reporter strain Agrobacterium tumefaciens A136...... 152

Chapter Six Figure 6-1: Effect of different light treatments on furanone concentration in the thallus of Delisea pulchra...... 169

Appendices Figure 7-1: Furanones produced by Delisea pulchra………………………………….175

15 Table of Tables

Chapter One Table 1-1: AHL-driven quorum sensing among plant associated bacteria...... 22

Chapter Two Table 2-1: Number of LuxI and LuxR-type proteins found in species with completed genomes...... 76

Chapter Four Table 4-1: 16S rRNA gene intragenomic heterogeneity among a variety of bacterial taxonomic groups ...... 118 Table 4-2: Characteristics of rpoB datasets and phylogenies at different taxonomic levels ...... 121 Table 4-3: Characteristics of 16S rRNA datasets and phylogenies at different taxonomic levels...... 122

Chapter Five Table 5-1: List of strains used in this study ...... 144 Table 5-2: Nomenclature of unsubstituted, oxo or hydroxy acyl homoserine lactones (AHLs) ...... 147 Table 5-3: Acyl homoserine lactones (AHLs) identified from marine Roseobacter, Roseovarius and Ruegeria strains ...... 153

Appendices

Table 7-1: List of bacterial genomes used to construct the datasets to compare the rpoB and 16S rRNA genes as phylogenic markers in microbial ecology……………176

16 1 General Introduction

Bacteria were first thought of as silent machines, turning over the sulfur, nitrogen and other elemental cycles that make our planet habitable. The discovery that bacteria are not silent (128) and that they generally do not exist as single entities (167), unaware of their environment or each other, presents a level of genetic and physiological sophistication previously considered impossible. However, it is not surprising that bacteria are capable of complex social organization as they have evolved and adapted to the variety of conditions on this planet for over 3.5 billion years, one thousand times longer than humans have inhabited the planet.

One of the first indications that bacteria were capable of social organization was the discovery of bacterial communication (128). Bacteria communicate through chemical signals produced within a population to monitor their own density. Upon reaching a critical 'quorum', the population can alter their transcriptome, to express certain phenotypes that are advantageous to the population, but not when expressed by a single cell. Subsequently, cell differentiation was identified in bacteria, whereby it was appreciated that labor was shared across specialized cells (50). Later, it was revealed that quorum sensing molecules can serve as cues for cell differentiation within populations (48). While communication and cell differentiation are thought to be characteristics unique to 'higher organisms', prokaryotes also drive complex, multicellular dependent processes.

1.1 Acyl homoserine lactone (AHL) driven quorum sensing

Through quorum sensing, bacteria can indirectly determine population density by sensing the concentration of a signal molecule. The capacity to signal is widespread among bacteria, with a variety of signaling systems described for Firmicutes, Actinobacteria and Proteobacteria (42, 46, 132, 136). One of the best-studied signaling system is the quorum sensing mechanism found in Proteobacteria, which uses N-acylhomoserine lactones (AHLs) as signal molecules (55). AHL-driven quorum sensing is characterized by two proteins, the AHL synthase (LuxI protein family) and the response regulator (LuxR protein family). Two alternate AHL synthases have been identified, HdtS in Pseudomonas fluorescens (95) and VanM in Vibrio anguillum (121). However, these appear to be exceptions as few homologues have been found.

17 In AHL-driven quorum sensing, the AHL synthase constitutively produces AHLs which either freely pass through the cell membrane or are actively transported in and out of the cell via efflux proteins, as is the case for long chain AHLs (138). In either scenario, this allows for the intracellular AHL concentration (the AHL concentration within the cytoplasm of an AHL producing bacterium) to approximate the intercellular concentration (the AHL concentration within the local environment around AHL producing bacteria). When a quorum is established, a critical concentration is met at which the AHL binds to the response regulator forming an AHL-LuxR complex, which in turn binds upstream of the promoter of targeted genes. This AHL-LuxR complex will then activate or repress the transcription of targeted genes (74, 188). In a given organism there will be no one population density (AHL concentration) at which all quorum sensing regulated genes will be activated or repressed, rather genes will be differentially regulated at different population densities (70, 164, 190).

The AHL-LuxR complex activates transcription by binding to the lux box upstream of quorum sensing regulated genes. This lux box is a ~ 20 bp DNA sequence which forms a hairpin structure to which the AHL-LuxR complex anchors itself (171). The AHL-LuxR complex then recruits the RNA polymerase to activate transcription. For genes that are transcriptionally repressed by quorum sensing, it appears that the LuxR-type protein itself binds to the lux box. In the presence of AHLs, it forms an AHL-LuxR complex which liberates the LuxR-type protein from the lux box such that the genes are no longer transcribed.

There are two important variations to the AHL-driven quorum sensing model. The first describes the V. fischeri paradigm (128). V. fischeri uses AHL-driven quorum sensing to regulate luminescence (hence the AHL synthase and response regulator are called LuxI and LuxR). LuxI produces a constituent level of AHLs until a threshold concentration is met when the AHL binds LuxR. This AHL-LuxR complex in turn binds to the transcriptional activation site of target genes. One of these target genes is luxI, so that the concentration of LuxI and consequently, the AHL concentration, exponentially increase by a process known as auto-induction (see Fig. 1-1A) whereby the LuxI product (AHLs) induces the transcription of luxI. The secondary induction of AHL uncouples the AHL concentration from the cell density of the organism V. fischeri, as its concentration relative to cell density has dramatically increased.

18 A Regulatory genes Structural genes R I

Colonization Phenotypes R I (e.g., swarming, biofilm formation, antimicrobials, virulence factors)

AHLs

Environment

B Regulatory genes Structural genes I R

I R Colonization Phenotypes (e.g., swarming, biofilm formation, antimicrobials, virulence factors)

AHLs

Environment

Figure 1-1: Schematic diagram of the Vibrio fischeri quorum sensing paradigm, auto-induction (A) and quorum sensing without auto-induction (B). Auto-induction is where the AHL synthase (LuxI-type protein) is quorum sensing regulated. This results in the AHL concentration being uncoupled from the quorum sensor's cellular density when the threshold AHL concentration (at quorum) is established. AHLs bind to the response regulator (LuxR-type proteins) to form an AHL-LuxR complex that acts as a transcriptional activator or repressor. The second AHL-driven quorum sensing model does not involve auto-induction as its AHL synthase is not quorum sensing regulated. In this sense, it is true quorum sensing given that the AHL concentration always relates to the population density

(Fig. 1-1B) and does not exacerbate the population density as is the case for autoinduction. Species that do not undergo auto-induction include P. stewartii and members of the Entrobacteriaceae (157, 187). Bacteria can also employ anti-activators as an additional level of quorum sensing regulation such that auto-induction does not exacerbate the quorum sensing response at high cellular densities (22, 77, 134). The quorum sensing response regulator can also be under cell density dependent expression as is the case for LasR in P. aeruginosa (4), or constituently expressed as is the case for AhlR in P. syringae (151).

The quorum sensing regulatory network is often integrated into much larger control networks, however these are not conserved among all quorum sensing bacteria. For example, the two regulatory networks integrated into the quorum sensing response in plant-associated bacteria are rsm (regulator of secondary metabolites) in Erwinia and Pseudomonas spp. (105, 142), and gac (global activator) in Erwinia, Pseudomonas and Agrobacterium spp. (67, 130). These networks represent independent regulatory networks as they regulate more than the quorum sensing response and are not unique to quorum sensing bacteria (78).

There are three examples of regulatory proteins that provide additional regulation to the quorum sensing response in a quorum sensing specific manner. All three act as anti- activators. In A. tumefaciens, a truncated homologue of TraR (its quorum sensing response regulator), TrlR is found. TrlR contains an AHL binding domain, but not a DNA binding domain (134). In this way TrlR inactivates TraR as it dimerizes to active TraR and binds its cognate AHL, but this complex can not act as a transcriptional regulator as TrlR is missing its DNA binding domain (23). A truncated LuxR-type protein is also found in S. liquifaciens MG1 (M. Labbate, personal communication).

The second example is TraM which is also an anti-activator of quorum sensing in A. tumefaciens (77). Like TrlR, TraM binds to TraR forming an anti-activation complex (149), however it is not itself a homologue of TraR. TraM delays induction of quorum sensing regulated conjugal transfer (145), thereby ensuring that conjugation is not induced at a population density too low for efficient conjugal transfer of the Ti plasmid. Homologues of TraM have also been identified in several species with quorum sensing

20 regulated conjugal transfer, including Sinorhizobium meliloti (112), Rhizobium etli (181), R. leguminosarum bv. viciae (39) and Rhizobium sp. strain NGR234 (66).

The third example is not a quorum sensing regulator; however it acts to effectively reduce the quorum sensing response by degrading AHLs. The lactonase AiiA was first identified in E. carotovora (44) and has since been identified in P. aeruginosa (168), Ralstonia strain XJ12B (101) and A. tumefaciens (22). A tumefaciens contains three lactonases, two of which have been shown to have AHL hydrolase activity (22). At high cell densities, the AHL concentration is also high and the population has the potential to exhaust itself (22). Lactonases lower the AHL concentration relative to the cellular density at high cell densities by degrading AHLs. Lactonases are also found in Gram positive species that lack quorum sensing, however the role of these enzymes in Gram positive species is to interfere with AHL-driven quorum sensing (43, 45, 97, 137, 201). This is discussed in Section 1.3.

1.2 Quorum sensing regulation of colonization and virulence traits in plant associated bacteria

AHL-driven quorum sensing regulates a variety of phenotypes responsible for attachment, biofilm formation, surface motility, luminescence, gene transfer agent, conjugation, type III secretion, and the expression of exo-enzymes, antibiotics, secondary metabolites, virulence and extracellular polysaccharide (EPS) (Table 1-1), (48, 76, 81, 146, 163, 166, 177, 188, 207). All these phenotypes play an important role in colonization or in mediating species-species interactions. It is therefore not surprising that quorum sensing is commonly found in bacteria that interact with a eukaryote host, including symbiotic and pathogenic bacteria. For plant associated bacteria, quorum sensing plays a duplicitous role in both host colonization and in modulating the bacterial-plant interaction. The role of quorum sensing varies, such that quorum sensing mutants in some species are avirulent or unable to form symbiosis (206, 207), while such mutants in other species simply show a reduced interaction (56, 150). For the purpose of this review only plant associated quorum sensing species will be discussed.

1.2.1 Attachment and colonization

Bacterial colonization of surfaces occurs by the process of biofilm formation (Fig. 1-2). Biofilms are surface associated communities that are embedded in a matrix of protein, DNA and EPS (20, 79, 195). They can consist of complex communities including both micro- and macro-organisms but can also be monocultures as can be the case for 21 Table 1-1: AHL-driven quorum sensing among plant associated bacteria

Organism AHL QS regulated phenotype Reference system

Agrobacterium traR/traI Plasmid transfer, plasmid (146) tumefaciens replication A. vitis aviR/aviI Virulence (64, 206) avhR/avhI Virulence Erwinia carotovora carR/carI Pectolytic enzymes, (26, 81) subsp. Carotovora endoglucanases, proteases, hrp secretion, carpapenem Mesorhizobium mrtR/mrtI Nodulation, attachment (207) tianshanense Pantoea stewartii esaR/esaI Attachment, biofilm formation, host (91, 188) subsp. Stewartii colonization, EPS Pseudomonas phzR/phzI Phenazine (199, 205) aureofaciens strain 30- csaR/csaI Exo-proteases, cell surface 84 components P. chlororaphis phzR/phxI Phenazine (28) PCL1391 P. fluorescens strain 2- phzR/phzI Phenazine (82) 79 P. fluorescens F113 hdtS Unknown (95) P. syringae pv. ahlR/ahlI Swimming, swarming, EPS, (150, 151) syringae strain B728a oxidative stress, phylosphere survival Ralstonia solR/solI Unknown (51) solanacearum Rhizobium etli CFN42 traR/traI Plasmid transfer (181) R. etli CNPAF512 cinR/cinI Nitrogen fixation, growth inhibition, (38, 162) symbiosome development raiR/raiI Nitrogen fixation, growth inhibition R. leguminosarum bv. raiR/raiI Unknown (39, 197) viciae traR/traI Plasmid transfer cinR/cinR Growth inhibition Rhizobium sp. strain traR/traI Plasmid transfer, growth inhibition (66) NGR234 Sinorhizobium meliloti sinR/sinI EPS, nodulation (113, 140) Rm 1021 S. meliloti Rm41 sinR/sinI EPS, nodulation (113, 140) traR/traI Plasmid transfer

22 symbiotic and pathogenic interactions (133). Biofilm formation in bacteria involves four distinct stages: attachment, growth including microcolony formation, lateral colonization including swarming and dispersal. Quorum sensing has been implicated in regulating all of these stages in different organisms (91, 187).

Given that quorum sensing regulates transcription in a cell density dependent manner and that cell density is at its lowest during initial colonization, the role of quorum sensing in attachment is surprising. In the nitrogen fixing rhizobia species Mesorhizobium tianshanense, Zheng et al. (207) found that a mrtI mutant achieved only 40% of the attachment of the parent strain on the host Glycyrrhiza uralensis. However, the quorum sensing regulated attachment factor is unknown. This poor attachment was reflected in poor initial nodulation in the mrtI mutant (2.5 nodules compared with 16 per G. uralensis plant) (207).

The EPS matrix that encases the bacterial cell is thought to be important for bacterial attachment by acting as a glue at the interface between the cell and the substratum. EPS is quorum sensing regulated in many species (91, 111, 140, 150, 188), and therefore the role of quorum sensing in attachment by Pantoea stewartii has been investigated (91). Quorum sensing was found to negatively regulate EPS synthases, with AHLs liberating the EsaR from the esa box in this organism. Surprisingly, the hypermucoid esaR mutant and esaR/I double mutant showed effectively no attachment, while the parent strain demonstrated low levels of attachment (91). The esaI mutant, which is not mucoid, showed a several fold higher attachment (91), indicating that EPS and quorum sensing have an inhibitory effect on attachment. EPS was also identified as important for developing complex 3D-structures in the P. stewartii biofilms, with the parent strain developing column and channel structures in the mature biofilm, while the esaI mutant had few of these structures and the esaR/I double mutant did not develop structures, but rather formed a flat biofilm (91).

Surface motility also plays an important role in colonization as it allows a bacterium to move away from adverse conditions and move toward favorable conditions for colonization. Swarming is a coordinated behavior within a population where cells differentiate into hyperflagellated and elongated cells capable of rapid movement across a surface, while other feeder cells differentiate into short rods that provide the metabolic needs for the swarmer cells (and hitch a ride) (50). This type of motility is usually quorum sensing regulated as it requires a quorum of bacteria in order to coordinate behavior and undergo differentiation. Swarming motility in S. meliloti and P.

23 syringae is negatively regulated by quorum sensing (56, 150), indicating that these species are motile on surfaces at low cell densities and not at high cell densities. It suggests that they use motility for exploration at low cell densities, and once a suitable colonization site is arrived at the cells will remain localized possibly due to localized nutrients being made available from the action of exo-enzymes. Further colonization would provide opportunities for competing species as available nutrients will be spread over a larger area and therefore more available to invasion. This appears to be the scenario in P. syringae where the parent strain produces a small wound site with macerated tissue and an esaI/R double mutant had a larger wound site, however no tissue maceration occurs in the bean pod (150).

1.2.2 Symbiosis and infection

Quorum sensing was first described for the regulation of phenotypes involved in the V. fischeri-Squid symbiosis model (186). However it has since been implicated in other symbiotic relationships. The plant symbiotic bacteria include the nitrogen fixing Rhizobia, and quorum sensing has been reported in the genera Rhizobium, Sinorhizobium and Mesorhizobium. Rhizobia form root nodules on leguminous plants which are differentiated root structures in which Rhizobia live, reducing nitrogen to a form that is utilizable by the plant. Quorum sensing regulates a variety of phenotypes in these bacteria including EPS production (111, 150, 188), plasmid transfer (39, 66, 112, 146, 181, 197) and nodulation (38, 113, 207).

Nodulation may be indirectly controlled by quorum sensing in M. tianshanense (207). An mrtI mutant initially formed few nodules on G. uralensis and no nodules persisted two months post inoculation, compared with the maximal nodulation level sustained by the wild type M. tianshanense throughout this period. The quorum sensing regulated genes responsible for this attenuation in symbiosis are not known, however they appear to be involved in attachment (207). Similarly, while a cinI mutant in R. etli CNPAF512 displayed a 60-70% reduction in nitrogen fixation efficiency (38), quorum sensing has not been shown to regulate nitrogen fixation.

Conjugation is one of the most commonly observed quorum sensing regulated traits, found in both symbiotic and pathogenic bacteria (Table 1-1). Importantly, these plasmids contain the genetic machinery that drives the symbiotic or pathogenic nature of the relationship, such as Type IV secretion and oncogenic DNA on A. tumefaciens' Ti plasmid (60, 200) and sym and nod genes contained on quorum sensing regulated plasmids in many Rhizobia species (39). These plasmids are usually only maintained in

24 A

Figure 1-2: Model of bacterial colonization and biofilm formation. (A) Free-living bacteria initially attach to a surface. For bacterial attachment to a plant surface, attachment is often mediated by pili and fimbriae binding to specific surface receptors. (B) Bacteria grow and proliferate on the surface forming a thin monolayer biofilm. (C) Continued growth results in microcolony formation. Microcolonies are enclosed in a matrix that consists of extracellular polysaccharide (EPS), protein and DNA. Bacteria in biofilms attached to plant surfaces secrete a number of extracellular factors that mediate the interaction. These include exo-enzymes that make nutrients available through tissue maceration and virulence factors facilitating infection. Further colonization can be achieved through swarming and dispersal. Figure adapted from (110). a small fraction of the population and involve complex regulatory networks such as several quorum sensing systems in R. leguminosarum bv. viciae (39) or the additional plant opine regulation in A. tumefaciens (134).

In Rhizobia species, bacteria form an infection thread into the root in a similar fashion to plant pathogens in the infection process. Once in the root intercellular spaces Rhizobia induce cellular differentiation within the root to form the symbiosome in which the symbiotic Rhizobia now reside. S. meliloti quorum sensing mutants are unable to form infection threads (140). This is because quorum sensing mutants are deficient in EPS production, which is essential for the formation of the infection thread. Specificity in the legume-Rhizobia relationship results from the plant recognizing the EPS produced by the symbiont, and through a cascade of signaling, the symbiont is able to form an infection thread. Quorum sensing regulation of EPS is also important for the localization and biofilm structure by P. stewartii within the plant (91). Quorum sensing mutants in P. stewartii do not show the same localization at regular intervals along the xylem, as does the parent strain (91). Also, mucoid quorum sensing mutants form a denser, less structured biofilm on inanimate surfaces (91).

A range of antimicrobials including antifungal (e.g. phenazine) and antibacterial (e.g. carpapenem) agents are quorum sensing regulated in plant associated bacteria. Antimicrobials are used by both bio-control bacterial strains such as P. fluorescens (95) and P. chlororaphis (28) and pathogens such as E. carotovora (26). These species are likely to produce antimicrobials for the same reason, which is to protect themselves against invading species. The difference is that pathogenic bacteria protect the food source made available by virulence factors such as exo-enzymes, while bio-control strains are not pathogenic to the host, thereby conferring resistance to potentially pathogenic invading species.

The benefit of having virulence traits such as exo-enzyme production under quorum sensing regulation is that these phenotypes are not produced at a cellular density that would be ineffectual against the host. Exo-enzymes such as pectinases and proteases cause tissue maceration in plants, making nutrients available. If only a small part of the population were to produce these enzymes, or if they were not produced in a coordinated manner, there is the potential for 'cheaters' to evolve within the population. In addition, the requirement for quorum sensing auto-induction prevents detection (quorum sensing molecules will be at a low concentration until a quorum is established), by hosts (117).

26 The only reported role of quorum sensing on bacteria-marine plant interactions applies to green algae (80, 173, 194). Enteromorpha sp. spores preferentially settle on surfaces coated with AHLs (80). The signaling molecules serve as chemotactants, suggesting a symbiosis between Enteromorpha sp. and a quorum sensing species in the mixed species biofilms on which the spores settle. Rao (152) showed that the quorum sensing strain Roseobacter strain 2.10 (see Chapter 5) isolated from Ulva australis, could produce the same effect on U. australis spores. Roseobacter strain 2.10 has been shown to out-compete all other U. australis bacterial epiphytes (153) and does not appear to have a pathogenic effect on the algae (152). It suggests that there may be a symbiotic relationship between U. australis and Roseobacter strain 2.10.

1.3 Evolution fights back – quorum sensing inhibitors and mimics

Quorum sensing plays an important role in coordinating colonization and pathogenic traits on host eukaryotes, giving quorum sensing bacteria a competitive advantage over other epiphytes. Not surprisingly, host eukaryotes and bacteria without quorum sensing have evolved mechanisms to modulate or respond to these quorum sensing species.

Bacteria without complete quorum sensing systems are capable of eavesdropping on other species communication molecules (AHLs) by possessing a quorum sensing response regulator (LuxR-type protein), but not a corresponding AHL synthase (LuxI- type protein). This allows them to respond to other species AHLs. Whole genome sequencing has allowed many species with this potential to eavesdrop to be identified (see Section 2.3.2). The response of these LuxR-type proteins to exogenous AHLs described for several species. E. coli was first described as having the LuxR homologue, SdiA, that appears to up-regulate growth in response to exogenous AHLs (169, 192). In Salmonella, the LuxR homologue SdiA, acted as a transcriptional activator of its virulence island in response to exogenous AHLs (120, 170). It is of note that, Type IV secretion and flagella were identified as regulated by exogenous AHLs in Brucella melitensis (40). Many quorum sensing species posses Type IV secretion, however this trait has not previously been shown to be quorum sensing regulated.

Many Gram positive species, including several Bacillus spp., an Arthrobacter sp. and Rhodococcus sp., and the Gram negative Klebsiella pneumoniae have been found to contain homologues of the AHL lactonase AiiA, which degrades AHLs by cleaving the

27 A Regulatory genes Structural genes B O I R R O N H H O Colonization Phenotypes (e.g., swarming, biofilm formation, Acylated homoserine antimicrobials, virulence factors) lactones 3 I R C R 2 R B r

O Furanones AHLs R 4 O Environment Halogenated furanones from Delisea pulchra

Figure 1-3: Schematic diagram of furanone antagonism of acyl homoserine lactone (AHL)-driven quorum sensing (A), AHL (B) and furanone (C) chemical structures. AHLs and furanones competitively bind to the LuxR-type protein (the response regulator). The furanone-LuxR complex readily undergoes proteolytic degradation thereby increasing LuxR turnover and inhibiting quorum sensing. In this way, furanones produced by Delisea pulchra inhibit quorum sensing regulated colonization and virulence phenotypes. lactone ring (45, 102, 137, 176, 183). Several quorum sensing species also have an AiiA homologue, however it is thought to play a role in quorum sensing regulation (see Section 1.1). Gram positive species commonly co-occur in the phyllosphere with quorum sensing species, so it is possible that lactonases play a role in the interaction between these non-quorum sensing and quorum sensing species. Dong et al. (43) have also shown that plants expressing lactonases from Bacillus sp. show enhanced resistance to the quorum sensing plant pathogen E. carotovora. Other pathways may also exist for AHLs to be utilized by non-quorum sensing species such as Variovorax paradoxus and the quorum sensing species P. aeruginosa PAO1, both of which can use AHLs as a sole energy and nitrogen source (75, 96).

Eukaryotes have also developed mechanisms for defending themselves against quorum sensing. AHLs are known to cause a change in the morphology of Candida albicans morphology from budding to hyphal growth (71, 72). Hence, it is not surprising that fungi have quorum sensing inhibitors. Examples are penicillic acid and patulin isolated from Penicillum sp. (156). Rasmussen et al. (156), using microarray analysis showed that penicillic acid and patulin inhibited 60% and 45% of quorum sensing genes, respectively. These quorum sensing inhibitors have also been shown to accelerate the turnover of LuxR (89).

Plants defend themselves against quorum sensing species in a variety of ways. In E. carotovora infections, plants respond by pumping protons away from the wound site, effectively increasing the pH from less than 6.4 to greater than 8.2 (21). AHLs spontaneously undergo lactonolysis (breaking open the lactone ring) at a pH greater than 7 (204), thereby effectively inhibiting quorum sensing at the wound site.

Plants are also able to produce AHL mimics that induce quorum sensing reporter systems. While this may seem counter intuitive, plants may use these mimics to modulate quorum sensing in its epiphytes, in which quorum sensing acts as a transcriptional repressor and encourages colonization by symbiotic or bio-control strains. Such an AHL mimic has been isolated from pea seedlings (Pisum sativum) (175). This unidentified polar compound is not a structural analogue of AHLs, but somehow stimulates and represses different AHL reporter systems (175). Teplitski et al. (175) suggested that the AHL mimic will itself cause activation or inhibition of the AHL response regulator through binding specificity. P. sativum's AHL mimic stimulated the Serratia sp. swarming reporter as swarming is negatively regulated in Serratia sp. (74). Quorum sensing positively regulates violacein in Chromobacterium violaceum (119)

29 and is repressed by P. sativum's AHL mimic. Therefore it is suggested here that P. sativum's AHL mimic could simply act as a quorum sensing antagonist and have differential effects on phenotypes that are either induced or repressed by quorum sensing.

Quorum sensing inhibitors have also been found in grapes, strawberries, crown vetch, carrots, soybeans, water lilies, tomatoes, habanero (chilli) and garlic (53, 154). Garlic was further investigated and found to contain three quorum sensing inhibitory compounds, one of which was identified as a cyclic disulphur compound (154). This compound appears to have some antagonist specificity as it antagonizes LuxR-based quorum sensing but not the P. aeruginosa las or rhl quorum sensing systems (154).

Quorum sensing inhibitors are also found in marine plants. The best described are the secondary metabolites, furanones, produced by the red macroalga Delisea pulchra (Fig. 1-3).

1.4 Delisea pulchra

Delisea pulchra (Greville) Montagne is a red macroalga (123) found subtidally throughout its costal range in Australia (99), New Zealand (25), Japan (27) and Antarctica (135). Little is documented of its seasonality (16). Throughout this thesis, Bare Island, Sydney, New South Wales, Australia was used as the sampling site for D. pulchra. D. pulchra is found throughout the year at this site, with a decline in the number of plants found between depths of 3-10 m in late summer (January-April), however plants are found below a depth of 10 m during these months (personal observation). The decline in the number of shallow plants in late summer is presumed to be due to bleaching.

Gametophyte and tetrasporophyte D. pulchra are morphologically similar. They are up to 250 mm high with the main axes arising from a holdfast. Gametophytes have carpospores which are sessile, single and terminal on indeterminal branches. Sori contain tetrasporangia covering both sides of indeterminate branch apices (Fig. 1-4). Spermatangia have not been observed (16).

Gland cells containing the secondary metabolites, halogenated furanones, are found along the thallus surface in a concentration gradient (highest concentration at the tip). The higher concentration of gland cells at the tip of the plant is reflected in the surface concentration of furanones (47). Furanones are contained within a specialized vacuole

30 A

Figure 1-4: Description (A) and illustration of Delisea pulchra (B) from Harvey’s History of Australian Seaweeds (65). B A B

C D

Figure 1-5: Light micrographs of Delisea pulchra from Dworjanyn et al. (47). Apical tip showing high density of gland cells in growing region of plant (A). Transverse section showing medullary (m) and cortical (c) cells (arrowhead indicates gland cell, note absence of chloroplasts in these cells and central inclusion which contains yellowish substance (B). Surface view (arrowheads indicate gland cells at surface of algae surrounded by rosette of outer cortical cells (C). Surface of plant showing gland cell (g) and central vesicle (v) (D). 6FDOHEDU ȝPȝPȝPȝPUHVSHFWLYHO\ within the gland cell (Fig. 1-5). These vacuoles deliver furanones to the plant surface by fusing with the cell membrane and secreting them to the surface (47).

D. pulchra has been studied extensively due to its production of furanones, which inhibit a range of marine organisms (41, 61, 69, 70, 110, 118, 161). The mechanism for the inhibition of macro-organisms is not known, however the mechanism for furanone inhibition of bacteria has been elucidated (88, 108, 109, 155). Furanones are structurally similar to the quorum sensing signal molecules, AHLs (Fig. 1-3) and freely diffuse in and out of the cell like AHLs. Furanones compete with AHLs to bind to the AHL response regulator (LuxR-type protein) (85). Furanone binding to LuxR-type proteins cause conformational changes such that the furanone-LuxR complex readily undergoes proteolytic degradation, thereby increasing the turn over of the LuxR-type protein (85, 109).

Furanones have been shown to inhibit a number of quorum sensing phenotypes including swarming, violacein and carbapenem production, luminescence, virulence factor expression, biofilm formation, and exoenzyme production (69, 70, 85, 110, 155) at furanone concentrations found on D. pulchra's surface (47). Furanones have also been shown to inhibit bacterial attachment to furanone coated inanimate surfaces and to inhibit colonization phenotypes such as surface motility in bacteria isolated from a variety of marine surfaces (118). Interestingly, bacteria isolated from D. pulchra are more sensitive to furanones than bacteria isolated from other seaweeds, rocks or seawater, suggesting that D. pulchra's epiphytes are not resistant to its furanones (118). Longford (unpublished data) has shown that furanones modulate succession of bacterial epiphytes and reproducibly select the climax community. This suggests furanones have a duel role in D. pulchra, as quorum sensing inhibitors and in modulating the composition of the bacterial epiphytic community.

While furanones have clearly been shown to reduce attachment of epiphytic bacteria to surfaces in the marine environment and to inhibit a range of colonization and virulence traits in bacterial isolates from D. pulchra and standard laboratory strains, the role of furanones in protecting D. pulchra in vivo has not been demonstrated. In fact, it is not clear if furanones are simply toxic metabolic end products that are secreted from the plant, or if D. pulchra has evolved to produce furanones as specific inhibitors of bacterial quorum sensing, and in this way protect itself from quorum sensing regulated colonization and virulence.

34 1.4.1 Bacterial diseases of red algae

While disease causing species are likely to be common in the environment due to epiphytic bacteria being ubiquitous on algae, there are few examples of bacterial pathogens of red algae. In fact, many red algae can not grow axenically, presumably requiring epiphytic bacteria to provide specific nutrients. Bacteria have been implicated in ice-ice disease on Kappaphycus sp. (92-94), green rot disease on Chondrus crispus (32, 33), secondary infection in green patch disease on Iridaea laminarioides (30) and gall formation on I. laminarioides (31) and Prionitis lanceolata (10).

Gall formation on P. lanceolata has been shown to be caused by a Roseobacter sp. which was identified by retrieving its 16S rRNA gene from a clone library and using a species specific oligonucleotide probe for fluorescent in situ hybridization (119) to visualized and identify bacteria within the gall (10). This intercellular pathogen is unculturable like many symbiotic and pathogenic bacteria which appear to enter a state of unculturable bacteroids once they enter the host. A closely related species, Nereida ignava, has been isolated from Mediterranean sea water near an oyster farm (148). However, its potential virulence on host algae has not been experimentally tested.

The three Prionitis spp., P. lanceolata, P. decipiens and P. filiformis are geographically isolated and yet are all susceptible to gall disease. To investigate whether the same bacteria was infecting all these Prionitis spp., Ashen and Goff (9) recovered the 16S rRNA gene from their galls and found unique Roseobacter ribotypes (unique 16 rRNA gene sequences) from each of the three red algae. These three ribotypes form a monophyletic group within the roseobacter clade which suggests co-evolution between the gall symbionts and their hosts (9). This is further supported by the fact that these algae can not be cross infected by bacteria from galls of other algal species (9), demonstrating specificity within the algal-gall symbiont relationship that can facilitate co-evolution.

The Roseobacter sp. gall symbiont infects P. lanceolata initially through a wound site that penetrates to the medulla of the thallus (6). The wound site heals in about five weeks by forming a new epidermal cortex that seals the site (8). The gall symbiont then enters the medulla and colonizes the intercellular spaces between cortical cells, forming aggregates within what becomes the gall (8, 10). The gall symbiont is only found within the gall and not in adjacent thallus tissue. Eight to twelve weeks after inoculation the gall erupts through the epidermis, having formed a cell mass where

35 cells appear to be dividing asymmetrically, characteristic of the cancer-like growth (8). The gall symbiont appears to be localized only in the intercellular spaces and is not found intracellularly, except where necrotic cells have been colonized.

The plant hormone indole-3-acetic acid (IAA) is required for gall formation in terrestrial plants, however the specific role of IAA in tumorogenesis is unknown (202). P. lanceolata has elevated IAA levels usually two to three fold higher in its galls compared with its thallus (7). This finding is intriguing as Agrobacterium and Pseudomonas spp. encode IAA producing genes, and thereby direct uncontrolled cellular division (3, 203).

Roseobacter sp. were previously called marine Agrobacterium due to their close relationship to this group (182). This is of particular interest as Agrobacterium spp. cause disease in terrestrial plants and quorum sensing regulates conjugation of the Ti plasmid in A. tumefaciens (146). The Ti plasmid encodes most of the genes essential for the infection process (60). Another Agrobacterium sp., A. vitis is rendered avirulent when its quorum sensing response regulator (aviR) is mutated (206) or shows reduced virulence when its second quorum sensing response regulator encoding gene (avhR) is mutated (64).

There are few examples of bacterial diseases of red algae, however there is a growing number of species from the roseobacter clade that have been implicated as pathogens of eukaryotic marine organisms including corals, red algae, and oysters (8-10, 14, 15, 54). The Roseobacter clade as a potential reservoir of marine pathogens is further discussed in Chapter 3 and 4.

1.5 Molecular microbial ecology

The last two decades of molecular microbial ecology have revolutionized the way in which we study and think about prokaryotes. This revolution has been fueled by the rapid development and adoption of molecular techniques in microbial ecology. There are a few molecular methods that have been widely adopted and maintained their popularity; these include clone libraries, denaturing gradient gel electrophoresis (DGGE), terminal restriction fragment length polymorphism (T-RFLP) and fluorescent in situ hybridization (FISH) (119). There are also several new methods that have been developed in the last five years, that are significant advances in our understanding of molecular ecology, however their cost inhibits their widespread application: These include metagenomics and environmental microarray based technologies. All these methods have been extensively reviewed (5, 63, 114-116, 125-127, 160, 189). Their

36 function or role in molecular microbial ecology will be considered below. The aims of molecular microbial ecology are identified here as: the ability to 1) measure microbial diversity, 2) identify dynamic effects on the microbial community and 3) link the function of a microbial community to its structure.

1.5.1 Measuring diversity

It has been apparent since the early work of Winogradsky that unculturable micro- organisms were prevalent in the environment. It was Torsvik et al. (179, 180) who revealed the extent of unculturable bacterial diversity using DNA melting profiles to estimate the number of genomes isolated from DNA directly extracted from soil and DNA extracted from cultured soil isolates. From the soil-extracted DNA they identified 4000 bacterial genomes compared with the 20 genomes identified from the library of cultured soil isolates (180). There have been many studies that present a case for more or less prokaryote diversity (62, 144, 208), however it is the influence of the widely accepted dogma that there is an 'unseen majority' (196) that has fueled the prolific number of molecular-based diversity studies.

Bacterial diversity is usually surveyed from an environmental sample using 16S rRNA gene clone libraries (59). Such libraries are made using the polymerase chain reaction (PCR) to amplify the 16S rRNA gene from DNA extracted from an environmental sample. The 16S rDNA-PCR products are then cloned for sequencing. Sequences are then subjected to statistical and phylogenetic analyses to determine the extent of recovered diversity and to identify the bacteria from which the 16S rRNA gene sequences are derived. This method has been successful in identifying extensive bacterial diversity, however it has become marred by a number of limitations.

The bias introduced into all PCR-based methods is two fold. The DNA template is mixed, as environmental DNA contains many species 16S rRNA genes from many species. First, each cell will have differing DNA extraction efficiency, and each 16S rRNA gene copy a different affinity for the primers, thereby producing a bias in which species preferentially bind primers (24, 52, 147). Second, the PCR conditions will bias which species 16S rRNA gene is recovered as PCR cycle number, chimera formation and GC content have been shown to influence amplification (2, 49).

Another source of bias arises due to the existence of multiple 16S rRNA gene copies within a bacterium which can display intragenomic heterogeneity (34, 36, 37). This heterogeneity has resulted in most studies adopting a 98% 16S rRNA gene sequence

37 similarity cut off (57). This is problematic in the face of the subspecies diversity that is being uncovered by exhaustive clone libraries (2) and multilocus sequence typing analysis (MLSA) (17, 29, 57, 73). The extent of bacterial diversity at the sub-species level can not be assessed using a gene with the properties of the 16S rRNA gene, leading some researchers to instead use other single copy housekeeping genes (18, 29, 35, 37, 73, 83, 84, 87, 90, 107, 122, 124, 139, 158, 159, 172, 174, 191).

1.5.2 Community dynamics 16S rRNA gene-based molecular tools rapidly expanded with a variety of fingerprinting methods developed including length heterogeneity PCR, automated ribosomal intergenomic spacer analysis (ARISA), DGGE and T-RFLP (103), with DGGE and T- RFLP the most widely adopted. Fingerprinting methods make a molecular 'fingerprint' of the bacterial community by amplifying a specific gene fragment (usually the 16S rRNA gene) and separating the gene fragments on the basis of sequence. Sequence divergence is exploited in a number of ways, either due to differential melting in DGGE, or differential restriction enzyme digestion for ARISA and T-RFLP.

The fingerprint resulting from an environmental sample is then compared to those derived from other samples, such that changes in community composition between samples can be followed. Sampling will usually reflect environmental conditions, such as time of sampling, nutrient availability, presence of inhibitors and geographical variability. These methods are incredibly powerful as they are high throughput and cost effective, allowing an expansive sampling scheme (compared with the snapshot provided by a 16S rRNA gene clone library). Such methods are therefore adopted to describe ecological phenomena. (114). Semi-quantitative protocols have also been developed for DGGE and T-RFLP that allow for shifts in the abundance of species (changes in density of a band) to be evaluated, not simply the presence/absence of species (bands) (13, 143).

There are several limitations to fingerprinting methods, including difficulty in interpreting 16S rDNA-derived banding patterns, as a single organism can produce a complex banding pattern (34, 37) and the size of the gene fragment provides only limited sequence data. This often limits the identification of sequences from these methods, particularly T-RFLP fragments as they are difficult to isolate and of variable size. DGGE fragments are usually 200-600 bp and are commonly sequenced, however they provide limited sequence and DGGE bands commonly recover more than one sequence (165).

38 1.5.3 Linking function to diversity

The focus of molecular microbial ecology has shifted from cataloguing environmental 16S rRNA gene sequences to functional studies, where the function of a community and its interspecies interactions are explored. These new areas are not easily addressed using 16S rRNA gene clone libraries as a bacterium's function can rarely be derived from its identity. This uncoupling of identity with function is due to the prevalence of lateral gene transfer (LGT) as a mechanism in prokaryotic evolution (17) (see Chapter 2). The implications of LGT where certain traits can not be attributed to species as is the case for macro-organisms, has proved one of the greatest stumbling blocks for microbial ecology.

Several traditional methods have been modified to adopt to this shift in our understanding of prokaryotic evolution, with clone libraries, DGGE and T-RFLP directly targeting functional genes (1, 68, 114, 131, 178, 193). Other methods used a combinatorial approach such as FISH-MAR which uses metabolic markers in combination with phylogenetic markers (189) or CARD-FISH the increased detection resolution of which allowed pmoA mRNA to be determined in combination with 16S rRNA (141). Such methods are yet to be widely adopted but have the potential to overcome our current inability to adequately link diversity with function.

Metagenomics also arose as a method to address the need to assess the functionality of microbial communities. This technique catalogues environmental DNA (eDNA) sequences, coined the 'metagenome'. The metagenomes conceptualize that genes are freely exchanged between organisms. Metagenomics involves either shotgun sequencing clones of 1-3Kb (184), or the construction of large insert libraries from eDNA (11). Due to the associated cost, environmental shotgun sequencing has only been achieved by Venter et al. (184). However, large insert libraries are becoming commonly used as traits can be screened for in vectors that express their cloned eDNA (12, 19, 58, 63, 86, 104, 185, 198). The main drawback of this method is that unless part of the ribosomal operon is included in the cloned eDNA, its source is unknown. This can be overcome by screening (98, 100, 185) or the use of restriction enzymes that target the ribosomal operon, allowing digested eDNA containing a ribosomal operon to be selectively cloned (129).

39 1.6 Thesis aims and Chapter summary

The aims of this thesis are: 1. To determine if the quorum sensing gene families, luxI (the autoinducer synthase) or luxR (the response regulator) are susceptible to LGT and if quorum sensing 'cheats' are common among quorum sensing and non-quorum sensing bacteria 2. To identify quorum sensing epiphytic bacteria from D. pulchra whose colonization and / or pathogenesis of D. pulchra is augmented by furanones 3. To further characterize the phylogeny of the roseobacter clade using the 16S rRNA and rpoB genes and identify the quorum sensing strains within the roseobacter clade 4. To develop rpoB as an alternate molecular marker for microbial ecology

These aims are addressed in the following thesis chapters; Chapter Two describes the evolution of the quorum sensing gene families, luxI and luxR. Both these genes appear to undergo frequent LGT such that quorum sensing can not be identified using 16S rRNA-based diversity studies. While these genes characterize AHL-driven quorum sensing, luxR appears have been co-opted for eavesdropping on other species. Its presence in species without quorum sensing means that it is not a suitable gene target for DGGE.

Chapter Three identifies a quorum sensing bacterium, Ruegeria strain R11, among D. pulchra's epiphytic bacterial community using a culture based approach. Ruegeria strain R11 is identified as a novel intracellular pathogen of D. pulchra, and D. pulchra is shown to chemically defend itself through the production of furanones. Additionally, Ruegeria strain R11 is shown to have temperature regulated virulence.

Chapter Four compares the 16S rRNA and rpoB genes as molecular markers of microbial diversity. One hundred and ten completed bacterial genomes are used as a dataset to compare these genes for their phylogenetic resolution over the full length gene and DGGE-gene fragments. The implications of using a gene displaying intragenomic heterogeneity, such as the 16S rRNA gene is explored, especially in regard to sub-species diversity and the localization of heterogeneous positions.

Chapter Five is a revised phylogeny of the genera Roseobacter, Ruegeria and Roseovarius. These genera have been shown to be paraphyletic and an attempt is

40 made to resolve their phylogeny using the 16S rRNA and rpoB genes. Also, these strains are screened for the quorum sensing signal molecules, AHLs, and their AHLs are identified using a combination of thin layer chromatography (TLC) and the reporter strain A. tumefaciens A136.

Chapter Six is a general discussion of the thesis. It focuses on the role of Ruegeria strain R11 as a seaweed pathogen and the continuing work being undertaken. The broader role of the roseobacter clade as a reservoir of marine pathogens is also discussed. In addition, rpoB as a molecular marker in microbial ecology is discussed with reference to its potential and pitfalls.

41 1.7 References

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62 2 Finding quorum sensing bacteria in the environment: evolutionary implications for acyl homoserine lactone (AHL) – driven quorum sensing

2.1 Introduction

16S rRNA gene-based diversity studies attempt to describe the species composition of a defined environment. When complemented with in situ identification (e.g. FISH) or fingerprinting methods (such as T-RFLP or DGGE), an understanding of species localization and community dynamics can be obtained. Although microbial ecologists have rapidly adopted such molecular methods, the absence of a comprehensive theoretical framework for this new field has hindered meaningful interpretation of the data produced. More specifically, there has been a lack of strong evolutionary and ecological principles to guide a meaningful analysis of the abundant molecular data generated. A common mistake made by microbiologists is the view that in knowing what is present in a particular habitat, it is possible to understand their functional interactions with other species.

This mistake derives from the misconception that characteristics of ecosystems can be derived from diversity studies. The idea originates from the field of macro-ecology, where productivity and stability can be inferred from the diversity index of an environment (23). In such macro-scale systems, the function of organisms can often be inferred, i.e. plant species will be primary producers and feline species will be predators. However, ecological functions cannot be readily inferred from the presence of 16S rRNA gene sequences recovered from a clone library of a particular environment. A few such sequences often represent a group of organisms with a broad range of physiological characteristics. As an example, Roseobacter denitrificans is photosynthetic (34), however other closely related Roseobacter species are not (18).

This fundamental difference between prokaryotic and eukaryotic diversity results from a divergence in how genetic material is inherited. For eukaryotes, progeny obtains DNA through vertical inheritance, with recombination in meiosis the major source of genetic variation in offspring. In prokaryotes, offspring result from mitosis, so progeny are therefore genetically identical to their parent. However, genetic variation leading to speciation does occur in prokaryotes (28, 29, 42). This variation arises from point mutations and genomic rearrangements, but also lateral gene transfer (LGT). Among

63 these three sources of genomic variation, lateral transfer of genetic material between prokaryotes, and from phages and eukaryotes, is likely to be the one with the greatest impact on microbial evolution (3, 44). Bacterial genomes will constantly be subjected to LGT, with genetic material conveying phenotypic plasticity being frequently transferred while 'core' housekeeping genes undergo a much lower relative rate of transfer (4).

It is this fundamental difference in the way genetic variation arises in prokaryotic and eukaryotic species that leads to the requirement to re-examine themes borrowed from macro-ecology when considering microbial ecology. Within a new theoretical framework specific for microbial ecology, the fact that phenotype cannot be directly inferred from phylogeny for microbes becomes an expected result of the evolutionary properties of micro-organisms rather than an inconsistency.

Bacteria utilize regulatory systems called quorum sensing to sense their population density. Such systems are dependant on the production of signaling molecules that either diffuse out of the cell or are actively secreted. When signal molecules reach a critical threshold concentration, they re-enter the bacterial cells to activate specific genes, many of which are involved in population phenotypes such as swarming, biofilm formation and virulence factors (9, 15-17, 32) (see Section 1.2). The best characterized quorum sensing system is that driven by acylated homoserine lactone (AHL) signal molecules (see Section 1.1).

The AHL quorum sensing system is characterized by two core proteins, the LuxI-type protein (the AHL synthase), and the LuxR-type protein (the response regulator). Gray and Garey (11) demonstrated LGT among the LuxI/R protein families, which implied that quorum sensing species can not be inferred from diversity studies using 'core' genes. Many more quorum sensing species have been identified since Gray and Garey's (11) initial study, and the growing number of genome sequenced organisms has provided many more luxI/R gene sequences. This chapter re-examines the evolution of these gene families and the existence of 'cheaters', organisms that despite not having quorum sensing are capable of sensing quorum sensing.

64 2.2 Methods

2.2.1 Sequence retrieval and alignment

LuxI and LuxR-type protein sequences were retrieved from NCBI by BLASTP searches using amino acid sequences of biochemically characterized representatives of these families. Amino acid alignments (for LuxI and LuxR-type proteins) were constructed using CLUSTALW (36) and edited manually to remove ambiguous positions.

2.2.2 Phylogenetic analyses

Maximum likelihood phylogenetic analyses of LuxI and LuxR-type proteins were performed at the amino acid level protein datasets using the PROML program with the JTT amino acid substitution matrix, a rate heterogeneity model with Ȗ-distributed rates over four categories, with the D among-sites rate variation parameter estimated using TREE-PUZZLE, global rearrangements and randomized input order of sequences (10 jumbles) was performed. Bootstrap support values represent a consensus (obtained using CONSENSE) of 100 Fitch-Margoliash distance trees (obtained using PUZZLEBOOT and FITCH) from pseudo-replicates (obtained using SEQBOOT) of the original alignment. The settings of PUZZLEBOOT were the same as those used for PROML, except that no global rearrangements and randomized input order of sequences are available in this program. PROML, CONSENSE, FITCH and SEQBOOT are from the PHYLIP package version 3.6a (http://evolution.genetics. washington.edu/phylip.html). TREE-PUZZLE and PUZZLEBLOOT were obtained from the programs website (http://www.tree-puzzle.de).

65 2.3 Results and Discussion

2.3.1 The role of lateral gene transfer (LGT) in the evolution of the LuxI- and LuxR-type protein families

AHL-driven quorum sensing involves two characteristic and conserved proteins: the AHL or autoinducer synthase (LuxI) and the transcription regulator (LuxR). LuxI synthesizes a constitutive level of AHL that freely diffuses in and out of the cell. Once a critical concentration of signal molecule is reached (a "quorum" is established), the AHLs bind to the regulator (LuxR) forming an AHL-LuxR complex that in turn binds to the promoter of target genes, activating or repressing transcription (14, 39) (Fig. 1-1). AHL quorum sensing regulates a variety of phenotypes, including those responsible for biofilm formation, surface motility, gene transfer agent, conjugation and the production of exo-enzyme, antibiotics, secondary metabolites, virulence factors and EPS (9, 15, 16, 31, 37, 39). Despite the diversity of the phenotypes they regulate, luxI and luxR constitute evolutionarily conserved gene families. Their homologues can be identified in most species in which AHL quorum sensing is known to operate, although some alternative AHL synthases do exist (19, 26). Various species can also possess differing numbers of luxI and luxR homologues or even a luxR homologue alone (see Section 2.3.2). For example, Escherichia coli possesses a luxR homologue and can respond to exogenous AHLs (35), but lacks a luxI homologue and cannot synthesize AHLs.

The orientation, proximity, and location of luxI and luxR homologues are variable, with the only apparent conservation observed within species (11). Therefore, these characteristics are of little help in making phylogenetic inferences. luxI/R homologues can be found both within chromosomes (e.g., Pseudomonas aeruginosa) and on plasmids (e.g., Agrobacterium tumefaciens). In fact, AHL quorum sensing itself regulates the mobilization of two types of mobile element. In A. tumefaciens, the conjugational factor that transfers the Ti plasmid to plants is regulated by traI/R (30) and an AHL-regulated gene transfer agent has been identified in Rhodobacter capsulatus (33). The latter is of particular interest as the gene transfer agent packages random 4.5-kb DNA fragments in bacteriophage-like particles, providing a mechanism for LGT of any of its genes.

Members of the luxI/R families are found only within the Proteobacteria, specifically the D, E, and J classes, being absent from the G and H classes (although this may reflect limited sampling of the latter two classes) (24). Moreover in the proteobacterial groups

66 in which they are found, luxI/R homologues are rather patchily distributed. Two main hypotheses have been put forward to explain this distribution: differential loss events or LGT. Gray & Garey (11) specifically argued the case for LGT within the luxI/R gene families, pointing out that a differential loss scenario would involve a myriad of gene duplications and deletions. Their phylogenetic analyses of luxI/R homologues are consistent with this idea. Indeed, although the luxI and luxR trees are similar in topology, with incongruence being found mostly in poorly supported clades, a few strongly supported exceptions can be seen for the monophyly of each of the proteobacterial classes present in the tree (D, E, and J). The E-proteobacterium Chromobacterium violaceum cviR gene was shown to cluster with proteobacterial homologues from the J class with strong bootstrap support (11). The cviI gene of this organism also clusters with homologues from the J class, although with weaker bootstrap support. Our updated phylogeny (Fig. 2-1A&B) identified an additional case of LGT at the class level, this time between Pseudomonas and the E class. Within the Pseudomonas genera are three distinct groups of both luxI/R homologues, each with strong bootstrap support. One of these clades, in which rhlI/R of P. aeruginosa and csaI/R of P. aureofaciens are basal, contains nested E-proteobacterial homologues from Ralstonia and Burkholderia. These E-proteobacteria are therefore likely to have obtained AHL quorum sensing from this Pseudomonas luxI/R type.

Lateral transfer of luxI/R homologues has also been detected between more closely related organisms. Rhizobium leguminosarum provides one of the most interesting cases with two AHL synthases (rhiI and cinI) and four response regulators (rhiR, cinR, bisR, and triR) that are distributed throughout the two D-proteobacterial clades found in the luxI/R phylogenies (Fig. 2-1A&B). The coupled cinI and cinR are incorporated into the chromosome with the other three luxR homologues encoded within a plasmid (43). The bisR and cinR genes are more closely related to each other than to either of their plasmid-borne homologues. This strongly supported relationship suggests LGT of a cinR homologue from a plasmid to a chromosome.

Another interesting case is Serratia. The luxI/R gene sequences are publicly available for three species of this genus. S. proteamaculans and S. marscesens cluster together with strong bootstrap support within both the luxI and luxR trees (Fig. 2-1A&B), but the third species (Serratia sp. ATCC 39006) finds itself distal to the other Serratia spp.. Horng et al. (14) identified transposon sequences in the proximity of the spnTIR genes of S. marscesens involved in AHL quorum sensing. Eight ORFs were identified up- and

67 Figure 2-1: Best maximum likelihood phylogenetic trees of LuxR transcription regulator (A) and LuxI AHL synthase (B). Trees are updated from Gray and Garey (11) and were constructed using the PROML algorithm. Black dots indicate maximum likelihood distances bootstrap support over 95%, and white dots support over 80% (these values were obtained with PUZZLEBOOT). Strains are indicated after species names, followed by the gene name in parenthesis. Genes that encode for enzymes, the function of which has not been biochemically confirmed, are indicated as putative or hypothetical. If a gene is found on a plasmid, the plasmid name is indicated within brackets.

68 Pseudomonas aeruginosa PAO1 (RhlR) G Pseudomonas aureofaciens 30-84 (CsaR) G Ralstonia solanacearum GM1000 (putative LuxR) [megaplasmid] Pseudomonas aeruginosa PAO1 (QscR) G Burkholderia cepacia BD01 (BviR) B Ralstonia solanacearum GM1000 (SolR) Burkholderia cepacia LMG1222 (CepR) Burkholderia vietnamiensis PC259 (CepR) Burkholderia stabilis LMG14291 (CepR) Burkholderia ambifaria BcF (BafR) Rhizobium leguminosarum bv viciae (RhiR) [pRL1JI] Rhodopseudomonas palustris (hypothetical) Bradyrhizobium japonicum USDA110 (putative LuxR) A Bradyrhizobium japonicum USDA110 (putative LuxR) Agrobacterium tumefaciens C58(Cereon) (TraR) [Ti] Rhizobium leguminosarum bv viciae (TriR) [pRL1JI] Rhizobium rhizogenes MAFF03-01724 (putative TraR) [pRi1724] Rhizobium sp. NGR234 (putative TraR) [pNGR234a] Rhodobacter sphaeroides 2.4.1T (CerR) A Ruegeria sp. PR1b (putative TraR) [p5D25] Rhizobium etli CNPAF512 (RaiR) Rhizobium leguminosarum bv viciae (BisR) [pRL1JI] Rhizobium etli CNPAF512 (CinR) Rhizobium leguminosarum bv viciae (CinR) Pseudomonas syringae BR2.024 (PsyR) Yersinia ruckeri 1315 (YukR) Yersinia pseudotuberculosis O:1b (YtbR) Pectobacterium carotovorum Ecb168 (EcbR) Erwinia chrysanthemi NCPPB1066 (EchR) Serratia sp. ATCC39006 (SmaR) G Yersinia enterocolitica NCTC10460 (YenR) Yersinia pseudotuberculosis O:1b (YpsR) Pantoea stewartii SS104 (EsaR) Serratia marcescens SS-1 (SpnR) Serratia proteamaculans B5a (SprR) Aeromonas salmonicida NCIMB1102 (AsaR) Aeromonas hydrophila A1 (AhyR) Pseudomonas fluorescens NCIMB10586 (MupR) Pseudomonas putida IsoF (PpuR) G Pseudomonas aeruginosa PAO1 (LasR) Microbulbifer degradans 2-40 (hypothetical) Vibrio fischeri ES114 (LuxR) Listonella anguillarum NB10 (VanR)

0.1 substitution/site LuxR Pseudomonas aeruginosa PAO1 (RhlI) G Pseudomonas aureofaciens 30-84 (CsaI) G Ralstonia solanacearum GM1000 (putative LuxI) [megaplasmid] Burkholderia cepacia BD01 (BviI) Ralstonia solanacearum GM1000 (SolI) B Burkholderia stabilis LMG14291 (CepI) Burkholderia ambifaria BcF (BafI) Burkholderia cepacia LMG1222 (CepI) Burkholderia vietnamiensis PC259 (CepI) Microbulbifer degradans 2-40 (hypothetical) G Listonella anguillarum NB10 (VanI) G Vibrio fischeri ES114 (LuxI) G Pseudomonas fluorescens NCIMB10586 (MupI) G Pseudomonas aeruginosa PAO1 (LasI) G Pseudomonas putida IsoF (PpuI) G Agrobacterium tumefaciens C58 (Cereon) (TraI) [Ti] Rhizobium sp. NGR234 (putative TraI) [pNGR234a] Rhizobium rhizogenes MAFF03-01724 (putative TraI) [pRi1724] Rhodobacter sphaeroides 2.4.1T (CerR) A Ruegeria sp. PR1b (putative TraI) [p5D25] Rhizobium etli CNPAF512 (RaiI) Rhizobium etli CNPAF512 (CinI) Rhizobium leguminosarum bv viciae (CinI) Pseudomonas syringae BR2.024 (PsyI) Erwinia chrysanthemi NCPPB1066 (EchI) Yersinia enterocolitica NCTC10460 (YenI) Yersinia pseudotuberculosis O:1b (YpsI) Serratia sp. ATCC39006 (SmaI) G Pectobacterium carotovorum Ecb168 (EcbI)

Yersinia ruckeri 1315 (YukI) Pantoea stewartii SS104 (EsaI) Serratia proteamaculans B5a (SprR) Serratia marcescens SS-1 (SpnI) Aeromonas salmonicida NCIMB1102 (AsaI) G Aeromonas hydrophila A1 (AhyI) G Rhizobium leguminosarum bv viciae (RhiI) A Bradyrhizobium japonicum USDA110 (putative LuxI) A Rhodopseudomonas palustris (hypothetical) A

0.1substitution/site

LuxI downstream of spnTIR and were found to be remnants of transposons Tn3 and IS3 (14). In contrast, Serratia sp. ATCC 39006 swrI/R genes are flanked by remnants of the IS1 transposon. It suggests that luxI/R homologues were laterally transferred to Serratia via transposons, with different origins for the two luxI/R gene types found in this genus.

The luxI/R gene families are thought to be an early invention within the Proteobacteria that subsequently evolved within the different classes (11). However, these gene families are not represented within the G and H -Proteobacteria. Although early deletion events can be postulated for the absence of luxI/R homologues in these classes, they would have to be accompanied by several other deletion events throughout every clade of the Proteobacteria, since luxI/R homologues are found in a limited number of genera. What can be demonstrated within the "recent" evolution of the luxI/R families are cases of lateral transfer at the species, genus, and class levels. It suggests that LGT within the luxI and luxR families is frequent, and necessary - along with gene duplication and differential loss - to explain the dissemination of these gene families in Proteobacteria.

2.3.2 Uncoupled LuxR-type proteins: regulation or simply eavesdropping?

Almost all AHL producing bacteria rely on only two protein families, the LuxI-type protein (the AHL synthase), and the LuxR-type protein (the response regulator) for active quorum sensing circuits (3). Exceptions exist, however, such as the LuxM AHL synthase in Vibrio harveyi (2) and the putative HdtS AHL synthase identified in P. fluorescens F113 (19), which replace the LuxI-type AHL synthase.

A variety of phenotypes described above are quorum sensing regulated, but all have one thing in common: the population requires a quorum for gene expression to convey a competitive advantage. These phenotypes require a certain population density because either: 1) the multi-cellular characteristic of the behavior involves cell differentiation (e.g. swarming), or 2) the fitness benefit of many individual cells simultaneously expressing the same phenotype (e.g. virulence factors). The competitive advantage of quorum sensing regulation in turn creates selective pressure for co-occurring species to sense and respond to the quorum sensing of another species. One possible mechanism for doing this is for a microbe to use quorum sensing signals produced by competing bacteria in the transcriptional regulation of genes mediating species interaction.

The number of LuxI- and LuxR-type proteins in a given bacterium is not always equal. A LuxI- type protein has a specific LuxR-type protein that binds its AHL, but there are

71 often ‘extra’ or uncoupled LuxR-type proteins. An uncoupled LuxR protein is defined as either not having a corresponding LuxI protein in the same cell to activate it or as being ‘extra’ to an already complete quorum sensing LuxI/R circuit. For example, P. aeruginosa contains two quorum sensing circuits (LasI/R and RhlI/R) but also contains an extra LuxR-type protein, QscR (5). Also, bacteria exist that contain only a LuxR-type protein but no other LuxR or LuxI proteins (i.e. have no complete quorum sensing circuits). Examples are Salmonella typhimurium, E. coli and Brucella melitensis (7, 26, 40). S. typhimurium and E. coli contain an uncoupled LuxR-type protein called SdiA but do not produce any detectable AHLs (13, 25, 40). Importantly, SdiA has been shown to respond to exogenous AHLs and to effect gene expression (13, 25, 40). As a result, these organisms have the potential to eavesdrop on quorum sensing by cohabitating bacteria and modulate their interaction with competitors (25). A phylogenetic survey of all bacterial genomes in public databases identified 13 organisms that contained one or two LuxR-type proteins but no corresponding AHL synthase (LuxI, LuxM and HdtS) (Fig. 2-2A - micro-organisms in bold) thereby each having the potential to eavesdrop on AHL-driven quorum sensing by other microbes. This current study offers the hypothesis that uncoupled LuxR-type proteins detect exogenous AHLs produced by other bacterial quorums and consequently regulate transcription. This would occur in bacteria that contain complete as well as incomplete quorum sensing circuits.

The best characterized of the uncoupled LuxR-type proteins in a bacterium with complete quorum sensing circuits is found in Rhizobium leguminosarum bv. viciae. This bacterium has two quorum sensing networks, cin and rai, with two additional LuxR-type proteins, TriR and BisR. The latter negatively regulates cin quorum sensing, thereby maintaining a low endogenous 3O-C14-HSL concentration (as CinI synthesizes 3O- C14-HSL) (6). As 3O-C14-HSL is also the cognate AHL for BisR, an exogenous source is required to positively regulate triR, which is borne by the pRL1JI plasmid, and induce conjugal transfer of pRL1JI (6). The incorporation of BisR into the QS regulatory network allows R. leguminosarum bv. viciae to induce TriR regulated plasmid conjugal transfer only when a quorum of 3O-C14-HSL producing bacteria (the recipients) is established. The phylogeny of Rhizobia and Agrobacterium LuxR-type proteins, with the LuxR-type proteins whose cognate AHL is 3O-C14-HSL forming a monophyletic group illustrated in Fig. 2-2B. This suggests that cross-talk between these species originates from duplication or lateral transfer of the genes coding for 3O- C14-HSL-binding LuxR-type proteins within the Rhizobia.

72 A. Uncoupled LuxR-type proteins and nearest neighbors Pseudomonas syringae 1448A (AAZ33072) AhlR Pseudomonas fluorescens Pf-5 (YP_262370) Pseudomonas syringae 1448A (AAZ35974) Xanthomonas campestris ATCC33913 (NP_638166) AhyR Xanthomonas oryzae PXO86 (AAR91700) AhyR Xanthomonas axonopodis 306 (AAM37833) AhyR Rhizobium leguminosarum (A AO21112) TraR Brucella melitensis 16M (NP_542094) Brucella abortus 9-941 (YP_222926) Rhizobium leguminosarum (CAD20930) RaiR Rhizobium leguminosarum (A AO21111) BisR Rhizobium leguminosarum (AAF89989) CinR Photorhabdus luminescens TTO1 (NP_931726) Erwinia amylovora 552 (AAW78919) ExpR Escherichia coli O157:H7 (BAB36077) SdiA Escherichia coli K12 (NP_416426) SdiA Escherichia coli CFT073 (NP_754222) SdiA Shigella flexneri 301 (NP_707803) SdiA Shigella sonnei SS046 (AAZ87922) SdiA Salmonella typhimurium LT2 (AAL20862) SdiA Salmonella enterica ATCC9150 (YP_150210) SdiA Photorhabdus luminescens TTO1 (NP_927679) Pseudomonas fluorescens Pf-5 (YP_260729) Burkholderia cepacia K56-2 (AAD12726) CepR Brucella abortus 9-941 (YP_220957) Brucella melitensis 16M (AAL52939) 10 substitutions

Figure 2-2: Phylogenies of LuxR-type proteins in bacteria that lack complete quorum sensing circuits (bold) and nearest neighbours (A), Rhizobia and Agrobacterium LuxR-type proteins (B) and Pseudomonas and Burkholderia LuxR-type proteins (C). Pseudomonas aeroginosa LuxR-type proteins given in bold. The number in parentheses found after each taxon name is the accession number for the respective protein sequence, followed by the name of the protein in question. The trees were compiled by maximum likelihood using PROML. Black dots indicate maximum likelihood distances bootstrap support over 95%, and white dots support over 80% (these values were obtained with PUZZLEBOOT from 100 pseudo-replicates of the original dataset). B. Rhizobia and Agrobacterium LuxR-type proteins Agrobacterium tumefasciens (AAC17192) TraR Agrobacterium vitis (CAA80425) TraR Rhizobium etli CFN42 (AAO43545) TraR Rhizobium sp. NGR234 (P55407) TraR Agrobacterium rhizogenes MAFF03-01724 (BAB16238) TraR Rhizobium leguminosarum (AAO21112) TraR Mesorhizobium sp. BNC1 (EAN06571) Rhizobium sp. NGR234 (P55629) Rhizobium leguminosarum (CAD20930) RaiR Mesorhizobium sp. BNC1 (EAN05978) Rhizobium leguminosarum (AAO21111) BisR Rhizobium etli CFN42 (AAO43546) CinR 3O-C14-HSL Rhizobium leguminosarum (AAF89989)} CinR } 10 substitutions

C. Pseudomonas and Burkholderia LuxR-type proteins Pseudomonas chlororaphis 333 (P54303) PhzR Pseudomonas aeruginosa PAO1 (NP_252167) RhlR Pseudomonas chlororaphis 333 (AAK73190) CsaR Ralstonia solanacearum GMI1000 (NP_522339) Burkholderia ambifaria AMMD (EAO43680) Burkholderia mallei ATCC23344 (YP_102421) Burkholderia pseudomallei K96243 (CAH36350) Burkholderia ambifaria AMMD (EAO45999) Burkholderia cepacia DBO1 (AAK35156) BviR Pseudomonas aeruginosa PAO1 (NP_250589) QscR Burkholderia pseudomallei K96243 (CAH37760) Burkholderia pseudomallei K96243 (YP_111189) Pseudomonas fluorescens NCIMB10586 (AAK28504) MupR Pseudomonas putida IsoF (AAM75413) PpuR Burkholderia fungorum LB400 (ZP_00284685) Pseudomonas aeruginosa PAO1 (NP_250121) LasR Burkholderia vietnamensis G4 (ZP_00426008) Ralstonia solanacearum GMI1000 (CAD17075) SolR Burkholderia glumae BGR1 pBGA40 (AAV52804) TofR Burkholderia ambifaria AMMD (EAO49407) Burkholderia cenocepacia (ZP_00460782) Burkholderia stabilis LMG14291 (AAK70350) CepR

1 substitution Another example of an uncoupled LuxR-type protein is QscR in P. aeruginosa. QscR negatively regulates both the las and rhl quorum sensing systems by binding LasR, RhlR and their cognate AHLs (20). Very recently, QscR has been shown to affect a distinct regulon that is activated by the LasI generated signal 3O-C12-HSL (22). QscR displays a low specificity for a broad range of AHLs signals but is more sensitive to 3O- C10-HSL, an AHL which is not produced by P. aeruginosa. It suggests that QscR may function by responding to other AHLs produced by co-habitating microbes (10, 21). It is proposed that the most likely exogenous AHL candidates to interact with QscR are derived from other Pseudomonas and/or Burkholderia species. These organisms often have similar life styles as ubiquitous microbes commonly found in soil, with some species within both of these genera being opportunistic pathogens. Significantly, Burkholderia cepacia often co-habitat’s with P. aeruginosa in infected lungs (8). Although Pseudomonas and Burkholderia are from different orders of the Proteobacteria, the closest homologues of P. aeruginosa LuxR-type proteins are found in Burkholderia spp., suggesting that the genes coding for them have been involved in lateral transfer (Fig. 2-2C). The close phylogenetic relationship between Burkholderia LuxR-type proteins and QscR makes it likely that the latter would respond to AHLs produced by the formers. Such modulation of P. aeruginosa AHL regulated gene expression by Burkholderia spp. (or other co-habitating organisms) has yet to be tested.

A survey of all completed Proteobacterial genomes showed that 21 out of the 35 organisms with both LuxI and LuxR homologues have more LuxR-type proteins than LuxI-type proteins (Table 2-1). It suggests that eavesdropping among quorum sensing species maybe be widespread.

Given that bacteria rarely exist in monocultures but mostly live in complex mixed communities, it would not be surprising that some of them would evolve the ability to modify their activity after sensing their neighbours. By eavesdropping on the quorum established by another organism and consequently altering its own transcriptome, a bacterium would achieve a level of social sophistication previously thought to not exist among bacteria. R. leguminosarum bv. viciae eavesdrops on its 'friends' to delay conjugation until a quorum is established. Other bacteria may eavesdrop on 'foes' to exploit their quorum sensing response (such as nutrients made available by exo- enzymes). In any case, it has yet to be experimentally explored whether eavesdropping conveys a competitive advantage.

75 Table 2-1: Number of LuxI and LuxR-type proteins found in species with completed genomes. For species where the number of LuxR homologues are greater that the number of LuxI homologues, the number of LuxR homologues is in bold.

Organism LuxI LuxR

Agrobacterium tumefaciens C58 1 6 Bradyrhizobium japonicum USDA 110 1 3 Burkholderia mallei ATCC 23344 2 2 Burkholderia pseudomallei 1710b 3 4 Burkholderia pseudomallei K96243 1 2 Burkholderia sp. 383 1 1 Burkholderia thailandensis E264 3 5 Burkholderia xenovorans LB400 2 2 Chromobacterium violaceum ATCC 12472 1 1 Erwinia carotovora subsp. atroseptica SCRI1043 1 2 Jannaschia sp. CCS1 1 1 Mesorhizobium loti MAFF303099 4 5 Nitrobacter hamburgensis X14 3 3 Nitrobacter winogradskyi Nb-255 1 1 Nitrosospira multiformis ATCC 25196 1 1 Pseudomonas aeruginosa PAO1 2 3 Pseudomonas syringae pv. phaseolicola 1448A 1 2 Pseudomonas syringae pv. syringae B728a 1 3 Pseudomonas syringae pv. tomato DC3000 1 3 Ralstonia solanacearum GMI1000 2 2 Rhizobium etli CFN 42 3 10 Rhodobacter sphaeroides 2.4.1 1 2 Rhodopseudomonas palustris BisB18 2 3 Rhodopseudomonas palustris BisB5 1 2 Rhodopseudomonas palustris CGA009 1 1 Rhodopseudomonas palustris HaA2 1 2

76 Table 2-1 continued

Organism LuxI LuxR

Rhodospirillum rubrum ATCC 11170 1 1 Saccharophagus degradans 2-40 1 1 Silicibacter pomeroyi DSS-3 2 3 Sinorhizobium meliloti 1021 1 5 Sodalis glossinidius subsp. morsitans 1 2 Sphingopyxis alaskensis RB2256 2 3 Vibrio fischeri ES114 1 1 Yersinia pestis KIM 2 2 Yersinia pseudotuberculosis IP 32953 1 2

2.3.3 The use of quorum sensing genes to identify quorum sensing species in the environment

LGT is prevalent in the evolution of the LuxI/R protein families. This prevalence precludes any inference being made of the potential of an organism to sense its quorum through AHL signaling based on its identity. Therefore, undertaking diversity studies (such as clone libraries or fingerprinting methods) or in situ identification (such as FISH) would not have led to the identification of quorum sensing bacteria, as these methods are all based on the use of a conserved housekeeping gene (namely the 16S rRNA gene). The possibility of using the luxI/R genes directly to identify quorum sensing among Delisea pulchra's epiphytic community was extensively pursued without a definitive conclusion being reached (data not shown).

Several studies have used functional genes in combination with DGGE (1, 12, 27, 38, 41) and so attempts were made to design a quorum sensing primer set suitable for DGGE. The luxR gene was found to be unsuitable for identifying quorum sensing species as quorum sensing cheats, which possess a LuxR homologue and no LuxI homologue (therefore not having a complete quorum sensing circuit) exist (7, 25, 40) (Fig. 2-1A). Initially, a 'universal' luxI primer set was designed, but PCR amplification of luxI genes from a variety of species using these primers was unsuccessful. This is

77 most likely due to low primer specificity resulting from a lack of regions displaying enough sequence conservation for the design of efficient primers. When a quorum sensing pathogen was identified for D. pulchra (see Chapter 3), a luxI primer set was designed to target the D1 group (Fig. 2-1B), which includes Ruegeria strain PR1b, a close relative of the known quorum sensing pathogen Ruegeria strain R11 (see Chapter 5). However, these primers were not able to amplify the luxI gene from Ruegeria strain R11 and this aspect of the project was not pursued further. Further attempts were made to identify quorum sensing bacteria belonging to the Roseobacter clade in the environment and are discussed in Chapter Five.

78 2.4 References

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83 3 Delisea pulchra chemically defends itself against the novel intracellular pathogen, Ruegeria strain R11

3.1 Introduction

Marine fouling is the process of sequential colonization of marine organisms on a surface. Fouling can be described by the following four stages: I) surface conditioning by molecules adsorbing to the surface, II) prokaryote attachment and biofilm formation, III) subsequent settlement and attachment of eukaryotic micro-organisms including fungi, protists and finally IV) settlement of macro-organisms including marine animals and seaweeds. The fouling pressure in the marine environment is intense and occurs on non-living surfaces (physical substratum) as well as living surfaces (other marine organisms). Fouling is particularly problematic for seaweeds as it reduces rates of photosynthesis and reproduction due to increased shade and competition for nutrients (61, 72). Consequently, many organisms have evolved strategies to reduce fouling. These strategies include sloughing of surface cells (22, 36, 37), production of mucus (11), fast growth rates (59, 60), abandoning entire blades (43) and production of bioactive compounds that deter fouling organisms (21, 49, 70, 71, 73).

The marine environment is the richest source of bioactive compounds with antibacterial, antifungal and antiviral properties being commonly isolated from marine organisms. Bioactives are produced by both micro- and macro-organisms, including animals, seaweeds, fungi and bacteria, and have been implicated to play an important role in the ecology and evolution of these species (61, 62). Organisms that produce biologically active compounds largely do so through secondary metabolism, which leads to the following question: Are these bioactive compounds just incidental end products of secondary metabolism or do they present a level of chemical defense against competing or disease causing organisms? One of the best-studied examples of bioactive compounds inhibiting fouling of marine organisms is the furanones produced by the red macroalga Delisea pulchra.

D. pulchra chemically defends itself against fouling organisms by producing furanones, which are bioactive secondary metabolites that inhibit settlement of a range of micro- and macro-fouling organisms (21, 49, 73). Furanones are contained within specialized gland cells throughout the thallus (Fig 1-5). These gland cells deliver furanones to the algal surface (23). This specialized structure, along with the fact that furanones have

84 significant biological effects at naturally occurring concentrations (19, 23), suggests that these compounds play a role in chemically defending the alga from fouling and are not incidental toxic end products of secondary metabolism.

The mechanism through which furanones inhibit macro-organisms from colonizing D. pulchra is unknown (20). For micro-organisms, furanones are known to specifically inhibit AHL-driven quorum sensing (Fig. 1-3). They inhibit this process by competitively binding to the quorum sensing response regulator (LuxR-type proteins) (28), forming a furanone-LuxR complex which rapidly undergoes proteolytic degradation, thereby increasing the turnover of the response regulator protein (45, 47). It appears that that furanones specifically inhibit quorum sensing to disrupt the colonization and virulence traits it regulates (see Section 1.4). Furthermore, as furanones inhibit quorum sensing at concentrations that do not affect bacterial growth and survival, microbes with quorum sensing properties should be found among D. pulchra's bacterial epiphytes.

Quorum sensing species belonging to the roseobacter clade have been repeatedly isolated from D. pulchra (17, 34). In addition, rpoB-DGGE performed on the surface associated microflora identified several sequences belonging to the roseobacter clade, including a sequence identical to that of a bacterium previously isolated from the surface of this alga, Ruegeria strain R11 (34). 16S rRNA gene-based clone libraries of the epiphytic community on D. pulchra also identified several sequences belonging to the roseobacter clade (44) including sequences closely related to the gall symbionts from red algae of the genera Prionitis (3, 4). Given that D. pulchra constituently produces furanones, the potential of the roseobacter clade to colonize and infect D. pulchra was not anticipated. While Roseobacter species are known pathogens (1, 2, 14, 15, 26, 33, 53) and some species manifest quorum sensing (16, 29, 63, 69), no Roseobacter species are known to have quorum sensing regulated virulence.

During the austral summer, when ocean temperatures peak near Sydney, D. pulchra can become bleached in its natural environment (Fig. 3-4), an effect which is correlated with a decrease in the total furanone concentration of the thallus when exposed to UV light (Steinberg, P.D. et al., unpublished data) (Fig. 6-1). These observations, as well as repeated isolation from D. pulchra of bacteria that are related to known red algal pathogens (4) and are known to produce AHLs (17), suggest that bleaching in this alga may be due to interactions between bacterial infection, elevated summer temperatures and furanone levels. An AHL producing member of the roseobacter clade, Ruegeria strain R11, previously isolated from the surface of D. pulchra and identified as

85 producing the quorum sensing molecules AHLs (17), was chosen as a model organism to test this hypothesis.

While bacterial induced bleaching has not been previously described in red algae, the bacterial pathogen Vibrio shiloi is known to cause bleaching in the coral Oculina patagonica (39). Several Vibrio species have since been implicated as coral pathogens (13, 64). V. shiloi uses chemotaxis to direct itself towards coral mucus. It binds to a beta-galactoside-containing receptor in the mucus (66) produced by the coral endosymbiotic algae, zooxanthellae. V. shiloi actually targets these zooxanthellae and not the coral, as bleaching results from the loss of zooxanthellae. Consequently V. shiloi is unable to infect O. patagonica living in dark caves as they lack zooxanthellae (azooxanthellae) (6). Once attached to the algae, V. shiloi becomes intracellular and secretes superoxide dismutase, which protects it from the high concentrations of oxygen produced by intracellular zooxanthellae photosynthesis (9). Both attachment and expression of several virulence factors are temperature regulated in V. shiloi, being expressed at summer temperatures (9, 66). This is supported by the correlation between increasing incidence of coral bleaching and rising ocean temperatures resulting from global warming (58). Because of the important role of temperature in mediating V. shiloi's bleaching of O. patagonica, and the observation of bleaching in D. pulchra during the austral summer, a second objective of the present study was to determine if Ruegeria strain R11 bleaching of D. pulchra is temperature dependent.

86 3.2 Methods

3.2.1 Bacterial strains and media

Ruegeria strain R11 was previously isolated from the tip of Delisea pulchra (34). Ruegeria strain R11 was routinely grown at 25°C in Bacto Marine Broth 2216 (Difco Laboratories). Media was supplemented with 1.5% agar (Research Organics) for plating. VNSS media was used in flow cell experiments so that the concentration of individual components could be varied. One litre of VNSS consists of 1 g peptone, 0.5 g glucose, 0.5 g yeast extract and 0.01 g FeSO4.H2O, in Nine Salt Solution (NSS) which comprises 17.6 g NaCl, 1.47 g Na2SO4, 0.8 g NaHCO3, 0.04 g KCl, 0.04 g KBr,

1.87 g MgCl2.6H2O, 0.41 g CaCl2.2H2O, 0.008 g SrCl2.6H2O and 0.008 g H3BO3 per litre.

Artificial seawater was used as culture media to grow D. pulchra from tetraspores. Ten litres of artificial media contained of 240 g NaCl, 0.1144 g H3BO3, 4.7211 g CaCl2.2H2O,

1 g c3H7Na2O6P.H2O, 0.3001 g EDTA, 39.13 g MgSO4, 0.0433 g MgCl2.6H2O, 7 g KCl,

0.3005 g Na2O3Si.9H2O, 0.0126 g Na2MoO4.2H2O, 3 g NaNO3, 10 g Tris base, 0.0105 g ZnCl2, 0.0581 g FeCl3, 810 ȝl of a 500 ȝg/ml CoCl2.6H2O stock solution, 860 ȝl of a

500 ȝg/ml CuCl2 stock solution. Artificial seawater was then divided into 5 L of Br+ seawater (0.4185 g NaBr added) and 5 L of Br- seawater (0.2377 g NaCl added). Salinity and pH have then adjusted to that of seawater at Bare Island (sampling site), then sterile filtered (0.2 ȝm) and autoclaved.

3.2.2 Furanone minimal inhibitory concentration (MIC)

The MIC of furanone compounds 2 and 3 (two of the four furanones that comprise 95% of furanones extracted from the surface (23)) (Appendix 1) were determined for Ruegeria strain R11, following the NCCLS-recommended micro-dilution (100 ȝl total volume) method with Muller Hinton Broth being replaced by Marine Broth 2216. Furanones 2 and 3 were added from ethanol stocks to reach desired concentrations. Concentrations tested for both furanones were 0.5, 1, 2, 4, 8, 16, 32 and 64 μg/ml.

3.2.3 Flow cell experiments

Biofilms were grown in flow cells (channel dimensions 1 X 4 X 40 mm) at room temperature as previously described (50). Overnight cultures of Ruegeria strain R11 were grown at room temperature in 5 ml of VNSS media at 160 rpm. Cells were pelleted, washed and resuspended in amended VNSS (VNSS with 0.1 g peptone, 0.05

87 g glucose, 0.05 g yeast extract and 0.01 g FeSO4.H2O), Channels were inoculated with 1 ml of resuspended cells for 2 h. A continuous culture system was then established with amended VNSS at a flow rate of 150 ȝl/min.

Biofilms were set up in parallel with and without furanones 2 and 3. Furanones were added from ethanol stocks to a concentration of 16 ȝg/ml (as this was half the MIC of furanone 2 and less than half the MIC of furanone 3) in the amended VNSS. An equal volume of ethanol was added to the media for the control biofilm.

3.2.4 Microscopy of flow cells

The biofilms were fixed by injecting 400 μl of 2% glutaraldehyde in VNSS into the flow cell channel for 20 min. Cells were then stained with 400 ȝl of 0.2% acridine orange for 20 min before visualization of the biofilms with confocal laser microscopy (CLSM), using an Olympus LSM-GB200 BH2 (Olympus). Ten fields of view were taken for each flow cell.

3.2.5 Delisea pulchra sampling

Fertile D. pulchra was collected from a depth of 3 m near Bare Island, Botany Bay, New South Wales, Australia (33 59'38" S, 151 16'00" E) on the 21.06.2005. Plants were suspended in seawater and transported directly to the laboratory.

3.2.6 Growing Br+/- D. pulchra

To experimentally assess whether Ruegeria strain R11 can colonize and infect D. pulchra in the absence of furanones, D. pulchra plants without furanones need to be grown so that furanones do not inhibit colonization and virulence in vivo. Furanone free plants can only be obtained by growing plants from tetraspores in the absence of bromine (23). As furanones are brominated compounds, removing bromine from the media means that they cannot be synthesized. Fertile plants have only been successfully sporolated during the winter and take three months to grow to a size of ~0.5 cm.

D. pulchra plants were washed with 1% iodine aqueous solution to remove diatoms, rinsed three times in sterile seawater and then placed in aerated beakers of autoclaved seawater at 20°C for 2 d under cycled light (8 h light 16 h dark) to induce sporulation. Spores production started after 24 hr and then settled and attached to glass microscope cover slips at the bottom of the beakers. These were then removed to sterile specimen jars with 25 ml of sterile artificial seawater made with, and without,

88 sodium bromide. Plants were grown and maintained at 20°C under cycled light (8 h light 16 h dark) with gentle shaking (30 rpm) for aeration. Artificial seawater in the specimen jars was changed weekly, with sterile artificial seawater with, and without, sodium bromide (Br+/-) consistently used for all treatments for furanone (Br+) and furanone free (Br-) plants. Plants were grown for a minimum of three months up to a maximum of four months prior to experimentation (~0.5 cm long).

Before performing experiments, epiphytic bacteria were removed from the plant surface by exposing the plants to antibiotics for 24 h. Penicillin G (10 ȝg/ml), streptomycin (10 ȝg/ml) and kanamycin (20 ȝg/ml) were added to the seawater. Plants were then rinsed in artificial seawater (Br+/-) and checked microscopically using the light microscope Olympus BX5OF-3 (Olympus) to ensure the absence of surface biofilms (five fields of view taken for each plant).

3.2.7 Colonization experiments

To determine at which concentration Ruegeria strain R11 could colonize D. pulchra, and what role furanones play in deterring colonization, Br+/- D. pulchra was inoculated with Ruegeria strain R11 in a concentration series (102, 103, 104, 105, 106, 107 and 108 cells/ml).

Ruegeria strain R11 was grown at 25 °C, 160 rpm for 16 h (previously determined to be stationary phase for Ruegeria strain R11 and at approximately 109 cells/ml). Cells were harvested by centrifugation at 5000 rpm for 5 min at 4 °C and subsequently washed in Br+/- artificial seawater (depending on which plant they were being inoculated onto) to remove extracellular material, and bromine from cells inoculated onto Br- D. pulchra. After this wash, cells were pelleted and re-suspended in Br+/- artificial seawater to the appropriate cell concentration. Cell concentrations for all treatments were checked by drop plate counts on Bacto Marine Broth 2216 plates.

Each cell concentration of Ruegeria strain R11 was inoculated in microtitre plate wells containing Br+/- D. pulchra in Br+/- artificial seawater (no cells were added to control Br+/- D. pulchra). Triplicates of each control and each Ruegeria strain R11 cell concentration were included. Plants were grown and maintained at 20°C under cycled light (8 h light 16 h dark) with gentle shaking (30 rpm) for aeration. The water was not changed for these plants during the experiment and plants were observed microscopically using the light microscope Olympus BX5OF-3 (Olympus) daily over a two week period (five fields of view). The entire experiment was repeated two twice.

89 3.2.8 Infection experiments

Ruegeria strain R11 was grown, harvested and washed as described above (Section 3.2.6). Triplicate plants were placed in 2 ml of artificial seawater and inoculated with 106 cells/ml of Ruegeria strain R11. Uninoculated Br+/- plants were used as the control and microscopically inspected for surface biofilm and intracellular bacteria (see Section 3.2.9). This experiment was performed in parallel at 20°C and 25°C in triplicate (coastal mean monthly sea surface temperatures in central NSW [e.g. Wollongong to Newcastle] range between 17.7°C (min) – 24.6°C (max) (www.metoc.gov.au/ products/data/aussst.html)). The entire experiment was repeated three times.

3.2.9 Microscopy of D. pulchra

Plants were observed daily until the infected plants died (5 d). They were observed for signs of colonization and infection by Ruegeria strain R11 using the light microscope Olympus BX5OF-3 (Olympus). Ten fields of view were taken, each day for each plant. A microscopic Sony digital camera was used to capture images and video footage using Ultravision software.

3.2.10 Re-isolation and identification of Ruegeria strain R11

To confirm that Ruegeria strain R11 was the infectious agent on Br- D. pulchra, bacteria were re-isolated from three Br- D. pulchra algae which had been incubated with R11 (106 cells/ml) at 25 °C for 2 days. The sampled algae were first placed in Br+/- artificial seawater, supplemented with Penicillin G (10 ȝg/ml), streptomycin (10 ȝg/ml) and kanamycin (20 ȝg/ml) for 2 hr, to remove extracellular bacteria associated with the algae. This antibiotic treatment had previously been shown to remove epiphytic bacteria from D. pulchra (Longford, S, personal communication). The algae were rinsed with Br- artificial seawater, macerated and spread on separate Marine Broth 2216 plates. Four colonies were purified from each of three algae for identification.

3.2.10.1 DNA extraction

The 12 strains isolated from the infected Br- D. pulchra were identified by 16S rRNA gene sequencing. DNA was extracted as described by Peterson et al. (52), from 1.5 ml of overnight cultures from the 12 isolates grown at 25 °C in Bacto Marine Broth 2216.

3.2.10.2 PCR of the 16S rRNA gene

An approximately 1450bp fragment of the 16S rRNA gene was amplified by PCR using the 27F (AGAGTTTGATCMTGGCTCAG) and 1492R (ACGGTTACCTTGTTACG ACTT) primers for the 12 re-isolated strains. Where no DNA was amplified, the

90 alternate forward primer 327F (ACCGCTTGTGCGGGCCC) was used. The PCR reaction contained 1 ȝl DNA, 2 ȝl REDTaq buffer (Sigma), 2.5mM of each deoxynucleoside triphospate, 10 pmol of the forward and reverse primers, 0.5 ȝl of bovine serum albumin, 0.5 ȝl of REDTaq (Sigma) and sterile filtered Milli-Q water to a volume of 20 ȝl. The PCR conditions used were an initial cycle at 94°C for 5 min, followed by 25 cycles at 94°C for 30 s, 50°C for 90 s and 72°C for 90 s and a final extension cycle of 10 min at 72°C. A hot start PCR was done with Taq polymerase added after 4min of the initial denaturing cycle. PCR products were checked on a 1% agarose gel stained with 1 μg/ml ethidium bromide and then purified using the QIAquick PCR purification kit (Qiagen).

3.2.10.3 Sequencing the 16S rRNA gene

PCR products were sequenced using Big Dye Terminator RR Mix (PE Applied Biosystems) with both the forward (27F or 327F) and reverse (1492R) primers. The sequencing reaction consisted of 100 ng of purified PCR product placed in a 20 μl reaction volume with 4 μl of Big Dye Terminator RR Mix (PE Applied Biosystems), 4 μl of 2.5X CSA buffer, sterile filtered Milli-Q-water and 2.5 pmol of the primer (27F, 327F or 1492R). The sequencing reaction involved an initial single cycle of 94°C for 60 s, then 60 cycles at 96°C for 10 s, 55°C for 5 s and 60°C for 4 min. Sequencing products were precipitated with 64 μl 96% ethanol and 20 μl of sterile filtered Milli-Q-water at room temperature for 2 h, pelleted by centrifugation at 14000 rpm for 30 min at 4 °C and washed with 70% ethanol. Samples were analyzed at the DNA Sequencing Facility, UNSW.

3.2.10.4 Sequence analysis

16S rRNA gene sequences from the reverse and forward primers were aligned to create full length sequences. These sequences were used as queries in a BLASTN search of GenBank to make tentative identifications of the isolates. All sequences were then aligned with the Ruegeria strain R11 16S rRNA gene and the ROS537 probe using ClustalW (65) to see if any isolates other that R11 could be detected by the ROS537 probe (25).

3.2.11 Catalyzed reporter deposition - fluorescence in situ hybridization (CARD-FISH)

Two Br- plants inoculated with Ruegeria strain R11 at 25°C for 2 d were prepared for CARD-FISH to confirm the identify and localization of bacteria infecting Br- plants. CARD-FISH was used because the auto-florescence of seaweeds is greater than the

91 signal of FISH probes (67). The CARD-FISH protocol for algae (67) was conducted on fixed algal pieces using the ROS537 probe, which targets the marine alpha proteobacterial cluster, which includes most of the roseobacter clade (25). The hybridization conditions have been optimized for the ROS537 such that 16S RNA with >1 bp mismatch with the probe will not be detected (25). In brief, samples were fixed in 2% paraformaldhyde and cells permeabilized in lysozyme solution for 60 min at 37 °C. Samples were not sectioned as they were small enough to be hybridized and viewed directly. Hybridizations were performed at 46 °C for 90 min rotating at 16 rpm, using horseradish peroxidase probes (HRP) (Thermo Electron, Germany). Alexa546-labelled tyramide (Molecular Probes) was utilized as the reporter molecule and SYBR Green II (Molecular Probes) as a counter stain.

3.2.12 Microscopy of Br- D. pulchra stained by CARD-FISH

Samples were visualized by confocal scanning laser microscopy (CSLM) using an Olympus LSM-GB200 BH2 (Olympus). Microcolonies were located on Br- D. pulchra and ten fields of view that were cross-sections of microcolonies and the adjacent plant tissue were taken to identify intracellular bacteria stained by CARD-FISH.

92 3.3 Results

Ruegeria strain R11 biofilm formation in a flow cell occurred in a reproducible pattern of growth and differentiation. Cells initially attached to the glass surface of the flow cell either perpendicularly or horizontally to the surface. They then grew and differentiated in elongated cell chains and rod shaped cells aggregating to the cell chains to form loosely packed microcolonies (Fig. 3-1).

The MIC of furanone 2 and 3 for Ruegeria strain R11 was 32 μg/ml and >64 μg/ml, respectively (64 μg/ml was the maximum tested concentration). Consequently, biofilm experiments were done at half the MIC of furanone 2 (16 μg/ml) as it had been previously shown that furanones inhibit quorum sensing regulated phenotypes at non- growth inhibiting concentrations (31, 46, 48, 56). Ruegeria strain R11 did not develop biofilms in the presence of furanone 2 or 3 and the flow cells were clear of attached cells. When furanones 2 and 3 were added to the amended VNSS media for this experiment, the media developed an orange and pink color respectively, indicating that the furanones reacted with a media component. To test if furanones were reacting with a media component, furanone 2 was extracted from VNSS immediately after being added to the media. It was shown to be structurally modified due to addition to VNSS, by GC-MS (data not shown). Consequently, the influence of furanones on biofilm formation was further investigated in vivo using plants with and without furanones.

D. pulchra was cultured from tetraspores for three months in artificial seawater with (Br+) and without (Br-) bromine. Furanones are brominated, and removing bromine from the growth media prevents their production; thalli grown in these conditions are otherwise normal (23) as bromine is not essential for the growth of red algae (27). Furanones are contained in the vesicle of gland cells (Fig. 3-2B,D) which are atrophied in Br- (furanone free) plants (Fig. 3-2A,C) (23).

The effective inoculum concentration of Ruegeria strain R11 was also determined using a concentration series (102–108 cells/ml). Ruegeria strain R11 colonized Br- D. pulchra at all concentrations, with only 102 cells/ml not showing biofilm structures at 24 hr, although at 48 hr biofilm formation comparable to all other inoculates were established. A higher inoculum concentration (106 cells/ml) was used for all subsequent experiments to ensure that Ruegeria strain R11 established the majority of the epiphytic community of Br- plants. Comparatively, Vibrio shiloi can infect Oculina

93 A B

C D

Figure 3-1: Biofilm formation by Ruegeria strain R11. Rod shaped cells attach to the flow cell after 2 hr both perpendicularly and horizontally to the glass surface of the flow cell (A). At 48 hr a mature biofilm has developed with both microcolony and channel structures (B). Microcolonies are atypical as compared to the commonly observed mushroom like structure as cells are loosely packed inside microcolonies (C). Microcolonies are composed of two differentiated cells types, elongated cells forming cell chains and short rod cells that aggregate to these cell chains (D). Aerial cell chains form loosely structured microcolonies with an hollow center (E) 6FDOHEDU ȝP ȝPȝPDQGȝPUHVSHFWLYHO\ A B

e e C C

C D

C b C e e

Figure 3-2: Three months old Delisea pulchra grown in artificial seawater without bromine (Br-) at 20°C (A), with bromine (Br+) at 20°C (B), Br- at 25°C (C) and Br+ at 25°C (D). All plants were treated with an antibiotic wash and rinsed before being 6 inoculated with Ruegeria strain R11 (10 cells/ml) for two days. Plants were then examined under the light microscope. Fig. 3-2A-D are typical of three experiments each done with triplicate plants. Control plants not inoculated with Ruegeria strain R11 were used for all treatments and did not have a surface biofilm or intracellular bacteria. The surface biofilm (b), cortex (c), epidermal layer (e) and furanone containing vesicle (v) inside gland cells are shown in Br+ and Br- plants (the vesicles are atrophied in Br- SODQWV ,QWUDFHOOXODUEDFWHULDDUHGHQRWHGE\WKHDUURZLQ & 6FDOHEDU ȝP b

Figure 3-3: Intracellular bacteria visualized using CARD-FISH on three months old Delisea pulchra grown in artificial seawater without bromine (Br-). D. pulchra was treated with an antibiotic wash and rinsed before being inoculated with Ruegeria strain R11 (106 cells/ml) for two days at 25°C. The ROS537 probe was used with CARD-FISH to show bacteria belonging to the roseobacter clade (red) and counter stained with SYBR green (green) making cells appear yellow. Surface biofilm (b) is shown on the plant. The microcolony appears to have penetrated the epidermis into the cortical (c) OD\HU,QWUDFHOOXODUEDFWHULDLQDFRUWLFDOFHOODUHGHQRWHGE\WKHDUURZ 6FDOHEDU ȝP patagonica with an inoculum of 120 cells/ml, however 106 cells/ml is usually employed in aquaria experiments.

The ability of Ruegeria strain R11 to colonize and infect Br+ versus Br- plants differed markedly after two days (Fig.3-2A-D), and this effect was temperature dependent. A thick biofilm with microcolonies was present on all Br- plants after two days (Fig.3-2A, C). At 25°C, bacteria penetrated the epidermis and invaded the interior of Br- plants (Fig.3-2C). Algal cells surrounding the invasive bacteria lost pigmentation and contained motile intracellular bacteria. D. pulchra bleaching followed the infection, with the whole thallus bleached in five days. No biofilm was observed on Br+ plants (Fig.3- 2B, D) or uninoculated control plants.

Ruegeria strain R11 is capable of infecting Br- D. pulchra at 25 °C by penetrating the epidermal layer and becoming intracellular. Plants became infected after two days and intracellular bacteria were only observed directly adjacent to microcolonies. Careful microscopy revealed that the epidermal layer was broken below larger microcolonies and that these microcolonies penetrated the epidermal layer into the cortex in what appeared like an infection thread (Fig. 3-2C, Fig. 3-3). Plant cells surrounding the infection thread contained motile intracellular bacteria. The number of intracellular bacteria increased from 2-6 bacteria after two days, to being packed with swarming cells at day five (host cells appeared to have lost their integrity). The progression of bleaching followed the infection from day 2 to day 5, when all plants had died.

To confirm Ruegeria strain R11 infection of Br- thalli, colonies were reisolated from three individual D. pulchra plants that had been inoculated with Ruegeria strain R11 and incubated for 2 days. The 16S rRNA genes of four colonies from each of three plants were sequenced. Three of the twelve isolates were identified as Ruegeria strain R11 as the16 rRNA genes of these isolates were identical to an homologue from a pure culture of this organism. The relatively low recovery of R11 (25% of isolates) is thought to result from the re-isolation being performed on older Br- plants whose surface biofilm was not completely removed by the antibiotic treatment. Using these Br- plants to repeat the initial experiment was unavoidable due to the difficulty in culturing D. pulchra from tetraspores. However, Ruegeria strain R11 was isolated from each of the three plants (i.e. one isolate from each plant).

To further confirm that Ruegeria strain R11 was the intracellular bacteria in Br- thalli CARD-FISH was employed (67) using the ROS537 (25) probe for the roseobacter

97 clade. Intracellular bacteria were visualized intracellularly in a cortical cell adjacent to a microcolony that had penetrated the epidermis in an infection thread like structure (Fig. 3-3). Such infection is identical to that identified using light microscopy (Fig. 3-1C). These bacteria are likely to be Ruegeria strain R11 as all the other isolates (Alteromonas, Halomonas and Rhodospillaceae) from the plants have >1 bp mismatch with the ROS537 probe. These other isolates are thought to be to be culturable ‘weeds’ as they all readily formed colonies (within 24 hrs) compared with Ruegeria strain R11 that takes 2-3 days to form colonies. Additionally, no cells stained green (cells not stained with the ROS 537 probe) were identified in the biofilm or intracellularly, with all cells staining yellow (the combination of SYBR green and the ROS537 CARD-FISH probe) confirming that the surface biofilm and intracellular bacteria are roseobacter cells (Fig. 3-3).

98 3.4 Discussion

3.4.1 Furanone inhibition of biofilm formation in Ruegeria strain R11

Biofilm formation in Ruegeria strain R11 follows a reproducible programmed developmental pattern including attachment, cell chain formation, aggregation and microcolony formation. Biofilm development including cell chain formation and aggregation has also been described for the quorum sensing species Serratia liquefaciens MG1 (41). Quorum sensing is essential for the development of these complex structures in S. liquefaciens MG1's biofilm (41), and furanone inhibition of biofilm formation in Ruegeria strain R11 (Fig. 3-2) could be through quorum sensing antagonism. However, as furanones 2 and 3 react with a media component, furanone inhibition of attachment and/or biofilm formation could not be determined in vitro.

Ruegeria strain R11 colonized Br- Delisea pulchra plants forming a biofilm at both 20 and 25 °C. The biofilm formed on Br- D. pulchra showed a different morphology to that formed on the glass surface of the flow cell. On Br– D. pulchra, Ruegeria strain R11 formed compact microcolonies with uniform short rod shaped cells (Fig. 3-2 & 3-3) compared with the loose microcolonies characterized by cell chains and aggregates in the flow cell (Fig. 3-1). This difference in biofilm morphology has been described in other bacteria in response to variable environmental parameters and could be due to the different nutrient or surface conditions of the plant and in the flow cell experiments (18, 57).

Ruegeria strain R11 was capable of effectively colonizing Br- D. pulchra plants from a very small inoculum (100 cells/ml), much lower than has been shown for other algal epiphytic bacteria (106 cells/ml for Pseudoaltermonas tunicata attachment to Ulva australis) (55). However, this inoculum size is comparable to what is required for an effective inoculation of the coral pathogen V. shiloi on O. patagonica (120 cells/ml) (40). The ability of V. shiloi to infect O. patagonica at such a low inoculum is facilitated by the adhesion of V. shiloi to a beta-galactoside-containing receptor in the coral mucus (66). Actually, this receptor is produced by the zooxanthellae algae, the target for V. shiloi (6). Specific adhesion factors could exist also for the colonization by Ruegeria strain R11 on D. pulchra. Attachment assays were attempted as described by Toren et al. (66), but the presence of other bacterial epiphytes made counts problematic. Ruegeria strain R11 has since been GFP labeled (data not shown) so that bacterial counts can be done directly on the plant to ascertain if it attaches to both Br+/- D. pulchra.

99 3.4.2 Furanone inhibition of virulence in Ruegeria strain R11

This chapter reports the first evidence that increased temperature enhances virulence in a seaweed pathogen. Ruegeria strain R11 was able to colonize Br- D. pulchra at 20 °C, forming a surface biofilm (Fig. 3-2A). At 25 °C this biofilm was able to penetrate the epidermal layer in an infection thread like structure and became intracellular in adjacent cortical cells (Fig. 3-2C, Fig. 3-3). Furanones appear to inhibit colonization and infection by Ruegeria strain R11 of D. pulchra, as Br+ D. pulchra did not develop a surface biofilm or bleach at 20 or 25 °C (Fig. 3-2).

In the experimental system described here, furanones are likely to indirectly inhibit the infection by Ruegeria strain R11 by preventing biofilm formation, suggesting that infection cannot occur without biofilm formation. This model is supported by the finding that infection is localized to microcolonies (Fig. 3-2C). The results presented in this study suggest that virulence is temperature regulated in Ruegeria strain R11. Comparable colonization of the plants was observed at 20 and 25 °C, but successful infection only occurred at 25 °C. It demonstrates that elevated temperature is required for the infection of D. pulchra by Ruegeria strain R11. In V. shiloi, several virulence factors have been shown to be temperature regulated, including Toxin P that inhibits zooxanthellae photosynthesis (8), superoxide dismutase which protects V. shiloi from the high oxygen concentration found inside the zooxanthellae (9), proteases with an unknown role (10) and an unknown substance that causes zooxanthellae bleaching and lysis (12). Such temperature as well as quorum sensing regulated phenotypes in Ruegeria strain R11 need to be elucidated to fully understand the infection and bleaching processes in D. pulchra.

Several phenotypes that can be quorum sensing regulated have been identified in Ruegeria strain R11. This bacterium produces extracellular polysaccharide (EPS) (17) that can play an important role in terrestrial plant infection (54, 68). Also, swarming was observed inside infected plant cells five days after inoculation (data not shown). Attempts to produce swarming of Ruegeria strain R11 in vitro, using various nutrients and agar conditions, have all failed (17). As swarming is commonly quorum sensing regulated (5, 24, 38), the dynamics of this phenotype need to be further investigated.

3.4.3 Koch's postulates

Koch's postulates were applied to demonstrate that Ruegeria strain R11 is the causative agent of bleaching in Delisea pulchra. The first postulate, that a bacterium is always associated with the disease, is difficult to demonstrate as D. pulchra always

100 produces furanones in its natural environment. Bleached specimens of D. pulchra are rare and only found in late summer (Fig. 3-4). Attempts are currently being made to identify intracellular Ruegeria strain R11 using CARD-FISH on field collected plants. Notably the bleaching extends from a point midway along the thallus, rather than from the tip downward as would be observed with UV induced bleaching. The apparent infection midway along the thallus may be related to the declining furanone concentration along the thallus from tip to base (49).

Ruegeria strain R11 was isolated from healthy D. pulchra (34) and grows as a pure culture. It was identified as belonging to the roseobacter clade with its nearest relative Ruegeria strain PR1b, identified through phylogenetic analysis of their 16S rRNA and rpoB genes (see Chapter 5).

By manipulating furanone production in D. pulchra, it was found in controlled aquaculture experiments that Ruegeria strain R11 infects furanone free D. pulchra at 25 °C. Ruegeria strain R11 becomes intracellular in D. pulchra and produces bleaching and cell lysis with plants dying within five days. The bacterial induction of bleaching is further supported by observations that a few Br- D. puclhra plants treated with the antibiotic wash recovered pigmentation.

Ruegeria strain R11 was re-isolated from diseased Br- D. pulchra, but with low recovery efficiency. This could result from the presence of other epiphytic bacteria insensitive to the antibiotic wash. However, another possibility is that Ruegeria strain R11 enters into a viable but not culturable (VBNC) state on becoming intracellular. Such a phenomenon is seen in the coral pathogen V. shiloi (7, 35). Further confirmation of the association of Ruegeria strain R11 with disease in D. pulchra was obtained using CARD-FISH. Intracellular bacteria could be clearly visualized with this technique, confirming that a bacterium belonging to the roseobacter clade (likely Ruegeria strain R11 as it was inoculated at 106 cells/ml) is an intracellular pathogen of D. pulchra.

101 Figure 3-4: Bleached Delisea pulchra collected from Bare Island, Sydney, Australia, in the late astral summer, February 2006. 3.4.4 The importance of disease and global warming in marine ecology

Disease has emerged as a major factor for the ecology and management of natural marine communities (30, 42). The impact of disease in marine ecosystems has been linked to environmental changes such as global warming. On temperate reefs, seaweeds are typically the major habitat formers and therefore an understanding of the role of disease in this environment is essential for its management.

A strong link has been made between global warming and coral bleaching (30, 42), with predicted rising ocean temperatures resulting in <5% of coral reefs surviving until 2050 (32). Here, it is demonstrated that temperature also strongly affects bleaching in a temperate seaweed by the enhancement of bacterial virulence. The seasonal trend in roseobacter abundance, with populations highest in summer and lowest in winter (25, 51) suggest that these bacteria may pose a greater threat in the summer months. Thus, the impact of temperature-regulated virulence in bacterial pathogens on coral reefs should be a cause of concern for temperate reefs. Notably, several roseobacters have been implicated as marine pathogens, and if temperature regulated virulence is as widespread amongst roseobacters as it is being found to be among the Vibrios, then rising ocean temperatures stand to impact a wide diversity of marine organisms including micro- and macro-algae, corals and oysters (1, 2, 14, 15, 26, 33, 53).

This study has also shown for the first time, the complex interactions between temperature, virulence and chemical defense. The chemical defenses mediated by furanones and slowing the rise of ocean temperatures are currently the only known means to limit the impact of temperature-regulated virulence in the red algae D. pulchra.

Acknowledgments

I acknowledge that CARD-FISH data presented in this chapter was done in collaboration with Niina Tujula.

103 3.5 References

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110 4 Comparing the 16S rRNA and rpoB genes as molecular markers for microbial ecology

4.1 Introduction

Molecular microbial ecology commenced in 1990 with the direct amplification and sequencing of 16S rRNA genes from the environment (16). This procedure revolutionized microbial ecology and permanently changed the way we study prokaryotes in the environment. The adoption of molecular tools by microbial ecologists has rapidly enhanced our knowledge of prokaryote abundance, diversity and function. Certain molecular tools are now commonly used, including clone libraries, fluorescent in situ hybridization (FISH) and fingerprinting methods such as denaturing gradient gel electrophoresis (DGGE) and terminal restriction fragment length polymorphisms (T- RFLP). Each of these methods measures a different aspect of the community (diversity, in situ detection and community dynamics respectively), but all of them generally utilize a single gene to differentiate operational taxonomic units (OTUs), the 16S rRNA gene.

Pauling and Zuckerkandl (43) first proposed to use gene sequences as a molecular clock to decipher phylogenetic relationships. Woese (41, 42) introduced the use of ribosomal RNA genes for this purpose, which served as the basis for his definition of the three domains of life. The notion that ribosomal RNA genes could identify an organism by reconstructing its phylogeny, along with the possibility to store sequences in databases, resulted in the rapid adoption of the 16S rRNA gene by microbiologists. This gene has now established itself as the ‘gold standard’ not only in bacterial phylogeny, but also in microbial ecology studies.

However, none of the 16S rRNA based molecular methods allows for an accurate representation of microbial communities. While bias is introduced into molecular community analysis by many mechanical factors, such as sample handling, fixation, DNA extraction and the polymerase chain reaction (PCR) (8, 11, 12, 14, 27, 40), it is also created by the existence of multiple heterogeneous copies of the 16S rRNA gene within a genome.

The implications of using a gene displaying intragenomic heterogeneity for fingerprinting methods used in molecular community analysis were first described by Dahllöf et al. (10). These authors demonstrated that single species could produce

111 complex banding patterns with DGGE, similar to those reported for whole communities. Subsequently Crosby et al. (9) used an artificial community of bacteria for which the whole genome has been completely sequenced, to determine the factors causing both over- and under- estimates of diversity with various fingerprinting methods.

Most researchers currently adopt an OTU definition based on 16S rRNA sequence identity, usually considering organisms displaying 97-98% identity in this gene to be part of the same OTU (15). However, recent evidence suggests that, even when taking into account intragenomic heterogenity, clusters of sequences with 99% sequence identity reveal extensive ribotype microdiversity, which potentially underlies important ecological differentiation (2). For example, in a natural Vibrio splendidus population, even single ribotypes (unique 16 rRNA gene sequences) present important genotypic variations (36). The case for a greater diversity than can be detected using current 16 rRNA-based molecular community analysis techniques is also supported by multi-locus sequence analysis (MLSA) studies, which involve the sequencing of a number of genes coding for proteins with housekeeping functions to assess diversity in collections of isolates (22, 34). Such studies have identified organisms with identical 16S rRNA gene sequences that have significant sequence divergence in protein-coding genes. Although the 16S rRNA gene is by far the most frequently used, methods in molecular microbial ecology are not limited to this gene. Alternate 'core' housekeeping genes such as the RNA polymerase ß subunit (rpoB) have been used with DGGE (7, 10, 24, 30, 31).

The use of a single copy gene for community analysis is an important milestone in microbial ecology as it could allow for the accurate measurement of diversity and phylogenetic relationships, avoiding a loss in phylogenetic resolution and biases in diversity measurements due to the presence of intragenomic heterogeneity. However, the criteria for which the 16S rRNA gene was originally selected must be established for alternative markers. In this study, a comparison between the 16S rRNA and rpoB genes is performed in order to evaluate the use of an alternate gene as a marker for molecular microbial ecology.

This study addresses four issues. First, an exploration of whether intragenomic heterogeneity is localized in specific regions of the 16S rRNA gene. Secondly, to compare how well the 16S rRNA and rpoB genes and their fragments used for DGGE reconstruct bacterial phylogenies. Thirdly, to determine the influence of 16S rRNA gene intragenomic heterogeneity on bacterial phylogeny at the subspecies level. And finally,

112 whether the rpoB gene fulfills the criteria required for a molecular marker in microbial ecology is addressed.

113 4.2 Materials and Methods

4.2.1 Sequence retrieval and alignment rpoB and 16S rRNA gene DNA sequences were retrieved from 111 completely sequenced bacterial genomes Appendix 2). DNA sequences of the rpoB gene were translated to create an amino acid sequence dataset. For each taxonomic group analyzed, amino acid alignments (RpoB protein) and DNA alignments (rpoB and 16S rRNA genes) were constructed using CLUSTALW (35) and edited manually to remove ambiguous positions. The 16S rRNA gene alignment was edited to begin and end at the universal primer sites, 27F and 1492R, which are most commonly used for clone library construction. Taxonomic groups for which alignments were compiled cover multiple taxonomic levels: Domain (Bacteria), Phylum (Actinobacteria, Firmicutes, Proteobacteria), Order (Bacillales, Enterobacteriales, Lactobacillales), Class (Alphaproteobacteria, Gammaproteobacteria), Family (Chlamydiaceae, Mycoplasmataceae), Genus (Streptococcus) and Species / Subspecies (Escherichia coli / Shigella flexneri).

4.2.2 Recoding of alignment positions displaying intragenomic heterogeneity

Multiple copies of the 16S rRNA gene present in a single organism were condensed to a single consensus sequence. When heterogeneity was present between multiple copies found in a given genome, the specific positions at which this heterogeneity occurred were recoded to denote the multiple character states observed for that position. The following code, which is recognized by the PAUP* program (33) used to compile phylogenetic trees, was used for the recoding: R=AG, Y=CT, M=AC, K=GT, W=AT, S=CG, B=CGT, D=AGT, H=ACT, V=ACG, N=ACGT.

4.2.3 Mutational saturation analysis

The first and third positions within codons, being synonymous for many amino acids, display mutational rates higher than the second position. If the sequences compared are sufficiently distant, multiple consecutive nucleotide substitutions at the same position can occur after differentiation, making the position non-informative and/or misleading with regards to phylogenetic analyses. We therefore tested whether the rpoB datasets used for phylogenetic analysis were affected by mutational saturation. Saturation analyses were done for each codon position of the rpoB gene using comp_mat from MUST version 3.0 (26). The proportion of pairwise observed

114 differences between rpoB sequences was calculated with an uncorrected NJ (Neighbor-Joining) method using MUST 3.0 and was plotted against the proportion of inferred substitutions estimated by maximum parsimony using PAUP* 4.0b10 (33). If no linear fit could be found between observed and inferred nucleotide substitutions, the codon position tested was considered to present some degree of mutational saturation.

4.2.4 Phylogenetic analyses

Phylogenetic analyses were performed at the DNA level for the 16S rRNA gene datasets and some of the rpoB datasets. For the rpoB gene, third codon positions that did not display mutational saturation were included in the analyses. The trees were constructed with PAUP* 4.04b, applying the heuristic-search option and using the TBR branch-swapping algorithm. Maximum likelihood was used as the tree reconstruction method, with the nucleotide substitution model (GTR), among-sites rate variation parameter D (G), proportion of invariable sites (I) and nucleotide frequencies determined using MODELTEST (28). The confidence of each node was determined by building a consensus tree of 100 maximum likelihood trees from bootstrap pseudo- replicates of the original dataset.

Maximum likelihood phylogenetic analyses of the rpoB gene amino acid translation were performed using PROML with the JTT amino acid substitution matrix, a rate heterogeneity model with gamma-distributed rates over four categories with the D among-sites rate variation parameter estimated using TREE-PUZZLE, global rearrangements and randomized input order of sequences (10 jumbles). Bootstrap support values represent a consensus (obtained using CONSENSE) of 100 Fitch- Margoliash distance trees (obtained using PUZZLEBOOT and FITCH) from pseudo- replicates (obtained using SEQBOOT) of the original alignment. The settings of PUZZLEBOOT were the same as those used for PROML, except that no global rearrangements and randomized input order of sequences are available in this program. PROML, CONSENSE, FITCH and SEQBOOT are from the PHYLIP package version 3.6a (http://evolution.genetics.washington.edu/phylip.html). TREE-PUZZLE and PUZZLEBLOOT can be obtained from the programs website (http://www.tree- puzzle.de).

4.2.5 Random taxon sampling analysis

To evaluate the influence of intragenomic heterogeneity in a 16S rRNA gene phylogeny at the subspecies level, a random taxon sampling analysis of 16S rRNA paralogous gene copies from multiple Escherichia coli and Shigella flexneri strains was performed.

115 Shigella strains, although bearing a separate genus name, have been shown to be part of the E. coli species (29). Sequences from the more distant Salmonella typhi LT2 were also included as an outgroup for the analysis. All strains of E. coli, S. flexneri and S. typhi LT2 analyzed here possess seven copies of the 16S rRNA gene. In this analysis, one of these seven paralogous copies was randomly sampled from each strain to create a dataset for which a maximum likelihood tree was computed. The procedure was repeated 1000 times, giving a set of 16S rRNA gene trees, each including one randomly chosen 16S rRNA gene copy from each E. coli and S. flexneri strain. Trees were systematically rooted with randomly sampled 16S rRNA gene copies from S. typhi LT2.

4.2.6 Determination of evolutionary rates across sites (sliding window analysis)

To better define regions of the 16S rRNA and rpoB genes with a higher evolutionary rate, a sliding-window analysis was performed on a dataset composed of the evolutionary rates at each position in the sequence alignments. These evolutionary rates were calculated for each position of the RpoB amino acid alignment and the 16S rRNA gene alignment of sequences from 50 representative species of the domain bacteria. TREE-PUZZLE was used to assign an evolutionary rate category from 1 to 8 for each position (1=slowest, 8=fastest). These position and rate values were copied in an EXCEL sheet, in which a macro was used to calculate the average evolutionary rate category for each 10 neighboring positions. The 10 positions window was moved along the dataset by increments of a single position, recalculating the average evolutionary rate category each time.

116 4.3 Results

4.3.1 rpoB and 16S rRNA gene copy number and intragenomic heterogeneity

An alternative marker to the 16S rRNA gene for molecular microbial ecology studies is the single copy gene RNA polymerase ß subunit, rpoB. This study compares the rpoB and 16S rRNA genes by sampling all gene copies from 111 bacterial genomes (Table 4-1). Four hundred and sixty copies of the 16S rRNA gene (giving an average of 4.2 copies per genome), and 111 copies of the rpoB gene were recovered, the latter being found as a single copy gene in every genome. The extent of intragenomic 16S rRNA gene heterogeneity among bacteria ranges from 0-11.6% sequence divergence between 1 to 15 16S rRNA gene copies. Sixty-two percent of bacteria with more than one 16S rRNA gene copy were found to display some degree of intragenomic heterogeneity for this gene (Table 4-1).

4.3.2 Localization of intragenomic heterogeneity in the 16S rRNA molecule

Heterogeneous positions between intragenomic copies of the 16S rRNA gene were mapped on the Escherichia coli 16S rRNA secondary structure for all 110 genomes (Fig. 4-1). Positions that display heterogeneity in a single genome are color-coded in blue, while positions displaying heterogeneity for more than one genome are color- coded red. Nucleotide positions displaying intragenomic heterogeneity between paralogous copies were found throughout the length of the 16S rRNA gene (Fig. 4-1). However, such heterogeneous positions are concentrated in specific regions. These regions are called 'heterogeneity hotspots' here, and occur within helices 6, 9-11, 17, 33-34, 39 and 41 (Fig. 4-1).

4.3.3 Evolutionary characteristics of the rpoB and 16S rRNA genes

Sliding window analysis maps the evolutionary rate of nucleotide or amino acid positions along the length of a gene. Rate categories from one to eight are assigned to each position according to its variability: highly variable positions have high rate categories (6-8) and more conserved positions have low rate categories (1-2). Fig. 4- 2A&B show plots of the rate categories along the amino acid translation of the rpoB gene and the 16S rRNA gene such that variable and conserved regions can be visualized. A good phylogenetic marker displays some conserved regions, which are used as targets for universal probes and primers and useful to decipher phylogenetic

117 Table 4-1: 16S rRNA gene intragenomic heterogeneity among a variety of bacterial taxonomic groups

No. sequenced No. 16S No. Taxonomic group genomes (No. with genes per heterogeneous multiple 16S genes) genome positions Aquificae 1(1) 2 0 Thermotogae 1(0) 1 0 Deinococci 1(1) 3 2 Cyanobacteria 4(2) 1-4 0 Chlorobi 1(1) 2 0 Proteobacteria Alpha 9(6) 1-4 0 Beta 4(3) 1-4 0 Gamma 29(26) 1-11 0-30 Epsilon 4(3) 1-3 0-1 Firmicutes Bacillales 11(11) 5-13 4-34 Lactobacillales 12(12) 4-6 0-3 Clostridiales 3(3) 5-11 6-19 Thermoanaerobacteriales 1(1) 4 188 Mollicutes 6(2) 1-2 0-3 Actinobacteria 11(5) 1-6 0-8 Chlamydiae 7(2) 1-2 0 Spirochaetes 3(2) 1-2 0-1 Bacteroidetes 1(1) 5 34 Fusobacteria 1(1) 5 3

118 AA U G U U G C G C 1100 H37 G C 700 U G C C A H39 A G A A G U A H23 A G C H38 U U G G G CC U AC GA GC CCUUA UC C U UUG CC CG G U C GA A G UG A A UG C A UCU GGA G AU G GC G G C A A U G C U C G G G G G U A G G A A A C G G G C C G G U G A G A A U A G U C A A U G G C G U G G A C C U U G A G C G G U G A U G A A U G H36 A U H35 C G G 1150 G C A G U A A A G C G U G C A G C C G G C G C U U G U A G A G C U U G C A G G U A G C A U A U A 1200 G U C C G G C G A C U A H40 A G G C U G G UC H22 U A C G H34 A C G G C G C U A U G C A U H24 C G C G A U A A G C G H33 G A A A U A A A G 800 U A C G U U C G A UG A G A A U G A U G U G U A C 1050 C G A A A C G C 750 C G A C U U U U G G G C A U G A A G U A U G AG U G G G C G G C G H21 U G A A G C 650 G C C C A U AC UA U A G C C U A A C CU GGG A UG CA U CUG A CU G G C A A G C C U A 1000 U A U A C C G G C C U U C G U C C G C U U A C G G G C C C C G U G U A G A C U G A U U G U U U G G U G C G C C A G G C C G C A G C U A G A U H26 G A A A G A U G G C 600 G U A G H32 A C G A A G C C U U A C U C U C G C G A U G A G A C U A C G C G G A H20 G G G G 850 G C A A C G C U G U G C G U G A U C U A GC C A GUCG AC U U H31 A C U G A C C G U U A A C A A A C G C U A U G C G G C A m7 A G U A A A U U C A G C U G G C C G C U U C G U G C A A G C A G G G U H17 G C A A U A A C A G G C G U G 1250 G A A G H25 U C A A G C G C A A A C C H19 G C G U A A A U U C C U 950 U G A G G U C A U G G C G A G A U C C G U C A U U H30 U G A G U C A C G A C A G G G A C A A C U A G C G C U A A y A G A G C G U G C U GGG GGC C A U C U G U C H27 G A G C G U C G A A A G A A 900 G C A A U A H41 A C G A C U C U U G G A U G G G C H18 U A A A G C C A A A A H29 U G 450 A C U A AC G A G U G G G G A G C G C U G G H28 C G A C G G G A A C A A G A G C C G UUGACGGGG CCCG AC U U G C G U C A G A 500 C G U C G A C G A A A A U A C U U C C 550 A G A A C U G U U C C G G G C U G U G G U G C G U A U A A C A G U U A U U G U C C U 1300 U A A G C G U G A U G C A G C C G A U A A U U C G G G UU G U A C A C A G A U G G G A 10 C A C A C A H1 A 1350 A G U G G A A A A H16 U G C C 1400 C AA G U U C C G G U A U G G U H3 U U G U A G 400 C G C G G C U A A C G U G U G A G G A C A G A G A U C A G C U G A C U G C G C G C G G A C A C C A 1500 U AA CCG UA GG C G A A G C C U G U GCA G A G C G A U G A G C U G U U A G C U H42 C H4 C A H15 5' C G G U U G G C G U C C U C G C G G G U A C G U A A A A A G U A C U U A G A A C G A A G C G A A U H45 U C A U C G C C A A G C G H43 G C A C A G C G UA 50 U G C U G CA G U G C C U A C H14 G C G A A H5 A G U C G A U U A 350 C G G U G U A A U G C AG C C A G G C H13 C G A G U U G U 3' A C G C A C GA A A H6 U A A G U A C C A GU C AC G G U C AGG AA GA AGC U G G G U G U 300 A G A A U C G U C G G U C G G U G A C A G U C U U U C U U C G A U G A C G GA G G A U A G A A G U C C A U G C G 100 A U C A A C U G C C G A G G U G G C A H12 G U G A C G A A C A G G C U U U A C C A A U C A G U GA G U G C U G A U G C A G U G H44 G C A G U A G C C U A U G A C G H7 C G H11 G G C G U G C U G A C G A U U G A A C U A A A C G C A G U A A G 250 G C C G C G U 1450 U G U U U G C G G U C G G A C C G G C A G G U A U C G U A A U 150 C G H8 C G A U A A G A G GG C C U C U U G G GGG CUA CU G G C A U A U C C G G G G A G C G C C C G A U G G C A A A U A G A U A 200 U A A A A A H10 C C C G A U G C A G H9 A C

Figure 4-1: Mapping of the 16S rRNA positions for which intragenomic heterogeneity is observed among the 111 bacterial species analyzed. Intragenomic heterogeneity represents nucleotide substitutions between multiple copies of the 16S rRNA gene present in a single organism. Heterogeneous positions were mapped on the secondary structure of one of the Escherichia coli K12 16S rRNA. Positions indicated in blue are heterogeneous in one species and those in red in two or more species. relationships between distant organisms, as well as more variable regions, which are used as sites for genera and family level probes and primers and to differentiate closely related organisms. Both the RpoB protein and the 16S rRNA gene were found to have variable and conserved regions (Fig. 4-2A&B), fulfilling an important criteria for a phylogenetic marker.

The evolutionary characteristics of these markers can also be compared directly when it is possible to use the rpoB nucleotide sequence (rather than its amino acid translation) for phylogenetic analysis. The nucleotide sequence of a protein-coding gene can be used for such analysis when mutational saturation is absent at all codon positions or when it is present at the third (synonymous) position and the latter is removed from the dataset. We tested rpoB datasets representing various taxonomic levels for mutational saturation at all three codon positions, and only the domain level (all of Bacteria) dataset and one phylum level dataset (Proteobacteria) displayed saturation at codon positions other than the third. The evolutionary parameters of rpoB and 16S rRNA genes datasets that have been compiled for phylogenetic analyses at varying taxonomic levels are presented on Tables 4-2 and 4-3. When only considering nucleotide datasets (i.e. excluding the Bacteria and Proteobacteria datasets, for which analyses have been performed at the amino acid level), the rpoB gene displays greater variation in the evolutionary rate of nucleotide positions across its length than the 16S rRNA gene. This is illustrated by higher gamma rate parameters (G) and lower proportion of invariable sites (I) for most rpoB datasets (Table 4-2 and 4-3). Such variability in evolutionary rate across sites indicates that phylogenetically informative positions (i.e. not saturated or invariable) can be found for large scale (Domain / Phylum) or fine scale (Species / Subspecies) analyses.

The rpoB-DGGE fragment (Fig. 4-2A) contains a variable region allowing it to provide phylogenetic resolution between relatively closely related bacteria (Table 4-2). The rpoB primers used to amplify this fragment are found at conserved positions (10). The 16S rRNA gene 'universal' primer sites used for clone libraries, T-RFLP and DGGE are also shown to occur at conserved positions (Fig. 4-2B). However, the internal region of all these 16S rRNA gene fragments contains one or more 'heterogeneity hotspots', making all methods susceptible to the influence of using a gene displaying intragenomic heterogeneity. These 'heterogeneity hotspots' are located in fast-evolving

120 Table 4-2: Characteristics of rpoB gene datasets and phylogenies at different taxonomic levels

No. of Sat. Taxonomic group Taxonomic level rpoB (complete gene) rpoB (DGGE fragment) taxa pos.

No. No. G I Resol. G I Resol. pos. pos.

Bacteria Domain 50 all 774AA 0.67 0.05 26/50 126AA 0.65 0.08 8/50

Actinobacteria Phylum 11 none 3336 1.73 0.30 6/11 390 2.83 0.34 5/11

Chlamydiaceae Family 7 none 3756 0.59 0.30 2/7 387 1.13 0.56 2/7

Firmicutes Phylum 33 3rd 1978 0.82 0.16 19/33 262 1.61 0.30 10/33

Bacillales Order 11 3rd 2308 1.64 0.62 4/11 262 0.39 0.24 5/11

Lactobacillales Order 12 3rd 2336 0.74 0.37 5/12 262 0.87 0.36 4/12

Streptococcus Genus 9 none 3546 0.71 0.37 4/9 393 0.49 n.d. 6/9

Mycoplasmataceae Family 6 none 2679 1.7 0.18 2/6 354 1.34 0.15 1/6

Proteobacteria Phylum 46 1st,3rd 1147AA 0.57 0.08 35/46 127AA 0.52 0.10 23/46

Alphaproteobacteria Class 9 none 3993 0.4 n.d. 4/9 387 1.88 0.31 2/9

Gammaproteobacteria Class 29 3rd 2660 0.89 0.36 19/29 258 0.89 0.36 11/29

Enterobacteriales Order 14 none 4020 1.27 0.34 11/14 387 0.56 0.22 5/14

E. coli / S. flexneri Species 5 none 4026 n.d. n.d. 2/5 387 n.d. n.d. 1/5 Table 4-3: Characteristics of 16S rRNA gene datasets and phylogenies at different taxonomic levels

No. of 16S rRNA 16S rRNA Taxonomic group Taxonomic level taxa (complete gene) (DGGE fragment)

No. No.

pos. G I Resol. pos. G I Resol.

Bacteria Domain 50 1241 0.69 0.33 20/50 511 0.69 0.33 11/50

Actinobacteria Phylum 11 1428 0.67 0.49 6/11 563 0.67 0.49 5/11

Chlamydiaceae Family 7 1512 n.d. 0.76 2/7 588 n.d. 0.76 2/7

Firmicutes Phylum 33 1362 0.68 0.43 17/33 537 0.68 0.43 13/33

Bacillales Order 11 1498 0.54 0.56 4/11 585 0.54 0.56 5/11

Lactobacillales Order 12 1477 0.53 0.53 4/12 582 0.53 0.53 5/12

Streptococcus Genus 9 1510 n.d. 0.84 4/9 588 n.d. 0.84 4/9

Mycoplasmataceae Family 6 1453 0.64 0.32 3/6 575 0.64 0.32 2/6

Proteobacteria Phylum 46 1329 0.72 0.48 28/46 533 0.72 0.48 20/46

Alphaproteobacteria Class 9 1420 0.87 0.59 2/9 559 0.87 0.59 1/9

Gammaproteobacteria Class 29 1462 0.82 0.55 20/29 577 0.82 0.55 10/29

Enterobacteriales Order 14 1494 0.60 0.52 7/14 588 0.60 0.52 6/14

E. coli / S. flexneri Species 5 1505 n.d. n.d. 0/5 588 n.d. n.d. 0/5 Table 4-3 continued No. pos. = number of nucleotide (or amino acids if followed by AA) positions in alignment; G = among sites evolutionary rate variation parameter; I = proportion of invariable sites; n.d. = value cannot be defined (dataset too small and/or lacks informative positions); Resol. = number of nodes resolved (>80% bootstrap support value), bold typeface indicating the gene (rpoB or 16S rRNA) displaying the most resolved nodes.

Figure 4-2: Evolutionary rate and intragenomic heterogeneity at specific sites across the length of bacterial RpoB protein and 16S rRNA gene. A) Across-sites evolutionary rate variation for the amino acid translation of the rpoB gene (gray line). Sites that are slow-evolving or invariable have low rate categories and fast-evolving sites have high rate categories. The black bar above the graph illustrates the fragment targeted in DGGE analysis (10). B) Across-sites evolutionary rate variation for the 16S rRNA gene (gray line) and mapping of the number of species displaying intragenomic heterogeneity at all sites across the length of this gene (black line). Bars above the graph illustrate fragments of the 16S rRNA gene targeted for clone libraries (gray bar), T-RFLP (dashed bar indicating variable length) and DGGE (black bar) (32).

123 A. RpoB

2 Evolutionary Rate CategoryEvolutionary Rate Category 1

100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 Amino acid position B. 16S rRNA gene

8 8

7 7

6 6

5 5

4 4

3 3

2 2 Evolutionary Rate CategoryEvolutionary Rate Category 1 1

100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 Number of species displaying heterogeneity

Nucleotide position regions of the 16S rRNA gene, but not all fast-evolving regions of the 16S rRNA gene contain 'heterogeneity hotspots' (Fig. 4-2B).

4.3.4 Comparing rpoB and 16S rRNA gene phylogenies

To compare the phylogenetic resolution of the rpoB and 16S rRNA genes, both full length and DGGE fragments were used to reconstruct bacterial phylogenies at varying taxonomic levels (Table 4-2 & 4-3). Phylogeny of T-RFLP generated DNA fragments was not included as it generates DNA fragments of varying size. In order to reduce over-representation of some phyla and make computing intensive methods such as maximum likelihood phylogeny and maximum likelihood distance bootstrapping feasible, fifty bacteria were selected to reconstruct the phylogeny of the bacterial domain (Fig. 4-3). To compare the capacity of rpoB and 16S rRNA genes to reconstruct phylogenies at the subspecies level, datasets of these genes from E. coli and Shigella flexneri strains were compiled and analyzed using various phylogenetic tools (Fig. 4-4).

Both the RpoB protein and 16S rRNA gene trees reconstruct the major bacterial Phyla (Fig. 4-3), with a few exceptions. The Firmicutes do not form a monophyletic group in the 16S rRNA gene tree while they do so in the RpoB tree. The Mycoplasma are not within the Firmicutes for the RpoB protein or 16S rRNA gene trees, the parasitic intracellular lifestyle of these bacteria imposing strong evolutionary biases on their genes, which in turn cause phylogenetic artifacts. The RpoB tree also reconstructs a tentative relationship between the Gram positive Actinobacteria and Firmicutes. The Proteobacteria are monophyletic in both the RpoB and 16S rRNA gene trees, with the exception of the Epsilon Proteobacteria, which make the proteobacteria polyphyletic in the RpoB tree. The origin of the Beta Proteobacteria also differs between the trees. In the 16S rRNA gene tree the Beta Proteobacteria arise from within the Gamma Proteobacteria and in the RpoB tree the Beta Proteobacteria are a sister group to the Gamma Proteobacteria.

A summary of the comparison of phylogenetic resolution using the full length rpoB and 16S rRNA genes and their DGGE fragments at varying taxonomic levels (Domain, Phylum, Family, Order, Class and Species) is given in Table 4-2 and 4-3. The full length rpoB and 16S rRNA genes showed equal resolution (number of tree nodes showing significant statistical support) in four of the comparisons. The rpoB gene offers better resolution in seven of the thirteen comparisons, while the 16S rRNA gene only provides enhanced resolution in two of the comparisons. The rpoB- and

126 16S rRNA gene RpoB Thermotoga maritima Thermotoga maritima Ureaplasma urealyticum Aquifex aeolicus Mycoplasma genitalium 100 Thermoanaerobacter tengcongensis Thermoanaerobacter tengcongensis Oceanobacillus iheyensis 100 Clostridium perfringens 79 Bacillus halodurans Staphylococcus aureus Bacillus subtilia Listeria innocua 56 Staphylococcus aureus 100 Enterobacter faecalis 100 Listeria innocua Lactobacillus plantarum Lactobacillus plantarum 99 Streptococcus mutans Enterobacter faecalis 74 Lactococcus lactis 99 95 Streptococcus mutans Lactococcus lactis Bacillus halodurans Bacillus subtilia 74 100 Bifidobacterium longum Mycobacterium bovis Oceanobacillus iheyensis 87 Streptomyces coelicolor Bifidobacterium longum Fusobacterium nucleatum Mycobacterium bovis 100 Clostridium perfringens Streptomyces coelicolor 99 100 Ureaplasma urealyticum Prochlorococcus marinus Mycoplasma genitalium Thermosynechococcus elongatus 100 100 Campylobacter jejuni E Synechococcus sp. Helicobacter pylori E Nostoc sp. 98 Xyllela fastidiosa G Deinococcus radiodurans 65 Pseudomonas aeruginosa G Fusobacterium nucleatum Rickettsia prowazekii 99 Pasteurella multocida G A 99 100 Yersinia pestis G Bradorhizobium japonicum A 100 52 95 Salmonella typhimurium G A Caulobacter crescentus Escherichia coli G Agrobacterium tumefasciens A 83 Vibrio vulnificus G A Brucella suis 100 97 58 Shewanella oneidensis G B Neisseria meningitidis 99 75 Neisseria meningitidis B Ralstonia solanacearum 100 B 73 Nitrosomonas europea B B Nitrosomonas europea 99 Ralstonia solanacearum B G Xyllela fastidiosa Rickettsia prowazekii A G Pseudomonas aeruginosa 92 Pasteurella multocida 51 99 Caulobacter crescentus A G 98 99 Bradorhizobium japonicum A G Shewanella oneidensis Brucella suis A G Vibrio vulnificus 100 Firmicutes Agrobacterium tumefasciens 75 85 A GEscherichia coli Actinobacteria Deinococcus radiodurans G Salmonella typhimurium Prochlorococcus marinus 100 Cyanobacteria 100 G Yersinia pestis 87 Proteobacteria Thermosynechococcus elongatus Pirellula sp. 98 Synechococcus sp. Aquifex aeolicus Spirochaetes 56 Nostoc sp. E Campylobacter jejuni 100 Chlamydiae Pirellula sp. E Helicobacter pylori 52 100 Chlamydophila pneumoniae B. thetaiotaomicron 100 Chlamydia trachomatis Chlorobium tepidum 84 Chlorobium tepidum Chlamydia trachomatis 100 Chlamydophila pneumoniae B. thetaiotaomicron 100 Borrelia burgdorferi Leptospira interrogans 98 82 Treponema pallidum Borrelia burgdorferi 100 0.1 substitution/site Leptospira interrogans Treponema pallidum 1 substitution

Figure 4-3: Comparison of the best maximum likelihood trees of the 16S rRNA gene and RpoB protein for the domain Bacteria. A. 16S rRNA gene phylogeny (all copies)

E. coli K12 (1) E. coli O157:H7 (4) E. coli O157:H7 EDL933 (2) E. coli K12 (7) E. coli K12 (6) E. coli K12 (5) E. coli O157:H7 EDL933 (7) S. flexneri 2a str. 301 (4) E. coli K12 (4) E. coli K12 (3) S. flexneri 2a str. 2457T (3) E. coli K12 (2) 74 S. flexneri 2a str. 2457T (2) 77 S. flexneri 2a str. 301 (1) S. flexneri 2a str. 301 (2) S. flexneri 2a str. 2457T (4) S. flexneri 2a str. 2457T (5) S. flexneri 2a str. 2457T (1) S. flexneri 2a str. 2457T (6) S. flexneri 2a str. 301 (7) 77 S. flexneri 2a str. 301 (3) S. flexneri 2a str. 301 (5) 54 S. flexneri 2a str. 301 (6) S. flexneri 2a str. 2457T (7) E. coli O157:H7 (2) E. coli O157:H7 EDL933 (3) E. coli O157:H7 (5) E. coli O157:H7 (7) E. coli O157:H7 (6) E. coli O157:H7 EDL933 (6) 58 E. coli O157:H7 EDL933 (4) E. coli O157:H7 (1) E. coli O157:H7 (3) E. coli O157:H7 EDL933 (5) E. coli O157:H7 EDL933 (1) S. typhimurium LT2 (1) 100 S. typhimurium LT2 (7) 0.01 substitutions/site S. typhimurium LT2 (2) 71 S. typhimurium LT2 (3) S. typhimurium LT2 (5) 55 S. typhimurium LT2 (4)

Figure 4-4: Evaluation of 16S rRNA and rpoB genes as phylogenetic markers at the subspecies level. (A) Best maximum likelihood tree for the 16S rRNA genes of Escherichia coli and Shigella flexneri strains (all seven copies from each strain are included). (B) Random sampling analysis of 16S rRNA paralogous gene copies from multiple E. coli and S. flexneri strains. 1000 trees have been constructed, randomly choosing one 16S rRNA gene copy from each strain for every tree. Values above the nodes represent the number of trees in which the given node is recovered. (C) Best maximum likelihood tree of the 16S rRNA gene of E. coli and S. flexneri strains in which positions displaying intragenomic heterogeneity were recoded as ambiguous. (D) Best maximum likelihood tree of the rpoB gene of E. coli and S. flexneri strains. B. Random sampling of 16 rRNA gene copies

S. flexneri 2a str. 301 662 591 S. flexneri 2a str. 2457T

E. coli K12

E. coli O157:H7 505 E. coli O157:H7 EDL933

S. typhimurium LT2

C. 16S rRNA gene phylogeny (recoded heterogeneous positions)

E. coli K12

76 E. coli O157:H7

E. coli O157:H7 EDL933

S. flexneri 2a str. 301 85 S. flexneri 2a str. 2457T 0.005 S. typhimurium LT2

D. rpoB gene phylogeny

S. flexneri 2a str. 301 99

100 S. flexneri 2a str. 2457T

E. coli K12

E. coli O157:H7

100 E. coli O157:H7 EDL933 0.005 S. typhimurium LT2 16S rRNA-DGGE fragments show similar phylogenetic resolution power, with both fragments having improved resolution in five of the thirteen comparisons, and three of the comparisons having equal phylogenetic resolution. Interestingly, the rpoB- and 16S rRNA-DGGE fragments show comparable phylogenetic resolution to the full length rpoB and 16S rRNA genes for several datasets, including the Actinobacteria, Chlamydiaceae, Bacillales, Lactobacillales, Streptococcus, Mycoplasmataceae, Alphaproteobacteria and Enterobacteriales.

Intragenomic heterogeneity displayed by the 16S rRNA gene is most likely to affect fine-scale phylogeny of closely related organisms, as their 16S rRNA gene intergenomic heterogeneity could be comparable to intragenomic heterogeneity. For this reason we used the more exhaustively sampled species, E. coli / S. flexneri (Shigella strains are part of the E. coli species (29)), as a dataset for various phylogenetic methods to determine if their fine-scale phylogeny could be resolved. We recovered 17 unique 16S rRNA gene sequences from the five E. coli / S. flexneri strains in the dataset (Fig. 4-4A), which would cause diversity to be grossly over- estimated when a 100% 16S rRNA gene sequence identity is used to define an OTU. Additionally, intragenomic and intergenomic heterogeneity levels appear to be of comparable importance, given that the 16S rRNA gene copies from each strain do not form monophyletic clades. There is also little bootstrap support for the nodes, with the outgroup alone being supported with statistical significance as a monophyletic clade. If a single 16S rRNA gene is chosen to represent a strain, the phylogeny obtained can change significantly depending on which copy was chosen. This is illustrated by the results of the random taxon sampling analysis (Fig. 4-4B). In this analysis, one of the seven 16S rRNA paralogous gene copies found in each E. coli / S. flexneri genome was randomly chosen for phylogenetic analysis, a procedure which was replicated a thousand times. The trees obtained in these thousand analyses differed significantly from each other, as a consensus of these trees is poorly supported (Fig. 4-4B). Recoding nucleotide positions that display intragenomic heterogeneity as ambiguous, also yields a poorly resolved tree (Fig. 4-4C). All the methods employed here clearly show that the 16S rRNA gene cannot resolve the relationships among E. coli / S. flexneri strains. The rpoB gene, for its part, can resolve the relationships between some of these strains with strong statistical support (Fig. 4-4D).

130 4.4 Discussion

4.4.1 Frequency and distribution of intragenomic heterogeneity between 16S rRNA gene copies

The 16S rRNA gene copy number was found to range from 1-15 with an average of 4.2 copies per genome. This is consistent with the Ribosomal RNA Operon Copy Number Database, which calculates an average of 4.1 ribosomal operons per bacterial genome (20). Recently, it has been suggested that the average ribosomal RNA operon copy number should be revised down due to the over representation of generalist bacteria among genome sequenced bacteria (3). However, while it is clear that generalist bacteria have a higher ribosomal operon number than specialist bacteria (19), this does not translate to their over-representation among bacteria for which the genome has been sequenced. We would suggest the opposite, that genomics, since its early days, has been biased toward sequencing bacteria with a specialist lifestyle (such as pathogens and symbionts), which tend to display fewer copies of the ribosomal RNA operon.

There are two main hypotheses used to explain the existence of multiple ribosomal RNA operons within a genome: 1) multiple ribosomal RNA operons provide a multiplier effect on translation, allowing a bacterium to grow rapidly in response to environmental changes (19) and 2) functional differentiation between ribosomal RNA operons allows for differential expression of ribosomal RNA operons in response to environmental change (17). For the first hypothesis to be true, genetic drift would have to be counteracted by gene conversion to give rise to ribosomal RNA operons with little sequence heterogeneity distributed randomly across their length. The second hypothesis predicts that selection of functionally differentiated ribosomal RNA operons would lead to the concentration of heterogeneous positions in specific regions, and differentiated stem and loop structures between ribosomal RNA molecules.

Evidence has been found for both scenarios. The 38% of bacterial genomes which contain more than one 16S rRNA gene copy but display no sequence heterogeneity between copies suggest that multiple ribosomal RNA operons can exist because of their multiplier effect on translation. However, promoters, ribosomal proteins or the 5S and 23S rRNA genes have not examined, which could also be important for functional differentiation between ribosomal operons. For genomes with more than one

131 ribosomal RNA operon, 62% display some degree of sequence divergence (0-11.6%) between the intragenomic 16S rRNA gene copies. While heterogeneous positions are found throughout the length of 16S rRNA gene copies, localized regions display an above average number of heterogeneous positions (helices 6, 9-11, 17, 33-34, 39 and 41, Fig. 4-1). Such hotspots could result from the accumulation of neutral nucleotide substitutions or recombination. In haloarchea, hotspots have been found to result from recombination (6). For the firmicute Thermoanaerobacter tengcongensis, about half of the 11.6% pairwise sequence difference between its two most divergent 16S rRNA gene copies is a result of large insertions in one of these copies. These large inserts form secondary structures (3) suggestive of a functional role in the ribosome.

It has yet to be shown whether paralogous copies of ribosomal RNA operons are co- or differentially expressed under varying environmental conditions in prokaryotes. However, such a link between functionality and intragenomic rRNA divergence has been observed in the apicomplexan Plasmodium berghei (17). Its two types of 16S rRNA genes (which differ at 5.0% of their nucleotide positions) are preferentially expressed in different stages of the life cycle of this eukaryotic parasite (17).

4.4.2 Comparing the rpoB and 16S rRNA genes as phylogenetic markers

The rpoB and 16S rRNA genes were compared at various taxonomic levels for their ability to resolve bacterial phylogeny. From a total of thirteen datasets, the rpoB gene provided more phylogenetic resolution than the 16S rRNA gene in seven cases, equal resolution in four cases and lower resolution in two cases (Table 4-2 & 4-3). Importantly, it resolved more of the relationships in the comparison at the domain level (Bacteria), which is the level at which most molecular microbial ecology studies occur.

A different picture emerges from a comparison of the 16S rRNA and rpoB-DGGE fragments, each yielding better resolution in five of the comparisons and being equal in three of them. The 16S rRNA-DGGE fragment produced enhanced resolution in the comparison at the domain level (Bacteria), although both fragments have poor resolution at this level. This is not surprising, as the rpoB- and 16S rRNA-DGGE fragments are very small (380 and 550 bp, respectively).

It should be noted that neither rpoB nor 16S rRNA genes can resolve all, and generally only about half, of the phylogenetic relationships in a given dataset, with

132 either their full length or DGGE fragments. Phylogenetic studies should therefore be cautious in arriving at conclusions on the origin of environmentally derived sequences and employ rigorous phylogenetic methods involving maximum likelihood based algorithms to determine relationships between sequences. Also, a measure of statistical confidence, such as bootstrapping, should always be included in phylogenetic analyses.

The influence of intragenomic heterogeneity displayed by the 16S rRNA gene on bacterial phylogeny was also assessed, as most heterogeneous positions are localized within fragments commonly used in microbial ecology studies (namely clone libraries, DGGE and T-RFLP) (Fig. 4-2). Phylogenetic analysis of all 16S rRNA gene copies present in the five strains of E. coli / S. flexneri of our dataset (17 unique sequences) presents multiple clusters containing sequences from different strains. This clustering of sequences from various strains demonstrates a lack of correlation between the origin of 16S rRNA genes and their nucleotide sequences at the subspecies level for the E. coli / S. flexneri group. Intragenomic heterogeneity is therefore likely to affect the fine scale phylogeny of closely related bacteria. For such closely related organisms, intragenomic heterogeneity can be as significant as intergenomic heterogeneity, as has been shown here for the E. coli / S. flexneri strains. It suggests the use of caution in interpreting environmental 16 rRNA gene sequence derived phylogeny at the species level or lower. For some prokaryotes, such as the archaeal order Halobacteriales, levels of 16S rRNA intragenomic heterogeneity are so high (>5.0%) that they can even affect phylogeny at the genus level (6, 38).

The rpoB gene did resolve several of the relationships among the E. coli / S. flexneri strains with strong statistical support (Fig. 4-4D). rpoB may be considered as an additional or alternate marker in ecological studies, as it is capable of deciphering fine scale phylogenetic relationships that go undetected using the 16S rRNA gene.

4.4.3 Establishing rpoB as an alternative gene marker for microbial ecology

Protein-coding genes such as rpoB have several advantages over RNA-coding genes as molecular markers. They can be used both at the amino acid or nucleotide levels for phylogenetic analysis. Protein alignments allow for resolution of relationships at higher taxonomic levels (domain or phylum) when one or more codon positions are saturated. Nucleotide level alignments allow for fine scale resolution, with

133 synonymous first and third codon positions allowing for nearly neutral mutations which can be detected between very closely related organisms (species level or lower). This is likely the reason why rpoB performed better than the 16S rRNA gene in resolving relationships at the subspecies level. The resolution provided by rpoB can also be further increased by sequencing other protein-coding genes and examining allelic profiles of different isolates rather than using single gene sequence comparisons (34, 36). Although such multi-locus sequence analysis (MLSA) cannot be done directly on an environmental sample, a marker used to describe diversity in an environmental sample (such as rpoB) can also be included in the set of genes used for MLSA of a collection of isolates. The improved phylogenetic resolution at the subspecies level provided by rpoB seems to be of increasing importance, with recent studies suggesting important ecological or genotypic differences in organisms with identical 16S rRNA gene sequences (ribotypes) (e.g. (22)). Such differences among organisms with identical ribotypes also outlines the advantages of using a single copy gene as a marker, as it will not be affected by intragenomic heterogeneity, which would further bias diversity estimates.

The analyses presented here demonstrate that rpoB displays other important characteristics as an ecological marker, including: 1) universal presence in all prokaryotes; 2) the presence of slow and fast evolving regions for the design of probes and primers of differing specificities; 3) having an housekeeping function, making it less susceptible to some forms of lateral gene transfer; and 4) a large enough size to contain phylogenetic information, even after removal of regions that are difficult to align.

There are a few disadvantages in using rpoB (or another protein-coding gene with similar characteristics) over the 16S rRNA gene as a molecular marker for microbial ecology studies. The single major obstacle resides in a fundamental property of protein-coding genes, the saturation of all third codon positions over a long evolutionary timescale, which makes it more difficult to design universal primers for rpoB. Nonetheless, rpoB primers that can amplify a range of bacterial groups have been successfully used for DGGE studies (7, 10, 24, 30, 31). Alternative rpoB primers targeting the most conserved amino-acid motifs of the RpoB protein have been developed and tested on most culturable bacterial phyla (RJ Case, manuscript in preparation).

134 A distinct advantage of using 16S rRNA as an ecological marker is the high concentrations of targets in cells for FISH analyses. However, development of more sensitive methods, such as CARD-FISH, should also allow for detection of organisms using protein-coding genes (13, 25). Although mRNA for the rpoB gene would not be as abundant as ribosomal RNA in prokaryotic cells, it has been shown that this mRNA is relatively stable and should be present in significant concentrations regardless of the growth phase of the host (23).

Interestingly, we noticed that heterogeneous regions between the seven 16S rRNA gene copies in E. coli coincided with regions of poor FISH probe accessibility (data not shown) described by Brehens et al. (5), where probe accessibility was measured as a function of probe signal. However, poor probe signal could result from a heterogeneous pool of 16S rRNA, as Brehens et al. later showed that poor accessibility of probes did not result from the ribosome's tertiary structure (4).

There is little doubt of the scientific contribution made by studies using the 16S rRNA gene as molecular based studies have circumvented the need to culture bacteria in all cases. Central to this contribution is the appreciation of the extent of and ability to catalogue microbial diversity, by storing 16S rRNA gene sequences in free and accessible databases. Moreover, the growing number of sequenced genomes and environmental metagenomic libraries provides us with the necessary reference sequences to use other genes for molecular microbial ecology. Also contributing to the accumulation of sequences for alternative molecular markers are MLSA studies using protein-coding genes.

4.4.4 Alternative markers in molecular microbial ecology – the way forward

Lateral gene transfer has uncoupled function from phylogeny for prokaryotes, so the identity of a bacterium responsible for a function is unlikely to be uncovered through diversity studies. This has already led many research groups to use functional genes such as [NiFe] hydrogenase, amoA, pmoA, nirS, nirK, nosZ and pufM in conjunction with DGGE (1, 18, 21, 37, 39) and to detect pmoA and dysB mRNA with CARD-FISH (13, 25), leading the way for in situ identification of protein-encoding genes. The potential for alternate house keeping genes to study diversity, or the use of operational genes in molecular microbial ecology is an exciting prospect. This study has demonstrated that some of them, with characteristics similar to rpoB, would have

135 the potential to yield the same phylogenetic information as the 16S rRNA gene, with enhanced resolution for fine scale analyses.

Acknowledgments

I acknowledge that bioinformatics data presented in this chapter was done in collaboration with Yan Boucher.

136 4.5 References

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140 5 Quorum sensing and phylogeny of the Roseobacter, Roseovarius and Ruegeria genera: chatterboxes of the oceans

5.1 Introduction

A marine Agrobacterium species was first isolated in 1968 (3). A new genus, Roseobacter, was later described in 1991 (58) and the marine Agrobacterium were renamed to join what has become the roseobacter clade (64). The growing diversity contained within the roseobacter clade includes most of the Rhodobacteraceae family. The continual expansion of the roseobacter clade is fueled by 16S rRNA gene-based diversity studies that produce an ever-growing amount of environmentally derived sequence data. While such studies yield insights on the total diversity within the roseobacter clade, many of the species associated with these sequences are readily culturable (59), with one third of the known diversity of this group represented by cultured isolates (14).

The roseobacter clade consists of numerous genera including Antarctobacter, Jannaschia, Loktanella, Nereida, Octadecabacter, Oceanibulbus, Rhodobacter, Roseobacter, Roseovarius, Ruegeria, Roseovivax, Sagittula, Salipiger, Silicibacter, Stappia, Sulfitobacter and Thalassobius. Buchan et al. (14) proposed the roseobacter clade to be composed of 41 lineages and 13 major clades based on their 16S rRNA gene-based phylogeny. Most of the clusters from this phylogeny show poor bootstrap support with many genera being paraphyletic (i.e. species from one genus are represented in more than one cluster) (14). This suggests that the relationships between genera in the roseobacter clade are unresolved, and that some species have been incorrectly named.

Phylogenetic analysis of the 16S rRNA gene of bacteria often produce tree topologies displaying little resolution (9, 62, 69). In multiple instances alternative genes, such as the RNA polymerase ȕ subunit (rpoB), have been successfully used to improve the resolution of bacterial phylogenies (15, 16, 22, 28, 32-35, 39, 42, 52, 60, 67). The simultaneous use of multiple genes in evolutionary analysis, such as in multilocus sequence analysis (MLSA), can overcome methodological artifacts and describe fine- scale diversity (45, 68). The latter is particularly relevant as the marine environment is known to harbor extensive micro-heterogeneity in its microbial populations (1).

141 Species belonging to the Roseobacter, Ruegeria and Roseovarius genera have all been isolated from the marine environment, with the exception of Roseovarius tolerans, which was isolated from a hypersaline lake (36). Many of the strains were isolated from marine eukaryotic surfaces (including macro-algae and a dinoflagellate), ocean waters and marine sediments (Table 5-3). The diversity of niches that these species occupy is reflected in the metabolic diversity observed among members of the roseobacter clade. Notably, some roseobacters play a role in the sulfur cycle (44), degrading the abundant organic sulfur compound, dimethylsulfoniopropionate (DMSP), produced as an osmolyte by marine algae and coastal vascular plants (38). DMSP is degraded through the 'cleavage pathway' (31) or through the demethylation/demethiolation pathway (65). Some roseobacters are also phototrophs, capturing light energy through bacteriochlorophyll A (12, 20, 36, 58). Roseobacter photosystems have also been recovered from BAC libraries of DNA originating from ocean water samples (10).

Important niches for roseobacters are marine eukaryotic species. The probiotic Roseobacter strain 27-4 was isolated from turbot larvae and produces secondary metabolites that are thought to deter pathogenic Vibrio spp. from infecting these larvae (13, 24, 25). Roseobacters are also pathogenic to a number of marine eukaryotes, including macro-algae (See Chapter 3) (6-8), oysters (11, 12) and corals (19). Eukaryotic micro-organisms can also have an association with roseobacters. For example, roseobacters associated with the dinoflagellate Alexandrium sp. (the causative agent of 'red tide') (26, 30) produce algal-lytic agents (4) and promote Alexandrium cyst formation (2). These examples constitute a growing body of evidence which suggests that the roseobacter clade plays an important role in many species-species interactions in the marine environment.

Quorum sensing is commonly found among organisms that form symbiotic or pathogenic relationships with eukaryotes (see Section 1.2). Bacteria associated with marine eukaryotes have been screened in three different studies for production of quorum sensing signal molecules, AHLs (21, 61, 66). These studies identified roseobacter isolates that produce AHLs. The AHLs-producing isolates include the Roseobacter strain 27-4 mentioned above which was isolated from turbot larvae (13) as well as isolates from sponges (61), dinoflagellates, picoplancton, diatoms, the water column (66) and marine snow (21). These results suggest that quorum sensing

142 is widespread within the roseobacter clade. Despite the significant amount of data, no quorum sensing regulated genes have been identified in these species.

Marine genera belonging to the roseobacter clade were originally called Agrobacterium, due to their physiological similarities to this terrestrial group of Į- proteobacteria (64). The Agrobacterium-Rhizobia clade consists of plant pathogenic and symbiotic species in which quorum sensing plays an integral role in mediating the relationship with their host plant (See Section 1.2). AHL-driven quorum sensing is found in many other Į-proteobacteria, including some purple non-sulfur bacteria and the roseobacter clade (Table 2-1). Lateral gene transfer (LGT) of quorum sensing among the Į-proteobacteria has also been demonstrated (See Section 2.3.1). However, quorum sensing regulated phenotypes have only been characterized for Rhodobacter capsulatus (56), R. sphaeroides (49), Agrobacterium and Rhizobia species (Table 1-1).

The aims of the work described in this chapter were to: 1) determine if the genera Roseobacter, Ruegeria and Roseovarius form monophyletic clades within the roseobacter clade by performing phylogenetic analysis on their 16S rRNA and rpoB genes, and 2) determine the frequency and identity of AHLs produced by members of the Roseobacter, Ruegeria and Roseovarius genera using the AHL reporter strain Agrobacterium tumefaciens A136 and thin layer chromatography (TLC).

143 5.2 Materials and methods

5.2.1 Strains and media

All marine strains (Roseobacter, Ruegeria and Roseovarius isolates) were routinely maintained in Marine Broth 2216 (Difco) at 25 °C. Serratia liquifaciens was maintained in LB10 (10 g/L tryptone, 5 g/L yeast extract and 10 g/L NaCl) and Agrobacterium tumefaciens A136 was maintained in LB5 (10 g/L tryptone, 5 g/L yeast extract and 5 g/L NaCl) supplemented with tetracycline (4.5 ȝg/ml) and spectinomycin (50 ȝg/ml). For plating, all media were supplemented with 1.5% agar (Research Organics).

A. tumefaciens A136 was grown in AB medium as an overlay on TLC plates. The A

( 4 g (NH4)2SO4, 4.85 g Na2HPO4, 3 g KH2PO4, 3 g NaCl, made up to 100 ml in Milli-Q water) component was added to the B ( 1 ml 1 M MgCl2, 1 ml 0.1 M CaCl2, 1 ml 0.01

M FeCl3, 2.5 ml 1 mg/ml thiamine, 15 g agar, made up to 900 ml in Milli-Q water) component after autoclaving, with 40 ml of 20% glucose (sterile filtered) and 40 ml 20% casaminoacids (sterile filtered) added at 60 °C before plating.

Table 5-1: List of strains used in this study

Species Strain number Reference

Ruegeria algicola DSM10253 (37, 64) R. atlantica DSM5824 (54, 64) Ruegeria strain PR1b PR1b (71) Ruegeria strain R11 R11 (29) Roseobacter denitrificans DSM7001 (58) R. gallaeciensis DSM12240 (55) R. litoralis DSM6996 (58) Roseobacter strain 2.10 2.10 (50) Roseovarius nubinhibens DSM15170 (20) R. tolerans DSM11463 (36) Thalassobius gelatinovorus* DSM5887 (3, 5, 54, 64) A. tumefaciens A136 (57) S. liquifaciens MG1 (18)

* Ruegeria gelatinovorus was renamed Thalassobius gelatinovorus while this study was being carried out (5)

144 5.2.2 DNA extraction

DNA was extracted from all strains as described in Section 3.2.8.1.

5.2.3 PCR of the 16S rRNA and rpoB genes

An ~1400 bp fragment of the 16S rRNA and rpoB genes was PCR amplified and sequenced from all the strains listed in Table 5-1. The 16S rRNA gene was amplified using the 27F and 1492R primers as described (Section 3.2.8.2). rpoB primers RC1420F (ATYATYTAYCGBGTVATGCG) and RC2740R (GTAVCCMTTCCAVGGC AT) were designed by aligning rpoB genes from completely sequenced Į- proteobacterial genomes using ClustalW (63) and finding conserved sites suitable for priming. The same PCR conditions were used for amplifying rpoB and 16S rRNA genes (Section 3.2.8.2).

5.2.4 16S rRNA and rpoB gene sequencing

Sequencing of the 16S rRNA gene was performed using the 27F and 1492R primers as described in Section 3.2.8.4. The rpoB gene fragment was sequenced RC1420F and RC2740R primers (Section 5.2.3) as described in Section 3.2.8.4.

5.2.5 Phylogenetic analysis

Sequenced rpoB and 16S rRNA genes were used as queries to retrieve their homologues from the completely or partially sequenced genomes of bacteria belonging to the roseobacter clade (using BLASTP to retrieve amino acid translations of rpoB genes and BLATSN to retrieve DNA sequences of 16S rRNA genes). Amino acid alignments (RpoB protein) and DNA alignments (16S rRNA gene) were constructed using CLUSTALW (63) and edited manually to remove ambiguous positions.

Phylogenetic analyses of the 16S rRNA gene were performed using PAUP* 4.04b, applying the heuristic-search option and using the TBR branch-swapping algorithm. Maximum likelihood was used as the tree reconstruction method, with the nucleotide substitution model (GTR), among-sites rate variation parameter D (G), proportion of invariable sites (I) and nucleotide frequencies determined using MODELTEST (47). The confidence of each node was determined by building a consensus tree of 100 maximum likelihood trees from bootstrap pseudo-replicates of the original dataset.

Maximum likelihood phylogenetic analyses of the rpoB gene amino acid translation were performed using PHYML with the JTT amino acid substitution matrix, a rate

145 heterogeneity model with Ȗ-distributed rates over four categories with the D among- sites rate variation parameter estimated by the program (23). Bootstrap support values represent a consensus of 100 maximum likelihood trees from pseudo- replicates of the original alignment.

5.2.6 AHL streak assay

Marine strains were screened for AHL production by streaking the test strain along with the AHL reporter, A. tumefaciens A136. This reporter strain has a LuxR- controlled promoter fused to a gene encoding ȕ-galactosidase production, and consequently turns blue in the presence of exogenous AHLs and 5-bromo-4-chloro-3- indolyl ß-D-galactopyranoside (X-gal). For the streak assay, plates were poured with one medium, set, half the media was aseptically removed and the second media poured to replace the removed media. This was done because A. tumefaciens A136 and the marine strains cannot grow on the same medium. A. tumefaciens A136 was grown on LB5 plates supplemented with tetracycline (4.5 μg/ml), spectinomycin (50 μg/ml) and X-gal (50 μg/ml). Marine strains grew on Marine Broth 2216 supplemented with 1.5% agar. A. tumefaciens A136 was used as a negative control (as it does not produce AHLs) and Serratia liquifaciens was used as a positive control.

5.2.7 Extraction and characterization of AHLs produced by marine strains

Marine strains that gave a positive result in the AHL streak assay had their AHLs further characterized using TLC plates with an A. tumefaciens A136 overlay. To extract AHLs from these marine strains, they were grown to stationary phase in 10 ml of Marine Broth 2216. These 10 ml cultures were filtered (0.22 ȝm) and the supernatants retained. AHLs were extracted from the supernatants as described by Ravn et al. (51) and the AHL extracts resuspended in 100 μl of acidified ethyl acetate and 40-80 ȝl of each sample was applied to C18 TLC plates (TLC aluminum sheets 10x10 cm2 Rp-18 F254 s,1.05559, Merck 64271) and developed in 60:40 methanol:Milli-Q water as described by Shaw et al. (57). A lawn of A. tumefaciens A136 in AB media was overlaid on the TLC plate as described by Ravn et al. (51). AHLs were compared against commercial standards (OHHL, OOHL, OHL) and Rf values were calculated (57). AHLs were identified based on Rf values and the shape of spots. Identified AHLs were named using the nomenclature described in Table 5-2.

146 Table 5-2: Nomenclature of unsubstituted, oxo or hydroxy acyl homoserine lactones (AHLs)

3-hydroxy Chain Length Unsubstituted 3-oxo-substituted substituted

BHL, N-butanoyl- OBHL, N-3- HBHL, N-3- Lhomoserine oxobutanoyl-L- hydroxybutanoyl-L- 4 lactone homoserine lactone homoserine- lactone HHL, N-hexanoyl- OHHL, N-3- HHHL, N-3- DL-homoserine oxohexanoyl-L- hydroxyhexanoyl-L- 6 lactone homoserine lactone homoserine- lactone OHL, N-octanoyl- OOHL, N-3- HOHL, N-3- DL-homoserine oxooctanoyl- hydroxyoctanoyl-L- 8 lactone Lhomoserine homoserine lactone lactone DHL, N-decanoyl- ODHL, N-3- HDHL, N-3- 10 L-homoserine oxodecanoyl-L- hydroxydecanoyl-L- lactone homoserine lactone homoserine lactone

147 5.3 Results

RpoB and 16S rRNA gene phylogenies performed included bacteria belonging to the roseobacter clade, which had their genomes completely sequenced as well as representative Roseobacter, Ruegeria and Roseovarius isolates deposited in the DSMZ culture collection. Roseobacter gallaeciensis (DSM12240) was identified as a Pseudoaltermonas sp. by performing a BLASTN search against GenBank using its 16S rRNA gene sequence and was consequently omitted from this study.

RpoB protein and 16S rRNA gene phylogenies using maximum likelihood were employed to resolve relationships between these three genera. Unexpectedly, few relationships were resolved with either gene. Such a poor resolution could result from a number of factors including insufficient taxonomic sampling, divergent mutational biases for different members of the clade or variation of substitution rates across taxa. Phylogenetic analysis using the 16S rRNA gene or RpoB amino acid sequences confirmed that the roseobacter clade is monophyletic (Fig. 5-1 and 5-2). The only significant (statistically supported) difference between these two phylogenies is the placement of the genus Rhodobacter. Rhodobacter is paraphyletic to the roseobacter clade using 16S rRNA gene phylogeny, being found in a basal position in a tree rooted with non-roseobacter Į-proteobacteria (Fig. 5-1). This genus is included in a monophyletic roseobacter clade in the RpoB phylogeny (Fig. 5-2).

Rhodobacter is the only monophyletic genus in both the RpoB and16S rRNA gene phylogenies, and this monophyly is supported by strong bootstrap values in both gene trees. Roseovarius, Ruegeria, Roseobacter, Oceanicola and Silicibacter are all paraphyletic with little bootstrap support for any of the relationships. The paraphyletic nature of genera belonging to the roseobacter clade is one of the few consistencies between the RpoB and 16S rRNA gene phylogenies (Fig 5-1 and 5-2).

Cultured Roseobacter, Ruegeria and Roseovarius strains were initially screened for AHL production using the AHL reporter strain A. tumefaciens A136 in a streak assay. AHLs were identified using TLC with an overlay of the AHL reporter (Fig. 5-3, Table 5- 3). Five of the ten strains tested positive for AHL production, indicating that quorum sensing may be common within the roseobacter clade. At least one strain belonging to each of the three genera tested was found to produce AHLs. Ruegeria strain R11 and Ruegeria strain PR1b, which are each others closest relative based on 16S rRNA gene sequence identity, both produce AHLs. However, they do not appear to be each

148 other closest relatives based on the RpoB phylogeny (Fig. 5-2). They also differ in the amount and types of AHLs they produce (Table 5-3). This suggests potential differences between their quorum sensing circuits. Both Roseovarius nubinhibens and R. tolerans produce AHLs but Roseovarius does not appear to be a monophyletic genus (Fig. 5-1, 5-2). Roseobacter strain 2.10 is the only Roseobacter strain identified to produce AHLs. However, the naming of this strain is tentative (based on ~500 bp of 16S rRNA gene sequence) (50).

A variety of AHLs were identified in this study, including OOHL, OHHL, OHL, HHL, DHL and HHL or unsubstituted C7 (Table 5-3). All of these AHLs have a carbon chain of six or more carbons (Table 5-2), which is consistent with previously characterized AHLs from marine Į-proteobacteria (66). Further, some strains were initially screened with the reporter Chromobacterium violaceum CV026 and no AHLs were detected (data not shown), which is also consistent with marine Į-proteobacteria having long chain AHLs (66). In contrast to the resolution provided by A. tumefaciens A136, the reporter strain C. violaceum CV026 cannot detect longer chain AHLs (61, 66).

149 Rhizobium etli CFN 42 (NC007761) Agrobacterium tumefaciens strain C58 (NC003304) Sinorhizobium meliloti 1021 (NP385454) Rhodobacter sphaeroides 2.4.1 (NC007493) Rhodobacter sphaeroides ATCC17029 (NZAAMF00000000) Rhodobacter sphaeroides ATCC17025 (NZAAME00000000) Roseovarius tolerans DSM11463 Roseovarius strain 217 (NZAAMV00000000) Sulfitobacter strain EE-36 (NZAALV00000000) Roseobacter litoralis DSM6996 Roseobacter denitrigicans DSM7001 Oceanicola granulosus HTCC2516 (NZAAOT00000000) Jannaschia strain CCS1 (NC007802) Loktanella vestfoldensis SKA53 (NZAAMS00000000) Rhodobacterales bacterium HTCC2654 (NZAAMT00000000) Oceanicola batsensis HTCC2597 (NZAAMO00000000) Ruegeria algicola DSM10253 Roseobacter sp. MED193 (NZAANB00000000) Roseobacter strain 2.10 Thalassobius gelatanovorans DSM5887 Ruegeria strain R11 Ruegeria strain PR1b Roseovarius nubinhibens ISM (NZAALY00000000) Roseovarius nubinhibens DSM15170 Silicibacter pomeroyi DSS-3 (NC003911) Ruegeria atlantica DSM5824 Silicibacter strain TM1040 (NC008044) 0.1

Figure 5-1: 16S rRNA gene phylogeny of the roseobacter clade. The genes of Roseobacter, Ruegeria and Roseovarius strains from the DSMZ culture collection were aligned with homologues from partially or completely sequenced roseobacter genomes. The number in parentheses found after each taxon name is the accession number for the respective gene or genome sequence. The tree was compiled by maximum likelihood using PAUP* 4.04b. Black dots indicate bootstrap support over 95%, and white dots support over 80% (these values represent the consensus of 100 maximum likelihood trees made from pseudo-replicates of the original dataset). Sinorhizobium meliloti 1021 (NP385454) Rhizobium etli CFN 42 (YP469189) Agrobacterium tumefaciens strain C58 (NP354931)

Roseovaris tolerans DSM11463 Roseobacter sp. MED193 (ZP01055763) Roseobacter strain 2.10 Thalassobius gelatinovorus DSM5887 Ruegeria strain PR1b Silicibacter strain TM1040 (YP612229) Silicibacter pomeroyi DSS-3 (YP168703) Ruegeria strain R11 Oceanicola batsensis HTCC2597 (ZP00998137) Jannaschia strain CCS1 (YP508510) Rhodobacterales bacterium HTCC2654 (ZP01013343) Roseovarius nubinhibens DSM15170 Roseovarius nubinhibens ISM (ZP00958540) Roseovaris strain 217 (ZP01037901) Rhodobacter sphaeroides ATCC17025 (ZP00912751) Rhodobacter sphaeroides 2.4.1 (YP351755) Rhodobacter sphaeroides ATCC17029 (ZP00916706) Ruegeria atlantica DSM5824 Sulfitobacter strain EE-36 (ZP00953973) Oceanicola granulosus HTCC2516 (ZP01158416) Roseobacter denitrigicans DSM7001 Roseobacter litoralis DSM6996 Ruegeria algicola DSM10253 0.1 Loktanella vestfoldensis SKA53 (ZP01002560)

Figure 5-2: RpoB phylogeny of the roseobacter clade. The amino acid translation of rpoB for Roseobacter, Ruegeria and Roseovarius strains from the DSMZ culture collection were aligned with homologues from partially or completely sequenced roseobacter genomes. The number in parentheses found after each taxon name is the accession number for the respective protein sequence. The tree was compiled by maximum likelihood using PHYML. Black dots indicate bootstrap support over 95%, and white dots support over 80% (these values represent the consensus of 100 maximum likelihood trees made from pseudo-replicates of the original dataset). A B

Figure 5-3: Acylated homoserine lactones (AHLs) profiles on C18 reversed phase thin layer chromatography (TLC) with an overlay of the AHL reporter strain Agrobacterium tumefaciens A136. The TLC plate was developed using methanol:water (60:40) as a solvent. AHL extracts from all strains were run with standards for comparative identification. (A) 1. N-3-oxohexanoyl-L-homoserine lactone (OOHL); 4 μl of 120 mg/ml, 2. OOHL; 4 μl of 120 mg/ml, 3. N-octanoyl-DL-homoserine lactone (OHL); 4 μl of 5 μg/ml, 4. OHL 4 μl of 100 mg/ml, 5. Roseovarius tolerans DSM11463 (60μl of extract). (B) 1. OOHL; 6 μl of 120 mg/ml, 2. OOHL; 6 μl of 120 mg/ml, 3. OHL; 4 μl of 5 μg/ml, 4. OHL 4 μl of 100 mg/ml, 5. Ruegeria strain PR1b (40 μl of extract). Table 5-3: Acyl homoserine lactones (AHLs) identified from marine Roseobacter, Roseovaris and Ruegeria strains

Organism Habitat A136 streak assay TLC-A136 overlay Tentative (positive/negative) (Rf value) identification

Ruegeria algicola Prorocentrum lima Negative N.A. N.A. (dinoflagellate), Vigo, Spain R. atlantica northeastern Atlantic Ocean Negative N.A. N.A. bottom sediments Thalassobius Pecten maximus Negative N.A. N.A. gelatinovorus (scallop) Ruegeria strain PR1b Mission Bay Marsh Reserve Positive Two spots (0.42 and 0.67) OOHL and OHHL site, San Diego, CA, USA Ruegeria strain R11 Delisea pulchra (alga), Bare Positive Two spots (0.19 and 0.42) OHL and HHL Island, NSW, Australia Roseobacter denitrificans Seaweed surface Negative N.A. N.A. R. litoralis Seaweed surface Negative N.A. N.A. Roseobacter strain 2.10 Ulva australis (algae), Clovelly, Positive One spot (0.38) HHL or unsubstituted- NSW, Australia C7 Roseovaris nubinhibens Coastal waters, Georgia, USA Positive Two spots (0.23 and 0.34) OHL and HHL or unsubstituted C7 R. tolerans Ekho Lake, Vestfold Hills, East Positive Two spots (0.14 and 0.35) DHL and HHL or Antarctica unsubstituted C7

N.A. signifies that the identity of AHLs was not determined as the strain did not test positive for AHL production with the streak assay. 5.4 Discussion

RpoB and 16S rRNA gene phylogenies failed to resolve the majority of relationships between roseobacter species and genera. The inability to resolve relationships with either the RpoB or 16S rRNA gene phylogenies is unusual and suggests that there is poor taxon sampling for this group and that many species may have been incorrectly named. There is statistical support for the Rhodobacter genus to be included in the roseobacter clade in the RpoB phylogeny (Fig. 5-2). This inclusion of Rhodobacter in the roseobacter clade makes the clade identical in content to the Rhodobacteraceae family.

To resolve the phylogeny of the Rhodobacteraceae family, a MLSA approach is necessary, as neither RpoB nor the 16S rRNA gene could by themselves resolve the phylogeny of the roseobacter clade. Concatenated phylogeny, which uses a dataset composed of multiple genes concatenated in a single alignment, could be able to resolve relationships within this clade. Additional taxa would also need to be sampled as many genera are poorly represented. Using novel evolutionary models that take heterotachy (variation of evolutionary rates across taxa) into account for phylogeny could also improve resolution.

It was found that 50% of the tested isolates produce the quorum sensing signal molecules, AHLs. This is similar to a recent study which reported that 38 of 65 marine Į-proteobacteria screened produced AHLs (66). However, these 38 isolates represent only 11 unique species. Wagner-Döbler et al. (66) also tested two of the strains used in the current study, Roseobacter denitrificans and R. litoralis, and detected AHLs only from R. litoralis (neither of these strains were found to produce AHLs in our study). The discrepancy probably results from their more extensive screening methods involving a variety of bioassays as well as GC-MS (66). In contrast, Taylor et al. (61) screened sponge isolates (i.e. not pre-selected based on their identity) and found one of eleven isolates produced AHLs (a Roseobacter isolate), and Gram et al. (21) found that four marine snow isolates out of 43 produced AHLs (all roseobacter isolates). Because of their potentially high frequency, roseobacters producing the signal molecules AHLs could be thought of as the 'chatterboxes' of the oceans.

Silicibacter pomeroyi DSS-3 and Jannaschia sp. CCS1 as well as Rhodobacter sphaeroides 2.4.1 were identified as containing complete quorum sensing circuits (i.e. LuxI and LuxR homologues) in their completely sequenced genomes (Table 2-1).

154 Silicibacter pomeroyi DSS-3 is known to produce three AHLs (43) and in Rhodobacter sphaeroides 2.4.1, EPS production is quorum sensing regulated (49). Jannaschia sp. CCS1 represents a novel quorum sensing species. There are currently a number of roseobacter genome projects underway (http://www.roseobase.org/), and hopefully their completion will elucidate the frequency of quorum sensing within this group.

While the case for quorum sensing being widespread among the roseobacters is growing, quorum sensing regulated genes among these species remain unknown. As quorum sensing is a laterally transferred trait (See Chapter 2), it is difficult to infer in which bacteria quorum sensing genes should be found based on organisms already known to harbor these genes. However, quorum sensing may play a similar role in D- proteobacteria associated with marine plants as it does in bacteria of this class associated with terrestrial plants. In the latter group, quorum sensing regulates a host of phenotypes that play a role in host colonization and the formation of pathogenic or symbiotic relationships (Table 1-1).

In some Rhizobia species, quorum sensing mutants have a reduced ability to form root nodules on legumes (53, 70) and have a reduced ability to fix nitrogen (17). However, quorum sensing is not thought to directly regulate nitrogen fixation, rather it regulates traits important for colonization and infection, such as EPS (40). For roseobacters such as Silicibacter pomeroyi DSS-3 (43), that have quorum sensing and can degrade DMSP from marine plants, quorum sensing regulated colonization traits could have an indirect effect on DMSP degradation.

Ruegeria strain PR1b contains the large cryptic plasmid pSD25 (71). This plasmid contains LuxI/R homologues and was shown here to produce the AHLs, OOHL and OHHL. pSD25 contains a repABC-type replicon and an operon encoding the trb-type conjugation apparatus, both of which are quorum sensing regulated in A. tumefaciens (46). The analogy between Agrobacterium-induced gall formation in terrestrial plants and Roseobacter-induced gall formation in the red alga Prionitis makes quorum sensing in Ruegeria strain PR1b intriguing.

Organisms that interact with quorum sensing species are likely to possess mechanisms for modulating quorum sensing (See Section 1.3). Cyclic dipeptides are signaling molecules known to antagonize AHL-driven quorum sensing by interacting with the quorum sensing response regulator (27) and they can also interact with plant and animal receptors modulating a range of physiological activities (48). The intracellular

155 Ruegeria strain SDC-1 was isolated from the sponge Subertites domuncula and found to produce cyclic dipeptides (41). For example, the production of extracellular signals that can modulate quorum sensing by Ruegeria strain SDC-1 suggests that this organism interacts with quorum sensing species in the environment. The prevalence of quorum sensing among roseobacters, and the potential for cross-talk with cyclic dipeptide signaling, strongly supports the idea that quorum sensing is important in modulating species-species interaction within the roseobacter clade.

The roseobacter clade is emerging as an important taxonomic group in the marine environment: its representatives are abundant, play important roles in nutrient cycling and interact closely with many other marine organisms. The prevalence of quorum sensing among roseobacters suggests that this system of communication may play a role in mediating interactions between them as well as with other micro- and macro- organisms. The extensive phenotypic and genotypic diversity reported for this clade could be the cause of the unusually poor phylogenetic resolution provided by molecular markers such as RpoB and the 16SrRNA gene. Further attempts at resolving roseobacter diversity should therefore employ MLSA, to maximize phylogenetic information, as well as better taxon sampling, to have a greater proportion of total sequence diversity represented.

Acknowledgments

I acknowledge that Adrian Low performed the A136-TLC assays in this chapter.

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164 6 General Discussion

6.1 The use of rpoB as a molecular marker in microbial ecology

Over the past decade the 16S rRNA gene has been widely adopted for use in molecular microbial ecology studies. Consequently, an extensive framework exists for 16S rRNA gene based-studies. Central to this framework is the Ribosomal Database Project (RDP) (20), which maintains a database of all known 16S rRNA gene sequences, as well as a number of tools to manipulate and analyze those sequences. Linked to this database is ARB (an abbreviation of the Latin word for "tree") (19), a platform for the alignment of ribosomal RNA genes, rough phylogenetic analysis and primer/probe design. Partly because of these tools, there are a large number of 16S rRNA gene probes and primers available in the literature. This framework makes the use of the 16S rRNA gene as a molecular marker attractive. However, there are several limitations in using the 16S rRNA gene, which can be overcome by using alternative gene markers (see Chapter 4).

Such alternative markers include informational protein-coding genes, such as rpoB, as well as operational (metabolic) genes. The latter should be used preferentially over the 16S rRNA gene in inferring the presence of a particular biological activity in a given environment. Predicting a biological activity based on the presence of a 16S rRNA gene sequence from an organism that usually harbors that property, should be avoided. This is because many operational genes are laterally transferred (7), making it impossible to predict their presence or absence on purely phylogenetic grounds. For example, the two conserved gene families involved in AHL-driven quorum sensing, luxI and luxR, are shown in this thesis to have been affected by this phenomenon (Chapter 2). Attempts were made to target these genes directly in the environment, but because of the diversity and rapid evolutionary rate of these gene families, such attempts were unsuccessful. Consequently, a more traditional screening of a previously cultured library of isolates (14) were used to identify quorum sensing epiphytic bacteria from Delisea pulchra (see Chapter 5).

An important theme emerging in microbial ecology is the extensive sub-species diversity present within populations. This subspecies diversity could be in part responsible for the 'unseen majority' (30) (i.e. ribotypes that are not associated with

165 cultured organisms). MLSA studies have revealed much of this subspecies diversity by employing a number of housekeeping genes (23, 27, 29). Such studies have found micro-organisms with identical 16S rRNA genes having significant divergence in protein-encoding genes (23). The fact that a single ribotype can represent significant genotypic diversity is further complicated by multiple ribotypes often representing a single genotype. Acinas et al. (1) reported extensive Vibrio subspecies diversity in the marine environment. However, their use of the 16S rRNA gene meant that their diversity assessment was compromised by the heterogeneity displayed between intragenomic copies of this gene (2).

One of the major limitations for using protein encoding genes is that nearly-neutral mutations in the third codon position creates heterogeneity in the nucleotide positions coding for conserved amino acids. Consequently, it is difficult to design general primers able to amplify a given gene from most representatives of a higher taxonomic group. Primers have been successfully designed for amplification of the rpoB gene at the species (8, 16, 17, 22, 25), genus (15, 26), family (18, 28) (see Chapter 5) and domain levels, although some bias is introduced when targeting the latter (Case, RJ, manuscript in preparation). These examples make rpoB a valuable alternative to the 16S rRNA gene for molecular microbial ecology studies as it does not display intragenomic heterogeneity and has suitable phylogenetic characteristics (see Chapter 4). It should also be suitable for subspecies diversity studies as it displays greater phylogenetic resolution than the 16S rRNA gene at this level (see Chapter 4).

The 16S rRNA and rpoB genes were employed to resolve the phylogeny of the roseobacter clade. Both genes demonstrated the monophyly of this clade with one major difference being the inclusion of the Rhodobacter genus when using RpoB as a marker (see Chapter 5). The inclusion of Rhodobacter suggests that the roseobacter clade can be considered equivalent to the Rhodobacteraceae family. The resolution of the phylogeny of this group is important with the growing number of research groups studying these organisms, and a rapidly increasing number of described species which appear to be poorly named, with many genera being paraphyletic. Better taxon sampling and MLSA of this group could resolve their phylogeny. This should be facilitated by the growing number of roseobacter genomes being sequenced (http://www.roseobase.org/).

166 6.2 The novel pathogen Ruegeria strain R11, climate change and chemical defense against colonization and infection by Delisea pulchra

This thesis presents the first evidence that increased temperature enhances virulence in a seaweed pathogen, and that secondary metabolites produced by a host can deter colonization and infection in situ (see Chapter 3). As furanones are known to antagonize AHL-driven quorum sensing and the pathogen Ruegeria strain R11 produces AHLs, we suggest that D. pulchra defends itself through furanone inhibition of quorum sensing in Ruegeria strain R11. However, quorum sensing regulated colonization and virulence traits is yet to be identified in this bacterium.

Ruegeria strain R11 colonizes furanone free D. pulchra at 20 °C. At 25 °C, this bacterium colonizes D. pulchra and forms characteristic microcolonies from which it penetrates the epidermis of the alga in an infection-thread like structure. Ruegeria strain R11 then becomes intracellular in adjacent cortical cells. The number of intracellular bacteria increases over time until the cell loses its integrity. Bleaching follows the line of infection. It is unclear whether D. pulchra bleaches before or after cell integrity is lost.

So that more careful observations can be made throughout Ruegeria strain R11's infection of furanone free D. pulchra, this strain has been GFP labeled. This constitutively expressed GFP will allow us to follow the bacterium more closely and perform a series of experiments to determine if furanones indeed inhibit the attachment of Ruegeria strain R11 to D. pulchra. GFP labeling will allow more detailed microscopical observations throughout the infection process.

The role of temperature in regulating Ruegeria strain R11's infection of D. pulchra is the first reported case of temperature regulated virulence in a seaweed pathogen. The effect of intermediate temperatures between 20 and 25 °C needs to be explored, as the progress of the infection at 25 °C is rapid, making it difficult to observe the intermediate stages of infection. Also a good guideline for relevant experimental temperatures is the coastal mean monthly sea surface temperatures in central NSW (e.g., Wollongong to Newcastle), which ranges between 17.7 °C (min) – 24.6 °C (www.metoc.gov.au/ products/data/aussst.html).

167 D. pulchra was first studied because it is usually unfouled in its natural environment. This is attributed to its secondary metabolites, furanones, which are active against a range of micro- and macro-fouling organisms (9, 11, 21, 31). Plants at shallow depths (3 m) become fouled during the austral summer while deep plants (10 m) do not. The fouling was correlated with increased UV in shallow waters, which led to a series of shading experiments to assess the effect of different light treatments on furanone concentration. UV shading had the greatest effect on furanone concentrations and led to several-fold increases in furanone concentration (Fig. 6-1). It is hypothesized that furanones are photo-oxidized by UV, leading to a decrease in furanone concentration in D. pulchra after exposure to this light wavelength. The impact of human-mediated climate change on Ruegeria strain R11's infection of D. pulchra is therefore two-fold, with the 'green house effect' increasing ocean temperature and increased UV radiation due to the thinning ozone layer. As a consequence, current field work is focusing on a seasonal survey of bleaching incidence in D. pulchra populations along the east coast of Australia.

In an attempt to understand the underlying genetics of D. pulchra infection by Ruegeria, colonization and infection assays on furanone-free D. pulchra were carried out in parallel with strain R11 (a natural epiphyte of D. pulchra) and strain PR1b (for which the lux genes have been sequenced). Ruegeria strain PR1b was isolated from coastal water off the coast of San Diego, CA, USA and contains a large cryptic plasmid, pSD25 (33). Ruegeria strain R11 contains a plasmid of similar size (determined by pulse field gel electrophoresis, data not shown). pSD25 contains a complete quorum sensing circuit (luxI and luxR homologues) and a repABC-type replicon as well as an operon encoding the trb-type conjugation apparatus, both of which are quorum sensing regulated in Agrobacterium tumefaciens (24). It also contains a VirD2 homologue, the enzyme that cuts the oncogenic tDNA region from the Ti plasmid and then binds the tDNA, allowing its transfer into the host plant through the Type IV secretion apparatus (which is also encoded in pSD25). While VirD2 and the Type IV secretion apparatus are not known to be quorum sensing regulated in A. tumefaciens, Type IV secretion is regulated by exogenous AHLs in Brucella suis (10), and quorum sensing mutants in A. vitis are avirulent (indicating that quorum sensing does play a role in Agrobacterium virulence) (13, 32). While pSD25 does not contain homologues to genes encoded in A. tumefaciens tDNA, there is an operon of hypothetical genes downstream of the VirD2 homologue, one of which has an homologue of unknown function in red algae, suggestive of a potential tDNA region.

168

total furanone mg/g

control transparent UV- black Experimental treatment

Figure 6-1: Effect of different light treatments on furanone concentration in the thallus of Delisea pulchra. N = 4 -6, F < 0.01 for all treatments. (Steinberg, P.D., et. al., unpublished data) Ruegeria strain PR1b infected only six of the nine furanone free D. pulchra plants it was inoculated onto, suggesting some specificity in the Ruegeria strain R11 and D. pulchra interaction (R11 infected all plants on which it was inoculated). However, Ruegeria strain PR1b showed the same pattern of colonization at 20 °C and infection at 25 °C as R11. However, no gall formation was observed as would be predicted with the similarity in genetic machinery between pSD25 and the A. tumefaciens Ti plasmid. It is possible that, given the small size of laboratory grown D. pulchra and the rapid infection by the pathogens in vitro, bleaching and death caused by the Ruegeria strains PR1b and R11 may be necrosis, a generalized response of cell death that limits infection. From inoculation, it only takes 5 days for furanone free D. pulchra to die. This is probably an insufficient time for gall formation to take place, as Roseobacter induced gall formation on the red algae Prionitis spp. takes about six to eight weeks (3). Importantly, necrosis also occurs in gall formation, as the plant's initial response to the infection (3).

The observations referred to above, along with the growing number of roseobacters implicated as pathogens of marine plants and animals (3-6, 12), suggest that roseobacters may be a reservoir of pathogens in the marine environment. Such a possibility needs to be investigated, as does the prevalence of temperature regulated virulence, because these diseases could become more widespread as the ocean’s temperature rises.

Sequencing of Ruegeria strain R11's genome should be completed this year, opening many avenues of research. The genome sequence will give insights on the lifestyle of this organism and whether it displays some of the diverse metabolic capabilities found in the roseobacter group. The role of quorum sensing in Ruegeria strain R11 is of particular interest as it may play an important in the infection process. A transposon mutant library of Ruegeria strain R11 is currently being constructed in an attempt to obtain mutants deficient in quorum sensing, biofilm formation, colonization and infection of furanone free D. pulchra. Such mutants will provide us with the tools to not only unravel the chemical cross-talk between Ruegeria strain R11 and D. pulchra, but to also understand what they are talking about.

170 6.3 References

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174 7 Appendices

7.1 Appendix 1

Figure 7-1: Furanones produced by Delisea pulchra

Compound 1 from D. pulchra Br Br Br

Compound 2 from D. pulchra H Br Br

Compound 3 from D. pulchra H Br Br

OAc O

Compound 4 from D. pulchra H Br Br

OH O

175 7.2 Appendix 2

Table 7-1: List of bacterial genomes used to construct the datasets to compare the rpoB and 16S rRNA genes as phylogenic markers in microbial ecology

Taxonomic group Species Aquificae Aquifex aeolicus VF5 Thermotogae Thermotoga maritima MSB8 Deinococci Deinococcus radiodurans R1 Cyanobacteria Nostoc sp. PCC 7120 Prochlorococcus marinus subsp. marinus str. CCMP1375 Synechocystis sp. PCC 6803 Thermosynechococcus elongatus BP-1 Chlorobi Chlorobium tepidum TLS Proteobacteria Alpha Agrobacterium tumefaciens str. C58 Bradyrhizobium japonicum USDA 110 Brucella melitensis 16M Brucella suis 1330 Caulobacter crescentus CB15 Mesorhizobium loti MAFF303099 Rickettsia conorii str. Malish 7 Rickettsia prowazekii str. Madrid E Sinorhizobium meliloti 1021 Beta Neisseria meningitidis MC58 Neisseria meningitidis Z2491 Ralstonia solanacearum GMI1000 Nitrosomonas europaea ATCC 19718 Gamma Buchnera aphidicola str. APS (Acyrthosiphon pisum) Buchnera aphidicola str. Bp (Baizongia pistaciae) Buchnera aphidicola str. Sg (Schizaphis graminum) Coxiella burnetii RSA 493 Escherichia coli K12 Escherichia coli O157:H7 EDL933 Escherichia coli O157:H7 str. Sakai

176 Haemophilus ducreyi 35000HP Haemophilus influenzae Rd KW20 Pasteurella multocida subsp. multocida str. Pm70 Pseudomonas aeruginosa PAO1 Pseudomonas putida KT2440 Pseudomonas syringae pv. tomato str. DC3000 Salmonella enterica subsp. enterica serovar Typhi str. CT18 Salmonella enterica subsp. enterica serovar Typhi Ty2 Salmonella typhimurium LT2 Shewanella oneidensis MR-1 Shigella flexneri 2a str. 2457T Shigella flexneri 2a str. 301 Vibrio cholerae O1 biovar eltor str. N16961 Vibrio parahaemolyticus RIMD 2210633 Vibrio vulnificus CMCP6 Wigglesworthia glossinidia endosymbiont of Glossina brevipalpis Xanthomonas axonopodis pv. citri str. 306 Xanthomonas campestris pv. campestris str. ATCC 33913 Xylella fastidiosa 9a5c Xylella fastidiosa Temecula1 Yersinia pestis CO92 Yersinia pestis KIM Epsilon Campylobacter jejuni RM1221 Helicobacter hepaticus ATCC 51449 Helicobacter pylori 26695 Helicobacter pylori J99 Firmicutes Bacillales Bacillus anthracis str. Ames Bacillus cereus ATCC 14579 Bacillus halodurans C-125 Bacillus subtilis subsp. subtilis str. 168 Listeria innocua Clip11262 Listeria monocytogenes EGD-e

177 Oceanobacillus iheyensis HTE831 Staphylococcus aureus subsp. aureus Mu50 Staphylococcus aureus subsp. aureus MW2 Staphylococcus aureus subsp. aureus N315 Staphylococcus epidermidis ATCC 12228 Lactobacillales Enterococcus faecalis V583 Lactobacillus plantarum WCFS1 Lactococcus lactis subsp. lactis Il1403 Streptococcus agalactiae A909 Streptococcus agalactiae NEM316 Streptococcus mutans UA159 Streptococcus pneumoniae R6 Streptococcus pneumoniae TIGR4 Streptococcus pyogenes M1 GAS Streptococcus pyogenes MGAS315 Streptococcus pyogenes MGAS8232 Streptococcus pyogenes SSI-1 Clostridiales Clostridium acetobutylicum ATCC 824 Clostridium perfringens ATCC 13124 Clostridium tetani E88 Thermoanaerobacteriales Thermoanaerobacter tengcongensis MB4 Mollicutes Mycoplasma gallisepticum R Mycoplasma genitalium G37 Mycoplasma penetrans HF-2 Mycoplasma pneumoniae M129 Mycoplasma pulmonis UAB CTIP Ureaplasma parvum serovar 3 str. ATCC 700970 Actinobacteria Bifidobacterium longum NCC2705 Corynebacterium efficiens YS-314 Corynebacterium glutamicum ATCC 13032 Mycobacterium bovis AF2122/97 Mycobacterium leprae TN Mycobacterium tuberculosis CDC1551 Mycobacterium tuberculosis H37Rv Streptomyces avermitilis MA-4680 Streptomyces coelicolor A3(2)

178 Tropheryma whipplei str. Twist Tropheryma whipplei TW08/27 Chlamydiae Chlamydia muridarum Nigg Chlamydia trachomatis D/UW-3/CX Chlamydophila caviae GPIC Chlamydophila pneumoniae AR39 Chlamydophila pneumoniae CWL029 Chlamydophila pneumoniae J138 Chlamydophila pneumoniae TW-183 Spirochaetes Borrelia burgdorferi B31 Leptospira interrogans serovar Lai str. 56601 Treponema pallidum subsp. pallidum str. Nichols Bacteroidetes Bacteroides thetaiotaomicron VPI-5482 Fusobacteria Fusobacterium nucleatum subsp. nucleatum ATCC 25586 Planctomycetes Rhodopirellula baltica SH 1

179