Investigations Into Abiotic and Biotic Factors Regulating Saxitoxin Synthesis in the Dinoflagellate Genus Alexandrium

Home , Alexandrium catenella, Alexandrium tamarense, Anderseniella, Flavobacterium, Oxalophagus

Investigations into abiotic and biotic factors regulating saxitoxin synthesis

in the dinoflagellate genus Alexandrium

A DISSERTATION SUBMITTED BY Maria Wiese

(Dip. Biology University of Bremen, Germany)

IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE AWARD OF DOCTOR OF PHILOSOPHY (Ph.D.) AT THE SCHOOL OF BIOTECHNOLOGY AND BIOMOLECULAR SCIENCES THE UNIVERSITY OF NEW SOUTH WALES SYDNEY, AUSTRALIA

2012

Supervisors

PROF. BRETT A. NEILAN

SUPERVISOR

SCHOOL OF BIOLOGY AND BIOMOLECULAR SCIENCES

THE UNIVERSITY OF NEW SOUTH WALES

SYDNEY, AUSTRALIA

DR. SHAUNA A. MURRAY

JOINT-SUPERVISOR

SCHOOL OF BIOLOGY AND BIOMOLECULAR SCIENCES

THE UNIVERSITY OF NEW SOUTH WALES

SYDNEY, AUSTRALIA

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Many Alexandrium species produce saxitoxin (STX) and its analogues, which are responsible for paralytic shellfish poisoning (PSP). However, the regulation of toxin production on a gene and enzyme level, and the basis of intra-strain and intra-specific differences in toxin production are not well understood. In this study the role of transcriptional regulation of the class II aminotransferase putatively involved in sax itoxin synthesis, sxtA4 was investigated during growth in batch culture and in different light conditions. No sign ificant differences in sxtA4 gene express ion were detected, w hile significant variances in PST production were measured, suggesting that post-tra nscriptional regulation might prevail in dinoflagellates. The preferential transcription of high GC genomic DNA copies of sxtA4 have been found to play a potential role in the transcriptional regul ation of sxtA4. Furthermore the impact of spectral light quality on PST production was investigated and red light was found to evoke a higher PST per cell content than blue light in Alexandrium catenella. Higher PST levels in red light were accompani ed by higher ch lorophyll production and photoacclimatory processes in the different light conditions. Based on the results it ca n be concl uded that A.catenella is likely to be more toxic in upper water layers where more red light is present. Bacteria are an integral part of the proximate environment of dinoflagellates. The involvement of bacteria in PST production has been reported, but is sti ll elusive. In this study bacterial communities associated with a toxic and non toxic Alexandrium strain were characterized in order to further unravel which biotic factors potentially impact harmful algal bloom development and toxicity of Alexandrium species.

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Species of the dinoflagellate genus Alexandrium are prominent producers of saxitoxin and its analogs, known as paralytic shellfish toxins (PSTs), which are the causative agents of paralytic shellfish poisoning (PSP). Under certain environmental conditions, some species of the genus Alexandrium can proliferate and form harmful algal blooms (HABs). In this study, a real time PCR assay was developed and a set of suitable reference genes was tested to investigate the transcriptional regulation of the class II aminotransferase (sxtA4) putatively involved in saxitoxin synthesis, during growth in batch culture of Alexandrium catenella. No significant changes in transcript abundance of sxtA4 were detected at different growth rates. The phylogenetic analysis of sxtA4 and the comparison of cDNA and gDNA copies of sxtA4 revealed that preferential transcription of high GC genomic DNA copies of sxtA4, may play a role in its transcriptional regulation. Light plays a key role in the regulation of cell division, synchronized by the circadian rhythm and is therefore likely to be a major regulator of the signalling pathways leading to the development of toxic blooms. Light penetrates the water column with varying intensities and qualities, which impact the regulation of cell proliferation and nutritional status of microalgae. Light quality was shown to be a major regulator of PST production. Alexandrium catenella Group IV produced significantly higher amounts of the PSTs when grown in red and white light in comparison to blue light. Biotic factors which can influence PST production include the bacterial communities associated with Alexandrium. In this study, bacterial communities associated with toxic and non-toxic Alexandrium tamarense Group V strains were studied via PCR-based 454 pyrosequencing. The strains displayed a similar microbial diversity when analyzed on the family level, in both cases dominanted by the Rhodobacteraceae family, but differed on the genus and species level. The Rhodobacteraceae associated with the toxic strain were closely related to Thalassobacter genus, while the Rhodobacteraceae associated with the non-toxic Alexandrium were closer related to the genus Loktanella. Several orders with lower abundance such as Rhizobiales and Sphingomonadales were also identified in both strains. The novel molecular approaches implicated in this study are excellent tools complementing traditional methods in the investigation of the capacity and regulation of PST production of toxic Alexandrium strains. This work has shown that an integrative approach of molecular and traditional methods, as well as the combined investigation of biotic and abiotic fators are promising to further elucidate the evolution of PST production capacity in dinoflagellates.

Acknowledgement

I would like to thank the Australian Research Council, Diagnostic Technology and the University of New South Wales for supporting this project (LP0989830) and I thank Prof. Brett Neilan for assigning the APAI scholarship for this project to me, sharing his enthusiasm for genes and giving me the freedom to pursue my own ideas. I would like to thank Prof. Gustaaf Hallegraeff for the supply of Alexandrium cultures. I thank Dr. Shauna Murray for help with editing and scientific writing of Chapters 1, 3-5, 7 and also for help with the sxtA phylogeny and primer design. I thank everyone who was a part of BGGM from 2009-2012. Thanks to Toby and Alvin for introduction to HPLC analysis. I also thank the Centre for Astrobiology for the desk and company in the Astrobiology office.

A special thank you to those who were originally not involved in this project, but who were open minded and interested to share their expertise, who allowed me to use their lab equipment and visit their labs, when I needed to. I would like to thank Dr. Tim Harwood for sharing his expertise on PST analysis and for teaching me the PST screen method and also for edits on Chapter 2. I am grateful to Dr. Gautam Chattopadhyay for providing me a whole culture cabinet in the school of Civil and Environmental Engineering, at UNSW, this helped me a lot, I also enjoyed the occasional chat, thank you! I thank Dr. Mark Brown for sharing his expertise on pyrosequencing and ARISA data processing. I am very grateful to associate Prof. Dr. Min Chen from University of Sydney for granting me access to the spectrophotometer in her lab and for advice on pigment analysis. I also thank Dr. Rosalind Deaker from University of Sydney for conducting the acetylene reduction test on Alexandrium cultures with me and Chris Brownlee for help with flow cell cytometry. I am also grateful for the financial support by the school of Biotechnology and Biomolecular Sciences and the Graduate Research School, enabling me to attend international conferences.

I thank my friends Aurelie Gueydan, Carsten Kolve, Sian Day, Vicky Zhang, Thomas, Spas, Andrea for having big hearts. I also thank the “family” Nigel, Paula and Co, it just would not have been what it was and thank you to Anja and Pier and the Italian mob and my flatmates. Foremost I would like to thank my father, for everything he made possible for me, thanks for emotional and financial support, for good advice and trust. Thank you for always being there for me, I could not wish for a better father! Special thanks to my brother for the visit and a roadtrip that was only possible with him, you are the best! Thanks also to the rest of my family.

Table of Contents

Chapter 1 General Introduction 1.1. The dinoflagellate genus Alexandrium……………………………………………..……..3 1.2. Alexandrium and the synthesis of paralytic shellfish toxins………………………………4 1.3. The capacity to synthesize Paralytic Shellfish Toxins…………………………………….7 1.4. Regulation of PST production……………………………………………………………12 1.5. Growth and PST production of Alexandrium species……………………………………13 1.6. Light perception, the cell cycle and PST production……………………….……………13 1.7. Light, photosynthesis, nutritional status and PST synthesis………………….….………15 1.8. Alexandrium and bacteria………………………………………………………..…….....17

Chapter 2 Determination of the toxin profile of Alexandrium catenella ACCC01, Group IV ribotype, and the quantification of PSTs in extracts using the Lawrence method

2.1. Introduction……………………………………………………………………………..21 2.2. Material and Methods...... 22 2.2.1. PST analysis via UPLC using the Lawrence method...... 22 2.2.2. SPE-COOH fractionation for PST confirmation testing……….…………………...... 23 2.3. Results and Discussion……………..………………………………………………….24 2.3.1. Toxin Profile of A.catenella ACCC01…………………..………………………...... 24

Chapter 3 Gene expression and molecular evolution of sxtA4 in the saxitoxin producing dinoflagellate Alexandrium catenella

3.1. Abstract………………………………………………………………………………….31 3.2. Introduction ………………………………………………………………………….....31 3.3. Material and Methods……………………………………………...……………..…....33 3.3.1. Culture maintenance and quantification……..………………………………………..33 3.3.2. RNA extraction and DNAse treatment...... 34 3.3.3. cDNA synthesis ……………………………………………………..…………….….34 3.3.4. PCR primers……….…………………………….……………………………………34 3.3.5. Quantitative real- time PCR…………………………………………………………..35 3.3.6. DNA extraction, cloning, and sequencing of sxtA4 amplified from gDNA and cDNA...... 36

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3.3.7. Toxin extraction……………………………………………………………………....37 3.3.8. Determination of PST concentrations……………………………………………...…37 3.4. Results………...…………………………………………………………………………38 3.4.1. Culture growth and growth rate……………………………………………………....38 3.4.2. Primer specificity………………………………………………………………….….39 3.4.3. Reference gene expression stability……………………………………………….….39 3.4.4. Expression normalization of sxtA4……………………………..………………….…40 3.4.5. Toxin analysis……………………………………………..………………………….40 3.4.6. Phylogenetic analysis ……………………………………………………….………..41 3.4.7. Sequence comparison of sxtA4 cDNA and gDNA……………………..…………….43 3.5. Discussion ……………………………………………………………………………….45 3.6. Conclusion……………………………………………………………………………….49

Chapter 4 The impact of light spectra on cell cycle progression, saxitoxin production and gene expression in Alexandrium catenella

4.1. Abstract...... 52 4.2. Introduction………………………………………………………………………..…...52 4.3. Material and Methods……………………………………………………………….....55

4.3.1. Blue, red and white light experiment…………………………………………….…..55 4.3.2. RNA extraction and DNAse treatment...... 55 4.3.3. cDNA synthesis …………………………………………………………………..…56 4.3.4. Primers……………………………………………………………………………….56 4.3.5. Quantitative Real time PCR…………………………………………………..……...57 4.3.6. Statistical analyses…………………………………………………………………...58 4.3.7. Toxin extraction……………………………………………………………………...58 4.3.8. Determination of toxin concentration ……………….…….…………………..….…58 4.3.9. Flow Cytometric analysis …………………………………………………………....59 4.4. Results ...... 59 4.4.1. Cell cycle...... 60 4.4.2. Relative gene expression of sxtA4 and psbA...... 62 4.4.3. PST production of A. catenella during the diel cycle...... 64 4.5. Discussion………………………………………………………………….…………….67 4.5.1. Gene expression of sxtA4 and psbA...... 68 4.5.2. Cell cycle progression in A. catenella...... 69

4.5.3. PST synthesis...... 70 4.6. Conclusion ………………………………………………………….…………………..71

Chapter 5 Bacterial communities associated with toxic and non-toxic Alexandrium tamarense, Group V strains 5.1. Abstract...... 74 5.2. Introduction...... 74 5.3. Material and Methods...... 76 5.3.1. Culturing...... 76 5.3.2. DNA extraction and PCR...... 77 5.3.3. Automated Ribosomal Intergenic Spacer Analysis (ARISA)...... 77 5.3.4. 16S rRNA pyrosequencing ...... 78 5.3.5. Acetylene reduction Assay...... 78 5.3.6. Phylogenetic analysis...... 79 5.4. Results...... 79 5.4.1. Diversity of microbial communities………………………………………………....79 5.4.2. The dominant bacterial taxa in Alexandrium tamarense...... 80 5.4.3. Phylogenetic Analysis...... 88 5.4.4. ARISA...... 88 5.4.5. Acetylene Reduction Test...... 90 5.5. Discussion...... 91 5.6. Future studies and directions ...... 95

Chapter 6 The impact of light quality on paralytic shellfish toxin synthesis by Alexandrium catenella

6.1. Abstract………………………………………………………………………..……….99 6.2. Introduction ………………………………………………………………..…………100 6.3. Material and Methods…………………………………………………….…………..102 6.3.1. Culture growth conditions…………………………………………………………..102 6.3.2. Pigment extraction and quantification……………………………………………...103 6.3.3. Statistical analyses……………………………………………………………….....104 6.3.4. Toxin extraction…………………………………………………………………….104 6.3.5. Determination of toxin concentration per cell/ UPLC ……………………………..104 6.3.6. DNA extraction and PCR...... 104 v

6.3.7. 16S pyrosequencing and 16 S rRNA PCR...... 105 6.4. Results …………………………………………………..……………………………..106 6.4.1. Growth rate ………………………………………………………………………...106 6.4.2. Growth rate and PST synthesis…….……………………………………………….106 6.4.3. Pigments extracts of A. catenella cells grown in red, blue and white light....……...109 6.4.4. Pigment synthesis and growth rate……………………………………….……..…..114 6.4.5. Pigment and PST synthesis……………………………………………..…………..114 6.4.6. Bacterial communities associated with Alexandrium catenella grown in white blue and red light………………………………………………………………...... 115 6.5. Discussion …………………………………………………..…………………..…...... 116 6.5.1. Summary………………………………………………………………………...... 116 6.5.2. Growth rate ………………………………………………………………………...117 6.5.3. Absorption spectra and pigment synthesis………………………………….……....117 6.5.4. PST synthesis……………………………………………………………..………...118 6.5.5. Bacterial communities of A. catenella grown in red, blue and white light…………119 6.5.6. Bacterial communities of A. catenella in comparison with the bacterial communities of A.tamarense ATNWB01 and ATCJ33 (Chapter 5)……………...... 121 6.6. Conclusion and future studies……………………………………….……………...... 121

Chapter 7 Conclusion and future studies

7.1. Transcriptional regulation and molecular evolution of sxt genes in dinoflagellates……125 7.2. Photoperception cell cycle progression, PST production and gene expression ……...... 127 7.3. Bacteria associated with Alexandrium……………………………………………….....128 7.4. The impact of ligh quality on PST synthesis…………………………………………...131

APPENDIX A Publication “Neurotoxic Alkaloids: Saixtoxin and Its Analogues”...... 133 APPENDIX B PST standards……………………………………………………………135 APPENDIX C CTAB buffer for DNA extraction ………………………...……………139 APPENDIX D GSe Media………………………………………………...…………...... 142 APPENDIX E Aligned sxtA4 sequences…………………………………………………145

References...... ………...166

List of publications and presentations

Publications:

Wiese M., D’Agostino P. M., Mihali T. K., Moffitt M. C., Neilan BA., 2010. "Neurotoxic Alkaloids: Saxitoxin and Its Analogs." Mar. Drugs 8, no. 7: 2185-2211.

Murray SA., Wiese M., Stüken A., Brett S., Kellmann R., Hallegraeff G., Neilan BA. “sxtA- based quantitative molecular assay to identify saxitoxin-producing harmful algal blooms in marine waters.” Appl. Environ. Microbiol. 2011 Oct; 77(19):7050-7.

Murray SA., Wiese M., Neilan BA., Orr R. J.S., de Salas M., Brett S., Hallegraeff G.. A reinvestigation of saxitoxin production and sxtA in the ‘non-toxic’ Alexandrium tamarense Group V clade. Harmful Algae, Volume 18, June 2012, Pages 96-104

Poster presentations:

Wiese M, Murray SA, Mihali T, Hallegraeff G, Neilan BA (2010) Expression of the saxitoxin synthesis pathway enzyme sxtA4 in Alexandrium catenella. 14th International Conference on Harmful Algae, Hersonissos, Crete-Greece.

Wiese M, Murray SA, Neilan BA (2011) The role of light spectra on the circadian clock and gene expression in the saxitoxin producing microalgae Alexandrium catenella. Plant Organellar Signaling - from Algae to Higher Plants. Primosten- Croatia.

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List of Abbreviations

ANOVA analysis of variance BSA bovine serum albumin bp base pair cDNA complementary deoxynucleic acid CNP gene copy-number polymorphism CT cycle threshold EST expressed sequence tag Ex excitation Em emission HAB harmful algal bloom HCL hydrochloric acid mRNA messenger ribonucleic acid NaCl sodium chloride SAM s`adenosyl methionine synthase SEM scanning electron microscopy STX saxitoxin PBS phosphate buffered saline PCP peridinin- chlorophyll a protein PST paralytic shellfish toxins RT-qPCR quantitative reverse transcription polymerase chain reaction LSU large subunit SNP single nucleotide polymorphism UPLC ultra performance liquid chromatography

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List of Figures

Figure 1.1.: SEM of Alexandrium catenella…………….....……….………………………...... 3 Figure 1.2.: Hypothetical biosynthetic pathway of STX……………………..…………...... 8 Figure 1.3.: The putative pathway of STX biosynthesis in cyanobacteria...... 9 Figure 1.4.: The structure of sxtA in dinoflagellates and cyanobacteria……………...... 11 Figure 1.5.: Basic illustration of the depth at which different colors of light penetrate ocean waters...... 16 Figure 2.3.1.: Chromatograms of a representative A. catenella culture extract….....………...25 Figure 2.3.2.: PSP confirmation analysis chromatograms from a representative A. catenella ACCC01 extract. …………………………………………...………………………………...26 Figure 2.3.3.: Spike recovery..……..……………………………………………………...…….…...27 Figure 2.3.4.: Unoxidized sample extract. …………………………………………….……..28 Figure 3.4.1.: Growth curve of triplicate cultures of A. catenella ACCC01 …………………38 Figure 3.4.2.: PST analogs in Mol percent…………………………………………………...40 Figure 3.4.3.: Results of the phylogenetic analysis of genomic copies of sxtA4 from different Alexandrium strains and Gymnodinium catenatum, including the strain A. catenella ACCC01 sequenced in this study ……………………...………………………………………...……..42 Figure 3.4.4.: SxtA gene model and nucleotide acid sequences of sxtA4 of A. catenella ACCC01 derived from mRNA and gDNA...... 44 Figure 4.4.1.: Percentage of A.catenella cells in G1 phase ...... ……………………...…….60 Figure 4.4.2.: Percentage of A.catenella cells in G1 phase (left Y-axis), and percentages of cells in G2 and S-phase (right Y-axis) at different circadian hours grown in red light. …………………………………………………………………………………………….…..61 Figure 4.4.3.: Total average PST per cell (left Y-axis) of A.catenella and the average percentange of cells in S-phase (right Y-axis) when cells were grown in red, blue and white light...... 62 Figure 4.4.4.: Relative expression of sxtA4 and psbA during the light and dark...... 63 Figure 4.4.5.: Relative expression of sxtA4 in red, blue and white light……………………..63 Figure 4.4.6.: Relative expression of psbA in red, blue and white light……………………...64 Figure 4.4.7.: Production of PSTs by A. catenella ACCC01 at the circadian hours 1,3,7,10,12 during the light phase and at the circadian hour 24 (here -1) during the dark……………………………………………………………………………………………65 Figure 4.4.8.1.: Percentages of the PST analogs GTX – 1,4, GTX – 2,3, Neo – STX, STX produced by A. catenella when grown in white light...... 66 ix

Figure 4.4.8.2.: Percentages of the PST analogs GTX – 1,4, GTX – 2,3, Neo –-STX, STX produced by A. catenella when grown in red light...... 67 Figure 4.4.8.3: Percentages of the PST analogs GTX – 1,4, GTX – 2,3,Neo – STX, STX produced by A. catenella when grown in blue light.……………………………………………....67 Figure 5.4.1.: Bacterial community composition in the saxitoxin producing Alexandrium tamarense strain ATNWB01 and the non-toxic Alexandrium tamarense strain ATCJ33 analyzed on the family level...... 81 Figure 5.4.2.: Phylogenetic analysis of the dominant Rhodobacterales populations in A. tamarense Group V strains, ATNWB01 and ATCJ33...... 87 Figure 5.4.3.: UPMGA cluster analysis of automated ribosomal intergenic spacer analysis (ARISA)...... 89 Figure 5.4.4.: UPMGA cluster analysis of automated ribosomal intergenic spacer analysis (ARISA)...... 90 Figure 6.3.1.: Transmission profiles of the blue Roscolux (R367), the red Roscolux (R19) and the neutral density filter (Lee 210)……………………………..…………………………....103 Figure 6.4.1.: Growth of A. catenella ACCC01 over a period of 40 days at 40 µmol m-1 s-1 at a 12h L: D cycle at 18°C in white, red and blue light. …………..……………………………106 Figure 6.4.2.: Total average PST production and growth rate of A.catenella grown in blue, red and white light at 40 µmol m-2 sec-1. ……………………………………………………...... 107 Figure 6.4.3.: PST profile of A. catenella ACCC01 grown in red light…..…….…….….....108 Figure 6.4.4.: PST profile of A. catenella ACCC01 grown in white light………………...... 108 Figure 6.4.5.: PST profile of A. catenella ACCC01 grown in blue light...………..…….…..109 Figure 6.4.6: Absorption spectra (400 nm – 800 nm) of pigment extracts from A. catenella cultures grown in red, blue and white light…………………………………………………110 Figure 6.4.7.: Absorption spectra in the region of orange light (580 nm – 640 nm) of pigment extracts from A. catenella cultures grown in red, blue and white light………...…………...111 Figure 6.4.8.: Absorption of pigment extracts at 590 nm…………………………………...111 Figure 6.4.9.: Absorption spectra in the region of green light (458 nm – 553nm) of pigment extracts from A. catenella cultures grown in red, blue and white light light. ………………………………………………….…………………………………………....112 Figure 6.4.10.: Absorption of pigment extracts at 442 nm………………………………….112 Figure 6.4.11.: Absorption spectra in the red light region 620 nm – 800 nm, normalized at 442 nm……………………………………………………………………...... 113

Figure 6.4.12: The chlorophyll a/c ratio of A. catenella grown in blue, red and white light………………………………………………………………………………………….113 Figure 6.4.13: Growth rate and total average chlorophyll a + c content of A. catenella cultures grown in blue, red and white light…………………………………………………………..114 Figure 6.4.14: Total average PST and total average chlorophyll a +c content (pg cell-1) of A. catenella ACCC01 when grown in blue, red and white light………………………….……115 Figure 6.4.15.: Bacterial community composition on family level of A. catenella cells grown in white, red and blue light (sampled at day 14)………………………………...... 116

List of Tables Table 1.1.: Relative toxicity of paralytic shellfish toxins...... 6 Table 3.3.1.: Gene names, Primer sequences, Annealing temperature (AT), Amplicon, (AP) sizes in base pairs (bp), references……………………………………………………...35 Table 3.4.1.: Relative Expression ratio of sxtA4, growth rate and toxin content of A. catenella ACCC01..……………………………………………………………………………………..40 Table 3.4.2: Loci of the sxtA4 sequences derived from cDNA and gDNA that differed thoughout the clone pools……………………………….………………………………..…..45 Table 4.3.1.: Gene names, Primer sequences, Annealing temperature (AT), Amplicon (AP) sizes in base pairs (bp), references ……………………………………………...……………57 Table 4.4.1.: Average percentage of analogs present during the circadian hours tested...... 65 Table 4.4.2. Average Mol% of analogs present during the circadian hours...... 66 Table 5.4.1.: Bacterial OTUs present in the non-toxic ATCJ33 and not in the toxic ATNWB01 strain...... 82 Table 5.4.2.: Bacterial OTUs present in the toxic ATNWB01 and not in the non-toxic ATCJ33 strain...... 83 Table 5.4.3: Bacterial OTUs present in the toxic ATNWB01 and not in the non-toxic ATCJ33……………..………………………………………………………………………...85 Table 5.4.5.: Acetylene Reduction Assay…………………………………………………….90

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Chapter 1 General Introduction

1.1. The dinoflagellate genus Alexandrium Alexandrium is a dinoﬂagellate genus of the order Gonyaulacales, that currently contains more than 30 morphologically defined species. Of these around half are known to produce toxins, mostly saxitoxin (STX) and its analogues (Anderson et al., 2011; Balech, 1985). The genus is subdivided primarily on the basis of differences of shape of particular thecal plates; the presence or absence of a ventral pore; ornamentation in a few species, plus cell size, shape, and chain formation (for example, see Figure 1.1.) (Balech, 1985). Within the genus Alexandrium, A. tamarense, A. fundyense, and A. catenella comprise a closely related cosmopolitan toxigenic grouping of ‘‘morphospecies’’ the ‘‘Alexandrium tamarense’’ species complex, which plays a prominent role in Harmful Algal Blooms (HABs) (John et al., 2003; Scholin et al., 1998).

Figure 1.1.: SEM of Alexandrium catenella from Melbourne Australia. (Hallegraeff et al., 1991)

Chapter 1 General Introduction

When present in high cell numbers, species of Alexandrium can cause HABs and a variety of associated environmental and public health problems (Hallegraeff, 1993; Smayda, 1990). The diversity of toxic species is accompanied by a diversity among strains of those species with respect to temperature requirements, toxicity and bioluminescence. Equally diverse are the nutritional strategies, including the ability to utilize a range of inorganic and organic nutrient sources, and feeding by ingestion of other organisms (Anderson et al., 2011). Behavioral adaptations of this genus such as vertical migration are furthermore important features in regard of optimized nutrient acquisition (MacIntyre et al., 1997). Alexandrium species are capable of colonizing a wide spectrum of hydrographic regimes and have been reported to thrive in coastal, shelf and slope waters of subarctic, temperate and tropical regions of the Northern and Southern Hemispheres (Lilly et al., 2005; Taylor et al., 2008). Alexandrium has also the ability to persist through time, displaying a great adaptability and resilience. Cysts formed by Alexandrium are highly resistant to decay. They have been found in a wide range of environmental conditions and are known to survive for up to a hundred years (Furio et al., 2012; Miyazono et al., 2012). The biogeographic range of these species has expanded considerably over the last decades (Anderson et al., 2002; Hallegraeff, 1998). The natural expansion has been augmented by human activities such as ballast water discharge or shellfish stock transfers (Bolch and de Salas, 2007). Therefore, there is increasing interest to understand the regulation of growth, bloom development, and toxin production in species of Alexandrium.

1.2. Alexandrium and the synthesis of paralytic shellfish toxins Alexandrium catenella was the first dinoflagellate to be linked to Paralytic Shellfish Poisoning (PSP), initially by the positive correlation of dinoflagellate concentration in seawater with mussel toxicity (Sommer et al., 1937) and later by purification and extraction of the toxins from cultured cells (Schantz et al., 1966). Saxitoxin and its analogues are hence commonly referred to as parayltic shellfish toxins (PSTs) (Sommer et al., 1937). The toxin profile is a relatively conservative characteristic within an isolate or natural population (Cembella, 1998). Usually a PST- producing organism synthesizes a characteristic suite of PSTs. These analogs differ in side group moieties and also differ in specific toxicities (Table 1.1.) modified from (Wiese et al., 2010), full publication is attached, Appendix A. Variability in toxin profile has been reported to occur due to environmental changes and the manipulation of culture conditions. Changes in toxin profiles have been reported in cultures of advanced

Chapter 1 General Introduction

senescence, or under chronic nutrient-limitation, between different life stages and due to various variations in environmental factors such as salinity and light (Anderson et al., 1990; Boczar et al., 1988; Hamasaki et al., 2001; Persson et al., 2012). A lack of toxicity has been frequently reported in some strains of Alexandrium, even among isolates and natural populations of species which are known to be capable of toxin production, e.g. non-toxic genotypes of A. tamarense, A. ostenfeldii, Gymnodinium catenatum (Cembella et al., 1987; Higman et al., 2001; MacKenzie and Berkett, 1997; Murray et al., 2012; Oshima et al., 1993; Taroncher-Oldenburg et al., 1999; Wang et al., 2012). Variation in toxicity per cell among the bloom population in the same area are also prominent in natural ecosystems (Anderson et al., 1990a; Maranda et al., 1985; White, 1986). and several studies have shown that cultured Alexandrium cells are typically less toxic than the ones collected from natural populations in the same region (Montoya et al., 2010; White, 1986). There is no clear explanation for these observations. It has been proposed to be due to a relaxation of the selective pressure for high toxin production in natural populations, genetic drift in culture expressed and reduced toxin biosynthetic enzyme activity, or a higher cell division rates in culture, resulting in reduction of cell toxin quota (Cembella et al., 1998).

Chapter 1 General Introduction

Table 1.1.: Relative toxicity of paralytic shellfish toxins. Toxicity of the PSTs due to change in moiety is listed in descending order. Data obtained from (Usleber et al., 1997)

Structure Ω Toxin Relative toxicity Φ

O Non-Sulfated O H2N H R1 N N + NH2 STX 1

+ N H2N N OH OH NeoSTX 05-1.1 H H

O Mono-sulfated O H2N H R1 N N + ¥ NH2 GTX1/4 0.39/1.09-0.48/0.76 + N N H2N OH OH GTX2/3¥ 0.8/0.33-0.9/0.9 R2 R3

HO Decarbamoylated H H N dcSTX 0.43 N + NH2

+ N N H2N OH dcNeoSTX 0.43 OH H H dcGTX1-4 0.18-0.45

O Di-sulfated -O S O 3 N H H R1 N N + NH2 N + N OH H 2N C1-4 <0.01-0.14 OH R R 2 3

Ω Refer to Table 1 for assigned R groups. Moieties highlighted in red differentiate from the structure of STX; ¥ α/β epimeric mixture; Φ Relative toxicity based on the mouse bioassay results obtained from (Genenah and Shimizu, 1981; Oshima, 1989; Sullivan et al., 1985; Usleber et al., 1997) Table modified according to (Wiese et al., 2010)

Chapter 1 General Introduction

1.3. The capacity to synthesize Paralytic Shellfish Toxins The intriguing aspect of saxitoxin synthesis is that it is associated with species from two distantly related kingdoms of life, marine dinoflagellates and fresh- and brackish- cyanobacteria (Carmichael, 1994; Sommer et al., 1937). Marine dinoflagellates such as Alexandrium spp., Pyrodinium bahamense and Gymnodinium catenatum and certain species of cyanobacteria from the genera Anabaena (Mihali et al., 2009; Moustafa et al., 2009) Aphanizomenen (Mihali et al., 2009), Cylindrospermopsis (Kellmann et al., 2008) and Lyngbya (Mihali et al., 2011) are known to produce PSTs. These toxins have been also detected in freshwater and marine species of puffer fish (Nakashima et al., 2004; Sato et al., 1997; Zaman et al., 1997), the red alga Jania sp. (Kotaki et al., 1983), the skin of the Panamanian Golden frog Atelopus zetekii (Yotsu-Yamashita et al., 2004), in octopi (Robertson et al., 2004) and bacteria isolated from dinoflagellate cells (Gallacher et al., 1997; Kodama, 1990 ). The common hypothesis is that the PSP toxin biosynthesis is carried out in both cyanobacteria and dinoflagellates, through the same biosynthetic pathway, using homologous genes, possibly obtained by the dinoflagellates via horizontal gene transfer (Shimizu, 1996; Stüken et al., 2011). Nevertheless Hackett et al presented results and suggested that the STX synthesis pathway was likely assembled independently in the distantly related cyanobacteria and dinoflagellates, although using some evolutionarily related proteins (Hackett et al., 2012). The toxins appear to be synthesized by similar processes, precursor incorporation patterns and stereochemistry are identical in cyanobacteria and dinoflagellates (Shimizu, 1996). A hypothetical biosynthesis pathway of STX was proposed by Shimizu et al. (1984) (Shimizu et al., 1984). The biosynthetic pathway was further described by Kellmann et al (2008) (Figure 1.2.). The hypothetical intermediate metabolites are labeled with letters in brackets. The reaction steps are as follows: 1, Claisen condensation reaction between acetate and arginine; 2, amidino transfer from a second arginine to the α-amino group of intermediate B; 3, cyclization; 4, introduction of SAM methyl-derived side chain, involving the loss of one methionine methyl hydride; 5, epoxidation of side chain, leading to a 1,2-H shift; 6, opening of epoxide to an aldehyde followed by reduction of the aldehyde; 7 and 8, carbamoyl transfer and dihydroxylation ( Kellmann et al., 2008).

Chapter 1 General Introduction

Figure 1.2.: Hypothetical biosynthetic pathway of STX (Kellmann et al., 2008)

The finding of the genetic basis for the biosynthesis of saxitoxin has revealed a highly complex sequence of reactions, involving over 30 biosynthetic steps encoded by up to 26 genes clustered at one genomic locus, sxt (Kellmann et al., 2008). The gene cluster that is putatively responsible for the synthesis of PSTs, has been identiﬁed in ﬁve species of cyanobacteria, (Mihali et al., 2009; Moustafa et al., 2009; Stüken et al., 2011) and a putative sequence of reactions has been proposed Figure1.3; (Kellmann et al., 2008).

Chapter 1 General Introduction

Figure 1.3. : The putative pathway of STX biosynthesis in cyanobacteria Biosynthesis is initiated with sxtA, which contains four catalytic domains: a methyltransferase domain (sxtA1, MTP), a GNAT domain (sxtA2, ACTF) (loading of acyl carrier protein), an acyl carrier protein domain (sxtA3, ACP), and an AONS domain (sxtA4, AONS) (condensation domain) (Kellmann et al., 2008).

The enormous genome size of dinoflagellates (Lin, 2011; Rizzo, 1987) hampers the identification of genes putatively associated with STX production. Stüken et al (2011) screened large EST libraries for genes homologous to the sxt genes sequenced in the five cyanobacteria. This large EST library approach facilitated the detection of saxitoxin- biosynthesis associated genes and transcripts in dinoflagellates (Stüken et al., 2011). Contigs with a good alignment score and a significant e value were recovered for sxtG. Less significant matches were recovered for the other core biosynthesis genes sxtB, sxtF/M, sxtH/T, sxtI, sxtR and sxtU. No matches were found for the remaining STX genes. All the genes recovered from Alexandrium EST libraries were highly different from the cyanobacterial genes (Stüken et al., 2011). The only gene in the Alexandrium EST libraries which showed significant sequence similarity (bit score ˃ 55) and a highly significant e-value (

Chapter 1 General Introduction

The gene sxtA, encodes the enzyme proposed to initiate the synthesis of STX, sxtA has four catalytic domains with predicted activities of SAM-dependent methyltransferase (sxtA1), GCN-5 related N-acetyltransferase (sxtA2), acyl carrier protein (sxtA3), a class II aminotransferase (sxtA4) (Kellmann et al., 2008). The entire sxtA gene from Alexandrium was amplified by RACE- PCR analysis and normal PCR analysis (Figure 1.4.). Two different sxtA-like transcript families were obtained; the transcripts differed in their sequences, lengths and the number of sxtA domains that were encoded. The longer transcripts contained all four domains present in the known cyanobacterial sxtA genes, however, the shorter transcripts lacked the terminal aminotransferase domain. In contrast to the bacterial homologs, the dinoflagellate transcripts are monocistronic, have a higher GC content and occur in multiple copies up to 200 copies. Furthermore, the transcripts contain typical dinoflagellate spliced- leader (SL) sequences and eukaryotic polyA-tails. Thus the presence of SL sequence at the 5` ends, the poly-A at the 3` end and the high GC content characteristic of dinoflagellates indicates that the gene sxtA is encoded in the dinoflagellate genome. The investigation of 28 saxitoxin-producing and non-producing dinoflagellate strains from six different genera, for the presence of genomic sxtA homologs revealed a good correlation between the presence of sxtA and saxitoxin-synthesis. The exception was found in three strains of A. tamarense, for which sxtA was amplified, but the toxin was not detected (Stüken et al., 2011). However, some strains of this ribotype of Alexandrium tamarense (Group V) were shown to be capable of toxin production (Murray et al., 2012). The high sequence and domain structure similarity indicates that it is indeed homologous to the cyanobacterial sxtA gene and might have a common origin. These findings fa cilitate the possibility of the development of molecular tools for the investigation of gene expression in dinoflagellates.

Chapter 1 General Introduction

Figure 1.4: The structure of sxtA in dinoflagellates and cyanobacteria. a) Transcript structure of sxtA4 transcripts in A.fundyense CCMP1719. b) Genomic sxtA4 structure of C.raciborskii T3. (Stüken et al., 2011).

At least the putative sxtA, and possibly other sxt genes, are encoded in the nuclear genome of dinoflagellates and therefore STX-synthesis in dinoflagellates has been reported not to originate from co-cultured bacteria (Stüken et al., 2011). Bacteria may still, however, play an important role in modulating STX biosynthesis in dinoflagellates (Ho et al., 2006; Hold et al., 2001a; Stüken et al., 2011). Dinoflagellates display some unique features of cell biology (Rizzo, 1987) therefore research of the genetic regulation in these organisms is challenging. The nucleus of dinoflagellates is unlike that of any other eukaryote, because the chromosomes are condensed throughout the cell cycle except during DNA replication (Rizzo, 1987) Dinoflagellate nuclei also contain vast amounts of DNA compared to other eukaryotes, estimates range from 3-250 pg·cell-1, or approximately 3,000-215,000 megabases (MB) (Spector et al., 1981). The dinoflagellate nucleus contains such a high concentration of DNA that it exists in a liquid crystal state, which is responsible for its unique morphology (Gautier et al., 1986; Livolant and Bouligand, 1978). In dinoflagellates, genes may occur in multiple identical or non-identical copies, this is probably due to the highly unusual genetic mechanisms of these organisms, such as the recycling of processed cDNAs (Bachvaroff, 2008; Le et al., 1997; Slamovits and Keeling, 2008). Transcriptional regulation of genes in STX-producing Alexandrium species has been reported to be stimulated by abiotic factors, such as nitrogen and biotic factors such as the presence of bacteria (Lee et al., 2009; Moustafa et al., 2010).

Chapter 1 General Introduction

In dinoflagellates, gene regulation on the transcriptional level is thought to play a minor role compared to its role in other investigated eukaryotes. For example, microarray studies suggested that only about 10-27% of genes might be regulated transcriptionally (Erdner and Anderson, 2006; Lidie et al., 2005; Lin, 2011; Lin et al., 2010). Other studies of dinoflagellate gene expression have indicated that these organisms use both transcriptional and posttranscriptional regulation in roughly equal measure, depending on the stimulus (Okamoto et al., 2001). The trans-splicing system in dinoflagellates may provide an additional level of regulation (Bachvaroff, 2008). Dinoflagellate transcripts of nuclear encoded genes have polyA-tails and a unique dinoflagellate spliced-leader sequence, a conserved 22 base pair (bp) sequence. Spliced-leader sequences are small, non-coding RNAs that are trans-spliced onto the 5′end of mRNAs, in dinoflagellates, this process converts polycistronic transcripts into translatable monocistronic mRNAs (Bachvaroff, 2008; Lidie and Van Dolah, 2007; Stüken et al., 2011; Van Dolah et al., 2007a; Zhang et al., 2007).

1.4. Regulation of PST production Due to the lack of evidence of their involvement in known pathways of primary and intermediary metabolism, the PSTs have been deemed to be secondary metabolites (Cembella et al., 1998). Many studies have discussed the potential eco-physiological role of these compounds. Different roles of PSTs for the organisms have been hypothesized, such as nitrogen storage, a role in chromosome structure organization (Anderson and Cheng, 1988), chemical defense and pheromones (Cembella et al., 1998; Jasti et al., 2005; Wohlrab et al., 2010; Wyatt and Jenkinson, 1997). Recently it has been also proposed that the production of the GTX V analogs might be part of the dinoﬂagellates iron acquisition system (Stewart, 2011). Regardless of the origin of the biosynthetic genes, either derived via evolution from a common ancestor or as a secondarily acquired characteristic, the retention of this complex and metabolically expensive pathway indicates, that it is likely to provide a selective advantage in possessing organisms (Cembella et al., 1998).

Chapter 1 General Introduction

1.5. Growth and PST production of Alexandrium species Due to the high potency of PSTs, PSP outbreaks can occur when cell densities are very low. As few as 100-200 cells L-1 can lead to detectable PST levels in shellfish (Anderson, 1997; Anderson et al., 2002; Townsend et al., 2001). Most studies on PST toxin production are conducted in batch cultures, in which a shifting of the equilibrium of cell density and ambient nutrient variables can lead to unbalanced growth, particularly outside of the exponential phase. Growth in batch cultures is divided into three growth stages: lag phase, exponential phase and stationary phase. The dynamics of saxitoxin production have been investigated at different cell densities, growth stages and growth rates (Anderson et al., 1990; Boczar et al., 1988; Parkhill and Cembella, 1999). All previous studies have reported constitutive production of STX during growth in batch culture. Reports on the highest level of toxin production during these different growth phases have varied. Highest concentrations of saxitoxin production have been observed during the mid-exponential growth phase while other studies have reported an increase in toxin production in the stationary phase (Boczar et al., 1988; Lim et al., 2005; Parkhill and Cembella, 1999). Exogenous environmental factors influencing growth rate can be of abiotic or biotic nature (Anderson et al., 2011; Bolch et al., 2011; Ferrier et al., 2002). The relationship between cellular toxicity, environmental factors and growth rate is complex and not entirely consistent among or even within species. A multi- variable laboratory study of toxin production in A. tamarense indicated that cellular toxicity was independent of exogenous environmental factors throughout exponential growth phase, although it varied over the growth stages (Cembella, 1998; Cembella et al., 1987). Dinoflagellates are known for “slow” growth rates, maximal rates in laboratory cultures are typically 0.5 to 0.7 divisions day-1 (Cembella, 1998; Taroncher-Oldenburg et al., 1997). PST producing dinoflagellates do not seem to be clearly r (high reproductive rate, little investment in each progeny) - or K-selected (low reproductive rate, large investment in each progeny) based on in situ- growth rates, in line with their classification as species of nutrient-enriched waters (Smayda and Reynolds, 2001; Stolte and Garces, 2006, MacArthur et al. 2001).

1.6. Light perception, the cell cycle and PST production Light-perceiving organisms can exhibit circadian rhythms, which are reflected in gene activity, metabolism and physiology (Panda et al., 2002). The photoperiod provides the major input signal that serves to entrain the circadian rhythm (Roenneberg and Merrow, 1998). Circadian rhythms are oscillations in biochemical, physiological, and behavioral functions of an organism with a periodicity of approximately one d(ay Sancar, 2003). Such rhythms are 13

Chapter 1 General Introduction

the key regulators of many facets of the physiology and behavior of dinoflagellates, including photosynthesis, vertical migration, bioluminescence and cell division. In many dinoflagellate species the cell division cycles are phased by photocycles (Brunelle et al., 2007; Chisholm and Brand, 1981). In nature photoperception is mediated via five types of sensory photoreceptors BLUF- proteins, cryptochromes, phototropins, phytochromes, and rhodopsins (Hegemann, 2008). Differential effects of red and blue light on gene expression and progression of photo- controlled behavior have been reported in plants, animals and humans (Ahmad et al., 1995; Chaves et al., 2011; Egan et al., 1999; Panda et al., 2002). The intracellular signaling pathways that mediate the cues of photoperception and photoreceptors have not been studied for many dinoflagellates. Both red and blue light have been implicated in diel entrainment of the cell cycle in the dinoflagellates Karenia brevis and Gonyaulax polyedra (Brunelle et al., 2007; Roenneberg and Deng, 1997; Roenneberg and Hastings, 1988). In all photosynthetic dinoflagellate species studied, photoperiodic entrainment of the cell cycle results in the synchronous progression of the population through G1, S, G2 and M phases. In dinoflagellates with a generation time less than one day, only a percentage of the population enters the cell cycle on any given day, with the rest of the population remaining in G1 of the cell cycle (Chisholm and Brand, 1981; Roenneberg and Hastings, 1988). Little is known about photoperception of Alexandrium species and the regulation of circadian rhythms through different light receptors. It is also not fully understood if and how PST production is regulated by the circadian rhythm. PST production has been correlated with cell cycle progression during the diel cycle, nevertheless reports were inconsistent (Harlow et al., 2007; Taroncher-Oldenburg et al., 1997, 1999). Light has been suggested to set the pace for toxin production by Alexandrium fundyense, PST production was reported to be discontinious over the cell cycle and directly correlated to the duration of G1 phase during the light phase (Taroncher-Oldenburg et al., 1997, 1999). Siu et al reported that toxin content reached a maximum during the S- phase of the cell cycle of A. catenella (Siu et al., 1997). Harlow reported the net cellular PST production to be highest in the dark, before irradiance, when most (56%) of the cells are in the G2+M phase of the cell cycle in A. catenella (Harlow et al., 2007a). The reported conclusions about toxin production and cell cycle phase correlation are hence inconsistent, and suggest that differences in responses to the cell cycle may occur amongst different species or strains, or in response to specific culture conditions.

Chapter 1 General Introduction

1.7. Light, photosynthesis, nutritional status and PST synthesis To date, PSTs have only been found unequivocally to be produced by photosynthetic organisms. The direct and indirect effects of light, on PST production are multifaceted and complex. Toxin biosynthesis imposes an extra demand for photosynthetically derived carbon skeletons, e.g. for amino acids and acetate, as well as high energy light intermediates (e.g. ATP, NADH/NADPH, etc.) (Cembella, 1998). The production of nitrogen-rich PSTs might be also related to the photoassimilation of nitrate or ammonia into amino acid precursors (MacIsaac, 1978; Ogata et al., 1987; Syrett and Morris, 1963). Several studies reported variation in PST production levels at varying light intensity and growth phase (Ogata et al., 1987; Parkhill and Cembella, 1999). Ogata et al reported an increase in toxicity proportional with the decrease of growth rate, by lowering light intensity in A. tamarensis. However, increase of the toxicity was less remarkable, when the growth rate was lowered by decreasing light intensity compared to other environmental factors. Ogata et al hence concluded a photosynthetic impact on PST synthesis (Ogata et al., 1987). Parkhill et al (1999) reported that changes in toxicity were essentially independent of light, but varied over the growth stages, they concluded that toxicity may be affected by extrinsic factors, but it is not always a direct response (Parkhill and Cembella, 1999). Various other studies indicate that differences regarding an increase and decrease in toxicities, in response to lowered and increased light intensities exist amongst different Alexandrium species and strains (Boczar et al., 1988; Etheridge and Roesler, 2005; Fulco and Gayoso; Hamasaki et al., 2001; Hwang and Lu, 2000; Lim et al., 2006; Taroncher-Oldenburg and Anderson, 2000). Light intensity and spectral light quality penetrating the water column play a crucial role in the determination of photosynthetic rate and nutritional status of dinoflagellates. The intensity and spectral quality of light may vary markedly with depth of the water column, as there is a selective absorption of light in pure water. Photons with wavelengths from 400 to 480 nm (blue) are poorly captured by water molecules. The absorption of water begins to rise as wavelength increases above 550 nm and is significant in the red region (Kirk, 1994; Reynolds, 2006; Reynolds and Walsby, 1975). (Figure 1.5.). Alexandrium has a meroplanktonic life-cycle and also undertakes signiﬁcant vertical migration from nutrient- depleted well-lit surface waters, down to dark relatively nutrient replete waters encountering varying light intensities and spectral light qualities (Heaney and Eppley, 1981; McGillicuddy et al., 2005). The plastids allowing Alexandrium to photosynthesize are unique for dinoflagellates, and contain chlorophyll c and peridinin as the major carotenoid, chlorophyll a is present in a protein complex with peridinin called (PCP) (Boczar et al., 1980; Prezelin and 15

Chapter 1 General Introduction

Alberte, 1978; Prezelin and Triplett, 1989). These pigments determine which and how much light is used for photosynthesis, which is of major significance for the ecophysiology of Alexandrium.

Figure 1.5.: Basic illustration of the depth at which different colors of light penetrate ocean waters. Water absorbs light of long wavelength of red and orange colours, and it scatters light of shorter short wavelength light in the blue green colour range. (http://oceanexplorer.noaa.gov/explorations/04deepscope/background/deeplight/media/diagra m3.html)

Light quality is also likely to impact algal bacterial interactions (Maas and Brooks, 2010). Maas et al (2010) investigated the importance of light for PST synthesis in the dinoflagellate Alexandrium minutum and its bacterial consortium, they found that inhibition of photosynthesis resulted in changes of the toxin profile of A. minutum Anokoha and they observed a link with the presence of high nutrient requiring copiotrophic bacteria (Maas and Brooks, 2010).

Chapter 1 General Introduction

1.8. Alexandrium and bacteria The distribution and abundance of Alexandrium is defined by its interactions with its physical- chemical and biological environment and its ecological niche is largely defined by the physiological tolerance limits of abiotic factors such as temperature, salinity and light. However, relationships with the biological components of an ecosystem such as grazers, competing algal species and microbes, play an important role for its successful proliferation and survival (Kodama et al., 2006). The ecological significance of most naturally occurring bacterial- associations with HAB producing species is unclear. Bacteria exist as free living forms as well as attached to algal cells. They can also live within the dinoflagellate cell as symbionts, and can thrive even in the nucleus (Doucette, 1995; Doucette and Trick, 1995; Gallacher and Smith, 1999b; Maas et al., 2007; Silva, 1982; Sousa, 1978). These microbes can impact dinoflagellate growth either positively or negatively, and even impact transitions between the life history stages (Adachi et al., 2003; Bolch et al., 2011; Doucette et al., 1998; Ferrier et al., 2002). Bacteria may also play a role in providing various metabolites and micronutrients for the dinoflagellate, such as vitamins or iron, potentially equipping the dinoflagellate with a competititve advantage (Croft et al., 2006; Keshtacher-Liebso et al., 1995; Maldonado and Price, 1999). Recently, many dinoflagellates thought to be exclusively phototrophic species, have been revealed to be also capable of bacterivory and mixotrophy, such as the species Alexandrium tamarense and Alexandrium minutum (Du Yoo et al., 2009; Jacobson and Anderson, 1996; Jeong et al., 2005; Legrand and Carlsson, 1998; Nygaard and Tobiesen, 1993). Bacterial prey could hence also impact the nutritional status of the algae influencing the capacity of PST production and growth. However, mixotrophy in many Alexandrium species has not yet been explored and the involvement of bacteria in the production of PSTs is still elusive and controversial (Gallacher et al., 1999). Bacteria may contribute to toxicity in laboratory cultures, such as the observations of increased toxicity in non-axenic compared to axenic catenella and tamarense cultures (Hold et al., 2001; Uribe and Espejo, 2003). Some studies have reported an autonomous synthesis of STX by bacteria isolated from dinoflagellate cells (Gallacher, 1997; Kodama et al., 1982; Silva, 1990), bacteria are also implicated in the modification and biotransformation of algal toxins (Kotaki et al., 1985). In order to elucidate the contribution of particular bacterial species to dinoflagellate toxicity and bloom dynamics, it is essential to study the ecology of bacteria associated with marine dinoflagellates, such as Alexandrium spp. will be studied, initially requiring high resolution characterization of the bacteria associated with dinoflagellate cultures (Kopp et al., 1997). Following this, the combined effects of environmental and nutritional factors, and 17

Chapter 1 General Introduction

effects of bacteria, should be further studied to elucidate their involvement in the capacity for PST synthesis of different Alexandrium species.

. 18

Chapter 2 Determination of the toxin profile of Alexandrium catenella ACCC01, Group IV ribotype, and the quantification of PSTs in extracts using the Lawrence method

Chapter 2 Toxin analysis

2.1. Introduction Alexandrium catenella belongs to the A.tamarense- A.catenella- A.fundyense species complex, which comprises five groups (numbered I to V) defined on the basis of ribosomal DNA (rDNA) sequences (Lilly et al., 2007). The strain used in this study, ACCC01, a member of Group IV(Murray et al., 2011), was isolated from Cowan Creek, NSW, in the Sydney basin (31° 45`S and 121° 45`E), and was obtained from the culture collection of Prof Gustaaf Hallegraeff, University of Tasmania. A.catenella (Group IV) is the most prominent source related to PST findings in shellfish in New South Wales, these strains have been reported to produce mainly C1/C2 and GTX – 1,4 analogs (Hallegraeff et al., 1991; Murray et al., 2011; Negri et al., 2003). A. catenella strains from other geographic regions, such as A. catenella Group I from Chile and two strains of A. catenella (Group IV) from France have been found to produce GTX 5 as main analog of the profile (Aguilera-Belmonte et al., 2011; Lilly et al., 2002). It is hence crucial to evaluate toxin profiles of A.catenella strains in order to evaluate the toxicity and potential threats to the shellfish industry by local strains. The strain investigated in this study was found to produce GTX – 1,4, GTX – 2,3 STX, and Neo – STX. The toxin profile and per cell toxin quota of this strain of Alexandrium catenella were determined using a modified protocol based on the Lawrence method (AOAC official method 2005.06) (Lawrence et al., 2005); Harwood et al 2012 in prep.). Extracellular toxins have been neglected consistently throughout the experiments of this thesis. It is not known if there are extracellular PSTs in the culture supernatant of the A. catenella ACCC01. It was not possible to analyze more samples for the experiments within the budget and set up of this thesis. The principle of the Lawrence method involves pre-chromatographic oxidation of samples followed by liquid chromatography with fluorescence detection (LC-FLD). The oxidation products are more amenable to reversed phase separation than the parent toxins and they can be individually measured by fluorescence detection. Although the principal of monitoring hydrophilic PST oxidation products is simple, the chemistry is relatively complex. To aid with the analysis of commercial samples for regulatory purposes, a rapid screen test was developed to assess whether the PSTs are present, and a confirmatory test to accurately determine the contribution of each PST congener (Harwood et al 2012 in prep.). The PST screen method, which employs UPLC with fluorescence detection, uses periodate as the oxidant and allows for fast (6 min/sample) and sensitive detection of PSTs in samples with the requirement of only small sample volumes (Harwood et al 2012 in prep).

Chapter 2 Toxin analysis

However, the screen test does not distinguish between many PST congeners due to the co- elution of common fluorescent oxidation products. Depending on the PST profile observed an alternative oxidant, hydrogen peroxide, can be used to evaluate the contribution of non N- hydroxylated congeners to the toxin profile. Should a sample contain a complex mixture of PSTs, confirmation testing is required to determine the full PST profile. Consequently, the extracts must be fractionated using a SPE-COOH cartridge, which separates the extracts into three fractions of PSTs with varying charges, the C-toxins into the first fraction, the B and GTX and dcGTX toxins into the second fraction, and analogues without a negatively charged sulphate group such as STX, Neo – STX, dcSTX toxins into a third fraction. Each fraction is then oxidized with both periodate and peroxide, and then analyzed using the Lawrence method protocol described above ((Lawrence et al., 2005); Harwood et al 2012 in prep).

2.2. Material and Methods

2.2.1. PST analysis via UPLC using the Lawrence method Fourteen ml of Alexandrium catenella, Group IV, strain ACCC01 culture were centrifuged at 16,000g for 5 min, supernatant was discarded and cell pellets were stored at -20°C prior to toxin extraction. Toxins were extracted using 200 µl of 0.1 M HCL, through heating at 100 °C in a waterbath for 5 min (Ravn et al., 1995). The crude extracts were mixed by vortexing and centrifuged for 30 min at 16,000 g at 4°C to pellet insoluble debris. The supernatant was then transferred into a new 1.5 ml eppendorf tube. It was then centrifuged and transferred twice in order to acquire clear extracts, which were then stored at -20°C prior to analysis. UPLC was performed on a Waters ACQUITY UPLC coupled with a fluorescence detector (EX 340 nm, EM 395 nm). Chromatographic separation was achieved with a Kinetex 1.7µm C18, LC 100x 2.1 mm reversed phase analytical column (Phenomenex), eluted at 0.350 mL min-1. Mobile phases were (A) 0.1 M ammonium formate adjusted to pH 6 with 1% acetic acid, and (B) 90% of Mobile phase A with 10% methanol. The LC gradient consisted of 100% mobile phase A over 95% to 40% returning to 100 % after 4.55 min, continuing for another 1.45 min of 100% mobile phase A, with a total separation time of 6 min. Certified PST standards material was obtained from the Institute of Marine Biosciences, National Research Council of Canada (NRCC, Halifax, Nova Scotia, Canada). From this material calibration mixes were generated in order to identify the response of the various PST congeners. Each toxin was

Chapter 2 Toxin analysis quantitatively determined in the extracts by direct comparison to analytical standards at similar concentrations as anticipated in the samples. As suggested in the Lawrence method protocol, three analytical standard mixtures were used for quantification (Lawrence et al., 2005). The toxin mix solutions consisted of Mix 1: GTX – 1,4 and Neo – STX, Mix2: dcGTX – 2,3, dcSTX, GTX – 2,3 and STX, Mix 3: C 1,2, dcNeo, GTX 5. Each mix solution was analyzed at three different concentrations to enable calibration curves to be generated. Regression factors larger than 0.95 were regarded as acceptable. For PST analysis in samples, the peak area observed was compared to the relevant calibration - curve. Pre-column oxidation was performed with periodate (IO4 ) and hydrogen peroxide

(H2O2) in separate reactions (Lawrence et al., 2005); Harwood et al 2012 in prep). All A. catenella extracts were diluted 50- fold with MQ water prior to analysis, to ensure the level quantified remained within the calibration range of the method. All samples were initially analyzed following periodate oxidation to determine the likely PST profile, and then following hydrogen peroxide oxidation to determine the contribution of non N-hydroxylated toxins.

To ensure any observed peaks were due to the presence of PSTs and not due to fluorescent matrix components, several representative samples were analysed unoxidised. For confirmation testing, toxin extracts were fractionated using a SPE-COOH cartridge as described below. In this study, confirmatory analysis was used specifically to determine whether any C – 3,4 or GTX 6 was present in the samples, as the oxidation products of these PST congeners elute at the same retention time as GTX – 1,4 and NEO respectively. Furthermore, a representative sample was spiked to ensure recovery was acceptable. Spiking was performed with 20 µl of Standard Mix 1 which contains GTX – 1,4 and Neo – STX and 80 µl of A. catenella toxin extract sample, 20 µl of Standard Mix 1 were also run with 80 µl MQ water in order to assess spike recovery.

2.2.2. SPE-COOH fractionation for PST confirmation testing A 3 ml SPE-COOH cartridge (Bakerbond) was conditioned with 10 mL 0.01 M ammonium acetate. Two milliliters of the PSP-containing extract, generated for PSP screen testing, was passed through the cartridge and the effluent collected in a 15 mL plastic tube and then 4 mL of water were passed through the cartridge and collected into the same tube adding up to a final volume of 6.0 mL (Fraction 1). C-toxins elute in this fraction. Then, 4.0 mL of 0.05 mM NaCl solution was passed through the same cartridge, and collected in a test tube (Fraction 2). 23

Chapter 2 Toxin analysis

This fraction can contains GTX – 1,4, GTX – 2,3, GTX 5, GTX6 and dcGTX – 2,3 toxins. Finally, 5.0 mL of a 0.3 M NaCl solution was passed through the cartridge and collected in a plastic tube (Fraction 3). This fraction contains STX, NEO, dcSTX. The flow rate was kept between 2 and 3 mL min-1 for all elutions, without letting the cartridge run dry. All fractions were then oxidized with periodate and hydrogen peroxide and analyzed. The UPLC PST screen method was used for toxin quantification in the experiments outlined in Chapter 4 and 6.

2.3. Results and Discussion

2.3.1. Toxin Profile of A. catenella ACCC01 On a molar basis the strain of A. catenella investigated produces primarily GTX – 1,4 and Neo –STX, with low levels of GTX – 2,3 and STX. Periodate oxidation of the acidic A. catenella extracts resulted in 5 distinct chromatographic peaks with the retention times (RT) of 1.13 min, 1.68 min, 3.31 min, 3.82 min and 5.41 min (Figure 2.3.1. A). Comparison with the retention times of certified PST calibration standards (Appendix B) revealed that these peaks were likely due to GTX – 1,4 (RTs 1.13 min, 1.69 min and 3.8 min), Neo – SXT (RT 3.32 min ), GTX – 2,3 (RT 3.8 min) and SXT (RT 5.40 min). However, GTX – 1,4 and GTX – 2,3 have co-eluting oxidation peaks at RT 3.82 min. In addition, C – 3, 4 is known to co- elute with the early GTX – 1,4 peak with a retention time of 1.68 min and the late Neo – STX peak has the same retention time as STX at 5.4 min.

Chapter 2 Toxin analysis

Figure 2.3.1.: Chromatograms of a representative A. catenella culture extract. The extract was diluted 1/50 and oxidized with periodate (A) and peroxide (B) prior to analysis. A number of PST congeners give multiple fluorescent oxidation proucts, hence three peaks are detected for GTX – 1,4 and two for NEO – STX. GTX – 1,4 and Neo – STX do not produce fluorescent oxidation products with peroxide. In order to determine the contribution of N-hydroxylated PST analogues (GTX – 1,4 and Neo – STX) to the peaks detected in the periodate chromatogram, hydrogen peroxide was used to oxidize the samples. Only non N-hydroxylated analogues give fluorescent oxidation products with hydrogen peroxide. Oxidation of the extract with hydrogen peroxide resulted in 2 peaks at retention times of 3.82 and 5.38 min, representative of GTX – 2, 3 and STX respectively (Figure 2.3.1. B). These peak areas were used to determine the amount of GTX – 2, 3 and STX present in the culture extracts.

In order to investigate if the N-hydroxylated C 3,4 analogues contributed towards the peak observed at RT 1.69 min, and if GTX 6 contributed towards the peak observed at RT 3.32 min in the periodate oxidized sample (Figure 2.3.1. A) a representative sample was analyzed using the PST confirmation method. The resultant chromatograms (Figure 2.3.2.) show that no peaks were observed in Fraction 1, indicating the absence of C 3,4 in the tested extract. Fraction 2 contained peaks corresponding to GTX – 1, 4 and GTX – 2, 3 but no GTX 6 was observed. As expected, Fraction 3 contained oxidation peaks corresponding to STX (RT 5.4)

Chapter 2 Toxin analysis and Neo – STX (RT 3.34). There was also a peak observed at the RT of GTX – 2, 3, and this is likely due to carry over from fraction 2 during the SPE fractionation.

Figure 2.3.2.: PSP confirmation analysis chromatograms of a representative A. catenella ACCC01 extract. Only periodate oxidized fractions are shown.

Chapter 2 Toxin analysis

To assess recovery, spiking was performed on a sample with standard Mix 1 that contained GTX – 1, 4 and Neo – STX (Figure 2.3.3.). Spike recovery was 100% for the peak area at RT 1.68 which is used for GTX – 1,4 quantification, no matrix interference was observed.

Std alone (80ul MQ + 20ul Mix1 50x dil) PSP120626_11 (1) ACQUITY FLR ChA Ex340,Em395 nm 3.83 Range: 19941 1486 Area 17500.000 Spiked 15000.000

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EU x 10e4 7500.000 1.70 5000.000 329

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12500.000

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5000.000 1.68 240 2500.000

0.000 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00 4.25 4.50 4.75 5.00 5.25 5.50 5.75 6.00 PSP120626_09 (1) ACQUITY FLR ChA Ex340,Em395 nm Range: 2944 3.83 Area Standard with 151 1500.000

water 1.70 1000.000 84

500.000

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-500.000

-1000.000 Time 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00 4.25 4.50 4.75 5.00 5.25 5.50 5.75 6.00

Figure 2.3.3. : Spike recovery. Chromatograms of an A. catenella ACCC01 extract overspiked with GTX – 1,4 and Neo –STX mix.

Furthermore, no peaks were observed when an unoxidized sample was analyzed, which indicates that the detected peaks in the oxidized samples were due to PSTs and not fluorescent matrix components (Figure 2.3.4.). Once the PST profile is confirmed, the PST screen method allows fast and sensitive detection of PSTs in samples with the requirement of only small sample volumes (Harwood et al 2012 in prep). 27

Chapter 2 Toxin analysis

Figure 2.3.4.: Unoxidized sample extract. Chromatogram of an un-oxidized sample, no peaks characteristic for PSTs were observed.

Chapter 3 Gene expression and molecular evolution of sxtA4 in the saxitoxin producing dinoflagellate Alexandrium catenella

Chapter 3 Gene expression and molecular evolution of sxtA4

3.1. Abstract The recent identification of saxitoxin related-genes and transcripts in species of Alexandrium and Gymnodinium catenatum has facilitated the opportunity for the first time to investigate the expression of genes involved in saxitoxin biosynthesis, via quantitative real time PCR. In this study the expression of sxtA4, putatively involved in the initiation of PST synthesis, in parallel with the biochemical quantification of PST production was investigated at different growth stages, in batch culture. No significant differences in gene expression of sxtA4 at different growth rates were detected, despite significant differences in PST production rates at the different growth stages (P˃0.023). Therefore, it appears that posttranscriptional mechanisms may play a major role in the regulation of saxitoxin biosynthesis. For the development of an RT-PCR assay and sxtA4 expression normalization, three reference genes were tested: actin, cytochrome b (cob), and the ribosomal gene 28S rRNA. The gene cob was found to be most stably expressed at different growth stages. The combination of two reference genes, actin and cob resulted in the best stability factor for real time qPCR normalization. Genomic sequences of sxtA4 from A. catenella phylogenetically clustered together with high statistical support, indicating that paralogs had the same origin, and that multiple lateral transfers or recombination among species of Alexandrium may have been infrequent. Comparison of the sxtA4 cDNA sequences with corresponding genomic DNA sequences indicated preferential expression of genomic DNA copies, with higher GC content.

3.2. Introduction Saxitoxin (STX) is one of the most potent marine toxins. Its toxicity is mediated mainly via inhibition of the flow of sodium ions through voltage-gated sodium channels (Ritchie and Rogart, 1977; Su et al., 2004; Wang et al., 2003). STX is the parent compound of 57 analogs, which are commonly known as the paralytic shellfish toxins (PSTs) (Oshima et al., 1977; Shimizu et al., 1984) reviewed in (Wiese et al., 2010). PSTs are the causative agents of paralytic shellfish poisoning (PSP) and saxitoxin pufferfish poisoning (SPFP) (Anderson et al., 1996; Geraci et al., 1989; Kao and Nishiyama, 1965; Rodriguez et al., 1993). In marine waters, PSTs are produced by dinoflagellates belonging to the genera Alexandrium, Gymnodinium, and Pyrodinium (Anderson et al., 1990, Oshima et al. 1993; Usup et al., 1994). Due to the high potency of PSTs, PSP outbreaks can occur when cell densities are very low, as few as 100-200 cells L-1 (Anderson, 1997; Anderson et al., 2002; Townsend et al., 2001). The dynamics of PST production have been investigated at different cell densities, growth 31

Chapter 3 Gene expression and molecular evolution of sxtA4 stages and growth rates (Anderson et al., 1990; Boczar et al., 1988; Parkhill and Cembella, 1999). All previous studies have reported constitutive production of PSTs during growth in batch culture, however reports varied on which growth phases were associated with highest PST production. Highest levels of PSTs and rates of production have been observed during the mid-exponential growth phase (Anderson et al., 1990; Boczar et al., 1988), while other studies have reported an increase in toxin production in the stationary phase (Lim et al., 2005; Parkhill and Cembella, 1999). The relationship between cellular toxicity, environmental factors and growth rate is complex and not entirely consistent among or even within species (Cembella et al., 1998). The enormous genome size of dinoflagellates (Lin, 2011) has hampered the identification of genes putatively associated with PST production. A large EST library approach facilitated the detection of saxitoxin- biosynthesis associated genes and transcripts in dinoflagellates, including SxtA, encoding the enzyme proposed to initiate the synthesis of STX (Stüken et al., 2011). SxtA has four catalytic domains with predicted activities of SAM-dependent methyltransferase (sxtA1), GCN-5 related N-acetyltransferase (sxtA2), acyl carrier protein (sxtA3), a class II aminotransferase (sxtA4) (Kellmann et al., 2008).

PSTs are generally considered to be secondary metabolites (Shimizu, 1993). The production of many microbial secondary metabolites in batch culture is limited to certain growth phases, with production at low growth rates or the exclusive production under specific conditions (Demain et al., 1983; Zhu et al., 2002). Despite their classification as secondary metabolites, observations such as growth phase related synthesis induction, were not confirmed for PSTs, possibly due to the lack of sensitivity of biochemical quantification methods implicated. Therefore, insights into the role of PSTs for the producing organism may be possible by examining their production throughout the growth cycle, via novel techniques including the examination of gene expression. The investigation of gene expression could potentially detect more subtle changes, as the first metabolic regulatory level.

Alexandrium catenella belongs to the A. tamarense- A. catenella- A. fundyense species complex, which comprises five groups (numbered I to V) defined on the basis of ribosomal DNA (rDNA) sequences (Lilly et al., 2007). In this study, the expression and molecular evolution of the gene sxtA4 in a strain of A. catenella was investigated. A. catenella, Group IV, is a common in temperate east Asia and has been present for many years in the coastal waters of south eastern Australia (Hallegraeff et al., 1988; Scholin, 1994), where it causes blooms that can lead to PST uptake in shellfish, annually (Murray et al., 2011). Gene

Chapter 3 Gene expression and molecular evolution of sxtA4 expression is potentially the initial regulator of saxitoxin biosynthesis, and real-time reverse transcription polymerase chain reaction (RT-qPCR) is the most sensitive and reliable method used for the reproducible measure of genetic transcription. Few former studies have investigated gene expression in toxic Alexandrium species (Fernandez, 2002; Harlow et al., 2007a; Hosoi-Tanabe et al., 2005; Toulza, 2010) and a suitable set of reliable and thoroughly validated reference genes has not yet been reported for Alexandrium. Ideally, two to three reference genes are recommended for normalization of the target gene in any RT-qPCR experiment (Bustin, 2002; Bustin et al., 2005; Nicot et al., 2005; Schmittgen and Zakrajsek, 2000; Vandesompele et al., 2002).

In this study, the expression stability of three candidate reference genes was validated: cytochrome b, as a component of the mitochondrial respiratory chain; actin, a ubiquitous cytoskeletal component; and the ribosomal gene 28S rRNA (LSU). These three genes encode metabolites belonging to different functional classes, theoretically reducing the probability of co-regulation. The expression of sxtA4 during growth was normalized accordingly. Additionally, the sequences of the sxtA4 transcripts were compared to the corresponding genomic DNA sequences and examined for evidence of preferential expression. Finally, the evolution of the genes encoding sxtA4 in A. catenella was investigated in relation to similar sequences from other Alexandrium strains and Gymnodinium catenatum.

3.3. Material and Methods

3.3.1. Culture maintenance and quantification The strain used in this study, ACCC01, a member of Group IV (Murray et al., 2011). A.catenella ACCC01 was grown in GSe medium (Blackburn, 1989) in a culture cabinet (Labec, Australia) at a temperature of 18°C ± 1°C and 60 µmol photon m-2 sec-1, on a 12/12 hour light/dark cycle. For growth studies triplicate cultures were set up in 1 L volumetric culture flasks. Media was inoculated with an exponentially growing culture to a cell concentration of 280 cells ml-1. The cultures were grown for 37 days. Culture growth was monitored by cell counts using a Sedgewick Rafter counting chamber (Proscitech, Australia) and an inverted light microscope (Leica Microsystems). The growth rate was calculated using the formula µ= ln (N1/N0)/ t1-t0 (Anderson et al., 1990), where t is the time in days and N is the cell number. Culture samples for RNA extraction and toxin cell quota analysis were taken on day 6, 12, 18, 27, 37 at the end of the light cycle (+11h).

Chapter 3 Gene expression and molecular evolution of sxtA4

3.3.2. RNA extraction and DNAse treatment RNA was extracted from 40 mL of cultures harvested by centrifugation at 5,000 x g for 5 min, according to the RNA extraction protocol of Harlow. (Harlow et al., 2006). Briefly, cell pellets were ground with microglass pestles in 1.5 ml microcentrifuge tubes with 30 μL RLT buffer (RNeasy Kit Plant and Fungi, Qiagen) containing 1/100 volume ß-mercaptoethanol on ice. Extractions were then continued following the manufacturer’s instructions. RNA was eluted in 30μL RNase-free water (Qiagen). Residual DNA was removed with TURBO DNAse according to the TURBO DNA-freeTM kit (Applied Biosystems). RNA quality and quantity was assessed using RNA 6000 Nano LabChip Kit in microcapillary electrophoresis (Agilent 2100 Bioanalyzer, Agilent Technologies).

3.3.3. cDNA synthesis cDNA synthesis was performed with the SuperScript TM III first-strand synthesis system for RT-PCR (Invitrogen) according to manufacturer`s instructions. Briefly, reverse transcription of 100 ng total mRNA was performed in 50 µl reactions with a mixture of the provided oligo- (dt) primer. Reverse transcription reactions were diluted 10-fold with RNase free water and 1 µl of the dilution was used as template in successive qPCRs.

3.3.4. PCR primers Three possible reference genes were chosen for analysis as they were most likely to be constitutively expressed and not co-regulated. Primers for cytochrome b, were designed with Primer 3 based on the consensus sequence from an alignment of Alexandrium sequences downloaded from GenBank. All other primer details are outlined in Table 3.3.1.

Chapter 3 Gene expression and molecular evolution of sxtA4

Table 3.3.1.: Table with Primer details: Gene names, primer sequences, annealing temperature (AT), Amplicon, (AP) sizes in base pairs (bp), references

Gene Primer sequence (5` to 3`) AT (°C) AP (bp) References

Primer name sxtA4 sxtA4F CTGAGCAAGGCGTTCAATTC sxtA4R TACAGATMGGCCCTGTGARC 60 125 (Murray et al., 2011)

Cob cob_F TCCCATTTTTCCCTTTCWTT cob_R ATTTTTGTTGGGCACAGCTT 60 212 (this study) actin act_F ATCAAGGAGAAGCTCTGCTACATC act_R TCAGACTCGGCTGGAAGAGA 60 166 ( Yauwenas et al, unpublished data)

LSU catF CCTCAGTGAGATTGTAGTGC catR GTGCAAAGGTAATCAAATGTCC 60 160 (Hosoi-Tanabe and Sako 2005)

SxtA4 sxt007 ATGCTAACATGGGAGTCATCC sxt008 GGGTCCAGTAGATGTTGACGATG 60 750 (Stüken et al., 2011)

3.3.5. Quantitative real- time PCR Primer efficiency in real-time qPCR was determined according to Rasmussen (Rasmussen, 2001). Briefly, the standard curve was constructed from a 10-fold dilution series of a known concentration of fresh PCR product, ranging from 2-2 x 10-5 ng (Hou et al., 2010). The efficiency of the reaction was calculated as; E = (10(-1/m))-1, with m being the slope of the equation (Pfaffl, 2001; Rasmussen, 2001) qPCR was performed in triplicate for each sample using Evagreen dye (Biorad) in a final volume of 10 µl. The reactions were supplemented with 1µl of (0.1 mg ml-1) BSA. The following PCR protocol was used: denaturation 95°C 15 s, annealing and amplification at 60°C for 30 s, over 40 cycles with continuous fluorescence measurements. All qPCR assays were followed by dissociation curve analysis to ensure that the single PCR products matched with the standard amplicon. The melt curve analysis was performed over the range 95-55°C, including a final cooling step and continuous fluorescence measurements. For the quantitative comparison of amplification rates of the investigated candidate reference genes and the target gene (sxtA4), the “threshold cycle “ CT was 35

Chapter 3 Gene expression and molecular evolution of sxtA4 identified for each run as the cycle at which the fluorescence signal exceeded the background fluorescence of the reaction. Three technical replicates were performed and the mean values were calculated for each of the three biological replicates. For stability comparison of candidate reference genes, the Microsoft Excel add-in NormFinder was used as outlined in Andersen (Andersen et al., 2004). The stability value is based on the combined estimate of intra- and intergroup expression variations of the genes studied. The gene with the least expression variability is calculated and an additional combination of the two genes is recommended that commonly reflects the lowest stability value for normalization (Andersen et al., 2004). The expression of sxtA4 was normalized against the reference genes recommended by NormFinder with the Pfaffl (2001) equation: ΔCt target (control-treated) ΔCt ref (control-treated) Ratio = (Etarget) /(Eref) (Pfaffl, 2001). The mean values of biological triplicates and standard deviations of biological replicates, as well as other statistical analyses were determined using GraphPad version 4.3 (San Diego, CA). The statistical analysis consisted of a one-way ANOVA applied to the growth rate, toxin content, toxin production rate and gene expression at different days. A post-hoc Tukey test was used to determine any differences and a P value <0.05 was considered to be significant.

3.3.6. DNA extraction, cloning, and sequencing of sxtA4 amplified from gDNA and cDNA DNA was extracted using the cetyltrimethylammonium bromide (CTAB) method (Doyle and Doyle, 1987) (Appendix D). PCR of the larger fragment of sxtA4 from cDNA and genomic DNA (gDNA) was performed with the primers sxt007 and sxt008 (Table 3.3.1). PCR reactions comprised 35 cycles of 3 min at 94°C, 30 s at 65°C, and 1 min at 72°C, followed by a final extension at 7 min at 72°C. PCR products were cloned into the TOPO-TA plasmid (Invitrogen) and positive clones were screened and sequenced using the MTF/ MTR primer pair. A pool of 20 cDNA and 20 gDNA sxtA4 clones from A. catenella ACCC01 were sequenced. Approximately 50 ng of PCR product was used for direct sequencing. Products were sequenced using the ABI Big-Dye reaction mix (Applied Biosystems) at the Ramaciotti Centre for Gene Function Analysis, University of New South Wales. A sequence alignment was constructed from the resulting sxtA4 sequences and was analyzed at both nucleotide and amino acid levels.

Chapter 3 Gene expression and molecular evolution of sxtA4

Dinoflagellate nucleotide sequences were aligned manually with the program Geneious v5.4 (Drummond et al., 2011) with consideration of the coding sequence in the correct reading frame. For phylogenetic analyses, the sequences of gDNA clones were aligned with additional database sequences of sxtA4 (accession numbers are given in Figure 3.4.2.) and aligned using Clustal W (Thompson et al., 1994). The program Findmodel (Posada and Crandall, 1998) was implemented to evaluate optimal substitution models for the alignments, and the GTR-model was chosen. Final alignments consisted of 74 sequences, 600 bp in length. Alignments were analyzed using maximum likelihood (ML) and the GTR model with parameters as implemented in the program PhyML v2.4.4 (Guindon and Gascuel, 2003). ML bootstrap analyses were performed with 100 replicates. Alignments were also analyzed using Bayesian inference (BI) using the same parameters, in the program Mr Bayes (Huelsenbeck and Ronquist, 2001). Two million generations were run, until the standard deviation of split frequencies was less than 0.01 and the potential scale reduction factors (PSRF) approached 1.00. Trees were sampled every 1000 generations, with a burnin of 1500 trees. Since the genes encoding sxtA4, are only ~40% similar to those of cyanobacteria or any other organisms at the protein level (Stüken et al., 2011), the nucleotide alignment determined in this study was analyzed without outgroups and the tree, therefore, is presented as unrooted.

3.3.7. Toxin extraction Ten milliliters from each culture was harvested on sample days by centrifugation at 5,000 x g for 5 min. The toxins were extracted with 300 µl of 0.1 M HCl by hydrolysis in a boiling water bath for 5 min (Chang et al., 1997). Extracted toxins were collected from the supernatant after centrifugation. The centrifugation step and transfer of the supernatant into a new 1.5 ml Eppendorf tube was repeated thrice to acquire clear extracts.

3.3.8. Determination of PST concentrations Toxin content of the culture samples was tested using HPLC, according to the AOAC Official Method 2005 for paralytic shellfish poisoning toxins in shellfish (Lawrence et al., 2005), however, a matrix modifier was not used. HPLC was performed on a Hewlett Packard 1100 series LC with fluorescence detection (EX 340 nm, EM 395 nm). Chromatographic separation was achieved with a Zorbax SB-C18 (4.6 × 250 mm, 5 µm) reversed phase analytical column (Agilent Technologies), eluted at 2 ml min-1. Mobile phases were 0.1 M ammonium formate (A) and 0.1 M ammonium formate in 5% acetonitrile (B), both adjusted to pH 6. The gradient 37

Chapter 3 Gene expression and molecular evolution of sxtA4 consisted of a linear gradient to 5% B over 15 min, a linear gradient to 70% B over 12 min, then returning to 100% A over 6 min and held for 3 min. Analytical standards for the STX analogs were obtained from the National Research Council, Canada Dilution curves of standards were used for quantification of the PSTs in sample material. The toxin production rate was calculated with the equation µTox = ln (T1/T0)/t1-t0 (Anderson 1990).

3.4. Results

3.4.1. Culture growth and growth rate The replicate cultures of Alexandrium catenella, strain ACCCO1 were sampled over a period of 37 days. Growth rates were highest on Day 6 with an average value of (0.44 µ Day -1) over the sampling period with values of 0.1 µ Day-1 during the lag phase, 0.17 µ day-1 for Day 18, 0.03 µ Day-1 for day 27, and -0.07 µ Day-1 for Day 37 (Figure 3.4.1., Table 3.4.2.). Growth rates at each of these sampling days differed significantly as determined by one-way Anova and the post-hoc Tukey test (P˂0.0001).

100000 0.6 Growth rate Growth

0.4

-1 10000

0.2  (day

Cells ml Cells 1000 0.0 -1 )

100 -0.2 0 10 20 30 40 Days

average growth rate

Flask 1 Flask 2 Flask 3

Figure 3.4.1.: Growth curve of triplicate cultures of A. catenella ACCC01 over a period of 37 days. Sampling for RNA and toxin analysis was performed on Days 6, 12, 18, 27, 37 indicated by the vertical line.

Chapter 3 Gene expression and molecular evolution of sxtA4

3.4.2. Primer specificity PCR primer specificity was confirmed with conventional PCR. Single bands were visualized on 3% agarose gels and were confirmed by sequencing of the amplicons. The melt curve analyses confirmed single melt temperatures for each primer pair of 77.5°C for cytochrome B, 86°C for actin, 80.5°C for LSU, and 77.5°C for sxtA4. Primer efficiency was determined to be 0.9 for all four genes.

3.4.3. Reference gene expression stability The evaluation of inter- and intragroup expression variability for the three investigated reference gene candidates cytochrome b, actin, LSU showed that the gene with the least variability in expression was cytochrome b. Its stability value was 0.041. Actin had a slightly higher stability value of 0.050 and LSU showed the highest variation between the biological replicates, and at the different sampling days with an overall stability value of 0.087. The overall best stability value as reference expression is achieved when using a combination of two genes actin and cytochrome b, with a stability value of 0.036.

3.4.4. Expression normalization of sxtA4 The relative expression ratio of sxtA4 was normalized against cytochrome b and actin. Samples from day 27 had a growth rate of 0 µ day -1 these samples were therefore treated as the control while all other days were considered to be the treatment, in order to evaluate changes in expression related to growth rate. The relative average expression ratio of sxtA4 on the different days is shown in Table 3.4.1. The aminotransferase sxtA4 is constitutively expressed throughout growth in batch culture. There was no significant difference in expression of sxtA4 among sampling days with significantly different growth rates.

3.4.5. Toxin analysis Alexandrium catenella ACCC01 produces gonyautoxins 1-4 (GTX – 1,4) and neosaxitoxin (Neo–STX), gonyautoxins 2-3 (GTX – 2,3) and saxitoxin (STX). The toxin content per cell during growth differed significantly, based on a one-way ANOVA and post-hoc Tukey test (P˃0.0001) (Table 3.4.1.). Total toxin was found to be 9.48 ± 0.3 pg cell-1 at lag phase, slightly increasing at exponential growth to 11.02 ± 0.2 pg per cell-1, and decreasing at stationary phase to 10.53 ± 0.25 pg per cell-1 (Table 3.4.1.). The Mol % ratio of GTX – 1,4

Chapter 3 Gene expression and molecular evolution of sxtA4 and GTX – 2,3 and of Neo – STX and STX was approximately 5/10 but changed to 3/10 for GTX – 1,4/GTX – 2,3 and 7/10 for Neo – SXT/STX at stationary phase Figure 3.4.2.

100%

80%

60% GTX 2-3 GTX 1-4 40% Neo-STX STX 20%

0% Day 6 Day 12 Day 18 Day 37

Figure 3.4.2.: PST analogs in Mol% (GTX – 1,4, GTX – 2,3, Neo – STX and STX) of total PST content at sampling days.

Table 3.4.1.: Relative Expression ratio of sxtA4, growth rate, total PST content and toxin production rate of A.catenella ACCC01 on the days 6, 12, 18, 37.

Day Growth rate Total PST Relative µ Expression (day -1) (pg cell-1) ratio

5-6 0.44 ± 0.01 9.48 ± 0.3 0.21 ± 0.78 11-12 0.10 ± 0.03 9. 5 ± 0.3 0.50 ± 0.75 17-18 0.17 ± 0.03 11.02±0.2 0.62 ± 0.16 36-37 -0.7 ± 0.04 10.53± 0.25 0.35 ± 0.57

PST production rate were calculated for the different growth stages between day 6 and 12 (0.004±0.005 pg cell day-1), day 12-18 (0.024 ± 0.001 pg cell day-1and day 18 and 37 (-0.05 ± 0.001 pg cell day-1). The PST production rates differed significantly (P˃0.023) at different growth stages.

Chapter 3 Gene expression and molecular evolution of sxtA4

3.4.6. Phylogenetic analysis A. catenella ACCC01 has several different copies of sxtA4 gene. Twenty clones were sequenced and 19 of the clones clustered on a highly supported branch (Figure 3.4.3.) with sxtA4 sequences from other A. catenella and A. fundyense strains. Only clone 13 formed a weakly supported separate clade with A. minutum strains and Gymnodinium catenatum. Most of the sxtA4 genes of A. minutum were found to form a clade with A. tamarense strains, which also included several other A. fundyense sequences (Figure 3.4.3.).

Chapter 3 Gene expression and molecular evolution of sxtA4

Figure 3.4.3.: Results of the phylogenetic analysis of genomic copies of sxtA4 from different Alexandrium strains and Gymnodinium catenatum, including the strain A. catenella ACCC01 sequenced in this study (highlighted in grey). The phylogentic tree depicted is based on a Maximum Likelihood (ML) analysis, using the GTR model with bootstrap (BS) values based on 100 replicates. The tree is unrooted. Bayesian analysis was also conducted, using 2,000,000 iterations. BS values and Bayesian Posterior Probabilities (PP/BS) are shown to the left of nodes. Values greater than 1.00/90 are shown as closed circles at nodes. Support values less than 0.50/50 are not shown.

3.4.7. Sequence comparison of sxtA4 cDNA and gDNA The comparison of the amplified fragment of sxtA4 cDNA and gDNA sequences (620 bp) revealed the presence of several different copies of the sxtA4 gene on both mRNA and gDNA levels in A. catenella ACCC01 (Figure 3.4.4., Appendix E). Clones amplified from gDNA and cDNA all contained SNPs at multiple positions in the sequence. At least two distinctly different gDNA copies of sxtA4 were identified (clone 13 with a GC content of 63% and clones 1-12, 14-20 with a GC content of ~65%). cDNA sequences contained SNPs but were not significantly different.

Chapter 3 Gene expression and molecular evolution of sxtA4

1 90 170 235 268 275 307 385 404 409 430 437 493 521 558 439 523 gDNA_cl01 TAC GAA GAA -TA CGC AAC GGC AAT AGC TGT AAT GTT ACT TTC AAG gDNA_cl02 TAC GAA GAA -TA CGC AAC GGC AAT AGC TGT AAT GTT ACT TTC AAG gDNA_cl03 TAC GAA GAA -TA CGC AAC GGC AAT AGC TGT AAT GTT ATT TTC AAG gDNA_cl04 TAC GAA GAA -TA CGC AAC GGC AAT AGC TGT AAT GTT ACT TTC AAG gDNA_cl05 TAC GAA GAA GTA CGC AAC GGC AAT AGC TGT AAT GTT TTT TTG AAG gDNA_cl06 TAC GAA GAA GTA CGC AAC GGC AAT AGT TGT AAT GTT ACT TTC AAG gDNA_cl07 TAC GAA GAA GTA CGC AAC GGC AAT AGC TGT AAT GTT ACT TTC AAG gDNA_cl08 TAC GAA GAA GTA CGC AAC GGC AAT AGC TGT AAT GTT ACT TTC AAG gDNA_cl09 TAC GAA GAA GCA CGC AAC GGC AAT AGC TGT AAT GTT ACT TTC AAG gDNA_cl10 TAC GAA GAA GTA CGC AAC GGC AAT AGC TGT AAT GTT ACT TTC AAG gDNA_cl11 TAC GAA GAA GTA CGC AAC GGC AAT AGC TGT AAT GTT ACT TTC AAG gDNA_cl12 TAC GAA GAA GTA CGC AAC GGC AAT ACC TGT AAT GTT ACT TCC AAG gDNA_cl13 GAC GAG GGA GTA CGC GAC GGC AAC GGC TGC AAG ATC ACT CTC AAG gDNA_cl14 TAC GAA GAA GTA CGC AAC GGC AAT AGC TGT AAT GTT ACC TTC AAG gDNA_cl15 TAC GAA GAA GTA CGC AAC GGC AAT AGC TGT AAT GTT ACT TTC AAG gDNA_cl16 TAC GAA GAA GTA CGC AAC GGC AAT AGC TGT AAT GTT ACT TTC AAG gDNA_cl17 TAC GAA GAA GTA CGC AAC GGC AAT AGC TGT AAT GTT ACT TTC AAG gDNA_cl18 TGC GAA GAA GTA CGC AAC GGC AAT AGC TGT AAT GTT ACT TTC AAG gDNA_cl19 TGC GAA GAA GTA CGC AAC GGC AAT AGC TGT AAT GTT ACT TTC AAG gDNA_cl20 TGC GAA GAA GTA CGC AAC GGC AAT AGC TGT AAT GTT ACT TTC AAG cDNA_cl01 GAC GAG GGA GTG CGA GAC GGT AAC GGC TGC AAG ATC ACC CTG AGG cDNA_cl02 GAC GAG GGA GTG CGA GAC GGT AAC GGC TGC AAG ATC ACC CTG AGG cDNA_cl03 GAC GAG GGA GTG CGA GAC GGT AAC GGC TGC AAG ATC ACC CTG AGG cDNA_cl04 GAC GAG GGA GTG CGA GAC GGT AAC GGC TGC AAG ATC ACC CTG AGG cDNA_cl05 GAC GAG GGA GTG CGA GAC GGT AAC GGC TGC AAG ATC ACC CTG AGG cDNA_cl06 GAC GAG GGA GTG CGA GAC GGT AAC GGC TGC AAG ATC ACC CTG AGG cDNA_cl07 GAC GAG GGA GTG CGA GAC GGT AAC GGC TGC AAG ATC ACC CTG AGG cDNA_cl08 GAC GAG GGA GTG CGA GAC GGT AAC GGC TGC AAG ATC ACC CTG AGG cDNA_cl09 GAC GAG GGA GTG CGA GAC GGT AAC GGC TGC AAG ATC ACC CTG AGG cDNA_cl10 GAC GAG GGA GTG CGA GAC GGT AAC GGC TGC AAG ATC ACC CTG AGG cDNA_cl11 GAC GAG GGA GTG CGA GAC GGT AAC GGC TGC AAG ATC ACC CTG AGG cDNA_cl12 GAC GAG GGA GTG CGA GAC GGT AAC GGC TGC AAG ATC ACC CTG AGG cDNA_cl13 GAC GAG GGA GTG CGA GAC GGT AAC GGC TGC AAG ATC ACC CTG AGG cDNA_cl14 GAC GAG GGA GTG CGA GAC GGT AAC GGC TGC AAG ATC ACC CTG AGG cDNA_cl15 GAC GAG GGA GTG CGA GAC GGT AAC GGC TGC AAG ATC ACC CTG AGG cDNA_cl16 GAC GAG GGA GTG CGA GAC GGT AAC GGC TGC AAG ATC ACG CTG AGG cDNA_cl17 GAC GAG GGA GTG CGA GAC GGT AAC GGC TGC AAG ATC ACC CTG AGG cDNA_cl18 GAC GAG GGA GTG CGA GAC GGT AAC GGC TGC AAG ATC ACC CTG AGG cDNA_cl19 GAC GAG GGA GTG CGA GAC GGT AAC GGC TGC AAG ATC ACC CTG AGG cDNA_cl20 GAC GAG GGA GTG CGA GAC GGT AAC GGC TGC AAG ATC ACC CTG AGG

Figure 3.4.4.: SxtA gene model and 17 of the sxtA4 sequence positions at which cDNA clones differ from the gDNA clones, nucleotide acid sequences derived from mRNA and gDNA of A. catenella ACCC01.

Chapter 3 Gene expression and molecular evolution of sxtA4

Table 3.4.2: Loci of the sxtA4 sequences derived from cDNA and gDNA that differed thoughout the clone pools. Part I of the table contains “potential “ mRNA editing position these nucleotide differences were present between all cDNA clones and all gDNA clones. Part II of the table contains nucleotide differences present in all but one gDNA clone (clone 13). Amino acids encoded by the codons and AA exchanges are listed. The last column indicates if changes have been found in the sxtA4 sequences of A. fundyense CMP1790 see alignment Figure 3.4.4. Appendix E.

Position in gDNA cDNA Amino acid Alexandrium alignment fundyense I

235 GUA GUG Val no 268 CGC CGA Arg fundyenseyes 274 CCC CCA Pro yes 307 GGC GGU Gly no 523 UUC CUG Phe →Leu no 558 AAG AGG Lys →Arg no II 1 UAC GAC Tyr→Asp yes 90 GAA GAG Glu yes 170 GAA GGA Glu→Gly yes 275 AAC GAC Asn→Asp no 313 AUC GUC Ile→Val yes 385 AAU AAC Asn no 404 AGC GGC Ser→Gly yes 409 UGU UGC Cys no 430 AAU AAG Asn→Lys no 437 GUU AUC Val→Ile no 439 GUU AUC Val→Ile yes 493 ACU ACC Thr no 521 UUC CUG Phe→Leu no 600 AAG AGG Arg→Lys -

3.5. Discussion This is the first study to examine the expression, regulation and molecular evolution of a gene putatively involved in STX biosynthesis in a harmful bloom-forming dinoflagellate. Gene expression of sxtA4 does not change significantly over growth, whereas significant changes were detected in toxin production (Table 3.4.1.). The analysis of gDNA and cDNA sequences of stxA4 indicated the presence of specific positions within the nucleotide sequence of sxtA4, 45

Chapter 3 Gene expression and molecular evolution of sxtA4 which are potential hot-spots for nucleotide polymorphisms present in different strains. Clear preferential transcription of high-GC gDNA sxtA4 templates was observed in A. catenella ACCC01. The analysis of cDNA and gDNA sequences of sxtA4 further suggested the potential involvement of mRNA editing in the maturation process of sxtA4 gene transcripts. The relative expression of the target gene sxtA4, normalized against the reference genes encoding cytochrome B and actin, did not change significantly during the different growth stages of A. catenella. It is possible that sxtA has a broader function in the overall metabolism of toxic strains than solely the synthesis of STX and its analogs, and is hence expressed constitutively. Some biosynthetic enzymes involved in secondary metabolite synthesis, such as the acyltransferase involved in penicillin synthesis in bacteria have been described to have a broad substrate specificity (Banko et al., 1987). Similarly broad substrates have been found in the polyketide synthases from plants (Abe and Morita, 2010; Wakimoto et al., 2011). It is hence possible that the aminotransferase sxtA4 is involved in further biosynthetic pathways crucial for toxic strains of Alexandrium.

It is also possible that sxtA4 is translationally or post-translationally regulated. It has been hypothesized that transcription level regulation may play a minor role in the expression of many dinoflagellate genes, compared to regulation in other organisms. Several microarray studies suggested that only about 10-27 % of genes might be regulated transcriptionally (Erdner and Anderson, 2006; Lidie et al., 2005; Lin, 2011; Lin et al., 2010). Other studies of dinoflagellate gene expression have indicated, that these organisms use both transcriptional and post-transcriptional regulation in equal measure, with the iron superoxide dismutase of Lingulodinium polyedrum exhibiting both modes, depending on the stimulus (Okamoto et al., 2001). Moreover, transcriptional regulation has been shown for the peridinin-chlorophyll a binding protein (Triplett et al., 1993), S-adenosyl-homocysteine-hydrolase-like protein, methionine-aminopeptidase-like protein, and histone like protein (Taroncher-Oldenburg and Anderson, 2000). On the other hand several physiological processes have been suggested to be regulated at the translational level, including bioluminescence (Mittag et al., 1998; Morse et al., 1989), carbon fixation (Fagan et al., 1999), photosynthesis (Le et al., 2001), and the cell cycle (Brunelle et al., 2007; Van Dolah et al., 2007a). A mechanism that has been suggested to explain the potential prevalence of post-transcriptional gene regulation is the trans-splicing mechanism, in analogy to Trypanosomas sp. of the kinetoplastid genus in which trans-splicing is also present and most genes are regulated post-translationaly (Morey et al., 2011). Trans- splicing of dinoflagellate mRNAs is a process by which a specific 22 base oligonucleotide, a trans-spliced leader, is added to the 5` end of a heterogenous group of RNA (Lidie and Van 46

Chapter 3 Gene expression and molecular evolution of sxtA4

Dolah, 2007; Zhang et al., 2007). The trans-splicing system in dinoflagellates may provide a level of regulation in addition to transcription (Bachvaroff, 2008) by creating a pool of fully mature translationally active mRNA (Bachvaroff, 2008; Lidie and Van Dolah, 2007; Zhang et al., 2007). The prevalence of the trans-splicing mechanisms could limit the application of real time PCR in dinoflagellates, as the transcript level that is detected by RT-PCR does not reflect solely the mature fraction of mRNA activated for translation, hence possibly not reflecting the changes that regulate expression of a gene product. Further experiments of sxtA4 expression under different conditions, with more drastic changes in toxin production may elucidate if regulation on the transcriptional level plays a role in sxtA4 synthesis, or if other regulatory mechanisms prevail. The additional investigation of the sxtA 3 domain will also allow a better evaluation of the role of transcriptional regulation in PST synthesis.

Dinoflagellates possess a number of remarkable genetic characteristics that distinguish them from other eukaryotes reviewed in (Lin, 2011; Rizzo, 1991), one of such striking features is the large amount of gDNA that they contain, 3-250 pg per cell (Allen et al., 1975; Rizzo, 1991). It has been suggested that the duplication of genomic copies of highly expressed genes in dinoflagellates may function as a means of increasing their transcription (Bachvaroff, 2008). Stüken et al reported up to 100-240 genomic copies of sxtA4 with slightly different sequences. These authors identified single nucleotide polymorphisms (SNPs) in 454 transcript studies in A. fundyense, of which two thirds were silent. They defined SNPs as a base pair change that occurred in at least two of the reads. In this study multiple copies of sxtA4 all containing SNPs were found (Stüken et al., 2011), (Figure 3.4.4., Appendix E.). Additionally two gDNA copies that differed substantially were identified. These were a common type which clustered together (19 clones, with a GC content ≈ 65%) in the A. catenella and A. fundyense clade (0.99/0.92). The other type of sxtA4 gDNA copy identified (clone 13) with a lower GC content of 63% was seemingly more closely related to sxtA4 sequences of A. minutum/tamarense and G. catenatum (support values less than 0.50/50) (Figure 3.4.3.). Most Alexandrium species appear to have independently evolved their own sxtA4 copies; there is little evidence of widespread horizontal transfer among species, but within closely related species e.g. A. catenella and A. fundyense, there may be some genetic exchange. It is possible that the presence of multiple gene copies of sxtA4 might also play a role in adaptation and provide plasticity. Multiple copy numbers and copy number variations (CNP) within genomes have been described for humans, mice, Drosophila and other eukaryotes (Cutler et al., 2007; Dopman and Hartl, 2007; Freeman et al., 2006). CNP is also widespread in the malaria parasite genome and manipulation of copy numbers has been shown to alter the response to 47

Chapter 3 Gene expression and molecular evolution of sxtA4 multiple drugs (Sidhu et al., 2006) suggests that they have the potential to make a significant contribution to adaptive evolution (Nair et al., 2008).

A preferential transcription of a particuler sxtA4 gene copy, was found in this study. It has been formerly suggested that some gDNA copies might be preferentially transcribed according to GC content (Hsiao et al., 2010; Stüken et al., 2011). In this study consistent differences between all clones of the sequences of sxtA4 from genomic DNA and that of cDNA, at 6 nucleotide positions were found (Figure 3.4.4, Table 3.4.3.). While it is highly likely that not all genomic copies were identified in the screening, there is no reason to suppose this was an unrepresentative sample. Even the sampling of 100-240 clones could not guarantee, that all different gDNA copies would be captured in the analysis. As it is not clear if the different gene copies are arranged in a tandem arrangement or if they are further appart on the genome. Amplification of genes is likely to be impacted by the large genome size of dinoflagellates and the position of the genes in the genome. It is hence not guarenteed that the gDNA copies would be equally amplified in the PCR reaction and hence cloned in an equal ratio into the vector for further analysis. It seems possible that mRNA editing might play a role in the maturation of sxtA4 transcripts and the regulation of sxtA4 expression. RNA editing, is a process by which sequences at the nucleotide sites may be changed during or after transcription (Benne et al., 1986; Gray, 2003). Recently, editing was detected for mitochondrial genes cob and cox1 in three species of dinoflagellates (Lin et al., 2002), and a highly flexible and sophisticated editing mechanism has been suggested (Lin et al., 2002; Nash et al., 2008; Zhang and Lin, 2008). RNA editing of transcripts of cyanobacterial origin such as genes encoded in the dinoflagellate minicircles (representing chloroplast DNA) was demonstrated in Cerratium horridum (Zauner et al., 2004). Although the critical function, of mRNA editing is not yet clear, it has been suggested to increase the G/C content of the genes and clustering of the edited sites implicates selection of targets for editing (Lin et al., 2002; Zauner et al., 2004). Editing events have been found to re-establish proper reading frames and evolutionary conserved functions in trypanosomes or plant mitochondrial types of RNA editing (Knoop, 2011). The potential for creating protein diversity through alternative editing in kinetoplastids has been recently emphasized (Abe and Morita, 2010; Knoop, 2011; Ochsenreiter et al., 2008; Ochsenreiter and Hajduk, 2006).

Stüken et al postulated that the sxtA4 genes are nuclear encoded, but identified signal peptides which indicate specific targeting of the STA4 product (Stüken et al., 2011). Nuclear encoded genes in dinoflagellates can be plastid derived and their product targeted to the plastid.

Chapter 3 Gene expression and molecular evolution of sxtA4

(Stüken et al., 2011). mRNA editing might hence play a role in the maturation of sxtA4 transcripts, after the transport of sxtA4 transcripts into the cytosol. As sxtA4 may also be a gene that originates from a plastid, possibly obtained through a lateral gene transfer from cyanobacteria or their close relatives (Stüken et al., 2011).

3.6. Conclusion The combined use of molecular methods and chemical analytical methods for PST identification and quantification is promising to foster novel insights into the role of saxitoxin as metabolite and its regulation within the organism. The study of gene transcripts involved in toxin production via real time PCR enables the observation of the immediate response to stimuli, as the transcriptional level is the first level of metabolic regulation and the basis for any further processes. Furthermore, several metabolic responses can be observed simultaneously bearing large potential for investigations of the co-regulation of metabolic pathways. The established set of Alexandrium specific reference genes for quantitative real- time PCR and the sxtA4 RT-marker are a valuable tool, to further investigate the regulation of saxitoxin production in dinoflagellates in addition to chemical analytical methods. However, the normalization of sxtA4 transcript levels against its own gDNA copy number over the growth could be a good alternative way of normalizing gene expression in dinoflagellates. In order to allow an integrated evaluation if the gene copy number stays stable or if gene copy numbers are involved in the regulation of transcription. Further studies on the transcriptional response of sxtA4 to environmental factors or nutrient availability might aid to elucidate if transcriptional regulation does play a role in the production of STX, triggered by specific environmental cues. The investigation of proteomics in combination with gene expression studies seems reasonable in order to fully unravel the regulation of toxin production on different levels. Future studies should also investigate gDNA and cDNA copies of other saxitoxin related genes in A. catenella and other toxic strains in order to investigate if the occurance of selective transcription of higher GC content transcripts exists more broadly. A broader mapping of loci that are susceptible to SNPs on the sxtA4 and other saxitoxin related gene sequences could aid to elucidate if some copies of sxtA4 are dysfunctional, a comparison with non-toxic Alexandrium strains might provide insights. Such mapping might also allow a better resolution and insights into the taxonomy and phylogenetic affinity of the strains.

Chapter 4 The impact of light spectra on cell cycle progression, saxitoxin production and gene expression in Alexandrium catenella

Chapter 4 Cell cycle progression and gene expression 4.1. Abstract Alexandrium catenella is a prominent producer of the neurotoxin saxitoxin (STX). It is crucial to determine the rate of cell division and toxin production in order to understand the development of HABs. Light plays a key role in the regulation of cell division, synchronized by the circadian rhythm. Saxitoxin production has been reported to correlate with the cell cycle phase progression in dinoflagellates. It is therefore likely to be a major regulator of the signaling pathways leading to the development of toxic blooms. In this study the cell cycle progression and the production of PSTs in white light as well as in blue and red light spectra was investigated in a strain of Alexandrium catenella, Group IV genotype. In addition, relative gene expression of two target genes psbA and sxtA4 in blue, red and white light, as well as during the diel phase was investigated via quantitative real-time PCR. The findings indicate that DNA synthesis and cell cycle progression are slightly shifted in the blue light and findings indicate that red light might induce DNA synthesis faster compared to blue light. Toxin synthesis was significantly higher in red light and no differential gene expression was detected for sxtA4 under these conditions. The differential response to red and blue light of A.catenella in cell cycle progression, toxin production suggests that light quality may play an important role in the development of toxic blooms and population dynamics of Alexandrium.

4.2. Introduction Alexandrium catenella is associated with harmful algal bloom events around the world (Anderson et al., 2002; Glibert et al., 2005). Despite various unusual genetic characteristics, that place dinoflagellates as a unique group among the eukaryotes (Rizzo, 1987; Rizzo, 1991), they display a typical eukaryotic cell cycle initiated by the mitotic division of the cells followed by interphase, consisting of three segments, G1, S and G2. Photoperiodic entrainment of the cell cycle can occur during a clearly defined interval such as the dark-to- light transition, resulting in a synchronous progression of the population through G1, S, G2 and M phases, with only a fraction of cells proceeding though the entire cell cycle on a given day, the other fraction remaining in G1 phase (Chisholm and Brand, 1981; Vaulot, 1995). Toxin production has been associated with particular phases of the cell cycle in previous studies. However, contradictory results have been found. For example, light has been suggested to set the pace for toxin production in the closely related saxitoxin-producing

Chapter 4 Cell cycle progression and gene expression species Alexandrium fundyense, PST production was reported to be discontinuous over the cell cycle and directly correlated to the duration of G1 phase during the light phase (Taroncher-Oldenburg et al., 1997, 1999). Siu et al reported that toxin content reached a maximum during S-phase of the cell cycle of A.catenella (Siu et al., 1997). Harlow reported the net cellular PST production to be highest in the dark before irradiance, when most (56%) of the cells are in the G2+M phase of the cell cycle in A.catenella (Harlow et al., 2007a). The reported toxin production and cell cycle phase correlation are hence inconsistent and may vary between species and strains. Cho et al (2011) studied PST production and cell proliferation in the dinoflagellate Alexandrium tamarense under the influence of metabolic inhibitors and noted that intracellular PST levels in cells treated with mitomycin C increased, gradually up to a 6-fold increase. It was concluded that mitomycin arrested cells in S-phase.

High concentrations of colchicine prolonged G1 phase in A. tamarense cells, which then were unable to produce PSTs. Their study demonstrated that toxin production can be manipulated by manipulation of cell cycle progression (Cho et al., 2011). Photosynthetic organisms regulate the synthesis of their photosystem, nuclear and chloroplast gene expression in response to photosynthesis mediated changes in cellular redox, as well as to changes in light intensity (Link, 2004; Pfannschmidt, 2003; Pfannschmidt et al., 1999). In addition to redox control, light-absorbing photoreceptors play a major role in the control of several metabolic pathways and the circadian rhythms in response to red and blue light intensity (Vierstra and Zhang, 2011). In higher plants, the collective response to a certain light stimuli is called photomorphogenesis and is directed by several photoreceptor types, including the blue light (B)-absorbing phototropin and cryptochrome flavoproteins, and the phytochrome family of biliproteins, which typically absorb red (R) and far-red (FR) light (Möglich et al., 2010; Rockwell et al., 2006; Vierstra and Zhang, 2011). Photoreceptors keep track of fluctuations in spectral composition and intensity of incoming light and set in motion signaling cascades that ultimately influence the organisms physiology, through modulation of gene activity (Fankhauser and Staiger, 2002; Tobin and Silverthorne, 1985). Photoperception through photoreceptors plays an important regulatory role in the synchronization of cell division by the circadian rhythm (Brunelle et al., 2007). Both toxin production and rate of cell division are central to formation of harmful algal blooms, which are mass proliferations of cells (Van Dolah et al., 2007a). These processes are regulated by light. Little is known about the photodetection mechanisms in marine dinoflagellates. It has been reported that photosynthetic stramenopiles (microalgae) (Kataoka, 1975; Takahashi et al., 2001), brown algae (Lüning, 1980), and diatoms (Nultsch, 1956) use blue light for light regulation of their 53

Chapter 4 Cell cycle progression and gene expression behavior and life cycle (Takahashi et al., 2007). Recently Brunelle et al (2007) characterized the first cryptochrome blue-light receptor expressed in K. brevis suggesting, that it may serve as a dawn cue receiver in the circadian rhythm pathway (Brunelle et al., 2007).

Red and blue light have been found to influence toxin production-related gene expression of mycrocystin synthesis related mycB and mycD transcripts in the cyanobacteria Mycrocystis aeroginosa (Kaebernick et al., 2000). For cyanobacteria, it was also shown that the circadian rhythm of Neo-STX production was lost in red light. Under blue light, the period with maximum production of STX and Neo-STX was longer (26h) than under white light (Carneiro et al., 2009; Kaebernick et al., 2000). A cryptochrome receptor like sequence has been found in Alexandrium catenella by Uribe et al. (Uribe et al., 2008). However, there is a lack in information about the potential regulatory role of blue and red light spectra and PST production, gene expression as well as cell cycle progression in Alexandrium. The recent finding of PST biosynthesis associated genes and transcripts in dinoflagellates (Stüken et al., 2011), has allowed for the development of a RT-assay to investigate STX-related gene expression (Chapter 3) in Alexandrium catenella. Studies on gene expression during the cell cycle have been conducted, investigating the transcription of Sam, S-adenosylhomocysteine hydrolase Sahh and methionine aminopeptidase Map. These genes were reported to be up- regulated during PST production and the G2+M phase of the cell cycle before irradiance (Harlow et al., 2007b). However, these genes are not thought to be directly involved in saxitoxin synthesis (Harlow et al., 2007a; Stüken, 2011). Therefore, the potential regulation of genes likely to be more directly involved in saxitoxin production throughout the cell cycle requires investigation. In the present study the regulatory effect of red, blue and white light on cell cycle progression, toxin production and gene expression was compared. The transcriptional response to light was investigated for two target genes, the nuclear-encoded gene sxtA4, coding for the aminotransferase putatively involved in the initiation of PST synthesis (Kellmann et al., 2008; Stüken et al., 2011) (Kellmann et al., 2008; Stüken, 2011) in parallel with the plastid- encoded gene psbA coding for the D1 protein of photosystem II. Gene expression during one diel cycle and during exposure to blue and red light were investigated. This study allows a first evaluation of potential regulatory signalling pathways on the transcriptional level through different chromophores, it also allows to attempt the evaluation of possible impacts of light quality on PST production and toxic bloom development.

Chapter 4 Cell cycle progression and gene expression 4.3. Material and Methods

4.3.1. Blue, red and white light experiment The strain used in this study, ACCC01, a member of Group IV (Murray et al., 2011),(see chapter 2 and 3). The A. catenella culture was grown to a cell number of 5000 cells mL -1. The culture was synchronized through 48h of continuous darkness and then subdivided into 9 flasks, each containing 350 mL of the initial culture. A. catenella cultures were maintained on a 12:12 L:D cycle with 110 µmol photons·m-2 s-1 at 18°C. Three flasks were then placed in a blue, three in a red and three in a white filter cylinder. Roscolux filters (Port Chester, NY, USA) of matched transmittance (approx. 20%) were used to obtain red (R19) or blue (R367) light as described by (Brunelle et al., 2007), and neutral density filters (Lee No. 210) were used for white-light controls with all treatments, thus receiving 40 µmol photon m-2 sec-1. The cultures were acclimatised to the filter light conditions for 6 days and then sampled on day 7 as described by Brunelle et al 2007 (Brunelle et al., 2007). For each sample, 20 ml of culture was harvested for cell cycle studies, 20 ml for toxin analysis and 5 ml for cell number determination. Additionally 40 ml of culture sample was collected during the middle of the light phase at the 6th circadian hour and at the end of the dark phase 24 th circadian hour for RNA extraction. Culture growth was monitored by cell counts using a Sedgewick Rafter counting chamber (Proscitech, Australia) and an inverted light microscope (Leica

Microsystems). The growth rate was calculated with the formula µ= ln(N1/N0)/ t1-t0 (Anderson et al., 1990), where t is the time in days and N is the cell number. In order to investigate gene expression over more circadian hours in white light cultures, white light grown cultures were sampled during the first, 6th and 12th hour of the light phase and during the first hour of the dark phase, the 6 th hour and the 12 th hour of the dark phase.

4.3.2. RNA extraction and DNAse treatment RNA was extracted from 40 mL of cultures harvested by centrifugation at 5,000 x g for 5 min, according to a published RNA extraction protocol (Harlow et al., 2006). Briefly, cell pellets were ground with microglass pestles in 1.5 ml microcentrifuge tubes with 30 μL RLT buffer (RNeasy Kit Plant and Fungi, Qiagen) containing 1/100 volume ß-mercaptoethanol on ice. Extractions were then continued following the manufacturer’s instructions. RNA was eluted in 30μL RNase-free water (Qiagen). Residual DNA was removed with TURBO DNAse according to the TURBO DNA-freeTM Kit (Applied Biosystems). RNA quality and quantity

Chapter 4 Cell cycle progression and gene expression was assessed using RNA 6000 Nano LabChip Kit in microcapillary electrophoresis (Agilent 2100 Bioanalyzer, Agilent Technologies).

4.3.3. cDNA synthesis cDNA synthesis was performed with the SuperScript TM III First-Strand Synthesis System for RT-PCR (Invitrogen) according to manufacturer`s instructions for First Strand cDNA synthesis. Briefly, reverse transcription of 100 ng total mRNA was performed in 50 µl reactions with a mixture of the provided oligo (dt) primer. Reverse transcription reactions were diluted 10 fold with RNase free water and 1 µl of the dilution was used as template in qPCR.

4.3.4. Primers Three possible reference genes were chosen for analysis, as they were most likely to be constitutively expressed and not co-regulated. Primers for the psbA, were designed with Primer 3 based on the consensus sequence from an alignment of Alexandrium sequences downloaded from GenBank. Primer details are outlined in Table 4.3.1.

Chapter 4 Cell cycle progression and gene expression

Table 4.3.1.: Gene names, Primer sequences, Annealing temperature (AT), Amplicon (AP) sizes in base pairs (bp), references

Gene Primer sequence (5` to 3`) AT (°C) AP (bp) Refrences

Primer name psbA psbAF CTGAATGGGAGTCAGCAACA psbAR ATCGAAAAAGCCCGTGGAGAA 60 167 this study sxtA4 sxtA4F CTGAGCAAGGCGTTCAATTC sxtA4R TACAGATMGGCCCTGTGARC 60 125 (Murray et al., 2011)

Cob cob_F TCCCATTTTTCCCTTTCWTT cob_R ATTTTTGTTGGGCACAGCTT 60 212 this study actin act_F ATCAAGGAGAAGCTCTGCTACATC act_R TCAGACTCGGCTGGAAGAGA 60 166 (Yauwenas in prep)

LSU rDNA catF CCTCAGTGAGATTGTAGTGC catR GTGCAAAGGTAATCAAATGTCC 60 108 (Hosoi-Tanabe and Sako, 2005)

4.3.5. Quantitative Real Time PCR Primer efficiency in real-time qPCR was determined according to Rasmussen (Rasmussen, 2001). Briefly, the standard curve was constructed from a 10-fold dilution series of a known concentration of fresh PCR product, ranging from 2-2 x 10-5 ng (Hou et al., 2010). The efficiency of the reaction was calculated as; E = (10(-1/m))-1, with m being the slope of the equation (Pfaffl, 2001; Rasmussen, 2001). qPCR was performed in triplicate for each sample using Evagreen dye (Biorad) in a final volume of 10 µl. The reactions were supplemented with 1µl of (0.1 mg ml-1) bovine serum albumin (BSA). The following PCR protocol was used: denaturation 95°C 15 s, annealing and amplification at 60°C for 30 s, over 40 cycles with continuous fluorescence measurements. All qPCR assays were followed by dissociation curve analysis to ensure that the single PCR products matched with the standard amplicon. The melt curve analysis was performed over the range 95-55°C, including a final cooling step and continuous fluorescence measurements.

Chapter 4 Cell cycle progression and gene expression

For the quantitative comparison of amplification rates of the investigated candidate reference genes and the target genes (sxtA4, psbA), the “threshold cycle “ CT was identified for each run as the cycle at which the fluorescence signal exceeded the background fluorescence of the reaction. Three technical replicates were performed and the mean values were calculated for each of the three biological replicates. For stability comparison of candidate reference genes, the Microsoft Excel add-in NormFinder was used as outlined in Andersen et al. (Andersen et al., 2004). The stability value is based on the combined estimate of intra- and intergroup expression variations of the genes studied. The gene with the least expression variability is calculated and an additional combination of the two genes is recommended that commonly reflects the lowest stability value for normalization (Andersen et al., 2004). The expression of sxtA4 was normalized against the reference genes recommended by NormFinder with the ΔCt target (control-treated) ΔCt ref (control-treated) Pfaffl equation: Ratio = (Etarget) /(Eref) (Pfaffl, 2001).

4.3.6. Statistical analyses The mean values of biological replicates and standard deviations of biological replicates as well as the statistical analysis were determined using GraphPad version 4.3 (San Diego, CA, USA). The statistical analysis consisted of a one-way ANOVA applied to the growth rate, toxin production and gene expression at different days. Post-hoc Tukey` s test were used to determine differences P value <0.05 was considered to be significant.

4.3.7. Toxin extraction Toxins were extracted from 14 ml of culture pellet with 200 µl of 0.1 HCl through boiling in a waterbath at 100 °C for 5 min (Ravn et al., 1995). Extracted toxins were collected in the supernatant by separation from cell debris by centrifugation at 16,000 rpm for 30 min at 4 °C, the centrifugation step was repeated thrice, the supernatant was transferred into a fresh tube each time, to acquire a clear extract. The toxin production rate was calculated with the equation µTox = ln(T1/T0)/t1-t0 (Anderson 1990).

4.3.8. Determination of toxin concentration per cell via Ultra Performance Liquid Chromatography, (UPLC)(Chapter 2)

Chapter 4 Cell cycle progression and gene expression

4.3.9. Flow cytometric analysis of DNA content and cell cycle stage with propidium iodine Ten to 20ml of culture was harvested by centrifugation at 5000 x g, preserved with 2% glutaraldehyde (v/v) and stored at 4°C. Subsequently the cells were centrifuged the supernatant discarded and the pellet resuspended in 1 ml of ice cold methanol and stored at 4°C for 3 h to extract pigments. The samples were then washed with 1 ml 1x PBS three times. After centrifugation the pellet was resuspended in 100 µl of propidium iodide (PI) staining solution working concentrations were made in 1ml 1x PBS (970 µl) with 10 µl RNAseA (1mg ml -1), 10 µg PI (1 mg ml-1), 10 μg RNase A ml-1, 0.1% v/v BSA per ml and 0.01% v/v tween. The cells were incubated in the staining solution at 4°C in the dark for at least 2 hours. The cells were then washed twice with 1x PBS before analysis and kept on ice in the dark. The proportions of cells in G1, S and G2+M were determined via flow cytometry. Cell cycle analysis and PI fluorescence were acquired via Flow Cytometry on the BD FACS Aria II, using a 20mW DPSS laser with 488 nm excitation wavelength and bandpass emission wavelength of 610/20. PI fluorescence intensities were deconvoluted using BD FACS Diva version 6.1.0 software to resolve cell cycle distributions. In brief 15,000 events were analyzed per sample. Dot-plots and histograms were created with FACS Diva software. Cell cycle analysis was achieved with FACS Diva software and the number of cells in a certain cell cycle was expressed as the percentage of the total cell number in the sample.

4.4. Results In general, light quality was found to have an impact on PST content levels of A. catenella. The highest PST content was measured in the cells grown in red light when compared to cells grown in white and blue light. The progression of cells through the cell cycle was not accompanied by signifcant changes in PST production levels at different circadian hours under any light conditions. Gene expression of sxtA4 and psbA did not change significantly over the circadian hours investigated in white light and darkness, and no significant differences in expression were detected in the blue and red light treatment.

Chapter 4 Cell cycle progression and gene expression

4.4.1. Cell cycle A. catenella displayed an average growth rate of 0.16 d-1 and an average division rate of 0.2. Hence only a small portion of the total population was found to proceed through the cell cycle each day.

100 30 (%) S-phase and G2 in Cells

80 20 60

40 10 20 CellsG1-phase in (%)

0 0 -2 0 2 4 6 8 10 12 14 Circadian hours

Blue G1 Blue S Blue G2

Figure 4.4.1.: Percentage of A.catenella cells in G1 phase (left Y-axis), and percentages of cells in G2 and S-phase (right Y-axis) at different circadian hours grown in blue light. The dark phase is indicated by shading.

When the population passed from the dark into the light phase, approximately 60 % of the cells were in G1 phase. With the beginning of the light phase, more cells divided, and the proportion of cells in G1 increased and the amount of cells in G2 decreased during the first three hours of the light phase. The proportion of cells in S and G2-phase increased then and peaked during the 7th circadian hour (Figure 4.4.1.). A small proportion of cells was still dividing over the light phase and cells in G2 and S-phase were increasing in average proportion till the last sampling hour.

The cells grown in red light seemed to have divided mostly in the dark phase (Figure 4.4.2.). The population of G1 cells decreased with the transition into light and cell percentages in the S-phase and G2-phase increased up to the 7 th circadian hour and decreased again after with an increase of cells in G1 phase, suggesting that division had started to take place again. (Figure 4.4.2.). It seems that red light induces DNA synthesis and replication slightly faster than blue light, whereas the transition hour into blue light induced division of the cells. It seems that the cell cycle progression is shifted in those two light conditions and likely to be prolonged in the blue light condition. Investigations over more circadian hours and over 60

Chapter 4 Cell cycle progression and gene expression several consecutive days are necessary to investigate this observation further. Red light might foster DNA synthesis and the proliferation of cells. In order to see if a shift in DNA-synthesis and S-phase is related to PST synthesis level changes, the proportion of cells in S-phase was plotted against PST production of cells grown in white, blue and red light (Figure 4.4.3.). Average highest PST production did not correlate with the time point of maximum of cell population in S-phase.

100 50 Cells in G2 and S-phase (%)

80 40

60 30

40 20

20 10 Cells in G1 phase (%) phase G1 in Cells

0 0 -2 0 2 4 6 8 10 12 14 Circadian hours G1 S G2

Figure 4.4.2.: Percentage of A. catenella cells in G1 phase (left Y-axis), and percentages of cells in G2 and S-phase (right Y-axis) at different circadian hours when grown in red light. Dark phase is indicated by shading.

Chapter 4 Cell cycle progression and gene expression

20 6 Cells in S-phase (%)

) White PST -1 15 White S-phase 4 Red PST 10 Red S-Phase Blue PST 2 Blue S-phase 5 Total PST (pg cell PST (pg Total

0 0 -2 0 2 4 6 8 10 12 14 Circadian (h)

Figure 4.4.3.: Total average PST per cell (left Y-axis) of A. catenella and the average percentage of cells in S-phase (right Y-axis) when cells were grown in red, blue and white light. Average highest PST production does not correlate with maximum of cell population in in S-phase

4.4.2. Relative gene expression of sxtA4 and psbA

Expression of sxtA4 and psbA over the diel cycle was stable, with a relative expression ratio of ± 0.5 (Figure 4.4.4.). Statistical analysis revealed that the fluctuations in expression were not significant, psbA, P= 0.1 and sxtA4 , P=0.4. The relative gene expression of sxtA4 in A.catenella when grown in blue, red and white light and sampled in the middle of the 6th circadian hour of the light phase (Figure 4.4.5.) showed a trend of downregulation for sxtA4 in blue light in comparison to red and white light, nevertheless the variance between the biological replicates was relatively high and the expression differences detected for sxtA4 (P=0.3) were not significant. The expression of psbA did not differ between light treatments (P=0.4) (Figure 4.4.6). Relative gene expression was calculated against reference genes that were chosen for each experiment, three reference genes cat, actin and cob were included as candidates. For the analysis of the relative expression of sxtA4 and psbA the best reference genes determined by Normfinder were cob and actin with a stability value of 0.054 when only investigated in for white light. A single reference gene, cob displayed the best stability value 0.060 for the analysis of gene expression in different light spectra. The expression of psbA

Chapter 4 Cell cycle progression and gene expression and sxtA4 was normalized against cob and actin against the 12th hour of the dark phase for the cell cycle experiment and for the light quality experiment respectively.

Figure 4.4.4.: Relative expression of sxtA4 and psbA during the light and dark. Gene expression was investigated at 6 circadian hours, the dark phase is indicated through shading.

1.0

0.5

0.0

-0.5 Expression ratio Expression

-1.0

red blue white Figure 4.4.5.: Relative expression of sxtA4 in red, blue and white light.

Chapter 4 Cell cycle progression and gene expression

2.0

1.5

1.0

0.5 Expression ratio Expression

0.0

red blue white

Figure 4.4.6.: Relative expression of psbA in red, blue and white light.

4.4.3. PST production of A. catenella during the diel cycle PST production of Alexandrium catenella Group IV, appears continuous over the cell cycle for the circadian period investigated. PSTs were detected at all circadian hours investigated, in the dark at the end of the dark phase at circadian hour 24 (-1) and during the circadian hours 1, 3, 7, 10, 12 in the light phase, the strain produced GTX – 1,4, Neo – STX , GTX – 2,3 and STX. The constant synthesis of PSTs over the different circadian hours was detected in all light conditions (Figure 4.4.7.). Total mean toxin content per cell differed significantly between the different light treatments, One-Way Anova with post-hoc Tukeys test P ˂0.0001. The highest PST content was detected in the cultures grown under red light (Figure 4.4.7.). The total PST content peaked in these cultures during the first circadian hour, with an average 18.8± 5.4 pg cell-1 and was the lowest in the dark with 13.3 ± 3.1 pg cell -1. The PST production in A.catenella grown under white light peaked during the 7th circadian hour with 13.1± 1.7 pg cell-1 (Figure 4.4.7.) during all other hours the toxin level remained between 10.7 ± 2.9 and 11.4 ± 4.9 pg cell-1. The culture grown under the blue light produced the lowest amount PSTs, the average per cell content was between 8.9 ± 0.53 and 10.6 pg cell-1 at all circadian hours. PST content did not differ significantly at different circadian hours of each treatment. One way ANOVA with post-hoc Tukey s test (p˂0.05) with a P-value of 0.4 for the blue light, 0.4 for white light, and 0.8 for the red light experiment. The toxin production rate Table (4.4.1.) did not differ significantly (P 0.788) in blue, red and white light.

Chapter 4 Cell cycle progression and gene expression

30 White

) 25 Red -1 Blue 20 15

Total PST (pg cell PST Total (pg 5

0 -2 0 2 4 6 8 10 12 Circadian (h)

Figure 4.4.7.: Production of PSTs by A. catenella ACCC01 at the circadian hours 1, 3, 7, 10, 12 during the light phase and at the circadian hour 24 (here -1) during the dark, when A. catenella was grown in blue, red and white light at 40 µmol s-1 min-1 photons. The dark phase is indicated through shading.

Table 4.4.1.: PST production rate of A. catenella cells grown in white, red and blue light between different circadian hours PST production rate PSTs (pg cell h-1) Time White light Red light Blue light 6am-7 am 0.07±0.31 0.34± 0.12 0.07±0.12 7am-9 am -0,01±0.04 -0.06± 0.23 0.05±0.07 9am-1pm 0.04±0.03 -0,02± 0.05 -0.04±0.04 1pm-4pm -0.06±0.05 0,00±0.07 -0.01±0.07 4pm-7pm -0.01±0.09 -0,01±0.05 0.03±0.04

The ratios of PSTs produced were similar under all conditions with the relative highest portions in the order GTX – 1,4 >GTX – 2,3 > Neo – STX and STX, (Table 4.4.2.). The average percentage of analogs of A.catenella did not differ significantly between the light treatments. In white light A.catenella produced 50.5 ± 2.95 Mol % GTX – 1,4, 11.9 ± 0.77 Mol % Neo – STX, 24.7 ± 2.53 Mol % GTX – 2,3 Mol % and 12.86 ± 1.12 Mol % STX. In 65

Chapter 4 Cell cycle progression and gene expression red light it produced 47.65 ± 3 Mol % GTX – 1,4, 11 ± 1.2 Mol % Neo – STX, 22 ± 2.18 Mol %, GTX – 2,3, 19.8 ± 2 Mol % STX and in blue light 52.17 ± 2.95 Mol % GTX – 1,4, 11.82 ± 0.72% Neo – STX, 24.14 ± 2.53 Mol % GTX – 2,3 and 11.97 ± 1.12 Mol % STX.The average Mol ratios did not differ significantly between treatments (P 0.95). The ratios of analogs produced changed slightly throughout the experiment in all three light conditions (Figures 4.4.8.1-3). The amount of the hydroxylated PSTs GTX – 1,4 and NEO – STX decreased with progressing hours throughout the light phase, whereas the non- hydroxylated PSTs GTX – 2,3 and STX increased proportionaly to the decrease of hydroxylated analogs.

Table 4.4.2.: Average Mol % of analogs present during the circadian hours tested GTX – 1,4 % Neo – STX % GTX – 2,3 % STX %

White 50.50 ± 2.95 11.94 ± 0.77 24.70 ± 2.53 12.86 ± 1.12

Red 47.65 ± 3.08 11.00 ± 1.22 22.24 ± 2.18 19.11 ± 2.09

Blue 52.17 ± 2.95 11.82 ± 0.72 24.14 ± 2.53 11.87 ± 1.12

70 GTX 1,4

60 Neo-STX 50 GTX 2,3 40 STX 30 20

10 Analog [%] total Analog PST of 0 -2 0 2 4 6 8 10 12 Circadian (Hours)

Figure 4.4.8.1.: Percentages of the PST analogs GTX – 1,4, GTX – 2,3, Neo – STX, STX produced by A. catenella when grown in white light.

Chapter 4 Cell cycle progression and gene expression

7 0 G T X 1 ,4 6 0 N e o -S T X 5 0 G T X 2 ,3 4 0 STX

3 0

2 0

1 0

Analog [%] of total0 PST -2 0 2 4 6 8 1012 Circadian (Hours)

Figure 4.4.8.2.: Percentages of the PST analogs GTX – 1,4, GTX – 2,3, Neo –STX, STX produced by A. catenella when grown in red light.

7 0 G T X 1 ,4 6 0 N e o -S T X 5 0 G T X 2 ,3

4 0 STX 3 0 2 0

1 0 Analog [%] of total PST 0 -2 0 2 4 6 8 1012 Circadian (Hours)

Figure 4.4.8. 3: Percentages of the PST analogs GTX – 1,4, GTX – 2,3, Neo – STX, STX produced by A. catenella when grown in blue light.

4.5. Discussion Light quality had a clear impact on the toxin content of A.catenella. The strain produced more of the analogues GTX – 1,4, Neo – STX and GTX – 2,3 and STX in white and red light than in blue light (Figure 4.4.7.). Toxin content levels did not differ significantly between the light and dark phase. With increasing hours of illumination a change in analog ratio was observed 67

Chapter 4 Cell cycle progression and gene expression during the diel cycle, a decrease of the hydroxylated PSTs (GTX – 1,4, Neo – STX) was compensated by an increase of non-hydroxylated PSTs (GTX – 2,3, STX). This conversion was observed in white, red and blue light. Although significant differences in toxin content were detected in cells grown in white, red and blue light (P˃0.0001) no significant differences in relative gene expression of sxtA4 and psbA (P=0.3 and P=0.4) were detected via RT-PCR in the different light treatments (Figure 4.4.4., 4.4.5., 4.4.6.). These genes might be regulated on the posttranscriptional level. In this study A. catenella displayed a rather slow growth and division rate of (0.16 day-1 and 0.2 division rate) under the light intensities of 40 µmol m-2 s-1. Therefore, only a small proportion of cells proceeded through the cell cycle at the given day. A trend in faster induction of cell cycle progression by red light was observed in comparison to blue and white, this observation needs further investigation, with more sampling points over consecutive days.

4.5.1. Gene expression of sxtA4 and psbA Real time PCR was performed in order to evaluate if the diel cycle and light quality influenced expression of the sxtA4 gene, putatively involved in the initation of STX synthesis and the gene psbA which encodes the D1 protein, a core protein of photosystem II, which is putitively regulated by light. Although significantly different total amounts of PSTs were produced in the different light treatments (P ˂0.0001), no significantly different levels in sxtA4 gene expression were detected (sxtA4 , P=0.3). The gene sxtA4 was constitutively expressed over the circadian hours investigated when PST levels were stable. No significant changes in psbA expression were detected under all light conditions and at different circadian hours (psbA, P= 0.1). Kobiyama et al investigated the expression patterns of the gene encoding the chlorophyll chla/c-binding protein (CAC) and peridinin chl a/-binding protein (PCP) from the dinoflagellate Alexandrium tamarense in light and darkness and found that mRNA levels of CAC were 7 fold higher during the light period compared to the dark, while accumulated mRNA and protein levels of PCP were nearly constant during the cycle. The study showed that PCP and CAC are differentially regulated, although their function is similar (Kobiyama, 2005). In this study relative expression of psbA was stable, which might indicate that psbA belongs to a group of genes that are post-transcriptionally regulated. This is in contrast to the regulation of genes in cyanobacteria in which light essentially modulates the transcription of the psbA gene (for review see (Golden, 1995). However, in higher plants and algae, the expression of the psbA gene has been reported to be mainly regulated at the post-

Chapter 4 Cell cycle progression and gene expression transcriptional level, e.g. mRNA stability and translation (for review see (Boyer and Mullet, 1988; Danon and Mayfield, 1994; Rochaix, 1992) and such is the case in this study for Alexandrium catenella. This study is also in line with the reports that most genes involved in circadian rhythms are regulated at the posttranslational level in dinoflagellates (Lin, 2011; Van Dolah et al., 2007a). In cyanobacteria toxin related genes have been reported to be differentially expressed in blue and red light. For example, the microcystin-synthesis related mcyB and mcyD gene expression was higher in red light compared to white light of the same intensity. When blue light was used, no change in transcript levels was observed (Kaebernick et al., 2000). However, the regulation of toxin synthesis pathways by different light quality is not well understood in dinoflagellates yet. In future microarray studies might be a better tool to detect genes that are differentially expressed in different light qualities. Since a microarray can contain tens of thousands of probes, it can accomplish the investigation of many genes in parallel. In addition comparison of proteomes of cells grown in blue, red and white light will allow to gain further insights into the regulatory cues of light on the metabolism of Alexandrium and its capacity to produce PSTs. Such studies could help to identify the metabolic changes that occur and lead to differential production of PSTs in red and blue light detected in this study.

4.5.2. Cell cycle progression in A.catenella Cell cycle studies on dinoflagellate cells are challenging due to their large genome size and their slow growth and division rate. In this study, only a small portion of the total population proceeded through the cell cycle each day. In the red and white light treatment the majority of the cells were entering the light phase as G1 concluding that division had taken place in the dark. In the light phase a proportion of cells progressed into S-phase, G2 and M-phase. In the blue light treatment cell cycle progression seemed to be shifted or prolonged as cell division also took place in the beginning of the light phase. In this study red light seemed to foster the progress of cells into S-phase followed by white and blue light. Light quality has been reported to influence cell cycle progression and the inititation of DNA synthesis in various organisms, red and blue light have been shown to have varying effects on circadian rhythms (Devlin and Kay, 1999). Brunelle et al reported for Karenia brevis, which displays phased cell division, in which cells enter S phase at precise times relative to the onset of light, that in the presence of blue light, the cells proceeded into S phase earlier, and a greater percentage of cells entered the cell cycle compared with the neutral density control and red light (Brunelle et

Chapter 4 Cell cycle progression and gene expression al., 2007). The circadian period of L. polyedrum was reported to be shorter with increasing intensity of blue light but was lengthened in increasing red light (Roenneberg and Hastings, 1988). In the green alga Chlamydomonas reinhardtii, the commitment point for cell division is shifted to a later time point and a larger cell size, when grown in blue as compared to red light. They observed cell division and DNA synthesis to occur earlier in cells grown red light compared to blue and white light (Oldenhof et al., 2004). The results in this study are hence mostly in line with the observations made for Chlamydomonas reinhardtii. The differential responses to red and blue light require further investigation and also characterization of photoreceptors involved in these processes. Future investigations will allow to further unravel which components of the light signaling pathways are involved in entrainment of the circadian rhythms and toxin production of the HAB forming species A. catenella ACCC01 .

4.5.3. PST synthesis A significant difference in average PST content levels was detected between the different light treatments in the present study (P ˂0.0001), however no correlation was found with the cell cycle progression. Former studies reported variations of PST levels in different Alexandrium strains over the diel light and dark period. Alexandrium strains seem to differ in cell cycle progression and PST production during the cycle (Harlow et al., 2007a; Taroncher- Oldenburg et al., 1999). It is possible that the proportional changes in cell populations progressing through different cell cycle stages were too minor to relate to a change in PST production in this experimental set up. Harlow et al 2007 reported that the highest PST production occured, when 56% of the cells of the population were in G2/M-phase and only a maximum of 20 % of the total population was seen to proceed into G2 phase. Light has been suggested to set the pace for toxin production in Alexandrium fundyense, PST production was reported to be discontinious over the cell cycle and directly correlated to the duration of the G1 phase during the light phase (Taroncher-Oldenburg et al., 1997, 1999). As the majority of the cells were actually in G1-phase over the circadian hours investigated, one could assume that PST production is likely to be related to G1-phase in this strain as well. In the present study, A. catenella produced PSTs throughout the light and dark phase. This is in line with Harlow et al who reported continuous synthesis of PSTs throughout the light and dark phase. Nevertheless, Harlow (2007) reported a constant profile of PSTs over the diel phase. In this study a change in PST ratios over the diel phase was observed as a decline of hydroxylated PSTs (GTX – 1,4 and Neo – STX) compensated by an equal increase in non-

Chapter 4 Cell cycle progression and gene expression hydroxylated PSTs (GTX – 2,3 and STX) occurring during the progression of the light phase. Such a proportional change of ratios of hydroxylated and non-hydroxylated PSTs may be due to the change of redox status of the cells during the diel cycle. The cell cycle is actually a redox cycle as studies in yeast, and in complex eukaryotes show that oscillations in energy metabolism, and redox state are intimately integrated with cell cycle progression (Burhans and Heintz, 2009; den Boer and Murray, 2000). Hydroxylation reactions are likely to be affected by a change in redox potential within the overall metabolism, which might explain the changes of ratios of hydroxylated and non-hydroxylated analogs observed in this study. In cyanobacteria Carneiro et al. suggested a circadian rhythm for PST production in the cyanobacteria C. raciborskii. They observed that the circadian rhythm of Neo-STX production was lost in the red light condition, the period with maximum production of STX and Neo-STX was longer (26h) in blue light than under white light (Carneiro et al., 2009). Such differences were not observed in this study. Future experiments should implicate more sampling hours and several sampling days in order resolve a better picture of cell cycle progression in different spectral light quality.

4.6. Conclusion Light is likely to be a major regulator of the signalling pathways leading to the development of toxic blooms. The light controlled physiological processes of species of Alexandrium are still poorly explored. Few photoreceptors have been described and identified in dinoflagellates, and it is not clear if cellular regulation occurs on the transcriptional or posttranscriptional level. Spectral light quality clearly impacts the toxicity of Alexandrium catenella, but it appears not to be regulated on the transcriptional level. Due to the observation that PST production occurred in all light conditions it is likely that regulation does not occur specifically through photoreceptors but might be influenced by different photosynthetic rates of Alexandrium catenella under the different light conditions, leading to a differential nutritional status and a difference in PST synthesis capacity. This requires further investigation (See Chapter 6). Knowledge about the light cues that regulate physiological processes of Alexandrium can help to predict development, progression and toxicity of Alexanrium bloom populations. This study provides valuable insights into the plasticity of PST production by a strain and indicates that light quality is a crucial regulator, which can play a role for different toxicities of Alexandrium cells within the water column.

Chapter 5 Bacterial communities associated with toxic and non-toxic Alexandrium tamarense, Group V strains

Chapter 5 Bacterial communities associated with Alexandrium tamarense

5.1. Abstract Bacteria are thought to play important roles in influencing the toxicity, ecophysiology and bloom dynamics of Alexandrium species. In this study, the temporal stability and community composition of bacteria associated with both a saxitoxin producing and a non-toxic strain of Alexandrium tamarense Group V clade (Tasmanian ribotype) were examined using molecular methods. Temporal analysis of community compositions, assessed at 5 time points during growth in batch culture using automated ribosomal intergenic spacer analysis (ARISA), suggested that bacterial community shifts were present but limited between specific phases of culture growth. Using 16S rRNA gene pyrosequencing, both strains were found to harbour a similar microbial diversity, with 84 operational taxonomic units (OTUs) and 90 OTUs identified for the non-toxic and toxic strain, at a sequencing depth of 12590 and 11274 sequences, respectively. In both the non-toxic and the toxic strain, the dominant bacterial species, representing 76.5 % and 61.4 % respectively of the total sequences recovered, belonged to the family Rhodobacteraceae. However, members of the Rhodobacteraceae associated with the toxic strain were closely related to Thalassobacter genus, while those associated with the non-toxic Alexandrium were more closely related to the genus Loktanella. Several orders with lower abundance such as Rhizobiales, Flavobacteriales, and Sphingomonadales were also identified in both strains and may be part of the core bacterial community associated with these dinoflagellates.

5.2. Introduction The genus Alexandrium contains more than 30 morphologically defined species, of which at least half are known to produce the toxin saxitoxin and its analogs, commonly known as paralytic shellfish toxins (PSTs), in varying quantities (Anderson et al., 2011; Balech, 1985). Generally, within the Alexandrium tamarense/catenella/fundyense species complex, the presence of toxin production capacity was thought to be characteristic within a clade (“ribotypes”), although the toxin profiles can differ substantially (Murray et al., 2012). Until recently, Alexandrium tamarense, Group V (“Tasmanian ribotype”) strains were considered exclusively non-toxic (Bolch and de Salas, 2007). However, it has been recently found that within this genotype, some strains can produce PSTs (Murray et al., 2012). This provided an opportunity to assess differences in bacterial community composition between PST producing and non-producing strains of the same ribotype. 74

Chapter 5 Bacterial communities associated with Alexandrium tamarense

Bacteria can be considered an integral part of the biological environment of toxic dinoflagellates, and lower toxicity has been reported in axenic compared to non-axenic Alexandrium catenella and Alexandrium tamarense cultures (Hold et al., 2001b; Uribe and Espejo, 2003). Bacteria can be free- living in the phycosphere or in the culture media (Bell et al., 1974; Blackburn et al., 1989; Hold et al., 2001b), can be attached to the dinoflagellate thecal surface (Kogure et al., 1981; Simon et al., 2002) or existing internally within the dinoflagellate cell as symbionts, and can thrive even in the nucleus (Doucette, 1995; Gallacher et al., 1997; Maas et al., 2007; Silva, 1990; Silva, 1962; Sousa, 1978). The role of bacteria in the production of PSTs is still elusive and controversial (Gallacher and Smith, 1999b). It has been proposed that bacteria are responsible for PST production in dinoflagellates (Kodama, 1990; Kodama et al., 1982; Silva, 1990). However, other studies have suggested that at least some of these putative PSTs produced by bacteria may not be PSTs, but chemically similar compounds (Baker et al 2003). The putative genes responsible for PST production are encoded in the dinoflagellate nucleus, possibly as a result of a lateral gene transfer from a bacterial species (Stüken et al 2011). Not every gene required in cyanobacteria for the production of STX has been found in studies of dinoflagellate EST libraries to date (Stüken et al., 2011). The genes encoding sxtD, sxtS, and sxtU, which are thought to be ‘core’ enzymes central to the STX synthesis pathway (Kellmann et al 2008), have not yet been found in studies of dinoflagellate transcripts (Stüken et al., 2011). Therefore, it is possible that there may be a role for enzymes produced by bacterial communities in the production of STX. In addition, bacteria have been implicated in the modification and biotransformation of algal toxins (Hold et al., 2001a; Hold et al., 2001b; Kodama, 1990). Besides their possible involvement in toxin production and conversion, it is known that the interactions between bacteria and phytoplankton can influence phytoplankton growth, reproduction, cyst formation, inhibition of mating and mortality (Adachi et al., 2003; Bolch et al., 2011; Ferrier et al., 2002) reviewed in (Doucette et al., 1998; Kodama et al., 2006). Most algal isolates are obtained by micropipetting a single algal cell from an environmental sample into a sterilized media, thereby producing a clonal culture (Guillard and Keller, 1984). The concept of the phycosphere, as the proximate surrounding of the microalgal cell, was introduced by Bell & Mitchell (1972), defined as an environment physically and chemically distinct from the surrounding water, which could favor the growth of certain microbial taxa (Bell et al., 1974). Bacteria that were initially present in the phycosphere are co-cultured with successive transfers (Jasti et al., 2005). Knowledge of the taxonomic community composition and the degree of natural variation of the bacterial community associated with species of

Chapter 5 Bacterial communities associated with Alexandrium tamarense

Alexandrium is limited. Former studies have investigated the composition of the bacterial community mostly through plating isolation techniques (Babinchak et al., 1997; Franca et al., 1995; Hold et al., 2001; Lu et al., 2000). Although valuable knowledge about bacterial consortia associated with Alexandrium has been acquired, culture based approaches may not provide an accurate representation of the true community structure in respect to abundance and taxonomy. Other studies have compared the bacterial community composition via 16S rRNA gene fragment analysis by DGGE (Jasti et al., 2005; Palacios et al., 2006). Some used tyramide signal amplification–fluorescent in situ hybridization (TSA-FISH) with confocal microscopy to determine the physical association of dinoflagellate cells with bacteria (Biegala et al., 2002). In this study, automated ribosomal intergenic spacer analysis (ARISA) and 16S rRNA gene pyrosequencing of the variable V1- V3 region were used to compare the bacterial populations associated with a saxitoxin producing and a non-toxic A. tamarense strain, Group V.

5.3. Material and Methods

5.3.1. Culturing Dinoflagellate cultures were maintained in GSe media (Blackburn 1989) at 18°C. Light was provided by white fluorescent bulbs (Crompton Light), with photon flux of 80 μmol photon m-2 sec-1 on 12/12 hour dark/light cycle. Strains used were ATCJ33, isolated from Cape Jaffa, South Australia, Australia (-36.94, 139.70) and ATNWB01, isolated from North West Bay, Tasmania, Australia (-43.08,147.31), isolated by M. de Salas and maintained in the University of Tasmania culture collection by G. Hallegraeff. Cultures for genomic DNA extraction and ARISA were inoculated in 500 ml of GSe media (Blackburn, 1989). Cultures were sampled during growth at day 7, 16, 22, 28, 34. Alexandrium tamarense ATNWBO1 produces GTX 5, with some STX, C1,2 and dcSTX with a concentration of 15.3 fmol cell-1 (Murray et al., 2012). The strain ATCJ33 has been confirmed as non-toxic. The detection limit of the HPLC of the cell cultures was considered to be 0.1 pg cell−1 for NEO and STX, 0.2 pg cell−1 for GTX – 1,4, GTX6 (B2) and GTX5 (B1), 0.5 pg cell−1 for C1,2, and <0.3 pg cell−1 for the analogues C 3,4 (Murray et al., 2012).

Chapter 5 Bacterial communities associated with Alexandrium tamarense

5.3.2. DNA extraction and PCR DNA was extracted from the cell pellets using the CTAB method. Quality and quantity of DNA was determined using a Nanodrop (Thermoscientific), and by amplifying the 16S rRNA gene with the universal bacterial primer pair R1494 5′-TACGGCTACCTTGTTACGAC-3, F27 5′-AGAGTTGATCCTGGCTCAG-3′ (Neilan et al., 1997). Polymerase chain reaction (PCR) amplification was performed in 20 μl reactions with a final concentration of 10 mM for each forward and reverse primers, 1 μl template, 2 μl 10x buffer (Bioline), 1 μl dNTPs

(Bioline), 1 μl MgCl2 (Bioline), 1 μl BSA (NEB), 0.2 μl Taq Polymerase (Bioline), and 11.8 μl MilliQ water. PCR cycling conditions were initial denaturation at 95°C for 5 min, followed by 30 cycles of 95°C for 30 sec, 55°C for 30 sec, 72°C for 1 min with a final extension at 72°C for 7 min.

5.3.3. Automated Ribosomal Intergenic Spacer Analysis (ARISA) The bacterial 16S-23S internal transcribed spacer (ITS, rDNA) region was PCR-amplified using the forward primer 1392f; 5′ GYACACACCGCCCGT 3′ (universal 16S rRNA gene) and a VIC (green) fluorochrome labeled reverse primer 23Sr; 5′ GGGTTBCCCCATTCRG 3′ (bacterial-specific 23S rRNA gene). PCR cycling conditions were initial denaturation at 95°C for 5 min, followed by 30 cycles of 95°C for 40 sec, 56°C for 40 s, 72°C for 1.30 min with a final extension at 72°C for 7 min. Polymerase chain reaction (PCR) amplification was performed in 20 μl reactions with a final concentration of 10 mM for each forward and reverse primers, 1 μl template, 2 μl 10x buffer (Bioline), 1 μl dNTPs (Bioline), 1 μl MgCl2 (Bioline), 1 μl BSA (NEB), 0.2 μl Taq Polymerase (Bioline), and 11.8 μl MilliQ water. Fragment length separation was performed at the Ramaciotti Centre for Gene Function Analysis (University of New South Wales, Sydney, Australia) using an Applied Biosystems 3730 DNA Analyser. A DNA size standard ladder, LIZ1200 (Applied Biosystems Ltd.), was added to each sample to facilitate fragment length identification. Fluorescence intensities were monitored with GeneMapper® v 3.7 (ABI Ltd.). All chromatographs were visually inspected to ensure quality runs. Fragment length and abundance data extracted from Genemapper were filtered using the T-REX (T-RFLP analysis EXpedited) online software (Culman et al., 2009) to distinguish true peaks from background fluctuations in fluorescence. This can interfere with correct ecological interpretation of automated data (Abdo et al., 2006). Filtered data was put into a custom fragment length binning script (Ramette, 2009) in R v2.10.1 (R Development Core Team 2009 (Alberto, 2009) to account for analytical errors in

Chapter 5 Bacterial communities associated with Alexandrium tamarense estimating fragment lengths. The algorithm allocated OUT`s to bins using a bin window size of 2 b.p. and a window shift of 0.1 b.p. calculated to provide the highest pairwise similarity among samples, Unweighted Pair Group Method with Arithmetic Mean (UPGMA).

5.3.4. 16S rRNA pyrosequencing Ribosomal tag pyrosequencing of the bacterial 16S rRNA gene variable regions V1-V3 was carried out at the Research and Testing Laboratories (Lubbock, Texas, USA) using the primers 27F and 519R (Lane, 1991). Potential chimeras were identified using the program chimera.slayer and removed, along with sequences containing any unresolved nucleotides (N). A 2% pre-clustering step was performed to remove other potential errors in sequence data (Huse et al., 2010). Sequences were aligned to the SILVA bacterial alignment database, and the alignment trimmed to ensure all sequences covered the entire alignment length. Clustering was performed at a sequence similarity cut-off of 0.03% dissimilarity (i.e. 97% similarity) and resultant operational taxonomic units (OTU’s) were taxonomically identified using the RDP taxonomy tool. All sequence manipulations were carried out in the Mothur suite of programs (Schloss et al., 2009). Sequences covered the entire alignment length. Clustering was performed at a sequence similarity cut-off of 0.03% dissimilarity (i.e. 97% similarity) and resultant operational taxonomic units (OTU’s) were taxonomically identified using the RDP taxonomy tool. All sequence manipulations were carried out in the Mothur suite of programs (Schloss et al., 2009).

5.3.5. Acetylene reduction Assay The acetylene-reduction assay (ARA) was performed on the toxic ATNWBO1 and the non- toxic ATCJ33 strain of Alexandrium tamarense in order to investigate if nitrogen fixation was detectable in the cultures. Nitrogen fixation could be putatively performed by associated bacteria, e.g. from the order Rhizobiales. Cultures were grown in GSe media and ethylene formation was measured using a Varian model 3700 Gas chromatograph equipped with a flame ionization detector and 1.8 m Porapak T column (Model HP 6890). The ARA for cultures was carried out in accordance with (Han and New, 1998). In brief 1ml of Alexandrium culture was aliquoted into rubber capped glass vials, the gas phase in the vials was replaced with an acetylene–air–nitrogen mixture (10:10:80 by volume) giving a reduced partial pressure of oxygen. The rate of ethylene production was measured by taking samples after 24 h and 48 h.

Chapter 5 Bacterial communities associated with Alexandrium tamarense

5.3.6. Phylogenetic analysis Pyrosequencing sequences of the most abundant OTUs (Rhodobacteraceae) for the non-toxic and toxic-strains were aligned and trimmed with Clustal W (Thompson et al., 1994). Representative sequences were used further for phylogenetic analysis, the sequences were aligned with related Rhodobaceraceae sequences from the NCBI and Silva database using Clustal W. Alignments were analyzed using maximum likelihood (ML) and the GTR model with parameters as implemented in the program PhyML v2.4.4 (Guindon and Gascuel, 2003). ML bootstrap analyses were performed using 100 replicates.

5.4. Results

5.4.1. Diversity of microbial communities Given the high similarity of ARISA profiles obtained for both cultures of the five week sampling period, we chose one sample (Time point 3) from each strain to examine using 16S rRNA gene pyrosequencing. After QC filtering there were 11274 and 12590 quality 16S rRNA gene sequence reads from the bacterial communities associated with the toxic and non- toxic A. tamarense strains respectively. At a 97 % sequence identity cutoff, these sequences clustered into 113 Operational Taxonomic Units (OTUs). Both samples had a similar microbial diversity and taxonomic composition. The non-toxic strain ATCJ33 harboured 79 OTUs of which 28 were unique and the toxic strain ATNWBO1 harboured 85 OTUs of which 34 were unique (Tables 5.4.1., 5.4.2.). The bacterial taxonomic composition detected in association with the non-toxic and the toxic strains was similar (Figure 5.4.1., 5.4.3.). Unique OTUs belonging mainly to the orders Sphingobacteriales, Spirochaetales, Oceanospirillales were detected in the non-toxic strain ATCJ33 (Table 1). Unique OTUs in the toxic ATNWBO1 strain belonged mainly to the orders of Rhizobiales, Rhodobacterales, Caulobacterales, Flavobacteriales (Table 5.4.2.). Overall these unique 16S rRNA sequences contributed only a small proportion to the overall sequence abundance, 3% in the toxic and 2% in the non-toxic, respectively. The most abundant unique OTU belonged to the genera Leptonemas and Hahella (0.7% of the total sequences) associated with non-toxic ATCJ33 and Donghicola and Aminobacter (0.5 % of the total sequences) associated with the toxic ATNWB01 strain.

Chapter 5 Bacterial communities associated with Alexandrium tamarense

5.4.2. The dominant bacterial taxa in Alexandrium tamarense The common dominant taxa were from the class Alphaproteobacteria, order Rhodobacterales representing 70.1 % of the bacterial population associated with the toxic strain ATNWBO1 and 84.7 % of the bacterial population associated with the non-toxic Alexandrium strain ATCJ33. Overall 31 OTUs of the family Rhodobacteraceae were detected. Eight OTUs were unique to the toxic and 4 OTUs to the non-toxic strain (Tables 5.4.1. and 5.4.2.). Major differences were detected in the relative abundance of OTU 43 which was identified as bacterium DG1128 (Table 5.4.3.) and further phylogenetic analysis identified it to be related to the genus Loktanella (Figure 5.4.4.). This 16S rRNA sequence comprised 76.5 % of the total sequences (bacterial community) derived from the non-toxic strain ATCJ33, but only 0.016 % of the sequences from the toxic strain ATNWBO1. In contrast, the bacterial community associated with ATNWBO1 was dominated by Rhodobacteracea OTUs 54 and 81 with 61.4 % of the total abundance. The SILVA database search did not relate these sequences to any cultured organism (Table 5.4.3.). Phylogentic analysis revealed these sequences to be closely related to Thalassobacter (Figure 5.4.4.). The second most abundant order in both strains was Flavobacteriales, comprising 20.3 % of the total bacterial community in the toxic Alexandrium strain and just 4.4 % of the non-toxic strain ATCJ33. Rhizobiales constituted 3% of the population of the toxic Alexandrium tamarense strain ATNWBO1 and 1% of the population of the non-toxic Alexandrium tamarense strain ATCJ33. The rest was represented by Spingobacteriales and other orders (Figure 5.4.3., Table 5.4.3.).

Chapter 5 Bacterial communities associated with Alexandrium tamarense

40 ATNWBO1

% of the community the of % 30 ATCJ33

Figure 5.4.1.: Bacterial community composition in the saxitoxin producing Alexandrium tamarense strain ATNWBO1 and the non-toxic Alexandrium tamarense strain ATCJ33 analyzed on the family level. The most common bacteria associated with the strains belonged to the family Rhodobacterales. Flavobacteriales, Sphingobacteriales, Rhizobiales and other families were represented by lower 16S rRNA abundance.

Chapter 5 Bacterial communities associated with Alexandrium tamarense

Table 5.4.1.: Bacterial OTUs present in the non-toxic ATCJ33 and not in the toxic ATNWBO1 strain.

Number of Sequences Phylum Class Order Family Genus Species

4 Verrucomicrobia Opitutae Opitutales Opitutaceae Opitutus Unclassified 45 Spirochaetes Spirochaetes Spirochaetales Leptospiraceae Leptonema Unclassified 12 Planctomycetes Planctomycetacia Planctomycetales Planctomycetaceae Blastopirellula Unclassified 1 Bacteroidetes Bacteroidia Bacteroidales M2PB4-65 Unclassified Unclassified 1 Firmicutes Bacilli Bacillales Paenibacillaceae Oxalophagus Unclassified 2 Proteobacteria Deltaproteobacteria Desulfobacterales Desulfobacteraceae Desulfatiferula Unclassified 3 Proteobacteria Deltaproteobacteria Bdellovibrionales Bacteriovoraceae Peredibacteria Unclassified 3 Proteobacteria Deltaproteobacteria Bdellovibrionales Bacteriovoraceae Peredibacter Unclassified 1 Proteobacteria Gammaproteobacteria Oceanospirillales Halomonadaceae Kushneria Unclassified 36 Proteobacteria Gammaproteobacteria Oceanospirillales Hahellaceae Hahella Unclassified 18 Proteobacteria Gammaproteobacteria Xanthomonadales Sinobacteraceae Solimonas Unclassified 1 Proteobacteria Gammaproteobacteria Alteromonadales Alteromonadaceae Teredinibacter Unclassified 1 Actinobacteria Actinobacteria Actinobacteridae Actinomycetales PeM15 Unclassified 1 Bacteroidetes Sphingobacteria Sphingobacteriales Flammeovirgaceae Uncultured Unclassified 2 Bacteroidetes Sphingobacteria Sphingobacteriales Flammeovirgaceae Microscilla Unclassified 1 Bacteroidetes Sphingobacteria Sphingobacteriales Cyclobacteriaceae Cyclobacterium Unclassified 5 Bacteroidetes Sphingobacteria Sphingobacteriales Cytophagaceae Pontibacter Unclassified 20 Bacteroidetes Sphingobacteria Sphingobacteriales Chitinophagaceae Balneola Unclassified 3 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Roseobacter_clade OCT_lineage 1 Proteobacteria Alphaproteobacteria Rickettsiales LWSR-14 Unclassified Unclassified 1 Proteobacteria Alphaproteobacteria Caulobacterales Hyphomonadaceae Robiginitomaculum Unclassified 1 Proteobacteria Alphaproteobacteria Rhodospirillales Rhodospirillaceae Inquilinus Unclassified 2 Proteobacteria Alphaproteobacteria Rhizobiales Phyllobacteriaceae Uncultured Unclassified 4 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Thalassobacter Unclassified 17 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Roseobacter_clade OBULB_lineage 18 Proteobacteria Alphaproteobacteria Rhodospirillales Rhodospirillaceae Thalassospira Unclassified 2 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Sulfitobacter Unclassified 9 Proteobacteria Alphaproteobacteria Rhizobiales Nordella unclassified unclassified

Chapter 5 Bacterial communities associated with Alexandrium tamarense

Table 5.4.2.: Bacterial OTUs present in the toxic ATNWBO1 and not in the non-toxic ATCJ33 strain.

Number of sequences Phylum Class Order Family Genus Species 4 Bacteroidetes Flavobacteria Flavobacteriales Flavobacteriaceae Psychroserpens Unclassified 2 Bacteroidetes Flavobacteria Flavobacteriales Flavobacteriaceae Pibocella Unclassified 10 Bacteroidetes Flavobacteria Flavobacteriales Flavobacteriaceae Flagellimonas Unclassified 1 Bacteroidetes Flavobacteria Flavobacteriales Flavobacteriaceae Gilvibacter Unclassified 3 Bacteroidetes Flavobacteria Flavobacteriales Flavobacteriaceae Sandarakinotalea Unclassified 8 Bacteroidetes Flavobacteria Flavobacteriales Flavobacteriaceae Winogradskyella Unclassified 1 Bacteroidetes Flavobacteria Flavobacteriales Flavobacteriaceae Robiginitalea Unclassified 2 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Roseobacter_clade NAC11-7 2 Proteobacteria Alphaproteobacteria Rhizobiales Phyllobacteriaceae Nitratireductor Unclassified 15 Proteobacteria Alphaproteobacteria Rhizobiales Phyllobacteriaceae Hoeflea Unclassified 1 Proteobacteria Alphaproteobacteria Sphingomonadales GOBB3-C20 Unclassified Unclassified 10 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Maritimibacter Unclassified 7 Proteobacteria Alphaproteobacteria Rhodospirillales Rhodospirillaceae Defluviicoccus Unclassified 6 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Stappia Unclassified 1 Proteobacteria Alphaproteobacteria Sphingomonadales Erythrobacteraceae Altererythrobacter Unclassified 3 Proteobacteria Alphaproteobacteria Sphingomonadales Erythrobacteraceae Erythrobacter Unclassified 4 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Roseovarius Unclassified 21 Proteobacteria Alphaproteobacteria Caulobacterales Hyphomonadaceae Hyphomonas Hyphomonas 1 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Yangia Unclassified 4 Proteobacteria Alphaproteobacteria Sphingomonadales KA1 Unclassified Unclassified 2 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Maribius Unclassified 3 Proteobacteria Alphaproteobacteria Rhodospirillales Rhodospirillaceae Roseospira Unclassified 22 Proteobacteria Alphaproteobacteria Rhizobiales Phyllobacteriaceae Aminobacter Unclassified 1 Proteobacteria Alphaproteobacteria Sphingomonadales Erythrobacteraceae Uncultured Unclassified 1 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Catellibacterium Unclassified 2 Proteobacteria Alphaproteobacteria Rhodospirillales Rhodospirillaceae OM75 Unclassified 43 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Donghicola Unclassified 6 Proteobacteria Gammaproteobacteria Oceanospirillales Alcanivoracaceae Alcanivorax Unclassified 18 Proteobacteria Gammaproteobacteria Alteromonadales Alteromonadaceae Marinobacter Unclassified 1 Proteobacteria Gammaproteobacteria Methylococcales Methylococcaceae Methylohalobius Unclassified 1 Firmicutes Clostridia Clostridiales Clostridiaceae Clostridium Unclassified 83

Chapter 5 Bacterial communities associated with Alexandrium tamarense

2 Firmicutes Clostridia Clostridiales Veillonellaceae Veillonella Unclassified 1 Bacteroidetes Sphingobacteria Sphingobacteriales Cyclobacteriaceae Uncultured Unclassified 3 Proteobacteria Alphaproteobacteria Rhodospirillales Rhodospirillaceae Roseospira Unclassified

Chapter 5 Bacterial communities associated with Alexandrium tamarense

Table 5.4.3: Bacterial OTUs present in the toxic ATNWBO1 strain and not in the non-toxic strain ATCJ33

Number of sequences Phylum Class Order Family Genus

ATNWBO1 ATCJ33 2 8620 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Roseobacter_clade DG1128 4353 3 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Seohaeicola Unclassified 3370 16 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Uncultured Unclassified 1723 55 Bacteroidetes Flavobacteria Flavobacteriales Flavobacteriaceae Sediminibacter Unclassified 402 381 Bacteroidetes Flavobacteria Flavobacteriales Flavobacteriaceae Maribacter Unclassified 325 10 Proteobacteria Alphaproteobacteria Sphingomonadales Sphingomonadaceae Sphingopyxis Unclassified 249 41 Proteobacteria Alphaproteobacteria Rhizobiales Phyllobacteriaceae Ahrensia Unclassified 73 28 Proteobacteria Alphaproteobacteria Rhizobiales Rhodobiaceae Anderseniella Unclassified 1 1 Proteobacteria Alphaproteobacteria Rhizobiales Rhodobiaceae Afifella Unclassified 4 28 Proteobacteria Alphaproteobacteria Rhizobiales TJ1 Unclassified Unclassified 263 231 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Roseobacter_clade Roseovarius 233 6 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Marinosulfomonas Unclassified 2 204 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Paracoccus Unclassified 73 86 Proteobacteria Gammaproteobacteria Thiotrichales Piscirickettsiaceae Methylophaga Unclassified 109 3 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Roseobacter_clade RGALL_lineage 227 6 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Roseobacter_clade Sulfitobacter 48 241 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Roseobacter_clade DC5-80-3 59 27 Bacteroidetes Flavobacteria Flavobacteriales Flavobacteriaceae Arenibacter Unclassified 4 15 Bacteroidetes Sphingobacteria Sphingobacteriales Cyclobacteriaceae Algoriphagus Unclassified 33 6 Bacteroidetes Sphingobacteria Sphingobacteriales Flammeovirgaceae Flexibacter Unclassified 10 155 Bacteroidetes Sphingobacteria Sphingobacteriales Flammeovirgaceae Flexithrix Unclassified 1 25 Bacteroidetes Sphingobacteria Sphingobacteriales Cytophagaceae Cytophaga Unclassified 5 171 Proteobacteria Gammaproteobacteria Oceanospirillales Oceanospirillaceae Pseudospirillum OM182 5 12 Bacteroidetes Sphingobacteria Sphingobacteriales Flammeovirgaceae Marinoscillum Unclassified 12 35 Bacteroidetes Sphingobacteria Sphingobacteriales Flammeovirgaceae Fulvivirga Unclassified 1 98 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Citreimonas Unclassified 1 35 Bacteroidetes Sphingobacteria Sphingobacteriales Flammeovirgaceae Reichenbachiella Unclassified 31 45 Proteobacteria Gammaproteobacteria Oceanospirillales Saccharospirillaceae Saccharospirillum Unclassified 8 1 Bacteroidetes Flavobacteria Flavobacteriales Flavobacteriaceae Yeosuan Unclassified 85

Chapter 5 Bacterial communities associated with Alexandrium tamarense

73 87 Proteobacteria Alphaproteobacteria Adriatic90 Unclassified Unclassified Unclassified 31 4 Proteobacteria Alphaproteobacteria Caulobacterales Hyphomonadaceae Hyphomonas Henriciella 5 3 Proteobacteria Alphaproteobacteria Rhodospirillales Rhodospirillaceae Pelagibius Unclassified 1 4 Proteobacteria Alphaproteobacteria Rhodospirillales Rhodospirillaceae uncultured Unclassified 4 8 Proteobacteria Alphaproteobacteria Rhodospirillales Rhodospirillaceae Telmatospirillum Unclassified 1 2 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Pseudoruegeria Unclassified 73 35 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Roseicyclus Unclassified 13 2 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Shimia Unclassified 9 24 Proteobacteria Alphaproteobacteria Rhodospirillales Rhodospirillaceae Thalassobaculum Unclassified 13 2 Proteobacteria Alphaproteobacteria Caulobacterales Hyphomonadaceae Maricaulis Unclassified 31 2 Proteobacteria Alphaproteobacteria Caulobacterales Hyphomonadaceae Oceanicaulis Unclassified 17 47 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Roseobacter_clade Jannaschia 4 3 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Roseobacter_clade ANT9093 29 1 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Roseobacter_clade Loktanella 3 2 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Roseobacter_clade TM1040 1 34 Proteobacteria Gammaproteobacteria Oceanospirillales Oleiphilaceae Oleiphilus Unclassified 1 5 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Thalassobius Unclassified 1 2 Proteobacteria Gammaproteobacteria Xanthomonadales Sinobacteraceae Singularimonas Unclassified 3 3 Proteobacteria Candidatus_Thiobios Unclassified Unclassified Unclassified Unclassified 1 1 Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobactraceae Sediminimonas Unclassified 8 1 Bacteroidetes Flavobacteria Flavobacteriales Flavobacteriaceae Salegentibacter Unclassified 77 2 Bacteroidetes Flavobacteria Flavobacteriales Flavobacteriaceae Leeuwenhoekiella Unclassified

Chapter 5 Bacterial communities associated with Alexandrium tamarense

Figure 5.4.2.: Phylogenetic analysis of the dominant Rhodobacterales populations in A. tamarense Group V strains, ATNWBO1 and ATCJ33. Bootstrap values > 50 are shown to the left of the nodes. The Rhodobacterales present in the culture of the non-toxic Alexandrium tamarense strain ATCJ33 and the toxic strain ATNWBO1 are highlighted.

Chapter 5 Bacterial communities associated with Alexandrium tamarense

5.4.3. Phylogenetic Analysis The Roseobacterales associated with the toxic and non-toxic Alexandrium ATNWBO1 and ATCJ33 branched seperately. The most abundant bacterial species identified in the non- toxic Alexandrium ATCJ33 was most closely related to Roseobacter, Loktanella species (Figure 5.4.2.). The most abundant bacterial species identified in the toxic strain was closely related to Thalassobacter and Roseobacter.

5.4.4. ARISA The ARISA data of the Alexandrium strain ATNWBO1 indicates that the bacterial community did not change drastically over growth in batch culture the smallest similarity seen was 57 between the first sampling point and all following sampling points. The bacterial community during exponential growth was very similar with 70-80 similarity at sampling point 2, 3, 4. The similarity was also high between the bacterial community at the 5th and the first sampling point with a similarity value of 60, but the slightly lower similarity indicated that community composition experienced a shift during growth (Figure 5.4.3.). The bacterial communities associated with Alexandrium ATCJ33 displayed a high similarity at different growth phases with a value of 70-90. The bacterial community experienced a shift at time point 4 at late exponential phase, similarity value of 55 (Figure 5.4.4.).

Chapter 5 Bacterial communities associated with Alexandrium tamarense

Figure 5.4.3: UPMGA cluster analysis of automated ribosomal intergenic spacer analysis (ARISA); (Fisher and Triplett, 1999) fingerprints generated from Alexandrium ATNWBO1 sampled over 5 weeks at days 7, 16, 22, 28, 34 represented by sampling points 1-5 during the growth in batch culture. ARISA was carried out as described (Brown et al., 2005). ARISA data in the form of abundance per binned operational taxonomic units were square root transformed and Bray- Curtis similarities used to generate the cluster.

Chapter 5 Bacterial communities associated with Alexandrium tamarense

Figure 5.4.4.: UPMGA cluster analysis of automated ribosomal intergenic spacer analysis (ARISA); (Fisher and Triplett, 1999) fingerprints generated from Alexandrium ATCJ33 sampled over 5 weeks at days 7, 16, 22, 28, 34 represented by sampling points 1-5 in the figure during the growth in batch culture. ARISA was carried out as described (Brown et al., 2005). ARISA data in the form of abundance per binned operational taxonomic units were square root transformed and Bray- Curtis similarities used to generate the cluster.

5.4.5. Acetylene Reduction Test No acetylene was reduced to ethylene during the incubation time in the vials inoculated with exponentially growing Alexandrium tamarense ATCJ33 and Alexandrium tamarense ATNWBO1 cultures (Table 5.4.4.)

Table 5.4.4. Acetylene Reduction Assay Sample Concentration of Acetylene in the Gas phase Alexandrium tamarense ATCJ33 99.902 Alexandriumtamarense ATNWBO1 99.904 Control (Acetylene) 100

Chapter 5 Bacterial communities associated with Alexandrium tamarense

5.5. Discussion The bacterial communities associated with both toxic and non-toxic Alexandrium strains did not differ greatly (50-80 % similarity) during growth in batch culture over a period of 5 weeks (Figure 5.4.1., 5.4.2.). Therefore, it is valid to assume that the bacterial community compositions detected by 16S rRNA pyrosequencing analysis, are representative for the bacterial communities associated with the strains in culture. Similarly Sapp et al (2007) investigated the bacterial community composition of various microalgae in batch culture and did not observe shifts in bacterial communities related to changes in the nutrient levels or algal growth phases (Sapp et al., 2007). However Fandino (2001) detected shifts in the bacterial community composition during a dinoflagellate bloom of Linguldinium polyedrum (Fandino et al., 2001). Discrepancies between reports might be due to differences between microalgal genera and species and also due to general differences between observations of batch cultures versus natural populations. Previous work has shown that an Alexandrium catenella culture was infected with intracellular bacteria (Cordova et al., 2003). Bacterial load was reported to be heavier when the culture was at stationary phase, and this observation has been termed “bloom inside the bloom”(Cordova et al., 2003). The interaction between intracellular bacteria and dinoflagellates was suggested to be bimodal: at the beginning of the growth curve it is mutualistic and at the later stages, bacteria become parasitic, possibly a factor that impacts the disappearance of blooms in nature (Cordova et al., 2003). Investigations on the total bacterial abundance or the bacteria/ algal cell ratio in the culture medium are needed in future to evaluate if this is also the case in the Alexandrium tamarense strains.

Both toxic and non-toxic Alexandrium tamarense strains, Group V, Tasmanian “ribotype” harboured bacteria from the orders Flavobacteriales, Sphingobacteriales, Rhodobacterales and Rhizobiales (Figure 5.4.3.). While both strains were dominated by the order Rhodobacterales, the taxonomy of the dominant Rhodobacterales OTU differed at the genus level, as phylogenetic analysis revealed. The most abundant species sequence associated with the non- toxic strain was closely related to Loktanella vestfoldensis, while the most abundant sequence of the toxic strain was related to Thalassobacter (Figure 5.4.4.). Several unique OTUs were identified for each strain, but these represented only 1-3 % of the total sequence abundance, suggesting that the bacterial communities of these two strains resemble each other on the order level.

Chapter 5 Bacterial communities associated with Alexandrium tamarense

These findings are in line with former reports using plating bacterial isolation techniques, restriction fragment polymorphism, DGGE of PCR 16S rRNA, sequencing of selected 16S rRNA genes. These studies also found Proteobacteria and bacteria from the Cytophaga- Flavobacteria-Bacteroides (CFB) to be the dominant phyla associated with Alexandrium in culture (Babinchak et al., 1997; Baker et al., 2003; Gallacher and Smith, 1999; Hold et al., 2001; Palacios et al., 2006). The bacterial diversity of the toxic and non-toxic strains of Alexandrium tamarense did not differ significantly, indicating that there might be a well established balance in the bacterial consortium thriving in the phycosphere of Alexandrium, which can harbor a certain amount of different bacteria based on their metabolic interdependence. The emerging picture is, that the bacterial communities associated with dinoflagellates are more notable for their similarities than their differences. The bacteria seem organized in a structured community rather than a random assemblage of species recruited from the marine bacterial metacommunity (Curtis and Sloan, 2004; Kodama et al., 2006).

Many of the bacterial orders present were common for toxic and non-toxic strains. One interpretation of this seemingly conserved community structure is, that it may reflect a physiological requirement for dinoflagellates (Alavi et al., 2001; Green et al., 2004; Kodama et al., 2006). However, bacteria from the same order can differ significantly in their physiological traits. Bacteria belonging to the Roseobacter clade have been reported to be particularly metabolically diverse (Buchan et al., 2005). Rhodobacterales possess diverse and flexible metabolic capabilities, including aerobic anoxygenic photosynthesis (Shiba, 1991), polyhydroxybutyrate metabolism (Cho and Giovannoni, 2004), catabolism of organic sulfur compounds (Geng and Belas, 2010; Gonzalez et al., 1999).

In this study the most abundant 16S rRNA sequence (76.5%) associated with the non-toxic strain was closely related to Loktanella vestenfoldensis (Figure 4) which has been described as a chemoheterotrophic pale-pink translucent short-rod-shaped bacterium (Van Trappen et al., 2004). The 16S rRNA sequence with the highest abundance (61.4 %) associated with the toxic Alexandrium strain ATNWBO1 was closly related to another relative of Roseobacter, Thalassobacter a Thalassobacter associated with Karlodinium micrum, Thalassobacter W-2- 2, E-3 (Zhu et al., 2010) and also Propane SIP20-6-30, GU584816 (Redmond et al., 2010) (Figure 5.4.2). Some Loktanella, Rhodovulum, Jannaschia sp. Thalassobacter species have been also described to produce bacteriochlorophyll a and be capable of anoxygenic photosynthesis (Allgaier et al., 2003; Macian et al., 2005; Schwalbach and Fuhrman, 2005; Yutin et al., 2005; Zeng et al., 2007). A previous study reported the isolation of Roseovarius

Chapter 5 Bacterial communities associated with Alexandrium tamarense from Alexandrium ostenfeldii and the finding of traces of bacteriochlorophyll a in the Roseovarius isolate (Biebl et al., 2005). This evidence for the association of bacteria capable of bacteriochlorophyll a synthesis and aerobic anoxygenic photosynthesis raises the question of whether such associations are more common amongst Alexandrium species, and if so if it is likely that this bacterial- association could be beneficial for the photosynthetic niche of the Alexandrium-bacterial consortium. HPLC pigment analysis and the molecular search of the marker gene of anoxygenic photosynthesis, pufM (Zeng et al., 2007) could further elucidate if this is the case in these strains. However, these abundant associates could be heterotrophic and chemoheterotrophic activity of the bacterial associate could be beneficial for the overall carbon metabolism when photosynthetic activity is limited.

It has been shown that α-Proteobacteria of the Roseobacter clade are the primary consumers of the algal osmolyte, dimethylsulfoniopropionate (DMSP). Bacteria can lyse DMSP to produce dimethylsulﬁde (DMS), a climatically active gas hypothesized to mitigate changes in global temperature (Charlson et al., 1987). Most DMSP, however, is quickly assimilated into bacterial biomass or transformed into nonvolatile compounds. The assimilation of sulfur from DMSP by marine bacteria is thought to occur through a demethylation– demethiolation process that produces methanethiol (MeSH), a volatile compound that can be used in the synthesis of methionine and cysteine (Kiene, 1996). The amino acid methionine is a precursor of saxitoxin and its analogues, the sulfur metabolism is hence very relevant to saxitoxin production, many of PSTs contain additional sulfur groups as side-moieties of the toxin backbone, e.g. the PSTs GTX and the C-toxins etc. (Shimizu, 1979; Shimizu et al., 1984). The abundance of some members of the Roseobacter group has been correlated with DMSP producing dinoflagellate blooms, and it has been suggested that they play an important role in sulfur cycling (Fandino et al., 2001; Gonzalez et al., 1999; Miller, 2005; Moran et al., 2003). The capacity to assimilate sulfur from DMSP is also spread amongst the bacterial groups of Alpha-, Beta-, Gamma-Proteobacteria and Cytophaga-Flavobacteria (Gonzalez et al., 1999; Vila et al., 2004), members of these groups have been also identified in this study (Table 5.4.1., 5.4.2., 5.4.3.). These findings highlight the need for the investigation of the physiology of the most abundant bacteria associated with the Alexandrium strains.

The bacterial 16S rRNA sequences, that constitute a smaller proportion of the bacterial communities in this study might play a more significant role in the bacterial-algal consortium and its physiology and potential toxicity than their abundance suggests. The bacterial

Chapter 5 Bacterial communities associated with Alexandrium tamarense community composition might be different in culture, than for the same Alexandrium strain in nature with changing and limiting environmental factors.

Species of the Rhizobiales are generally associated with nitrogen fixation (Somasegaran and Hoben, 1994). Considering nitrogen sources can be scarce in the marine environment (Fanning, 1989), this bacterial association might present a potential advantage for the microalgae to thrive under conditions when nitrogen sources are low. Their activity may increase nitrogen content in the phycosphere and marine microhabitat of the Alexandrium species. In this study nitrogen-fixation could not be detected under lab conditions with the acetylene reduction assay. No acetylene reduction was observed after 24 hours and 48 hours of incubation. However, the GSe media used for Alexandrium growth in this study is rich in nitrate (Blackburn 1989), and nitrogen fixation activity is known to be inhibited by nitrate (Manhart et al. 1980). Therefore further measurements under different culture conditions and culture media are needed for a final evaluation. The nifH gene could not be amplified in this study, eventhough Rhizobiales were detected in the cultures, possibly due to the large amount of dinoflagellate gDNA and inhibitors which can be challenging for the amplification of genes.

The abundance of nitrogen fixing associations should be further investigated under changing environmental conditions in nature. It is likely that some of these bacterial associates play a crucial role for the fitness of Alexandrium strains. As such associates have been formerly reported, for example. Hoefla alexandrii, a rhizobia isolated from Alexandrium minutum (Palacios et al., 2006). Similarly associated Flavobacteria, might play a potentially important role for siderophore production for the algal-bacterial consortium (Soltani et al., 2010).

Symbioses are a major source of evolutionary novelty by way of processes such as lateral gene transfer (Cavanaugh, 1994; Margulis, 1991; Sapp, 1994), and may be a possible origin of the genes involved in important processes such as saxitoxin synthesis (Stüken et al 2011). It is not clear where the members of the bacterial community in this study are localized within the cells, in the nucleus, attached to the cell surface or around the cells. The nature of the associations is also unclear and could be symbiotic, mutualistic, parasitic or commensalistic. Possibly several types are present. Nevertheless, a close association is likely to increase the probability of lateral gene transfer events (Hoffmeister and Martin, 2003; Timmis et al., 2004). An understanding of the association of bacteria with Alexandrium species will hence also foster a better understanding of genetic novelties of these microalgae.

Chapter 5 Bacterial communities associated with Alexandrium tamarense

Pyrosequencing does not necessarily replace traditional methods of bacterial isolation techniques and physiological classifications. It offers an excellent tool to analyze the composition of bacterial communities associated with microalgae in order to gain a comprehensive picture of the associated bacterial diversity. Knowledge of the taxonomic community composition and the degree of natural variation both within and between toxic and non-toxic strains is an important step to understand the physiological set-up and ecological niche of different Alexandrium strains, as well as biological cues leading to the toxicity of microalage in the context of the algal-bacterial consortium. Further studies should elucidate if the seemingly conserved bacterial community structures on the order level harbour functional physiological differences, depending on the associated bacterial species. More studies are needed on the changes of the bacterial community under different culture conditions in order to understand the community dynamics and shifts that may impact toxicity. The investigation of bacterial communities during bloom succession with pyrosequencing will be important to understand their role in the succession of HABs. High throughput sequencing can be used in future to characterize functional, physiological groups of phytoplankton through the implication of sequencing of target genes such as pufM for aerobic anoxygenic photosynthesis and nifH for nitrogen fixation in order to better understand potential nutritional dynamics of importance for the bacterial-algal consortium. This technology may subsequently also facilitate the development of better monitoring expertise and eventually improvement in the management of HABs.

5.6. Future studies and directions This study has shown that 16 S rRNA pyrosequencing of the bacterial community associated with toxic and non-toxic Alexandrium tamarense can provide high resolution identification of the bacterial community composition, revealing similarities and differences between the bacterial communities with a resolution up to the strain level. Further analysis of bacterial communities will provide significant insights into bacterial community structure. Further studies should elucidate if the differences observed on the strain level of bacterial associates differ due to their physiological characteristics, and if the seemingly conserved bacterial community structures on the order level harbor functional differences depending on the associated bacteria species, impacting the autecology of Alexandrium. The investigation of bacterial communities during bloom succession with pyrosequencing will be important to understand their role in the succession of HABs. High throughput sequencing can be used in 95

Chapter 5 Bacterial communities associated with Alexandrium tamarense future to characterize functional, physiological groups of phytoplankton through the implication of sequencing of target genes such as pufM for aerobic anoxygenic photosynthesis and nifH for nitrogen fixation in order to better understand potential nutritional dynamics of importance for the bacterial-algal consortium.

Chapter 6 The impact of light quality on paralytic shellfish toxin synthesis by Alexandrium catenella

Chapter 6 The impact of light on PST synthesis

6.1. Abstract High cell proliferation of the prominent saxitoxin STX producer Alexandrium catenella, often results in paralytic shellfish poisoning (PSP) incidents. Light is a major regulator of growth and biomass formation in the ocean. In the photic zone the quality of light changes with water depth and due to varying environmental factors. In this study the impact of light quality on growth rate, pigment composition, bacterial community composition and paralytic shellfish toxins (PSTs) synthesis was investigated for Alexandrium catenella, group IV. The specific growth rates observed for cells grown in the blue, red and white light were similar, with small differences in the order (blue >white>red). Negative correlation between growth rate and PST synthesis was observed in all light treatments (r= - 0.56, P=0.02). A. catenella displayed the lowest PST content (11.64 ± 1.2 pg cell -1) when grown in blue light, PST contents were higher in cells grown in white (17.82 ± 2.4 pg cell-1) and red light (15.04 ± 1.4 pg cell -1). The average PST production differed significantly between the white and the blue light condition (P 0.04). Similarly chlorophyll content was highest in cells grown in white and red light with 94 ± 5.1 pg cell-1 and 80 ± 2.5 pg cell-1, blue light grown cells contained only 49 ± 2.3 pg cell- 1. Photoacclimation had taken place over the incubation period, with slightly higher peridinin content in white and red light grown cells and higher absorption in the blue green light range in blue light grown cells. These findings suggest that PST production is related to growth rate and photoacclimatory processes, especially to the red light spectra. Small shifts of the bacterial community associated with A. catenella in the different light treatments indicate that light quality may also impact the relationship of Alexandrium with its biotic environment. PST synthesis is hence likely to change with water depth, when spectral light quality and bacterial community associated with the algae experience changes according to the vertical niche partitioning within the water column.

Chapter 6 The impact of light on PST synthesis

6.2. Introduction The formation of harmful algal blooms by PST producing dinoflagellates has been suggested to be affected by multiple environmental factors, such as temperature (Ogata et al., 1987), nutrient levels (Anderson et al., 1990; Boyer et al., 1987), salinity (Lim et al., 2011; Parkhill and Cembella, 1999; White, 1978) and light (Hwang and Lu, 2000; Ogata et al., 1987; Usup et al., 1994). The direct and indirect effects of light (photon flux, density, PFD) on PST production are potentially versatile. The synthesis of PSTs imposes an extra requirement for photosynthetically- derived carbon skeletons, e.g. for amino acids and acetate, as well as high energy light intermediates (e.g. ATP, NADH/NADPH) (Cembella, 1998). Several studies investigated the impact of different light intensities on PST production with inconsistent results. Distinct light intensities evoke the highest PST production in different Alexandrium species and strains (Boczar et al., 1988; Boyer et al., 1987; Etheridge and Roesler, 2005; Lim et al., 2006; Parkhill and Cembella, 1999). The photosynthetic rate of algae is defined by the light intensity and the spectral quality of the incoming light. The characteristic array of light harvesting pigments further determines, which and how much light is used for photosynthesis (Kirk, 1994). The intensity and spectral quality of light may vary markedly with the depth of the water column. Blue and green light are weakly absorbed and penetrate into deep waters. The absorption of light by water begins to rise as wavelength increase above 550 nm and is significant in the red region (Kirk, 1994). Species of Alexandrium undertake signiﬁcant vertical migration from nutrient-depleted well-lit surface waters down to dark relatively nutrient replete waters (MacIntyre et al., 1997). Alexandrium also thrives through a meroplanktonic life-cycle and is exposed to changing water depths during its life span (Wyatt and Jenkinson, 1997). The suite of photosynthetic pigments is of major significance for the ecological niche of an algal group and its ability to compete for solar radiation within the water column (Engelmann, 1883; Glazer, 1981; Kirk, 1994; Stomp et al., 2004). The plastids allowing Alexandrium species to photosynthesize are unique for dinoflagellates, and contain chlorophyll c2 and peridinin as the major carotenoid, chlorophyll a is present with peridinin in a protein complex called Peridinin-Chlorophyll a-Protein (PCP) (Ogata et al., 1994; Prezelin and Alberte, 1978; Prezelin and Triplett, 1989). Peridinin and chlorophyll c absorb light within the “Grünlücke” which describes the spectrum of light between 490 and 620 nm. This spectrum range lies out of the range of the absorption spectra of the chlorophyll a and b, and is not absorbed by green algae living close to the water surface (Engelmann, 1883; Engelmann, 1884; Krikunova et al., 2006). The absorption spectra of the chromoproteins chlorophyll c and peridinin facilitate the utilization of radiation in the blue-green (458 – 553 100

Chapter 6 The impact of light on PST synthesis nm) and orange (585 – 647 nm) regions of the visible spectrum (Faust et al., 1982). Similarly cyanobacteria, glaucophyta, cryptophyta have adapted to use light of this spectrum through the production of phycobilliproteins (Engelmann, 1883; Engelmann, 1884). It is hence plausible to ask, if the adaptation to efficiently absorb light in the spectrum of the “Grünlücke” is related to the capacity of PST synthesis in cyanobacteria and dinoflagellates and if changes in spectral light quality impact pigment and PST synthesis in an interconnected manner. The distribution and ecological success of Alexandrium is largely defined by its physical and chemical environment. However, relationships with the biological components of an ecosystem such as microbes, play an important role for its successful proliferation and survival (Kodama et al., 2006). Bacteria are an integral part of the ecophysiology of toxic Alexandrium sp. (Gallacher and Smith, 1999; Smith et al., 2002) and their role in PST production is controversial and not fully understood yet. However, bacteria associated with dinoflagellates have been reported to autonomously synthesize PSTs (Gallacher et al., 1997; Kodama, 1990) and biotransform PSTs (Kotaki et al., 1985). The impact of bacteria on the nutritional status, e.g. by supplying nutrients such as vitamins and iron to the dinoflagellate cell, could also impact the capacity for PST production (Amin et al., 2009; Croft et al., 2006; Keshtacher-Liebso et al., 1995; Maldonado and Price, 1999). Recently some Alexandrium species thought to be exclusively phototrophic, have been revealed to be also capable of bacterivory and mixotrophy (Du Yoo et al., 2009; Jacobson and Anderson, 1996; Jeong et al., 2005; Legrand and Carlsson, 1998; Nygaard and Tobiesen, 1993). Such behavior might play a crucial role for the maintenance of the nutritional status and survival, when light quality and intensity are limited and consequently photosynthetic activity insufficient.

Light is hence likely to impact the interactions of the algal-bacterial consortium and their role in PST synthesis. Theoretically algal-bacterial relationships may be impacted in various ways, fostering symbiotic relationships with bacteria, or feeding of algae on bacteria, depending on the nutritional situation (Biebl et al., 2005; Jacobson and Anderson, 1996; Legrand and Carlsson, 1998). Maas et al investigated if photosynthesis is a requirement for paralytic shellfish toxin production in the dinoflagellate Alexandrium minutum algal-bacterial consortium. They found that inhibition of photosynthesis resulted in changes in the toxin profile of an A.minutum strain and observed a link to the presence of high nutrient requiring copiotrophic bacteria (Maas et al., 2007). In this study the manipulation of the incoming orange/red and green/blue light spectra, was implicated to investigate the impact of light quality on growth, pigment synthesis, PST production of Alexandrium catenella. Additionaly, 101

Chapter 6 The impact of light on PST synthesis the impact of light quality on the bacterial community composition was investigated via PCR- based 454 pyrosequencing of the bacterial 16S rRNA gene in A.catenella cultures grown in blue, red, and white light.

6.3. Material and Methods

6.3.1. Culture growth conditions The strain used in this study, A. catenella ACCC01, a member of Group IV (Murray et al., 2011c), (see Chapter 2– 4) was grown in GSe medium (Blackburn et al., 1989) in a culture cabinet (Labec, Australia) at a temperature of 18°C ± 1°C and 100 µmol photon m-2 sec-1, on a 12/12 hour light/dark cycle. A bulk culture was set up and grown until cell density reached 135 cells ml-1, the culture was then split into 9 flasks, three flasks were placed in a blue, three in a red and three in a neutral density filter cylinder, and placed at equal distance from the light source. Roscolux filters (Port chester, NY, USA) of matched 20% transmittance were used, for red (R19) or blue (R367) and a neutral density filter (Lee No. 210) for the white light controls, with all treatments thus receiving 40 µmol photon m-2 sec-1. Filter transmission profiles are shown in Figure 6.3.1.. All cultures were grown for 40 days. Samples from triplicate cultures of the red, blue and neutral density filter control were taken for crude pigment extraction, toxin extraction and cell counts on day 13, 20, 28, 30, 34. Samples were taken during the 6th circadian hour of the light phase. Culture growth was monitored by cell counts using a Sedgewick Rafter Counting chamber (Prositech) and an inverted light microscope (Leica Microsystems). The specific growth rate was calculated using the equation: µ= ln(N2/N1)/ t2-t1 where µ= specific grwoth rate, N1 and N2 are the number of cells per ml at the time t1 and t2 respectively (Anderson et al., 1990).

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Lee 210 Roscolux # 19 100 Roscolux # 367

40 Transmission % Transmission 20

0 360 390 410 420 460 480 520 560 600 640 650 680 720 Wavelength nm

Figure 6.3.1.: Transmission profiles of the blue Roscolux (R367), the red Roscolux (R19) and the neutral density filter (Lee 210).

6.3.2. Pigment extraction and quantification For pigment extractions 14 mL of culture were harvested by centrifugation (5000 x g, 5 min , 4°C) in dim light in falcon tubes wrapped with appropriate filter colour. The supernatant was discarded and tubes containing the cell pellets were wrapped with aluminium foil and stored at -20°C prior to analysis. Crude pigment extracts were prepared by extraction in 90% methanol overnight at 4°C. Spectral analysis of pigments was performed at room temperature using a Hitachi F-4500 fluorescence spectrophotometer (5 nm slit width for emission and excitation) at wavelength between 400 nm and 800 nm. Chlorophyll a + c content was calculated with the equation according to Ritchie et al (2008): Chla (µg/ml) =13.655 *(A665- A632)-3.45*(A320-A750) and Chlc = 32.937*(A632-A750) -7.014*(A665-A750) (Ritchie, 2008). Pigment extract absorption spectra in the range between 400 and 800 nm were normalized against the white light measurement at 442 nm, for samples take on day 34 in order to assess relative differences of pigment contents in extracts from cells grown in white, red, and blue light. Additionally the pigment extract absorption spectra were normalized at wavelength 590 nm (peridinin specific) (ref) and 455 nm (chlorophyll c specific) specific for all samples for the sampling days 13, 20, 28, 30, 34.

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6.3.3. Statistical analyses The mean values of biological replicates and standard deviations of biological replicates as well as the statistical analysis were determined using GraphPad version 4.3 (San Diego, CA, USA). The statistical analysis consisted of one-way ANOVA applied to the growth rate, toxin production and pigment synthesis. Post-hoc Tukey s test was used to determine the P value, a value of <0.05 was considered to be significant.

6.3.4. Toxin extraction 14 ml of culture at sample days was harvested by centrifugation at 5.000g for 5 min. The toxins were extracted with 300µl of 0.1 HCL by hydrolization in a boiling water bath for 5 min (Chang et al., 1997). Extracted toxins were collected in the supernatant by centrifugation.

6.3.5. Determination of toxin concentration per cell/ UPLC

See chapter 2

The toxin production rate was calculated with the equation µTox = ln(T1/T0)/t1-t0 (Anderson 1990).

6.3.6. DNA extraction and PCR DNA was extracted from A. catenella cells grown in red, blue and white light for 16 days, using the CTAB method (Blackburn, 1989). Quality and quantity of DNA was determined using a Nanodrop (Thermoscientific), and by amplifying the 16S rRNA gene with the universal bacterial primer pair R1494 5′-TACGGCTACCTTGTTACGAC-3, F27 5′- AGAGTTGATCCTGGCTCAG-3′ (Neilan et al., 1997). Polymerase chain reaction (PCR) amplification was performed in 20 μl reactions with a final concentration of 10 mM for each forward and reverse primers, 1 μl template, 2 μl 10x buffer (Bioline), 1 μl dNTPs (Bioline), 1

μl MgCl2 (Bioline), 1 μl BSA (NEB), 0.2 μl Taq Polymerase (Bioline), and 11.8 μl MilliQ water. PCR cycling conditions were initial denaturation at 95°C for 5 min, followed by 30 cycles of 95°C for 30 sec, 55°C for 30 sec, 72°C for 1 min with a final extension at 72°C for 7 min.

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6.3.7. 16S pyrosequencing and 16 S rRNA PCR Ribosomal tag pyrosequencing of the bacterial 16S rRNA gene variable regions V1-V3 was carried out at the Research and Testing Laboratories (Lubbock, Texas, USA) using the primers 27F and 519R (Lane, 1991).

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6.4. Results

6.4.1. Growth rate A. catenella ACCC01 displayed a similar growth rate under the three light conditions. The growth rate was slightly higher in blue light with an average of 0.23 ± 0.02 than white light with 0.22 ± 0.01 and red light with 0.21 ± 0.0. Statistical Analysis with One-way Anova and Tukey´s Post-hoc test (P >0.05) revealed that the growth rates differed significantly between the red and blue light treatment with a P-value of 0.0178 (*) (Figure 6.4.1).

100000

10000

Cells/mL 1000

100 0 5 10 15 20 25 30 35 40 Days Blue White Red

Figure 6.4.1.: Growth of A. catenella ACCC01 over a period of 40 days at 40 µmol m-1 s-1 at a 12h L: D cycle at 18°C in white, red and blue light. Five sampling points are indicated with dashed lines.

6.4.2. Growth rate and PST synthesis A. catenella ACCC01 displayed decreasing growth rates from 0.3 d-1 to 0.14 d-1, when passing from early exponential to late exponential growth during the incubation period (Figure 6.4.1.). The total PST production per cell increased with decreasing growth rate over time. The highest average PST production was detected in white light, with an average of 17.82 ± 2.4 pg cell-1 followed by the red light treatment with an average of 15.04 ± 1.4 pg cell -1 and only 11.64 ± 1.2 pg cell -1 in the blue light condition. The average PST production differed significantly P= 0.04 (*) between the white and blue light treatment.

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40 0.4 Growth rate (

) -1 30 0.3

20 0.2

 day

10 0.1 -1 ) Total PST (pg cell PST (pg Total

0 0.0 10 15 20 25 30 35 40 Days Growth rate white PST red Growth rate blue PST blue Growth rate red PST white

Figure 6.4.2.: Total average PST production and growth rate of A.catenella grown in blue, red and white light at 40 µmol m-2 sec-1.

Toxin production increased with decreasing growth rate. The growth rate and PST production correlated with, r = -0.56, (P = 0.015), Figure 6.4.2. The relatively highest PST levels were detected at the slowest growth rate of 0.14 d-1 with 29.8 ± 1.8 pg cell-1 in cells grown in white light and 23.7± 2 pg cell-1, 14.1 ± 2.6 pg cell-1 in cells grown in red and blue light, respectively (Figure 6.4.1.). The average PST production rate of cells grown in different light spectra did not differ signifcantly P (0.39), with on average 0.063 ± 0.08 pg per cell per day in white light, 0.059 ± 0.05 pg per cell per day in red light and on average 0.023 ± 0.05 pg per cell per day in blue light. The toxin profiles of A. catenella cells grown in red, blue and white light did not differ significantly. Cells grown in all treatments displayed a characteristic ratio of analogs. The most abundant analog being GTX – 1,4 (≈ 70 %), GTX – 2,3 (≈10-25%), Neo-STX (≈10-15%) and STX with up to 2 %. The ratios fluctuated slightly between treatments and at different sampling points. Such fluctuations are likely due to conversions between hydroxylated GTX – 1,4 and Neo-STX and non-hydroxylated GTX – 2,3 and STX. Saxitoxin levels were slightly lower in the blue light grown cells compared to the red and white light grown cells (Figures 6.4.3., 6.4.4., 6.4.5.).

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75 GTX 1,4 Neo-STX 60 GTX 2,3 45 STX

15 Analog [%] total Analog PST of 0 10 15 20 25 30 35 Days

Figure 6.4.3.: PST profile of A.catenella ACCC01 grown in red light. Percentage of GTX – 1,4, Neo-STX, GTX – 2,3 and STX of the total toxin content over the growth period

75 GTX 1,4 Neo-STX 60 GTX 2,3 45 STX

15 Analog [%] total Analog PST of 0 10 15 20 25 30 35 Days

Figure 6.4.4.: PST profile of A.catenella ACCC01 grown in white light. Percentage of GTX –1,4, Neo-STX, GTX – 2,3 and STX of the total toxin content over the growth period

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75 GTX 1,4 Neo-STX 60 GTX 2,3 45 STX

15 Analog [%] total Analog PST of 0 10 15 20 25 30 35 Days .

Figure 6.4.5.: PST profile of A.catenella ACCC01 grown in blue light. Percentage of GTX – 1,4, Neo-STX, GTX – 2,3 and STX of the total toxin content over the growth period.

The molar percentage of PST analogs was on average as follows in the blue light treatment analogs were present with 66.98 ± 1.63 % Mol GTX – 1,4, 17.09 ± 1,55 % Mol, Neo-STX, 14.7 ± 2.77 % Mol GTX – 2,3, 1.2 ± 0.34 % Mol STX. In the red light treatment 69.05 ±1.2 % Mol GTX – 1,4, 14.68 ± 1.64% Mol and 1.36 ± 0.36 % Mol STX. In the white light treatment 68.78 ± 0.96 % Mol GTX – 1,4, 15.4 ± 2.1 % Mol Neo-STX, 14,2 ±1.6 % Mol GTX – 2,3 and 1.64±0,49 % Mol STX. The molar % of analogs did not differ significantly between light treatments (P=0.99).

6.4.3. Pigment extracts of A. catenella cells grown in red, blue and white light Absorption spectra were measured for pigment extracts of A. catenella cells grown in red, blue and white light. In general, red and white light grown cells displayed almost identical absorption spectra, whereas blue light grown cells displayed slightly higher absorption in the blue light region and slightly lower absorption in the red light region at the end of the incubation period on day 34 (Figure 6.4.6.). Absorption spectra in the region of orange light, absorbed by peridinin in the range of 585-647 nm were lower in the blue light compared to red and white light grown cells, on day 34 (Figure 6.4.7.). The normalized absorption at 590 nm (characteristic for peridinin absorption) of pigment extracts of A. catenella cultures grown in red, blue and white light, did not differ significantly (P=0,054) 4.6.9. but displayed a trend with decreasing absorption at 590 nm in the pigment extracts of blue light grown cultures, over the investigated time from day 13 to day 34. The absorption of blue/green light 485-558 nm, absorbed by chlorophyll c was higher in the blue light grown cells, compared to red and 109

Chapter 6 The impact of light on PST synthesis white light grown cells (Figure 6.4.9.) on day 34. Normalized absorption at 455 nm of pigment extracts of A. catenella cultures grown in red, blue and white light did not differ significantly (P=0,39) Figure 6.4.10, but showed a subtle trend of increasing absorption at 455 nm in the blue light grown cells compared to red and white, over the investigated time period. Blue light grown cells had an overall slightly higher absorption in the blue-green range and a lower absorption in the red region especially around 670 nm, compared to red and white light grown cells on day 34 (Figure 6.4.11.). The chlorophyll a/c ratio indicated a trend of higher chlorophyll c levels in blue light grown cells Figure 6.4. 12.

1.2

1.0

0.8

0.6

Absorption 0.4

0.2

0.0 400 450 500 550 600 650 700 750 800 nm

Red White Blue

Figure 6.4.6: Absorption spectra (400 nm – 800 nm) of pigment extracts from A. catenella cultures grown in red, blue and white light. Spectra were normalized at wavelength 442 nm.

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0.15

0.10

0.05 Absorption

0.00 600 620 640 nm

Blue Red White

Figure 6.4.7.: Absorption spectra in the region of orange light (580 nm – 640 nm) of pigment extracts from A. catenella cultures grown in red, blue and white light. Spectra were normalized at wavelength 442 nm (Day34).

0 .0 8 B R 0 .0 6 W

0 .0 4 5 9 0 n m

0 .0 2 Normalized Absorption 0 .0 0 0 5 10 15 20 25 30 35 Sampling Days

Figure 6.4.8.: Absorption at 590 nm of pigment extracts of A. catenella cultures grown in red, blue and white light. Spectra were normalized at wavelength 442nm. One-Way ANOVA (P=0,054)

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Chapter 6 The impact of light on PST synthesis

1.5

1.0

0.5 Absorption

0.0 460 480 500 520 540 nm B R W

Figure 6.4.9.: Absorption spectra in the region of green light (458 nm – 553 nm) of pigment extracts from A. catenella cultures grown in red, blue and white light. Spectra were normalized at wavelength 442 nm (Day 34).

B 1 .0 R W 0 .8

0 .6 4 5 5 n m

0 .4 Normalized Absorption 0 .2 0 5 10 15 20 25 30 35 Sampling Points

Figure 6.4.10. : Absorption at 455 nm of pigment extracts of A. catenella cultures grown in red, blue and white light. Spectra were normalized at wavelength 442nm and are plotted for the sampling days 13, 20, 28, 30, 34. One-Way ANOVA (P=0.39)

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0.4

0.3

0.2

Absorption 0.1

0.0 650 700 750 800 nm

Blue Red White Figure 6.4.11.: Absorption spectra in the red light region 620 nm – 800 nm, normalized at 442 nm

3 Chla/c ratio Chla/c 2

1 1 2 3 4 5 6 Sampling Days

White Red Blue

Figure 6.4.12: The chlorophyll a/c ratio of A. catenella grown in blue, red and white light.

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6.4.4. Pigment synthesis and growth rate Growth rate and chlorophyll content were similar in white and red light, with chlorophyll content per cell being higher at growth stages with slower growth rates (Figure 6.4.13). The correlation of growth rate and chlorophyll synthesis was negative in white and red light, with a correlation coefficient of r= -0.313 (P=0.6) in white light and r = -0.057 (P=0.2) for cells grown in red light. For cells grown in blue light the correlation coefficient of growth rate and chlorophyll production was positive r= 0.781 (P= 0.9).

150 0.4 Growth rate ( Growth rate )

-1 0.3 100

0.2  50 day 0.1 -1 Chl a+c (pg cell (pg a+c Chl )

0 0.0 1 2 3 4 5 6 7 8 Days White chla/c Growth rate white Red chla/c Growth rate red Blue chla/c Growth rate blue

Figure 6.4.13: Growth rate and total average chlorophyll a + c content of A. catenella cultures grown in blue, red and white light.

6.4.5. Pigment and PST synthesis Blue light grown cells had on average the lowest chlorophyll a + c content and also the lowest PST content per cell, the red and white light grown cells had higher average PST contents and twice the chlorophyll content than blue light grown cells (Figure 4.6.14). The average chlorophyll a + c content of A. catenella cells grown in white light was 94 ± 5.1 pg cell-1 and 80 ± 2.5 pg cell-1 in the red light treatment, in both of those treatments pigment content was significantly higher than in the blue light treatment with an average of 49 ± 2.3 pg cell-1. One way Anova with post-hoc Tukey s test revealed significant difference of P=0.0008 white vs blue (***) and red vs blue (**).

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100 140

120 Total chla/c pg cell

-1 80 100 60 80

40 60 40 -1

Total PST pg cell PSTpg Total 20 20 0 0 10 15 20 25 30 35 40 Sampling days PST white White chla/c PST red Blue chla/c PST blue Red chla/c

Figure 6.4.14: Total average PST and total average chlorophyll a +c content ( pg cell-1) of A.catenella ACCCO1 when grown in blue, red and white light.

6.4.6. Bacterial communities associated with Alexandrium catenella grown in white blue and red light

The 16S rRNA abundance of the bacterial community of A. catenella was dominated by Rhodobacteraceae, Cryomorphaceae, Alteromonadaceae and Ectothiorhodospiraceae. Rhodobacteraceae were the most abundant bacteria under all light conditions, most abundant in blue light with 59.3 % of the total community, and with 54.9% and 48.7% in red and white light grown cultures (Figure 6.4.15.). Species identification of the most abundant Rhodobacteraceae revealed it to be Roseovarius. For Ectothiorhodospiraceae, Altermonadaceae an opposite trend of higher abundance in the order white> red > blue light was detected. Cryomorphaceae were most abundant in blue light with 16.9 % of the overall 16S rRNA abundance, compared to 10.6 % in white light and 9.7% for red light grown cells.

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30 W 20 R

10 B

Figure 6.4.15.: Bacterial community composition on family level of A. catenella cells grown in white, red and blue light (sampled at day 14).

6.5. Discussion

6.5.1. Summary During their life time Alexandrium species experience a variety of light regimes within the water column. Little is known about the impact of light quality on the physiology and capacity of PST production of Alexandrium species. In this study the effect of white, red and blue light on growth rate, PST and pigment synthesis, as well as bacterial community composition of Alexandrium catenella, group IV was investigated. PST production increased with decreasing growth rate in white and red light. The total toxin and pigment content per cell was higher in white and red light, compared to blue light grown Alexandrium cells, suggesting a regulatory effect of chromatic acclimation on PST production. Higher PST synthesis in white and red light grown cells was accompanied by higher chlorophyll and peridinin levels in A.catenella. Cells grown in red, blue and white light displayed a stable toxin profile and produced GTX – 1,4, Neo-STX, GTX – 2,3 and STX at similar ratios, throughout the growth period investigated. Sightly lower amounts of STX in the blue light grown cells were detected. Additionally changes in the bacterial community were observed in

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Chapter 6 The impact of light on PST synthesis the light treatments, playing a putative role for the varying capacity for PST production of A.catenella cells grown in red, blue and white light.

6.5.2. Growth rate The growth rate of phytoplankton is an expression of the relative ecological success of a species and its adaptability to its environment (Tortell et al., 2000). This study shows that A.catenella, group IV, is able to display a similar growth rate in white, red and blue light with small differences in the order blue˃white˃red (Figure 6.4.1.). This observation indicates that this species might be well adapted to thrive successfully in water layers, where red light is scarce. Generally higher growth rates in blue green radiance have been described formerly for microalgae as result of adaptation to the prevalence of the blue light spectra within the water column (Faust et al., 1982; Hess and Tolbert, 1967; Vesk and Jeffrey, 1977). Similarly, Das et al. (2011) observed maximum growth rates in the order blue˃white˃green˃red light for Nannochloropsis species (Das et al., 2011). Light utilization efficiency for photosynthesis is higher for blue light than the other monochromatic primary wavelengths red and green, or the combination of these wavelength in white light, in low light intensities when photosynthetic capacity is not saturated. As the photons of the shortest wavelength related to blue light have the highest µmax, whereas red light has the longest wavelength with minimum µmax. (Das et al., 2011). Blue light hence theoretically allows to maintain the same photosynthetic rate with less plastid capacity, compared to red light and white light grown cells. Blue light grown cells are likely to be able to utilize more resources for replication, targeting less nutrients into plastid synthesis. Future studies should include photosynthetic rate measurements of A. catenella in these light conditions in order to evaluate if the same photosynthetic rate is maintained with less plastid capacity in blue light. However, A. catenella might follow a different metabolic strategy to maintain its growth rate. e.g. by decreasing cell size or acquisition of high molecular weight organic comounds (Legrand and Carlsson, 1998) present in the non- axenic cultures.

6.5.3. Absorption spectra and pigment synthesis Red light has been reported to induce the synthesis of chlorophyll in plants, triggered by the perception of the red light spectrum through phytochrome and leading to the accumulation of the light harvesting chlorophyll protein (Apel, 1979; Stiekema et al., 1983). In this study higher chlorophyll levels were measured in the white and red light treatment (Figure 6. 4.14.)

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Chapter 6 The impact of light on PST synthesis indicating that red light might also play an important role in the regulation of chlorophyll synthesis in Alexandrium. The normalized pigment absorption spectra of A. catenella cells displayed a high similarity between red and white light grown cells (Figure 6.4.6.). Pigment extracts from cells grown in blue light displayed lower absorption in the orange-red light region of peridinin (Figure 6.4.7, 6.4.8.) and increased absorption in the blue green region related to chlorophyll c content (Figure 6.4.9.). Slightly higher chlorophyll a/c ratios were detected in blue light grown A. catenella cells (Figure 6.4.12). These findings suggest that chromatic acclimation had taken place. Chromatic acclimation has been described for many photosynthetic algae, which respond to changing light quality and diminishing light intensity in their aquatic environment by increasing cellular concentrations of pigments with absorption properties complementary to the colour of the incident light (Engelmann et al. 1982; Brody et al., 1959; Halldal et al., 1958; Bogorad et al., 1975). In future further investigations on pigment content and ratios should be conducted via High Throughput Chromatography (HPLC), in order to allow a more sensitive and quantitative detection of changes in the pigment profile.

6.5.4. PST synthesis Toxin production increased with decreasing growth rates, in all light treatments. However, average toxin levels were lower in blue light compared to red and white light 11.64 ± 1.2 pg cell -1 vs 15.04 ± 1.4 pg cell -1 and 17.82 ± 2.4 pg cell-1 (Figure 6.4.2.). Chlorophyll synthesis and photoacclimation within the red light range might hence play a role in addition to growth rate in PST synthesis regulation. It has been reported that the amino acid pools of microalgae may differ when grown under blue, red and white light. Blue light has been reported to affect serine and glycine synthesis and potentially other amino acids (Hauschild et al., 1962, 1962; Hess and Tolbert, 1967). PSTs are synthesized from amino acid precursors, a change in the amino acid pool might hence be responsible for varying PST synthesis levels of cells grown in red, white and blue light. Ogata et al. also suggested that the de novo synthesis of amino acids by photoassimilation plays an important role in the production of toxin by A. tamarensis (Ogata et al., 1987). The impact of light on PST synthesis has been reported to differ between different Alexandrium species and strains (Boczar et al., 1988; Etheridge and Roesler, 2005; Fulco and Gayoso; Hamasaki et al., 2001; Hwang and Lu, 2000; Lim et al., 2006; Taroncher- Oldenburg and Anderson, 2000). The reported differences might be due to different adaptations of the strains, which originate from different areas and light conditions. Extended studies on the impact of light quality and light intensity on PST production and nutritional 118

Chapter 6 The impact of light on PST synthesis adaptation strategies are hence needed. Minor profile changes of PST analogs synthesized were observed in the different light conditions (Figure 6.4.3, 6.4.4., 6.4.5.). These differences appear to be the result of inter conversion between hydroxylated and non-hydroxylated analogs. Slightly decreased amounts of STX were observed in the blue light treatment (Figure 6.4.5.), this observation eventhough minor is in accord with findings reported by Maas et al. 2010 who reported a profile change in Alexandrium minutum with changing light conditions. They found that after a 22 day incubation period in the dark, A.minutum Anokoha A failed to produce saxitoxin, however both gonyautoxin and STX were present in the light and the dark (Maas and Brooks, 2010).

6.5.5. Bacterial communities of A. catenella grown in red, blue and white light The relative contribution of dinoflagellates and bacteria to overall toxicity still requires clarification, particularly as the inter- relationship appears to be complex. Bacteria have been reported to produce PSTs autonomously and also have the ability to biotransform these toxins (Gallacher et al., 1997; Kodama et al., 1988; Kotaki et al., 1985). The influence of bacteria on the nutritional status, e.g. by supplying nutrients is likely to impact the capacity for PST production (Amin et al., 2009; Croft et al., 2006; Keshtacher-Liebso et al., 1995; Maldonado and Price, 1999). Alexandrium has been reported to be able to uptake high molecular weight organic comounds and also to display bacterivory (Du Yoo et al., 2009; Jacobson and Anderson, 1996; Jeong et al., 2005; Legrand and Carlsson, 1998; Maldonado and Price, 1999; Nygaard and Tobiesen, 1993). Bacteria might hence play an important role in the maintenance of the nutritional status, the capacity for PST synthesis and survival, when light quality and intensity are limited and consequently photosynthetic activity insufficient. Maas et al incubated parallel cultures of toxin producing Alexandrium minutum Anokoha A in the dark and in a natural daylight cycle. They found that inhibition of photosynthesis resulted in changes in the toxin profile and correlated with the presence of copiotrophic bacteria, suggesting that abiotic and biotic factors act in combination on the regulation of toxicity (Maas and Brooks, 2010). In this study small shifts in the bacterial community were detected for A. catenella cultures grown in red, white and blue light (Figure 6.4.15). The bacterial community associated with Alexandrium catenella constituted of bacteria belonging to the families of Rhodobacteraceae, Cryomorphaceae, Alteromonadaceae and Ectothiorhodospiraceae. Rhodobacteraceae were most abundant under all light conditions (Figure 6.4.15.). The observation of shifts in bacterial community compositions under different light conditions followed a trend higher 119

Chapter 6 The impact of light on PST synthesis abundance in the order white> red > blue light for Ectothiorhodospiraceae, Altermonadaceae. Cryomorphaceae were most abundant in blue light with 16.9 %, compared to 10.6 % in white light and, 9.7% for red light grown cells. The abundance of Rhodobacteraceae was higher in blue light compared to red and white light (Figure 6.4.15). Bacterial community shifts are likely due to a direct response of the bacteria to the light conditions, as well as an indirect response due to the changes in the physiology of Alexandrium. Differences in photosynthetic activity in Alexandrium grown in red, blue and white light are likely to lead to a difference in the oxygen concentration in the phycosphere of the microalgae. The concentration of oxygen is essential for the regulation of growth and many physiological processes of bacteria. Low oxygen concentrations can impact growth of facultative anaerobes (Gottschal and Szewzyk, 1985) and oxygen can promote the respiration of heterotrophic bacteria (Caffrey et al., 1998). Further studies are needed to investigate the respiration rate and metabolism of the algal- bacterial consortium under different light conditions in order to evaluate if bacterial acitivity contributes to metabolic changes and differential PST synthesis in A. catenella cultures.

Species identification of the most abundant Rhodobacteraceae revealed it to be Roseovarius. A previous study reported the isolation of Roseovarius from Alexandrium ostenfeldii and the finding of traces of bacterichlorophyll a in the isolate (Biebl et al., 2005). Associations with bacteria capable of anoxygenic photosynthesis could be beneficial for the photosynthetic niche and carbon acquisition of the Alexandrium-bacterial consortium and the capacity for PST synthesis. In general oxygen partial pressure is the major factor that regulates the formation of the photosynthetic apparatus and the cell differentiation of most anoxygenic phototrophic bacteria capable of respiratory and photosynthetic modes, of energy transduction. Photosynthesis in bacteria can be aerobic or anaerobic (Drews et al., 2004; Fuerst et al., 1993; Hansen et al. 1973; Nickens et al 1996; Shiba et al 1991, Yurkov et al. 1998). The increased abundance of Rhodobacteraceae in the blue light condition could be hence a response to lower oxygen levels due to reduced photosynthetic rate of Alexandrium inducing respiratory or photosynthetic capacity in the Rhodobacteraceae. It is hence necessary to investigate the physiology of the associated Rhodobacteraceae in order to understand the regulation of their metabolism in changing oxygen concentrations and potential switches from heterotrophy to autotrophy which could impact symbiotic relationships with Alexandrium. Besides the potential regulatory role of oxygen concentrations and their changes due to different photosynthetic rates of Alexandrium, changes in the synthesis of carbohydrates and other metabolites produced by Alexandrium, which are important for its bacterial associations could have led to the changes in the bacterial community in the phycosphere (Bell et al., 120

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1974). The changes in bacterial community associated may be responsible or partially responsible for differential PST production capacity in dinoflagellates and further studies integrating the investigation of abiotic factors such as light and biotic factors are necessary to elucidate interactions and dynamics within the algal-bacterial consortium.

6.5.6. Bacterial communities of A.catenella in comparison with the bacterial communities of A.tamarense ATNWBO1 and ATCJ33 (Chapter 5)

The bacterial community of A. catenella ACCC01 resembles the bacterial community of Alexandrium tamarense ATCJ33 and ATNWB01 (Chapter 5) when compared on the family level. In all three strains the most abundant family is the family of Rhodobacteraceae, with approx 60% of the total sequences in Alexandrium catenella and 70% and 84% in the toxic ATNWB01 A. tamerense and the non toxic ATCJ33 strain respectively. Nevertheless the Rhodobacteracea differ on the species level. Despite the overall similarity of the most abundant Rhodobacteracea family, there are also differences in the remaining bacterial community on the family level when comparing A. catenella ACCC01 with A. tamerense strains.

6.6. Conclusion and future studies Alexandrium strains representing one genetic ribotype can be toxic- or non-toxic (Murray et al., 2011), to date it is not known what role the toxins play for the producing organisms and what regulates their production and the changes of toxicity of a species (Anderson et al., 2011; Cembella et al., 1987). It is likely that subtle ecophysiological differences can significantly impact the capacity to produce PSTs by microalgae. It is hence crucial to investigate the ecotypes of Alexandrium species in order to better understand adaptation and related regulation of PST production, in the integrated context of biotic and abiotic factors and the nutritional capacity of the algal bacterial consortium. Knowledge about the varying toxicity of Alexandrium species and strains due to environmental factors is essential, for improved prediction of toxication events and development of improved environmental markers for harmful algal bloom monitoring.

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This study indicates that A. catenella is well adapted to thrive under changing light conditions, and is likely to be able to grow at similar growth rates at different water depths. The underwater light regime can be an important factor in the initial phase of toxic phytoplankton blooms (Johnsen et al. 1997; Johnsen et al. 1992). The ability to thrive under varying light conditions is the key to survival and the success to proliferate at high cell numbers leading to HABs. The findings of this study indicate that A. catenella is likely to be more toxic in upper water layers when photosynthetic activity and pigment synthesis is fostered by red light. Hence photoacclimatory processes, which alter the spectral signatures, such as a relatively higher peridinin content of Alexandrium species may well be related to changes in their toxicity. Thus, in future the prediction of growth rates and potential toxicity of Alexandrium species based on light regime-dependant differences in bio-optical signature might be a useful tool for early warning systems, such as described by Johnsen et al 1993 (Johnsen et al., 1993).

Future studies should investigate the impact of spectral light qualities at different light intensities, on different species and strains of Alexandrium. Further biochemical analysis of the N/C ratio, amino acid content and effective photosynthetic and respiratory rate of cells, will aid to understand how light quality affects the metabolism of these microalgae and how these changes are interconnected with PST production. More studies on the impact of vertical niche partitioning of Alexandrium are needed in order to unravel the impact of changing light quality also on the dynamics of the interactions with associated bacteria, which might change significantly due to gradients of abiotic and biotic factors within the water column. Investigation of bacterial communities during chromatic acclimation over time will improve the understanding of PST synthesis dynamics and the potential impact of heterotrophic and aerobic or anaerobic phototrophic bacteria on the nutritional capacity of algal bacterial consortium to synthesize or biotransform PSTs. Different ecotypes are often lumped together as a single species on the basis of their rDNA similarities (Hagstroem et al., 2002), yet they can remarkably differ in their physiology. Differences in photosynthetic activity have been described to offer subtle opportunities for niche differentiation within one species (Rocap et al., 2003), and this study indicates that such differences need further in depth investigation for Alexandrium species in relation to PST synthesis.

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7. Conclusion and future directions

7.1. Transcriptional regulation and molecular evolution of sxt genes in dinoflagellates The identification of genes putatively involved in saxitoxin synthesis in dinoflagellates facilitates the investigation of regulation of PST synthesis in toxic dinoflagellates using molecular tools. The investigation of gene expression via RT-PCR is a new and exciting avenue to acquire insights about the regulation of saxitoxin on the transcriptional level. Gene expression is the initial level of metabolic regulation of any biosynthetic pathway and RT- qPCR is the most sensitive and reliable method used for the reproducible measure of transcription. The finding of this study support the hypothesis that transcriptional regulation of STX production, and possibly other genetic pathways is mostly regulated post- transcriptionally in dinoflagellates. When investigating the expression of STX related genes during the growth in batch culture and under different light conditions, significant changes in toxin per cell content were detected (Chapter 3 and Chapter 4), however no significant changes in the relative gene expression of STX and photosynthesis related genes were measured. It is therefore likely that sxtA4 is translationally or post-translationally regulated. A minor role for transcriptional regulation in dinoflagellates, compared to regulation in other organisms, has been hypothesized in former studies (Erdner and Anderson, 2006; Van Dolah et al., 2007b). An alternative explanation for the observations in the present study is, that the number of transcripts detected by RT-PCR may not reflect solely the mature fraction of mRNA activated for translation. This is due to the prevalence of trans-splicing mechanisms in dinoflagellates (Zhang et al., 2007; Zhang and Lin, 2008). Other studies of dinoflagellate gene expression have indicated that these organisms use both transcriptional and posttranscriptional regulation in roughly equal measure, dependant on the stimulus (Okamoto et al., 2001). Therefore future studies might reveal abiotic or biotic stimuli that impact sxt expression on the transcriptional level. Further investigation is also needed on the transcription of other sxt –related genes, it is possible that genes encoding other enzymes, for example those involved in tailoring the toxin with additional side groups, are regulated differentially than the sxtA gene, which encodes the enzyme responsible for STX synthesis initiation. It is also possible that putative sxtA genes have a broader function in the overall metabolism of toxic strains than solely the synthesis of STX and its analogs. Such could be associated with photo-acclimatory responses related to pigment synthesis as findings of this study indicate (Chapter 6). In such scenario putative sxt genes would be regulated by several factors 125

Chapter 7 Conclusion and future directions in a hierarchical way. Putative sxt genes are present and expressed in non-toxic Alexandrium strains (Stüken et al., 2011). Comparative investigations of gene copy numbers and gene expression in toxic and non-toxic strains could help elucidate the regulation of these genes. The real time PCR assay and the reference genes selected and tested in this study are valuable tools for such future investigations. In the future, proteomics studies of STX-related proteins might be useful in order to elucidate further if the translational level is more important for the regulation of STX synthesis. Dinoflagellates possess a number of remarkable genetic characteristics that distinguish them from other eukaryotes one of such striking features is the large amount of gDNA that they contain. It has been suggested that the duplication of genomic copies of highly expressed genes in dinoflagellates may function as a means of increasing their transcription (Bachvaroff, 2008). This study revealed that not all genetic copies of sxtA in Alexandrium catenella were transcribed. Comparison of the sxtA4 cDNA sequences with corresponding genomic DNA sequences indicated preferential transcription of gene copies, with higher GC content in A. catenella (Chapter 3). It is unclear why there is a discrepancy in transcription and what the role of multiple copies is for the organisms, but it is possible that some copies are not transcribed at all. In the future, it would be interesting to investigate if preferential transcription is a universal mechanism of “transcriptional regulation” of genes with multiple copies in dinoflagellates. The manipulation of copy numbers might play a role for toxicity and impact adaptative evolution of dinoflagellates, and this needs further investigation. RT-PCR design and the normalization of gene expression of sxtA against a specific gDNA copy would be a way to investigate, the relative expression of certain copies.

The analysis of gDNA and cDNA sequences of stxA4 indicated the presence of specific positions within the nucleotide sequence of sxtA4, that were potential “hot-spots” for nucleotide polymorphisms present in different strains. The analysis of cDNA and gDNA sequences of sxtA4 further suggested the potential involvement of mRNA editing in the maturation process of sxtA4 gene transcripts. This observation should be investigated further in order to understand the scope of potential steps, that might be involved in transcript maturation in dinoflagellates. The multiple genomic sequences of sxtA4 from A. catenella clustered together with high statistical support indicating that all paralogs had the same origin and that multiple lateral transfers or recombination between other strains of Alexandrium may have been infrequent or non-existent within this strain. Within closely related species such as A. catenella and A.fundyense genetic exchange may have occured. In the future phylogenetic

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Chapter 7 Conclusion and future directions analysis of cDNA, gDNA and amino acid sequences will allow to further investigate the evolution and relation of sxt genes in different dinoflagellates.

7.2. Photoperception cell cycle progression, PST production and gene expression Light plays a key role in the regulation of cell division, synchronized by the circadian rhythm. PST production has been reported to correlate with the cell cycle phase progression in dinoflagellates, with varying reports about the highest PST levels in regard to the cell cycle phase (Harlow et al., 2007a; Siu et al., 1997; Taroncher-Oldenburg et al., 1999a). PST production did not correlate with a specific cell cycle phase in this study (Chapter 4, Figure 4.4.3). In Alexandrium catenella PST production was found to be continuous over the diel phase. The dark to light transition did not evoke a change in PST production. Higher light intensities, compared to those implemented in this study (40 µmol m-2 s-1), will likely induce a higher growth rate and facilitate a better resolution of cell cycle stages and cell cycle stage progression. Former reports about PST production and cell cycle phase correlation seem to differ between different strains. It is hence possible that PST production in this strain is continuous over the cell cycle progression. The complex relationship between PST production and cell cycle progression needs further investigation.

In higher plants, the collective response to a certain light stimuli is directed by several photoreceptor types, including the blue light (B)-absorbing phototropin and cryptochrome flavoproteins, and the phytochrome family of biliproteins, which typically absorb red (R) and far-red (FR) light (Rockwell et al., 2006; Möglich et al. 1010, Vierstra et al. 2011). Photoreceptors essentially keep track of fluctuations in spectral composition and intensity, perceived light stimuli then set in motion signaling cascades that ultimately influence the organisms physiology, through modulation of gene activity (Tobin et al 1985, Frankhauser et al. 2002). Little is known about photoperception and photoreceptors in dinoflagellates. Only, recently a blue light receptor was characterized in Karenia brevis (Brunelle et al., 2007). Potential gene regulatory cues of blue and red light are unknown for dinoflagellates yet. Red and blue light have been found to influence toxin production-related gene expression of mycB and mycD transcripts in Mycrocystis aeroginosa, a cyanobacterial species (Kaebernick et al., 2000). In this study the investigation of relative gene expression of two target genes psbA and sxtA4 in response to exposure to blue, red and white light did not reveal significant changes in gene expression levels, suggesting that PST production is not regualted on the transcriptional

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Chapter 7 Conclusion and future directions level by blue and red light. However, changes in PST levels of cells grown in different light conditions were detected (Chapter 4, Figure 4.4.7.). In the future comparative microarray and proteomes studies under blue, red and white light could reveal potential gene and metabolite regulation through light and photoreceptor inititated cues. The nature of the entraining light cues and light-dependent signaling pathways in dinoflagellates remain poorly defined. Future studies could also be conducted to identify and characterize the photoreceptors that keep track of fluctuations in spectral composition and set in motion signaling cascades that ultimately influence the physiology of dinoflagellates. Several processes could be potentially controlled, for example those that oscillate with the circadian-rhythm, including cell cycle-progression, but also photosynthesis, vertical migration and bioluminescence (Roenneberg et al 1998; Suzuki et al., 2001). It has been shown that the cell cycle progression can be altered through the exposure to blue and red light in the dinoflagellate Karenia brevis (Brunelle et al., 2007). In this study a trend of cell cycle shift in the different light treatments was observed, but did not correlate with an accompanying trend in PST production changes. Although no significant changes in PST production were detected over the diel phase in white, blue and red light, the same slight change in profile differences was observed for all light treatments, with a decrease of hydroxylated PST analogs compensated by a slight increase by non-hydroxylated PST analogs (Chapter 4, Figure 4.8.1- 3). A significant difference in total PST production per cell, was detected in the different light conditions PST production was higher in red light compared to blue light (Chapter 4, Figure 4.4.7). Due to the observation that PST production occurred in all light conditions, it is likely that regulation of PST synthesis does not occur through photoreceptors, but is influenced by a difference in photosynthetic rate and nutritional status in the different light conditions.

7.3. Bacteria associated with Alexandrium Bacteria are an integral part of the environment of dinoflagellates. The characterization of bacterial communities associated with dinoflagellates is essential in order to understand the ecophysiology of the algae and the potential role of bacteria in harmful algal bloom development and toxicity. Interactions between bacteria and harmful algae may play an important regulatory role for population dynamics and for toxin production. These interactions are still poorly understood (Doucette et al., 1998; Simon et al., 2002). For STX- producing Alexandrium species the role of bacteria in the production of SXT is still elusive and controversial (Gallacher et al., 1999). It has been proposed formerly that bacteria are

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Chapter 7 Conclusion and future directions responsible for PST production in dinoflagellates (Kodama et al. 1988, Kodama et al., 1990, Silva et al., 1990). Bacteria are also implicated in the modification and biotransformation of toxins and might dynamically impact the toxicity of STX producing dinoflagellates (Hold et al., 2001). It has been reported that the putative genes responsible for STX production are encoded in the dinoflagellate nucleus (Stüken et al., 2011). However, not every gene required in cyanobacteria for the production of STX was found in the study of dinoflagellate EST libraries (Stüken et al., 2011). Consequently, there may be a role for enzymes produced by bacterial communities in the production of STX (Stüken, 2011). A detailed characterization of the bacterial community is hence required to identify species that may play a role in STX modification, synthesis and nutritional capacity of the algal-bacterial consortium or other aspects of bloom development. The culture independent nature of most molecular techniques allows to identify the numerous non-cultivable bacteria present in marine ecosystems. The currently-available massive parallel pyrosequencing (using 16S rRNA genes) of environmental DNA facilitates the rapid analysis of microbial communities with a much higher throughput and taxonomical resolution than has previously been possible (Huse et al., 2007; Lee et al., 2010; Manter et al., 2010). In this study the microbial communities of a toxic and non-toxic Alexandrium tamarense strain were identified with high resolution using a region of the 16S rRNA gene (Chapter 5). The strains were found to have a similar microbial diversity, dominated by core populations of Rhodobacteraceae which represented around approximately 80 % of the total 16S rRNA abundance. The most abundant sequences were identified as Rhodobacteraceae. The most common sequences associated with the toxic strain were closely related to Thalassobacter genus, while those associated with the non-toxic Alexandrium were closer related to the genus Loktanella (Chapter 5, Figure 5.4.2). The high abundance of 16S rRNA sequences of these species indicated that these might be symbiotic associations with a potentially significant role for the Alexandrium strains investigated. Such role could be associated with the sulfur or carbon metabolism. As members of α- Proteobacteria of the Roseobacter clade are the primary consumers of the algal osmolyte, dimethylsulfoniopropionate (DMSP) (Fandino et al., 2001; Miller, 2005). Some members also perform aerobic anoxygenic photosynthesis (Shiba, 1991), which could play an important role for the expansion of the ecological niche of the algal-bacterial consortium of Alexandrium in an environment with varying light conditions. Further investigations will fully evaluate if the associated bacteria contribute significantly to the nutritional status and the capacity for toxin production of Alexandrium species. Future studies should further characterize changes and dynamics of the bacterial community under different culture conditions in order to detect

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Chapter 7 Conclusion and future directions bacteria, which affect PST synthesis. Such as in this study conducted in different light qualities (Chapter 6). Core populations were shared by the two strains, and included the commonly reported orders Flavobacteriales and several orders with lower abundance such as Rhizobiales, Sphingomonadales (Chapter 5, Figure 5.4.1., Table 5.4.1.-3). Rhizobiales are known for their ability to fix nitrogen and Flavobacteriales are prominent for siderophore production (Pagan et al., 1975; Soltani et al., 2010). These bacteria may substantially impact the nutritional status of the Alexandrium sp. Many of these physiological processes, such as nitrogen fixation are controlled by specific environmental conditions and can not always be easily detected in the lab (Pagan et al., 1975). However, in nature the abundance of these bacterial associates might increase and under specific environmental conditions they could provide a nutritional advantage to the microalgae. Further research and investigation of functional bacterial genes such as nifH, encoding a part of the pathway involved in nitrogen fixation (Zehr et al., 1995) in cultured strains and in natural bloom samples during bloom succession will allow to evaluate the significance of these bacterial communities in the supply of nutrients for PST production and HAB development. Future studies could reveal if these associations are species or strain specific and if and how they vary between different Alexandrium strains from various geographical regions, and if they play a significant role in the characterization of Alexandrium ecotypes. These investigations will aid to a more integrated understanding of the ecological rules that govern microbial diversity and abundance associated with Alexandrium. Studies on the localization of specific bacteria, such as those now possible with tyramide signal amplification–fluorescent in situ hybridization (TSA-FISH) and confocal microscopy (Biegala et al., 2002; Brinkmeyer et al., 2000; Simon et al., 2002) will allow to define the dynamics of the interactions within the bacterial algal consortium. Bacterial associations and bacterial symbioses are known to be a major source of genetic novelty (Margulis et al., 1991; Cavanaugh et al., 1994; Sapp et al., 1994). A close association is likely to increase the probabilty of lateral gene transfer. The genomes of dinoflagellates have potentially been shaped by their association with bacterial communities (Margulis, 1991; Syvanen, 1994), it is therefore interesting and crucial to characterize and investigate the bacterial communities associated with microalagae, to better understand their impact on the genetics of dinoflagellates. The presence of bacteria has been reported to impact gene expression (Moustafa et al., 2010). Responses and interactions of dinoflagellates are likely to be stimulated by bacteria at every level of physiological regulation. It is crucial to further investigate these complex relationships and the impact of bacteria on the shaping of dinoflagellate genomes, as well as on transcriptional regulation of sxt and other genes.

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Chapter 7 Conclusion and future directions

7.4. The impact of light quality on PST synthesis PST synthesis is associated with photosynthetic organisms from two different kingdoms, cyanobacteria and dinoflagellates and the direct and indirect effects of light on the capacity for PST synthesis are potentially diverse. The photosynthetic rate of algae is defined by the light intensity, the spectral quality of the incoming light and the characteristic array of light harvesting pigments. The intensity and spectral quality of light may vary markedly with the depth of the water column. Little is known about the impact of light quality on the physiology and capacity of PST production of Alexandrium species. In this study white, blue and red light evoked significant differences in pigment and PST synthesis by A.catenella. PST and pigment synthesis were significantly higher in white and red light compared to blue light (Chapter 6 Figure 6.4.14). The cells acclimatized chromatically over time and not only a significant difference in Chlorophyll a content but also a difference in relative pigment absorbance of chlorophyll c and peridinin was detected in pigment extracts. White and red light grown cells had slightly higher peridinin contents, suggesting that photoacclimatory processes may play a role in PST synthesis regulation. Future studies should investigate if this observation is valid for other Alexandrium strains grown in red and blue light. Furthermore several different light intensities and spectral light qualities should be implemented in these comparisons. PST production was higher in cells with a relatively lower chlorophyll c and a higher peridinin content, the peridinin index was slightly lower in pigment extracts from blue light grown cells (Chapter 6). Future studies could also investigate if a generally lower peridinin index is associated with non-toxic Alexandrium strains and if this index can be used for the estimation of toxicity in Alexandrium species and prediction of relative toxicity of HABs. The investigation of accessory pigment evolution in PST producing microalgae could further reveal if the capacity for PST synthesis evolved in relation to the acquisition of photosynthetic pigments. The present study suggests that Alexandrium catenella is likely to be more toxic when present in upper water layers where red light penetrates. In the future field studies of per cell toxin quota of the Alexandrium species at different water depths in relation to light quality, will allow us to evaluate the impact of light quality on PST production in the natural environment. The comparison of physiologies and adaptative strategies of Alexandrium ecotypes might reveal the foundations for the observed differences in their capacity to synthesize PSTs which might be related to their vertical niche partitioning within the water column. Differences in photosynthetic activity might offer subtle opportunities for niche differentiation within one species (Rocap et al., 2003). The differences in bacterial communities associated with Alexandrium catenella grown in blue, red and white light further

131

Chapter 7 Conclusion and future directions indicate that integrated investigations of bacterial communities and abiotic factors might aid to reveal important differences in Alexandrium ecotypes, which facilitate the potential for PST synthesis capacity.

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Appendix A : Review publication

134

Mar. Drugs 2010, 8, 2185-2211; doi:10.3390/md8072185 OPEN ACCESS Marine Drugs ISSN 1660-3397 www.mdpi.com/journal/marinedrugs Review Neurotoxic Alkaloids: Saxitoxin and Its Analogs

Maria Wiese 1,†, Paul M. D’Agostino 2,†, Troco K. Mihali 1, Michelle C. Moffitt 2 and Brett A. Neilan 1,*

1 School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW, 2052, Australia; E-Mails: [email protected] (M.W.); [email protected] (T.K.M.) 2 School of Biomedical and Health Sciences, University of Western Sydney, Campbelltown, NSW, 2560, Australia; E-Mails: [email protected] (P.M.D.); [email protected] (M. C.M.)

† These authors contributed equally to this work.

* Author to whom correspondence should be addressed; E-Mail: [email protected]; Tel.: +61-2-93853235; Fax: +61-2-93851591.

Received: 9 July 2010; in revised form: 12 July 2010 / Accepted: 16 July 2010 / Published: 20 July 2010

Abstract: Saxitoxin (STX) and its 57 analogs are a broad group of natural neurotoxic alkaloids, commonly known as the paralytic shellfish toxins (PSTs). PSTs are the causative agents of paralytic shellfish poisoning (PSP) and are mostly associated with marine dinoflagellates (eukaryotes) and freshwater cyanobacteria (prokaryotes), which form extensive blooms around the world. PST producing dinoflagellates belong to the genera Alexandrium, Gymnodinium and Pyrodinium whilst production has been identified in several cyanobacterial genera including Anabaena, Cylindrospermopsis, Aphanizomenon Planktothrix and Lyngbya. STX and its analogs can be structurally classified into several classes such as non-sulfated, mono-sulfated, di-sulfated, decarbamoylated and the recently discovered hydrophobic analogs—each with varying levels of toxicity. Biotransformation of the PSTs into other PST analogs has been identified within marine invertebrates, humans and bacteria. An improved understanding of PST transformation into less toxic analogs and degradation, both chemically or enzymatically, will be important for the development of methods for the detoxification of contaminated water supplies and of shellfish destined for consumption. Some PSTs also have demonstrated pharmaceutical potential as a long-term anesthetic in the treatment of anal fissures and for chronic tension-type headache. The recent elucidation of the saxitoxin biosynthetic gene cluster in cyanobacteria and the identification of new PST analogs will present opportunities to further explore the pharmaceutical potential of these intriguing alkaloids. Mar. Drugs 2010, 8 2186

Keywords: saxitoxin; STX; paralytic shellfish poisoning; PSP; paralytic shellfish toxins; PSTs; neurotoxins; alkaloid analogs

1. Introduction

The paralytic shellfish toxins (PSTs) are a group of naturally occurring neurotoxic alkaloids. Saxitoxin (STX) is the most researched PST to date, and since its discovery in 1957 [1], 57 analogs have been described. The PSTs are primarily produced in detrimental concentrations during harmful algal bloom (HAB) events [2–5] Over the last few decades, HABs have become more frequent, intense, and span a wider global distribution, the cause of which is still under debate [3,6]. The PSTs can be broadly characterized as hydrophilic or hydrophobic, and can be divided into subgroups based on substituent side chains such as carbamate, sulfate, hydroxyl, hydroxybenzoate, or acetate. Each moiety then imparts a varying level of toxicity [7]. In marine environments, PSTs are primarily produced by the eukaryotic dinoflagellates, belonging to the genera Alexandrium, Gymnodinium and Pyrodinium [8–10]. The toxins are passed through the marine food web via vector organisms, which accumulate the toxins by feeding on PST producing dinoflagellates without apparent harm to themselves [11,12]. These include filter feeding invertebrates such as shellfish, crustaceans, molluscs and also other, non-traditional vectors such as gastropods and planktivorous fish [13]. In freshwater environments the PSTs are produced by prokaryotic cyanobacteria belonging to the genera Anabaena, Cylindrospermopsis, Aphanizomenon, Planktothrix and Lyngbya. Cyanobacterial PST producing blooms result in the contamination of drinking and recreational water resources. In the past, high levels of toxins have been detected in the freshwater resources of many countries such as Australia, Brazil, USA, Mexico, Germany and China [14–22]. Intoxication with PSTs may result in the severe and occasionally fatal illness known as paralytic shellfish poisoning (PSP) or saxitoxin pufferfish poisoning (SPFP) [23–27]. This illness is caused when PSTs reversibly bind voltage-gated Na+ channels in an equimolar ratio. This is mediated by the interaction between the positively charged guanidinium groups of STX with negatively charged carboxyl groups at site 1 of the Na+ channel, thereby blocking the pore (Figure 1) [28–30]. Currently, there is no antidote for PSP with artificial respiration and fluid therapy the only treatment available. A recent case of PSP involved the death of two fishermen after consumption of the filter feeder bi-valve Aulacomya ater in the Chilean Patagonian Fjords [26]. The threat of PSP is not only a major cause of concern for public health but is also detrimental to the economy. Outbreaks of PSTs often result in the death of marine life and livestock, the closure of contaminated fisheries, while the continual expenditure required for the maintenance and running of monitoring programs, all combine to present a major economic burden around the world [31,32]. This review will focus on the structural diversity of PSTs characterized to date and the biosynthetic and metabolic basis for this diversity. The saxitoxin biosynthetic gene cluster (sxt) was recently identified in cyanobacteria, which now provides insight into the biosynthesis of STX and its analogs [33,34]. A specific suite of analogs can be isolated from a single PST-producing organism, which is directly a result of the evolution of genes present within the organism’s genome [14,33–37]. Naturally occurring

Mar. Drugs 2010, 8 2187

PSTs can also be precursors for extracellular metabolic or chemical transformations into new analogs. Knowledge of these transformations may have important implications for the detection, toxicity and removal of PSTs from a contaminated source. Other medicinal uses for PSTs may become more established by screening the bioactivity of less toxic analogs, since their use as a potential local anesthetic has long been known [38,39]. The characterization of PST biosynthesis genes and their potential use in combinatorial biosynthesis, together with the constant discovery of novel analogs (either natural or transformed), is likely to expand the possibilities for the pharmaceutical use of PSTs [40,41].

Figure 1. The proposed transmembrane arrangement of the α-subunit of Na+ channels. The pore is represented in red, the voltage sensors in yellow and the inactivation gate in blue. PSP is mediated by the interaction and blockage of Site 1 by STX. Figure adapted from [30].

2. Saxitoxin and Its Analogs, the Paralytic Shellfish Toxins

STX is one of the most potent natural neurotoxins known. A dose of approximately 1 mg of the toxin from a single serving of contaminated shellfish is fatal to humans. STX was the first PST isolated in pure form from the Alaskan butter clam, Saxidomus gigangteus in 1957 [1]. Its highly polar characteristics represent poor conditions for crystallization and hampered structure elucidations for 18 years, until the crystal structure was solved by two groups independently in 1975 [42,43]. STX is an alkaloid with the molecular formula C10H17N7O4 (Molecular Weight = 299) and is composed of a 3,4-propinoperhydropurine tricyclic system. STX belongs to the large family of guanidinium-containing marine natural products, due to the presence of two guanidino groups which are responsible for its high polarity [44,45]. Since its initial discovery, 57 naturally occurring STX analogs have been identified in a number of organisms, collectively referred to as the PSTs (Table 1).

Mar. Drugs 2010, 8 2188

Table 1. The paralytic shellfish toxins.

R H 1 N N 1 7 + 8 NH2 2 9 3 N + N R H2N 12 5 11 OH

R2 R3

Toxin R1 R2 R3 Ω R4 R5 Origin Ref.

STX H H H OCONH2 OH Alexandrium andersoni [46] A. catenella [47–49] A. fundyense [50–52] A. tamarense [53–56] A. circinalis [35,57–59] Aphanizomenon flos-aquae [60–63] Aph. gracile [20,64] Aph. issatschenkoi [65] Anabaena lemmermannii [66] C. raciborskii [16,36,67–69] Gymnodinium catenatum [70–72] Pyrodinium bahamense [10] Planktothrix sp. [73]

neoSTX OH H H OCONH2 OH A. andersoni [46] A. catenella [47–49] A. fundyense [50–52] A. tamarense [53–56] Aph. flos-aquae [60–63] Aph. gracile [20,64] Aph. issatschenkoi [65] Aph. sp. [74] C. raciborskii [16,36,69] G. catenatum [70,71] P. bahamense [10] Mono-Sulfated − GTX1 OH H OSO3 OCONH2 OH A. catenella [47–49,75,76] A. fundyense [50–52] A. minutum [77–79] A. tamarense [53–56] Aph. flos-aquae [37] G. catenatum [9,70,72]

Mar. Drugs 2010, 8 2189

Table 1. Cont.

Toxin R1 R2 R3 ΩR4 R5 Origin Ref. Mono-Sulfated − GTX2 H H OSO3 OCONH2 OH A. catenella [48,49] A. fundyense [50–52] A. minutum [77–79] A. ostenfeldii [80] A. tamarense [53–56] A. circinalis [35,57–59] C. raciborskii [36,67] G. catenatum [9,70,72] − GTX3 H OSO3 H OCONH2 OH A. catenella [47–49] A. fundyense [50–52] A. minutum [77–79] A. ostenfeldii [80] A. tamarense [53–56] A. circinalis [35,57–59] Aph. flos-aquae [37] C. raciborskii [36,67] G. catenatum [9,70,72] − GTX4 OH OSO3 H OCONH2 OH A. catenella [47–49,75,76] A. fundyense [50–52] A. minutum [77–79] A. tamarense [53–56] Aph. flos-aquae [37] G. catenatum [9,70,72] − GTX5 H H H OCONHSO3 OH A. catenella [48,49,75,76] (B1) A. fundyense [50–52] A. tamarense [54,56] A. circinalis [35,57,59] Aph. flos-aquae [60,63] Aph. gracile [20] Aph. issatschenkoi [37,65] G. catenatum [9,71,81] P. bahamense [10] − GTX6 OH H H OCONHSO3 OH A. catenella [47,49,75,76] (B2) A. fundyense [52] A. ostenfeldii [80] A. tamarense [54] Aph. flos-aquae [63] C. raciborskii [69] G. catenatum [9,71,72,81] P. bahamense [10]

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Table 1. Cont.

Toxin R1 R2 R3 ΩR4 R5 Origin Ref. Di-Sulfated − − C1 H H OSO3 OCONHSO3 OH A. catenella [48,49,75,76] A. fundyense [50–52] A. ostenfeldii [80] A. tamarense [53–56] A. circinalis [35,57–59] C. raciborskii [68] G. catenatum [9,71,72,81] − − C2 H OSO3 H OCONHSO3 OH A. catenella [48,49,75] A. fundyense [50–52] A. ostenfeldii [80] A. tamarense [53–56] A. circinalis [35,57–59] C. raciborskii [68] G. catenatum [9,71,72,81] − − C3 OH H OSO3 OCONHSO3 OH A. catenella [48,49,75,76] G. catenatum [9,72,81] − − C4 OH OSO3 H OCONHSO3 OH A. catenella [48,49,75,76] G. catenatum [9,72,81] Decarbamoylated dcSTX H H H OH OH A. catenella [49] A. circinalis [35,59] Aph. flos-aquae [60,63] Aph. gracile [20] Aph. issatschenkoi [65] Aph. sp. [74] C. raciborskii [16,67,69] Lyngbya wollei [82] G. catenatum [9,71,72] P. bahamense [10] dcneoSTX OH H H OH OH C. raciborskii [69] − dcGTX1 OH H OSO3 OH OH G. catenatum [83] − dcGTX2 H H OSO3 OH OH A. catenella [49] A. fundyense [52] A. circinalis [35,57–59] G. catenatum [9,71] L. wollei [14,82] − dcGTX3 H OSO3 H OH OH A. catenella [49] A. fundyense [50,52] A. circinalis [35,57–59] Aphanizomenon sp. [74] L. wollei [14,82] G. catenatum [9,71] − dcGTX4 OH OSO3 H OH OH G. catenatum [83]

Mar. Drugs 2010, 8 2191

Table 1. Cont.

Toxin R1 R2 R3 ΩR4 R5 Origin Ref. Deoxy-Decarbomoylated doSTX H H H H OH G. catenatum [9,84] − doGTX1 OH H OSO3 H OH G. catenatum [9,84] − doGTX2 H H OSO3 H OH G. catenatum [9,84] L. wollei toxins − LWTX1 H H OSO3 OCOCH3 H L. wollei [82] − LWTX2 H H OSO3 OCOCH3 OH L. wollei [82] − LWTX3 H OSO3 H OCOCH3 OH L. wollei [82] LWTX4 H H H H H L. wollei [82]

LWTX5 H H H OCOCH3 OH L. wollei [82]

LWTX6 H H H OCOCH3 H L. wollei [82] Mono-Hydroxy-Benzoate Analogs − GC1 H H OSO3 OCOPhOH OH G. catenatum [83] − GC2 H OSO3 H OCOPhOH OH G. catenatum [83] GC3 H H H OCOPhOH OH G. catenatum [83] − *GC4 OH H OSO3 OCOPhOH OH G. catenatum [85] − *GC5 OH OSO3 H OCOPhOH OH G. catenatum [85] *GC6 OH H H OCOPhOH OH G. catenatum [85] Di-Hydroxy Benzoate Analogs ŧ − GC1a H H OSO3 DHB OH G. catenatum [85] ŧ − GC2a H OSO3 H DHB OH G. catenatum [85] ŧGC3a H H H DHB OH G. catenatum [85] ŧ − GC4a OH H OSO3 DHB OH G. catenatum [85] ŧ − GC5a OH OSO3 H DHB OH G. catenatum [85] ŧGC6a OH H H DHB OH G. catenatum [85] Sulfated Benzoate Analogs ŧ − GC1b H H OSO3 SB OH G. catenatum [85] ŧ − GC2b H OSO3 H SB OH G. catenatum [85] ŧGC3b H H H SB OH G. catenatum [85] ŧ − GC4b OH H OSO3 SB OH G. catenatum [85] ŧ − GC5b OH OSO3 H SB OH G. catenatum [85] ŧGC6b OH H H SB OH G. catenatum [85] Other PST Analogs − M1 H OH H OCONHSO3 OH Metabolic [56,81] transformation

M2 H OH H OCONH2 OH Metabolic [56] transformation − M3 H OH OH OCONHSO3 OH Metabolic [56] transformation

M4 H OH OH OCONH2 OH Metabolic [56] transformation *M5 Metabolic [56] transformation

Mar. Drugs 2010, 8 2192

Table 1. Cont.

Toxin R1 R2 R3 ΩR4 R5 Origin Ref. Other PST Analogs *A Unknown [86] *B Unknown [86] *C Unknown [86] *D Unknown [86] − SEA H CCOO H OCONH2 OH Atergatis floridus [87]

STX-uk H H H OCONHCH3 OH Tetraodon cutcutia [88]

Zetekitoxin AB O H Atelopus zeteki [89] O N O OH

O N N HN 1 7 8 NH 2 9 HN 3 N N H OH

OH OH

OSO3H * Not structurally characterized ŧ R4 group putatively assigned based on major ions obtained via MS [85] O Ω O OCONH2 H2N O O Ω − HN OCONHSO3 - O3S O Ω O OCOCH3 H3C O O ΩOCOPhOH HO O Ω O OCONHCH3 H3C N H ΩDHB: Di-hydroxyl-benzoate ΩSB: Sulfated-benzoate

Usually a PST- producing organism synthesizes a characteristic suite of toxins made up of several PST analogs. These analogs differ in side group moieties and thus are commonly grouped according to these variable residues. The most commonly occurring PSTs are hydrophilic and have been studied in depth [7]. They may be non-sulfated, such as STX and neosaxitoxin (neoSTX), mono-sulfated, such as the gonyautoxins (GTXs 1–6), or di-sulfated (C1-4 toxins) [7,90]. In addition, decarbamoyl variants of these analogs also exist, including decarbamoyl-saxitoxins (dcSTX, dcneoSTX), decarbamoyl-gonyautoxins (dcGTXs 1–4), and the 13-deoxy-decarbamoyl derivatives (doSTX, doGTX 2,3). Three structural families of SXT are classified by the identity of the R4 side chain as either N-sulfocarbamoyl, decarbamoyl, or carbamoyl, each with increasing toxicity in mammalian bioassays (Table 2) [7,9,90]. Recently, an increase in screening efforts, coupled with improved methods for detection and structure elucidation, has seen an increase in the number of new PSTs reported in the literature.

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Table 2. Relative toxicity of the paralytic shellfish toxins. Toxicity of the PSTs due to change in moiety is listed in descending order. Data obtained from [95]. Structure Ω Toxin Relative toxicity Φ O H O N O OH

O N N HN ω NH Zetekitoxin AB 63, 160, 580 HN N N H OH OH OH OSO H 3 O Non-Sulfated O H2N H R1 N N + NH2 STX 1

+ N H2N N OH NeoSTX 05–1.1 OH H H O Mono-sulfated O H2N H R1 N N + ¥ NH2 GTX1/4 0.39/1.09–0.48/0.76 ¥ + N N H2N OH GTX2/3 0.8/0.33–0.9/0.9 OH R2 R3 HO Decarbamoylated H H N N + dcSTX 0.43 NH2

+ N N dcNeoSTX 0.43 H2N OH OH dcGTX1-4 0.18–0.45 H H O Di-sulfated -O S O 3 N H H R1 N N + NH2 N C1-4 <0.01–0.14 + N OH H 2N OH R R 2 3 Ω Refer to Table 1 for assigned R groups. Moieties highlighted in red differentiate from the structure of STX; ¥ α/β epimeric mixture; Φ Relative toxicity based on the mouse bioassay results obtained from [95–98]; ω Based on binding affinity to human brain, heart and muscle Na+ channels assessed in Xenopus oocytes, respectively [89].

A novel group of PSTs with a hydrophobic side chain were identified within the cyanobacterium Lyngbya wollei and are characterized by the presence of an acetate at C13 (LWTX 1–3,5,6) and a carbinol at C12 (LWTX 2,3,5) in place of a hydrated ketone [82]. This was the first report of STX

Mar. Drugs 2010, 8 2194 derivatives with a hydrophobic substituent and these toxins have only been found exclusively in the freshwater environment [14,82]. The presence of an acetate side chain in the LWTXs correlated with a decrease in mouse toxicity, while the reduction at C12 resulted in a complete loss of mouse toxicity [82].

Interestingly, Negri et al. reported a novel subclass of analogs containing a hydrophobic R4 side chain designated GC1-3. These were first isolated and structurally characterized from Australian isolates of the dinoflagellate Gymnodinium catenatum and since have also been identified within Alexandrium catenatum globally [72]. High-resolution mass-spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR) revealed that GC3 is a 4-hydroxybenzoate ester derivative of dcSTX, while GC1 and GC2 are epimeric 11-hydroxysulfate derivatives of GC3 [83,91]. Negri et al. emphasized that the lipophilic nature of these toxins may lead to an increased potential to bioaccumulate in marine organisms [72]. These novel analogs have also been shown to bind strongly to the voltage gated Na+ channel. The binding affinity of GC3 resembles the affinity of the GTXs, whereas the epimer pair GC1 and GC2 bind with a similar affinity compared to the C-toxins [72,92]. More recently, other GC PST analogs have been identified, such as GC4-6, the di-hydroxylated benzoate GC analogs GC1-6a and the sulfated benzoate analogs GC1-6b for which only putative structures have been determined via mass spectrometry (MS) [85]. Due to their hydrophobic nature, these toxins easily escape conventional chromatography methods. The frequently used C18 solid-phase separation is based on polarity and thus hydrophobic compounds are retained on the column and cannot be detected. This is significant from a shellfish monitoring and public safety viewpoint, and presents a major challenge to water authorities [72,93,94]. Recently, Vale et al. reported the isolation of four unusual compounds (denoted A–D) and categorized them as novel STX analogs based on fluorescence emission, ultraviolet absorption maxima and cross-reactivity to a commercial antibody towards STX [86]. These extracts originated from shellfish samples (Semele proficua and Senilia senilis) collected from Luanda and Mussulo Bay, Angola. Compounds A and D were classified as non-N1-hydroxyl PST analogs and compound B as a N1-hydroxyl analog. Even though the presence of G. catenatum and Pyrodinium bahamense has been reported from the coast of Angola, none of the 18 PSTs commonly found in dinoflagellates were identified in these extracts. The authors therefore suggested a possible cyanobacterial source, though neither a definitive chemical structure, nor a PST-producing organism were conclusively identified [86]. Further analysis of the compounds by MS and NMR is required to elucidate these structures and confirm them as STX analogs. The most exotic STX isolate identified to date was isolated from the Panamanian golden frog Atelopus zeteki and designated zetekitoxin AB (Tables 1 and 2). Zetekitoxin AB was confirmed to be a PST containing a unique 1,2-oxazolidine ring-fused lactam. The binding affinity of zetekitoxin AB for brain, heart, and muscle Na+ channels was extremely potent, displaying a toxicity of approximately 580-, 160- and 63-fold greater than STX against each channel, respectively [89]. The constant discovery of novel and diverse STX analogs is a challenge to PST identification and monitoring. Improvement of detection methods will no doubt uncover new natural forms of STX, however, we are still only beginning to understand the mechanisms by which these complex molecules are produced in nature.

Mar. Drugs 2010, 8 2195

3. Biotransformation of the Paralytic Shellfish Toxins

Naturally occurring PSTs may be structurally modified by various biological factors. In some cases, these biotransformations can result in new PSTs that cannot be biosynthesized by cyanobacteria or dinoflagellates alone (Figure 2). In addition, less toxic PSTs may be converted into analogs with greater toxicity (e.g., C-toxins→GTXs) or vice versa. Therefore, a clearer understanding of PST biotransformation is needed for predicting more accurate levels of toxicity. This knowledge may also allow for a mechanism of detoxification to be established and utilized in the water supply and shellfish farming industries. Cell extracts of PST-producing dinoflagellates are capable of enzymatically modifying PSTs. Oshima et al. demonstrated that GTX2 + 3 can be converted into GTX1 + 4 by incubation with Alexandrium tamarense homogenate [92]. Introduction of a sulfate moiety on the carbamoyl group, resultingin the formation of C1 and C2 toxins, has been shown following incubation with G. catenatum homogenate [44,99]. In these organisms, biotransformation is likely to occur via inherent STX tailoring enzymes which are a part of the SXT biosynthetic pathway encoded within the organism. Due to differences in the toxin profiles of filter-feeding invertebrate PST vectors and causative producing organisms, various studies have been conducted to monitor toxin biotransformation [84,100–105]. Enzymatic transformation of carbamoyl and carbamoyl-N sulfated toxins into the decarbamoyl compounds was detected within the little neck clam, Prothotheca staminea [106]. In addition, the conversion of the GTXs and neoSTX to STX by reduction of the O22-sulfate and N1-hydroxyl groups, respectively, has been observed within the homogenate of the scallop Placopecten magellanicus [107]. GC1-3 can be converted into dcSTX, as has been confirmed in vitro through incubation of semi-purified GC toxins with bivalve digestive glands [93]. Similarly, the recently identified M-toxins (M1-5) are reportedly bivalve metabolites of the PSTs and are not present in PST- producing microalgae [56]. The M-toxins constitute an important toxin fraction in mussels contaminated by A. tamarense and G. catenatum and have been detected in shellfish, including mussels, cockles and clams [56,86]. These findings are similar to previous reports on the isolation of 11-saxitoxinethanoic acid (SEA), a novel PST from the xanthid crab Atergatis floridus, inhabiting the pacific coast of Shikoku Island [87]. Other examples include a novel carbamoyl-N-methylsaxitoxin (STX-uk) isolated from the Bangladeshi freshwater puffer Tetraodon cutcutia [88]. These exotic STX analogs are likely products of toxin transforming enzymes within the vector organism or its associated microorganisms. However, the mechanism of enzymatic transformation in these organisms is yet to be elucidated [56,86–88,106–109]. Biotransformation of the PSTs by bacteria was first suggested many years ago by Kotaki et al., who proposed that marine bacteria, such as Vibrio and Pseudomonas spp., are capable of metabolizing PSTs [110]. In addition, isolates from the viscera of marine crabs, snails and the marine red algae Jania sp., were studied and demonstrated transformation GTX derivatives into STX through reductive eliminations [110,111]. Bacterial conversion of GTX1-4 to STX and neoSTX is reportedly due to the bacterial thiol compounds glutathione and 2-mercaptoethanol [112]. The ability of bacteria to degrade PSTs has been further described by Smith et al., who screened marine bacterial isolates from various shellfish species for their ability to metabolize a range of PSTs, such as GTX1-5, STX and neoSTX, suggesting that bacteria might play an important role in the clearance of PSTs from bivalve

Mar. Drugs 2010, 8 2196 molluscs [113]. Novel strains of Pseudoalteromonas haloplanktis, isolated from the digestive tracts of blue mussels (Mytilus edulis) have been reported to possess the ability to reduce the overall toxicity of a PST mixture of algal extracts by 90% within three days [114,115]. Catabolism of the PSTs most likely occurred via oxidation reactions catalyzed by oxidases and peroxidases into aliphatic products for subsequent use in purine and arginine metabolism, although this is speculated, as no catabolized PST products could be identified [115]. Degradation has also been observed during the passage through a bioactive treatment plant, leading to a decrease in predominant C-toxins and an increase of GTX2 + 3 which display relatively higher toxicity [116].

Figure 2. Biotransformation of the paralytic shellfish toxins. Refer to Table 1 for assigned R groups. Moieties highlighted in red indicate a differentiation from the structure of STX. Unbroken line refers to experimental data of toxin conversion. Broken line refers to putative biotransformation based on structural analysis.

O H2N H H N N + NH2 N + N OH H2N O OH O

O O HO R3 H3C N H2N H H H H N HO N M2/4 N N + + NH2 NH2 N N N + N OH +H N OH H2N 2 OH OH

H H H H O NeoSTX O STX-uk

H2N

O H H N O HO N H2N + NH2 H H H N H N N N + N + NH2 N NH2 +H N OH N 2 N +H N N OH + N OH 2 OH H2N OH OH

H H - H H H OOCC dcSTX STX SEA

O O O O O O O O H N H2N H2N 2 H2N H H HO H N N N N H H + + N NH2 NH2 HO H N N N N N + +H N N +H N N NH2 2 OGluc 2 OGluc + OH OH NH2 N + N OH R2 R3 R2 R3 N H2N + N OH H2 N OH GTX1/4-Gluc OH GTX2/3-Gluc

R2 R3 R2 R3 GTX1/4 GTX2/3

O O O - O - O O3S O HO O3S N H2N N H H H H H H H H H N N N N HO N N N N + + + NH + NH2 NH2 NH2 2 N N N N + N + N OH + N OH +H N N OH H2N OH H2N H2N 2 OH OH OH OH

H H H H R2 R3 HO R3 NeoSTX dcSTX C1/2 M1/3

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Detoxification of the paralytic shellfish toxins within mammals

Metabolism of PSTs by humans has not been studied in depth. Nevertheless, Garcia et al. suggested biotransformation of STX to neoSTX and the oxidation of the GTX2 + 3 epimers into GTX1 + 4 within samples of pancreas, bile, urine, brain and heart obtained post-mortem from PSP victims [26]. Further investigations confirmed their findings of biotransformation in humans. N1-oxidation of GTX2 + 3 into the corresponding hydroxylamine analogs GTX1 + 4 has been demonstrated in vitro when incubated with a microsomal fraction isolated from healthy human livers. Moreover, in vitro glucuronidation of GTX2 + 3 into the hydrophilic compounds GTX3-Gluc and GTX2-Gluc, through conjugation at the hydroxyl-C12 group has also been reported (Figure 2) [117]. The oxidation and glucuronidation of STX and GTX2 + 3 epimers into neoSTX or GTX1 + 4 epimers, respectively, has been suggested to be significant detoxification pathways of GTX2 + 3 and other PSTs in humans and other mammals [117]. Similar studies were conducted with cat liver, however, enzymatic transformation was not detected, with 100% recovery of the STX used in the incubation being recovered [118]. This was explained by the fact that with the exception of cats, the liver of mammals produces glucuronides as a major metabolic product, thus supporting the specificity of human tissue transformation [119]. However, biotransformation of STX was not detected when STX was passaged through rat’s urine, indicating further mammalian variability in models [120,121]. Gessner et al. investigated serum and urine in human PSP victims and detected a significant increase of the PST C1 in comparison to GTX2, which is distinguished by an additional sulfate on the carbamoyl side group [122]. A new assay for STX and neoSTX quantification in human urine samples has been developed recently [123]. It is proposed that methodological improvements should also contribute to a better understanding of PST profile and its change while passaging through the human body [123]. The research described above highlights the need to characterize the diversity of biological transformations of PSTs. Detoxification pathways could be manipulated to improve biological removal strategies, while further characterization of detoxification of PSTs within the human body could lead to improved treatment of PSP.

4. A Genetic Basis for the Paralytic Shellfish Toxins

4.1. The saxitoxin biosynthetic gene cluster

Recently the saxitoxin biosynthesis pathway was proposed [124], and the sxt gene cluster was identified in three cyanobacterial species of the family Nostocaceae [33,34] and one from the family Oscillatoriaceae [125]. The sxt gene clusters within each organism all contain a core set of genes putatively responsible for the biosynthesis of STX. However, the gene profile between each cluster differs, resulting in the production of a different suite of STX analogs by each organism. It is foreseeable that identification of the cyanobacterial PST biosynthesis genes will eventually lead to the identification of the homologs within dinoflagellates. However, the dinoflagellate PST biosynthesis genes remain elusive. There is also some debate on whether the enzymes for PST biosynthesis are encoded by the dinoflagellate genome, including plastids or other sources such as symbiotic bacteria or viruses [126–128].

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In cyanobacteria, biosynthesis of STX is catalyzed by several enzymes otherwise rare in microbial metabolism. The core PST biosynthetic gene, sxtA, is thought to have a chimeric origin and is putatively responsible for the initiation of STX biosynthesis, catalysing the incorporation of acetate to the enzyme complex and its subsequent methylation and Claisen condensation with arginine [33,34,129]. SxtA consists of four catalytic domains (SxtA1-SxtA4) with the N-terminal region showing similarities to a polyketide synthase (PKS) complex [130] consisting of a GCN5-related N-acetyltransferase [131], acyl-carrier protein (ACP) and a S-adenosylmethionine-dependant (SAM) methyltransferase [132] domains, while the C-terminal region contains a domain homologous to previously characterized aminotransferases [133]. Specific PST analog profiles are proposed to be the result of tailoring enzymes encoded by the sxt gene cluster. The function of tailoring enzymes within each of the characterized sxt clusters has been inferred by analysis of the specific toxin profile produced by each cyanobacterium. For example, neoSTX differs from STX by hydroxylation at the N1 position (Table 1). NeoSTX is produced by C. raciborskii T3, Aphanizomenon sp. NH-5 and L. wollei, but has not been detected in A. circinalis [14,35,36,57,62]. Sequence analysis of the four sxt gene clusters revealed SxtX as a protein putatively responsible for the N1-hydroxylation of STX, since sxtX was identified in all neoSTX producing strains and absent from the A. circinalis AWQC131C gene cluster [33,34]. This protein displayed high structural similarities to cephalosporin hydroxylase [134], further affirming its role in the N1-hydroxylation of STX. The GTXs are produced by mono-sulfation at N21 or O22 of STX which can then be di-sulfated to produce the C-toxins. Previous studies of the dinoflagellate G. catenatum, revealed two 3′-phosphate 5′-phosphosulfate (PAPS)-dependant sulfotransferases responsible for the N21 sulfation of STX, GTX2 and GTX3, and the O22 sulfation of 11-hydroxy STX [135,136]. Two genes, sxtO, a PAPS forming enzyme and sxtN, a sulfotransferase, within cyanobacterial sxt clusters are proposed to encode proteins that play a similar sulfation role in the synthesis of GTXs and C-toxins. The requirement of SAM for STX biosynthesis has long been hypothesized and thus has been targeted during attempts to identify the PST genes [137,138]. Harlow et al. were able to use degenerate primers to screen several dinoflagellate genomes in an attempt to identify genes encoding SAM as a candidate involved in PST biosynthesis [138]. Although several SAM genes were successfully identified within dinoflagellates, these were not correlated to PST biosynthesis. The study was hampered by a limited knowledge of dinoflagellate codon usage and a lack of related sequence information within the NCBI database [138,139]. Kellmann et al. used a similar degenerate PCR approach to identify a gene encoding a O-carbamoyltransferase (sxtI), which ultimately led to the identification of the entire sxt biosynthesis pathway in cyanobacteria [33,138,140]. There are now multiple genes that may be utilized to target homologs of the sxt cluster in dinoflagellates. However, a recent study identified the dinoflagellate sxt cluster may differ from cyanobacteria more than would be expected from a recent gene transfer event. Hence, mRNA present solely within toxic dinoflagellates may be more successful at identifying the candidate sxt pathway in these organisms [141].

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4.2. Pharmaceutical potential of the paralytic shellfish toxins Recent years has seen a renewed interest in marine alkaloids and their analogs, including the PSTs, with regards to their use as therapeutic agents or as a drug lead. Bioactivity studies and molecular modeling of a range of PSTs could also lead to the design of unnatural analogs with improved pharmaceutical characteristics. Recently, a group of toxins isolated from marine cone snails (genus Conus), known as conotoxins, have been shown to contain over 2,000 peptide analogs [142]. The conotoxins are able to specifically target a broad range of ion channels and membrane receptors with several currently under investigation for possible clinical trials [142]. In 2004, a synthetic version of a single conotoxin analog, ω-conotoxin MVIIA, also known as ziconotide (trade name Prialt®) was the first marine natural product to be approved for use by the US Food and Drug Administration since 1976 [143,144]. Ziconotide acts by targeting N-type voltage sensitive Ca2+ channels and is used for the treatment of chronic pain in spinal cord injury [145,146]. Like Prialt®, STX also has a huge pharmaceutical potential for its ability to induce anesthesia through interaction with site 1 of the voltage gated Na+ channel [38,39]. It has been suggested that site 1 blockers prolong the duration of anaesthesia in a synergistic manner when combined with other local anaesthetics [39,147,148]. In spite of this, the push for STX to enter clinical trials has been hindered by its systematic toxicity [149]. The use of STX as a slow release, prolonged anesthetic was recently demonstrated using a novel controlled release system in male Sprague-Dawley rats [150]. Liposomal formulations of STX, either alone and in conjunction with dexamethasone and/or bupivacaine, were able to block the sciatic nerve within rats for long periods with no damaging myotoxic, cytotoxic or neurotoxic effects and little associated inflammation [150]. Liposome formulations of STX for slow and site-directed release for prolonged anaesthesia have since been postulated as a putative treatment of localized pain and severe joint pain [151]. PSTs such as GTX2 + 3 also have clinical potential and have been utilized for the treatment of anal fissures [152–154]. Since 1951, surgery has been the most common form of anal fissure treatment with several possible side effects [155–157], while other treatments include ointments [158], botulinium toxin [159] and topical application of nitroglycerine [160]. Treatment with GTX2 + 3 involves direct injection into both sides of the fissure. A success rate of 98% with remission after 15 and 28 days for acute and chronic conditions, respectively (n = 100) was observed [153]. A follow up study with an enhanced method has since been performed by Garrido et al. with an improved time of healing of seven to 14 days for chronic cases (n = 23) [154]. Both studies identified GTX2 + 3 as safe and effective when compared to other treatments [153,154]. GTX2 + 3 have also been used in the treatment of chronic tension type headache, with 70% of patients (n = 27) responding to treatment [161]. These studies recognize that PSTs other than STX also have potential as future pharmaceutical leads. Their use in the past has also been limited largely due to problems obtaining purified PST analogs. The genetic characterization of PST biosynthesis pathways from diverse producer organisms has increased our insight into sxt tailoring reactions and the molecular understanding of the mechanisms by which a particular suite of PSTs can be synthesized. This will ultimately advance research into the pharmaceutical potential of the PSTs as Na+ channel blockers, by generating new analogs or by increasing the availability of analogs otherwise biosynthesized in low concentrations. Bioengineering can also be utilized to further enhance the structural diversity of bioactive small molecules by using in vitro approaches that utilize enzymes in chemical synthesis, as well as in vivo approaches, such as

Mar. Drugs 2010, 8 2200 combinatorial biosynthesis [40,41]. Combinatorial biosynthesis is the process of incorporating genes from multiple biosynthetic clusters into an expression plasmid, in a combinatorial fashion, to generate a library of ―unnatural‖ natural products expressed in vivo. However expression of large gene fragments in a heterologous host is required and analogs of interest may then be extracted, purified and assayed to determine their bioactivity. The bioactive nature of STX as an anaesthetic and GTX2 + 3 for the treatment of anal fissures and chronic tension type headaches demonstrates that these alkaloids have pharmaceutical potential deserving of further investigation. The recent elucidation of the sxt gene clusters in cyanobacteria and the identification of novel PSTs has provided more options for further PST bioactivity studies. Novel analogs could also be devised by redesigning PST biosynthesis genes in amenable host systems via combinatorial biosynthesis.

5. Conclusions

The structure of STX has been known for 53 years and the discovery of novel STX analogs has continued steadily ever since. Today, 57 PST analogs have been reported. With more sensitive detection methods, new STX analogs will most likely continue to be identified, with new functional moieties and possibly novel bioactivity. Despite extended research on the role of saxitoxin and its analogs as a sodium channel blocker, the effect of these toxins on the environment, and the genes that are responsible for their production, there is still a vast gap in knowledge in regards to their potential intracellular role within the producing organism. Nevertheless, it is possible that the different analogs display varying functions within the cells due to their partial differences in charges and chemical properties. More studies are needed to elucidate the localization of saxitoxin and its derivatives might provide clues to the potential role of the PST analogs within the producing organism. In the future, a better understanding of the intracellular and extracellular functions of STX might open more avenues for pharmaceutical applications. Since PSTs are produced by distantly related organisms, spanning two domains, including cyanobacteria, dinoflagellates and the Panamanian golden frog, it is possible that their occurrence in nature is more widespread than we know. Further investigations are needed to elucidate the extent of their distribution, diversity and their fundamental biology, such as their biosynthesis, metabolic and eco-physiological function. This is in addition to the role of chemical transformation of the different toxins in shellfish and the environment. Future research is also needed to understand the integration of PST biosynthesis within the overall cell metabolism and the possible recruitment of enzymes from other biosynthetic pathways for PST bioconversions. Proteomic and transcriptomic studies are likely to provide a link between STX biosynthesis, regulation and cellular metabolism. It is expected that data will allow us to acquire a better understanding of the conservation of the SXT biosynthesis pathway at the enzymatic level in comparison to the genetic level, may give further insight into the molecular function of these toxins and also lead to clues of their evolutionary history. In future, characterization of PST biosynthetic genes from dinoflagellates and comparison with cyanobacterial genes will also aid in our understanding of the evolutionary history of these genes with regard to their origin and transfer. PSP is a serious health problem and its incidence has continued to rise on a global scale. PSTs negatively impact the fisheries industry globally and the development of novel methods of

Mar. Drugs 2010, 8 2201 detoxification is essential from a human health and financial perspective [104,113,162]. The enzymatic basis for the structural diversity of PSTs is now beginning to be understood from the genetics of their biosynthesis in cyanobacteria and characterization of transformations catalyzed by bacteria, marine invertebrates and mammals. Biotransformation pathways could also be manipulated to efficiently remove toxins from water supplies. Specific enzymes or bacterial strains that degrade PSTs could be introduced into shellfish to assist detoxification. Currently, the PSTs represent extraordinary potential for pharmacy. This potential is likely to increase as we continue to gain a better molecular understanding of the PSTs, leading to future prospects of their use in combinatorial biosynthesis for the production of novel alkaloids with beneficial application.

Acknowledgements

The authors would like to thank the Australian Research Council, Diagnostic Technology, NSW Department of Primary Industries, Safe Food NSW, Department of Health and Human Services Tasmania and Primary Industries and Resources SA for supporting this work.

References

1. Schantz, E.J.; Mold, J.; Stanger, D.; Shavel, J.; Riel, F.; Bowden, J.; Lynch, J.; Wyler, R.; Riegel, B.; Sommer, H. Paralytic shellfish poison VI. A procedure for the isolation and purification of the poison from toxic clams and mussel tissues. J. Am. Chem. Soc. 1957, 79, 5230–5235. 2. Anderson, D.M.; Cembella, A.D.; Hallegraeff, G.M. Physiological Ecology of Harmful Algal Blooms, 1st ed.; Springer: Berlin, Germany, 1998; p. 662. 3. Anderson, D.M.; Glibert, P.M.; Burkholder, J.M. Harmful algal blooms and eutrophication: Nutrient sources, composition, and consequences. Estuaries 2002, 25, 704–726. 4. Sellner, K.G.; Doucette, G.J.; Kirkpatrick, G.J. Harmful algal blooms: Causes, impacts and detection. J. Ind. Microbiol. Biotechnol. 2003, 30, 383–406. 5. Zingone, A.; Enevoldsen, H.O. The diversity of harmful algal blooms: A challenge for science and management. Ocean Coast. Manage. 2000, 43, 725–748. 6. Van Dolah, F.M. Marine algal toxins: Origins, health effects, and their increased occurrence. Environ. Health Perspect. 2000, 108, 133–141. 7. Llewellyn, L.E. Saxitoxin, a toxic marine natural product that targets a multitude of receptors. Nat. Prod. Rep. 2006, 23, 200–222. 8. Lefebvre, K.A.; Bill, B.D.; Erickson, A.; Baugh, K.A.; O'Rourke, L.; Costa, P.R.; Nance, S.; Trainer, V.L. Characterization of intracellular and extracellular saxitoxin levels in both field and cultured Alexandrium spp. samples from Sequim Bay, Washington. Mar. Drugs 2008, 6, 103–116. 9. Oshima, Y.; Blackburn, S.I.; Hallegraeff, G.M. Comparative study on paralytic shellfish toxin profiles of the dinoflagellate Gymnodinium catenatum from three different countries. Mar. Biol. 1993, 116, 471–476. 10. Usup, G.; Kulis, D.M.; Anderson, D.M. Growth and toxin production of the toxic dinoflagellate Pyrodinium bahamense var. compressum in laboratory cultures. Nat. Toxins 1994, 2, 254–262.

Mar. Drugs 2010, 8 2202

11. Gainey, L.; Shumway, J.; Shumway, S. A compendium of the responses of bivalve molluscs to toxic dinoflagellates. J. Shellfish Res. 1988, 7, 623–628. 12. Shumway, S.E. Phycotoxin-related shellfish poisoning: Bivalve molluscs are not the only vectors Rev. Fish. Sci. 1995, 3, 1–31. 13. Deeds, J.; Landsberg, J.; Etheridge, S.; Pitcher, G.; Longan, S. Non-traditional vectors for paralytic shellfish poisoning. Mar. Drugs 2008, 6, 308–348. 14. Carmichael, W.W.; Evans, W.R.; Yin, Q.Q.; Bell, P.; Moczydlowski, E. Evidence for paralytic shellfish poisons in the freshwater cyanobacterium Lyngbya wollei (Farlow ex Gomont) comb. nov. Appl. Environ. Microbiol. 1997, 63, 3104–3110. 15. Hoeger, S.J.; Shaw, G.; Hitzfeld, B.C.; Dietrich, D.R. Occurrence and elimination of cyanobacterial toxins in two Australian drinking water treatment plants. Toxicon 2004, 43, 639–649. 16. Molica, R.J.R.; Oliveira, E.J.A.; Carvalho, P.V.V.C.; Costa, A.N.S.F.; Cunha, M.C.C.; Melo, G.L.; Azevedo, S.M.F.O. Occurrence of saxitoxins and an anatoxin-a(s)-like anticholinesterase in a Brazilian drinking water supply. Harmful Algae 2005, 4, 743–753. 17. Clemente, Z.; Busato, R.H.; Oliveira Ribeiro, C.A.; Cestari, M.M.; Ramsdorf, W.A.; Magalhães, V.F.; Wosiack, A.C.; Silva de Assis, H.C. Analyses of paralytic shellfish toxins and biomarkers in a southern Brazilian reservoir. Toxicon 2010, 55, 396–406. 18. Liu, Y.; Chen, W.; Li, D.; Shen, Y.; Li, G.; Liu, Y. First report of aphantoxins in China— waterblooms of toxigenic Aphanizomenon flos-aquae in Lake Dianchi. Ecotoxicol. Environ. Saf. 2006, 65, 84–92. 19. Berry, J.P.; Lind, O. First evidence of "paralytic shellfish toxins" and cylindrospermopsin in a Mexican freshwater system, Lago Catemaco, and apparent bioaccumulation of the toxins in "tegogolo" snails (Pomacea patula catemacensis). Toxicon 2010, 55, 930–938. 20. Ballot, A.; Fastner, J.; Wiedner, C. Paralytic shellfish poisoning toxin-producing cyanobacterium Aphanizomenon gracile in Northeast Germany. Appl. Environ. Microbiol. 2010, 76, 1173–1180. 21. Codd, G.A. Cyanobacterial toxins: occurrence, properties and biological significance. Water Sci. Technol. 1995, 32, 149–156. 22. Sivonen, K.; Jones, G. Cyanobacterial toxins. In Toxin Cyanobacteria in Water: A Guide to Their Public Health Consequences, Monitoring and Management; Chorus, I., Bartram, J., Eds.; WHO E & FN Spon: London, UK, 1999; pp. 41–111. 23. Kao, C.Y. Paralytic shellfish poisoning. In Algal Toxins in Seafood and Drinking Water; Falconer, E.R., Ed.; Academic: London, UK, 1993; p. 75. 24. Anderson, D.M.; Kulis, D.M.; Qi, Y.; Zheng, L.; Lu, S.; Lin, Y. Paralytic shellfish poisoning in Southern China. Toxicon 1996, 34, 579–590. 25. Rodrigue, D.C.; Etzel, R.A.; Hall, S.; de Porras, E.; Velasquez, O.H.; Tauxe, R.V.; Kilbourne, E.M.; Blake, P.A. Lethal paralytic shellfish poisoning in Guatemala. Am. J. Trop. Med. Hyg. 1990, 42, 267–271. 26. Garcia, C.; del Carmen Bravo, M.; Lagos, M.; Lagos, N. Paralytic shellfish poisoning: Post-mortem analysis of tissue and body fluid samples from human victims in the Patagonia fjords. Toxicon 2004, 43, 149–158.

Mar. Drugs 2010, 8 2203

27. Landsberg, J.H.; Hall, S.; Johannessen, J.N.; White, K.D.; Conrad, S.M.; Abbott, J.P.; Flewelling, L.J.; Richardson, R.W.; Dickey, R.W.; Jester, E.L.; Etheridge, S.M.; Deeds, J.R.; Van Dolah, F.M.; Leighfield, T.A.; Zou, Y.; Beaudry, C.G.; Benner, R.A.; Rogers, P.L.; Scott, P.S.; Kawabata, K.; Wolny, J.L.; Steidinger, K.A. Saxitoxin puffer fish poisoning in the United States, with the first report of Pyrodinium bahamense as the putative toxin source. Environ. Health Perspect. 2006, 114, 1502–1507. 28. Catterall, W.A.; Morrow, C.S.; Hartshorne, R.P. Neurotoxin binding to receptor sites associated with voltage-sensitive sodium channels in intact, lysed, and detergent-solubilized brain membranes. J. Biol. Chem. 1979, 254, 11379–11387. 29. Catterall, W.A. Neurotoxins that act on voltage-sensitive sodium channels in excitable membranes. Annu. Rev. Pharmacol. 1980, 20, 15–43. 30. Cestèle, S.; Catterall, W.A. Molecular mechanisms of neurotoxin action on voltage-gated sodium channels. Biochimie 2000, 82, 883–892. 31. Guy, A.L.; Griffin, G. Adopting alternatives for the regulatory monitoring of shellfish for paralytic shellfish poisoning in Canada: Interface between federal regulators, science and ethics. Regul. Toxicol. Pharmacol. 2009, 54, 256–263. 32. Stewart, I.; Seawright, A.A.; Shaw, G.R. Cyanobacterial poisoning in livestock, wild mammals and birds—an overview. In Cyanobacterial Harmful Algal Blooms: State of the Science and Research Needs; Hudnell, H.K., Ed.; Springer: New York, NY, USA, 2008; pp. 613–637. 33. Kellmann, R.; Mihali, T.K.; Jeon, Y.J.; Pickford, R.; Pomati, F.; Neilan, B.A. Biosynthetic intermediate analysis and functional homology reveal a saxitoxin gene cluster in cyanobacteria. Appl. Environ. Microbiol. 2008, 74, 4044–4053. 34. Mihali, T.K.; Kellmann, R.; Neilan, B.A. Characterisation of the paralytic shellfish toxin biosynthesis gene clusters in Anabaena circinalis AWQC131C and Aphanizomenon sp. NH-5. BMC Biochem. 2009, 10, 8. 35. Llewellyn, L.E.; Negri, A.P.; Doyle, J.; Baker, P.D.; Beltran, E.C.; Neilan, B.A. Radioreceptor assays for sensitive detection and quantitation of saxitoxin and its analogues from strains of the freshwater cyanobacterium, Anabaena circinalis. Environ. Sci. Technol. 2001, 35, 1445–1451. 36. Lagos, N.; Onodera, H.; Zagatto, P.A.; Andrinolo, D.; Azevedo, S.M.F.Q.; Oshima, Y. The first evidence of paralytic shellfish toxins in the freshwater cyanobacterium Cylindrospermopsis raciborskii, isolated from Brazil. Toxicon 1999, 37, 1359–1373. 37. Ferreira, F.M.B.; Soler, J.M.F.; Fidalgo, M.L.; Fernández-Vila, P. PSP toxins from Aphanizomenon flos-aquae (cyanobacteria) collected in the Crestuma-Lever reservoir (Douro river, northern Portugal). Toxicon 2001, 39, 757–761. 38. Hille, B. The receptor for tetrodotoxin and saxitoxin. A structural hypothesis. Biophys. J. 1975, 15, 615–619. 39. Adams, H.J.; Blair, M.R., Jr.; Takman, B.H. The local anesthetic activity of saxitoxin alone and with vasoconstrictor and local anesthetic agents. Arch. Int. Pharmacodyn. Ther. 1976, 224, 275–282. 40. Khosla, C.; Keasling, J.D. Metabolic engineering for drug discovery and development. Nat. Rev. Drug Discov. 2003, 2, 1019–1025.

Mar. Drugs 2010, 8 2204

41. Zhang, W.; Tang, Y. Combinatorial biosynthesis of natural products. J. Med. Chem. 2008, 51, 2629–2633. 42. Bordner, J.; Thiessen, W.E.; Bates, H.A.; Rapoport, H. Structure of a crystalline derivative of saxitoxin. Structure of saxitoxin. J. Am. Chem. Soc. 1975, 97, 6008–6012. 43. Schantz, E.J.; Ghazarossian, V.E.; Schnoes, H.K.; Strong, F.M.; Springer, J.P.; Pezzanite, J.O.; Clardy, J. Structure of saxitoxin. J. Am. Chem. Soc. 1975, 97, 1238–1239. 44. Shimizu, Y. Chemistry and mechanism of action. In Seafood and Freshwater Toxins: Pharmacology, Physiology, and Detection; Botana, L.M., Ed.; Marcel Dekker: New York, NY, USA, 2000; pp. 151–172. 45. Berlinck, R.G.S.; Kossuga, M.H. Natural guanidine derivatives. Nat. Prod. Rep. 2005, 22, 516–550. 46. Ciminiello, P.; Fattorusso, E.; Forino, M.; Montresor, M. Saxitoxin and neosaxitoxin as toxic principles of Alexandrium andersoni (Dinophyceae) from the Gulf of Naples, Italy. Toxicon 2000, 38, 1871–1877. 47. Siu, G.; Young, M.; Chan, D. Environmental and nutritional factors which regulate population dynamics and toxin production in the dinoflagellate Alexandrium catenella. Hydrobiologia 1997, 352, 117–140. 48. Sebastián, C.R.; Etheridge, S.M.; Cook, P.A.; O'Ryan, C.; Pitcher, G.C. Phylogenetic analysis of toxic Alexandrium (Dinophyceae) isolates from South Africa: implications for the global phylogeography of the Alexandrium tamarense species complex. Phycologia 2005, 44, 49–60. 49. Krock, B.; Seguel, C.G.; Cembella, A.D. Toxin profile of Alexandrium catenella from the Chilean coast as determined by liquid chromatography with fluorescence detection and liquid chromatography coupled with tandem mass spectrometry. Harmful Algae 2007, 6, 734–744. 50. Poulton, N.J.; Keafer, B.A.; Anderson, D.M. Toxin variability in natural populations of Alexandrium fundyense in Casco Bay, Maine—evidence of nitrogen limitation. Deep-Sea Res. PT. II 2005, 52, 2501–2521. 51. Anderson, D.M.; Kulis, D.M.; Sullivan, J.J.; Hall, S. Toxin composition variations in one isolate of the dinoflagellate Alexandrium fundyense. Toxicon 1990, 28, 885–893. 52. Jaime, E.; Gerdts, G.; Luckas, B. In vitro transformation of PSP toxins by different shellfish tissues. Harmful Algae 2007, 6, 308–316. 53. Parkhill, J.; Cembella, A. Effects of salinity, light and inorganic nitrogen on growth and toxigenicity of the marine dinoflagellate Alexandrium tamarense from northeastern Canada. J. Plankton Res. 1999, 21, 939–955. 54. Yu, R.; Hummert, C.; Luckas, B.; Qian, P.; Li, J.; Zhou, M. A modified HPLC method for analysis of PSP toxins in algae and shellfish from china. Chromatographia 1998, 48, 671–676. 55. Ichimi, K.; Suzuki, T.; Ito, A. Variety of PSP toxin profiles in various culture strains of Alexandrium tamarense and change of toxin profile in natural A. tamarense population. J. Exp. Mar. Biol. Ecol. 2002, 273, 51–60. 56. Dell'Aversano, C.; Walter, J.A.; Burton, I.W.; Stirling, D.J.; Fattorusso, E.; Quilliam, M.A. Isolation and structure elucidation of new and unusual saxitoxin analogues from mussels. J. Nat. Prod. 2008, 71, 1518–1523.

Mar. Drugs 2010, 8 2205

57. Velzeboer, R.M.A.; Baker, P.D.; Rositano, J.; Heresztyn, T.; Codd, G.A.; Raggett, S.L. Geographical patterns of occurrence and composition of saxitoxins in the cyanobacterial genus Anabaena (Nostocales, Cyanophyta) in Australia. Phycologia 2000, 39, 395–407. 58. Testé, V.; Briand, J.-F.; Nicholson, B.C.; Puiseux-Dao, S. Comparison of changes in toxicity during growth of Anabaena circinalis (cyanobacteria) determined by mouse neuroblastoma bioassay and HPLC. J. Appl. Phycol. 2002, 14, 399–407. 59. Negri, A.P.; Jones, G.J. Bioaccumulation of paralytic shellfish poisoning (PSP) toxins from the cyanobacterium Anabaena circinalis by the freshwater mussel Alathyria condola. Toxicon 1995, 33, 667–678. 60. Dias, E.; Pereira, P.; Franca, S. Production of the paralytic shellfish toxins by Aphanizomenon sp. LMECYA 31 (cyanobacteria). J. Phycol. 2002, 38, 705–712. 61. Ikawa, M.; Wegener, K.; Foxall, T.L.; Sasner, J.J., Jr. Comparison of the toxins of the blue-green alga Aphanizomenon flos-aquae with the Gonyaulax toxins. Toxicon 1982, 20, 747–752. 62. Mahmood, N.A.; Carmichael, W.W. Paralytic shellfish poisons produced by the freshwater cyanobacterium Aphanizomenon flos-aquae NH-5. Toxicon 1986, 24, 175–186. 63. Pereira, P.; Onodera, H.; Andrinolo, D.; Franca, S.; Araújo, F.; Lagos, N.; Oshima, Y. Paralytic shellfish toxins in the freshwater cyanobacterium Aphanizomenon flos-aquae, isolated from Montargil reservoir, Portugal. Toxicon 2000, 38, 1689–1702. 64. Pereira, P.; Li, R.; Carmichael, W.; Dias, E.; Franca, S. Taxonomy and production of paralytic shellfish toxins by the freshwater cyanobacterium Aphanizomenon gracile LMECYA40. Eur. J. Phycol. 2004, 39, 361–368. 65. Nogueira, I.C.G.; Pereira, P.; Dias, E.; Pflugmacher, S.; Wiegand, C.; Franca, S.; Vasconcelos, V.M. Accumulation of paralytic shellfish toxins (PST) from the cyanobacterium Aphanizomenon issatschenkoi by the cladoceran Daphnia magna. Toxicon 2004, 44, 773–780. 66. Rapala, J.; Robertson, A.; Negri, A.P.; Berg, K.A.; Tuomi, P.; Lyra, C.; Erkomaa, K.; Lahti, K.; Hoppu, K.; Lepistö, L. First report of saxitoxin in Finnish lakes and possible associated effects on human health. Environ. Toxicol. 2005, 20, 331–340. 67. Castro, D.; Vera, D.; Lagos, N.; García, C.; Vásquez, M. The effect of temperature on growth and production of paralytic shellfish poisoning toxins by the cyanobacterium Cylindrospermopsis raciborskii C10. Toxicon 2004, 44, 483–489. 68. Pomati, F.; Moffitt, M.C.; Cavaliere, R.; Neilan, B.A. Evidence for differences in the metabolism of saxitoxin and C1+2 toxins in the freshwater cyanobacterium Cylindrospermopsis raciborskii T3. BBA-Gen. Subjects 2004, 1674, 60–67. 69. Molica, R.; Onodbra, H.; Garcia, C.; Rivas, M.; Andrinolo, D.; Nascimento, S.; Meguro, H.; Oshimo, Y.; Azevedo, S.; Lagos, N. Toxins in the freshwater cyanobacterium Cylindrospermopsis raciborskii (Cyanophyceae) isolated from Tabocas reservoir in Caruaru, Brazil, including demonstration of a new saxitoxin analogue. Phycologia 2002, 41, 606–611. 70. Holmes, M.J.; Bolch, C.J.S.; Green, D.H.; Cembella, A.D.; Teo, S.L.M. Singapore isolates of the dinoflagellate Gymnodinium catenatum (Dinophyceae) produce a unique profile of paralytic shellfish poisoning toxins. J. Phycol. 2002, 38, 96–106.

Mar. Drugs 2010, 8 2206

71. Gárate-Lizárraga, I.; Bustillos-Guzmán, J.J.; Morquecho, L.; Band-Schmidt, C.J.; Alonso- Rodríguez, R.; Erler, K.; Luckas, B.; Reyes-Salinas, A.; Góngora-González, D.T. Comparative paralytic shellfish toxin profiles in the strains of Gymnodinium catenatum Graham from the Gulf of California, Mexico. Mar. Pollut. Bull. 2005, 50, 211–217. 72. Negri, A.P.; Bolch, C.J.S.; Geier, S.; Green, D.H.; Park, T.-G.; Blackburn, S.I. Widespread presence of hydrophobic paralytic shellfish toxins in Gymnodinium catenatum. Harmful Algae 2007, 6, 774–780. 73. Pomati, F.; Sacchi, S.; Rossetti, C.; Giovannardi, S.; Onodera, H.; Oshima, Y.; Neilan, B.A. The freshwater cyanobacterium Planktothrix sp. FP1: Molecular identification and detection of paralytic shellfish poisoning toxins. J. Phycol. 2000, 36, 553–562. 74. Liu, Y.; Chen, W.; Li, D.; Shen, Y.; Liu, Y.; Song, L. Analysis of paralytic shellfish toxins in Aphanizomenon DC-1 from Lake Dianchi, China. Environ. Toxicol. 2006, 21, 289–295. 75. Navarro, J.M.; Muñoz, M.G.; Contreras, A.M. Temperature as a factor regulating growth and toxin content in the dinoflagellate Alexandrium catenella. Harmful Algae 2006, 5, 762–769. 76. Samsur, M.; Yamaguchi, Y.; Sagara, T.; Takatani, T.; Arakawa, O.; Noguchi, T. Accumulation and depuration profiles of PSP toxins in the short-necked clam Tapes japonica fed with the toxic dinoflagellate Alexandrium catenella. Toxicon 2006, 48, 323–330. 77. Franco, J.; Fernández, P.; Reguera, B. Toxin profiles of natural populations and cultures of Alexandrium minutum Halim from Galician (Spain) coastal waters. J. Appl. Phycol. 1994, 6, 275–279. 78. Hwang, D.-F.; Lu, Y.-H.; Noguchi, T. Effects of exogenous polyamines on growth, toxicity, and toxin profile of dinoflagellate Alexandrium minutum. J. Food Hyg. Soc. Jpn. 2003, 44, 49–53. 79. Pitcher, G.C.; Cembella, A.D.; Joyce, L.B.; Larsen, J.; Probyn, T.A.; Ruiz Sebastián, C. The dinoflagellate Alexandrium minutum in Cape Town harbour (South Africa): Bloom characteristics, phylogenetic analysis and toxin composition. Harmful Algae 2007, 6, 823–836. 80. Hansen, P.J.; Cembella, A.D.; Moestrup, Ø. The marine dinoflagellate Alexandrium ostenfeldii: Paralytic shellfish toxin concentration, composition and toxicity to a tintinnid cilliate. J. Phycol. 1992, 28, 597–603. 81. Vale, P. Metabolites of saxitoxin analogues in bivalves contaminated by Gymnodinium catenatum. Toxicon 2010, 55, 162–165. 82. Onodera, H.; Satake, M.; Oshima, Y.; Yasumoto, T.; Carmichael, W.W. New saxitoxin analogues from the freshwater filamentous cyanobacterium Lyngbya wollei. Nat. Toxins 1997, 5, 146–151. 83. Negri, A.; Stirling, D.; Quilliam, M.; Blackburn, S.; Bolch, C.; Burton, I.; Eaglesham, G.; Thomas, K.; Walter, J.; Willis, R. Three novel hydroxybenzoate saxitoxin analogues isolated from the dinoflagellate Gymnodinium catenatum. Chem. Res. Toxicol. 2003, 16, 1029–1033. 84. Oshima, Y.; Sugino, K.; Itakura, H.; Hirota, M.; Yasumoto, T. Comparative studies on paralytic shellfish toxin profile of dinoflagellates and bivalves. In Toxic Marine Phytoplankton; Grane'li, E., Sundstrom, B., Edler, L., Anderson, D.M., Eds.; Elsevier Science Publishing: New York, NY, USA, 1990; pp. 391–396.

Mar. Drugs 2010, 8 2207

85. Vale, P. Complex profiles of hydrophobic paralytic shellfish poisoning compounds in Gymnodinium catenatum identified by liquid chromatography with fluorescence detection and mass spectrometry. J. Chromatogr. A 2008, 1195, 85–93. 86. Vale, P.; Rangel, I.; Silva, B.; Coelho, P.; Vilar, A. Atypical profiles of paralytic shellfish poisoning toxins in shellfish from Luanda and Mussulo bays, Angola. Toxicon 2009, 53, 176–183. 87. Arakawa, O.; Nishio, S.; Noguchi, T.; Shida, Y.; Onoue, Y. A new saxitoxin analogue from a xanthid crab Atergatis floridus. Toxicon 1995, 33, 1577–1584. 88. Zaman, L.; Arakawa, O.; Shimosu, A.; Shida, Y.; Onoue, Y. Occurrence of a methyl derivative of saxitoxin in Bangladeshi freshwater puffers. Toxicon 1998, 36, 627–630. 89. Yotsu-Yamashita, M.; Kim, Y.H.; Dudley, S.C.; Choudhary, G.; Pfahnl, A.; Oshima, Y.; Daly, J.W. The structure of zetekitoxin AB, a saxitoxin analog from the Panamanian golden frog Atelopus zeteki: A potent sodium-channel blocker. Proc. Natl. Acad. Sci. USA 2004, 101, 4346–4351. 90. van Apeldoorn, M.E.; van Egmond, H.P.; Speijers, G.J.A.; Bakker, G.J.I. Toxins of cyanobacteria. Mol. Nutr. Food Res. 2007, 51, 7–60. 91. Negri, A.P.; Bolch, C.J.; Blackbum, S.I.; Dickman, M.; Llewellyn, L.E.; Mendez, S. Paralytic shellfish toxins in Gymnodinium catenatum strains from six countries. In Harmfull Algal Blooms 2000; Hallegraeff, G., Bolch, C.J., Blackburn, S.I., Lewis, R.J., Eds.; Intergovernmental Oceanographic Commission of UNESCO: Paris, France, 2001; pp. 210–213. 92. Llewellyn, L.; Negri, A.; Quilliam, M. High affinity for the rat brain sodium channel of newly discovered hydroxybenzoate saxitoxin analogues from the dinoflagellate Gymnodinium catenatum. Toxicon 2004, 43, 101–104. 93. Vale, P. Fate of benzoate paralytic shellfish poisoning toxins from Gymnodinium catenatum in shellfish and fish detected by pre-column oxidation and liquid chromatography with fluorescence detection. J. Chromatogr. A 2008, 1190, 191–197. 94. Codd, G.A.; Morrison, L.F.; Metcalf, J.S. Cyanobacterial toxins: risk management for health protection. Toxicol. Appl. Pharm. 2005, 203, 264–272. 95. Usleber, E.; Donald, M.; Straka, M.; Märtlbauer, E. Comparison of enzyme immunoassay and mouse bioassay for determining paralytic shellfish poisoning toxins in shellfish. Food Addit. Contam. 1997, 14, 193–198. 96. Genenah, A.A.; Shimizu, Y. Specific toxicity of paralytic shellfish poisons. J. Agr. Food Chem. 1981, 29, 1289–1291. 97. Sullivan, J.J.; Wekell, M.M.; Kentala, L.L. Application of HPLC for the Determination of PSP Toxins in Shellfish. J. Food Sci. 1985, 50, 26–29. 98. Oshima, Y.; Sugino, K.; Yasumoto, T. Mycotoxins and Phycotoxins '88; Elsevier Applied Science: Amsterdam, The Netherlands, 1989. 99. Oshima, Y. Chemical and enzymatic transformation of paralytic shellfish toxins in marine organisms. In Harmful Marine Algal Blooms; Lassus, P., Arzul, G., Erard, E., Gentien, P., Marcaillou, C., Eds.; Lavoisier: Paris, France, 1995.

Mar. Drugs 2010, 8 2208

100. Asakawa, M.; Miyazawa, K.; Takayama, H.; Noguchi, T. Dinoflagellate Alexandrium tamarense as the source of paralytic shellfish poison (PSP) contained in bivalves from Hiroshima Bay, Hiroshima Prefecture, Japan. Toxicon 1995, 33, 691–697. 101. Bricelj, V.M.; Lee, J.H.; Cembella, A.D. Influence of dinoflagellate cell toxicity on uptake and loss of paralytic shellfish toxins in the northern quahog Mercenaria mercenaria. Mar. Ecol. Prog. Ser. 1991, 74, 33–46. 102. Bricelj, V.M.; Lee, J.H.; Cembella, A.D.; Anderson, D.M. Uptake kinetics of paralytic shellfish toxins from the dinoflagellate Alexandrium fundyense in the mussel Mytilus edulis. Mar. Ecol. Prog. Ser. 1990, 63, 177–188. 103. Cembella, A.D.; Shumway, S.E.; Lewis, N.I. Anatomical distribution and spatio-temporal variation in paralytic shellfish toxin composition in two bivalve species from the Gulf of Maine. J. Shellfish Res. 1993, 12, 389–403. 104. Lassus, P.; Bardouill, M.; Massselin, P.; Naviner, P.; Truquet., P. Comparative efficiencies of different non-toxic microalgal diets in detoxification of PSP-contaminated oysters (Crassoatrea gigas Thunberg). J. Nat. Toxins 2000, 9, 1–12. 105. Oshima, Y.; Fallon, W.E.; Shimizu, Y.; Noguchi, T.; Hashimoto, Y. Toxins of the Gonyaulax sp. and infested bivalves in Owase Bay. Bull. Jpn. Soc. Sci. Fish. 1976, 42, 851–856. 106. Sullivan, J.J.; Iwaoka, W.T.; Liston, J. Enzymatic transformation of PSP toxins in the littleneck clam (Protothaca staminea). Biochem. Biophys. Res. Commun. 1983, 114, 465–472. 107. Shimizu, Y.; Yoshioka, M. Transformation of paralytic shellfish toxins as demonstrated in scallop homogenates. Science 1981, 212, 547–549. 108. Lu, Y.; Hwang, D. Effects of toxic dinoflagellates and toxin biotransformation in bivalves. J. Nat. Toxins 2002, 11, 315–322. 109. Fast, M.D.; Cembella, A.D.; Ross, N.W. In vitro transformation of paralytic shellfish toxins in the clams Mya arenaria and Protothaca staminea. Harmful Algae 2006, 5, 79–90. 110. Kotaki, Y.; Oshima, Y.; Yasumoto, T. Bacterial transformation of paralytic shellfish toxins in coral reef crabs and a marine snail. Nippon Suisan Gakk. 1985, 51, 1009–1013 111. Kotaki, Y. Screening of bacteria which convert gonyautoxin 2,3 to saxitoxin. Nippon Suisan Gakk. 1989, 55, 1293. 112. Sugawara, A.; Imamura, T.; Aso, S.; Ebitani, K. Change of paralytic shellfish poison by the marine bacteria living in the intestine of the Japanese surf clam, Pseudocardium sybillae, and the brown sole, Pleuronectes herensteini. Sci. Rep. Hokkaido Fish. Exp. Stat. 1997, 50, 35–42. 113. Smith, E.A.; Grant, F.; Ferguson, C.M.J.; Gallacher, S. Biotransformations of paralytic shellfish toxins by bacteria isolated from bivalve molluscs. Appl. Environ. Microbiol. 2001, 67, 2345–2353. 114. Donovan, C.J.; Garduno, R.A.; Kalmokoff, M.; Ku, J.C.; Quilliam, M.A.; Gill, T.A. Pseudoalteromonas bacteria are capable of degrading paralytic shellfish toxins. Appl. Environ. Microbiol. 2009, 75, 6919–6923. 115. Donovan, C.J.; Ku, J.C.; Quilliam, M.A.; Gill, T.A. Bacterial degradation of paralytic shellfish toxins. Toxicon 2008, 52, 91–100. 116. Kayal, N.; Newcombe, G.; Ho, L. Investigating the fate of saxitoxins in biologically active water treatment plant filters. Environ. Toxicol. 2008, 23, 751–755.

Mar. Drugs 2010, 8 2209

117. García, C.; Rodriguez-Navarro, A.; Díaz, J.C.; Torres, R.; Lagos, N. Evidence of in vitro glucuronidation and enzymatic transformation of paralytic shellfish toxins by healthy human liver microsomes fraction. Toxicon 2009, 53, 206–213. 118. Andrinolo, D.; Michea, L.F.; Lagos, N. Toxic effects, pharmacokinetics and clearance of saxitoxin, a component of paralytic shellfish poison (PSP), in cats. Toxicon 1999, 37, 447–464. 119. Kasper, B.C.; Henton, D. Glucuronidation. In Enzymatic Basis of Detoxication; Jakob, W.B., Ed.; Academic: New York, NY, USA, 1960; Vol. 1. 120. Stafford, R.G.; Hines, H.B. Urinary elimination of saxitoxin after intravenous injection. Toxicon 1995, 33, 1501–1510. 121. Hines, H.; Naseem, S.; Wannemacher, R.J. 3H-Saxitoxinol metabolism and elimination in the rat. Toxicon 1993, 31, 905–908. 122. Gessner, B.D.; Bell, P.; Doucette, G.J.; Moczydlowski, E.; Poli, M.A.; Van Dolah, F.; Hall, S. Hypertension and identification of toxin in human urine and serum following a cluster of mussel- associated paralytic shellfish poisoning outbreaks. Toxicon 1997, 35, 711–722. 123. Johnson, R.C.; Zhou, Y.; Statler, K.; Thomas, J.; Cox, F.; Hall, S.; Barr, J.R. Quantification of saxitoxin and neosaxitoxin in human urine utilizing isotope dilution tandem mass spectrometry. J. Anal. Toxicol. 2009, 33, 8–14. 124. Kellmann, R.; Neilan, B.A. Biochemical characterization of paralytic shellfish toxin biosynthesis in vitro. J. Phycol. 2007, 43, 497–508. 125. Mihali, T.K.; Carmichael, W.W.; Neilan, B.A. Biosynthesis of the Lyngbya wollei (Farlow ex Gomont) paralytic shellfish toxins - natural biocombinatorics. PLoS One 2010, Submitted for publication. 126. Prol, M.J.; Guisande, C.; Barreiro, A.; Miguez, B.; de la Iglesia, P.; Villar, A.; Gago-Martinez, A.; Combarro, M.P. Evaluation of the production of paralytic shellfish poisoning toxins by extracellular bacteria isolated from the toxic dinoflagellate Alexandrium minutum. Can. J. Microbiol. 2009, 55, 943–954. 127. Baker, T.R.; Doucette, G.J.; Powell, C.L.; Boyer, G.L.; Plumley, F.G. GTX4 imposters: Characterization of fluorescent compounds synthesized by Pseudomonas stutzeri SF/PS and Pseudomonas/Alteromonas PTB-1, symbionts of saxitoxin-producing Alexandrium spp. Toxicon 2003, 41, 339–347. 128. Gallacher, S.; Flynn, K.; Franco, J.; Brueggemann, E.; Hines, H. Evidence for production of paralytic shellfish toxins by bacteria associated with Alexandrium spp. (Dinophyta) in culture. Appl. Environ. Microbiol. 1997, 63, 239–245. 129. Moustafa, A.; Loram, J.E.; Hackett, J.D.; Anderson, D.M.; Plumley, F.G.; Bhattacharya, D. Origin of saxitoxin biosynthetic genes in cyanobacteria. PLoS ONE 2009, 4, e5758. 130. Hill, A.M. The biosynthesis, molecular genetics and enzymology of the polyketide-derived metabolites. Nat. Prod. Rep. 2006, 23, 256–320. 131. Wolf, E.; Vassilev, A.; Makino, Y.; Sali, A.; Nakatani, Y.; Burley, S.K. Crystal Structure of a GCN5-Related N-acetyltransferase: Serratia marcescens Aminoglycoside 3-N-acetyltransferase. Cell 1998, 94, 439–449.

Mar. Drugs 2010, 8 2210

132. Kagan, R.M.; Clarke, S. Widespread occurrence of three sequence motifs in diverse S-adenosylmethionine-dependent methyltransferases suggests a common structure for these enzymes. Arch. Biochem. Biophys. 1994, 310, 417–427. 133. Alexander, F.W.; Sandmeier, E.; Mehta, P.K.; Christen, P. Evolutionary relationships among pyridoxal-5'-phosphate-dependent enzymes. Eur. J. Biochem. 1994, 219, 953–960. 134. Alexander, D.C.; Jensen, S.E. Investigation of the Streptomyces clavuligerus cephamycin C gene cluster and its regulation by the CcaR protein. J. Bacteriol. 1998, 180, 4068–4079. 135. Yoshida, T.; Sako, Y.; Uchida, A.; Kakutani, T.; Arakawa, O.; Noguchi, T.; Ishida, Y. Purification and characterization of sulfotransferase specific to O-22 of 11-hydroxy saxitoxin from the toxic dinoflagellate Gymnodinium catenatum (dinophyceae). Fish. Sci. 2002, 68, 634–642. 136. Sako, Y.; Yoshida, T.; Uchida, A.; Arakawa, O.; Noguchi, T.; Ishida, Y. Purification and characterization of a sulfotransferase specific to N-21 of saxitoxin and gonyautosin 2+3 from the toxic dinoflagellate Gymnodinium catenatum (Dinophyceae) J. Phycol. 2001, 37, 1044–1051. 137. Shimizu, Y. Microalgal metabolites. Chem. Rev. 1993, 93, 1685–1698. 138. Harlow, L.D.; Koutoulis, A.; Hallegraeff, G.M. S-adenosylmethionine synthetase genes from eleven marine dinoflagellates. Phycologia 2007, 46, 46–53. 139. Altschul, S.F.; Madden, T.L.; Schaffer, A.A.; Zhang, J.; Zhang, Z.; Miller, W.; Lipman, D.J. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997, 25, 3389–3402. 140. Kellmann, R.; Mihali, T.K.; Neilan, B.A. Identification of a saxitoxin biosynthesis gene with a history of frequent horizontal gene transfers. J. Mol. Evol. 2008, 67, 526–538. 141. Yang, I.; John, U.; Beszteri, S.; Glockner, G.; Krock, B.; Goesmann, A.; Cembella, A. Comparative gene expression in toxic versus non-toxic strains of the marine dinoflagellate Alexandrium minutum. BMC Genomics 2010, 11, 248. 142. Halai, R.; Craik, D.J. Conotoxins: Natural product drug leads. Nat. Prod. Rep. 2009, 26, 526–536. 143. Klotz, U. Ziconotide—a novel neuron-specific calcium channel blocker for the intrathecal treatment of severe chronic pain—a short review. Int. J. Clin. Pharmacol. Ther. 2006, 44, 478–483. 144. Glaser, K.B.; Mayer, A.M.S. A renaissance in marine pharmacology: From preclinical curiosity to clinical reality. Biochem. Pharmacol. 2009, 78, 440–448. 145. Olivera, B.M.; Cruz, L.J.; de Santos, V.; LeCheminant, G.W.; Griffin, D.; Zeikus, R.; McIntosh, M.; Galyean, R.; Varga, J.; Gray, W.R.; Rivier, J. Neuronal calcium channel antagonists. Discrimination between calcium channel subtypes using omega-conotoxin from Conus magus venom. Biochemistry 1987, 26, 2086–2090. 146. Molinski, T.F.; Dalisay, D.S.; Lievens, S.L.; Saludes, J.P. Drug development from marine natural products. Nat. Rev. Drug Discov. 2009, 8, 69–85. 147. Kohane, D.S.; Yieh, J.; Lu, N.T.; Langer, R.; Strichartz, G.R.; Berde, C.B. A re-examination of tetrodotoxin for prolonged duration local anesthesia. Anesthesiology 1998, 89, 119–131. 148. Barnet, C.S.; Tse, J.Y.; Kohane, D.S. Site 1 sodium channel blockers prolong the duration of sciatic nerve blockade from tricyclic antidepressants. Pain 2004, 110, 432–438.

Mar. Drugs 2010, 8 2211

149. Kohane, D.S.; Lu, N.T.; Gökgöl-Kline, A.C.; Shubina, M.; Kuang, Y.; Hall, S.; Strichartz, G.R.; Berde, C.B. The local anesthetic properties and toxicity of saxitonin homologues for rat sciatic nerve block in vivo. Reg. Anesth. Pain Med. 2000, 25, 52–59. 150. Epstein-Barash, H.; Shichor, I.; Kwon, A.H.; Hall, S.; Lawlor, M.W.; Langer, R.; Kohane, D.S. Prolonged duration local anesthesia with minimal toxicity. Proc. Natl. Acad. Sci. USA 2009, 106, 7125–7130. 151. Chorny, M.; Levy, R.J. Site-specific analgesia with sustained release liposomes. Proc. Natl. Acad. Sci. USA 2009, 106, 6891–6892. 152. Garrido, R.; Lagos, N.; Lattes, K.; Azolas, C.G.; Bocic, G.; Cuneo, A.; Chiong, H.; Jensen, C.; Henriquez, A.I.; Fernandez, C. The gonyautoxin 2/3 epimers reduces anal tone when injected in the anal sphincter of healthy adults. Biol. Res. 2004, 37, 395–403. 153. Garrido, R.; Lagos, N.; Lattes, K.; Abedrapo, M.; Bocic, G.; Cuneo, A.; Chiong, H.; Jensen, C.; Azolas, R.; Henriquez, A.; Garcia, C. Gonyautoxin: New treatment for healing acute and chronic anal fissures. Dis. Colon Rectum 2005, 48, 335–343. 154. Garrido, R.; Lagos, N.; Lagos, M.; Rodríguez-Navarro, A.J.; Garcia, C.; Truan, D.; Henriquez, A. Treatment of chronic anal fissure by gonyautoxin. Colorectal Dis. 2007, 9, 619–624. 155. Eisenhammer, S. The surgical correction of chronic internal anal (sphincteric) contracture. S. Afr. Med. J. 1951, 25, 486–489. 156. Khubchandani, I.T.; Reed, J.F. Sequelae of internal sphincterotomy for chronic fissure in ano. Br. J. Surg. 1989, 76, 431–434. 157. Hsu, T.-C.; MacKeigan, J. Surgical treatment of chronic anal fissure. Dis. Colon Rectum 1984, 27, 475–478. 158. Ezri, T.; Susmallian, S. Topical nifedipine vs. topical glyceryl trinitrate for treatment of chronic anal fissure. Dis. Colon Rectum 2003, 46, 805–808. 159. Maria, G.; Brisinda, G.; Bentivoglio, A.R.; Cassetta, E.; Gui, D.; Albanese, A. Botulinum toxin injections in the internal anal sphincter for the treatment of chronic anal fissure: Long-term results after two different dosage regimens. Ann. Surg. 1998, 228, 664–669. 160. Gorfine, S.R. Topical nitroglycerin therapy for anal fissures and ulcers. N. Engl. J. Med. 1995, 333, 1156–1157. 161. Lattes, K.; Venegas, P.; Lagos, N.; Lagos, M.; Pedraza, L.; Rodriguez-Navarro, A.J.; Garcia, C. Local infiltration of gonyautoxin is safe and effective in treatment of chronic tension-type headache. Neurol. Res. 2009, 31, 228–233. 162. Yan, T.; Fu, M.; Li, J.; Yu, R.; Zhou, M. Accumulation, transformation and elimination of PSP in Mytilus edulis. Oceanol. Limnol. Sin. 2001, 32, 421–427.

Samples Availability: Available from the authors.

© 2010 by the authors; licensee MDPI, Basel, Switzerland. This article is an Open Access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).

Appendix B: PST standards

135

136

Mix 1 50x dil 05/06/12 PSP120626_03 Late GTX 1,4 (1) ACQUITY FLR ChA Ex340,Em395 nm 3.35 Range: 10400 Neo- 3.84 SXT GTX 1,4 Late 6000.000 Neo- STX 1.71 EU x 10e4 Early 4000.000 Early GTX 1,4, Neo- STX 5.41 1.22 2000.000 2.14 0.72 0.49 0.000

0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00 4.25 4.50 4.75 5.00 5.25 5.50 5.75 6.00 PSP120626_04 (1) ACQUITY FLR ChA Ex340,Em395 nm 3.83 Range: 49355

GTX 2,3 40000.000 GTX 2,3 SXT 30000.000 1.70 EU x 10e4 dcGTX 2,3 20000.000 confirmation peak dc- SXT SXT 10000.000 1.49 3.35 5.41

0.000 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00 4.25 4.50 4.75 5.00 5.25 5.50 5.75 6.00 PSP120626_05 (1) ACQUITY FLR ChA Ex340,Em395 nm 2.25 Range: 4814 C 1,2

3000.000 dcNeo-STX

2000.000 2.91 EU x 10e4

1000.000 GTX 5 (B1) 3.82 0.72 1.02 1.20 1.381.47 1.71 1.931.99 0.11 0.31 0.59 0.95 2.53 2.62 3.34 4.62 0.000

Time 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00 4.25 4.50 4.75 5.00 5.25 5.50 5.75 6.00

Top chromatogram: PST standard MIX 1 (GTX 1,4 and Neo-STX), periodate oxidized. Middle chromatogram: PST standard MIX 2 (dcGTX 2,3; dcSTX, GTX 2,3; STX), periodate oxidized. Bottom chromatogram: PST standard MIX 3 (C1,2; dcNeo-STX; GTX5(B1)) periodate oxidized.

137

Mix 2 100x dil 05/06/12 Peroxide PSP120623_73 (1) ACQUITY FLR ChA Ex340,Em395 nm 2.93 Range: 52168 3.85 45000.000

40000.000 dcSTX dcSTX 5.40 35000.000 STX 30000.000

25000.000 dcGTX 2,3 1.46 20000.000 EU x 10e4 15000.000

10000.000

3.35 5000.000 1.66

0.28 0.000

-5000.000 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00 4.25 4.50 4.75 5.00 5.25 5.50 5.75 6.00 PSP120623_74 (1) ACQUITY FLR ChA Ex340,Em395 nm 4.64 Range: 25732

18000.002 2.21 GTX 5 (B1) 16000.001

14000.001 C1,2

12000.001

10000.001

8000.000

EU x 10e4 6000.000

4000.000

2000.000 1.21 0.03 0.68 0.000

-2000.000

-4000.000 Time 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00 4.25 4.50 4.75 5.00 5.25 5.50 5.75 6.00 Top chromatogram: PST standard Mix 2 (dcGTX 2,3; GTX 2,3; dcSTX; STX)

hydrogen peroxide oxidized

Bottom chromatogram: PST standard Mix 3 (C1,2; GTX 5 (B1))

hydrogen peroxide oxidized

138

APPENDIX C CTAB buffer for DNA extraction

139

140

CTAB buffer for DNA extraction

100 mM TRIS HCl 100 ml 1 M Tris HCl pH 8.0

20 mM EDTA 40 ml of 0.5 M EDTA

CTAB 20g of CTAB

0.2% beta mercaptoethanol

1.4 M NaCl 280 ml 5M NaCl

add H2O up to 100 ml

141

APPENDIX D Gse Media

142

143

Gse media

Seawater used for the media was filtered through a 0.22 µm filter (Millipore) followed by sterilization by autoclaving at 121 °C and 101.3 kPA for 15 minutes. Nutrient solutions were sterilized through 0.22 µm filter prior to addition.

Stock solutions

-1 Nitrate KNO3 100 g L MQ

-1 Phosphate K2HPO4 34.8g L MQ

Vitamin Biotin 2mL

Vitamin B12 1mL

Thiamine HCL 100 mg

-1 PII Metal Mix Na2EDTA 6g L MQ

-1 FeCl26H2O 0.29g L MQ

-1 H3BO3 6.85 g L MQ

-1 MnCl2 4H2O 0.86g L MQ

-1 ZnCl2 0.06 g L MQ

-1 CoCl2 6H2O 0.026 g L MQ

-1 Selenium H2 SeO3 1.29 Mg L MQ

Gse Nutrients Nitrate stock 4 mL

Phosphate stock 2 mL

Vitamin stock 2 mL

PII Metal Mix 12.5 mL

Selenium stock 2 mL

MilliQ water 100 mL

Gse media Gse nutrients 20 mL

Soil Extract 5 mL Seawater 1000 mL 144

APPENDIX E sxtA4 Sequences aligned

145

146

*....|....| ....|....| ....|....| ....|....| ....|....| 10 20 30 40 50 gDNA_cl01 TACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA gDNA_cl02 TACATAAACG CCCACGAGTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA gDNA_cl03 TACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA gDNA_cl04 TACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA gDNA_cl05 TACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA gDNA_cl06 TACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA gDNA_cl07 TACATAAACG CCCACGACTG CGCGCAGACG GCCGCCAGGC TCTGCAAGAA gDNA_cl08 TACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA gDNA_cl09 TACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA gDNA_cl10 TACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA gDNA_cl11 TACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA gDNA_cl12 TACATAAACC CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA gDNA_cl13 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA gDNA_cl14 TACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA gDNA_cl15 TACATAAACG CCCACGACTG CCTGCAGACG GCCGCCAGGC TCTGCAAGAA gDNA_cl16 TACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA gDNA_cl17 TACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA gDNA_cl18 TGCATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA gDNA_cl19 TGCATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA gDNA_cl20 TGCATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA cDNA_cl01 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA cDNA_cl02 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA cDNA_cl03 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA cDNA_cl04 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA cDNA_cl05 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA cDNA_cl06 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA cDNA_cl07 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA cDNA_cl08 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA cDNA_cl09 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA cDNA_cl10 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA cDNA_cl11 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA cDNA_cl12 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA cDNA_cl13 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA cDNA_cl14 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA cDNA_cl15 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA cDNA_cl16 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA cDNA_cl17 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA cDNA_cl18 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA cDNA_cl19 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA cDNA_cl20 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA

....|....| ....|....| ....|....| ....|....* ....|....| 60 70 80 90 100 gDNA_cl01 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAA CAGCCCGAGC gDNA_cl02 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAA CAGCCCAAGC gDNA_cl03 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAA CAGCCCGAGC gDNA_cl04 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAA CAGCCCGAGC gDNA_cl05 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAA CAGCCCGAGC gDNA_cl06 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAA CAGCCCGAGC gDNA_cl07 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGGCACGGAA CAGCCCGAGC gDNA_cl08 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAA CAGCCCGAGC gDNA_cl09 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAA CAGCCCGAGC

147

gDNA_cl10 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAA CAGCCCGAGC gDNA_cl11 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAA CAGCCCGAGC gDNA_cl12 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACCCGGAA CAGCCCGAGC gDNA_cl13 GGGCGCCACC GTCGTGCGCC TGAAGCACAA CGACACGGAG CAGCCTGAGC gDNA_cl14 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACCGAA CAGCCCGAGC gDNA_cl15 GGGCGCCCCC GTGGTGCGCC TGAAGCACAA CGACACCGAA CAGCCCGAGC gDNA_cl16 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACCGAA CAGCCCGAGC gDNA_cl17 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACCGAA CAGCCCGAGC gDNA_cl18 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAA CAGCCCGAGC gDNA_cl19 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAA CAGCCCGAGC gDNA_cl20 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAA CAGCCCGAGC cDNA_cl01 GGGCGTCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC cDNA_cl02 GGGCGTCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC cDNA_cl03 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC cDNA_cl04 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC cDNA_cl05 GGGCGTCACC GGGTTGCCCC TGAAGCACAA CGACACGGAG CAGCTCGAGC cDNA_cl06 GGGCGTCACC GGGTTGCCCC TGAAGCACAA CGACACGGAG CAGCTCGAGC cDNA_cl07 GGGCGTCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC cDNA_cl08 GGGCGTCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC cDNA_cl09 GGGCGTCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC cDNA_cl10 GGGCGTCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC cDNA_cl11 GGGCGTCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC cDNA_cl12 GGGCGTCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC cDNA_cl13 GGGCGTCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC cDNA_cl14 GGGCGTCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC cDNA_cl15 GGGCGTCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC cDNA_cl16 GGGCGTCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC cDNA_cl17 GGGCGTCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC cDNA_cl18 GGGCGTCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC cDNA_cl19 GGGCGTCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC cDNA_cl20 GGGCGTCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC

....|....| ....|....* ....|....| ....|....| ....|....| 160 170 180 190 200 gDNA_cl01 GGCGTGTACT CCACGGACGA AGAGCTCGCC GACTT-GCCC GCCATATGTG gDNA_cl02 GGCGTGTACT CCACGGACGA AGAGCTCGCC GACTT-GCCC GCCATATGTG gDNA_cl03 GGCGTGTACT CCACGGACGA AGAGCTCGCC GACTT-GCCC GCCATATGTG gDNA_cl04 GGCGTGTACT CCACGGACGA AGAGCTCGCC AACTT-GCCC GCCACATGTG gDNA_cl05 GGCGTGTACT CCACGGACGA AGAGCTCGCC GACTT-GCCC GCCATATGTG gDNA_cl06 GGCGTGTACT CCACGGACGA AGAGCTCGCC GACTT-GCCC GCCATATGTG gDNA_cl07 GGCGTGTACT CCACGGACGA AGAGCTCGCC GACTT-GCCC GCCATATGTG gDNA_cl08 GGCGTGTACT CCACGGACGA AGAGCTCGCC AACTT-GCCC GCCACATGTG gDNA_cl09 GGCGTGTACT CCACGGACGA AGAGCTCGCC GACTT-GCCC GCCATATGTG gDNA_cl10 GGCGTGTACT CCATAGACGA AGAGCTCGCC GACTT-GCCC GCCATATGTG gDNA_cl11 GGCGTGTACT CCACGGACGA AGAGCTCGCC GACTT-GCCC GCCATATGTG gDNA_cl12 GGCGTGTACT CCACGGACGA AGAGCTCGCC GACTT-GCCC GCCATATGTG gDNA_cl13 GGCGTTTACT CCACGGACGG AGAGCTCGCG GACTT-GCCC GCCATATGTG gDNA_cl14 GGCGTGTACT CCACGGACGA AGAGCTCGCC GACTTTGCCC ACCATATGTG gDNA_cl15 GGCGTGTACT CCACGGACGA AGAGCTCGCC GACTTTGCCC ACCATATGTG gDNA_cl16 GGCGTGTACT CCACGGACGA AGAGCTCGCC GACTTTGCCC ACCATATGTG gDNA_cl17 GGCGTGTACT CCACGGACGA AGAGCTCGCC GACTTTGCCC ACCATATGTG gDNA_cl18 GGCGTGTACT CCACGGACGA AGAGCTCGCC GACTT-GCCC GCCATATGTG gDNA_cl19 GGCGTGTACT CCACGGACGA AGAGCTCGCC GACTT-GCCC GCCATATGTG gDNA_cl20 GGCGTGTACT CCACGGACGA AGAGCTCGCC GACTT-GCCC GCCATATGTG

148

cDNA_cl01 GGCGTGTACT CCACAGACGG AGAGCTCGCC GACTT-GCCC GCCATATGTG cDNA_cl02 GGCGTGTACT CCACAGACGG AGAGCTCGCC GACTT-GCCC GCCATATGTG cDNA_cl03 GGCGTGTACT CCACAGACGG AGAGCTCGCC GACTT-GCCC GCCATATGTG cDNA_cl04 GGCGTGTACT CCACAGACGG AGAGCTCGCC GACTT-GCCC GCCATATGTG cDNA_cl05 GGCGTGTACT CCACAGACGG AGAGCTCGCC GACTT-GCCC GCCATATGTG cDNA_cl06 GGCGTGTACT CCACAGACGG AGAGCTCGCC GACTT-GCCC GCCATATGTG cDNA_cl07 GGCGTGTACT CCACAGACGG AGAGCTCGCC GACTT-GCCC GCCATATGTG cDNA_cl08 GGCGTGTACT CCACAGACGG AGAGCTCGCC GACTT-GCCC GCCATATGTG cDNA_cl09 GGCGTGTACT CCACAGACGG AGAGCTCGCC GACTT-GCCC GCCATATGTG cDNA_cl10 GGTGTGTACT CCACAGACGG AGAGCTCGCC GACTT-GCCC GCCATATGTG cDNA_cl11 GGTGTGTACT CCACAGACGG AGAGCTCGCC GACTT-GCCC GCCATATGTG cDNA_cl12 GGTGTGTACT CCACAGACGG AGAGCTCGCC GACTT-GCCC GCCATATGTG cDNA_cl13 GGTGTGTACT CCACAGACGG AGAGCTCGCC GACTT-GCCC GCCATATGTG cDNA_cl14 GGCGTGTACT CCACAGACGG AGAGCTCGCC GACTT-GCCC GCCATATGTG cDNA_cl15 GGCGTGTACT CCACAGACGG AGAGCTCGCC GACTT-GCCC GCCATATGTG cDNA_cl16 GGTGTGTACT CCACAGACGG AGAGCTCGCC GACTT-GCCC GCCATATGTG cDNA_cl17 GGTGTGTACT CCACAGACGG AGAGCTCGCC GACTT-GCCC GCCATATGTG cDNA_cl18 GGTGTGTACT CCACAGACGG AAAGGTCGCC GACTT-GCCC GCCATATGTG cDNA_cl19 GGTGTGTACT CCACAGACGG AAAGGTCGCC GACTT_GCCC GCCATATGTG cDNA_cl20 GGTGTGTACT CCACAGACGG AGAGCTCGCC GACTT-GCCC GCCATATGTG

....|....| ....|....| ....|....| ....↓....| ....|....| 210 220 230 240 250 gDNA_cl01 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TC-TAGACGA CTCGCATGGC gDNA_cl02 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TC-TAGACGA CTCGCATGGC gDNA_cl03 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TC-TAGACGA CTCGCATGGC gDNA_cl04 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TC-TAGACAA CTCGCATGGC gDNA_cl05 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTAGACGA CTCGCATGGC gDNA_cl06 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTAGACGA CTCGCATGGC gDNA_cl07 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTAGACGA CTCGCATGGC gDNA_cl08 CTTGTTTGAG GCCGCGCGGG GCCAGGATAC TCGTAGACAA CTCGCATGGC gDNA_cl09 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TCGCAGACGA CTCGCATGGC gDNA_cl10 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC ACGTAGACGA CTCGCGTGGC gDNA_cl11 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTAGACGA CTCGCATGGC gDNA_cl12 ATTGTTTGAG GCCGCGCCGG GCCAAGATAC TCGTAGACGA CTCGCATGGC gDNA_cl13 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTAGACGA CTCGCACGGC gDNA_cl14 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTAGACAA CTCGCATGGC gDNA_cl15 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTAGACAA CTCGCATGGC gDNA_cl16 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTAGACAA CTCGCATGGC gDNA_cl17 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTAGACAA CTCGCATGGC gDNA_cl18 CTCGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTAGACGA CTCGCATGGC gDNA_cl19 CTCGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTAGACGA CTCGCATGGC gDNA_cl20 CTCGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTAGACGA CTCGCATGGC cDNA_cl01 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTGGACGA CTCGCATGGC cDNA_cl02 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTGGACGA CTCGCATGGC cDNA_cl03 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTGGACGA CTCGCATGGC cDNA_cl04 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTGGACGA CTCGCATGGC cDNA_cl05 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTGGACGA CTCGCATGGC cDNA_cl06 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTGGACGA CTCGCATGGC cDNA_cl07 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTGGACGA CTCGCATGGC cDNA_cl08 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTGGACGA CTCGCATGGC cDNA_cl09 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTGGACGA CTCGCATGGC cDNA_cl10 CCTGTTTGAG GCCACGCGGG GCCAAGATAC TCGTGGACGA CTCGCATGGC cDNA_cl11 CCTGTTTGAG GCCCCGCGGG GCCAAGATAC TCGTGGACGA CTCGCATGGC

149

cDNA_cl12 CCTGTTTGAG GCCACGCGGG GCCAAGATAC TCGTGGACGA CTCGCATGGC cDNA_cl13 CCTGTTTGAG GCCACCCGGG GCCAAGATAC TCGTGGACGA CTCGCATGGC cDNA_cl14 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTGGACGA CTCGCATGGC cDNA_cl15 CTTGTTTGAG GCCGCGCGGG GCCAAGATAC TCGTGGACGA CTCGCATGGC cDNA_cl16 CCTGTTTGAG GCCACGCGGG GCCAAGATAC TCGTGGACGA CTCGCATGGC cDNA_cl17 CCTGTTTGAG GCCACGCGGG GCCAGGATAC TCGTGGACGA CTCGCATGGC cDNA_cl18 CCTGTTTGAG GCCACGCGGG GCCAGGATAC TCGTGGACGA CTCGCATGGC cDNA_cl19 CCTGTTTGAG GCCACGCGGG GCCAGGATAC TCGTGGACGA CTCGCATGGC cDNA_cl20 CCTGTTTGAG GCCACGCGGG GCCAAGATAC TCGTGGACGA CTCGCATGGC

....|....| ....|..↓.| ...↓*....| ....|....| ....|....| 260 270 280 290 300 gDNA_cl01 TGCGGCGTTC TTGGCCGCAA CCCCAACTCG GAGCAACTCC TCGGGTATGG gDNA_cl02 TGCGGCGTTC TTGGCCGCAA CCCCAACTCG GAGCAACCCC TCGGGTATGG gDNA_cl03 TGCGGCGTTC TTGGCCGCAA CCCCAACTCG GAGCAACCCC TCGGGTATGG gDNA_cl04 TGCGGCGTTC TTGGCCGCAA CCCCAACTCG GAGCAACCCC TCGGGTATGG gDNA_cl05 TGCGGCGTTC TTGGCCGCAA CCCCAACTCG GAGCAACCCC TCGGGTATGG gDNA_cl06 TGCGGCGTTC TTGGCCGCAA CCCCAACTCG GAGCAACCCC TCGGGTATGG gDNA_cl07 TGCGGCGTTC TTGGCCGCAA CCCCAACTCG GAGCAACCCC CCGGGTATGG gDNA_cl08 TGCGGCGTTC TTGGCCGCAA CCCCAACTCG GAGCAACCCC TCGGGTATGG gDNA_cl09 TGCGGCGTTC TTGGCCGCAA CCCCAACTCG GAGCAACCCC TCGGGTATGG gDNA_cl10 TGCGGCGTTC TTGGCCGCAA CCCCAACTCG GAGCAACCCC TCGGGTATGG gDNA_cl11 TGCGGCGTTC TTGGCCGCAA CCCCAACTCG GAGCAACCCC TCGGGTATGG gDNA_cl12 TGCGGCGTTC TTGGCCGCAA CCCCAACTCG GAGCAACCCC TCGGGTATGG gDNA_cl13 TGCGGCGTTC TTGGCCGCAA CCCCGACTCG GAGCAACCCC TCGGGTATGG gDNA_cl14 TGCGGCGTTC TTGGCCGCAA CCCCAACTCG GAGCAACCCC TCGGGTATGG gDNA_cl15 TGCGGCGTTC TTGGCCGCAA CCCCAACTCG GAGCAACCCC TCGGGTATGG gDNA_cl16 TGCGGCGTTC TTGGCCGCAA CCCCAACTCG GAGCAACCCC TCGGGTATGG gDNA_cl17 TGCGGCGTTC TTGGCCGCAA CCCCAACTCG GAGCAACCCC TCGGGTATGG gDNA_cl18 TGCGGCATTC TTGGCCGCAA CCCCAACTCG GATTAACCCC TTTGGTATGG gDNA_cl19 TGCGGCATTC TTGGCCGCAA CCCCAACTCG GAGCAACCCC TCGGGTATGG gDNA_cl20 TGCGGCATTC TTGGCCGCAA CCCCAACTCG GAGCAACCCC TCGGGTATGG cDNA_cl01 TGCGGCGTTC TTGGCCGAAA CCCAGACTCG GAGCAACCCC TCGGGTATGG cDNA_cl02 TGCGGCGTTC TTGGCCGAAA CCCAGACTCG GAGCAACCCC TCGGGTATGG cDNA_cl03 TGCGGCGTTC TTGGCCGAAA CCCAGACTCG GAGCAACCCC TCGGGTATGG cDNA_cl04 TGCGGCGTTC TTGGCCGAAA CCCAGACTCG GAGCAACCCC TCGGGTATGG cDNA_cl05 TGCGGCGTTC TTGGCCGAAA CCCAGACTCG GAGCAACCCC TCGGGTATGG cDNA_cl06 TGCGGCGTTC TTGGCCGAAA CCCAGACTCG GAGCAACCCC TCGGGTATGG cDNA_cl07 TGCGGCGTTC TTGGCCGAAA CCCAGACTCG GAGCAACCCC TCGGGTATGG cDNA_cl08 TGCGGCGTTC TTGGCCGAAA CCCAGACTCG GAGCAACCCC TCGGGTATGG cDNA_cl09 TGCGGCGTTC TTGGCCGAAA CCCAGACTCG GAGCAACCCC TCGGGTATGG cDNA_cl10 TGCGGCGTTC TTGGCCGAAA CCCAGACTCG GAGCAACCCC TCGGGTATGG cDNA_cl11 TGCGGCGTTC TTGGCCGAAA CCCAGACTCG GAGCAACCCC TCGGGTATGG cDNA_cl12 TGCGGCGTTC TTGGCCGAAA CCCAGACTCG GAGCAACCCC TCGGGTATGG cDNA_cl13 TGCGGCGTTC TTGGCCGAAA CCCAGACTCG GAGCAACCCC TCGGGTATGG cDNA_cl14 TGCGGCGTTC TTGGCCGAAA CCCAGACTCG GAGCAACCCC TCGGGTATGG cDNA_cl15 TGCGGCGTTC TTGGCCGAAA CCCAGACTCG GAGCAACCCC TCGGGTATGG cDNA_cl16 TGCGGCGTTC TTGGCCGAAA CCCAGACTCG GAGCAACCCC TCGGGTATGG cDNA_cl17 TGCGGCGTTC TTGGCCGAAA CCCAGACTCG GAGCAACCC- TCGGTTATG- cDNA_cl18 TGCGGCGTTC TTGGCCGAAA CCCAGACTCG GAGCAACCCC TCGGGTATGG cDNA_cl19 TGCGGCGTTC TTGGCCGAAA CCCAGACTCG GAGCAACCCC TCGGGTATGG cDNA_cl20 TGCGGCGTTC TTGGCCGAAA CCCAGACTCG GAGCAACCCC TCGGGTATGG

150

....|.↓..| ...*|....| ....|....| ....|....| ....|....| 310 320 330 340 350 gDNA_cl01 TGGCGGCGGC GTCATCGAGT ACCTCGGGCT GGACTACGCG GAGAACAACA gDNA_cl02 TGGCGGCGGC GTCATCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA gDNA_cl03 TGGCGGCGTC GTCATCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA gDNA_cl04 TGGCGGCGGC GTCATCGAGT ACCTCGGGCT GGACTACGCG GAGAACAACA gDNA_cl05 TGGCGGCGTC GTCATCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA gDNA_cl06 TGGCGGCGGC GTCATCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA gDNA_cl07 TGGCGGCGGC GTCATCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA gDNA_cl08 TGGCGGCGGC GTCATCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA gDNA_cl09 TGGCGGCGGC GTCATCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA gDNA_cl10 TGGCGGCGGC GTCATCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA gDNA_cl11 TGGCGGCGGC GTCATCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA gDNA_cl12 TGGCGGCGGC GTCATCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA gDNA_cl13 TGGCGGCGGC GTCGTCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA gDNA_cl14 TGGCGGCGGC GTCATCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA gDNA_cl15 TGGCGGCGGC GTCATCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA gDNA_cl16 TGGCGGCGGC GTCATCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA gDNA_cl17 TGGCGGCGGC GTCATCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA gDNA_cl18 TGGCGGCGGC GTCATCTAGT ACTTCGGGTT GGACTACGCG GAGAACAACA gDNA_cl19 TGGCGGCGGC GTCATCGAGT ACTTCGGGTT GGACTACGCG GAGAACAACA gDNA_cl20 TGGCGGCGGC GTCATCGAGT ACTTCGGGTT GGACTACGCG GAGAACAACA cDNA_cl01 TGGCGGTGGC GTCGTCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA cDNA_cl02 TGGCGGTGGC GTCGTCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA cDNA_cl03 TGGCGGTGGC GTCGTCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA cDNA_cl04 TGGCGGTGGC GTCGTCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA cDNA_cl05 TGGCGGTGGC GTCGTCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA cDNA_cl06 TGGCGGTGGC GTCGTCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA cDNA_cl07 TGGCGGTGGC GTCGTCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA cDNA_cl08 TGGCGGTGGC GTCGTCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA cDNA_cl09 TGGCGGTGGC GTCGTCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA cDNA_cl10 TGGCGGTGGC GTCGTCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA cDNA_cl11 TGGCGGTGGC GTCGTCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA cDNA_cl12 TGGCGGTGGC GTCGTCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA cDNA_cl13 TGGCGGTGGC GTCGTCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA cDNA_cl14 TGGCGGTGGC GTCGTCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA cDNA_cl15 TGGCGGTGGC GTCGTCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA cDNA_cl16 TGGCGGTGGC GTCGTCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA cDNA_cl17 TGGCGGTGGC GTCGTCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA cDNA_cl18 TGGCGGTGGC GTCGTCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA cDNA_cl19 TGGCGGTGGC GTCGTCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA cDNA_cl20 TGGCGGTGGC GTCGTCGAGT ACTTCGGGCT GGACTACGCG GAGAACAACA

....|....| ....|....| ....|....| ....*....| ....|....| 360 370 380 390 400 gDNA_cl01 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAATTCGCC CGGCGGATTC gDNA_cl02 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAATTCGCC CGGCGGATTC gDNA_cl03 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAATTCGCC CGGCGGATTC gDNA_cl04 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAATTCGCC CGGCGGATTC gDNA_cl05 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAATTCGCC CGGCGGATTC gDNA_cl06 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAATTCGCC CGGCGGATTC gDNA_cl07 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAATTCGCC CGGCGGATTC gDNA_cl08 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAATTCGCC CGGCGGATTC gDNA_cl09 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAATTCGCC CGGCGGATTC

151

gDNA_cl10 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAATTCGCC CGGCGGATTC gDNA_cl11 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAATTCGCC CGGCGGATTC gDNA_cl12 TCATCTACGC CGGGCAGTTG AGCAAGGCGT TCAATTCGCC CGGCGGATTC gDNA_cl13 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAACTCGCC CGGCGGATTC gDNA_cl14 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAATTCGCC CGGCGGATTC gDNA_cl15 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAATTCGCC CGGCGGATTC gDNA_cl16 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAATTCGCC CGGCGGATTC gDNA_cl17 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAATTCGCC CGGCGGATTC gDNA_cl18 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAATTCGCC CGGCGGATTC gDNA_cl19 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAATTCGCC CGGCGGATTC gDNA_cl20 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAATTCGCC CGGCGGATTC cDNA_cl01 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAACTCGCC CGGCGGATTC cDNA_cl02 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAACTCGCC CGGCGGATTC cDNA_cl03 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAACTCGCC CGGCGGATTC cDNA_cl04 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAACTCGCC CGGCGGATTC cDNA_cl05 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAACTCGCC CGGCGGATTC cDNA_cl06 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAACTCGCC CGGCGGATTC cDNA_cl07 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAACTCGCC CGGCGGATTC cDNA_cl08 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAACTCGCC CGGCGGATTC cDNA_cl09 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAACTCGCC CGGCGGATTC cDNA_cl10 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAACTCGCC CGGCGGATTC cDNA_cl11 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAACTCGCC CGGCGGATTC cDNA_cl12 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAACTCGCC CGGCGGATTC cDNA_cl13 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAACTCGCC CGGCGGATTC cDNA_cl14 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAACTCGCC CGGCGGATTC cDNA_cl15 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAACTCGCC CGGCGGATTC cDNA_cl16 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAACTCGCC CGGCGGATTC cDNA_cl17 TCATCTACGC CGGGCAGCTG AGCAGGGCGT TCAACTCGCC CGGCGGATTC cDNA_cl18 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAACTCGCC CGGCGGATTC cDNA_cl19 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAACTCGCC CGGCGGATTC cDNA_cl20 TCATCTACGC CGGGCAGCTG AGCAAGGCGT TCAACTCGCC CGGCGGATTC

...*|...*| ....|....| ....|....* ....|.*.*.| ....|....| 410 420 430 440 450 gDNA_cl01 GTCAGCTGTG CGCGCGAGAC CGACGAGAAT TTCGGCGTTC TGAACCTGGC gDNA_cl02 GTCAGCTGTG CGCGCGAGAC CGACGAGAAT TGCGGCGTTC TGAACTTGGC gDNA_cl03 GTCAGCTGTG CGCGCGAGAC CGACGAGAAT TTCGGCGTTC TGAACTTGGC gDNA_cl04 GTCAGCTGTG CGCGCGAGAC CGACGAGAAT TTCGGCGTTC TGAACTTGGC gDNA_cl05 GTCAGCTGTG CGCGCGAGAC CGACGAGAAT TTCGGCGTTC TGAACTTGTC gDNA_cl06 GTCAGTTGTG CGCGCGAGAC CGACGAGAAT TTCGGCGTTC TGAACTTGGC gDNA_cl07 GTCAGCTGTG CGCGCGAGAC CGACGCGAAT TTCGGCGTTC TGAACTTGGC gDNA_cl08 GTCAGCTGTG CGCGCGAGAC CGACGAGAAT TTCGGCGTTC TGAACTTGGC gDNA_cl09 GTCAGCTGTG CGCGCGAGAC CGACGAGAAT TTCGGCGTTC TGAACTTGGC gDNA_cl10 GTCAGCTGTG CGCGCGAGAC CGACGAGAAT TTCGGCGTTC TGAACTTGGC gDNA_cl11 GTCAGCTGTG CGCGCGAGAC CGACGAGAAT TTCGGCGTTC TGAACTTGGC gDNA_cl12 GTCACCTGTG CGCGCGAGAC CGACGAGAAT TTCGGCGTTC TGAACTTGGC gDNA_cl13 GTCGGCTGCG CGCGCGAGAC CGACGAGAAG TTCGGCATCC TGAACTTGGC gDNA_cl14 GTCAGCTGTG CGCGCGAGAC CGACGAGAAT TTCGGCGTTC TGAACTTGGC gDNA_cl15 GTCAGCTGTG CGCGCGAGAC CGACGAGAAT TTCGGCGTTC TGAACTTGGC gDNA_cl16 GTCAGCTGTG CGCGCGAGAC CGACGAGAAT TTCGGCGTTC TGAACTTGGC gDNA_cl17 GTCAGCTGTG CGCGCGAGAC CGACGAGAAT TTCGGCGTTC TGAACTTGGC gDNA_cl18 GTCAGCTGTG CGCGCGAGAC CGACGAGAAT TTCGGCGTTC TGAACTTGGC gDNA_cl19 GTCAGCTGTG CGCGCGAGAC CGACGAGAAT TTCGGCGTTC TGAACTTGGC gDNA_cl20 GTCAGCTGTG CGCGCGAGAC CGACGAGAAT TTCGGCGTTC TGAACTTGGC cDNA_cl01 GTCGGCTGCG CGCGCGAGAC CGACGAGAAG TTCGGCATCC TGAACTTGGC

152

cDNA_cl02 GTCGGCTGCG CGCGCGAGAC CGACGAGAAG TTCGGCATCC TGAACTTGGC cDNA_cl03 GTCGGCTGCG CGCGCGAGAC CGACGAGAAG TTCGGCATCC TGAACTTGGC cDNA_cl04 GTCGGCTGCG CGCGCGAGAC CGACGAGAAG TTCGGCATCC TGAACTTGGC cDNA_cl05 GTCGGCTGCG CGCCCGAGAC CGACGAGAAG TTCGGCATCC TGAACTTGGC cDNA_cl06 GTCGGCTGCG CGCCCGAGAC CGACGAGAAG TTCGGCATCC TGAACTTGGC cDNA_cl07 GTCGGCTGCG CGCGCGAGAC CGACGAGAAG TTCGGCATCC TGAACTTGGC cDNA_cl08 GTCGGCTGCG CGCGCGAGAC CGACGAGAAG TTCGGCATCC TGAACTTGGC cDNA_cl09 GTCGGCTGCG CGCGCGAGAC CGACGAGAAG TTCGGCATCC TGAACTTGGC cDNA_cl10 GTCGGCTGCG CGCGCGAGAC CGACGAGAAG TTCGGCATCC TGAACTTGGC cDNA_cl11 GTCGGCTGCG CGCGCGAGAC CGACGAGAAG TTCGGCATCC TGAACTTGGC cDNA_cl12 GTCGGCTGCG CGCGCGAGAC CGACGAGAAG TTCGGCATCC TGAACTTGGC cDNA_cl13 GTCGGCTGCG CGCGCGAGAC CGACGAGAAG TTCGGCATCC TGAACTTGGC cDNA_cl14 GTCGGCTGCG CGCGCGAGAC CGACGAGAAG TTCGGCATCC TGAACTTGGC cDNA_cl15 GTCGGCTGCG CGCGCGAGAC CGACGAGAAG TTCGGCATCC TGAACTTGGC cDNA_cl16 GTCGGCTGCG CGCGCGAGAC CGACGAGAAG TTCGGCATCC TGAACTTGGC cDNA_cl17 GTCGGCTGCG CGCGCGAGAC CGACGAGAAG TTCGGCATCC TGAACTTGGC cDNA_cl18 GTCGGCTGCG CGCGCGAGAC CGACGAGAAG TTCGGCATCC TGAACTTGGC cDNA_cl19 GTCGGCTGCG CGCGCGAGAC CGACGAGAAG TTCGGCATCC TGAACTTGGC cDNA_cl20 GTCGGCTGCG CGCGCGAGAC CGACGAGAAG TTCGGCATCC TGAACTTGGC

....|....| ....|....| ....|....| ....|....| ..*.|....| 460 470 480 490 500 gDNA_cl01 CAAGAACTCG AACACACTCG TGTTCACAGG GCCGATCTGT ACTTCCGGCC gDNA_cl02 CAAGAACTCG AACACACTCG TGTTCACAAG GCCGATCTGT ACTGCCGGCC gDNA_cl03 CAAGAACTCG AACACACTCG TGTTCACAGG GCCGATCTGT ATTGCCGGCC gDNA_cl04 CAAGAACTCG AACACACCCG TGTTCACAGG GCCGATCTGT ACTGCCGGCC gDNA_cl05 CCAGACATGG AACACAATAG TGTTCACCGG GGAAATGTAA TTTGCCGCCC gDNA_cl06 CAAGAACTCG AACACACTCG TGTTCACAGG GCCGATCTGT ACTGCCGGCC gDNA_cl07 CAAGAACTCG AACACACTCG TGTTCACAGG GCCGATCTGT ACTGCCGGCC gDNA_cl08 CAAGAACTCG AACACACCCG TGTTCACAGG GCCGATCTGT ACTGCCGGCC gDNA_cl09 CAAGAACTCG AACACACTCG TGTTCACAGG GCCGATCTGT ACTGCCGGCC gDNA_cl10 CAAGAACTCG AACACACTCG TGTTCACAGG GCCGATCTGT ACTGCCGGCC gDNA_cl11 CAAGAACTCG AACACACTCG TGTTCACAGG GCCGATCTGT ACTGCCGGCC gDNA_cl12 CAAGAACTCG AACACACTCG TGTTCACAGG GCCGATCTGT ACTGCCGGCC gDNA_cl13 GAAGAACTCG AACACGCTCG TGTTCACAGG GCCGATCTGT ACCGCGGGCC gDNA_cl14 CAAGAACTCG AACACACCCG TGTTCACAGG GCCGATCTGT ACTGCCGGCC gDNA_cl15 CAAGAACTCA AACACACCCG TGTTCACAGG GCCGATCTGT ACTGCCGGCC gDNA_cl16 CAAGAACTCG AACACACCCG TGTTCACAGG GCCGATCTGT ACTGCCGGCC gDNA_cl17 CAAGAACTCG AACACACCCG TGTTCACAGG GCCGATCTGT ACTGCCGGCC gDNA_cl18 CAAGAACTCG AACACACTCG TGTTCACAGG GCCGATCTGT ACTGCCGGCC gDNA_cl19 CAAGAACTCG AACACACTCG TGTTCACAGG GCCGATCTGT ACTGCCGGCC gDNA_cl20 CAAGAACTCG AACACACTCG TGTTCACAGG GCCGATCTGT ACTGCCGGCC cDNA_cl01 CAAGAACTCG AACACACTCG TGTTCACAGG GCCGATCTGT ACCGCCGGCC cDNA_cl02 CAAGAACTCG AACACACTCG TGTTCACAGG GCCGATCTGT ACCGCCGGCC cDNA_cl03 CAAGAACTCG AACACACTCG TGTTCACAGG GCCGATCTGT ACCGCCGGCC cDNA_cl04 CAAGAACTCG AACACACTCG TGTTCACAGG GCCGATCTGT ACCGCCGGCC cDNA_cl05 CAAGAACTCG AACACACTCC TGTTCACAGG GCCGATCTGT ACCGCCGGCC cDNA_cl06 CAAGAACTCG AACACACTCC TGTTCACAGG GCCGATCTGT ACCGCCGGCC cDNA_cl07 CAAGAACTCG AACACACTCG TGTTCACAGG GCCGATCTGT ACCGCCGGCC cDNA_cl08 CAAGAACTCG AACACACTCG TGTTCACAGG GCCGATCTGT ACCGCCGGCC cDNA_cl09 CAAGAACTCG AACACACTCG TGTTCACAGG GCCGATCTGT ACCGCCGGCC cDNA_cl10 CAAGAACTCG AACACGCTCG TGTTCACGGG GCCGATCTGC ACCGCCGGCC cDNA_cl11 CAAGAACTCG AACACGCTCG TGTTCACGGG GCCGATCTGC ACCGCCGGCC cDNA_cl12 CAGGAACTCG AACACTCTCG TGTTCACGGG GCCGATCTGC ACCGCCGGCC cDNA_cl13 CAAGAACTCG AACACGCTCG TGTTCACGGG GCCGATCTGC ACCGCCGGCC

153

cDNA_cl14 CCAGAACTCG AACACACTCG TGTTCACAGG GCCGATCTGT ACCGCCGGCC cDNA_cl15 CCAGAACTCG AACACACTCG TGTTCACAGG GCCGATCTGT ACCGCCGGCC cDNA_cl16 CAGGA-CTCG -ACACGCTCG TG-TCACGGG GCCGATCTGC ACGGCGG--C cDNA_cl17 CAAGAACTCG AACACGCTCG TGTTCACGGG -CCGATCCGC ACCGCCGGCC cDNA_cl18 CAAGAACTCG AACACGCTCG TGTTCACGGG GCCGATCCGC ACCGCCGGCC cDNA_cl19 CAAGAACTCG AACACGCTCG TGTTCACGGG GCCGATCCGC ACCGCCGGCC cDNA_cl20 CAGGAACTCG AACACTCTCG TGTTCACGGG GCCGATCTGC ACCGCCGGCC

....|....| ....|....| *.↓.|....| ....|....| ....|....| 510 520 530 540 550 gDNA_cl01 TATCGAGTGC GAAGACGACC TTCGACCTCA ACGCCGCCGA GGGGGACCTT gDNA_cl02 TGTCGAGTGC GAAGACGACC TTCGACCTCA ACGCCACCGA GGGGGACCTT gDNA_cl03 TGTCGAGTGC GAAGACGACC TTCGACCTCA ACGCAGCCGA GGGGGACCTT gDNA_cl04 TGTCGAGTGC GAAGACGACC TTCGACCTCA ACGCCGCCGA GGGGGACCTT gDNA_cl05 TATAGAGTGA GAAGGCGCCG TTGGACCTCA ATGCAGCCGA GCGGGGCGGC gDNA_cl06 TGTCGAGTGC GAAGACGACC TTCGACCTCA ACGCCGCCGA GGGGGACCTT gDNA_cl07 TGTCGAGTGC GAAGACGACC TTCGACCTCA ACGCCGCCGA GGGGGACCTT gDNA_cl08 TGTCGAGTGC GAAGACGACC TTCGACCTCA ACGCCGCCGA GGGGGACCTT gDNA_cl09 TGTCGAGTGC GAAGACGACC TTCGACCTCA ACGCCGCCGA GGGGGACCTT gDNA_cl10 TGTCGAGTGC GAAGACGACC TTCGACCTCA ACGCCGCCGA GGGGGACCTT gDNA_cl11 TGTCGAGTGC GAAGACGACC TTCGACCTCA ACGCCGCCGA GGGGGACCTT gDNA_cl12 TGTCGAGTGC GAAGACGACC TCCGACCTCA ACGCCGCCGA GGGGGACCTT gDNA_cl13 TGTCGAGTGC GAGGACGACC CTCGACCTCA ACGCCGCCGA GGGGGACCTT gDNA_cl14 TGTCGAGTGC GAAGACGACC TTCGACCTCA ACGCCGCCGA GGGGGACCTT gDNA_cl15 TGTCGAGTGC GAACACGACC TTCGACCTCA ACGCCGCCGA GGGGGACCTT gDNA_cl16 TGTCGAGTGC GAAGACGACC TTCGACCTCA ACGCCGCCGA GGGGGACCTT gDNA_cl17 TGTCGAGTGC GAAGACGACC TTCGACCTCA ACGCCGCCGA GGGGGACCTT gDNA_cl18 TGTCTAGTGC GAAGACGACC TTCGACCTCA ACGCCGCCGA GGGGGACCTT gDNA_cl19 TGTCGAGTGC GAAGACGACC TTCGACCTCA ACGCCGCCGA GGGGGACCTT gDNA_cl20 TGTCGAGTGC GAAGACGACC TTCGACCTCA ACGCCGCCGA GGGGGACCTT cDNA_cl01 TGTCGAGTGC AAAGACGACC CTGGACCTCA ACGCCGCCGA GGGGGACCTT cDNA_cl02 TGTCGAGTGC AAAGACGACC CTGGACCTCA ACGCCGCCGA GGGGGACCTT cDNA_cl03 TGTCGAGTGC AAAGACGACC CTGGACCTCA ACGCCGCCGA GGGGGACCTT cDNA_cl04 TGTCGAGTGC AAAGACGACC CTGGACCTCA ACGCCGCCGA GGGGGACCTT cDNA_cl05 TGTCGAGTGC AAAGACGACC CTGGACCTCA ACGCCGGCGA GGGGGATCTT cDNA_cl06 TGTCGAGTGC AAAGACGACC CTGGACCTCA ACGCCGGCGA GGGGGATCTT cDNA_cl07 TGTCGAGTGC AAAGACGACC CTGGACCTCA ACGCCGCCGA GGGGGACCTT cDNA_cl08 TGTCGAGTGC AAAGACGACC CTGGACCTCA ACGCCGCCGA GGGGGACCTT cDNA_cl09 TGTCGAGTGC AAAGACGACC CTGGACCTCA ACGCCGCCGA GGGGGACCTT cDNA_cl10 TGTCGAGCGC GAAGACGACC CTGGACCTCA ACGCCGCCGA GGGGGACCTT cDNA_cl11 TGTCGAGCGC GAAGACGACC CTGGACCTCA ACGCCGCCGA GGGGGACCTT cDNA_cl12 TGTCGAGCGC GAAGACGACC CTGGACCTCA ACGCCGCCGA GGGGGACCTT cDNA_cl13 TGTCGAGCGC AAAGACGACC CTGGACCTCA ACGCCGCCGA GGGGGACCTT cDNA_cl14 TGTCGAGTGC -AAGACGACC CTGGACCTCA -CGCCGCCGA GGGGGACCTT cDNA_cl15 TGTCGAGTGC -AAGACGACC CTGGACCTCA -CGCCGCCGA GGGGGACCTT cDNA_cl16 TGTCGAGCGC GAAA-CGACC CTGGACTTCA ACGCCGCCGA GGGGGAC--T cDNA_cl17 TGTCGAGCGC GAAGACGACC CTGGACCTCA ACGCCGCCGA GGGGGACCTT cDNA_cl18 TGTCGAGCGC GAAGACGACC CTGGACCTCA ACGCCGCCGA GGGGGACCTT cDNA_cl19 TGTCGAGCGC GAAGACGACC CTGGACCTCA ACGCCGCCGA GGGGGACCTT cDNA_cl20 TGTCGAGCGC GAAGACGACC CTGGACCTCA ACGCCGCCGA GGGGGACCTT

....|..↓.| ....|....| ....|....| ....|....| ....|....*

154

560 570 580 590 600 gDNA_cl01 CAGCGCAAGC GGCTTCTGGC GGCTACCCTC GAATTCTGCG AGGGGCTCAA gDNA_cl02 CAGCGCAAGC GGCTTCTGGC GGCTACCCTC GAATTCTGCG AGGGGCTCAA gDNA_cl03 CAGCGCAAGC GGCTTCTGGC GGCTACCCTC GAATTCTGCG AGGGGCTTAA gDNA_cl04 CAGCGCAAGC GGCTTCTGGC GGCTACCCTC GAATTCTGCG AGGGGCTCA- gDNA_cl05 CGCGGCAAGT GGCTTCTGGT CAACACCGGA GTATTCTGCG AGGGGCTTAA gDNA_cl06 CAGCGCAAGC GGCTTCTGGC GGCTACCCTC GAATTCTGCG AGGGGCTCAA gDNA_cl07 CAGCGCAAGC GGCTTCTGGC GGCTACCCTC GAATTCTGCG AGGGGCTCAA gDNA_cl08 CAGCGCAAGC GGCTTCTGGC GGCTACCCTC GAATTCTGCG AGGGGCTCA- gDNA_cl09 CAGCGCAAGC GGCTTCTGGG GGCTACCCTT CAATTCTGCC AGGGGCTCAA gDNA_cl10 CAGCGCAAGC GGCTTCTGGC GGCTACCCTC GAATTCTGCG AGGGGCTCAA gDNA_cl11 CATCGCAAGC GGCTTCTGGC GGCTACCCTC GAATTCTGCG AGGGGCTCAA gDNA_cl12 CAGCGCAAGC GGCTTCTGGC GGCTACCCTC GAATTCTGCG AGGGGCTCAA gDNA_cl13 CAGCGCAAGC GGCTTCTGGA GGCGACCCTC GAGTTCTGCG AGGGGCTCAG gDNA_cl14 CAGCGCAAGC GGCTTCTGGC GGCTACCCTC GAATTCTGCG AGGGGCTCAA gDNA_cl15 CAGCGCAAGC GGCTTCTGGG GGCTACCCTC GAATTCTGCG AGGGGCTCAA gDNA_cl16 CAGCGCAAGC GGCTTCTGGC GGCTACCCTC GAATTCTGCG AGGGGCTCAA gDNA_cl17 CAGCGCAAGC GGCTTCTGGC GGCTACCCTC GAATTCTGCG AGGGGCTCAA gDNA_cl18 CAGCGCAAGC GGCTTCTGGC GGCTACCCTC GAATTCTGCG AGGGGCTCAA gDNA_cl19 CAGCGCAAGC GGCTTCTGGC GGCTACCCTC GAATTCTGCG AGGGGCTCAA gDNA_cl20 CAGCGCAAGC GGCTTCTGGC GGCTACCCTC GAATTCTGCG AGGGGCTCAA cDNA_cl01 CAGCGCAGGC GGCTCCTGGC GGCGACCCTC GAGTTCTGCG AGGGGCTCAG cDNA_cl02 CAGCGCAGGC GGCTCCTGGC GGCGACCCTC GAGTTCTGCG AGGGGCTCAG cDNA_cl03 CAGCGCAGGC GGCTCCTGGC GGCGACCCTC GAGTTCTGCG AGGGGCTCAG cDNA_cl04 CAGCGCAGGC GGCTCCTGGC GGCGACCCTC GAGTTCTGCG AGGGGCTCAG cDNA_cl05 CAGCGCAGGC GGGTCCTGGG GGCGACCCTC GAATTCTGCG AGGGGCTCAC cDNA_cl06 CAGCGCAGGC GGGTCCTGGG GGCGACCCTC GAATTCTGCG AGGGGCTCAC cDNA_cl07 CAGCGCAGGC GGCTCCTGGC GGCGACCCTC GAGTTCTGCG AGGGGCTCAG cDNA_cl08 CAGCGCAGGC GGCTCCTGGC GGCGACCCTC GAGTTCTGCG AGGGGCTCAG cDNA_cl09 CAGCGCAGGC GGCTCCTGGC GGCGACCCTC GAGTTCTGCG AGGGGCTCAG cDNA_cl10 CAGCGCAGGC GGCTCCTGGC GGCGACCCTC GAGTTCTGCG AGGGGCTCAG cDNA_cl11 CAGCGCAGGC GGCTCCTGGC GGCGACCCTC GAGTTCTGCG AGGGGCTCAG cDNA_cl12 CAGCGCAGGC GGCTCCTGGC GGCGACCCTC GAGTTCTGCG AGGGGCTCAG cDNA_cl13 CAGCGCAGGC GGCTCCTGGC GGCGACCCTC GAGTTCTGCG AGGGGCTCAC cDNA_cl14 CAGCGCAGGC GGCTCCTGGC GGCGACCCTC GAG-TCTGCG A-GGGCTCAG cDNA_cl15 CAGCGCAGGC GGCTCCTGGC GGCGACCCTC GAG-TCTGCG A-GGGCTCAG cDNA_cl16 CAGCGCAGGC GGCTCCTGGC GGCGACCCTC GAGTTCTGCA A-GGGCTCAG cDNA_cl17 CAGCGCAGGC GGCTCCTGGC GGCGACCCTC GAGTTCTGCG AGGGGCTCAG cDNA_cl18 CAGCGCAGGC GGCTCCTGGC GGCGACCCTC GAGTTCTGCG AGGGGCTCAG cDNA_cl19 CAGCGCAGGC GGCTCCTGGC GGCGACCCTC GAGTTCTGCG AGGGGCTCAG cDNA_cl20 CAGCGCAGGC GGCTCCTGGC GGCGACCCTC GAGTTCTGCG AGGGGCTCAG

Alignment of the nucleotide acid sequences of sxtA4 of A. catenella ACCCO1 derived from mRNA and gDNA. The arrowhead ↓ indicates sequence positions at which all cDNA clones differ from the gDNA clones. A star * indicates positions at which 20 of the cDNA clones differ from 19 of the gDNA clones, the exception in the gDNA clone pool is clone 13 which is identical with the cDNA clones at these positions.

155

....|....| ....|....| ....|....| ....|....| ....|....| 10 20 30 40 50 JF343373.1 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343375.1 GACATCAACG CCCACGACTG TGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343378.1 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343379.1 GACATAAACG CGCACGACTG CGTGTAGACG GCCGCCAGGC TCTGCAAGAA JF343380.1 GACATCAACG CCCACGACTG TGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343381.1 -ACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343382.1 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343383.1 GGCATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343385.1 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343388.1 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343389.1 GACATAAACG CCCACGACTG CGTACAGACG GCCGCCAGGC TCTGCAAGAA JF343392.1 GACATCAACG CCCACGACTG TGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343384.1 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343386.1 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343393.1 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343394.1 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343390.1 GGCATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343390.1 GACATAAACG CCCACGACTG CGTGCAGACG GCAGCCAGGC TCTGCAAGAA JF343398.1 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343396.1 GACATAAACG CGCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343399.1 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343397.1 GACATAAACG CCCACGACTG TGTGCAGACG GCCGCCAGGC TCTGCAAGAA fundy gDNA GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343337.1 TACATAAACG CCCACGTCTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343345.1 TACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAC JF343340.1 TACAAAAATG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343353.1 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343339.1 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343341.1 TACATAAACG CCCACGACTG CGTGCAGACA GCCGCCAGGC TCTGCAAGAA JF343338.1 TACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343343.1 TACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAC JF343342.1 TACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA JF343339.1 GACATAAACG CCCACGACTG CGTGCAGACG GCCGCCAGGC TCTGCAAGAA

....|....| ....|....| ....|....| ....|....| ....|....| 60 70 80 90 100 JF343373.1 GGGCGCCACC GTGGTGCGCC TGAGGCACAA CGACGCGGAG CAGCTCGAGC JF343375.1 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC JF343378.1 GGGCGCCACC GTGGTGCGCC TGAGGCACAA CGACGCGGAG CAGCTCGAGC JF343379.1 GGGCGCCACC GTGGTGCGCC TGAGGCACAA CGACGCGGAG CAGCTCGAGC JF343380.1 GGGCACCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC JF343381.1 GGGCGCCACC GTGGTGCGCC TGAGGCACAA CGACGCGGAG CAGCTCGAGC JF343382.1 GGGCGCCACC GTGGTGCGCC TGAGGCACAA CGACGCGGAG CAGCTCGAGC JF343383.1 GGGCGCCACC GTGGTGCGCC TGAGGCACAA CGACGCGGAG CAGCTCGAGC JF343385.1 GGGCGCCACC GTGGTGCGCC TGAGGCACAA CGACGCGGAG CAGCTCGAGC JF343388.1 GGGCGCCACC GTGGTGTGCC TGAGGCACAA CGACGCGGAG CAGCTCGAGC JF343389.1 GAGCGCCTCC GTGGTGCGCC TGAGGCACAA CGACGCGGAG CAGCTCGAGC JF343392.1 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC JF343384.1 GGGCGCCACC GTGGTGCGCC TGAGGCACAA CGACGCGGAG CAGCTCGAGC JF343386.1 GGGCGCCACC GTGGTGCGCC TGAGGCACAA CGACGCGGAG CAGCTCGAGC JF343393.1 GGGCGCCACC GTGGTGCGCC TGAGGCACAA CGACGCGGAG CAGCTCGAGC JF343394.1 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACGCGGAG CAGCTCGAGC JF343390.1 GGGCGCCACC GTGGTGCGCC TGAGGCACAA CGACGCGGAG CAGCTCGAGC JF343390.1 GGGAGTCACC GTCGTGCGCC TGAAGCACAA CGACACGGAG CTGCTCGAGC JF343398.1 GGGCGCCACC GTGGTGCGCC TGAGGCACAA CGACGCGGAG CAGCTCGAGC JF343396.1 GGGCGCCACC GTGGTGCGCC TGAGGCACAA CGACGCGGAG CAGCTCGAGC JF343399.1 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACGCGGAG CAGCTCGAGC JF343397.1 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC 156

fundy gDNA GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACGCGGAG CAGCTCGAGC JF343337.1 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAA CAGCCCGAGC JF343345.1 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC JF343340.1 GGGAGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAA CAGCCCGAGC JF343353.1 GGGCGCCACC GTGGTGCGCC TGAGGCACAA CGACGCGGAG CAGCTCGAGC JF343339.1 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACGCGGAG CAGCTCGAGC JF343341.1 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC JF343338.1 GGGTGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAA CAGCCCGAGC JF343343.1 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAG CAGCTCGAGC JF343342.1 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACACGGAA CAGCCCGAGC JF343339.1 GGGCGCCACC GTGGTGCGCC TGAAGCACAA CGACGCGGAG CAGCTCGAGC

....|....| ....|....| ....|....| ....|....| ....|....| 110 120 130 140 150 JF343373.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343375.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343378.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343379.1 ACATGCTCTC GACGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343380.1 ACATGCTCTC GTAGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343381.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343382.1 ACATGCTCTC GTCGATCCCG CAGGGG-CCG ACATCACCTA CGTGTGCGAC JF343383.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343385.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343388.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343389.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343392.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343384.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343386.1 ACATGCTCTC GTCGGTCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343393.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343394.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343390.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343390.1 GCGTGCTCTC GTCGATCCCG GAGGGGGCCG ACATCACCTA CGCGTGCGAC JF343398.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343396.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343399.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343397.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC fundy gDNA ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343337.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343345.1 ACATGCTCTC GCCGATCCTG CAGGGGGGCG ACATCACCTA CATGTGCGAC JF343340.1 ACATACTCTC GTCGATCCCG CAGGGGGGCG ACATCACCTA CATGTGCGAC JF343353.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343339.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343341.1 ACATACTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343338.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC JF343343.1 ACATGCTCTC GCCGATCCTG CAGGGGGGCG ACATCACCTA CATGTGCGAC JF343342.1 ACATGCTCTC GTCGATCCCG CAGGGG-CCG ACATCACCTA CGTGTGCGAC JF343339.1 ACATGCTCTC GTCGATCCCG CAGGGGGCCG ACATCACCTA CGTGTGCGAC

....|....| ....|....| ....|....| ....|....| ....|....| 160 170 180 190 200 JF343373.1 GGCGTGTACT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343375.1 GGCGTGTACT CCACGGACGG AGAGCTCGCT GACTTGCCCG CCATATGTGC JF343378.1 GGCGTGTACT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343379.1 GGCGTGTACT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343380.1 GGCGTGTACT CCACGGACGG AGAGCTCGCT GACTTGCCCG CCATATGTGC JF343381.1 GGCGTGTACT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343382.1 GGCGTGTACT CCACGGACGG AGAGCTCGCC GACTAGCCCA CCATATGTGC JF343383.1 GG--TGTACT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343385.1 GGCGTGTATT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC 157

JF343388.1 GGCGTGTACT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343389.1 GGCGTGTACT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343392.1 GGCGTGTACT CCACGGACGG AGAGCTCGCT GACTTGCCCG CCATATGTGC JF343384.1 GGCGTGTACT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343386.1 GGCGTGTACT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343393.1 GGCGTGTACT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343394.1 GGCGTGTACT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343390.1 GG--TGTACT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343390.1 GGCGTCTACT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343398.1 GGCGTGTACT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343396.1 GGCGTGTACT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343399.1 GACGTGTACT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343397.1 GGCGTGTACT CTACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC fundy gDNA GGCGTGTACT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343337.1 G-----TACT CCACGGACGA AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343345.1 GGCGTGTACT CCACGGACGG AGAGCTCGCC AACTTGCCCG CCATATGTGC JF343340.1 GGCGTGTACT CCACGGACAG AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343353.1 GGCGTGTACT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343339.1 GGCGTGTACT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343341.1 GGCGTGTACT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343338.1 GGCGTGTACT CCACGGACGA AGAGCTCGCC GACTTGCCCG CCATATGTGC JF343343.1 GGCGTGTACT CCACGGACGG AGAGCTCGCC AACTTGCCCG CCATATGTGC JF343342.1 GGCGTGTACT CCACGGACGA AGAGCTCGCC GGCTTGCCCG CCATATGTGC JF343339.1 GGCGTGTACT CCACGGACGG AGAGCTCGCC GACTTGCCCG CCATATGTGC

....|....| ....|....| ....|....| ....|....| ....|....| 210 220 230 240 250 JF343373.1 TTGTCTGAGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343375.1 TTGTTTGAGG CCACGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343378.1 TTGTTTGAGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343379.1 TTGTTTGAGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343380.1 TTGTTTGAGG CCACGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343381.1 TTGTCTGAGG CCGCGCGGGG CCGAGATACT CGTAGACGAC TCGCATGGCT JF343382.1 TTGTCTGAGG CCGCGTGGGG CCAAGATACC CGTAGACGAC TCGCATGGCT JF343383.1 TTGTCTGAGG CCGCGCGGGG CCAAGGTACT CGTAGACGAC TCGCATGGCT JF343385.1 TTGTCTGAGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343388.1 TTGTCTGAGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343389.1 TTGTCTGTGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343392.1 TTGTTTGAGG CCACGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343384.1 TTGTCTGAGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343386.1 TTGTCTGAGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343393.1 TTGTCTGAGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGTT JF343394.1 TTGTTTGAGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343390.1 TTGTCTGAGG CCGCGCGGGG CCAAGGTACT CGTAGACGAC TCGCATGGCT JF343390.1 TTGTTTGAGG CCGCGCGGGG CCAAGATACT CGTGGACGAC TCGCATGGCT JF343398.1 TTGTCTGAGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343396.1 TTGTTTGAGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343399.1 TTGTTTGAGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343397.1 TTGTTTGAGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCACATGGCT fundy gDNA TTGTTTGAGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343337.1 TTGTTTGAGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343345.1 TTGTTTGAGG CCGCGTGGGG CCAACATACG CGTAGACGAC TCGCATGGTT JF343340.1 TTGTTTGAGG CCGCGTGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343353.1 TTGTTTGAGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343339.1 TTGTTTGAGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343341.1 TTGTTTGAGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343338.1 TTGTGTGAGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGTT JF343343.1 TTGTTTGAGG CCGCGTGGGG CCAACATACG CGTAGACGAC TCGCATGGTT JF343342.1 TTGTTTGAGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT JF343339.1 TTGTTTGAGG CCGCGCGGGG CCAAGATACT CGTAGACGAC TCGCATGGCT 158

....|....| ....|....| ....|....| ....|....| ....|....| 260 270 280 290 300 JF343373.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT JF343375.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AACAACCCTT CGGGTATGGT JF343378.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT JF343379.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT JF343380.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCTC CGGGTATGGT JF343381.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT JF343382.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT JF343383.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT JF343385.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT JF343388.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT JF343389.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT JF343392.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT JF343384.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT JF343386.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT JF343393.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT JF343394.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT JF343390.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT JF343390.1 GCGGCGTTCT TGGCCGCGAC CCCGACTCGG AGCAACCCCT CGGGTATGGT JF343398.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT JF343396.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT JF343399.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT JF343397.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT fundy gDNA GCGGCGTTCT TGACCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT JF343337.1 GCGGCGTTCT TGGCCGCAAC CCCAACTCGG AGCAACCCCT CGGGTATGGT JF343345.1 GCGGCGCTCT TGGCCGCAAC CCCGACTCGG AGCAACCCCT CGGGTATGGT JF343340.1 GCGGCTTTCT TGGCCGCACC CCCGACTCGG AGCAACCCCT CGGGTATGGT JF343353.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT JF343339.1 GCGGCGTTCT TGACCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT JF343341.1 GCGGCGTTCT TGGCCGCAAC CCCGACTCGG AGCAACCCCT CGGGTATGGT JF343338.1 GCGGCGTTCT TGGCCGCAAC CCCAACTCGG AGCAACCCCG CGGGTATGGT JF343343.1 GCGGCGCTCT TGGCCGCAAC CCCGACTCGG AGCAACCCCT CGGGTATGGT JF343342.1 GCGGCGTTCT TGGCCGCAAC CCCAACTCGG AGCAACCCCT CGGGTATGGT JF343339.1 GCGGCGTTCT TGACCGCAAC CCCGACTCGG AGCAACCCTT CGGGTATGGT

....|....| ....|....| ....|....| ....|....| ....|....| 310 320 330 340 350 JF343373.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343375.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343378.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343379.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343380.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343381.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343382.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343383.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343385.1 AGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343388.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343389.1 GGCGGCGGCG TCGTCGAGTA CTACGGGCTG GACTACGCGG AGAACAACAT JF343392.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343384.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343386.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343393.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343394.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343390.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343390.1 GGCGGCGGCG CCGTCGAGTA TTTCGGGCTG GGCTACGCGG AGAACAACAT JF343398.1 GGCGGCGGCG TCGTCGAGTA CTTCGRGCTG GACTACGCGG AGAACAACAT JF343396.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT 159

JF343399.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343397.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT fundy gDNA GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343337.1 GGCGGCGGCG TCATCGAGTA CTTCGGGCTG GACTACGCGG AGAACACCAT JF343345.1 GGCGGCGGCG GCGCCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343340.1 GGCGGCGTCG TCA---AGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343353.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343339.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343341.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343338.1 GGTGGCGGCG TCATGGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343343.1 GGCGGCGGCG GCGCCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343342.1 GGCGGCGGCG TCATCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT JF343339.1 GGCGGCGGCG TCGTCGAGTA CTTCGGGCTG GACTACGCGG AGAACAACAT

....|....| ....|....| ....|....| ....|....| ....|....| 360 370 380 390 400 JF343373.1 CATCTACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343375.1 CATCTATGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343378.1 CATCTACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343379.1 CATCTACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343380.1 CATCTATGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343381.1 CATCTACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343382.1 CATCTACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343383.1 CATCTACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343385.1 CATCTACGCC GGGCAGCCGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343388.1 CATCTACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343389.1 CATCTACGCC GGGCAGCTGA ACAAGGCGTT CAATTCGCCC GGCGGATTCG JF343392.1 CATCTATGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343384.1 CATCTACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343386.1 CATCTACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343393.1 CATCTACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343394.1 CATCTACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343390.1 CATCTACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343390.1 CAGCTACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGAATCG JF343398.1 CATCTACGCC GGGCAGCTGA GCAAGGCGTT CA------JF343396.1 CATCTGCGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343399.1 CATCTACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343397.1 CATCTACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG fundy gDNA CATCTACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343337.1 CATATACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343345.1 CATCTACGCC GGGCAGTTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343340.1 CAACTACGCC GGGCATCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343353.1 CATCTACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343339.1 CATCTACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343341.1 CATCTACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343338.1 CATCTATGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343343.1 CATCTACGCC GGGCAGTTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343342.1 CATCTACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG JF343339.1 CATCTACGCC GGGCAGCTGA GCAAGGCGTT CAATTCGCCC GGCGGATTCG

....|....| ....|....| ....|....| ....|....| ....|....| 410 420 430 440 450 JF343373.1 TCGGCTGTGC GCGCGAGACC GACGAGAAGT TCGGCATTCT GAACTTGGCC JF343375.1 TCGGCTGTGC GCGCGAGACC GACGAGAAGT TCGGCATTCT GAACTTGGCC JF343378.1 TCGGCTGTGC GCGCGAGACC GACGAGAAGT TCGGCATTCT GAACTTGGCC JF343379.1 TCGGCGGTGC GCGCGAGACC GACGAGAAGT TTGGCATTCT GAACTTGGCC JF343380.1 TCGGCTGTGC GCGCGAGACC GACGAGAAGT TCGGCATTCT GAACTTGGCC JF343381.1 TCGGCTGTGC GCGCGAGACC GACGAGAAGT TCGGCATTCT GAACTTGGCC JF343382.1 TCGGCTGTGC GCGCGAGACC GACGAGAAGT TCGGCATTCT GAACTTGGCC 160

JF343383.1 TTGGCTGTGC GCGCGAGACC GACGAGAAGT TCGGCATTCT GAGCTTGGCC JF343385.1 TCGGCTGTGC GCGCGAGACC GATGAGAAGT TCGGCATTCT GAACTTGGCC JF343388.1 TCGGCTGTGC GCGCGAGACC GACGAGAAGT TCGGCATTCT GAACTTGGCC JF343389.1 TCGGCTGTGC GCGCGAGACC GACGAGAAGT TCGGCATTCT GAACTTGGTC JF343392.1 TCGGCTGTGC GCGCGAGACC GACGAGAAGT TCGGCATTCT GAACTTGGCC JF343384.1 TCGGCTGTGC GCGCGAGACC GACGAGAAGT TCGGCATTCT GAACTTGGCC JF343386.1 TCGGCTGTGC GCGCGAGACC GACGAGAAGT TCGGCATTCT GAACTTGGCC JF343393.1 TCGGCTGTGC GCGCGAGACC GACGAGAAGT TCGACATTCT GAACTTGGCC JF343394.1 TCGGCTGTGC GCGCGAGACC GACGAGAAGT TCGGCATTCT GAACTTGGCC JF343390.1 TTGGCTGTGC GCGCGAGACC GACGAGAAGT TCGGCATTCT GAGCTTGGCC JF343390.1 TCGGTTGTGC GCGCGAGACC GACGAGAATT TCGGCGCTCT GAACTTGGCC JF343398.1 ------JF343396.1 TCGGCTGTGC GCGC------JF343399.1 TCGGCTGTGC GCGC------JF343397.1 TCGGCTGTGC GCGC------fundy gDNA TCGGCTGTGC GCGCGAGACC GACGAGAAGT TCGGCATTCT GAACTTGGCC JF343337.1 TCAGCTGTGC GCGCGAGACC GACGAGAATT TCGGCGTTAT GAACTTGGCC JF343345.1 TCTTTTGTGC GCGC-AGACC GACGCGAAGT TTGGCTTTCT GAACTTGGCC JF343340.1 TCGGCTGTGC GCGC-AGACC GACGATAATT TCGGCGTTCT GAACTTGGCC JF343353.1 TCGGCTGTGC GCGCGAGACC GACGAGAAGT TCGGCATTCT GAACTTGGCC JF343339.1 TCGGCTGTGC GCGCGAGACC GACGAGAAGT TCGGCATTCT GAACTTGGCC JF343341.1 TCGGCTGTGC GCGCGAGACC GACGAGAAGT TCGGCATTCT GAACTTGGCC JF343338.1 TCAGCTGTGC GCGC-AGACC GACGAGAATT GCGGCGTTCT GAACTTGGCC JF343343.1 TCTTTTGTGC GCGC-AGACC GACGCGAAGT TTGGCTTTCT GAACTTGGCC JF343342.1 TCAGCTGTGC GCGC-AGACC GACGAGAATT TCGGCGTTCT GAACTTGGCC JF343339.1 TCGGCTGTGC GCGCGAGACC GACGAGAAGT TCGGCATTCT GAACTTGGCC

....|....| ....|....| ....|....| ....|....| ....|....| 460 470 480 490 500 JF343373.1 AAGAACTCGA GCACACTCGT GTTCACAGGG CCGATCTGTA CTGCCGGCCT JF343375.1 AAGAACTCGA ACACACTCGT GTTCACAGGG CCGATCTGTA CTGCCGGCCT JF343378.1 AAGAACTCGA ACACACTCGT GTTCACAGGG CCGATCTGTA CTGCCGGCCT JF343379.1 AAGAACTCGA ACACACTCGT GTTCGCAGGG CCGATCTGTA CTGCCGGCCT JF343380.1 AAGAACTCGA ACACACTCGT GTTCACAGGG CCGATCTGTA CTGCCGGCCT JF343381.1 AAGAACTCGA ACACACTCGT GTTCACAGGG CCGATCTGTA CTGCCGGCCT JF343382.1 AAGAACTCGA ACACACTCGT GTTCACAGGG CCGATCTGTA CTGCCAGCCT JF343383.1 AAGAACTCGA ACACACTCGT GTTCACAGGG CCGATCTGTA CTGCCGGCCT JF343385.1 AAGAACTCGA ACACACTCGT GTTCACAGGG CCGATCTGTA CTGCCGGCCT JF343388.1 AAGAACTCGA ACACACTCGT GTTCACAGGG CCGATCTGTA CTGCCGGCCT JF343389.1 AAGAACTCGA ACACACTTGT GTTCACAGGG CCGATCTGTA CTGCCGGCCC JF343392.1 AAGAACTCGA ACACACTCGT GTTCACAGGG CCGATCTGTA CTGCCGGCCT JF343384.1 AAGAACTCGA ACACACTCGT GTTCACAGGG CCGATCTGTA CTGCCGGCCT JF343386.1 AAGAACTCAA ACACACTCGT GTTCACAGGG CCGATCTGTA CTGCCGGCCT JF343393.1 AAGAACTCGA ACACACTCGT GTTCACAGGG CCGATCTGTA CTGCCGGCCT JF343394.1 AAGAACTCAA ACACACTCGT GTTCACAGGG CCGATCTGTA CTGCCGGCCT JF343390.1 AAGAACTCGA ACACACTCGT GTTCACAGGG CCGATCTGTA CTGCCGGCCT JF343390.1 AAGAACTCGA GCACACTCGC GCTCACAGGG CCGATCTGTA CTGTCGGCCT JF343398.1 ------JF343396.1 ------JF343399.1 ------JF343397.1 ------fundy gDNA AAGAACTCAA ACACACTCGT GTTCACAGGG CCGATCTGTA CTGCCGGCCT JF343337.1 AAGAACTCGA ACACACTCGT GTTCACAGGG CCGATCTGTA CTGCCGGCCT JF343345.1 AAGAGCTCGA ACCCACTCGT GCTCACAGGG CCGATCTGTC CTGCCGGCCT JF343340.1 AAGAACTCGA CCACACTCGC GCTCACAGGG CCGATCTGTA CTGCCGGCCT JF343353.1 AAGAACTCAA ACACACTCGC GTTCACAGGG CCGATCTGTA CTGCCGGCCT JF343339.1 AAGAACTCAA ACACACTCGT GTTCACAGGG CCGATCTGTA CTGCCGGCCT JF343341.1 AAGAACTCAA ACACACTCGT GTTCACAGGG CCGATCTGTA CTGCCGGCCT JF343338.1 AAGAACTCGA ACACACTCGT GTTCACAGGG CCGATCTGTA TTGCCGGCCT JF343343.1 AAGAGCTCGA ACCCACTCGT GCTCACAGGG CCGATCTGTC CTGCCGGCCT 161

JF343342.1 AAGAACTCGA ACACACTCGT GCTCACAGGG CCGATCTGTA CTGCCGGCCT JF343339.1 AAGAACTCAA ACACACTCGT GTTCACAGGG CCGATCTGTA CTGCCGGCCT

....|....| ....|....| ....|....| ....|....| ....|....| 510 520 530 540 550 JF343373.1 GTCGAGTGCG ATGACGACCC TCGACCTCAA CGCCGCCGAG GGGGACCTTC JF343375.1 GTCGAGTGCG AAGACGACCC TCGACCTCAA CGCCGCCGAG GGGGACCTTC JF343378.1 GTCGAGTGCG AAGACGACCC TCGACCTCAA CGCCGCCGAG GGGGACCTTC JF343379.1 GTCGAGTGCG AAGACGACCC TCGACCTCAA CGCCGCCGAG GGGGACCTTC JF343380.1 GTCGAGTGCG AAGACGACCC TCGACCTCAA CGCCGCCGAG GGGGACCTTC JF343381.1 GTCGAGTGCG ATGACGACCC TCGACCTCAA CGCCGCCGAG GGG-ACCTTC JF343382.1 GTCGAGTGCG ATGACGACCC TCGACCTCAA CGCCGCCGAG GGGGACCTTC JF343383.1 GTCGAG------JF343385.1 GTCGAG------JF343388.1 GTCAAGTGCG ATGACGACCC TCGACCTCAA CGCCGCCGAG GGGGACCTTC JF343389.1 GTCGAGTGCG ATGACGACCC TCGACCTCAA CGCCGCCGAG GGGGACCCTC JF343392.1 GTCGAGTGCG AAGACGACCC TCGACCTCAA CGCCGCCGAG GGGGACCTTC JF343384.1 GTCGAGTA------JF343386.1 GTCGAG------JF343393.1 GTCGAGTGCG ATGACGACCC TCGACCTCAA CGCCGCCGAG GGGGACCTTC JF343394.1 GTCGAGTGCG ATGACGACCC TCGACCTCAA CGCCGCCGAG GGGGACCTTC JF343390.1 GTCGAG------JF343390.1 GTCGAGTGCG AAGACGACCT TCGACCTCAA CGCCGTCGAG GGGGACTTTC JF343398.1 ------JF343396.1 ------JF343399.1 ------JF343397.1 ------fundy gDNA GTCGAGTGCG ATGACGACCC TCGACCTCAA CGCCGCCGAG GGGGACCTTC JF343337.1 GTCGAGTGCG AAGACGACCT TCGACCTCAA CGCCGCCGAG GGGGACCTTC JF343345.1 GTCGAGTGCG AAGACGACCT TCGACCTCAA CGCCGCCGAG GGGGACCTTC JF343340.1 GTAGAGTGCG AAGACGACCT TCGACCTCAA CGCCGCCGAG GGGGACCTTC JF343353.1 GTCGAGTGCG ATGACGACCC TCGACCTCAA CGCCGCCGAG GGGGACCTTC JF343339.1 GTCGAGTGCG ATGACGACCC TCGACCTCAA CGCCGCCGAG GGGGACCTTC JF343341.1 GTCGAGTGCG AAGACGACCT TCGACCTCAA CGCCGCCGAG GGGGACCTTC JF343338.1 GTCGAGTGCG AAGACGACCT TCGACCTCTA CGCCGCCGAG GGGGGCCTTC JF343343.1 GTCGAGTGCG AAGACGACCT TCGACCTCAA CGCCGCCGAG GGGGACCTTC JF343342.1 GTCGAGTGCG AAGACGACCT TCGACCTCAA CGCCGCCGAG GGGGACCTTC JF343339.1 GTCGAGTGCG ATGACGACCC TCGACCTCAA CGCCGCCGAG GGGGACCTTC

....|....| ....|....| ....|....| ....|....| ....|.. 560 570 580 590 JF343373.1 AGCGCAAGCG ACTTCTGGCG GCGACCCTCG AATTCTGTGA GGGGCTC JF343375.1 AGCGCAAGCG GCTTCTGGCG GCGACCCTCG AATTCTGCGA GGGGCTC JF343378.1 AGCGCAAGCG GCTTCTGGCG GCGACCCTCG AATTCTGCGA GGGGCTC JF343379.1 AGCGCAAGCG GCTTCTGGCG GCGACCCTCG AATTCTGCGA GGGGCTC JF343380.1 AGCGCAAGCG GCTTCTGGCG GCGACCCTCG AATTCTGCGA GGGGCTC JF343381.1 AGCGCAAGCG GCTTCTGGTG GCGACCCTCG AATTCTGTGA GGGGCTC JF343382.1 AGCGCAAGCG GCTTCTGGCG GCGACCCTCG AATTCTGTGA GGGGCTC JF343383.1 ------JF343385.1 ------JF343388.1 AGCGCAAGCG GCTTCTGGCG GCGACCCTCG AATTCTGTGA GGGGCTC JF343389.1 AGCGCAAGCG GCTTCTGGCG GCGACCCTCG AATTCTGTGA GGGGCTC JF343392.1 AGCGCAAGCG GCTTCTGGCG GCGACCCTCG AATTCTGCGA GGGGCTC JF343384.1 ------JF343386.1 ------JF343393.1 AGCGCAAGCG GCTTCTGGCG GCGACCCCCG AATTCTGTGA GGGGCTC JF343394.1 AGCGCAAGCG GCTTCTGGCG GCGACCCTCG AATTCTGCGA GGGGCTC JF343390.1 ------JF343390.1 AGCGCAAGCG GCTGTTGGCG ACTACCCTCG AATTCTGCGA GGGGCTC 162

JF343398.1 ------JF343396.1 ------JF343399.1 ------JF343397.1 ------fundy gDNA AGCGCAAGCG GCTTCTGGCG GCGACCCTCG AATTCTGCGA GGGGCTC JF343337.1 AGCGCAAGCG GCTTCTGGCG GCTACCCTCG AATTCTGCGA GGGGCTC JF343345.1 AGCGCAAGCG GCTTCTGGCG GCGACCCTCG AATTCTGCGA GGGGTTC JF343340.1 AGCGCAAGCG GCTTCTGGCG GCTACCCTCG AATTCTGCGA GGGGCTC JF343353.1 AGCGCAAGCG GCTTCTGGAG GCGGCCCTCG AATTCTGCGA GGGGCTC JF343339.1 AGCGCAAGCG GCTTCTGGCG GCGACCCTCG AATTCTGCGA GGGGCTC JF343341.1 AGCGCAAGCG GCTTCTGGCG GCGACCCTCG AATTCTGCGA GGGGCTC JF343338.1 AGCGCAAGCG GCTTCTGGCG GCTACCCTCG AATTCTGCGA GGGGCTC JF343343.1 AGCGCAAGCG GCTTCTGGCG GCGACCCTCG AATTCTGCGA GGGGTTC JF343342.1 AGCGCAAGCG GCTTCTGGCG GCGACCCTCG AATTCTGCGA GGGGCTC JF343339.1 AGCGCAAGCG GCTTCTGGCG GCGACCCTCG AATTCTGCGA GGGGCTC Alignment of the nucleotide acid sequences of sxtA4 of A.fundyense derived from mRNA and gDNA sequences originate from the study (Stücken et al 2011)

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References

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165

References

Abdo, N.Y., Overton, A.J., Garms, J., Parsons Jr, J.E., Loh, A., Field, S.A., 2006. Automatic re-authentication. US7080404 B2 Google Patents. Abe, I., Morita, H., 2010. Structure and function of the chalcone synthase superfamily of plant type III polyketide synthases. Natural Product Reports 27(6), 809-838. Adachi, M., Kanno, T., Okamoto, R., Itakura, S., Yamaguchi, M., Nishijima, T., 2003. Population structure of Alexandrium (Dinophyceae) cyst formation-promoting bacteria in Hiroshima Bay, Japan. Applied and Environmental Microbiology 69(11), 6560-6568. Aguilera-Belmonte, A., Inostroza, I., Franco, J.M., Riobó, P., Gómez, P.I., 2011. The growth, toxicity and genetic characterization of seven strains of Alexandrium catenella (Whedon and Kofoid) Balech 1985 (Dinophyceae) isolated during the 2009 summer outbreak in southern Chile. Harmful Algae. Ahmad, M., Lin, C., Cashmore, A.R., 1995. Mutations throughout an Arabidopsis blue light photoreceptor impair blue light responsive anthocyanin accumulation and inhibition of hypocotyl elongation. The Plant Journal 8(5), 653-658. Alavi, M., Miller, T., Erlandson, K., Schneider, R., Belas, R., 2001. Bacterial community associated with Pfiesteria like dinoflagellate cultures. Environmental Microbiology 3(6), 380-396. Alberto, F., 2009. MsatAllele_1. 0: an R package to visualize the binning of microsatellite alleles. Journal of Heredity 100(3), 394-397. Allen, J., Roberts, T.M., Loeblich, A.R., Klotz, L.C., 1975. Characterization of the DNA from the dinoflagellate Crypthecodinium cohnii and implications for nuclear organization. Cell 6(2), 161-169. Allgaier, M., Uphoff, H., Felske, A., Wagner-Döbler, I., 2003. Aerobic anoxygenic photosynthesis in Roseobacter clade bacteria from diverse marine habitats. Applied and Environmental Microbiology 69(9), 5051-5059. Amin, S.A., Green, D.H., Hart, M.C., Küpper, F.C., Sunda, W.G., Carrano, C.J., 2009. Photolysis of iron siderophore chelates promotes bacteria algal mutualism. Proceedings of the National Academy of Sciences 106(40), 17071-17076. Andersen, C., Jensen, J., Ørntoft, T., 2004. Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets. Cancer Research 64(15), 5245. Anderson, D., 1997. Bloom dynamics of toxic Alexandrium species in the northeastern US. Limnology and Oceanography, 1009-1022. Anderson, D., Glibert, P., Burkholder, J., 2002. Harmful algal blooms and eutrophication: nutrient sources, composition, and consequences. Estuaries and Coasts 25(4), 704-726. Anderson, D., Kulis, D., Qi, Y., Zheng, L., Lu, S., Lin, Y., 1996. Paralytic shellfish poisoning in southern China. Toxicon 34(5), 579-590. Anderson, D., Kulis, D., Sullivan, J., Hall, S., Lee, C., 1990a. Dynamics and physiology of saxitoxin production by the dinoflagellates Alexandrium spp. Marine Biology 104(3), 511-524. Anderson, D.M., Alpermann, T.J., Cembella, A.D., Collos, Y., Masseret, E., Montresor, M., 2011. The globally distributed genus Alexandrium: multifaceted roles in marine ecosystems and impacts on human health. Harmful Algae 14, 10-35. Anderson, D.M., Cheng, T.P.O., 1988. Intracellular localization of saxitoxins in the dinoflagellate Gonyaulax tamarensis. Journal of Phycology 24(1), 17-22. Anderson, D.M., Kulis, D.M., Sullivan, J.J., Hall, S., 1990b. Toxin composition variations in one isolate of the dinoflagellate Alexandrium fundyense. Toxicon 28(8), 885-893. Apel, K., 1979. Phytochrome Induced Appearance of mRNA Activity for the Apoprotein of

166

References

the Light Harvesting Chlorophyll a/b Protein of Barley (Hordeum vulgare). European Journal of Biochemistry 97(1), 183-188. Babinchak, J.A., Doucette, G.J., IOC, P., Reguera, B., 1997. Isolation and characterization of the bacterial flora associated with PSP- related dinoflagellate species. Instituto Espanol de Oceanografia, Centro Oceanografico de Vigo, Vigo(Espana). Bachvaroff, T.R., 2008. From Stop to Start: Tandem Gene Arrangement, Copy Number and Trans-Splicing Sites in the Dinoflagellate Amphidinium carterae. PLoS One 3(8), e2929. Baker, T., Doucette, G., Powell, C., Boyer, G., Plumley, F., 2003. GTX4 imposters: characterization of fluorescent compounds synthesized by Pseudomonas stutzeri SF/PS and Pseudomonas/Alteromonas PTB-1, symbionts of saxitoxin-producing Alexandrium spp. Toxicon 41(3), 339-347. Balech, E., 1985. The genus Alexandrium or Gonyaulax of the tamarensis group. In: Anderson D.M., White A.W., Baden, D.G. Toxic Dinoflagellates. Elsevier, New York, 33-38. Banko, G., Demain, A.L., Wolfe, S., 1987. -(L- -Aminoadipyl)-L-cysteinyl-D-valine synthetase (ACV synthetase): a multifunctional enzyme with broad substrate specificity for the synthesis of penicillin and cephalosporin precursors. Journal of the American Chemical Society 109(9), 2858-2860. Bell, W.H., Lang, J.M., Mitchell, R., 1974. Selective stimulation of marine bacteria by algal extracellular products. Limnology and Oceanography 19, 833-839. Benne, R., Van Den Burg, J., Brakenhoff, J.P.J., Sloof, P., Van Boom, J.H., Tromp, M.C., 1986. Major transcript of the frameshifted coxll gene from trypanosome mitochondria contains four nucleotides that are not encoded in the DNA. Cell 46(6), 819-826. Biebl, H., Allgaier, M., Lansdorf, H., Pukall, R., Tindall, B.J., Wagner-Döbler, I., 2005. Roseovarius mucosus sp. nov., a member of the Roseobacter clade with trace amounts of bacteriochlorophyll a. International Journal of Systematic and Evolutionary Microbiology 55(6), 2377-2383. Biegala, I.C., Kennaway, G., Alverca, E., Lennon, J.F., Vaulot, D., Simon, N., 2002. Identification of bacteria associated with dinoflagellates (dinophyceae) Alexandrium spp. using Tyramide Signal Amplification Fluorescent in Situ Hybridization and Confocal Microscopy. Journal of Phycology 38(2), 404-411. Blackburn, S., Hallegraeff, G., Bolch, C., 1989. Vegetative reproduction and sexual life cycle of the toxic dinoflagellate Gymnodinium catenatum from Tasmania, Australia. Journal of Phycology 25(3), 577-590. Blackburn, S.I., Hallegraeff, G. M. and Bolch, C. J. , 1989. Vegetative reproduction and sexual life cycle of the toxic dinoflagellate Gymnodinium catenatum from Tasmania. J. Phycol(25), 577-590. Boczar, B.A., Beitler, M.K., Liston, J., Sullivan, J.J., Cattolico, R.A., 1988. Paralytic shellfish toxins in Protogonyaulax tamarensis and Protogonyaulax catenella in axenic culture. Plant Physiology 88(4), 1285. Boczar, B.A., Prezelin, B.B., Markwell, J.P., Thornber, J.P., 1980. A chlorophyll c-containing pigment-protein complex from the marine dinoflagellate, Glenodinium sp. FEBS Letters. Bogorad, L.1975. Phycobiliproteins complementary chromatic adaptation. Annual Review of Plant Physiology 26(1),123-128. Bolch, C.J.S., de Salas, M.F., 2007. A review of the molecular evidence for ballast water introduction of the toxic dinoflagellates Gymnodinium catenatum and the Alexandrium tamarensis complex to Australasia. Harmful Algae 6(4), 465-485. 167

References

Bolch, C.J.S., Subramanian, T.A., Green, D.H., 2011. The toxic dinoflagellate Gymnodinium catenatum (Dinophyceae) requires marine bacteria for growth. Journal of Phycology 47(5), 1009-1022. Boyer, G., Sullivan, J., Andersen, R., Harrison, P., Taylor, F., 1987. Effects of nutrient limitation on toxin production and composition in the marine dinoflagellate Protogonyaulax tamarensis. Marine Biology 96(1), 123-128. Boyer, S.K., Mullet, J.E., 1988. Sequence and transcript map of barley chloroplast psbA gene. Nucleic Acids Research 16(16), 8184. Brinkmeyer, R., Rappe, M., Gallacher, S., Medlin, L., 2000. Development of clade- (Roseobacter and Alteromonas) and taxon-specific oligonucleotide probes to study interactions between toxic dinoflagellates and their associated bacteria. European Journal of Phycology 35(4), 315-329. Brody, M., Emerson, R., 1959. The wavelength intensity of light on the proportion of pigments in Porphyridium cruentum. American Journal of Botany, 433-440. Brown, M.V., Schwalbach, M.S., Hewson, I., Fuhrman, J.A., 2005. Coupling 16S ITS rDNA clone libraries and automated ribosomal intergenic spacer analysis to show marine microbial diversity: development and application to a time series. Environmental Microbiology 7(9), 1466-1479. Brunelle, S.A., Hazard, E.S., Sotka, E.E., Dolah, F.M.V., 2007. Characterization of a dinoflagellate cryptochrome blue light receptor with a possible role in circadian control of the cell cycle. Journal of Phycology 43(3), 509-518. Buchan, A., Gonzalez, J.M., Moran, M.A., 2005. Overview of the marine Roseobacter lineage. Applied and Environmental Microbiology 71(10), 5665-5677. Burhans, W.C., Heintz, N.H., 2009. The cell cycle is a redox cycle: linking phase-specific targets to cell fate. Free Radical Biology and Medicine 47(9), 1282-1293. Bustin, S., 2002. Quantification of mRNA using real-time reverse transcription PCR (RT- PCR): trends and problems. Journal of Molecular Endocrinology 29(1), 23. Bustin, S., Benes, V., Nolan, T., Pfaffl, M., 2005. Quantitative real-time RT-PCR-a perspective. Journal of Molecular Endocrinology 34(3), 597. Caffrey, J.M., Cloern, J.E., Grenz, C., 1998. Changes in production and respiration during a spring phytoplankton bloom in San Francisco Bay, California, USA: implications for net ecosystem metabolism. Marine Ecology Progress Series 172, 1-12. Carmichael, W.W., 1994. The toxins of cyanobacteria. Scientific American 270(1), 64-70. Carneiro, R., dos Santos, M., Pacheco, A., Azevedo, S., 2009. Effects of light intensity and light quality on growth and circadian rhythm of saxitoxins production in Cylindrospermopsis raciborskii (Cyanobacteria). Journal of Plankton Research 31(5), 481. Cavanaugh, C.M., 1994. Microbial symbiosis: patterns of diversity in the marine environment. American Zoologist 34(1), 79-89. Cembella, A., Anderson, D., Hallegraeff, G., 1998. Physiological Ecology of Harmful Algal Blooms. Book, p. Cembella, A.D., 1998a. Ecophysiology and metabolism of paralytic shellfish toxins in marine microalgae. In Anderson, DM, AD Cembella, GM Hallegraeff (Eds.) Physiological Ecology of Harmful Algal Blooms, Springer-Verlag, Heidelberg, NATO-Advanced Study Institute Series 41, 381-403. Cembella, A.D., Sullivan, J.J., Boyer, G.L., Taylor, F.J.R., Andersen, R.J., 1987. Variation in paralytic shellfish toxin composition within the Protogonyaulax tamaronsis/catenella species complex; red tide dinoflagellates. Biochemical Systematics and Ecology 15(2), 171-186. Chang, F.H., Anderson, D.M., Kulis, D.M., Till, D.G., 1997. Toxin production of 168

References

Alexandrium minutum (Dinophyceae) from the Bay of Plenty, New Zealand. Toxicon 35(3), 393-409. Charlson, R.J., Lovelockl, J.E., Andreaei, M.O., Warren, S.G., 1987. Oceanic phytoplankton, atmospheric sulphur, cloud albedo and climate. Nature 326, 655-661. Chaves, I., Pokorny, R., Byrdin, M., Hoang, N., Ritz, T., Brettel, K., Essen, L.O., Van Der Horst, G.T.J., Batschauer, A., Ahmad, M., 2011. The cryptochromes: blue light photoreceptors in plants and animals. Annual Review of Plant Biology 62, 335-364. Chisholm, S., Brand, L., 1981. Persistence of cell division phasing in marine phytoplankton in continuous light after entrainment to light: dark cycles. Journal of Experimental Marine Biology and Ecology 51(2-3), 107-118. Cho, J.C., Giovannoni, S.J., 2004. Oceanicola granulosus gen. nov., sp. nov. and Oceanicola batsensis sp. nov., poly-hydroxybutyrate-producing marine bacteria in the order Rhodobacterales. International Journal of Systematic and Evolutionary Microbiology 54(4), 1129-1136. Cho, Y., Ogawa, M., Hirota, M., Oshima, Y., 2011. Effects of mitomycin C and colchicine on toxin production and cell cycle regulation in the dinoflagellate Alexandrium tamarense. Harmful Algae 10(3), 235-244. Cordova, J.L., Escudero, C., Bustamante, J., 2003. Bloom inside the bloom: intracellular bacteria multiplication within toxic dinoflagellates. Revista de Biologia Marina y Oceanografia 38(2), 57-67. Croft, M.T., Warren, M.J., Smith, A.G., 2006. Algae need their vitamins. Eukaryotic Cell 5(8), 1175-1183. Culman, S., Bukowski, R., Gauch, H., Cadillo-Quiroz, H., Buckley, D., 2009. T-REX: software for the processing and analysis of T-RFLP data. BMC Bioinformatics 10(1), 171. Curtis, T.P., Sloan, W.T., 2004. Prokaryotic diversity and its limits: microbial community structure in nature and implications for microbial ecology. Current Opinion in Microbiology 7(3), 221-226. Cutler, G., Marshall, L.A., Chin, N., Baribault, H., Kassner, P.D., 2007. Significant gene content variation characterizes the genomes of inbred mouse strains. Genome Research 17(12), 1743-1754. Danon, A., Mayfield, S.P., 1994. Light-regulated translation of chloroplast messenger RNAs through redox potential. Science 266(5191), 1717. Das, P., Lei, W., Aziz, S.S., Obbard, J.P., 2011. Enhanced algae growth in both phototrophic and mixotrophic culture under blue light. Bioresource Technology 102(4), 3883-3887. Demain, A.L., Aharonowitz, Y., Martin, J.F., 1983. Metabolic control of secondary biosynthetic pathways. Biotechnology Series[Biotechnol. Ser.]. 1983. den Boer, B.G.W., Murray, J.A.H., 2000. Triggering the cell cycle in plants. Trends in Cell Biology 10(6), 245-250. Devlin, P.F., Kay, S.A., 1999. Cryptochromes bringing the blues to circadian rhythms. Trends in Cell Biology 9(8), 295-298. Dopman, E.B., Hartl, D.L., 2007. A portrait of copy-number polymorphism in Drosophila melanogaster. Proceedings of the National Academy of Sciences 104(50), 19920. Doucette, G., 1995. Interactions between bacteria and harmful algae: a review. Natural Toxins 3(2), 65-74. Doucette, G., Kodama, M., Franca, S., Gallacher, S., 1998. Bacterial interactions with harmful algal bloom species: bloom ecology, toxigenesis, and cytology. Nato Asi Series Ecological Sciences 41, 619-648. Doucette, G., Trick, C., 1995. Characterization of bacteria associated with different isolates of Alexandrium tamarense. Harmful Marine Algal Blooms, 33-38. 169

References

Doyle, J., Doyle, J., 1987. A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochemical Bulletin 19(1), 11-15. Drews, G., Golecki, J., 2004. Structure, molecular organization, and biosynthetesis of membranes of purple bacteria. Anoxygenic Photosynthetic Bacteria, 231-157. Drummond, A., Ashton, B., Buxton, S., Cheung, M., Cooper, A., Duran, C., Field, M., 2011. Geneious v5. 4 [computer program]. Du Yoo, Y., Jeong, H.J., Kim, M.S., Kang, N.S., Song, J.Y., Shin, W., Kim, K.Y., Lee, K., 2009. Feeding by Phototrophic Red Tide Dinoflagellates on the Ubiquitous Marine Diatom Skeletonema costatum. Journal of Eukaryotic Microbiology 56(5), 413-420. Egan, E.S., Franklin, T.M., Hilderbrand-Chae, M.J., McNeil, G.P., Roberts, M.A., Schroeder, A.J., Zhang, X., Jackson, F.R., 1999. An extraretinally expressed insect cryptochrome with similarity to the blue light photoreceptors of mammals and plants. The Journal of Neuroscience 19(10), 3665. Engelmann, T.W., 1883. Farbe und Assimilation. III Weitere Folgerungen. Bot Z. Engelmann, T.W., 1884. Untersuchungen über die quantitativen Beziehungen zwischen Absorption des Lichtes und Assimilation in Pflanzenzellen. . Bot Z 44, 43-52. Erdner, D., Anderson, D., 2006. Global transcriptional profiling of the toxic dinoflagellate Alexandrium fundyense using Massively Parallel Signature Sequencing. BMC genomics 7(1), 88. Etheridge, S.M., Roesler, C.S., 2005. Effects of temperature, irradiance, and salinity on photosynthesis, growth rates, total toxicity, and toxin composition for Alexandrium fundyense isolates from the Gulf of Maine and Bay of Fundy. Deep Sea Research Part II: Topical Studies in Oceanography 52(19-21), 2491-2500. Fagan, T., Morse, D., Hastings, J.W., 1999. Circadian synthesis of a nuclear-encoded chloroplast glyceraldehyde-3-phosphate dehydrogenase in the dinoflagellate Gonyaulax polyedra is translationally controlled. Biochemistry 38(24), 7689-7695. Fandino, L.B., Riemann, L., Steward, G.F., Long, R.A., Azam, F., 2001. Variations in bacterial community structure during a dinoflagellate bloom analyzed by DGGE and 16S rDNA sequencing. Aquatic Microbial Ecology 23, 119. Fankhauser, C., Staiger, D., 2002. Photoreceptors in Arabidopsis thaliana: light perception, signal transduction and entrainment of the endogenous clock. Planta 216(1), 1-16. Fanning, K.A., 1989. Influence of atmospheric pollution on nutrient limitation in the ocean. Nature 339, 460-463. Faust, M.A., Sager, J.C., Meeson, B.W., 1982. Response of Prorocentrum Mariae- Lebouriae (Dinophyceae) to light of different spectral qualities and irradiances: growth and pigmentation. Journal of Phycology 18(3), 349-356. Fernandez, S., Natalia Zabalegui, Jesus Garcia-Fovillas, and Rosa Martinez, 2002. Real-Time RT-PCR Study of differential Expression of Two Genes in Alexandrium tamarense (Lebour) Balech, Cultured Under Varying Nitrate/Phosphate Ratios In: Harmful Algae (ed. By K.A. Steidinger, J.H. Landsberg, C.R. Tomas & G.A. Vargo), Florida Fish and Wildlife Conservation Commission, Florida Institute of Oceanography, and Intergovernmental Oceanographic Comission of UNESCO, St. Petersburg, Florida, pp. 261-263. Ferrier, M., Martin, J., Rooney Varga, J., 2002. Stimulation of Alexandrium fundyense growth by bacterial assemblages from the Bay of Fundy. Journal of Applied Microbiology 92(4), 706-716. Fisher, M.M., Triplett, E.W., 1999. Automated approach for ribosomal intergenic spacer analysis of microbial diversity and its application to freshwater bacterial communities. Applied and Environmental Microbiology 65(10), 4630-4636. Franca, S., Viegas, S., Mascarenchas, V., Pinto, L., Doucette, G., Lassus, P., Arzul, G., Erard- 170

References

Le Denn, E., 1995. Prokaryotes in association with a toxic Alexandrium lusitanicum in culture. In P. Lassus, G. Arzul, E. Erad-LeDenn, P. Gentien, and C. Marcaillou-Le Baut, Harmful marine algal blooms. Lavoisier, Paris, France., 45-51. Freeman, J.L., Perry, G.H., Feuk, L., Redon, R., McCarroll, S.A., Altshuler, D.M., Aburatani, H., Jones, K.W., Tyler-Smith, C., Hurles, M.E., 2006. Copy number variation: new insights in genome diversity. Genome Research 16(8), 949-961. Fuerst, J. A., Hawkins, J.A., Holmes, A., Sly, L.I. Moore, CJ., Stackebrandt, E., 1993 Porphyrobacter neustonensis gen. nov., sp. nov., an aerobic bacteriochlorophyll- synthesizing bacterium from fresh water. International Journal of Systematic Bacteriology 43 (1), 125-134. Fulco, V.K., Gayoso, A.M., Effects of light, temperature and salinity on the growth rate of Alexandrium tamarense from Patagonia (Argentina). Harmful Algae 2002, 391-392. Furio, E.F., Azanza, R.V., Fukuyo, Y., Matsuoka, K., 2012. Review of geographical distribution of dinoflagellate cysts in Southeast Asian coasts. The University of Tokyo. Gallacher, S., Flynn, K., Franco, J., Brueggemann, E., Hines, H., 1997. Evidence for production of paralytic shellfish toxins by bacteria associated with Alexandrium spp. (Dinophyta) in culture. Applied and Environmental Microbiology 63(1), 239-245. Gallacher, S., Smith, E., 1999a. Bacteria and paralytic shellfish toxins. Protist 150(3), 245- 255. Gautier, A., Michel-Salamin, L., Tosi-Couture, E., McDowall, A., Dubochet, J., 1986. Electron microscopy of the chromosomes of dinoflagellates in situ: confirmation of Bouligand's liquid crystal hypothesis. Journal of Ultrastructure and Molecular Structure Research 97(1), 10-30. Genenah, A.A., Shimizu, Y., 1981. Specific toxicity of paralytic shellfish poisons. Journal of Agricultural and Food Chemistry 29(6), 1289-1291. Geng, H., Belas, R., 2010 Molecular mechanisms underlying Roseobacter phytoplankton symbioses. Current Opinion in Biotechnology 21(3), 332-338. Geraci, J.R., Anderson, D.M., Timperi, R.J., St Aubin, D.J., Early, G.A., Prescott, J.H., Mayo, C.A., 1989. Humpback whales (Megaptera novaeangliae) fatally poisoned by dinoflagellate toxin. Canadian Journal of Fisheries and Aquatic Sciences 46(11), 1895- 1898. Glazer, A.N., 1981. Photosynthetic accessory proteins with bilin prosthetic groups. The Biochemistry of Plants 8, 51-96. Glibert, P.M., Anderson, D.M., Gentien, P., Graneli, E., Sellner, K.G., 2005. The global, complex phenomena of harmful algal blooms. Oceanography 18(2). Golden, S.S., 1995. Light-responsive gene expression in cyanobacteria. Journal of Bacteriology 177(7), 1651. Gonzalez, J.M., Kiene, R.P., Moran, M.A., 1999. Transformation of Sulfur Compounds by an Abundant Lineage of Marine Bacteria in the Subclass of the ClassProteobacteria. Applied and Environmental Microbiology 65(9), 3810-3819. Gottschal, J.C., Szewzyk, R., 1985. Growth of a facultative anaerobe under oxygen-limiting conditions in pure culture and in co-culture with a sulfate-reducing bacterium. FEMS Microbiology Letters 31(3), 159-170. Gray, M., 2003. Diversity and evolution of mitochondrial RNA editing systems. IUBMB Life 55(45), 227-233. Green, D.H., Llewellyn, L.E., Negri, A.P., Blackburn, S.I., Bolch, C.J.S., 2004. Phylogenetic and functional diversity of the cultivable bacterial community associated with the paralytic shellfish poisoning dinoflagellate Gymnodinium catenatum. FEMS Microbiology Ecology 47(3), 345-357. Guillard, R.R.L., Keller, M.D., 1984. Culturing dinoflagellates. In Dinoflagellates, Spector, 171

References

D.L. Academic Press, Orlando, 391-442. Guindon, S., Gascuel, O., 2003. A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Systematic Biology 52(5), 696-704. Hackett, J.D., Wisecaver, J.H., Brosnahan, M.L., Kulis, D.M., Anderson, D.M., Bhattacharya, D., Plumley, F.G., Erdner, D.L., 2012. Evolution of saxitoxin synthesis in cyanobacteria and dinoflagellates. Molecular Biology and Evolution. Hagstroem, Ã., Pommier, T., Rohwer, F., Simu, K., Stolte, W., Svensson, D., Zweifel, U.L., 2002. Use of 16S ribosomal DNA for delineation of marine bacterioplankton species. Applied and Environmental Microbiology 68(7), 3628-3633. Hallegraeff, G., Bolch, C., Blackburn, S., Oshima, Y., 1991. Species of the toxigenic dinoflagellate genus Alexandrium in southeastern Australian waters. Botanica marina 34(6), 575-588. Hallegraeff, G., Steffensen, D., Wetherbee, R., 1988. Three estuarine Australian dinoflagellates that can produce paralytic shellfish toxins. Journal of Plankton Research 10(3), 533-541. Hallegraeff, G.M., 1993. A review of harmful algal blooms and their apparent global increase. Phycologia 32(2), 79-99. Hallegraeff, G.M., 1998. Transport of toxic dinoflagellates via ships' ballast water: bioeconomic risk assessment and efficacy of possible ballast water management strategies. Marine Ecology Progress Series 168(297-309), 10-53. Hamasaki, K., Horie, M., Tokimitsu, S., Toda, T., Taguchi, S., 2001. Variability in toxicity of the dinoflagellate Alexandrium tamarense isolated from Hiroshima Bay, western Japan, as a reflection of changing environmental conditions. Journal of Plankton Research 23(3), 271-278. Han, S.O., New, P., 1998. Variation in nitrogen fixing ability among natural isolates of Azospirillum. Microbial Ecology 36(2), 193-201. Hansen, T.A., Veldkamp, H., 1973. Rhodopseudomonas sulfidophila, nov. spec., a new species of the purple nonsulfur bacteria. Archives of Microbiology 92 (1), 45-58. Harlow, L., Koutoulis, A., Hallegraeff, G., 2006. A novel, simplified technique for preservation and rapid isolation of total RNA from the toxic dinoflagellate Alexandrium catenella (Dinophyceae). Phycologia 45(3), 311-318. Harlow, L., Negri, A., Hallegraeff, G., Koutoulis, A., 2007a. Sam, Sahh and Map gene expression during cell division and paralytic shellfish toxin production of Alexandrium catenella (Dinophyceae). Phycologia 46(6), 666-674. Hauschild, A., Nelson, C., Krotkov, G., 1962a. The effect of light quality on the products of photosynthesis in Chlorella vulgaris. Canadian Journal of Botany 40(1), 179-189. Heaney, S., Eppley, R., 1981. Light, temperature and nitrogen as interacting factors affecting diel vertical migrations of dinoflagellates in culture. Journal of Plankton Research 3(2), 331-344. Hegemann, P., 2008. Algal sensory photoreceptors. Annu. Rev. Plant Biol. 59, 167-189. Hess, J., Tolbert, N., 1967. Changes in Chlorophyll a/b Ratio and Products of 14 CO2 Fixation by Algae Grown in Blue or Red Light. Plant Physiology 42(8), 1123-1130. Higman, W.A., Stone, D.M., Lewis, J.M., 2001. Sequence comparisons of toxic and non-toxic Alexandrium tamarense (Dinophyceae) isolates from UK waters. Phycologia 40(3), 256- 262. Ho, A.Y.T., Hsieh, D.P.H., Qian, P.Y., 2006. Variations in paralytic shellfish toxin and homolog production in two strains of Alexandrium tamarense after antibiotic treatments. Aquatic Microbial Ecology 42(1), 41-53. Hoffmeister, M., Martin, W., 2003. Interspecific evolution: microbial symbiosis, endosymbiosis and gene transfer. Environmental Microbiology 5(8), 641-649. 172

References

Hold, G., Smith, E., Harry Birkbeck, T., Gallacher, S., 2001a. Comparison of paralytic shellfish toxin (PST) production by the dinoflagellates Alexandrium lusitanicum NEPCC 253 and Alexandrium tamarense NEPCC 407 in the presence and absence of bacteria. FEMS microbiology ecology 36(2 3), 223-234. Hold, G.L., Smith, E.A., Rappé, M.S., Maas, E.W., Moore, E.R.B., Stroempl, C., Stephen, J.R., Prosser, J.I., Birkbeck, T.H., Gallacher, S., 2001d. Characterisation of bacterial communities associated with toxic and non toxic dinoflagellates: Alexandrium spp. and Scrippsiella trochoidea. FEMS Microbiology Ecology 37(2), 161-173. Hosoi-Tanabe, S., Sako, Y., 2005. Species-Specific Detection and Quantification of Toxic Marine Dinoflagellates Alexandrium tamarense and A. catenella by Real-Time PCR Assay. Marine Biotechnology 7(5), 506-514. Hosoi-Tanabe, S., Tomishima, S., Nagai, S., Sako, Y., 2005. Identification of a gene induced in conjugation-promoted cells of toxic marine dinoflagellates Alexandrium tamarense and Alexandrium catenella using differential display analysis. FEMS Microbiology Letters 251(1), 161-168. Hou, Y., Zhang, H., Miranda, L., Lin, S., 2010. Serious overestimation in quantitative PCR by circular (supercoiled) plasmid standard: microalgal pcna as the model gene. PLoS One 5(3), e9545. Hsiao, Y.Y., Lin, C.H., Liu, J.K., Wong, T.Y., Kuo, J., 2010. Analysis of codon usage patterns in toxic dinoflagellate Alexandrium tamarense through Expressed Sequence Tag data. Comparative and Functional Genomics 2010. Huelsenbeck, J.P., Ronquist, F., 2001. MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics 17(8), 754-755. Huse, S.M., Huber, J.A., Morrison, H.G., Sogin, M.L., Welch, D.M., 2007. Accuracy and quality of massively parallel DNA pyrosequencing. Genome Biol 8(7), R143. Huse, S.M., Welch, D.M., Morrison, H.G., Sogin, M.L., 2010. Ironing out the wrinkles in the rare biosphere through improved OTU clustering. Environmental Microbiology 12(7), 1889-1898. Hwang, D.F., Lu, Y.H., 2000. Influence of environmental and nutritional factors on growth, toxicity, and toxin profile of dinoflagellate Alexandrium minutum. Toxicon 38(11), 1491-1503. Jacobson, D.M., Anderson, D.M., 1996. Widespread phagocytosis of ciliates and other protists by marine mixotrophic and heterotrophic thecate dinoflagellates Journal of Phycology 32(2), 279-285. Jasti, S., Sieracki, M.E., Poulton, N.J., Giewat, M.W., Rooney-Varga, J.N., 2005. Phylogenetic diversity and specificity of bacteria closely associated with Alexandrium spp. and other phytoplankton. Applied and Environmental Microbiology 71(7), 3483. Jeong, H.J., Yoo, Y., Park, J.Y., Song, J.Y., Kim, S.T., Lee, S.H., Kim, K.Y., Yih, W.H., 2005. Feeding by phototrophic red-tide dinoflagellates: five species newly revealed and six species previously known to be mixotrophic. Aquatic Microbial Ecology 40(2), 133- 150. John, U., Fensome, R.A., Medlin, L.K., 2003. The application of a molecular clock based on molecular sequences and the fossil record to explain biogeographic distributions within the Alexandrium tamarense a species complex (Dinophyceae). Molecular Biology and Evolution 20(7), 1015-1027. Johnsen, G., Prezelin, B.B., Jovine, R.V.M., 1997. Fluorescence excitation spectra and light utilization in two red tide dinoflagllates. Limnology and Oceanography, 1166-1177. Johnsen, G., Sakshaug, E., 1993. Bio-optical characteristics and photoadaptative responses in the toxic and bloom forming dinoflagellates Gyrodinium aureolum, Gymnodinium galatheanum and two strains of Prorocentrum minimum. Journal of Phycology 29(5), 173

References

627-642. Johnsen, G., Sakshaug, E., Vernet, M., 1992. Pigment composition, spectral characterization and photosynthetic parameters in Chrysochromulina polylepis. Marine ecology progress series. Oldendorf 83 (2), 241-249. Kaebernick, M., Neilan, B., Borner, T., Dittmann, E., 2000. Light and the transcriptional response of the microcystin biosynthesis gene cluster. Applied and Environmental Microbiology 66(8), 3387. Kao, C., Nishiyama, A., 1965. Actions of saxitoxin on peripheral neuromuscular systems. The Journal of Physiology 180(1), 50. Kataoka, H., 1975. Phototropism in Vaucheria geminata II. The mechanism of bending and branching. Plant and Cell Physiology 16(3), 439. Kellmann, R., Mihali, T.K., Jeon, Y.J., Pickford, R., Pomati, F., Neilan, B.A., 2008. Biosynthetic intermediate analysis and functional homology reveal a saxitoxin gene cluster in cyanobacteria. Applied and Environmental Microbiology 74(13), 4044-4053. Keshtacher-Liebso, E., Hadar, Y., Chen, Y., 1995. Oligotrophic Bacteria Enhance Algal Growth under Iron-Deficient Conditions. Applied and Environmental Microbiology 61(6), 2439-2441. Kiene, R.P., 1996. Production of methanethiol from dimethylsulfoniopropionate in marine surface waters. Marine Chemistry 54(1), 69-83. Kirk, J.T.O., 1994. Light and Photosynthesis in Aquatic Ecosystems, 3 ed. Cambridge University Press. Knoop, V., 2011. When you can not trust the DNA: RNA editing changes transcript sequences. Cellular and Molecular Life Sciences, 1-20. Kobiyama, A., N. Yoshida, S. Suzuki, K. Koike, and T.Ogata., 2005. Differences in expression patterns of photosynthetic genes in the dinoflagellate Alexandrium tamarens . Eur. J. Protistol. 41, 277-285. Kodama, M., Doucette, G., Green, D., 2006. Relationships between bacteria and harmful algae. In: Ecological Studies Graneli, E., Turner J.T. Ecology of Harmful Algae 189, 243-255. Kodama, M., Fukuyo, Y., Ogata, T., Igarashi, T., Kamiya, H., Matsuura, F., 1982. Comparison of toxicities of Protogonyaulax cells of various sizes. Bull. Japan. Soc. Sci. Fish 48, 567-571. Kodama, M., Ogata, T., Sato, S., 1988. Bacterial Production of Saxitoxin (Microbiology & Fermentation Industry). Agricultural and Biological Chemistry 52(4), 1075-1077. Kodama, M., Ogata T., Sakamoto, S., Sato S., Honda T., and Miwatani T., 1990 Production of paralytic shellfish toxins by a bacterium Moraxella sp. isolated from Protogonyaulax tamaresnsis. Toxicon 28(6), 707-714. Kogure, K., Simidu, U., Taga, N., 1981. Bacterial attachment to phytoplankton in sea water. Journal of Experimental Marine Biology and Ecology 56(2), 197-204. Kopp, M., Doucette, G., Kodama, M., Gerdts, G., Schütt, C., Medlin, L., 1997. Phylogenetic analysis of selected toxic and non toxic bacterial strains isolated from the toxic dinoflagellate Alexandrium tamarense. FEMS microbiology ecology 24(3), 251-257. Kotaki, Y., Oshima, Y., Yasumoto, T., 1985. Bacterial transformation of paralytic shellfish toxins in coral reef crabs and a marine snail. Bull. Jap. Soc. Sci. Fish./Nissuishi. 51(6), 1009-1013. Kotaki, Y., Tajiri, M., Oshima, Y., Yasumoto, T., 1983. Identification of a calcareous red alga as the primary source of paralytic shellfish toxins in coral reef crabs and gastropods. Bulletin of the Japanese Society of Scientific Fisheries 49(2), 283-286. Krikunova, M., Lokstein, H., Leupold, D., Hiller, R.G., Voigt, B., 2006. Pigment -pigment interactions in PCP of Amphidinium carterae investigated by nonlinear polarization 174

References

spectroscopy in the frequency domain. Biophysical Journal 90(1), 261-271. Lane, D.J., 1991. 16S/23S rRNA sequencing. In E. Stackebrandt and M. Goodfellow (ed.) Nucleic Acid: Techniques in Bacterial Systematics. John Wiley and Sons, Chichester, United Kingdom, 115–148. . Lawrence, J.F., Niedzwiadek, B., Menard, C., 2005. Quantitative determination of paralytic shellfish poisoning toxins in shellfish using prechromatographic oxidation and liquid chromatography with fluorescence detection: collaborative study. Journal of AOAC International 88(6), 1714-1732. Le, Q., Markovic, P., Hastings, J., Jovine, R., Morse, D., 1997. Structure and organization of the peridinin-chlorophyll a-binding protein gene in Gonyaulax polyedra. Molecular and General Genetics MGG 255(6), 595-604. Le, Q.H., Jovine, R., Markovic, P., Morse, D., 2001. Peridinin-chlorophyll a-protein is not implicated in the photosynthesis rhythm of the dinoflagellate Gonyaulax despite circadian regulation of its translation. Biological Rhythm Research 32(5), 579-594. Lee, F.W.F., Morse, D., Lo, S.C.L., 2009. Identification of Two Plastid Proteins in the Dinoflagellate Alexandrium affine That Are Substantially Down-Regulated by Nitrogen- Depletion. Journal of Proteome Research 8(11), 5080-5092. Lee, O.O., Wang, Y., Yang, J., Lafi, F.F., Al-Suwailem, A., Qian, P.Y., 2010. Pyrosequencing reveals highly diverse and species-specific microbial communities in sponges from the Red Sea. The ISME Journal 5(4), 650-664. Legrand, C., Carlsson, P., 1998. Uptake of high molecular weight dextran by the dinoflagellate Alexandrium catenella. Aquatic Microbial Ecology 16(1), 81-86. Lidie, K., Van Dolah, F., 2007. Spliced Leader RNA Mediated trans Splicing in a Dinoflagellate, Karenia brevis. Journal of Eukaryotic Microbiology 54(5), 427-435. Lidie, K.B., Ryan, J.C., Barbier, M., Dolah, F.M., 2005. Gene expression in Florida red tide dinoflagellate Karenia brevis: analysis of an expressed sequence tag library and development of DNA microarray. Marine Biotechnology 7(5), 481-493. Lilly, E., Kulis, D., Gentien, P., Anderson, D., 2002. Paralytic shellfish poisoning toxins in France linked to a human-introduced strain of Alexandrium catenella from the western Pacific: evidence from DNAand toxin analysis. Journal of Plankton Research 24(5), 443-452. Lilly, E.L., Halanych, K.M., Anderson, D.M., 2005. Phylogeny, biogeography, and species boundaries within the Alexandrium minutum group. Harmful Algae 4(6), 1004-1020. Lilly, E.L., Halanych, K.M., Anderson, D.M., 2007. Species boundaries and global biogeography of the Alexandrium tamarense complex (Dinophyceae) 1. Journal of Phycology 43(6), 1329-1338. Lim, P., Leaw, C., Kobiyama, A., Ogata, T., 2005. Growth and toxin production of tropical Alexandrium minutum Halim (Dinophyceae) under various nitrogen to phosphorus ratios. Journal of Applied Phycology 22(2), 203-210. Lim, P.T., Leaw, C.P., Sato, S., Thuoc, C.V., Kobiyama, A., Ogata, T., 2011. Effect of salinity on growth and toxin production of Alexandrium minutum isolated from a shrimp culture pond in northern Vietnam. Journal of Applied Phycology 23(5), 857-864. Lim, P.T., Leaw, C.P., Usup, G., Kobiyama, A., Koike, K., Ogata, T., 2006. Effects of light and temparature on growth, nitrate uptake, and toxin production of two tropical dinoflagellates: Alexandrium tamiyavanichii and Alexandrium minutum (dinophyceae). Journal of Phycology 42(4), 786-799. Lin, S., 2011. Genomic understanding of dinoflagellates. Research in Microbiology. Lin, S., Zhang, H., Spencer, D.F., Norman, J.E., Gray, M.W., 2002. Widespread and extensive editing of mitochondrial mRNAs in dinoflagellates. Journal of Molecular Biology 320(4), 727-740. 175

References

Lin, S., Zhang, H., Zhuang, Y., Tran, B., Gill, J., 2010. Spliced leader–based metatranscriptomic analyses lead to recognition of hidden genomic features in dinoflagellates. Proceedings of the National Academy of Sciences 107(46), 20033. Link, G., 2004. Redox regulation of photosynthetic genes. Regulation of Photosynthesis, 85- 107. Livolant, F., Bouligand, Y., 1978. New observations on the twisted arrangement of dinoflagellate chromosomes. Chromosoma 68(1), 21-44. Lu, Y., Chai, T., Hwang, D., 2000. Isolation of bacteria from toxic dinoflagellate Alexandrium minutum and their effects on algae toxicity. Journal of Natural Toxins 9(4), 409. Lüning, K., 1980. Critical levels of light and temperature regulating the gametogenesis of three Laminaria species (Phaeophyceae). Journal of Phycology 16(1), 1-15. Maas, E.W., Brooks, H.J.L., 2010 Is photosynthesis a requirement for paralytic shellfish toxin production in the dinoflagellate Alexandrium minutum algal–bacterial consortium? Journal of Applied Phycology 22(3), 293-296. Maas, E.W., Latter, R.M., Thiele, J., Waite, A.M., Brooks, H.J.L., 2007. Effect of multiple antibiotic treatments on a paralytic shellfish toxin-producing culture of the dinoflagellate Alexandrium minutum. Aquatic Microbial Ecology 48(3), 255-260. Macian, M., Arahal, D., Garay, E., Ludwig, W., Schleifer, K., Pujalte, M., 2005. Thalassobacter stenotrophicus gen. nov., sp. nov., a novel marine proteobacterium isolated from Mediterranean sea water. International Journal of Systematic and Evolutionary Microbiology 55(1), 105-110. MacIntyre, J.G., Cullen, J.J., Cembella, A.D., 1997. Vertical migration, nutrition and toxicity in the dinoflagellate Alexandrium tamarense. Marine Ecology Progress Series 148(1), 201-216. MacIsaac, J., 1978. Diel cycles of inorganic nitrogen uptake in a natural phytoplankton population dominated by Gonyaulax polyedra. Limnology and Oceanography, 1-9. MacKenzie, L., Berkett, N., 1997. Cell morphology and PSP•toxin profiles of Alexandrium minutum in the Marlborough Sounds, New Zealand. New Zealand Journal of Marine and Freshwater Research 31(3), 403-409. Maldonado, M.T., Price, N.M., 1999. Utilization of iron bound to strong organic ligands by plankton communities in the subarctic Pacific Ocean. Deep Sea Research Part II: Topical Studies in Oceanography 46(11-12), 2447-2473. Manter, D.K., Delgado, J.A., Holm, D.G., Stong, R.A., 2010. Pyrosequencing reveals a highly diverse and cultivar-specific bacterial endophyte community in potato roots. Microbial Ecology 60(1), 157-166. Maranda, L., Anderson, D.M., Shimizu, Y., 1985. Comparison of toxicity between populations of Gonyaulax tamarensis of eastern North American waters. Estuarine, Coastal and Shelf Science 21(3), 401-410. Margulis, L., 1991. Symbiogenesis and Symbionticism, In: Symbiosis as a source of evolutionary innovation: speciation and morphogenesis, Marguilis,L. Fester, R. The MIT Press. McGillicuddy, D.J., Anderson, D.M., Lynch, D.R., Townsend, D.W., 2005. Mechanisms regulating large-scale seasonal fluctuations in Alexandrium fundyense populations in the Gulf of Maine: results from a physical-biological model. Deep Sea Research Part II: Topical Studies in Oceanography 52(19-21), 2698-2714. Mihali, T., Kellmann, R., Neilan, B., 2009. Characterisation of the paralytic shellfish toxin biosynthesis gene clusters in Anabaena circinalis AWQC131C and Aphanizomenon sp. NH-5. BMC Biochemistry 10(1), 8. Mihali, T.K., Carmichael, W.W., Neilan, B.A., 2011. A putative gene cluster from a Lyngbya wollei bloom that encodes paralytic shellfish toxin biosynthesis. PLoS One 6(2), e14657. 176

References

Miller, T.R., 2005. Swimming for sulfur: analysis of the Roseobacter-dinoflagellate interaction. Dissertation. Mittag, M., Li, L., Hastings, J.W., 1998. The mRNA level of the circadian regulated Gonyaulax luciferase remains constant over the cycle. Chronobiology International 15(1), 93-98. Miyazono, A., Nagai, S., Kudo, I., Tanizawa, K., 2012. Viability of Alexandrium tamarense cysts in the sediment of Funka Bay, Hokkaido, Japan: Over a hundred year survival times for cysts. Harmful Algae. Möglich, A., Yang, X., Ayers, R.A., Moffat, K., 2010. Structure and function of plant photoreceptors. Annual Review of Plant Biology 61, 21-47. Montoya, N.G., Fulco, V.K., Carignan, M.O., Carreto, J.I., 2010. Toxin variability in cultured and natural populations of Alexandrium tamarense from southern South America- Evidences of diversity and environmental regulation. Toxicon 56(8), 1408-1418. Moran, M.A., Gonzalez, J.M., Kiene, R.P., 2003. Linking a bacterial taxon to sulfur cycling in the sea: studies of the marine Roseobacter group. Geomicrobiology Journal 20(4), 375- 388. Morey, J., Monroe, E., Kinney, A., Beal, M., Johnson, J., Hitchcock, G., Van Dolah, F., 2011. Transcriptomic response of the red tide dinoflagellate, Karenia brevis, to nitrogen and phosphorus depletion and addition. BMC Genomics 12(1), 346. Morse, D., Milos, P., Roux, E., Hastings, J., 1989. Circadian regulation of bioluminescence in Gonyaulax involves translational control. Proceedings of the National Academy of Sciences of the United States of America 86(1), 172. Moustafa, A., Evans, A.N., Kulis, D.M., Hackett, J.D., Erdner, D.L., Anderson, D.M., Bhattacharya, D., 2010. Transcriptome profiling of a toxic dinoflagellate reveals a gene- rich protist and a potential impact on gene expression due to bacterial presence. PLoS One 5(3), e9688. Moustafa, A., Loram, J., Hackett, J., Anderson, D., Plumley, F., Bhattacharya, D., 2009. Origin of saxitoxin biosynthetic genes in cyanobacteria. PLoS One 4(6), e5758. Murray, S., Wiese, M., Neilan, B., Orr, R.J.S., de Salas, M., Brett, S., Hallegraeff, G., 2011a. A reinvestigation of saxitoxin production and sxtA in the non-toxic Alexandrium tamarense Group V clade. Harmful Algae. Murray, S.A., Wiese, M., Stüken, A., Brett, S., Kellmann, R., Hallegraeff, G., Neilan, B.A., 2011. sxtA-Based Quantitative Molecular Assay To Identify Saxitoxin-Producing Harmful Algal Blooms in Marine Waters. Applied and Environmental Microbiology 77(19), 7050-7057. Nair, S., Miller, B., Barends, M., Jaidee, A., Patel, J., Mayxay, M., Newton, P., Nosten, F., Ferdig, M.T., Anderson, T.J.C., 2008. Adaptive copy number evolution in malaria parasites. PLoS Genetics 4(10), e1000243. Nakashima, K., Arakawa, O., Taniyama, S., Nonaka, M., Takatani, T., Yamamori, K., Fuchi, Y., Noguchi, T., 2004. Occurrence of saxitoxins as a major toxin in the ovary of a marine puffer Arothron firmamentum. Toxicon 43(2), 207-212. Nash, E.A., Nisbet, R.E.R., Barbrook, A.C., Howe, C.J., 2008. Dinoflagellates: a mitochondrial genome all at sea. Trends in Genetics 24(7), 328-335. Negri, A., Llewellyn, L., Doyle, J., Webster, N., Frampton, D., Blackburn, S., 2003. Paralytic shellfish toxins are restricted to few species among Australia's taxonomic diversity of cultured microalgae. Journal of Phycology 39(4), 663-667. Neilan, B.A., Jacobs, D., Blackall, L.L., Hawkins, P.R., Cox, P.T., Goodman, A.E., 1997. rRNA sequences and evolutionary relationships among toxic and nontoxic cyanobacteria of the genus Microcystis. International Journal of Systematic Bacteriology 47(3), 693-697. 177

References

Nicot, N., Hausman, J.F., Hoffmann, L., Evers, D., 2005. Housekeeping gene selection for real-time RT-PCR normalization in potato during biotic and abiotic stress. Journal of Experimental Botany 56(421), 2907. Nultsch, W., 1956. Studien iiber die Phototaxis der Diatomeen. Arch. Protistenk 101(1). Nygaard, K., Tobiesen, A., 1993. Bacterivory in algae: A survival strategy during nutrient limitation. Limnology and Oceanography 38(2), 273-279. Ochsenreiter, T., Cipriano, M., Hajduk, S.L., 2008. Alternative mRNA editing in trypanosomes is extensive and may contribute to mitochondrial protein diversity. PLoS One 3(2), e1566. Ochsenreiter, T., Hajduk, S.L., 2006. Alternative editing of cytochrome c oxidase III mRNA in trypanosome mitochondria generates protein diversity. EMBO Reports 7(11), 1128- 1133. Ogata, T., Ishimaru, T., Kodama, M., 1987. Effect of water temperature and light intensity on growth rate and toxicity change in Protogonyaulax tamarensis. Marine Biology 95(2), 217-220. Ogata, T., Kodama, M., Nomura, S., Kobayashi, M., Nozawa, T., Katoh, T., Mimuro, M., 1994. A novel peridinin--chlorophyll a protein (PCP) from the marine dinoflagellate Alexandrium cohorticula: A high pigment content and plural spectral forms of peridinin and chlorophyll a. FEBS Letters 356(2-3), 367-371. Okamoto, O.K., Robertson, D.L., Fagan, T.F., Hastings, J.W., Colepicolo, P., 2001. Different regulatory mechanisms modulate the expression of a dinoflagellate iron-superoxide dismutase. Journal of Biological Chemistry 276(23), 19989-19993. Oldenhof, H., Bisova, K., Van Den Ende, H., Zachleder, V., 2004. Effect of red and blue light on the timing of cyclin-dependent kinase activity and the timing of cell division in Chlamydomonas reinhardtii. Plant Physiology and Biochemistry 42(4), 341-348. Oshima, Y., 1989. Latest advances in HPLC analysis of paralytic shellfish toxins. Mycotoxins and Phycotoxins 88., 319-326. Oshima, Y., Blackburn, S., Hallegraeff, G., 1993. Comparative study on paralytic shellfish toxin profiles of the dinoflagellate Gymnodinium catenatum from three different countries. Marine Biology 116(3), 471-476. Oshima, Y., Buckley, L.J., Alam, M., Shimizu, Y., 1977. Heterogeneity of paralytic shellfish poisons. three new toxins from cultured Gonyaulax tamarensis cells, Mya arenaria and Saxidomus giganteus. Comparative Biochemistry and Physiology Part C: Comparative Pharmacology 57(1), 31-34. Pagan, J., Child, J., Scowcroft, W., Gibson, A., 1975. Nitrogen fixation by Rhizobium cultured on a defined medium. Palacios, L., Arahal, D.R., Reguera, B., Maran, I., 2006a. Hoeflea alexandrii sp. nov., isolated from the toxic dinoflagellate Alexandrium minutum AL1V. International Journal of Systematic and Evolutionary Microbiology 56(8), 1991-1995. Palacios, L., Reguera, B., Franco, J., Maran, I., 2006b. Phylogenetic diversity of bacteria associated with toxic and non-toxic strains of Alexandrium minutum. African Journal of Marine Science 28(2), 409-414. Panda, S., Hogenesch, J.B., Kay, S.A., 2002. Circadian rhythms from flies to human. Nature 417(6886), 329-335. Parkhill, J., Cembella, A., 1999a. Effects of salinity, light and inorganic nitrogen on growth and toxigenicity of the marine dinoflagellate Alexandrium tamarense from northeastern Canada. Journal of Plankton Research 21(5), 939. Parkhill, J.P., Cembella, A.D., 1999b. Effects of salinity, light and inorganic nitrogen on growth and toxigenicity of the marine dinoflagellate Alexandrium tamarense from northeastern Canada. Journal of plankton research 21(5), 939-955. 178

References

Persson, A., Smith, B.C., Alix, J.H., Senft-Batoh, C., Wikfors, G.H., 2012. Toxin content differs between life stages of Alexandrium fundyense (Dinophyceae). Harmful Algae. Pfaffl, M.W., 2001. A new mathematical model for relative quantification in real-time RT– PCR. Nucleic Acids Research 29(9), e45. Pfannschmidt, T., 2003. Chloroplast redox signals: how photosynthesis controls its own genes. Trends in Plant Science 8(1), 33-41. Pfannschmidt, T., Nilsson, A., Allen, J.F., 1999. Photosynthetic control of chloroplast gene expression. Nature 397(6720), 625-628. Posada, D., Crandall, K.A., 1998. Modeltest: testing the model of DNA substitution. Bioinformatics 14(9), 817-818. Prezelin, B.B., Alberte, R.S., 1978. Photosynthetic characteristics and organization of chlorophyll in marine dinoflagellates. Proceedings of the National Academy of Sciences 75(4), 1801-1804. Prezelin, B.B., Triplett, E.L., 1989. Molecular Biology of the Photoregulation of Photosynthetic Light-Harvesting Complexes in Marine Dinoflagellates. DTIC Document ADA209650. Ramette, A., 2009. Quantitative community fingerprinting methods for estimating the abundance of operational taxonomic units in natural microbial communities. Applied and Environmental Microbiology 75(8), 2495-2505. Rasmussen, R., 2001. Quantification on the LightCycler. Ravn, H., Anthoni, U., Christophersen, C., Nielsen, P.H., Oshima, Y., 1995. Standardized extraction method for paralytic shellfish toxins in phytoplankton. Journal of Applied Phycology 7(6), 589-594. Redmond, M.C., Valentine, D.L., Sessions, A.L., 2010. Identification of novel methane-, ethane-, and propane-oxidizing bacteria at marine hydrocarbon seeps by stable isotope probing. Applied and Environmental Microbiology 76(19), 6412-6422. Reynolds, C., 2006. Pelagic Ecology. Encyclopedia of Environmetrics. Reynolds, C.S., Walsby, A., 1975. Water blooms. Biological Reviews 50(4), 437-481. Ritchie, J.M., Rogart, R., 1977. The binding of saxitoxin and tetrodotoxin to excitable tissue. Ergebnisse der Physiologie, biologischen Chemie und experimentellen Pharmakologie 79(-1), 1-50. Ritchie, R.J., 2008. Universal chlorophyll equations for estimating chlorophylls a, b, c, and d and total chlorophylls in natural assemblages of photosynthetic organisms using acetone, methanol, or ethanol solvents. Photosynthetica 46(1), 115-126. Rizzo, P., 1987. Biochemistry of the dinoflagellate nucleus. The biology of dinoflagellates. Blackwell Scientific, 143–173. Rizzo, P.J., 1991. The enigma of the dinoflagellate chromosome. Journal of Eukaryotic Microbiology 38(3), 246-252. Robertson, A., Stirling, D., Robillot, C., Llewellyn, L., Negri, A., 2004. First report of saxitoxin in octopi. Toxicon 44(7), 765-771. Rocap, G., Larimer, F.W., Lamerdin, J., Malfatti, S., Chain, P., Ahlgren, N.A., Arellano, A., Coleman, M., Hauser, L., Hess, W.R., 2003. Genome divergence in two Prochlorococcus ecotypes reflects oceanic niche differentiation. Nature 424(6952), 1042-1047. Rochaix, J., 1992. Post-transcriptional steps in the expression of chloroplast genes. Annual Review of Cell Biology 8(1), 1-28. Rockwell, N.C., Su, Y.S., Lagarias, J.C., 2006. Phytochrome structure and signaling mechanisms. Annual Review of Plant Biology 57, 837. Rodriguez, M., Cho, J.W., Sauer, H.W., Rizzo, P.J., 1993. Evidence For the Presence of A Cdc2 Like Protein Kinase In the Dinoflagellate Crypthecodinium Cohnii. Journal of 179

References

Eukaryotic Microbiology 40(1), 91-96. Roenneberg, T., Deng, T.S., 1997. Photobiology of the Gonyaulax circadian system. I. Different phase response curves for red and blue light. Planta 202(4), 494-501. Roenneberg, T., Hastings, J., 1988. Two photoreceptors control the circadian clock of a unicellular alga. Naturwissenschaften 75(4), 206-207. Roenneberg, T., Merrow, M., 1998. Molecular circadian oscillators: an alternative hypothesis. Journal of Biological Rhythms 13(2), 167. Sancar, A., 2003. Structure and function of DNA photolyase and cryptochrome blue-light photoreceptors. Chemical Reviews 103(6), 2203-2238. Sapp, J., 1994. Evolution by association: a history of symbiosis. Oxford University Press, New York, USA. Sapp, M., Schwaderer, A.S., Wiltshire, K.H., Hoppe, H.G., Gerdts, G., Wichels, A., 2007. Species-specific bacterial communities in the phycosphere of microalgae? Microbial Ecology 53(4), 683-699. Sato, S., Kodama, M., Ogata, T., Saitanu, K., Furuya, M., Hirayama, K., Kakinuma, K., 1997. Saxitoxin as a toxic principle of a freshwater puffer, Tetraodon fangi, in Thailand. Toxicon 35(1), 137-140. Schantz, E.J., Lynch, J.M., Vayvada, G., Matsumoto, K., Rapoport, H., 1966. The Purification and Characterization of the Poison Produced by Gonyaulax catenella in Axenic Culture. Biochemistry 5(4), 1191-1195. Schloss, P.D., Westcott, S.L., Ryabin, T., Hall, J.R., Hartmann, M., Hollister, E.B., Lesniewski, R.A., Oakley, B.B., Parks, D.H., Robinson, C.J., 2009. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Applied and Environmental Microbiology 75(23), 7537-7541. Schmittgen, T., Zakrajsek, B., 2000. Effect of experimental treatment on housekeeping gene expression: validation by real-time, quantitative RT-PCR. Journal of Biochemical and Biophysical Methods 46(1-2), 69-81. Scholin, C.A., Anderson, D.M., Cembella, A.D., Hallegraeff, G.M., 1998. Morphological, genetic and biogeographic relationships of toxic dinoflagellates Alexandrium tamarense, A. catenella and A. fundyense. Nato Asi Series Ecological Sciences 41, 13-28. Scholin, C.A.a.A., D. M., 1994. Identification of group and strain specific genetic markers for globally distributed Alexandrium (Dinophyceae). RFLP analysis of SSU rRNA genes. Journal of Phycology 30(4), 744-754. Schwalbach, M.S., Fuhrman, J.A., 2005. Wide-ranging abundances of aerobic anoxygenic phototrophic bacteria in the world ocean revealed by epifluorescence microscopy and quantitative PCR. Limnology and Oceanography, 620-628. Shiba, T., 1991. Roseobacter litoralis gen. nov., sp. nov., and Roseobacter denitrificans sp. nov., Aerobic Pink-Pigmented Bacteria which Contain Bacteriochlorophyll a. Systematic and Applied Microbiology 14(2), 140-145. Shiba, T., Shioi, Y., Takamiya, K.I., Sutton, D.C., Wilkinson, C.R. 1991. Distribution and physiology of aerobic bacteria containing bacteriochlorophyll a on the east and west coasts of Australia. Applied and Environmental Microbiology 57(1), 295-300. Shiba, T., Simidu, U., Taga, N., 1979. Distribution of bacteria which contain bacteriochlorophyll a. Applied and Environmental Microbiology 38(1), 43-45. Shimizu, Y., 1979. Developments in the study of paralytic shellfish toxins, p. 321. Shimizu, Y., 1993. Microalgal metabolites. Chemical Reviews 93(5), 1685-1698. Shimizu, Y., 1996. Microalgal metabolites: a new perspective. Annual Reviews in Microbiology 50(1), 431-465. Shimizu, Y., Norte, M., Hori, A., Genenah, A., Kobayashi, M., 1984. Biosynthesis of 180

References

saxitoxin analogs: the unexpected pathway. Journal of the American Chemical Society 106(21), 6433-6434. Sidhu, A.B.S., Uhlemann, A.C., Valderramos, S.G., Valderramos, J.C., Krishna, S., Fidock, D.A., 2006. Decreasing pfmdr1 copy number in Plasmodium falciparum malaria heightens susceptibility to mefloquine, lumefantrine, halofantrine, quinine, and artemisinin. Journal of Infectious Diseases 194(4), 528-535. Silva, E., 1982. Relationship between dinoflagellates and intracellular bacteria. Marine Algae in Pharmaceutical Science 2, 269-288. Silva, E., 1990. Intracellular bacteria: the origin of dinoflagellate toxicity. Journal of Environmental Pathology, Toxicology and Oncology: Official Organ of the International Society for Environmental Toxicology and Cancer 10(3), 124. Silva, E.S., 1962. Some observations on marine dinoflaegllate cultures. III. Gonyaulax spinifera (Clap. and Lach.) Dies., Gonyaulax tamarensis Leb., and Peridinium trochoideum (Stein) Lemm. Notas Est. Inst. Bio. Bar. 26, 1-21. Simon, N., Biegala, I.C., Smith, E.A., Vaulot, D., 2002. Kinetics of attachment of potentially toxic bacteria to Alexandrium tamarense. Aquatic Microbial Ecology 28(3), 249-256. Siu, G.K.Y., Young, M.L.C., Chan, D.K.O., 1997. Environmental and nutritional factors which regulate population dynamics and toxin production in the dinoflagellate Alexandrium catenella. Hydrobiologia 352(1), 117-140. Slamovits, C.H., Keeling, P.J., 2008. Widespread recycling of processed cDNAs in dinoflagellates. Current Biology 18(13), R550-R552. Smayda, T.J., 1990. Novel and nuisance phytoplankton blooms in the sea: evidence for a global epidemic. In E. Graneli, B. Sundstrom, L. Edler and D. M. Anderson (eds.)Toxic Marine Phytoplankton, Elsevier, New York, 29–40. Smayda, T.J., Reynolds, C.S., 2001. Community assembly in marine phytoplankton: application of recent models to harmful dinoflagellate blooms. Journal of Plankton Research 23(5), 447-461. Smith, E.A., Mackintosh, F.H., Grant, F., Gallacher, S., 2002. Sodium channel blocking (SCB) activity and transformation of paralytic shellfish toxins (PST) by dinoflagellate- associated bacteria. Aquatic Microbial Ecology 29(1), 1-9. Soltani, A.A., Khavazi, K., Asadi-Rahmani, H., Omidvari, M., Abaszadeh Dahaji, P., Mirhoseyni, H., 2010. Plant Growth Promoting Characteristics in Some Flavobacterium spp. Isolated from Soils of Iran. Journal of Agricultural Science 2(4), p106. Somasegaran, P., Hoben, H.J., 1994. Handbook for rhizobia: methods in legume-Rhizobium technology. Springer-Verlag New York Inc. Sommer, H., Whedon, W., Kofoid, C., Stohler, R., 1937. Relation of paralytic shell-fish poison to certain plankton organisms of the genus Gonyaulax. Archives of Pathology 24(5), 537-559. Sousa, E.S.E., 1978. Endo Nuclear Bacteria in 2 Species of Dinoflagellates. Protistologica 14(2), 113-120. Spector, D., Vasconcelos, A., Triemer, R., 1981. DNA duplication and chromosome structure in the dinoflagellates. Protoplasma 105(3), 185-194. Stewart, J.E., 2011. Enhancement by Gonyautoxin V of the Iron (III) Reducing or Binding Activity, Produced by the Dinoflagellate, Alexandrium excavatum. Harmful Algae. Stiekema, W.J., Wimpee, C.F., Silverthorne, J., Tobin, E.M., 1983. Phytochrome control of the expression of two nuclear genes encoding chloroplast proteins in Lemna gibba L. G- 3. Plant Physiology 72(3), 717-724. Stolte, W., Garces, E., 2006. Ecological aspects of harmful algal in situ population growth rates. Ecology of Harmful Algae, 139-152. Stomp, M., Huisman, J., De Jongh, F., Veraart, A.J., Gerla, D., Rijkeboer, M., Ibelings, B.W., 181

References

Wollenzien, U.I.A., Stal, L.J., 2004. Adaptive divergence in pigment composition promotes phytoplankton biodiversity. Nature 432(7013), 104-107. Stüken, A., Orr, R.J.S., Kellmann, R., Murray, S.A., Neilan, B.A., Jakobsen, K.S., 2011. Discovery of Nuclear-Encoded Genes for the Neurotoxin Saxitoxin in Dinoflagellates. PloS One 6(5), e20096. Stüken, A., Russell J. S. Orr, Ralf Kellmann, Shauna A. Murray, Brett A. Neilan, Kjetill S. Jakobsen, 2011. Discovery of Nuclear-Encoded Genes for the Neurotoxin Saxitoxin in Dinoflagellates Su, Z., Sheets, M., Ishida, H., Li, F., Barry, W.H., 2004. Saxitoxin blocks L-type ICa. Journal of Pharmacology and Experimental Therapeutics 308(1), 324-329. Sullivan, J.J., Wekell, M.M., Kentala, L.L., 1985. Application of HPLC for the determination of PSP toxins in shellfish. Journal of Food Science 50(1), 26-29. Syrett, P., Morris, I., 1963. The inhibition of nitrate assimilation by ammonium in Chlorella. Biochimica et Biophysica Acta (BBA)-Specialized Section on Enzymological Subjects 67, 566-575. Syvanen, M., 1994. Horizontal gene transfer: evidence and possible consequences. Annual Review of Genetics 28(1), 237-261. Takahashi, F., Hishinuma, T., Kataoka, H., 2001. Blue light-induced branching in Vaucheria Requirement of nuclear accumulation in the irradiated region. Plant and Cell Physiology 42(3), 274. Takahashi, F., Yamagata, D., Ishikawa, M., Fukamatsu, Y., Ogura, Y., Kasahara, M., Kiyosue, T., Kikuyama, M., Wada, M., Kataoka, H., 2007. Aureochrome, a photoreceptor required for photomorphogenesis in stramenopiles. Proceedings of the National Academy of Sciences 104(49), 19625. Taroncher-Oldenburg, G., Anderson, D.M., 2000. Identification and characterization of three differentially expressed genes, encoding S-adenosylhomocysteine hydrolase, methionine aminopeptidase, and a histone-like protein, in the toxic dinoflagellate Alexandrium fundyense. Applied and Environmental Microbiology 66(5), 2105-2112. Taroncher-Oldenburg, G., Kulis, D., Anderson, D., 1997. Toxin variability during the cell cycle of the dinoflagellate Alexandrium fundyense. Limnology and Oceanography 42(5), 1178-1188. Taroncher-Oldenburg, G., Kulis, D., Anderson, D., 1999. Coupling of saxitoxin biosynthesis to the G1 phase of the cell cycle in the dinoflagellate Alexandrin fundyense: temperature and nutrient effects. Natural Toxins 7(5), 207-219. Taylor, F.J.R., Hoppenrath, M., Saldarriaga, J.F., 2008. Dinoflagellate diversity and distribution. Biodiversity and Conservation 17(2), 407-418. Thompson, J.D., Higgins, D.G., Gibson, T.J., 1994. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position- specific gap penalties and weight matrix choice. Nucleic Acids Research 22(22), 4673- 4680. Timmis, J.N., Ayliffe, M.A., Huang, C.Y., Martin, W., 2004. Endosymbiotic gene transfer: organelle genomes forge eukaryotic chromosomes. Nature Reviews Genetics 5(2), 123- 135. Tobin, E.M., Silverthorne, J., 1985. Light regulation of gene expression in higher plants. Annual Review of Plant Physiology 36(1), 569-593. Tortell, P.D., Rau, G.H., Morel, F.M.M., 2000. Inorganic carbon acquisition in coastal Pacific phytoplankton communities. Limnology and Oceanography 45(7), 1485-1500. Toulza, E., Mi-Sun Shin, Guillaume Blanc, Stephane Audie, Mohamed Laabir, Yves Collos, Jean-Michael Claverie, and Daniel Grzebyk, 2010. Gene Expression in Proliferating Cells of the Dinoflagellate Alexandrium catenella (Dinophyceae) 182

References

Applied and Environmental Microbiology 76(13). Townsend, D., Pettigrew, N., Thomas, A., 2001. Offshore blooms of the red tide dinoflagellate, Alexandrium sp., in the Gulf of Maine. Continental Shelf Research 21(4), 347-369. Triplett, E.L., Jovine, R.V.M., Govind, N., Roman, S., Chang, S., Prezelin, B., 1993. Characterization of two full-length cDNA sequences encoding for apoproteins of peridinin-chlorophyll a-protein (PCP) complexes. Molecular Marine Biology and Biotechnology 2(4), 246-254. Uribe, P., Espejo, R.T., 2003. Effect of associated bacteria on the growth and toxicity of Alexandrium catenella. Applied and Environmental Microbiology 69(1), 659-662. Uribe, P., Fuentes, D., Valdés, J., Shmaryahu, A., Zúñiga, A., Holmes, D., Valenzuela, P.D.T., 2008. Preparation and analysis of an expressed sequence tag library from the toxic dinoflagellate Alexandrium catenella. Marine Biotechnology 10(6), 692-700. Usleber, E., Donald, M., Straka, M., Märtlbauer, E., 1997. Comparison of enzyme immunoassay and mouse bioassay for determining paralytic shellfish poisoning toxins in shellfish. Food Additives & Contaminants 14(2), 193-198. Usup, G., Kulis, D.M., Anderson, D.M., 1994. Growth and toxin production of the toxic dinoflagellate Pyrodinium bahamense var. compressum in laboratory cultures. Natural toxins 2(5), 254-262. Van Dolah, F.M., Lidie, K.B., Morey, J.S., Brunelle, S.A., Ryan, J.C., Monroe, E.A., Haynes, B.L., 2007a. Microarray analysis of diurnal and circadian regulated genes in the florida red tide dinoflagellate Karenia brevis (Dinophyceae) Journal of Phycology 43(4), 741- 752. Van Dolah, F.M., Lidie, K.B., Morey, J.S., Brunelle, S.A., Ryan, J.C., Monroe, E.A., Haynes, B.L., 2007. Microarray analysis of diural and circadian regulated genes in the Florida red tide dinoflagellate Karenia brevis (Donophyceae) 1. Journal of Phycology 43(4), 741-752. Van Trappen, S., Mergaert, J., Swings, J., 2004. Loktanella salsilacus gen. nov., sp. nov., Loktanella fryxellensis sp. nov. and Loktanella vestfoldensis sp. nov., new members of the Rhodobacter group, isolated from microbial mats in Antarctic lakes. International Journal of Systematic and Evolutionary Microbiology 54(4), 1263-1269. Vandesompele, J., De Preter, K., Pattyn, F., Poppe, B., Van Roy, N., De Paepe, A., Speleman, F., 2002. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biology 3(7). Vaulot, D., 1995. The cell cycle of phytoplankton: coupling cell growth to population growth. Nato Asi Series Ecological Sciences 38, 303-303. Vesk, M., Jeffrey, S., 1977. Effect of blue green light on photosynthetic pigments and chloroplast structure in unicellular marine algae from six classes. Journal of Phycology 13(3), 280-288. Vierstra, R., Zhang, J., 2011. Phytochrome signaling: solving the Gordian knot with microbial relatives. Trends in Plant Science. Vila, M., Simo, R., Kiene, R.P., Pinhassi, J., Gonzalez, J.M., Moran, M.A., Pedros-Alio, C., 2004. Use of microautoradiography combined with fluorescence in situ hybridization to determine dimethylsulfoniopropionate incorporation by marine bacterioplankton taxa. Applied and Environmental Microbiology 70(8), 4648-4657. Wakimoto, T., Mori, T., Morita, H., Abe, I., 2011 Cytotoxic Tetramic Acid Derivative Produced by a Plant Type-III Polyketide Synthase. Journal of the American Chemical Society. Wang, D.Z., Li, C., Zhang, Y., Wang, Y.Y., He, Z.P., Lin, L., Hong, H.S., 2012. Quantitative proteomic analysis of differentially expressed proteins in the toxicity-lost mutant of 183

References

Alexandrium catenella (Dinophyceae) in the exponential phase. Journal of Proteomics. Wang, J., Salata, J.J., Bennett, P.B., 2003. Saxitoxin is a gating modifier of HERG K+ channels. The Journal of General Physiology 121(6), 583-598. White, A., 1978. Salinity effects on growth and toxin content of Gonyaulax excavata, a marine dinoflagellate causing paralytic shellfish poisoning. Journal of Phycology 14(4), 475-479. White, A.W., 1986. High toxin content in the dinoflagellate Gonyaulax excavata in nature. Toxicon 24(6), 605-610. Wiese, M., D’Agostino, P., Mihali, T., Moffitt, M., Neilan, B., 2010. Neurotoxic Alkaloids: Saxitoxin and Its Analogs. Marine Drugs 8(7), 2185. Wohlrab, S., Iversen, M.H., John, U., 2010. A molecular and co-evolutionary context for grazer induced toxin production in Alexandrium tamarense. PLoS One 5(11), e15039. Wyatt, T., Jenkinson, I., 1997. Notes on Alexandrium population dynamics. Journal of Plankton Research 19(5), 551-575. Yotsu-Yamashita, M., Kim, Y.H., Dudley, S.C., Choudhary, G., Pfahnl, A., Oshima, Y., Daly, J.W., 2004. The structure of zetekitoxin AB, a saxitoxin analog from the Panamanian golden frog Atelopus zeteki: a potent sodium-channel blocker. Proceedings of the National Academy of Sciences of the United States of America 101(13), 4346. Yurkov, V.V., Beatty, J.T., 1998. Isolation of aerobic anoxygenic photosynthetic bacteria from the black smoker plume waters of the Juan de Fuca Ridge in the Pacific Ocean. Applied and Environmental Microbiology 64(1), 337-341. Yutin, N., Suzuki, M.T., Beja, O., 2005. Novel primers reveal wider diversity among marine aerobic anoxygenic phototrophs. Applied and Environmental Microbiology 71(12), 8958-8962. Zaman, L., Arakawa, O., Shimosu, A., Onoue, Y., 1997. Occurrence of paralytic shellfish poison in Bangladeshi freshwater puffers. Toxicon 35(3), 423-431. Zauner, S., Greilinger, D., Laatsch, T., Kowallik, K.V., Maier, U.G., 2004. Substitutional editing of transcripts from genes of cyanobacterial origin in the dinoflagellate Ceratium horridum. FEBS letters 577(3), 535-538. Zehr, J.P., Mellon, M., Braun, S., Litaker, W., Steppe, T., Paerl, H.W., 1995. Diversity of heterotrophic nitrogen fixation genes in a marine cyanobacterial mat. Applied and Environmental Microbiology 61(7), 2527-2532. Zeng, Y., Chen, X., Jiao, N., 2007. Genetic diversity assessment of anoxygenic photosynthetic bacteria by distance based grouping analysis of pufM sequences. Letters in Applied Microbiology 45(6), 639-645. Zhang, H., Hou, Y., Miranda, L., Campbell, D., Sturm, N., Gaasterland, T., Lin, S., 2007. Spliced leader RNA trans-splicing in dinoflagellates. Proceedings of the National Academy of Sciences 104(11), 4618. Zhang, H., Lin, S., 2008. mRNA editing and spliced leader RNA Trans splicing groups Oxyrrhis, Noctiluca, Heterocapsa, and Amphidinium as basal lineages of dinoflagellates Journal of Phycology 44(3), 703-711. Zhu, J., Miller, M.B., Vance, R.E., Dziejman, M., Bassler, B.L., Mekalanos, J.J., 2002. Quorum-sensing regulators control virulence gene expression in Vibrio cholerae. Proceedings of the National Academy of Sciences 99(5), 3129. Zhu, P., You, Y., Chu, J., Jin, H., Yan, X., 2010. Screening and characterization of antibacterial and cytotoxic marine bacteria associated with Karlodinium micrum. Acta Microbiologica Sinica 50(8), 1044.

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