Diversity and Distribution of Heterotrophic Flagellates in the Arctic Ocean

Diversity and distribution of heterotrophic flagellates in the Arctic Ocean

Thèse

Mary Thaler

Doctorat en Océanographie Philosophiae Doctor (PhD.)

Québec, Canada

Résumé

Dans les environnements marins arctiques, les protistes unicellulaires constituent les premiers maillons du réseau trophique. Les flagellés hétérotrophes (HF) jouent un rôle clé au sein de ce réseau trophique comme brouteurs de bactéries et de phytoplanctons, étant broutés à leur tour par les microzooplanctons comme les dinoflagellés ou les ciliés. Les scientifiques prévoient que les changements environnementaux extrêmes qui ont présentement lieu dans l‟Océan Arctique transformeront ces communautés de protistes. Le sujet de cette thèse porte sur la composition taxonomique des communautés marines HF dans l‟Océan Arctique, et leur réponse aux facteurs environnementaux. L‟approche a été d‟utiliser le comptage sur microscope à l‟aide de l‟hybridation fluorescente in situ pour évaluer l‟abondance de deux taxons HF importants, le genre Cryothecomonas et le clade MAST-1 parmi les straménopiles marins. Une approche complémentaire a été de décrire la répartition de tous les taxons HF, y compris l‟ordre Cryomonadida, les straménopiles marins, Picozoa, Telonemia, et les choanoflagellés, par l‟utilisation du séquençage à haut débit. Les résultats des deux approches nous ont permis de capturer les tendances environnementales sur une large échelle géographique dans l‟Arctique. Il a été mis en évidence une composition taxonomique structurée, principalement dû à l‟influence de la glace de mer et d‟autres facteurs environnementaux. Les cellules de Cryothecomonas semblaient provenir de la glace de mer, et au sein de la colonne d‟eau ils se trouvaient les plus nombreuses près du bord de glace. Par contre, les trois sous-clades de MAST-1 étaient retrouvés principalement dans la colonne d‟eau, mais répartis différemment par rapport au couvert de glace et les zones marginales de glace. La composition de la totalité de la communauté HF variait aussi par région, avec une plus grande importance de Telonemia et des choanoflagellés dans le Bassin du Canada. Pour plusieurs taxons, nous avons pu identifier un ou deux phylotypes dominants pour une région donnée. L‟importance relative de ces taxons devrait changer lors de la retraite de glace continue dans l‟Arctique, menant à des changements importants dans les réseaux trophiques et les cycles biogéochimiques

iii

Abstract

In marine environments, single-celled protists form the initial links of the food web. Heterotrophic flagellates (HF) play a key role by grazing on bacteria and phytoplankton, being grazed upon in their turn by microzooplankton such as dinoflagellates and ciliates. The extreme environmental changes currently taking place in the Arctic Ocean are expected to transform protist communities. The subject of this thesis is the taxonomic composition of marine HF communities in the Arctic Ocean, and their response to environmental factors. The approach was to use fluorescent oligonucleotide probes to assess the abundance of two important HF taxa, the genus Cryothecomonas and the clade MAST-1 of the marine stramenopiles, via microscope counts. A complementary approach was to describe distribution of all HF taxa, including Cryomonadida, marine stramenopiles, Picozoa, Telonemia and choanoflagellates, by means of high-throughput sequencing. Results from these two approaches allowed us to capture broad environmental trends over a large geographic scale in the Arctic. A picture emerged of taxonomic composition largely structured by the influence of sea ice and other environmental factors. Cryothecomonas cells are inferred to live principally in the sea ice, and in the water column are more numerous close to the ice edge, whereas three sub-clades of MAST-1 are all found principally in the water column but are distributed differently relative to ice cover and marginal ice zones. The composition of the total HF community also varied by region, with a greater importance of Telonemia and choanoflagellates in the Canada Basin. For several taxa it was possible to identify one or two dominant phylotypes in a given region. The relative importance of these taxa is expected to change as sea ice retreat continues in the High Arctic, leading to important changes in trophic webs and biogeochemical cycles.

Table de Matières

RÉSUMÉ ...... III ABSTRACT ...... V TABLE DE MATIÈRES ...... VII LISTE DES TABLEAUX ...... XI LISTE DES FIGURES ...... XIII LISTE DE TABLEAUX SUPPLÉMENTAIRES ...... XVII LISTE DES ABRÉVIATIONS ...... XIX REMERCIEMENTS ...... XXI AVANT-PROPOS ...... XXIII CHAPTER 1 : INTRODUCTION GÉNÉRALE ...... 1

1.01. INTRODUCTION ...... 1 1.02. LES FLAGELLÉS HÉTÉROTROPHES ET LES RÉSEAUX TROPHIQUES MARINS ...... 1 1.03. L‘IMPORTANCE ÉCOLOGIQUE DE LA TAILLE DES ORGANISMES...... 2 1.04. L‘EFFET DES CHANGEMENTS CLIMATIQUES SUR LES ORGANISMES DE L‘ARCTIQUE ...... 2 1.05. LES OBJECTIFS DE CETTE THÈSE ...... 3 1.06. LES TAXONS HF ...... 4 1.06.1. Cryomonadida ...... 4 1.06.2. Choanoflagellés ...... 4 1.06.3. Straménopiles Marins (MAST) ...... 5 1.06.4. Picozoa ...... 5 1.06.5. Telonemia ...... 5 1.07. MÉTHODOLOGIE ...... 6 1.07.1. Hybridation fluorescente in situ (FISH) ...... 6 1.07.2. Séquençage à haut-débit ...... 7 1.08. ANALYSES STATISTIQUES ...... 8 1.08.1. Les différents types de variables ...... 8 1.08.2. Analyses de correspondance et de chemin...... 8 1.08.3. Analyse canonique de correspondance ...... 9 1.09. RÉGION D‘ÉTUDE ...... 10 1.09.1. Nord de la Mer de Baffin ...... 10 1.09.2. Archipel Arctique Canadien ...... 10 1.09.3. Mer de Beaufort ...... 11 1.09.4. Bassin du Canada ...... 11 1.09.5. Mer des Tchouktches ...... 11 1.10. PLAN DE LA THÈSE ...... 11 CHAPTER 2 : DISTRIBUTION AND DIVERSITY OF A PROTIST PREDATOR CRYOTHECOMONAS (CERCOZOA) IN ARCTIC MARINE WATERS ...... 21

RÉSUMÉ ...... 21 ABSTRACT ...... 22 2.01. INTRODUCTION ...... 23 2.02. MATERIALS AND METHODS ...... 24

vii 2.02.1. Sample collection ...... 24 2.02.2. DNA extraction and cloning ...... 26 2.02.3. Phylogenetic analysis ...... 27 2.02.4. Probe design ...... 28 2.02.5. Grazing experiments ...... 28 2.02.6. Fluorescent in situ hybridization ...... 28 2.02.7. Environmental variables ...... 29 2.03. RESULTS ...... 30 2.03.1. Phylogenetic analysis ...... 30 2.03.2. FISH ...... 31 2.04. DISCUSSION ...... 33 2.04.1. Phylogeny ...... 33 2.04.2. Observations with FISH...... 33 2.04.3. Distribution ...... 34 2.04.4. Trophic position of Cryothecomonas ...... 36 2.05. CONCLUSION ...... 37 2.06. ACKNOWLEDGEMENTS ...... 37 CHAPTER 3 : ENVIRONMENTAL SELECTION OF MARINE STRAMENOPILE CLADES IN THE ARCTIC OCEAN AND COASTAL WATERS ...... 43

RÉSUMÉ ...... 43 ABSTRACT ...... 44 3.01. INTRODUCTION ...... 45 3.02. MATERIALS AND METHODS ...... 46 3.02.1. Sample Collection ...... 46 3.02.2. FISH ...... 48 3.02.3. Environmental Variables ...... 49 3.02.4. Phylogenetic Analysis ...... 50 3.03. RESULTS ...... 50 3.03.1. FISH ...... 50 3.03.2. Phylogenetic Analysis ...... 52 3.04. DISCUSSION ...... 52 3.04.1. Environmental phylogenetic clusters ...... 52 3.04.2. Depth Distribution ...... 53 3.04.3. Relationship with ice-influenced waters ...... 54 3.05. CONCLUSION ...... 55 3.06. ACKNOWLEDGMENTS ...... 55 CHAPTER 4 : DISTINCT HETEROTROPHIC FLAGELLATE COMMUNITIES IN DIFFERENT REGIONS OF THE ARCTIC OCEAN ...... 63

RÉSUMÉ ...... 63 ABSTRACT ...... 64 4.01. INTRODUCTION ...... 65 4.02. MATERIALS AND METHODS ...... 66 4.02.1. Experimental Design ...... 66 4.02.2. Chukchi Sea samples ...... 67 4.02.3. Placement of Reads on Phylogenetic Trees ...... 67 4.03. RESULTS ...... 68 4.03.1. Pyrosequencing and HF community composition...... 68 viii

4.03.2. Phylogenies and evolutionary placement of reads ...... 69 4.04. DISCUSSSION ...... 70 4.04.1. Regional differences between HF communities ...... 71 4.04.2. Size Fractionation of the HF community ...... 72 4.04.3. Changes in HF with depth ...... 73 4.04.4. MAST ...... 74 4.04.5. Cryomonadida ...... 74 4.04.6. Telonemia ...... 76 4.04.7. Picozoa ...... 76 4.04.8. Choanoflagellates ...... 76 4.05. CONCLUSION ...... 77 4.06. ACKNOWLEDGMENTS ...... 77 CHAPTER 5 : CONCLUSIONS GÉNÉRALES ...... 95

5.01. SYNTHÈSE DE L‘ÉTUDE ...... 95 5.02. COMPARAISON DES TECHNIQUES MOLÉCULAIRES ...... 97 5.03. PERSPECTIVES ...... 98 5.03.1. Échantillonnage taillé aux questions de recherche ...... 98 5.03.2. Mesure des taux écologiques ...... 99 5.03.3. Impact des changements climatiques ...... 101 BIBLIOGRAPHIE ...... 103

Liste des tableaux

Table 1.1 Méta-données pour les stations d‟échantillonnage dans cette thèse...... 14 Table 2.1 Simple and partial correlations between abundance of Cryothecomonas and sixteen other biotic and abiotic variables...... 39 Table 3.1. Temperature and salinity characteristics of Arctic water masses as defined in this study...... 56 Table 4.1. References for pyro-tag sequencing data used in this paper. Total reads is given after removing low-quality reads and sub-sampling to an equal number of reads for each sample in a study...... 78 Table 4.2. Percentages of HF taxa in < 3 µm and > 3 µm size fractions from the Chukchi Sea...... 80

Liste des figures

Figure 1.1. Carte des régions de l‟Arctique étudiées dans cette thèse ...... 20 Figure 2.1. Stations sampled for counts of Cryothecomonas using Fluorescent in-situ Hybridization. Station names are given where elevated Cryothecomonas events occurred, or where additional manipulations were performed. Stars indicate clone libraries, 2008; Diamonds indicate grazing experiments...... 40 Figure 2.2. Rooted maximum-likelihood phylogeny of the Cryothecomonas clade and other Cryomonadida genera, screened from Arctic clone libraries and reference sequences from the NCBI nr nucleotide database. Scale bar indicates number of substitutions per position. Bayesian posterior probabilities/Maximum Likelihood bootstrap values (as percentages) greater than 0.60/60 are printed above each node. Open circles indicate sequences from Arctic clone libraries. Closed circles indicate sequences from sediment clone libraries...... 41 Figures 2.3 and 2.4. Epifluorescence micrographs of Cryothecomonas cells hybridized with the Cryo1134 probe from Station 101 on 15 September 2008, showing the range of morphological variation observed. The difference in size of non-hybridized cells between Figure 2.3 and 2.4. is due to the fact that small bacterial cells are not sharply focused in Figure 2.3, and a longer exposure time causing increased halo-ing. Scale bars = 10 µm for all images. A panels: Green excitation, showing the yellow cytoplasm with fluorescent in situ hybridization (FISH). B panels: Overlay of two pictures of the same cell observed under green excitation and ultraviolet excitation (showing the nucleus stained with 4,6-diamidino-2-phenylindole (DAPI))...... 42 Figure 3.1. Map of sampling stations. Shapes correspond with those in Figure 3.2: Beaufort Sea (square), Baffin Bay (circle), Canada Basin (triangle, point down), Labrador Sea (triangle, point up), Lancaster Sound (diamond). Open symbols are sites sampled July–August 2007. Closed symbols are sites sampled July–October 2008...... 57 Figure 3.2. Concentration of: a) MAST-1A; b) MAST-1B; and c) MAST-1C in samples from water masses in different regions of the Arctic. d) Water masses referred to in text. Symbols: Beaufort Sea (square), Baffin Bay (circle), Canada Basin (triangle, point down), Labrador Sea Water (LSW); Atlantic Water (AtW); Bottom Water (BW); Lower Halocline (LH); Arctic Water (AW); Pacific Water (PW); Winter Water (WW); Surface Water (SW). The dashed line indicates the freezing point of seawater at different salinities. Curved grey lines indicate density (sigma-theta)...... 58 Figure 3.3. Ordination diagram of the first two axes of Canonical Correspondence Analysis (CCA) showing the relationship between MAST-1 sub-clades and a) environmental variables, b) water masses. Axes are constrained by abundance of MAST-1 clades and environmental variables. Distance to ice edge (squares) is included as a nominal variable. Water mass features (triangles) are projected a posteriori onto the diagram. See text and Figure 3.2D, for definition of water masses: Labrador Sea Water (LSW); Atlantic Water (AtW); Bottom Water (BW); Lower Halocline (LH); Arctic Water (AW); Pacific Water (PW); Winter Water (WW); Surface Water (SW)...... 59 Figure 3.4. Rooted maximum-likelihood phylogenies of a) MAST-1A; b) MAST-1B and c) MAST- 1C sequences from the NCBI nr nucleotide database. Outgroups not shown. Scale bar indicates number of substitutions per position. Closed circles indicate nodes with bootstrap values > 50

xiii (out of 100). Labels of end-nodes provide clone number, sampling region, and sample depth. Continued on facing page...... 60 Figure 4.1. Stations sampled by studies in this paper...... 81 Figure 4.2. Heterotrophic protist groups as a proportion of all eukaryote sequences from studies in the Arctic Ocean. a) Amundsen Gulf time series (Comeau et al. 2011); b) Franklin Bay sea-ice study 2008 (Comeau et al. 2013); c) Beaufort Sea 2009 (Monier et al. 2013); d) Canada Basin 2007 (Comeau et al. unpublished); e) Chukchi Sea < 3 µm (this study); f) Chukchi Sea > 3 µm (this study). Note the different scale in panel e. Panel c x-axis labels: a = “above SCM”, b = “below SCM. „*‟ in e indicates a sample which had a lower number of non-metazoan reads (n = 1044) ...... 82 Figure 4.3. Marine stramenopile clades as a proportion of all eukaryote sequences from studies in the Arctic Ocean. “Other” includes clades 4, 5, 9 and 10. a) Amundsen Gulf time series (Comeau et al. 2011); b) Franklin Bay sea-ice study 2008 (Comeau et al. 2013); c) Beaufort Sea 2009 (Monier et al. 2013); d) Canada Basin 2007 (Comeau et al. unpublished); e) Chukchi Sea < 3 µm (this study); f) Chukchi Sea > 3 µm (this study). Note the different scale in panel e. Panel c x-axis labels: a = “above SCM”, b = “below SCM. „*‟ in e indicates a sample which had a lower number of non-metazoan reads (n = 1044)...... 83 Figure 4.4. Phylogenetic mapping of Cryomonadida reads from all five studies in this paper. Rooted Cryomonadida reference phylogenetic tree was constructed using maximum likelihood from an alignment of 92 sequences and 1689 characters. Some non-Cryomonadida reference sequences have been omitted for clarity. Closed circles indicate nodes with bootstrap support > 50 (out of 100). Reads are mapped onto the nodes marked with blue circles using RAxML evolutionary placement algorithm; only placements likelihood weight > 0.5 are shown. Left scale bar indicates number of substitutions per position. Protaspis longipes (*) was formerly identified as Cryothecomonas longipes (Hoppenrath and Leander 2006) and Rhogostoma minus (**) was formerly identified as Lecythium sp. (Howe et al. 2011). Outgroups (not shown) are two radiolarian sequences and an acantharean (Spongaster tetras AB101542, Lithomelissa setosa HQ651801, Acanthometra fusca KC172856). Reference and outgroup sequences are listed in Supplementary Table S4.3 ...... 84 Figure 4.5. Phylogenetic mapping of Telonemia reads from all five studies in this paper. Rooted Telonemia reference phylogenetic tree was constructed using maximum likelihood from an alignment of 52 sequences and 1942 characters. Closed circles indicate nodes with bootstrap support > 50 (out of 100). Reads are mapped onto the nodes marked with blue circles using RAxML evolutionary placement algorithm; only placements likelihood weight > 0.5 are shown. Left scale bar indicates number of substitutions per position. Labelled clades correspond to Bråte et al. (2010b). Outgroups (not shown) are a haptophyte and a katablepharid (Prymnesium parvum AJ246269 and Katablepharis japonica AB231617). Reference and outgroup sequences are listed in Supplementary Table S4.4 ...... 85 Figure 4.6. Phylogenetic mapping of Picozoa reads from all five studies in this paper. Rooted Picozoa reference phylogenetic tree was constructed using maximum likelihood from an alignment of 55 sequences and 1168 characters. Closed circles indicate nodes with bootstrap support > 50 (out of 100). Reads are mapped onto the nodes marked with blue circles using RAxML evolutionary placement algorithm; only placements likelihood weight > 0.5 are shown. Left scale bar indicates number of substitutions per position. Clades are labelled xiv

following Seenivasan et al. 2013. Outgroups (not shown) are a haptophyte, a katablepharid, and a Telonemia (Prymnesium parvum AJ246269, Katablepharis japonica AB231617 and Telonema antarcticum (AJ564773). Reference and outgroup sequences are listed in Supplementary Table S4.5 ...... 86 Figure 4.7. Phylogenetic mapping of choanoflagellate reads from all five studies in this paper. Choanoflagellate reference phylogenetic tree was constructed using maximum likelihood from an alignment of 49 sequences and 1963 characters. Closed circles indicate nodes with bootstrap support > 50 (out of 100). Reads are mapped onto the nodes marked with blue circles using RAxML evolutionary placement algorithm; only placements likelihood weight > 0.5 are shown. Left scale bar indicates number of substitutions per position. Outgroups (not shown) are two metazoan sequences, Mnemiopsis leidyi (AF293700) and Beroe ovata (AF293694), a sponge (AY348876), two ichthyosporeans (Y16260 and AF232303), and Corallochytrium (L42528). Reference and outgroup sequences are listed in Supplementary Table S4.6 ...... 87

Liste de tableaux supplémentaires

Supplementary Table S3.1. Number of cells counted for each MAST-1 sub-clade...... 62 Supplementary Table S4.1. Number of reads per sample after processing ...... 88 Supplementary Table S4.2. Pyrosequencing raw data, filtering and OTU statistics for data from ICESCAPE 2010 study. Percentages are given relative to reads available from the preceding step...... 89 Supplementary Table S4.3. Cercozoan sequences used to construct a reference tree for phylogenetic placement of Cryomonadida reads. Protaspis longipes (*) was formerly identified as Cryothecomonas longipes (Hoppenrath and Leander 2006) and Rhogostoma minus (**) was formerly identified as Lecythium sp. (Howe et al. 2011)...... 90 Supplementary Table S4.4. Telonemia sequences used to construct a reference tree for phylogenetic placement of reads...... 92 Supplementary Table S4.5. Picozoa sequences used to construct a reference tree for phylogenetic placement of reads...... 93 Supplementary Table S4.6. Choanoflagellate sequences used to construct a reference tree for phylogenetic placement of reads...... 94

xvii

Liste des abréviations

18S : petite sous-unité du ribosome eucaryote ACC ou CCA : analyses canonique des correspondances ADN ou DNA : acides désoxyribonucléiques ADNc ou cDNA : acides désoxyribonucléiques complémentaires ARN ou RNA : acides ribonucléiques ARNr ou rRNA : acides ribonucléiques ribosomaux AtW : Eau Atlantique (Atlantic Water) AW : Eau Arctique (Arctic Water BLAST : basic local alignment search tool bp ou pb : paire de bases (base pairs) BW : Eau du fond (bottom water) C3O : Canada‟s Three Oceans CARD-FISH : catalyzed reporter deposition fluorescent in situ hybridization CCA ou ACC : analyse canonique des correspondances CCGS ou NGCC : Canadian Coastguard Ship (Navire de Garde Côtière Canadien) cDNA ou ADNc : acides désoxyribonucléiques complémentaires CFL : Circumpolar Flaw Lead Study chl a : chlorophylle a CHONe : Canadian Healthy Oceans Network CTD : conductivité-température-profondeur DAPI : 4‟,6-diamidino-2-phenylindole DNA ou ADN : acides désoxyribonucléiques dNTP : désoxyribonucléotide DOTUR : Distance-based Operational Taxonomic Units and Richness Determination EDTA : acide éthylène diamine tétraacétique EPA : Environmental Placement Algorithm FCM : cytométrie en flux FISH : hybridation fluorescente in situ FLB : fluorescently labeled bacteria (bactéries marquées par un fluorochrome) GF/F : glass fiber (fibre de verre) class F filter GTR : general time-reversible HF : flagellés hétérotrophes HPLC : high-performance liquid chromatography (chromatographie en phase liquide à haute performance) ICESCAPE : Impacts of Climate change on the Ecosystems and Chemistry of the Arctic Pacific Environment IPY : International Polar Year (Année Polaire Internationale) LH : halocline inférieure (lower halocline) LSW : Eau de la Mer du Labrador (Labrador Sea Water) MAST : straménopile marin (marine stramenopile) ML : maximum likelihood (maximum de vraisemblance) MUSCLE : Multiple Sequence Comparison by Log-Expectation N2 : Fréquence de Brunt-Väisäla NCBI : National Center for Biotechnology Information NGCC ou CCGS : Navire de Gard Côtière Canadienne (Canadian Coastguard Ship) NJ : neighbour-joining

xix NSERC : Natural Science and Engineering Council of Canada (Conseil de recherches en sciences naturelles et en génie du Canada) OTU : Operational Taxonomic Unit pb ou bp : paire de bases PAR : rayonnement photosynthétiquement actif PC : polycarbonate PCR : réaction en chaîne par polymérase PSU : practical salinity units PW : Eau Pacifique RAxML : Randomized Accelerated Maximum Likelihood RFLP : restriction fragment length polymorphism (polymorphisme de longeur des fragments de restriction) RNA ou ARN : acides ribonucléiques rRNA ou ARNr : acides ribonucléiques ribosomaux SCM : maximum sous-superficiel de la chlorophylle a SDS : dodécylsulfate de sodium SRA : Sequence Read Archive SW : eau du surface TE : Tris-EDTA Tris : Tris(hydroxymethyl)aminomethane USCGS : United States Coastguard Ship WW: Eau d‟hiver (Winter Water)

Remerciements

Je tiens premièrement à remercier ma directrice de recherche Connie Lovejoy, qui m‟a fait découvrir l‟intersection merveilleuse entre la biologie moléculaire, la microbiologie et l‟océanographie dans l‟Arctique. Lors d‟innombrable contretemps, quand une crise se produisait sur le terrain, une expérience semblait être en panne, ou la logique d‟un paragraphe de la discussion qui risquait de se compliquer au-delà de la raison, elle était toujours disponible avec ses conseils et encouragements. Je me sens chanceuse d‟avoir bénéficier de sa sagesse et de son soutien constant tout au long de ce processus.

Je voudrais également remercier les membres de mon comité d‟encadrement, Jean-Éric Tremblay et Nicolas Dérôme, pour leurs précieux conseils, commençant avec ma présentation de projet et continuant pendant plusieurs réunions très productives. Je remercie également Jean-Éric Tremblay, Rebecca Gast et Alex Culley pour avoir consenti à être sur le comité d‟évaluation pour cette thèse.

Entre de nombreux mentors lors de ma carrière scolaire, je souhaite mentionner ma directrice de mémoire au baccalauréat, Irena Kaczmarska, qui était la première à me transmettre le virus, de la joie et merveille, des organismes marins microscopiques, et ma chère amie et collègue Anne Jungblut qui m‟a précédé par plusieurs années sur ce chemin, et m‟a donné la confiance de la suivre.

J‟ai été surtout chanceuse de travailler au sein d‟un groupe de recherche où se promouvait un climat de collaboration et d‟entraide. Ce serait impossible de raconter toutes les façons dont chaque personne m‟a aidé au long des années. Mais, pour faire une liste inévitablement incomplète, je mentionne Ramon Terrado qui, en partageant un bureau pour les derniers cinq ans, a vu tous les hauts et les bas de mon doctorat, et restait sage et rassurant tout du long; Marianne Potvin pour les formations dans les techniques de biologie moléculaire quand j‟étais une débutante nerveuse; André Comeau et Adam Monier pour leur aide avec tout ce qui est bioinformatique; Emmanuelle Medrinal, avec qui j‟ai partagé de beaux moments d‟exaltation et d‟anxiété sur le terrain; Cindy DaSilva et Bérangère Péquin pour leur soigneuse relecture de mon français, et les échanges fructueux; et Vani Mohit, Sophie Charvet, et Sophie Crevecoeur pour divers soutiens, conseils, et des matchs de volley-ball vivement engageants. Travailler avec vous tous était une joie, et je vous souhaite tous les bonheurs que vous méritez sur vos chemins respectifs

xxi Une portion des travaux décrits ici a été effectuée pendant un stage de trois mois sous la direction de Carlos Pedrós-Aliñ et Ramon Massana à l‟Institut de Ciències del Mar. Je tiens à les remercier pour leur accueil chaleureux ainsi que Irene Forn, qui m‟a formé dans les techniques de laboratoire.

La plupart de l‟échantillonnage pour cette recherche a été effectué à bord des navires de la Garde Côtière Canadienne. Je dois des remerciements aux commandants et aux équipages de la NGCC Amundsen et la NGCC Louis S. St-Laurent pour leur professionnalisme et leur soutien sur le terrain.

Au niveau personnel, je dois une énorme reconnaissance à mes parents pour leur exemple de courage et de détermination, leur confiance inlassable en moi, et leur amour inconditionnel. Plusieurs autres m‟ont soutenu dans cette période de ma vie, ici à Québec ou de loin. Je veux mentionner mes frères, John et Mike, ainsi que les amis Kristen Conrad, Nicole Journal, Mike Walker et Alain LeBlond, et bien d‟autres trop nombreux pour les nommer mais chacun bien apprécié.

xxii

Avant-propos

Cette thèse présente mes travaux de doctorat effectués sous la direction du Dr. Connie Lovejoy, professeure du département de Biologie de l‟Université Laval. La thèse est composée de cinq chapitres, dont trois présentés sous forme d‟articles, précédés d‟un résumé en français. Le premier chapitre consiste en une introduction générale à la problématique, la méthodologie, et les régions d‟étude. Elle se termine par une présentation des objectifs des chapitres suivants. Le dernier chapitre présente les conclusions et perspectives de la recherche.

Je suis première auteure de chacun des articles, avec ma directrice Connie Lovejoy comme co- auteure. L‟échantillonnage sur le terrain a été effectué par moi-même ou par des collègues au sein de plusieurs programmes de recherche majeurs : Canadian Arctic Shelf Exchange Study 2003–2004, ArcticNet 2005–2010, Canada’s Three Oceans (C3O) 2007, le Circumpolar Flaw Lead Study (CFL; « Étude sur le chenal de séparation circumpolaire ») 2007–2008, Malina 2009, et ICESCAPE 2010. Pour les chapitres 2 et 3, j‟ai réalisé les banques de clones, l‟hybridation fluorescente in situ (FISH) et les comptes sur microscope. Les données contextuelles, tel que l‟abondance de bactéries, la concentration de chlorophylle a et de nutriments, étaient fournies par les collègues qui sont identifiés dans les chapitres pertinents. Le cinquième chapitre inclut des nouvelles données avec une méta-analyse des données provenant de quatre études déjà publiées ou en voie de publication. Les nouvelles analyses substantielles effectuées sur ces données répondaient à des questions de recherche nettement différentes que les articles originaux. J‟ai réalisé l‟interprétation des données et la rédaction pour tous les trois articles.

Chapitre 1 : Introduction générale

Chapitre 2 : Thaler M, Lovejoy C (2012) Distribution and Diversity of a Protist Predator Cryothecomonas (Cercozoa) in Arctic Marine Waters. Journal of Eukaryotic Microbiology 59: 291– 299. doi: 10.1111/j.1550-7408.2012.00631.x

Chapitre 3 : Thaler M, Lovejoy C (2013) Environmental selection of marine stramenopile clades in the Arctic Ocean and coastal waters. Polar Biology. doi 10.1007/s00300-013-1435-0

Chapitre 4 : Distinct heterotrophic flagellate communities in different regions of the Arctic Ocean. Ce chapitre sera soumis sous peu pour publication.

Chapitre 5 : Conclusion générale

xxiii Par ailleurs, les travaux de recherche de la thèse ont été présentés à des réunions scientifiques générales du Réseau ArcticNet et du regroupement inter-institutionnel Québec-Océan. De plus, certains résultats préliminaires ont été présentés sous la forme d‟affiche au congrès de l‟ASLO (Association for the Sciences of Limnology and Oceanography) à Nice en 2009, et les résultats du deuxième article ont été présentés sous la forme d‟affiche au congrès de l‟ASLO à Salt Lake City en 2012.

Finalement, les travaux effectués pendant le doctorat ont contribué à d‟autres publications :

1) Terrado R, Medrinal E, Dasilva C, Thaler M, Vincent VF, Lovejoy C (2011) Protist community composition during spring in an Arctic flaw lead polynya. Polar Biology 34 : 1901–1914.

2) Blais M, Tremblay J-É, Jungblut A, Gagnon J, Martin J, Thaler M, Lovejoy C (2012) Nitrogen fixation and identification of potential diazotrophs in the Canadian Arctic. Global Biogeochemical Cycles 26 : GB302.

3) Terrado R, Thaler M, Scarcella K, Vincent WF, Lovejoy C (2013) Small phytoplankton in Arctic seas : vulnerability to climate change. Biodiversity 14.

4) Comeau AM, Philippe B, Thaler M, Gosselin M, Poulin M, Lovejoy C (2013) Protists in Arctic drift and land-fast ice. Journal of Phycology 49 : 229–240.

5) Monier A, Terrado R, Thaler M, Comeau AM, Medrinal E, Lovejoy C (2013) Upper Arctic Ocean water masses harbor distinct communities of heterotrophic flagellates. Biogeosciences 10 : 3397–3430.

xxiv

Chapter 1 : Introduction Générale

1.01. Introduction Bien que tous les niveaux des réseaux trophiques marins arctiques sont probablement sensibles aux changements climatiques récents (ex. Fortier et al. 2006; Falk-Petersen et al. 2007; Laidre et al. 2008), ses impacts sont déjà visibles dans la communauté des organismes unicellulaires qui composent la base de ces réseaux (Li et al. 2009; Comeau et al. 2011). Comprendre la composition taxonomique de la communauté des protistes marins hétérotrophes dans l‟Océan Arctique sera primordial pour comprendre la réponse de cet écosystème aux changements. Plusieurs fonctions intéressantes des écosystèmes, comme la respiration et l‟utilisation des substrats, dépendent de la composition taxonomique des communautés bactériennes dans les sols et l‟eau douce (Bell et al. 2005; Langenheder et al. 2006; Strickland et al. 2009). Chez les eucaryotes hétérotrophes, la grande variabilité des taux de broutage et de croissance rapportés (Weisse 2002) suggère que la composition de cette communauté doit également avoir un effet sur les fonctions de l‟écosystème. Les facteurs qui affectent la répartition des taxons et la composition des communautés peuvent donc avoir des effets sur les cycles biogéochimiques et les réseaux trophiques.

Les mécanismes conduisant la répartition de microorganismes sont encore débattus (Hanson et al. 2012). L‟existence des assemblages taxonomiques caractéristiques dans les environnements différents comme les bassins anoxiques et les masses d‟eaux arctiques (Filker et al. 2007; Hamilton et al. 2008; Orsi et al. 2011) suggère un mécanisme au-delà des processus stochastiques. Par contre, plusieurs chercheurs pensent que les barrières à la dispersion ne sont pas importantes pour la répartition des protistes (Fenchel et Finlay 2004; Cermeðo et Falkowski 2009). Donc, c‟est la sélection des organismes par les facteurs environnementaux qui reçoit un intérêt croissant. Les effets des conditions environnementales sur la répartition ont été démontrés pour plusieurs groupes pélagiques marins, y compris une algue de la classe des prasinophytes (Foulon et al. 2008) et un flagellé hétérotrophe (Rodríguez-Martínez et al. 2013). Donc, pour comprendre et prédire les changements dans la répartition des protistes marins, cela est primordial de comprendre comment les variables environnementales déterminent ces répartitions.

1.02. Les flagellés hétérotrophes et les réseaux trophiques marins C‟est reconnu depuis longtemps que les organismes unicellulaires sont responsables de la plupart de la production primaire dans les environnements marins. Dans les trente dernières années, nous sommes parvenus à comprendre que la plupart de cette production est également consommée et

1 recyclée par les organismes unicellulaires (Azam et al. 1983). Ce réseau microbien implique les membres des trois domaines de la vie, Eukaryota, Bacteria et Archaea. L‟action des microbes peut faire un « court-circuit » des chaînes trophiques en empêchant le carbone de se transférer aux maillons supérieurs.

1.03. L’importance écologique de la taille des organismes La taille des organismes influe sur la prise de nutriments, la durée de génération, et les pertes dues au broutage et la sédimentation (Raven 1998). Normalement, les planctons sont cloisonnés dans les classes par leur rétention sur une membrane d‟une taille de pore donnée, selon le système de Sieburth et al. (1978). Les trois classes de taille les plus pertinentes pour les protistes sont les picoplanctons (0,2–2 µm), les nanoplanctons (2–20 µm), et les microplanctons (20–200 µm).

Les petits protistes hétérotrophes, dans la gamme de taille pico à nano, ont reçu moins d‟attention que les phototrophes pigmentés ou les microhétérotrophes comme les dinoflagellés ou les ciliés, en partie à cause des difficultés d‟identification par les moyens conventionnels (Boenigk et al. 2005); ils jouent cependant un rôle clé comme brouteurs des procaryotes hétérotrophes et phototrophes (Sherr et Sherr 2002; Chen et Liu 2010), et dans plusieurs environnements, incluant l‟Arctique, ils exercent un contrôle sur les populations bactériennes (Jürgens et Massana 2008; Vaqué et al. 2008). Le broutage sur les autotrophes picoeucaryotes est moins souvent rapporté, mais a été détecté dans les cultures (Christaki et al. 2005; Bręk-Laitinen et Ojala 2011) et les échantillons environnementaux (Sherr et al. 1997). Les pico- et nano- hétérotrophes sont consommés à leur tour par les microhétérotrophes et le zooplancton (Kuparinen et Bjornsen 1992; Jeong et al. 2007).

1.04. L’effet des changements climatiques sur les organismes de l’Arctique L‟Arctique présente plusieurs particularités environnementales pour les organismes unicellulaires. La disponibilité de la lumière pour les organismes photosynthétiques est saisonnièrement très limitée à cause des hautes latitudes et le couvert de glace, et l‟eau reste froide pendant toute l‟année. À cause des patrons globaux d‟évaporation et de précipitation, les apports riverains d‟eau douce, et la fonte saisonnière de la glace de mer (Aagaard et al. 1981), la colonne d‟eau est fortement stratifiée par la salinité (Carmack 2007), ce qui permet la formation de la glace de mer. Cette stratification par la salinité impose également la profondeur de la couche de mélange, dans laquelle les nutriments sont souvent peu disponibles aux planctons (Tremblay et al. 2008). Le compromis entre accès aux nutriments et la lumière crée un maximum sous-superficiel de la biomasse et la fluorescence de chlorophylle a (le SCM; Martin et al. 2010). L‟environnement unique de l‟Arctique

fait qu‟il possède également une communauté de protistes unique (ex. Lovejoy et al. 2006; Terrado et al. 2012). Par exemple, les cyanobactéries, qui sont des picophytoplanctons dominants dans la plupart des Océans mondiaux, sont absentes de l‟Arctique (Waleron et al. 2007), où les picochlorophytes photosynthétiques du genre Micromonas sont les picophytoplanctons dominants (Lovejoy et al. 2007).

Une dernière particularité de l‟Océan Arctique est que la communauté de la colonne d‟eau interagit de façon saisonnière avec la communauté dans la glace de mer. La communauté de la glace s‟initie pendant la formation de glace avec l‟incorporation des cellules de la colonne d‟eau (Rñżańska et al. 2008). Cependant, l‟environnement des bulles et canaux de saumure dans la structure de glace sélectionne une communauté qui est distincte de la communauté de la colonne d‟eau (Ikävalko et Gradinger 1997; Sime-Ngando et al. 1997a). Thomsen et al. (1997) ont trouvé, pour les choanoflagellés acanthoecides dans l‟Antarctique, que la différence dans la communauté est due à un taux de survie différentiel plutôt qu‟un recrutement sélectif pendant la formation de la glace. Ces cellules sont enfin relâchées dans la colonne d‟eau pendant la fonte de glace (Juul-Pedersen et al. 2010).

Tout cet environnement distinctif est présentement menacé par les changements climatiques. Pour plusieurs raisons, l‟effet du réchauffement global est plus sévère dans les régions polaires. Les effets les plus frappants comprennent une augmentation dans les apports d‟eau douce (ACIA 2005), et le retrait massif de la glace (Stroeve et al. 2012). Des tels effets se répercuteront naturellement au sein de la communauté microbienne. Il est fort possible que la production primaire totale dans l‟Océan Arctique augmentera à cause d‟une prolongation de la saison de croissance et une augmentation dans la superficie de l‟eau ouverte (Arrigo et al. 2008). Li et al. (2009) ont détecté une diminution de la taille moyenne des cellules, probablement due à une plus forte stratification et l‟inaccessibilité des nutriments, ce qui peut avoir des effets sur l‟export du carbone par la sédimentation, et le broutage par des niveaux trophiques supérieurs. Comeau et al. (2011) ont détecté un changement dans la composition taxonomique de la communauté de protistes avant et après l‟année minimum de glace en 2007. Les conséquences d‟un tel changement pour le réseau trophique ne sont pas encore bien comprises. Donc, une meilleure compréhension de tous les compartiments du réseau microbien nous aiderait à prédire les effets des changements climatiques sur l‟écosystème, mais surtout des groupes comme les HF, qui ont historiquement reçu moins d‟attention.

1.05. Les objectifs de cette thèse 1) Identifier les taxons HF importants et leur répartition géographique dans l‟Arctique.

3 2) Comprendre l‟impact des variables environnementales sur l‟abondance des différents taxons HF, afin de comprendre comment les changements environnementaux dans l‟Arctique peuvent modifier la composition de la communauté.

1.06. Les taxons HF Bien qu‟ils puissent se ressembler morphologiquement, les petits HF comprennent une large diversité de niches écologiques. Cinq taxons HF connus pour être répandus dans l‟Océan Arctique ont été sélectionnés et ont reçus une attention particulière dans cette thèse: l‟Ordre des Cryomonadida, l‟Ordre des Choanoflagellida, le groupe polyphylétique des straménopiles marins (MAST), et les super-groupes eucaryotes Telonemia et Picozoa.

1.06.1. Cryomonadida L‟Ordre Cryomonadida est dans le super-groupe Rhizaria et le groupe Cercozoa. Cercozoa est sans rang taxonomique officiel reconnu, mais se compose de plusieurs amiboflagellés benthiques et planctoniques qui utilisent un pseudopode pour capturer leur proie (Cavalier-Smith 1998; Chantangsi et al. 2010). Cryomonadida comprend les genres Cryothecomonas, Protaspis, Rhogostoma, Rhizapis et Capsellina (Mylnikova et Mylnikov 2012), dont les trois derniers sont rapportés seulement dans les eaux douces. La majorité des taxons décrits sont des prédateurs de bactéries et des petits phytoplanctons, mais il y a au moins deux espèces, Cryothecomonas aestivalis (Drebes et al. 1996) et Protaspis longipes (Schnepf et Kühn 2000) qui sont des parasitoïdes des diatomées planctoniques. Pour les deux genres marins, Cryothecomonas a été rapporté dans la glace de mer et la colonne d‟eau (Thomsen et al. 1991; Sime-Ngando et al. 1997a; Tillmann et al. 1999; Garrison et al. 2005), alors que Protaspis a été rapporté dans les sédiments marins (Lee et Patterson 2000; Saburova et al. 2009), les lacs (Auer et Arndt 2001), la glace de mer (Ikävalko et Gradinger 1997) et la colonne d‟eau marine (Vørs 1993b).

1.06.2. Choanoflagellés L‟Ordre Choanoflagellida est dans le super-groupe Opisthokonta, qui inclut ainsi les animaux metazoaires et les Fungi (Adl et al. 2012). Il est caractérisé par la présence d‟un collier des microvillosités en forme d‟un entonnoir qui entoure le flagelle. À l‟exception d‟une brève phase motile suite à la division cellulaire, ce flagelle n‟est pas utilisé pour la motilité, mais pour générer un courant d‟alimentation. Les espèces connues sont attachées à un substrat, ou passivement suspendues dans la colonne d‟eau (Leadbeater 2008). Historiquement, cet ordre a été divisé en trois familles, Codonosigidae, Salpingoecidae et Acanthoecidae. Cependant, dans les phylogénies multigènes révisées, le seul clade retenu était Acanthoecidae, distingué par la possession d‟une

lorica siliceuse. Cette lorica leur permet un mode de vie planctonique sans fixation à un substrat, en leur donnant assez de masse pour résister à la poussée de la courante d‟alimentation (Carr et al. 2008). Les choanoflagellés comprennent des espèces dans tous les habitats aquatiques, y inclut l‟eau douce et marine, la glace der mer (Ikävalko et Gradinger 1997) et possiblement les sédiments (Dayel et al. 2011).

1.06.3. Straménopiles Marins (MAST) L‟expression « MAST » décrit plusieurs clades indépendants dans le super-groupe des straménopiles qui ont été récemment découverts à partir des études environnementales du gène 18S rRNA (Dìez et al. 2001; Not et al. 2009). L‟utilisation de l‟hybridation fluorescente in situ (FISH) a permis la caractérisation morphologique et écologique de plusieurs de ces clades phylogénétiquement définis. MAST-1 semble être un clade globalement répandu (Massana et al. 2006) alors que MAST-4, aussi très répandu dans les Océans globaux, semble être exclut des eaux froides, incluant l‟Arctique (Rodrìguez-Martínez et al. 2013). MAST-2 semble être le plus abondant des MASTs dans la glace de mer (Piwosz et al. 2013). Les observations et les expériences de broutage indiquent que la majorité des clades sont bactérivores (Massana et al. 2002, 2009; Piwosz et al. 2013). Cependant il a été observé chez MAST-6 des petits phytoplanctons eucaryotes dans ses vacuoles (Piwosz et Pernthaler 2010), et il y a une possibilité que MAST-4 puisse consommer des cyanobactéries (Lin et al. 2012).

1.06.4. Picozoa Les Picozoa ont été découverts dans les banques de clones du gène 18S ARNr de la fraction de taille < 3 µm (Not et al. 2007). Les observations originales avec les sondes d‟oligonucléotides spécifiques au groupe trouvaient une fluorescence de la phycobiline, concordante avec un lien proche aux cryptophytes (Cuvelier et al. 2008). Cependant, dans une étude génomique des cellules individuelles, Yoon et al. (2011) n‟ont pas détecté les gènes liés à la photosynthèse. Un représentant cultivé de Picozoa peut consommer le matériel colloïdal ou des particules virales (Seenivasan et al. 2013). L‟association putative entre les cellules ciblées par les sondes spécifiques aux Picozoa et la fluorescence de la phycobiline peut se produire si les cryptophytes mangent les Picozoa, ou, inversement, si les Picozoa s‟associent aux cyanobactéries, peut-être même en façon symbiotique comme observé pour un prymnésiophyte (Thompson et al. 2012).

1.06.5. Telonemia Le genre Telonema est connu depuis 1913, mais son gène 18S ARNr a été séquencé seulement dans cette dernière décennie. Il est devenu évident que ce groupe consistait un taxon de haut niveau

5 phylogénétique, peu apparenté aux autres super-groupes eucaryotes (Shalchian-Tabrizi et al. 2006). Une étude sur le gène 18S ARNr a montré qu‟il y avait des clades spécifiques à l‟eau douce et marine (Bråte et al. 2010b). Les espèces Telonemia décrits sont des nanoflagellés qui consomment des phytoplanctons eucaryotes (Klaveness et al. 2005).

1.07. Méthodologie L‟identification des HF est couramment un problème en écologie microbienne. Bien que les cultures sont essentielles pour pleinement caractériser les taxons, elles sont difficiles à établir pour la majorité d‟entre eux. La microscopie optique conventionnelle peut exiger des échantillons vivants pour une identification concrète, ou simplement ne pas fournir suffisamment de caractères diagnostiques.

Les techniques basées sur le gène 18S ARNr fournissent une solution à ce problème. Ce gène, qui code la petite sous-unité de l‟ARN ribosomique, est retrouvé chez tous les eucaryotes, et une accumulation croissante des séquences de référence publiées facilite l‟identification basée sur la similarité des séquences et l‟analyse phylogénétique (Lim 1996). La présence des régions conservées, ainsi que variables, dans le gène fournit une bonne résolution pour une gamme d‟échelles taxonomiques.

1.07.1. Hybridation fluorescente in situ (FISH) FISH utilise une sonde oligonucléotide fluorescente, qui s‟hybride spécifiquement à l‟ARNr 18S. En ciblant différentes régions du gène, il est possible de concevoir des sondes pour de grands groupes taxonomiques ou spécifiques selon les objectifs du chercheur (Amann et a. 1990b). La présence d‟un grand nombre de ribosomes dans une cellule multiplie naturellement le signal fluorescent, qui peut être observé avec un microscope à épifluorescence (Pernthaler et al. 2001). L‟un des avantages de la technique est que les cellules sont observées directement. Nous pouvons interpréter les résultats sans ambiguïté comme la concentration des cellules dans un échantillon. Aussi, la plupart de la morphologie est préservée. Nous pouvons alors calculer la taille des cellules et leur biomasse, dans le cas des cellules phagotrophiques observer des proies dans les vacuoles de phagocytose. Les incertitudes associées à cette technique sont la perte de cellules pendant les manipulations, l‟hybridation non spécifique, et le potentiel que les futures révisions phylogénétiques révèlent des clades qui ne s‟accordent plus avec la séquence de la sonde. Également, le comptage des cellules prends beaucoup de temps, et le chercheur peut seulement examiner un nombre limité de taxons.

1.07.2. Séquençage à haut-débit Le séquençage à haut-débit, utilisant des techniques comme le pyroséquençage 454 (Margulies et al. 2005) ou Illumina (Bennett 2004), fournit une méthode pour capturer la diversité entière d‟un échantillon, incluant les taxons rares (Sogin et al. 2006). Les chercheurs peuvent décider de séquencer l‟ARN (sous forme d‟ADNc) au lieu de l‟ADN (p. ex. Terrado et al. 2011; Logares et al. 2012). Il est possible que le séquençage de l‟ARN donne plus d‟information sur l‟activité et l‟expression des gènes dans la cellule, en excluant les cellules mortes ou l‟ADN extracellulaire. Les limitations de cette technique sont le coût initial pour analyser un échantillon (bien que le coût par séquence soit assez bas), et les séquences relativement courtes qui pourraient ne pas fournir une résolution taxonomique assez fine pour certaines questions de recherche. Pourtant les avancées technologiques rapides ont apporté des améliorations aux niveaux des coûts et des longueurs de séquences. Une autre limitation est qu‟il n‟est pas toujours évident d‟anticiper le nombre de séquences produites par échantillon en fonction de l‟abondance initiale des cellules. Le nombre de copies du gène 18S ARNr varie de façon importante chez les protistes, même entre les souches du même genre (Zhu et al. 2005), les cellules avec plus des copies peuvent donc être surreprésentées dans les séquences. S‟il y a une étape initiale de PCR, les biais taxonomiques qui y sont associés (Jeon et al. 2008; Potvin et Lovejoy 2009) s‟appliquent aussi. Finalement, il faut s‟assurer que les erreurs de séquençage ne surestiment pas artificiellement la diversité de l‟échantillon (Huse et al. 2007).

Mon approche dans ce projet était d‟utiliser la technique du FISH pour évaluer la concentration de deux taxons HF, le genre Cryothecomonas et le clade MAST-1 (avec ses sous-clades MAST-1A, - 1B et -1C), à différents sites au travers de la Mer de Beaufort, l‟Archipel Arctique Canadien et le nord de la Mer de Baffin. Les échantillons d‟eau de mer étaient récoltés en utilisant un système CTD-rosette, à diverses profondeurs incluant la surface, le SCM, et le cas échéant, les masses d‟eau plus profondes. J‟ai utilisé des analyses statistiques pour déterminer l‟effet d‟une série de variables environnementales sur la répartition de ces taxons. Ces variables incluaient la distance au bord de la glace, la concentration de la chlorophylle a et les concentrations en nutriments nitrate et phosphate, et la biomasse des autres cellules phototrophes ou hétérotrophes dans la communauté.

À la suite des analyses avec la technique du FISH, les résultats étaient comparés à une analyse de l‟abondance relative des cinq taxons HF décrits ci-dessus, à l‟aide de données tirées du pyroséquençage 454. Les séquences HF étaient extraites de l‟ensemble de données déjà analysées provenant de la Mer de Beaufort et du Bassin du Canada, permettant une importante couverture spatiale et temporelle de l‟Ouest d‟Arctique des années 2003–2010. De nouvelles séquences

7 analysées provenaient de la Mer des Tchouktches. Pour les MAST, la répartition des sous-clades était examinée aussi. Pour les quatre autres taxons, la classification taxonomique des sous-clades est moins bien définie. Pour cette raison, les séquences courtes du pyroséquençage étaient intégrées à un arbre phylogénétique de référence pour caractériser davantage les organismes dans ces échantillons et identifier la potentielle structuration géographique de leurs répartitions.

1.08. Analyses Statistiques L‟analyse des données d‟abondance des taxons comporte plusieurs particularités statistiques, incluant un manque de réplication, une forte proportion des valeurs nulles, des données non équilibrées et souvent une violation des suppositions de normalité et d‟homoscédasticité. Plusieurs variables environnementaux contextuels peuvent être mesurées et sont probablement autocorrélées. Les approches multivariées permettent de trouver des patrons de répartitions des taxons et peuvent être adaptées dans le cas où les suppositions de normalité et d‟homoscédasticité sont transgressées. Même dans une étude plutôt descriptive que expérimentale, les techniques statistiques qui construisent et testent des hypothèses sont cruciales pour identifier l‟effet des différentes variables environnementales.

1.08.1. Les différents types de variables Les variables sont continues si elles peuvent prendre n‟importe quelle valeur réelle dans une gamme possible. Elles sont discrètes, ou catégoriques si seulement un nombre limité de valeurs est possible. Dans le chapitre 3 de cette thèse, la proximité au bord de glace était traitée comme une variable discrète avec trois catégories : couverte de glace, près du bord de glace (≤ 55 km), et eau libre (≥ 55 km). Cette décision a été prise parce que nous considérons que la différence entre ces catégories est qualitative. En effet, la différence entre un site couvert de glace (distance = 0 km) et un site se trouvant à 1 km du bord de glace est plus importante que la différence entre deux sites se trouvant à 1 et 2 km du bord de glace. Au-delà de 55 km, l‟effet de la glace devient insignifiant et ne change pas avec distance. Un autre variable discrète est la masse d‟eau d‟où provient un échantillon. Dans les analyses multivariables, les variables discrètes prennent des valeurs de zéro ou un selon leur catégorie.

1.08.2. Analyses de correspondance et de chemin L‟analyse de correspondance trouve des relations entre les paires de variables. Par contre, le chercheur doit toujours garder à l‟esprit que ces relations ne signifient aucune rélation de cause à effet, surtout en ce qui concerne les variables environnementales où leur interdépendance peut masquer les vrais mécanismes de causalité sous-jacents. La correspondance partielle, définie comme

la correspondance entre deux variables si toutes les autres variables dans l‟ensemble sont fixées à leurs moyens, peut servir pour démêler ces relations. Le chercheur peut formuler des hypothèses comme suit : « L‟effet de la variable A sur la variable B est dû à son effet sur la variable intervenante C ». Ces hypothèses sont ensuite testées par comparaison entre les coefficients de correspondance et correspondance partielle. De plus, avec l‟inclusion des coefficients de régression, il est possible de partitionner ces effets entre les variables de façon quantitative, ce qui s‟appelle l‟analyse de chemin (en anglais path analysis). Il est à noter que ces hypothèses causales sont moins puissantes car elles sont construites a posteriori. Néanmoins, l‟exigence de les construire peut se voir comme un avantage car cela force le chercheur à s‟adresser, de façon explicite et mécaniste, à la biologie du système (Legendre et Legendre 1998).

1.08.3. Analyse canonique de correspondance Les techniques d‟ordination visent à représenter en façon bidimensionnelle les relations entre l‟abondance des taxons et les variables environnementales. Elles définissent des axes formés de combinaisons linéaires de toutes les variables environnementales et qui donnent la meilleure séparation des taxons dans cet espace bidimensionnel. Plus particulièrement, l‟analyse canonique de correspondance (ACC) suppose que chaque taxon a une valeur optimale pour chaque variable environnementale, c‟est-à-dire, que les taxons et les variables environnementales suivent une relation unimodale au lieu de linéaire. Cette rélation peut être vérifiée en regardant les données (ter Braak and Šmilauer 1998) et est généralement très plausible pour des systèmes biologiques.

Bien qu‟il n‟y ait pas une limite formelle au nombre de variables dans l‟analyse, trop de variables la rendre difficile à interpréter. Une étape initiale de sélection est donc cruciale. Parmi les différentes méthodes de sélection, un des plus populaires est la sélection ascendante. Cette méthode choisit les variables qui contribuent le plus à la variabilité de l‟abondance des taxons. Une fois choisie, chaque variable est enlevée du modèle et les contributions des autres variables sont recalculées. Le chercheur doit être conscient du fait que la sélection ascendante n‟est pas un test rigoureux de l‟importance des variables car elle procède à des testes multiples qui gonflent le taux d‟erreur Type I (Blanchet et al. 2008). Le bon sens dû à la connaissance biologique est le critère qui devrait ultimement primer dans la sélection des variables environnementales.

Comme l‟analyse de correspondance discutée ci-dessus, l‟ACC a un pouvoir limité pour tester les hypothèses, mais peut aider à les construire.

9 1.09. Région d’étude Le tableau 1.1 présente une liste des sites d‟échantillonnage, et les méta-données associées, pour les trois articles de cette thèse. L‟échantillonnage a eu lieu au cours de différentes missions dans l‟Arctique, et se concentrait dans cinq régions avec des caractéristiques physiques distinctes : le nord de la Mer de Baffin, l‟Archipel Arctique Canadien, la Mer de Beaufort, le Bassin du Canada, et la Mer des Tchouktches (Figure 1.1). Bien que la disposition des masses d‟eau varie beaucoup à travers l‟Arctique, la plupart des régions sont caractérisées par (de la surface vers le fond): 1) une couche de mélange superficielle; 2) une couche d‟Eau d‟Hiver plus froide et saline, parfois d‟origine Pacifique; 3) l‟Eau Atlantique chaude et encore plus saline; 4) les eaux froides du fond, dont la provenance varie selon la région (Melling et Moore 1995; Bâcle et al. 2002; Lazier et al. 2002; McLaughlin et al. 2002; Prinsenberg et Hamilton 2004; Hamilton et al. 2008; et les références dans les sections ci-dessous).

1.09.1. Nord de la Mer de Baffin La Mer de Baffin est caractérisée par un entrelacement extensif entre les masses d‟eau dans la région frontale entre le courant chaud du Groenland occidental, s‟écoulant vers le nord, et le courant froid du Labrador, s‟écoulant vers le sud (Lovejoy et al. 2002). En hiver, un barrage de glace se forme à travers le Détroit de Nares, qui communique avec l‟Océan Arctique au nord, de sorte qu‟il empêche la glace d‟entrer dans la mer. En dessous du barrage les vents poussent la glace vers le sud lorsqu‟elle se forme, créant une région libre de glace, appelé une polynie (Tang et al. 2004). Cette eau libre de glace permet la persistance d‟un haut niveau de biomasse photosynthétique (Lewis et al. 1996), de la productivité primaire et secondaire, des oiseaux et des mammifères marins (Stirling 1980).

1.09.2. Archipel Arctique Canadien L‟Archipel Arctique Canadien inclut une importante aire complexe de détroits et de chenaux. Cependant, les études décrites dans cette thèse portent seulement sur le Chenal Parry, spécifiquement les détroits interconnectés de Vicomte Melville, Barrow et Lancaster. Ce chenal est couvert de banquise fixée à la côte qui provient de glace localement formée, ainsi que de glace exportée des autres régions par les vents et les courants. Selon les conditions dans le chenal ainsi que dans les régions avoisinantes, cette glace peut persister au long de l‟année, ou peut se disperser vers la fin de l‟été (Howell et al. 2009). La dérive de glace par les courants dans ce chenal se fait vers l‟est (Welch et al. 1992).

1.09.3. Mer de Beaufort La plupart de la Mer de Beaufort est très oligotrophe, sauf une partie du Golfe Amundsen au sud- est, caractérisée par des niveaux plus hauts de nutriments et de productivité primaire (Ardyna et al. 2011). Une caractéristique du sud de la Mer de Beaufort est la polynie récurrente du Cap Bathurst aux alentours de l‟Île Banks (Stirling 1980), et les chenaux de séparation le long de la côte, créés par la rotation anticyclonique de la banquise dans la Gyre de Beaufort (voir la discussion du Bassin du Canada ci-dessous). Ces chenaux restent ouverts pendant l‟hiver. En été, les eaux de surfaces de la Mer de Beaufort sont aussi influencées jusqu‟à une centaine de kilomètres au large de la côte par le panache d‟eau douce et turbide du Fleuve Mackenzie (Carmack et Macdonald 2002).

1.09.4. Bassin du Canada Le Bassin du Canada, dont la Mer de Beaufort constitue la partie sud, est dominé par une circulation anticyclonique, appelée la Gyre de Beaufort. La plongée d‟eau produite par cette circulation approfondit la nitracline, ce qui fait que la plupart de la biomasse se trouve à un SCM situé à 60 m ou plus de profondeur (McLaughlin et Carmack 2010). Le Bassin du Canada reste couvert par la banquise centrale de l‟Arctique pendant la plupart de l‟année, mais une partie est découverte par le retrait du bord de glace durant la saison de fonte, de juillet à septembre. Dans les dernières années, l‟ampleur de la zone libre de glace a augmenté, et le bord de la glace peut maintenant se trouver à plus de 80°N vers la fin de l‟été (Service Canadien des Glaces; URL : http://www.ec.gc.ca/glaces- ice).

1.09.5. Mer des Tchouktches La mer des Tchouktches recouvre un plateau continental très peu profond, moins de 60 m sur la plupart de sa superficie. L‟eau est mélangée jusqu‟au fond par les vents de surface (Woodgate et al. 2005). Elle est très productive, avec des exports importants de la surface vers le benthos (Grebmeier et al. 2006). Deux courants entrent dans la mer des Tchouktches par le Détroit de Bering: le courant Alaska sur la côte Est, pauvre en nutriments, et le courant Anadyr sur la côte Ouest, très riche en nutriments. La mer des Tchouktches reste couverte par la glace la plupart de l‟année. Les polynies commencent à paraître en juin, et deviennent continues avec l‟eau libre de la Gyre de Beaufort vers la fin août (Stringer et Groves 1991).

1.10. Plan de la thèse Les trois chapitres de cette thèse consistent en trois articles qui examinent le rôle des facteurs environnementaux qui déterminent la répartition des taxons HF. Elle procède de la spécifque à la

11 générale : d‟une étude sur un seul genre, continuant avec une étude d‟un groupe majeur des HF, pour terminer avec une étude de l‟ensemble des HF dans l‟Arctique.

Article I — Distribution and diversity of a protist predator Cryothecomonas (Cercozoa) in Arctic Marine Waters (« Répartition et diversité d’un prédateur protiste Cryothecomonas (Cercozoa) dans les eaux arctiques marines »)

Publication: Journal of Eukaryotic Microbiology 59: 291–299, 2012.

Cet article décrit la répartition du genre HF Cryothecomonas dans l‟Arctique pendant une période de cinq ans (2006–2010). Les relations phylogénétiques entre les représentants en culture et les séquences environnementales, incluant des séquences provenant de nouvelles banques de clones, ont été examinées pour la première fois et utilisées pour concevoir une nouvelle sonde oligonucléotide ciblant ce genre pour la technique du FISH. Les cellules de Cryothecomonas étaient comptées dans les échantillons environnementaux, et les analyses de correspondance simples et partielles étaient utilisées pour regarder les relations avec les variables environnementales. Les objectifs de ce chapitre étaient :

1) Réactualiser la phylogénie de Cryothecomonas afin de vérifier l‟identification des séquences environnementales dans les bases de données.

2) Déterminer si les Cryothecomonas dans l‟Arctique sont des espèces brouteurs ou parasitoïdiques, en se basant sur les analyses phylogénétiques et les expériences de broutage.

3) Identifier les facteurs environnementaux qui influencent la répartition de Cryothecomonas.

Article II — Environmental selection of marine stramenopile clades in the Arctic Ocean and coastal waters (« Sélection environnementale des clades de straménopiles marins dans l’Océan Arctique et les eaux côtières »)

Publication : Polar Biology, 2013

Cet article utilise également la technique de FISH pour décrire la répartition géographique de trois sous-clades apparentés de MAST, MAST-1A, -1B et -1C, dans différentes régions de l‟Arctique de 2007 à 2008. Une analyse multivariée était utilisée pour examiner les relations avec les variables

environnementales. La phylogénie était également réactualisée afin d‟identifier les groupes spécifiques aux différents environnements. L‟objectif de ce chapitre était de détecter les différences entre la répartition des trois sous-clades le long des gradients environnementaux.

Article III — Communautés distinctes des flagellés hétérotrophes dans les régions différentes de l’Arctique

Cet article présente une méta-analyse de données de cinq études différentes, quatre de la colonne d‟eau et une de la glace de mer, par l‟utilisation du pyroséquençage 454. Trois études étaient tirées du sud de la Mer de Beaufort et le Golfe Amundsen, une du Bassin du Canada, et une de la Mer des Tchouktches. Ce chapitre compare la proportion des séquences identifiées dans les groupes HF connues (Cryomonadida, MAST, Picozoa, choanoflagellés, et Telonemia) et analyse ces données dans le contexte des variables environnementales. Cryomonadida, Picozoa, choanoflagellés et Telonemia étaient examinés avec un placement phylogénétique plus fin. Les objectifs de cette étude étaient :

1) Comparer la communauté HF dans les régions différentes de l‟Arctique, et les facteurs environnementaux responsables des différences entre ces régions.

2) Vérifier l‟attribution taxonomique des séquences courtes à partir du placement phylogénétique pour certains taxons HF.

13 Table 1.1 Méta-données pour les stations d‟échantillonnage dans cette thèse. Canadian Arctic Shelf Exchange Study 2003–2004 :

Station Date Latitude (°N) Longitude (°W) Chapitre

CA-15 2003/10/10 71.5367 126.9555 4

200 2003/11/04 69.929 126.4887 4

200 2004/07/16 70.0453 126.3025 4

200 2004/08/06 70.0418 126.2608 4

ArcticNet 2005 :

Station Date Latitude (°N) Longitude (°W) Chapitre

CA-18 2005/09/12 70.6663 -122.993 4

ArcticNet 2006 :

Station Date Latitude (°N) Longitude (°W) Chapitre

BA04-05 2006/10/01 75.2727 74.978 2 132 2006/09/06 78.9955 72.3332 2 129 2006/09/11 78.3292 74.0145 2 126 2006/09/12 77.3468 73.4225 2 123 2006/09/13 77.3413 74.6395 2 118 2006/09/14 77.34 76.949 2 115 2006/09/15 76.3231 71.1688 2 109 2006/09/18 76.2546 74.1731 2 101 2006/09/18 76.3823 77.4438 2 301 2006/09/20 74.124 83.3443 2 308 2006/09/24 73.5073 103.4832 2 Table 1.1. Méta-données pour les stations d‟échantillonnage dans cette thèse (suite)

ArcticNet 2006 (suite) : Station Date Latitude (°N) Longitude (°W) Chapitre 310 2006/09/25 71.4987 102.2413 2 405 2006/10/01 70.6511 -122.9483 4

Canada’s Three Oceans (C3O) 2007–2008 : Station Date Latitude (°N) Longitude (°W) Chapitre LS2 2007/07/07 54.2543 54.1005 2, 3 LS4 2007/07/08 58.4836 53.6623 2, 3 LS7 2007/07/10 66.0017 57.6666 2, 3 BB1 2007/07/11 68.1953 56.4188 2, 3 BB5 2007/07/12 68.8308 61.7605 2, 3 BB8 2007/07/13 68.0908 64.0000 2, 3 BB10 2007/07/14 71.5651 65.3994 2, 3 BEW11 2007/07/16 72.3846 73.8938 2 CAA1 2007/07/17 74.1411 81.5537 2 CAA2 2007/07/17 74.2177 85.6500 2 CAA5 2007/07/20 73.5258 85.5086 2 CAA6 2007/07/22 71.9487 94.2889 2 CAA10 2007/07/22 70.6508 98.5883 2 CAA12 2007/07/24 68.6795 103.9175 2 CAA16 2007/07/28 68.382 113.115 2 BFB-5 2008/07/26 71.3297 133.7657 4

Canada Basin 2007 : Station Date Latitude (°N) Longitude (°W) Chapitre CB-4 2007/08/06 74.9183 150.1585 2 CB-9 2007/08/10 77.9348 149.8262 2 CB-10a 2007/08/11 78.3222 154.0436 2 CB-11b 2007/08/12 79.9915 149.9893 2 CB-15 2007/08/15 76.999 140.1874 2, 3, 4 CB-15 2007/08/18 76.9688 140.075 2, 3, 4

Table 1.1. Méta-données pour les stations d‟échantillonnage dans cette thèse (suite)

15 Canada Basin 2007 (Suite): Station Date Latitude (°N) Longitude (°W) Chapitre PP-6.5 2007/08/19 76.0565 132.481833 4 PP-2 2007/08/20 75.8447 128.6422 2, 3, 4 CB-17.5 2007/08/21 75.6501 139.7168 2, 3, 4 CB-21 2007/08/23 73.967 140.088 2

Circumpolar Flaw Lead Study 2007–2008 : Station Date Latitude (°N) Longitude (°W) Chapitre 405 2007/11/19 70.6217 123.0014 4 D22 2008/02/18 71.3108 124.4966 2 D26 2008/02/25 70.9341 123.9226 2 D27 2008/03/02 70.7905 123.0694 2 D29 2008/03/10 71.0389 123.9108 2 D33 2008/03/28 71.064 121.7867 2 D38 2008/04/12 71.245 124.6117 2 FB1 2008/06/14 69.9838 125.8527 2 FB3 2008/06/14 69.968 125.8699 2 FB5 2008/06/15 69.9563 125.875 2 434 2008/06/20 70.1779 133.5542 2 421 2008/06/20 71.4725 133.9029 2 435 2008/07/02 71.0789 133.9776 2 6006 2008/07/04 72.6588 128.3601 2 410 2008/07/08 71.6947 126.4948 2 420 2008/07/08 71.0506 128.5108 2 416 2008/07/10 71.2884 127.7568 2 405 2008/07/21 70.6936 122.9173 2, 3 CA04.08 2008/07/31 71.0706 133.5682 3

Table 1.1. Méta-données pour les stations d‟échantillonnage dans cette thèse (suite) Échantillons de glace de mer 2008 : Station Date Latitude (°N) Longitude (°W) Chapitre D32 2008/03/22 71.064 121.787 4 D41-1 2008/04/19 70.597 121.864 4 F1-L 2008/05/08 70.182 124.831 4 F1-M 2008/05/08 70.182 124.831 4 F2-1 2008/05/16 69.947 126.172 4 D46 2008/05/30 71.574 125.218 4

ArcticNet 2008 : Station Date Latitude (°N) Longitude (°W) Chapitre 303 2008/09/07 74.2378 89.6578 3 134 2008/09/09 74.3035 80.0015 2, 3 138 2008/09/11 74.9333 69.0667 2 115 2008/09/12 76.3285 71.2743 2 115 2008/09/13 76.3287 71.2248 2, 3 108 2008/09/14 76.267 74.5793 2, 3 101 2008/09/15 76.3587 77.5056 2, 3 126 2008/09/18 77.3467 73.4245 3 233 2008/09/20 76.7362 71.828 2 141 2008/09/22 73.8713 74.2887 2, 3

Malina 2009 : Station Date Latitude (°N) Longitude (°W) Chapitre 690 2009/08/01 69.4553 137.9388 2 280 2009/08/04 70.8807 130.5285 2 110 2009/08/06 71.6973 126.4783 2 170 2009/08/07 70.9139 128.9182 2 380 2009/08/09 70.3964 133.6092 2 670 2009/08/10 69.7974 138.4374 4 620 2009/08/11 70.6806 139.6215 4 760 2009/08/12 70.554 140.7963 2, 4

17 Table 1.1. Méta-données pour les stations d‟échantillonnage dans cette thèse (suite) Malina 2009 (Suite) : Station Date Latitude (°N) Longitude (°W) Chapitre 540 2009/08/17 70.7524 137.8774 2, 4 430 2009/08/18 71.2193 136.7127 4 460 2009/08/19 70.6771 136.0565 2, 4 135 2009/08/20 71.3123 127.489 2 135 2009/08/21 71.3115 127.4946 4

ArcticNet 2009 : Station Date Latitude (°N) Longitude (°W) Chapitre 437 2009/10/12 71.7957 126.4928 2 408 2009/10/13 71.3162 127.5914 2 405 2009/10/15 70.3145 122.9981 2, 4 304 2009/10/24 74.3149 91.3825 2 103 2009/10/27 76.3429 76.589 2 105 2009/10/28 76.2974 75.7629 2 115 2009/10/29 76.3362 71.2458 2 141 2009/11/01 71.7833 70.1438 2

ArcticNet 2010 : Station Date Latitude (°N) Longitude (°W) Chapitre 437 2010/10/01 71.7833 126.5974 2 408 2010/10/06 71.3119 127.5476 2 407 2010/10/07 71.0079 125.991 2 405 2010/10/08 70.6357 123.0386 2, 4 450 2010/10/09 72.0517 119.7765 2 308 2010/10/11 74.1032 108.413 2 304 2010/10/12 74.216 91.5033 2 323 2010/10/14 74.1987 79.7482 2 115 2010/10/16 76.3452 71.1821 2 111 2010/10/16 76.3081 73.2555 2 108 2010/10/17 76.2567 74.781 2

Table 1.1. Méta-données pour les stations d‟échantillonnage dans cette thèse (suite) ArcticNet 2010 (Suite) : Station Date Latitude (°N) Longitude (°W) Chapitre 105 2010/10/17 76.3138 75.8517 2

Chukchi Sea ICESCAPE 2010 : Station Date Latitude (°N) Longitude (°W) Chapitre BS1 2010/06/18 65.68552 168.66879 4 AN1 2010/06/19 65.988 168.92345 4 KS6 2010/06/21 67.34343 166.80692 4 CHA1 2010/06/21 67.67672 168.96233 4 EC5 2010/06/24 70.35948 163.98582 4 HLY 2010/06/29 70.7044 168.92262 4 CC18 2010/07/01 70.09609 163.367663 4 CN3 2010/07/07 72.3879 168.19098 4 CN14 2010/07/01 71.67696 164.01634 4 BCH7 2010/07/08 71.05104 159.48807 4 IE 2010/07/10 71.73346 156.10189 4 HSN5 2010/07/14 72.62484 162.65586 4

Figure 1.1. Carte des régions de l‟Arctique étudiées dans cette thèse

Chapter 2 : Distribution and Diversity of a Protist Predator Cryothecomonas (Cercozoa) in Arctic Marine Waters

Résumé Les flagellés hétérotrophes (HF) sont des composants clés dans les réseaux trophiques microbiens, et peuvent potentiellement influencer la composition de la communauté via un contrôle par le haut de leurs proies ou hôtes préférés. Les cercozoaires Cryothecomonas sont des espèces HF marines parasitoïdiques et prédateurs qui ont été rapportées de la glace de mer, des sédiments, et la colonne d‟eau. Bien que Cryothecomonas soit fréquemment rapporté dans les mers arctiques et subarctiques, les facteurs qui déterminent son occurrence ne sont pas connus. Nous avons étudié la répartition temporelle et géographique de Cryothecomonas dans les mers arctiques canadiennes pendant les périodes d‟été et d‟automne de 2006 à 2010. Nous avons conçu un sonde pour la technique de l‟hybridation fluorescente in situ (FISH) spécifique à Cryothecomonas, ciblant l‟ARNr 18S ribosomique pour estimer les concentrations des cellules dans les échantillons naturels et manipulés. Une comparaison des coefficients de corrélation simple et partielle a montré que la salinité, la profondeur, et la biomasse de l‟ensemble de la communauté sont des facteurs importants pour déterminer l‟abondance de Cryothecomonas. Nous n‟avons pas trouvé d‟évidence de parasitisme dans nos échantillons. Les cellules hybridées ont montré des individus plus petits que tous les Cryothecomonas formellement décrits à ce jour, ce qui suggère la présence de taxons nouveaux ou de stades de vie inconnus dans ce genre. Une association positive entre l‟abondance des Cryothecomonas, la glace et l‟eau de fonte suggère qu‟il est un indicateur sensible à la fonte des glaces dans la colonne d‟eau de l‟Arctique.

21 Abstract Heterotrophic flagellates (HF) are key components in microbial food webs, potentially influencing community composition via top-down control of their favoured prey or host. Marine cercozoan Cryothecomonas species are parasitoid and predatory HF that have been reported from ice, sediments, and the water column. Although Cryothecomonas is frequently reported from Arctic and subarctic seas, factors determining its occurrence are not known. We investigated the temporal and geographic distribution of Cryothecomonas in Canadian Arctic Seas during the summer and autumn periods from 2006-2010. We developed a Cryothecomonas-specific fluorescent in situ hybridization (FISH) probe targeting ribosomal 18S rRNA to estimate cell concentrations in natural and manipulated samples. Comparison of simple and partial correlation coefficients showed that salinity, depth, and overall community biomass are important factors determining Cryothecomonas abundance. We found no evidence of parasitism in our samples. Hybridized cells included individuals smaller than any formally described Cryothecomonas, suggesting the presence of novel taxa or unknown life stages in this genus. A positive relationship between Cryothecomonas abundance and ice and meltwater suggests that it is a sensitive indicator of ice melt in Arctic water column.

2.01. Introduction The importance of heterotrophic nanoflagellates (HF) in aquatic food webs is well recognized (Arndt et al. 2000; Sherr and Sherr 2002). However, the taxonomic diversity, distribution, and ecology of these protists in marine environments remain little known. Taxon-specific differences in feeding behaviour, population dynamics, and life histories may have significance over broad ecosystem scales (Weisse 2002). Cryothecomonas is a HF genus that is often reported from polar and other cold marine waters, either in the sea-ice or the water column, with two major feeding strategies reported. Most described species ingest living particles: Cryothecomonas armigera feeds on diatoms and on the dictyochophyte Pseudopedinella tricostata, while the digestive vacuoles of Cryothecomonas scybalophora have been observed to contain protists and bacteria (Thomsen et al. 1991). However, the genus also includes a putative parasitoid species, the morphologically distinct Cryothecomonas aestivalis, which is found inside diatom frustules (Hoppenrath and Leander 2006). The persistent appearance of Cryothecomonas-related sequences in Arctic clone libraries suggests that this genus may be an important predator in Arctic microbial food webs. Because of the functional diversity of this genus, information on the diversity and distribution of Cryothecomonas over time and space will add to our understanding of their potential trophic role.

Cryothecomonas is sporadically reported from the water column, and concentrations are highly variable (Sime-Ngando 1997a; Thomsen et al. 1991; Tillmann, Hesse and Tillmann 1999). Thomsen et al. (1991) suggested that this might be an opportunistic taxon, capable of high growth rates when environmental conditions permit. For a parasitoid species, the presence of a suitable host would be a prerequisite for reaching significant abundances. However, factors that limit or promote growth of free-living Cryothecomonas are unknown. Abundances of free-living HF generally are controlled by both grazing and resource availability in marine systems (Kuparinen and Bjørnsen 1992; Weisse and Scheffel-Möser 1991). Therefore we predicted first, that the presence of heterotrophic protists, including ciliates and dinoflagellates, which are potential predators and competitors for the same resources, would influence the abundance of Cryothecomonas. Second, we predicted that presence of potential prey, including small phytoplankton and bacteria, or in the case of parasitoid taxa, diatoms or other hosts, would promote its occurrence. It follows that physical factors that influence prey abundance, such as nutrient and light availability required for photosynthetic production, and subsequent release of substrates for bacterial growth, would also be significant factors for predicting Cryothecomonas occurrence both directly and indirectly.

23 The goals of this study were first, to identify the phylogenetic relationships among environmental sequences and cultured Cryothecomonas and second, to infer key environmental factors in Arctic marine water columns that could influence the growth and ecology of Cryothecomonas. We used publicly available sequences as well as sequences from new Arctic clone libraries. The resulting phylogenetic analysis enabled us to design an oligonucleotide probe for fluorescent in situ hybridization (FISH) specifically targeting this genus. We then applied FISH to samples collected over five years from across the Canadian Arctic including the Canada Basin, Beaufort Sea, Canadian Archipelago, Northern Baffin Bay, and the Labrador Sea. We used simple and partial correlation analysis to analyze the distribution of Cryothecomonas, identify factors determining its abundance, and infer the presence of grazers versus putative parasitoid species.

2.02. Materials and Methods

2.02.1. Sample collection Samples for DNA analysis, FISH, microscopy, and chlorophyll a (chl a) were collected on board the CCGS Amundsen during the ArcticNet Expeditions in 2006 and 2008–2010. Additional samples were from the 2008 International Polar Year (IPY) Circumpolar Flaw Lead Study, the MALINA Project in 2009, and from the CCGS Louis St-Laurent in July 2007 during the IPY Canada‟s Three Oceans (C3O) Expedition (Figure 2.1). Samples were collected directly into clean, rinsed carboys from 12-liter Niskin-type bottles (Ocean Test Equipment, Fort Lauderdale, FL) mounted on a shipboard-deployed rosette. Conductivity (C), temperature (T), and depth (D) were recorded using a SB9 CTD (SeaBird, Bellingham, WA). Other instruments on the rosette system recorded fluorescence (Seapoint, Exeter, NH), photosynthetically available radiation (PAR; Biospherical Instruments, San Diego, CA), pH (Seabird), and relative nitrate concentrations (Satlantic In-Situ Ultraviolet Spectrometer, Halifax, Nova Scotia). Oxygen values from the CTD were calibrated potentiometrically from samples taken at discrete depths (Granéli and Granéli 1991). Nutrient samples collected aboard the Amundsen were taken from the same cast and depths. Concentrations - 3- of nitrate (NO3 ) and phosphate (PO4 ) were determined on board with a Bran and Luebbe Autoanalyzer III (Delavan, WI) with routine colorimetric methods (Grasshoff, Kremling, and Ehrhardt 1976) and a detection limit of 0.03 µM. Nutrient samples collected aboard the Louis St- Laurent were analyzed using a Technicon Autoanalyzer (Folio Instruments, Montreal, Quebec) following Barwell-Clarke and Whitney (1996), with a detection limit of 0.09 µM.

Total chl a concentrations were estimated following filtration of 0.5–1 liter of seawater onto GF/F filters (Whatman, Sanford, ME). The < 3-µm size fraction was estimated from a separate 0.5–1 liter

that had been gravity filtered through a 3-µm pore size polycarbonate filter (AMD Manufacturing, Mississauga, Ontario) prior to filtration onto the GF/F filters. All filters were stored at –80°C until extraction in 95% ethanol at 70°C for 5 min, with the exception of chl a samples from the MALINA cruise, which were extracted in 90% acetone (Nusch 1980). Concentrations were determined by spectrofluorometry (Cary Eclipse, Agilent Technologies, Santa Clara, CA)

Samples for estimation of plankton biomass by microscopy were initially fixed in 1% (v/v) glutaraldehyde (Canemco, Gore, Quebec) for 1–24 h in the dark at 4°C. For eukaryote biomass, 50 ml were filtered by vacuum filtration onto a 0.8-µm pore size, 25-mm diameter black polycarbonate (PC) filter (AMD Manufacturing) and incubated for 5 min with 4‟,6-diamidino-2- phenylindole (DAPI; a stain for DNA, Porter and Feig 1986) at a final concentration of 50 µg ml-1. For bacterial biomass, 15 ml were filtered onto a 0.2-µm pore size filter. Filters were mounted on slides using a drop of non-fluorescent immersion oil and stored at –20°C until they could be examined.

Samples for FISH were fixed immediately in 3.7% (v/v) formaldehyde and kept in the dark at 4C for 6–24 h. Either 50 or 90 ml of fixed sample were filtered by vacuum filtration through a 25-mm diameter PC filter of pore size 0.8 µm (AMD Manufacturing) and rinsed twice with 5 ml of filtered milli-Q water. Filters were allowed to air dry and stored at –20C.

Clone libraries were constructed from 3 samples collected in 2008 from the Beaufort Sea, (depth 52 m; latitude 70º 41.61 N, longitude 122º 55.04 W), Lancaster Sound (depth 2 m; latitude 74º 18.21 N, longitude 80º 00.89 W) and Northern Baffin Bay (depth 2 m; latitude 76º 19.72 N, longitude 71º 13.49 W) (Figure 2.1). Genomic DNA was collected by sequentially filtering 6 liters of seawater through 50-m nylon mesh, a 3-m pore size, 47-mm diameter polycarbonate (PC) filter (AMD Manufacturing), and a 0.22-m pore size Sterivex cartridge (Fisher Scientific, Billerica, MA). The 0.2–3-µm size fraction was subsequently used for clone library construction, as preliminary clone libraries from the > 3 µm fraction had not retrieved Cryothecomonas-related sequences, whereas other libraries from the smaller fraction consistently retrieved Cryothecomonas (Lovejoy et al. 2006). This method of size fractionation is imperfect, and although the resulting libraries are enriched in sequences belonging to smaller cells, larger, fragile cells are always detected, probably because of breakage (Terrado et al. 2009). Buffer (50 mM Tris•HCl pH 8.3, 40 mM EDTA pH 8.0 and 0.75 M sucrose) was added to the Sterivex cartridge, which was stored at –80C until DNA was extracted.

25 In October 2010, grazing experiments were conducted in the Beaufort Sea, Northwest Passage, and Northern Baffin Bay (North Water) on board the CCGS Amundsen. Seawater was collected as described above for other samples, and 4.5 liters of seawater were immediately filtered through a 50-µm mesh to remove large grazers and kept in the dark at 4 °C until the experiment began, within 2–3 h.

2.02.2. DNA extraction and cloning Salt-extraction of genomic DNA from the < 3-µm size fraction was adapted from Aljanabi and Martinez (1997) using an initial incubation with 1.1 mg ml-1 lysozyme (Sigma-Aldrich, St. Louis, MO) at 37°C for 45 min, and 0.2 mg ml-1 proteinase K (Invitrogen, Carlsbad, Germany) with 1.11% SDS at 55 °C for 1 h. The Sterivex was then emptied into a 15-ml centrifuge tube and rinsed with 1 ml lysis buffer. The contents were added to the 15-ml tube after being held at 55°C for 15 min. Cell debris was precipitated by the addition of 2.3 M NaCl and centrifugation for 10 min at 17 000 g. Finally, the supernatant was transferred to a new tube and precipitated with cold 70% ethanol; the precipitate was rinsed once with ethanol. DNA was resolubilised in 1X TE buffer (10 mM Tris•HCl pH 8.3, 1 mM EDTA pH 8.0) and stored at –80°C.

For clone library construction, the 18S rRNA gene was amplified in a 25-µl reaction volume with 0.2 mM dNTPs, Taq DNA polymerase (Feldan Bio, Montréal, Quebec), 0.4 mg ml-1 bovine serum albumin, and 0.5 M each of primers NSF4/18 (Henriks et al. 1989) and EukR (Medlin et al. 1998) (Fermentas, Burlington, Ontario). The PCR reaction consisted of an initial step of 3 min at 94C, followed by 30 cycles of denaturation at 94C for 45 s, annealing at 50C for 1 min and extension at 72C for 3 min, and finally 10 min of extension at 72C. Amplicon size (i.e. ~ 1700 bp) and PCR product quality were verified by gel electrophoresis. PCR products were then purified using a QIAquick PCR Purification Kit (Qiagen, Germantown, MD). PCR products were cloned using either the TOPO TA Cloning Kit (Invitrogen, Carlsbad, Germany) or the Stratagene Cloning Kit (Stratagene, Cedar Creek, TX). Ligation and transformation were performed according to the manufacturer‟s protocols. Positive clones were picked and transferred to 96-well plates containing 200 l Luria-Bertani (LB) medium with 8% glycerol, and plates were stored at –80°C.

Eight clone libraries from samples collected in 2008 were screened as in Diez et al. (2001), using Restriction Fragment Length Polymorphism (RFLP) analysis following digestion with HaeIII (New England BioLabs, Ipswich, MA). These digests were run on a 2.5% low-melting point agarose gel and visualized using the BIORAD Gel Doc imaging system and Quantity One software (BIORAD version 4.5.1). At least one clone was sequenced for each unique RFLP pattern, with more

sequenced for common patterns. Clones were sequenced using primers NSF4/18, Euk528f (Hendriks et al. 1989), and Euk1055f (Elwood et al. 1985) by the Centre de Recherche du Centre Hospitalier d l‟Université Laval with an ABI 3730xl system (Applied Biosystems, Foster City, CA), which included a purification step. The 18S rRNA gene sequences were deposited in GenBank under accession numbers JN048118–JN048125 and JN390437.

2.02.3. Phylogenetic analysis Clone sequences from the three sequencing primers were assembled using eBiox (Lagercrantz 2008) and verified manually, resulting in 1700–1800 bp sequences. Cercozoan sequences were initially identified by Key DNA Tools (Guillou et al. 2008). Suspected chimeras were checked by a Basic Local Alignment Search Tool (BLAST; Altschul et al. 1997) search of short sequence fragments, to check for consistency. A BLAST search using the entire sequence was used to retrieve other environmental clones with closest matches to cultured strains of the Cryomonadida genera Cryothecomonas, Protaspis, and Lecythium. In addition to new environmental sequences, 38 additional partial and complete 18S rRNA gene sequences from cultured and uncultured organisms were retrieved from the NCBI database. When two sequences from the same study were > 99% similar, only one was included. The two sequences U42446 and EF455776 of Thaumatomonas were used as outgroups. Sequences were aligned using MUSCLE (Edgar 2004), and the alignment was visually checked using eBiox.

Following alignment, a 1000-replicate bootstrapped neighbour-joining (NJ) tree was constructed using CLUSTALX (Thompson et al. 1997). In addition, a 1000-replicate bootstrapped maximum likelihood (ML) analysis was carried out using RAxML (Stamatakis 2006) with the general time- reversible model, using four discrete rate categories to approximate a gamma distribution. Finally, Bayesian analysis was carried out using MrBayes v.3.1.2 (Ronquist and Huelsenbeck 2003), using the same nucleotide substitution model as described for RAxML. Bayesian posterior probabilities were computed by running four chains for 1 000 000 generations using the program default priors. Trees were sampled every 100 generations in two independent runs. Two-thousand five-hundred trees were discarded from the burn-in phase of the analysis, so that only trees in the stationary phase of the run were considered. There was good agreement in tree topology between the Bayesian and ML analyses, although certain nodes were only resolved in one or the other method. The NJ analysis differed in the order of some deeper branches, but within the Cryothecomonas clade it agreed with the other two methods. Additional trees were constructed using an alignment of shorter sequences, in order to confirm the placement of shorter sequences from other studies (data not

27 shown). Sequence similarity within clades was determined using DOTUR 1.53 (Distance-based Operational Taxonomic Units and Richness Determination; Schloss and Handelsman 2005).

2.02.4. Probe design Probes were designed against the Cryothecomonas clade as defined by our phylogenetic analysis, using the Probe Design and Probe Check options of the ARB program package (Ludwig et al. 2004). Two potential probe sequences were selected for testing. HPLC-purified probes modified with a Cy3 fluorochrome at the 5-end were manufactured by ThermoFisher Scientific (Ulm, Germany) and diluted to 50 ng µl-1 according to the manufacturer‟s specifications.

2.02.5. Grazing experiments Grazing experiments were performed following Massana et al. (2009) with modifications. Triplicate 1.5-liter samples of seawater were pre-filtered through a 50-µm mesh, while 0.2-µm filtered seawater was used as a negative control. Samples and controls were kept at 4°C. Fluorescently-labeled bacteria (FLB) were prepared as in Sherr et al. (1987). Cell density was determined by epifluorescence microscopy, and cells were kept at –20°C until use. A known quantity of FLB, 30% of the natural density of bacterial cells as estimated by immediate examination of the DAPI-stained slides described above, was added to each replicate and control. FLB aliquots were sonicated for 10 min before being added to samples to prevent aggregation. Sub- samples of 90 ml were immediately taken from each replicate and fixed in 3.7% (v/v) formaldehyde (final concentration). Subsequent sub-samples collected at 45 min and 2 h were fixed in 0.37% (v/v) formaldehyde to prevent cells from ejecting FLB (Sieracki et al. 1987). Samples were fixed at 4°C for 6–24 h and then filtered as described above for FISH samples.

2.02.6. Fluorescent in situ hybridization The culture APCC MC5-1 Cryothecomonas from the Wood‟s Hole Antarctic Protist Culture Collection, Massachusetts was used as a positive control for hybridization with Cryothecomonas. This culture was maintained on 0.1% yeast extract in filtered seawater, plus a few sterile rice grains to sustain bacterial growth. To confirm that the culture was Cryothecomonas, the 18S rRNA gene was sequenced following direct amplification from the purified DNA. Filters for positive controls were made as described above for FISH samples.

FISH hybridizations were as in Pernthaler et al. (2001) with modifications. Briefly, to minimize loss of cells, all filters for FISH were coated with 0.1% agarose, allowed to dry at 37°C, and then briefly rinsed in ethanol before further manipulations. Much of the chl a was removed by this step.

Sections of filter were hybridized for 3 h at 46°C in hybridization buffer, and then washed in a second buffer at 48 °C. Filter sections were mounted on slides using a mixture of 77% (v/v) glycerol, 15% (v/v) Vectashield (Vector Laboratories, Peterborough, UK), and 8% (w/v) sodium phosphate buffered saline with 5 µg ml-1 DAPI as a counterstain. Probes were tested over a 10–70% gradient of formamide in the hybridization buffer at constant temperature (46 °C). The formamide concentration optimum was defined as the concentration where all hybridisable cells were hybridized; the next highest concentration tested (40%) resulted in a 10–15% reduction in the number of hybridized cells. The general eukaryotic probe Euk502 (Amann et al. 1990a) was used to confirm the efficacy of this protocol with Cryothecomonas.

Hybridized cells were visualized using an Olympus (Richmond Hill, Ontario) IX71 epifluorescence microscope at 1000X magnification, using a green excitation block specific for the Cy3 fluorochrome. We do not anticipate that naturally occurring autofluorescent pigments could have confused our results, as chlorophyll is not excited using this filter configuration. Although phycoerythrin fluoresces with green excitation, it is generally only present in cyanobacteria and cryptophytes, both of which are morphologically distinct. The average area of the filter section used for counting was 18.5 mm2 (standard deviation 4.3 mm2).

2.02.7. Environmental variables Sixteen environmental variables were examined with respect to the abundance of Cryothecomonas. Six represented potential food sources for Cryothecomonas: biomass of heterotrophic flagellates < 3 µm, biomass of phytoplankton < 3 µm and 3–6 µm, biomass of diatoms, total concentration of chl a, and chl a in the < 3 µm size fraction of the planktonic community. One variable, the total biomass of dinoflagellates plus heterotrophic flagellates 6–10 µm, represented potential predators and competitors. We also investigated nine physicochemical variables: depth, Julian day, salinity, temperature, PAR, dissolved oxygen, nitrate concentration, phosphate concentration, and distance to nearest ice edge. Distance to nearest ice edge was measured on ice charts obtained from the Canadian Ice Services archives (http://ice-glaces.ec.gc.ca/). Biomass was determined by counting cells on an epifluorescence Olympus IX71 microscope at 1000X magnification. Cells with DAPI- stained, intact nuclei were visualized under ultraviolet excitation. Cells with natural red fluorescence due to chlorophyll as visualized under blue excitation were considered photosynthetic. The cell density of each functional and size category was converted to carbon biomass using conversion factors given in Menden-Deuer and Lessard (2000).

29 Data were transformed by a Box-Cox power transformation (Box and Cox 1964), and Pearson correlation coefficients were calculated between Cryothecomonas abundance and all variables using the statistics package R (R Development Core Team 2008). The Pearson correlation coefficient is more robust than non-parametric methods for zero-inflated data (Huson 2007). For partial correlation analysis, the R package ggm (Marchetti 2006) was used to calculate Spearman‟s correlation coefficient on untransformed data, because the matrix of transformed data was computationally singular, making calculation of partial correlation coefficients impossible. Simple and partial correlations were compared to identify factors determining Cryothecomonas abundance. Based on correlation analysis, path analysis (Legendre and Legendre 1998) was used to test three causal models: distance to ice edge and salinity; temperature and depth; and total chl a, chl a < 3 µm, and phototrophs 3–6 µm.

Because of unequal sampling efforts, it was not possible to look at differences among years.

2.03. Results

2.03.1. Phylogenetic analysis A total of 415 clones was screened from eight 18S rRNA gene libraries. Cercozoa accounted for less than 4% of all sequences. Five sequences were found whose closest BLAST match to a cultured strain was a Cryothecomonas. Three of these were from the Beaufort Sea, one from Lancaster Sound, and one from Northern Baffin Bay. A total of 44 taxa, including outgroups, consisting of 1552 characters, were included in the phylogeny. We defined the Cryothecomonas clade to be the smallest clade with strong bootstrap support and clade credibility that contained the sequenced isolates of Cryothecomonas and unidentified environmental sequences, and did not contain cultured strains of other described genera (Figure 2.2). Sequences in the Cryothecomonas clade had a minimum similarity of 95% to each other over an approximately 1800-bp length as determined by DOTUR.

In NJ, Bayesian, and maximum-likelihood analyses, five monophyletic clusters were distinguished within the Cryothecomonas clade with high bootstrap support and posterior probability (Figure 2.2). All of these clusters except Cluster 1 contained sequences reported from sediment clone libraries. One sequence in Cluster 2 (DSGM-43) from a cold methane seep sediment clone library had an unusual motif in the V2 region (Figure 2.2). Sequences from Arctic clone libraries were found in Clusters 1, 3, 4 and 5 (Figure 2.2). The two cultured strains of the C. aestivalis (Figure 2.2) both fell into Cluster 2.

Phylogenetic analyses using shorter sequences placed other sequences in this Cryothecomonas clade, notably the clone from Arctic snow, DFCe1 (HQ230174; Harding et al. 2011). A few sequences whose highest BLAST match was to Cryothecomonas were retrieved from freshwater habitats, but none of these were in the Cryothecomonas clade, except for a sequence from a brackish coastal lagoon (NAMAKO-3).

2.03.2. FISH The probe Cryo1134 (5-AAA ACA ACG TTC ACC CAT C-3) matched all target sequences within the Cryothecomonas clade defined by our phylogenetic analysis, except the uncultured cercozoan clone DSGM-43. A BLAST search against the probe sequence uncovered a match with one group of glissomonads, an order of soil-dwelling cercozoans that is thought to be exclusively non-marine (Howe et al. 2009). The probe has at least three mismatches with all other non-target sequences in GenBank. The probe Cryo1156 (5-AGG TGC AGA TGA AGT CAA-3) matched all target sequences inside Cryothecomonas except for uncultured clones SS1 E 01 80 (Tian et al. 2009) and DSGM-43, and had no matches outside the group. Cryo1134 worked optimally at a formamide concentration of 30% while Cryo1156 required a formamide concentration of 20%. Cryo1134 was therefore used in all subsequent analyses to take advantage of the more stringent binding of a higher formamide concentration. The specificity of the probe was further inferred since in many cases no hybridized cells were detected in samples that otherwise had high numbers of protists, suggesting that non-specific binding of our probe did not occur. We do note, however, that unknown organisms with slight mismatches could exist, although such sequences have never been recovered from Arctic clone libraries.

The culture MC5-1 cells were mostly > 10 µm and oval to spindle-shaped, sometimes with a central constriction. A number of cells were dividing. Most cells were hybridized by both Cryo1134 and Cryo1156. However, ~ 1/3 of the cells could not be hybridized to any probe, including the nominally universal Euk502 (Amann et al. 1995). Unhybridized cells were more rounded, with a large, DAPI-stained nucleus. A number of permeabilization protocols were attempted to test whether the cell‟s theca was preventing probe uptake, including treatment with strong acid, detergents, microwaves, chitinase, and cellulase, but the fraction of unhybridized cells remained consistent. Attempts to visualize the theca using calcofluor white were also unsuccessful. CARD- FISH, a technique that increases the hybridization signal and is therefore used for small or slow- growing microorganisms (Pernthaler, Pernthaler, and Amann 2002), was also attempted, but failed to hybridize to the cellular content of the rounded cells.

31 A total of 863 Cryo1134-hybridized cells were observed in Arctic environmental samples collected over the 5-year period. Of these cells, only two were ever observed associated with diatom cells such that they may have been feeding on the larger cells. Cryo1134-hybridized cells ranged in size from 2.5–29 µm with variable shapes from round to oval (Figure 2.3, 2.4). Cells in the < 5 µm size fraction comprised up to 56% of hybridized cells in some years. A Kruskal-Wallis test found a significant effect of overall concentration of hybridized cells (i.e. factor levels < 1, 1–5, and > 5 cells ml-1) on cell size (p < 0.0001), such that median cell size is lowest at high concentrations. Cells generally contained as many as six or more dark, rounded bodies, possibly food vacuoles as noted by Thomsen et al. (1991). On a few occasions, coloured material was observed inside the vacuoles. A few large, hybridized cells were observed with condensed chromosomes similar to those of dinoflagellates. Since preliminary tests did not find important concentrations of Cryothecomonas in deep waters, we focused on samples from the subsurface chlorophyll maximum or, when there was no chlorophyll maximum, from the surface.

In three out of the five years a total of eleven elevated Cryothecomonas density events (> 5 cells ml- 1) were noted at sites widely dispersed throughout the Arctic (Figure 2.1). The maximum density was ~ 60 cells ml-1 at Station CAA1 at the eastern opening of Lancaster Sound in July 2007. Overall density of HF in this sample, as estimated from stained DAPI-stained slides, was 970 cells ml-1 for the 1–3 µm size fraction, 890 cells ml-1 for the 3–6 µm size fraction, and 680 cells ml-1 for the > 6 µm size fraction. In subsequent years, however, densities were quite low in the same region. Cryothecomonas were detected with the FISH probe at all sites where clone libraries recovered Cryothecomonas sequences except for Station 134 in 2008 (clone library LS16_16). The station where most sequences were recovered (i.e. Station 405 in 2008, clone libraries BF9_3 and BF9_20) had an exceptionally high concentration of Cryothecomonas as detected by FISH. In total, Cryothecomonas cells were detected at 54 of the 94 sampling stations examined.

Cryothecomonas abundance as determined by FISH was analysed along with 16 environmental variables using both correlation and partial correlation analysis. These data are available in the Polar Data Catalogue (polardata.ca, CCIN #10799). The significance and even the sign of correlation tended to change depending on the method used (Table 2.1). Path analysis found that 25% of the covariation with distance to ice edge was through its effect on salinity; 26% of the covariation with temperature was an indirect effect of depth; and 54% of the covariation with chl a < 3 µm was through its effect on total chl a.

Cryo1134-hybridized cells were present at Stations 437, 408, 304, and 323 of the seven sites selected for grazing experiments, at densities ranging from 0.27–1.2 cells ml-1. However, no cells were observed with FLB in their vacuoles.

2.04. Discussion

2.04.1. Phylogeny The higher taxonomic classification of Cryothecomonas within the Cercozoa has not been well resolved, but they consistently group with Protaspis and Lecythium (Chantangsi et al. 2010; Howe et al. 2011). As is the case for most pelagic heterotrophic protists, there are few living cultures or unequivocally defined reference sequences for this genus. Hence environmental sequences cannot be assigned to defined taxa at species levels, although they can be grouped phylogenetically (Countway et al. 2005; Gilg et al. 2010; Guillou et al. 2008; Šlapeta et al. 2006). Our phylogeny, which included all longer environmental sequences available (Dawson and Pace 2002; Lovejoy et al. 2006; Luo et al. 2009; Takishita et al. 2007a, 2007b), separated out a well-supported Cryothecomonas clade comprising six groups. Sequences within the clade were ≥ 95% similar, which falls within the range commonly regarded as genus level for free-living protists (Caron et al. 2009). With this in mind, we designed a genus-specific probe to record the distribution of Crythecomonas over the Canadian Arctic. This probe missed one sequence, DSGM-43. As this sequence was retrieved from a deep-sea methane cold seep (Takishita et al. 2007b), and similar sequences have never been retrieved from the Arctic, we are confident that we were able to detect all cryothecomonads in our samples.

2.04.2. Observations with FISH The FISH probe hybridized to morphologically diverse cells in the natural samples, including cells < 5 µm. Cell size of formally described species of Cryothecomonas ranges from 9–32 µm (Drebes et al. 1996; Thomsen et al. 1991). The large proportion of smaller Cryo1134-positive cells may be a novel species. Alternately, the small cells, which dominated at high Cryothecomonas densities, could also represent a swarmer or zoospore life-stage within this genus. A few cells were observed with condensed chromosomes, as has previously been reported for this genus (Thomsen et al. 1991). There was also morphological variation within the culture used as a positive control. About a third of cells in MC5-1 culture of Cryothecomonas resisted hybridization even by universal eukaryotic probes. A direct PCR of the 18S rRNA gene for this culture yielded one single product, implying no contamination by non-target protists. Some species of Cryothecomonas have a close- fitting theca, up to 200-nm thick (Thomsen et al. 1991), and we hypothesized that, if present, this

33 may have impeded access to cell contents by the FISH probes. However, in this case the enzymatic treatments tested should have increased the proportion of hybridized cells, as happens, for example, in thecate dinoflagellates (Palacios and Marín 2008), but it did not. Alternately, this non-hybridizing fraction may be a resting or cyst stage with low ribosomal activity and little 18S rRNA, such that no signal was observed even with CARD-FISH. Oligonucleotide probes can penetrate the protein- based cyst wall of Giardia lamblia (Metamonada) even without permeabilization, but will not hybridize when rRNA has been destroyed by RNase (Dorsch and Veal 2001). Cyst-like cells were noted in a culture of the parasitoid Cryothecomonas aestivalis (Drebes et al. 1996) and are common in related cercozoan orders such as Cercomonadida (Bass et al. 2009). Cysts, commonly found in dinoflagellates (de Vernal et al 2001; Montresor et al. 2003) and diatoms (von Quillfeldt et al 2000), may be an ecologically important strategy in polar regions, which have marked seasonal physical changes.

2.04.3. Distribution Our environmental gene surveys suggest that Cryothecomonas is restricted to marine environments, including sea ice, with two notable exceptions: a clone from Arctic snow (DFCe1, accession number HQ230174; Harding et al. 2011) and a clone from a brackish coastal lagoon (NAMAKO-3, accession number AB252743; Takishita et al. 2007a). Harding et al. (2011) retrieved sequences of many other marine taxa in the high Arctic snow samples, and suggested that they most likely arrived by aerial transport. The coastal lagoon where the NAMAKO study was carried out has marine inputs (Woodruff et al. 2009), which is consistent with a marine origin, but suggests some halotolerance within Cryothecomonas.

Although living cells of Cryothecomonas have not been reported from sediments, four of the five clusters of Cryothecomonas represented in our phylogenetic analysis contained sequences retrieved from sediments (Dawson and Pace 2002; Takishita et al. 2007a, 2007b), suggesting that DNA, at least, from Cryothecomonas is present and persists under such conditions. The closely related genus Protaspis is commonly reported from microscopy-based studies of marine benthic habitats (Hoppenrath and Leander 2006; Lee and Patterson 2000). Whether Cryothecomonas, possibly misidentified under the microscope as Protaspis, plays an active role in benthic microbial communities or whether DNA is present due to the sinking of senescent cells, resting stages, or association with sinking particles, is unresolved.

Sequences that have closest matches to Cryothecomonas are often retrieved in low numbers from pelagic Arctic 18S rRNA gene libraries (Lovejoy et al. 2006; Lovejoy and Potvin 2011; Terrado et

al 2009). There are numerous microscopy-based reports of Cryothecomonas from sea-ice (Garrison et al. 2005; Ikävalko and Gradinger 1997; Sime-Ngando et al. 1997a; Thomsen et al. 1991), and occasional reports from both polar and temperate zone water columns (Drebes et al. 1996; Sime- Ngando et al 1997a; Thomsen et al 1991). Records are uncertain because distinguishing Cryothecomonas from other amoeboid flagellates in standard phytoplankton samples requires some expertise (Howe et al. 2011), and the nucleus has characteristic areas of permanently condensed chromatin, leading to confusion with dinoflagellates under epifluorescence microscopy (Thomsen et al. 1991). Taxon-specific probes provide a tool to positively identify morphologically variable and non-descript taxa (Massana et al. 2002), making our genus-specific probe results comparable to earlier microscopy studies carried out by experts (Garrison et al. 2005; Ikävalko and Gradinger 1997; Sime-Ngando et al. 1997b, 1997b; Thomsen et al. 1991). Similar to those studies, we found Cryothecomonas abundance was sporadic over space and time. We also collected contextual environmental data with the goal of understanding the ecological significance of Cryothecomonas distribution in the High Arctic.

Because Cryothecomonas has been reported from microscopy- and sequencing-based studies in sea- ice from northern Japan (Sime-Ngando et al. 1997b), Greenland (Ikävalko and Gradinger 1997), Antarctica (Garrison et al. 2005; Thomsen et al. 1991), and near the North Pole (Bachy et al. 2011), sometimes at much higher densities than in the under-ice water column (Sime-Ngando et al. 1997a), it has been regarded as a typical sea ice organism. The sea-ice community is recruited into the ice over fall and winter from the surrounding seawater (Rñżańska et al. 2008). Populations reach maximal levels in spring and are released back into the water during ice melt in late spring and early summer (Juul-Pedersen et al. 2010; Rñżańska et al. 2009). Within brine channels, which can become very saline (Deming 2007), high densities of bacteria, diatoms, and other phototrophs likely provide Cryothecomonas with abundant food. This perspective suggests that the pelagic Cryothecomonas recorded over the Arctic are derived from melting sea-ice and perhaps not a „normal‟ member of the water column community. In our analysis, the negative simple correlation with distance from ice-edge supports this; path analysis indicates that about a third of this effect results indirectly from the change in salinity through the process of freshening due to ice-melt, which would also be consistent with an ice origin of the cryothecomonads.

Other such indirect effects may account for the change in sign when partial rather than simple correlations are calculated. Partial correlation analysis identifies the portion of the correlation that is shared with other confounding variables (Legendre and Legendre 1998) For example, the apparent negative correlation between temperature and Cryothecomonas abundance changes sign in partial

35 correlation analysis, indicating that much of this effect should probably be ascribed to correlation with other variables, rather than a real selection of Cryothecomonas by temperature, and path analysis shows that 26% of the effect of temperature results from its co-correlation with depth; Cryothecomonas is found in colder waters closer to the surface. The role of depth and salinity suggests that stratification is an important process regulating Cryothecomonas abundance in the Canadian Arctic. The surface layer where Cryothecomonas is almost exclusively found has highly variable salinity and temperature, characteristics that change rapidly over the summer melt season and are locally dependent on boundary processes, such as ice melt, solar radiation, and mixing by wind (Bâcle et al. 2002). The variability of these factors probably contributes to the variability of Cryothecomonas abundance.

2.04.4. Trophic position of Cryothecomonas A variety of modes of feeding have been reported for Cryothecomonas, including parasitism (Drebes et al. 1996) and grazing on bacteria and phytoplankton (Thomsen et al. 1991). The feeding method of Cryothecomonas may be ecologically important because parasites may be more effective than grazers at controlling bloom activity of specific hosts (Montagnes et al. 2008; Sherr and Sherr 2009). The two strains of parasitoid species C. aestivalis are reported to feed inside particular diatom hosts (Hoppenrath and Leander 2006; Kühn et al. 2000). These strains, both isolated from northern European Seas, made up Cluster 2 of our phylogeny, and other sequences in the group were from shallow sediment and a deep sea cold seep; however, phylogenetic analysis provided no evidence relating Arctic clones to this group. Reports of Cryothecomonas attached to diatoms in the Canadian Arctic (Horner 1976; CL, pers. observ.) do not necessarily indicate parasitism, as diatom frustules and associated exudates from the diatom itself might act as a substrate for bacterial growth that attracts Cryothecomonas.

The requirement of Culture MC5-1 for a bacteria-rich rice-medium indicates that this strain of Cryothecomonas is bacterivorous. Several Arctic sequences were closely related to this strain, suggesting that bacterivorous cryothecomonads were present. Bacterivory by uncultivated heterotrophs has been previously documented using grazing experiments in natural samples (Massana et al. 2009; Šimek et al. 2004; Unrein, Gasol, and Massana 2010). The negative results of our experiments may have been due to the rarity of Cryothecomonas in the samples compared to, for example, marine stramenopiles, which are relatively more abundant (Lovejoy and Potvin 2011). Alternately, if Cryothecomonas are better adapted to gliding on substrates and grazing on attached bacteria, as is reported for the Cryomonadida genus Protaspis (Hoppenrath and Leander 2006), though not Mataza (Yabuki and Ishida 2011), the FLB technique as used here would not be an

appropriate test. Cryothecomonas aestivalis will glide along a chain of diatoms when approaching a host cell (Drebes et al. 1996).

According to path analysis, total chl a explains roughly a third of the covariance with 3–6 µm phototrophs and a fifth of the covariance with diatoms. The relative importance of overall biomass, as represented by total chl a compared to biomass of specific prey functional groups, may indicate that Cryothecomonas is not a very specialized predator. Significant negative simple and partial correlations with small heterotrophic flagellates suggest different ecological roles, consistent with Cryothecomonas as a generalist grazer and smaller heterotrophic flagellates as true pelagic bacterivores (Massana et al 2006).

2.05. Conclusion The combination of updated analysis of the 18S rRNA gene and an oligonucleotide probe targeted to a specific taxon has enabled us to gather environmentally pertinent data on a single genus, Cryothecomonas. We found no evidence either from microscopy or our phylogenetic analysis that Arctic Cryothecomonas were parasitoids, but rather they all appeared to be free-living. Based on interpretation of environmental data, we suggest that Cryothecomonas-related sequences retrieved from pelagic marine samples are generalist predators associated with the high-biomass surface waters of salinity-stratified water columns. Occasional high-density events, marked by an increase in smaller cells, suggest sensitivity to specific conditions and perhaps a distinct role in marine food webs at high latitudes. The association with the ice and melting ice suggests that Cryothecomonas may prove to be a valuable indicator of recent ice extent.

2.06. Acknowledgements We would like to thank the members of the Canadian Coast Guard aboard the CCGS Amundsen. We are grateful to R. Gast who provided the culture MC5-1, and R. Rodríguez who provided the fluorescently labelled bacteria. C. Pedrós-Alió, R. Massana, and I. Forn contributed advice and materials for the fluorescent in situ hybridization work. We also thank the numerous students and post-doctoral fellows who collected samples during the different years. We also thank the anonymous reviewers and the editor of Journal of Eukaryotic Microbiology for their helpful suggestions and time. Natural Science and Engineering Council of Canada (NSERC) provided much of the funding, including for ArcticNet and the Canadian Healthy Ocean Network (CHONe) and the following International Polar Year (IPY) projects: the Canadian Flaw Lead Study (CFL), MALINA, and Canada‟s Three Oceans (C3O). Additional NSERC Discovery funding to CL and fellowships to MT made the study possible.

37 38

Table 2.1 Simple and partial correlations between abundance of Cryothecomonas and sixteen other biotic and abiotic variables.

Variable Simple Partial Correlation Correlation Depth -0.24 * 0.15 Julian Day 0.16 -0.24 ** Heterotrophic flagellates 1–3 µm, biomass 0.51 ** -0.23 ** Heterotrophic flagellates 6–10 µm + 0.29 * -0.03 dinoflagellates, biomass Phototrophs 1–3 µm, biomass -0.17 0.11 Phototrophs 3–6 µm, biomass -0.40 ** 0.23 ** Diatoms, biomass -0.49 *** 0.25 ** Chlorophyll a, Total 0.41 *** 0.14 Chlorophyll a, < 3 µm size fraction 0.11 * -0.18 * Nitrate 0.00 0.15 Phosphate 0.29 0.11 Temperature -0.48 ** 0.41 *** Salinity -0.17 -0.26 ** Photosynthetically Active Radiation (PAR) 0.01 0.08 Dissolved Oxygen -0.33 0.19 * Distance to Ice Edge -0.64 * 0.31 *** Significance: *** < 0.001, ** < 0.01, * < 0.05

Figure 2.1. Stations sampled for counts of Cryothecomonas using Fluorescent in-situ Hybridization. Station names are given where elevated Cryothecomonas events occurred, or where additional manipulations were performed. Stars indicate clone libraries, 2008; Diamonds indicate grazing experiments.

Figure 2.2. Rooted maximum-likelihood phylogeny of the Cryothecomonas clade and other Cryomonadida genera, screened from Arctic clone libraries and reference sequences from the NCBI nr nucleotide database. Scale bar indicates number of substitutions per position. Bayesian posterior probabilities/Maximum Likelihood bootstrap values (as percentages) greater than 0.60/60 are printed above each node. Open circles indicate sequences from Arctic clone libraries. Closed circles indicate sequences from sediment clone libraries.

Figure 2.3 Figure 2.4

Figures 2.3 and 2.4. Epifluorescence micrographs of Cryothecomonas cells hybridized with the Cryo1134 probe from Station 101 on 15 September 2008, showing the range of morphological variation observed. The difference in size of non-hybridized cells between Figure 2.3 and 2.4. is due to the fact that small bacterial cells are not sharply focused in Figure 2.3, and a longer exposure time causing increased halo-ing. Scale bars = 10 µm for all images. A panels: Green excitation, showing the yellow cytoplasm with fluorescent in situ hybridization (FISH). B panels: Overlay of two pictures of the same cell observed under green excitation and ultraviolet excitation (showing the nucleus stained with 4,6-diamidino-2-phenylindole (DAPI)).

Chapter 3 : Environmental selection of marine stramenopile clades in the Arctic Ocean and coastal waters Résumé Des brouteurs unicellulaires des bactéries sont des composants clés des écosystèmes marins, et parfois représentent les eucaryotes dominants de l‟Océan Arctique. Parmi eux, on trouve de petits straménopiles, phylogénétiquement divers, connus presque exclusivement grâce aux séquences de gène ARNr 18S. Les straménopiles marins (MAST) ont été trouvés dans les eaux épipélagiques de l‟Océan Mondial et toutes les Mers arctiques. En particulier, trois sous-clades de MAST-1, MAST- 1A, -1B et -1C, sont retrouvés ensemble dans les eaux arctiques; cependant nous manquons de détails quant à leur écologie et leur répartition. Dans cette étude, nous avons réactualisé les phylogénies du clade MAST-1 pour déterminer s‟il existe des écotypes de MAST-1 spécifiques à l‟Arctique. Ainsi, profitant des échantillons récoltés pendant deux ans dans le cadre de plusieurs missions arctiques précédentes et durant l‟Année Polaire Internationale, nous avons appliqué des sondes spécifiques aux sous-clades par la technique de l‟hybridation fluorescente in situ (FISH) pour décrire la répartition des trois sous-clades dans l‟Arctique canadien. Les trois groupes se trouvaient principalement dans la zone euphotique; par contre, l‟évidence des écotypes restreints à l‟Arctique reste ambigue. Une certaine séparation spécifique à l‟environnement entre les sous- clades a été détectée : MAST-1C a atteint les concentrations significativement plus élevées près de la zone marginale de glace, tandis que les MAST-1A et MAST-1B s‟associent aux stations couvertes et libres de glace, respectivement. MAST-1B semblait être capable de persister dans les eaux plus profondes par comparaison avec les autres sous-clades. Nous attendons donc que les changements de la couverture de glace et des régimes de mélange aient un impact sur les concentrations et répartitions de ces sous-clades, avec des répercussions possibles sur les réseaux trophiques marins.

43 Abstract Single celled bacterial grazers are key components of marine ecosystems, and at times represent the dominant eukaryotes in the Arctic Ocean. Among these are small, phylogenetically diverse stramenopiles, known almost exclusively from their 18S rRNA gene sequences. Marine Stramenopiles (MAST) have been found in the upper waters of the world ocean and in all Arctic Seas. In particular three sub-clades of MAST-1, MAST-1A, -1B and -1C, co-occur in Arctic Waters, but ecological and distributional details are lacking. Here we have updated phylogenies of the MAST-1 clade to test whether there are Arctic-specific MAST-1 ecotypes. In addition, taking advantage of samples collected over two years as part of several Arctic cruises leading up to and during the International Polar Year, we applied sub-clade specific probes and fluorescent in situ hybridization (FISH) to describe the distribution of the three sub-clades in the Canadian Arctic. The three groups were found principally in the euphotic zone; however, evidence of Arctic ecotypes remains elusive. Some environment-specific separation among sub-clades was detected, with MAST-1C reaching significantly greater concentrations near the marginal ice zone, while MAST- 1A and MAST-1B were associated with ice-covered stations and open water, respectively. MAST- 1B appeared to be able to persist at greater depths. Changing ice-cover and mixing regimes are therefore expected to have an impact on the concentrations and distribution of these sub-clades, with possible downstream consequences on the marine food webs.

3.01. Introduction In marine ecosystems, bacterivorous, single celled marine eukaryotes, often referred to as heterotrophic nanoflagellates (HF), are a principle agent of bacterial loss in pelagic systems (Sherr and Sherr 2002; Jürgens and Massana 2008), especially in the Arctic (Vaqué et al. 2008), where microbial food webs are active for much of the year (Rokkan Iversen and Seuthe 2011). Since taxon-specific differences in feeding behaviour, population dynamics and life histories may be important over broad ecosystem scales (Weisse 2002), the identification and quantification of ecologically significant groups can add substantially to our understanding of marine ecosystems. Among phototrophs, niche partitioning has been reported for phylotypes of the green algae Micromonas pusilla (Foulon et al. 2008) and Ostreococcus (Rodríguez et al. 2005) and the coccolithophorid Emiliana huxleyi (Langer et al. 2009) but similar information on HF is lacking.

As with many small single-celled taxa, a lack of diagnostic morphological features makes identification of HF groups challenging, and molecular based techniques are essential for characterizing many taxa (Boenigk et al. 2005). Culture-independent techniques such as 18S rRNA gene clone libraries detect known taxa, but also reveal groups previously not identified in cultures or microscopy. Among these are Marine Stramenopiles (MAST; Massana et al. 2004), which occur in all oceans (Massana et al. 2006). The term MAST refers to a number of independent clades, including the putatively bacterivorous HF clade MAST-1, which composes up to 35% of total HF at some sites (Massana et al. 2006). Three major MAST-1 subclades are denoted 1A, 1B and 1C (Massana et al. 2006). All three have been reported in the Arctic (Lovejoy et al. 2006), but data is lacking on the environmental and ecological conditions which affect their distributions. MAST-1C, which has received the most study, is reported to be an efficient grazer (Massana et al. 2009). To date, MAST-1A is reported to be the least abundant of the three clades in world Oceans (Massana et al. 2006; Lin et al. 2012). Interestingly, in Pacific waters MAST-1B was positively correlated to a phylogenetically distant clade, MAST-4 (Lin et al 2012). MAST-4 dominates in most Oceans, but is absent from waters < 5°C (Massana et al. 2006), perhaps because it is thought to prey on the picocyanobacteria Synechococcus (Lin et al. 2012), which are virtually absent from polar waters (Waleron et al. 2007).

The Arctic Ocean has many physically and biologically distinctive features, including seasonal and multi-year ice cover, and a salinity-stratified water column (Carmack 2007). In general, most regions are characterized by a surface mixed layer overlying colder, more saline water of Pacific or Arctic origin, followed by warmer, even more saline Atlantic Water (AtW), and finally cold bottom waters, whose provenance varies by region (see references in Materials and Methods). However,

45 water column structure varies by region. At one extreme, anti-cyclonic circulation in the Canada Basin accumulates fresh water, producing a very deep, stable pycnocline (Proshutinsky et al. 2009), while at the other, the summer mixed-layer depth in the Labrador Sea can be less than 10 m (Harrison and Li 2007). Productivity also varies from region to region, with the Canada Basin and western Beaufort Sea being oligotrophic, while Lancaster Sound, Baffin Bay, and parts of the eastern Beaufort Sea (the Amundsen Gulf “hotspot”) are characterized by higher primary production (Ardyna et al. 2011). Finally, ice conditions can vary greatly among years and regions. In the Beaufort Sea, ice break-up typically begins in June (Carmack and Macdonald 2002), and propagates northward across the Canada Basin to about 70–75° N by the end of September (Canadian Ice Services, URL: http://ice-glaces.ec.gc.ca/). Lancaster Sound typically begins to lose land-fast ice in early to mid-July, but in some years never becomes completely ice-free owing to the movement of current-borne floes through the channel (Prinsenberg and Hamilton 2005). Baffin Bay ice cover can extend south to 59 °N in winter, covering parts of the Labrador Sea. Ice retreats northward beginning in April, more rapidly on the eastern side because of the warm West Greenland Current, with the entire Bay becoming ice-free by September (Tang et al. 2004). Given such a heterogeneous environment, we tested the idea that the three MAST-1 sub-clades could be associated with different geographic, vertical or physical conditions.

The distribution of MAST-1 sub-clades was investigated by applying specific probes with fluorescent in situ hybridization (FISH). We used FISH to quantify cell concentrations from sites in the Canadian Arctic and Labrador Sea. In addition, we retrieved MAST-1 18S rRNA gene sequences from previously published clone libraries and expanded current MAST-1 phylogenies with an aim to identify possible environment-specific clades. Previous studies have looked at factors affiliated with the geographic (Lin et al. 2012) and vertical distribution of MAST-1 sequences (Logares et al. 2012; Monier et al. 2013). However, to our knowledge this is the first study that uses a quantitative technique to examine the distribution of MAST-1 sub-clades from different depths and water masses. The goals of this study were to describe this distribution, and to determine whether the sub-clades might exploit different ecological niches at high latitudes.

3.02. Materials and Methods

3.02.1. Sample Collection Samples for FISH, DNA, RNA, microscopy, flow cytometry, and chlorophyll a (chl a) were collected on board the CCGS Louis St-Laurent during the International Polar Year (IPY) Canada‟s Three Oceans Expedition in July–August 2007, and the CCGS Amundsen during the Circumpolar

Flaw Lead Study in July 2008 and the ArcticNet Expedition in September 2008 (Figure 3.1). Three to eight depths were sampled at 10 stations, and two depths from 8 other stations, giving a total of 72 samples × 3 FISH probes or 216 slides for subsequent cell counts. The surface and sub-surface chlorophyll maximum (SCM; Martin et al. 2010) were sampled at all stations. Samples were collected directly into clean, rinsed carboys from 10 or 12-liter Niskin-type bottles (Ocean Test Equipment) mounted on a shipboard-deployed rosette. Conductivity, temperature and depth were recorded using a SBE-911 CTD (SeaBird, Bellingham, WA, U.S.A.). Other instruments on the rosette system recorded fluorescence (Seapoint), photosynthetically active radiation (PAR, Biospherical Instruments), transmissivity (Chelsea/Seatech/Wetlab CStar) and relative nitrate concentrations (Satlantic ISUS). Oxygen values from the CTD were calibrated potiometrically from samples taken at discrete depths (Granéli and Granéli 1991). Nutrient samples collected aboard the - Amundsen were taken from the same cast and depths. Concentrations of nitrate (NO3 ) and 3- phosphate (PO4 ) were determined on board with a Bran and Luebbe Autoanalyzer III with routine colorimetric methods (Grasshoff et al. 1976) and a detection limit of 0.03 µM. Nutrient samples collected aboard the Louis St-Laurent were analyzed using a Technicon Autoanalyzer following Barwell-Clarke and Whitney (1996), with detection limits of 0.09 µM and 0.03 µM for nitrate and phosphate respectively.

Total chl a concentrations were estimated following filtration of 0.5–1 liter of seawater onto GF/F filters (Whatman, Sanford, ME). The < 3 µm size fraction was estimated from a separate 0.5-1 liter that had been gravity filtered through a 3-µm pore size polycarbonate filter (AMD Manufacturing, Mississauga, Canada) prior to filtration onto the GF/F filters. All filters were stored at -80 °C until extraction in 95% ethanol at 70 °C for 5 min (Nusch 1980). Concentrations were determined by spectrofluorometry (Cary Eclipse, Agilent Technologies, Santa Clara, CA, U.S.A.).

Samples for estimation of plankton biomass by microscopy were initially fixed in 1% glutaraldehyde (v/v; Canemco, Gore, Canada) for 1–24 h in the dark at 4 °C. Fifty ml of seawater was filtered by vacuum filtration onto a 0.8-µm pore size, 25-mm diameter black polycarbonate (PC) filter (AMD Manufacturing, Mississauga, Canada) and the final 5 ml stained with 4‟,6- diamidino-2-phenylindole (DAPI; Porter and Feig 1986) at a final concentration of 50 µg ml-1 for 5 min. Filters were mounted on slides using a drop of non-fluorescent immersion oil and stored at -20°C.

47 Samples for bacterial abundance estimated from flow cytometry (FCM) were collected from a rosette cast at the same stations taken within 3 hours. FCM bacteria from the 2008 missions were estimated as in Belzile et al. (2008), and as in Li and Dickie (2001) for the 2007 samples.

Samples for FISH were fixed immediately in 3.7% formaldehyde and kept in the dark at 4C for 6– 24 h. Either 50 or 90 ml of fixed sample was filtered by vacuum filtration through a 25-mm diameter PC filter of pore size 0.8 µm (AMD Manufacturing, Mississauga, Canada), and rinsed twice with 5 ml of filtered milli-Q water. Filters were allowed to air-dry and stored at -20C.

3.02.2. FISH Cy3-labelled probes NS1A, NS1B, NS1C (Invitrogen, Burlington, Canada), specific to sub-clades MAST-1A, -1B, and -1C respectively (Massana et al. 2006), were used to hybridize cells in samples as in Pernthaler et al. (2001), with modifications. Briefly, to reduce loss of cells, all filters for FISH were coated with 0.1% agarose, allowed to dry at 37°C, and then rinsed with ethanol before further manipulations. Sections of filter were hybridized for 3 h at 46 °C in hybridization buffer with 30% formamide, and then washed in a second buffer at 48°C for 15 minutes. Filter sections were mounted on slides using a 5:1 mixture of Citifluor antifadant AF1 (Citifluor, Leicester, UK) and Vectashield (Vector Laboratories, Peterborough, UK) with 5 µg ml-1 DAPI as a counterstain. Hybridized cells were visualized using an Olympus IX71 epifluorescence microscope at 1000X magnification using a green excitation block specific for the Cy3 fluorochrome. Numbers of cells counted for each probe are given in Supplementary Table S3.1. DAPI-stained cells were also counted, as a control for cell loss during the hybridization process. About 800 DAPI-stained cells were seen per filter, and the hybridized cells were counted over the entire area of the filter section, an average of 220 fields at 1000X magnification. We estimate less than 10% error with a 95% confidence interval, and it can be shown (Lund et al. 1958) that a single hybridized cell, equivalent to about 1.2 cells ml-1, would be detected ca. 90% of the time. We estimated cell loss by a regression of DAPI-stained cells on hybridized versus the non-hybridized filters used for biomass estimations, with the intercept forced to zero. The slope of this regression was 0.43 (p < 0.001), i.e. only 43% of cells could be successfully counted. This relatively high percentage could be due either to cell loss during manipulations, or to inefficient counting resulting from the fact that filters for FISH are prepared with a white PC filter, have a shorter incubation period with DAPI, and have a higher volume filtered, which may result in cell densities too high to be effectively counted because of fading over time exposed to UV excitation. However, the high R2 (0.75) indicates that cell loss was related linearly to density, and cell counts can therefore be compared to each other within this study.

3.02.3. Environmental Variables Fourteen environmental variables, six biological and eight physicochemical, were examined with respect to the abundance of the MAST-1A, 1B and 1C sub-clades. Biological variables included: diatom biomass, biomass of non-diatom phototrophs < 3 µm and 3–6 µm, bacterial concentration, and concentration of chl a in the < 3 and > 3 µm size fractions. The eight physicochemical variables were temperature, salinity, transmissivity, phosphate and nitrate concentrations, PAR, oxygen concentration, and distance to the nearest ice edge. Unfortunately, unequal sampling effort between years did not permit analysis of seasonal or interannual effects. Distance to nearest ice edge was estimated from ice charts obtained from the Canadian Ice Services archives (URL: http://ice- glaces.ec.gc.ca/), where ice edge was defined as 10% ice cover, as the threshold for the occurrence of ice-edge blooms (Perrette et al. 2011). Biomass was determined by counting cells on an Olympus (Richmond Hill, ON) IX71 microscope at 1000X magnification using UV and Blue excitation blocks. Cells with DAPI-stained, intact nuclei were visualized under ultraviolet excitation. Cells with natural red fluorescence due to chlorophyll as visualized under blue excitation were considered photosynthetic. The cell density of each functional and size category was converted to biovolume following Hillebrand et al. (1999) and carbon biomass using conversion factors given in Menden- Deuer and Lessard (2000). In practice, the diatoms were similar sized with median biovolumes close to the average, and 110 µm3 per cell was used. Bacterial concentrations were from FCM.

Canonical correspondence analysis (CCA) was performed on log-transformed data using CANOCO 4.5 (ter Braak and Šmilauer 1998). Transmissivity data was first arcsine transformed, as is appropriate for percentage data. Forward selection was used to select the subset of environmental variables which contributed the most to the explained variation of the species data. Distance to ice edge was included as a nominal variable with three categories: Ice (station ice-covered), Near Ice (≤ 55 km from ice edge) and Open (> 55 km from ice edge). This distance represented a natural break-point in our data, and may also be assumed to be the average extent of ice-edge blooms, which are typically 20–100 km wide (Perrette et al. 2011).

Based on salinity and temperature, samples were categorized as coming from water masses identified in the Arctic (Table 3.1, Figure 3.2D; Melling and Moore 1995; Bâcle et al. 2002; Lazier et al. 2002; McLaughlin et al. 2002; Prinsenberg and Hamilton 2004; Tang et al. 2004; Hamilton et al. 2008). Winter Water (WW) is formed locally due to cooling and brine rejection during freeze- up, while Pacific Water (PW) has been cooled by winters in the North Pacific and flows through the Bering Strait. The same water is modified as it flows from west to east, and is referred to as Arctic Water (AW) when it arrives in Baffin Bay. In the Beaufort Sea, we refer to the water of increasing

49 temperature and salinity below the PW as the Lower Halocline (LH). In Baffin Bay, we refer to the water of decreasing temperature beneath the deep Atlantic layer (AtW) as Bottom Water (BW). Finally, Labrador Sea Water (LSW) is a water mass found only in the Labrador Sea stations, and represents a very thick (1800 m) layer of almost uniform temperature and salinity. In our samples, it is found only at station LS4.

Water mass was projected onto the ordination diagram but did not constrain the axes. Significance of the first canonical axis and of all axes were tested using a Monte Carlo test with 499 permutations under the reduced model. The CCA diagram was used as a guide to focus further detailed analyses using correlations and the Kruskal-Wallis test, performed with the statistical software package R (R Development Core Team, 2008)

3.02.4. Phylogenetic Analysis 335 partial and complete 18S rRNA gene sequences associated with MAST-1, excluding MAST- 1D, which is apparently absent from the Arctic (Monier et al. 2013), were retrieved from Protist Ribosomal Reference database (Guillou et al. 2012; URL: http://ssu-rrna.org/), 99 from polar samples (Arctic and Antarctic) and 236 from non-polar samples. A preliminary analysis, using two sequences of labrynthulids, AB022103 and AB022105 as an outgroup, was used to determine the affiliation of sequences, and then individual trees were constructed for each sub-clade, using sequences from the other sub-clades as outgroups. Sequences were aligned using MAFFT (Katoh et al. 2002), with default settings, and suspected chimeric sequences were checked by splitting the sequence in half and BLASTing each part separately. 100-replicate bootstrapped maximum- likelihood trees were constructed using PhyML 3.0 (Guindon et al. 2010), with a general time- reversible model. Sequence similarity between clades was determined using Mothur v. 1.29.2 (Schloss et al. 2009). Trees have been pruned for clarity using Dendroscope (Huson and Scornavacca 2012).

3.03. Results

3.03.1. FISH Three fluorescently-labelled oligonucleotide probes, NS1A, NS1B and NS1C (Massana et al. 2006) were used to target sub-clades MAST-1A, MAST-1B and MAST-1C respectively. NS1A-targeted cells were typically oval-shaped with a median diameter 8 µm (range 3–12 µm), and a mean cell density of 1.1 cells ml-1. NS1B-targeted cells were typically round with a median diameter 2.5 µm (2–4 µm), and a mean cell density of 16.5 cells ml-1. NS1C-targeted cells were round or oval-

shaped, with a median diameter 5.5 µm (3–8 µm), and a mean cell density of 12.3 cells ml-1. The highest total density of MAST-1 cells as a percentage of HF cells on the same filter, was 12% at the surface sample from Station 101. All sub-clades were present in the Arctic and Labrador Sea, though MAST-1A was found at much lower concentrations (Figure 3.2A).

For all three sub-clades, cell concentrations were greatest in SW samples (Figure 3.2B, C). However, at Station 115 in the northern Baffin Bay, an elevated concentration of MAST-1B cells (85.6 cells ml-1) was recorded in the cold core underlying the layer of warmer AtW, at 360 m (Figure 3.2B).

Concentrations of the three MAST-1 clades, determined by FISH, were analysed along with 14 environmental variables using CCA. These data are available in the Polar Data Catalogue (http://www.polardata.ca/, CCIN #11645). When all environmental variables were included, the first two axes explained 33% of the taxon-level variance. Following forward selection, the following variables were selected and using for subsequent analysis: biomass of phototrophs 1–3 µm, distance to ice edge, diatom biomass, concentration of nitrate, and sample depth (Figure 3A). In this reduced analysis, the first two axes found explained 24% of the taxon-level variance. Both the first axis (P < 0.01) and all canonical axes (P < 0.01) were significant.

The environmental variable most responsible for the separation of the three taxa along these axes was distance to the ice edge, with MAST-1B associated most with open water, MAST-1C with near-ice stations, and MAST-1A with near-ice and ice-covered stations. A Kruskal-Wallis test confirmed a significant effect of distance to ice edge for MAST-1C only (MAST-1A, P = 0.02; MAST-1B, P > 0.1; MAST-1C, P < 0.01; with Bonferroni‟s adjustment  = 0.05/3 = 0.017 to account for multiple tests). Based on the ordination diagram (Figure 3.3A), near-ice stations appear to have a higher biomass of small phytoplankton than open-water stations. This effect, along with average depth of the pycnocline (defined as the depth of maximum Brunt-Väisäla frequency, N2), and depth of the nitracline, were tested using Kruskal-Wallis tests. No significant effect was detected between the three categories; however, the pycnocline was non-significantly deeper at near-ice sites. In the ordination diagram, MAST-1B appeared to be positively associated with concentration of nitrate. Correlation analysis showed that in fact all three sub-clades were negatively correlated with nitrate concentration, and the seemingly positive correlation with MAST- 1B reflects a less strong negative correlation (MAST-1A, r = -0.33, P < 0.01; MAST-1B, r = -0.26, P = 0.04; MAST-1C, r = -0.37, P < 0.01).

51 3.03.2. Phylogenetic Analysis Nearly a third of 18S rRNA gene sequences retrieved from GenBank came from polar clone libraries. Other sequences came from diverse environments, including anoxic sediments and sea-ice as well as sequences from high- and low-latitude studies. An alignment consisting of 921 characters was used to construct a maximum-likelihood phylogenetic tree (Figure 3.4). Sub-clades were identified based on previously published taxonomies (Massana et al. 2006; Lin et al. 2012). All three sub-clades had high bootstrap support; however, clusters within sub-clades tended to be less well-supported. Sequences in MAST-1A, -1B and -1C had a minimum similarity of 93%, 97% and 95% respectively, calculated using Mothur, with gaps weighted equally regardless of length.

3.04. Discussion We used taxon-specific oligonucleotide probes to collect data on the relative abundance of three closely-related, ubiquitous hetetotrophic flagellate taxa, and looked for environmentally-specific sub-clades using phylogenetic analysis. Our overall goal was to distinguish their ecological niches within Arctic water masses and to test if such niches could be generalized to other oceans at the level of sub-clade.

Median cell sizes for MAST-1B and -1C were smaller than reported global averages (Massana et al. 2006), despite the fact that inverse size-temperature correlations reported for MAST-1B (Lin et al. 2012) and MAST-1C (Massana et al. 2006) suggest that we should find larger cells in Arctic waters. Maximum concentrations of MAST-1A, -1B and -1C in our samples were roughly the same magnitude as those reported from the North Pacific (Lin et al. 2012), although at most sites MAST- 1B dominated numerically rather than MAST-1C. We note that another bacterivorous clade, MAST-4, has not been detected at polar latitudes using FISH (Massana et al. 2006) and only rarely using environmental 18S gene surveys (Lovejoy and Potvin 2011). However, there is no noticeable increase in MAST-1 concentrations that would suggest that the MAST-1 clade expands to fill a niche that would otherwise be filled by MAST-4. The low photosynthetic and bacterial productivity of the summer Arctic waters covered in this study (Forest et al. 2011), may limit overall bacterial grazer biomass, reflected in the low MAST-1 concentrations.

3.04.1. Environmental phylogenetic clusters Our phylogenetic analysis was based on previously published phylogenies (Lin et al. 2012; Monier et al. 2013) with the addition of recently published sequences. In particular we included sequences from oxygenated mesopelagic Arctic waters (Terrado et al. 2009). Although these Pacific-origin waters have a different history and properties from the surface waters from which MAST-1

sequences have been recovered, there was no apparent phylogenetic structuring by depth, and all three sub-clades were represented in mesopelagic samples. The MAST-1C sub-clade contained sequences from the greatest diversity of environments, including sediments and sea-ice. In their analysis of MAST-1, Lin et al. (2012) found clusters restricted to either low or high latitudes in MAST-1A and -1C. In our own analysis, we found similar clusters, although with low bootstrap support (clusters 1Aa and 1Ab in Figure 3.4A). While cluster 1Ab received low bootstrap support, it had a distinctive 25-bp motif 5‟-CTCTGTCCTTAGTTGGATGGGGTTT-3‟ located about 80 bp from the beginning of the V4 variable region (nomenclature follows Nelles et al. 1984). Cluster 1Ab consisted mostly of high-latitude sequences, but also contained a sequence from a temperate zone (AMT15_33_5m, 37° 50‟ S; Figure 3.4A) and from an anoxic inlet of Vancouver Island, Canada. A low-latitude sub-cluster was identified in MAST-1C, but with low bootstrap support. Notably, putative high-latitude clades included recent sequences from Saanich Inlet (Orsi et al. 2012), a temperate, often anoxic, coastal inlet on the west coast of Canada, which is influenced by the East Pacific waters. Since saline, anoxic conditions can preserve DNA, it is possible that these sequences were allochthonous, transported to the site by advection by, for example, ocean currents, and represent a history of ocean or even aerial transport (Terrado et al. 2012). Therefore, in the absence of viability studies, these results do not necessarily contradict the idea that these clusters represent genetically distinct populations not found at lower latitudes; however, without strong bootstrap support, all clusters described here are only tentative, and longer sequences are probably required for definitive identification. We did not identify latitude-specific clusters for MAST-1B.

3.04.2. Depth Distribution The taxonomic composition of the MAST-1 community has previously been found to vary by depth (Logares et al. 2012). Monier et al. (2013) also found that MAST-1A was more diverse at the surface than at SCM, while the reverse was true for MAST-1C. In our study, while all three taxa appear best adapted to surface water according to cell counts, numerous sequences from mesopelagic samples were identified belonging to each group (Figure 3.4). We did not find exclusive mesopelagic or surface-specific clusters; however, CCA suggests some vertical structuring of MAST-1 distribution. MAST-1B was the taxon found closest to the centroid for deeper water masses in CCA (Figure 3.4B), and its association with the vector for nitrate concentration hints at an association with water from below the nitracline. This suggests that MAST-1B may survive longer at depth than the other two clades. Indeed, MAST-1B was present three times more frequently than MAST-1C in both AtW and BW, while MAST-1A was never detected in AtW.

53 Evidence for vertical structuring also comes from depth profiles of cell concentrations. The occurrence of a higher-density MAST-1B event in BW at Station 115 suggests that MAST-1B was more tolerant of deep conditions than the other two taxa. Upwelling commonly occurs in northern Baffin Bay (Melling et al. 2001), which is accompanied by downwelling in adjacent waters and would be a mechanism for transporting MAST-1B from the euphotic zone to greater depth. High sedimentation rates have also been reported following high productivity in Northern Baffin Bay (Lalande et al. 2009); however, given the great depth and small cell size of MAST-1, this mechanism of vertical transfer would imply time scales of at least 1–2 years, implying either dormant stages or active growth rather than simple survival. Interestingly, similar sub-surface peaks were never observed for MAST-1A or MAST-1C, consistent with preferential survival of MAST- 1B at depth.

3.04.3. Relationship with ice-influenced waters A single MAST-1C sequence has been detected in first-year Baltic sea-ice (Majaneva et al. 2012; sequence 5-F10 in Figure 3.4C), and previous studies of sea-ice samples using FISH (Piwosz et al. 2013) and pyrosequencing (Comeau et al. 2013) suggest that MAST-1 is only a very minor component of the sea-ice community. However, the presence of sea-ice may indirectly affect their abundance via food web interactions. For example, Comeau et al. (2011) theorized that the decrease in proportion of MAST reads in their analysis after the ice-minimum year of 2007 may have resulted from the concurrent decrease in their potential prey Bacteroidetes, which is negatively impacted by sea-ice retreat

Within MAST-1, CCA also showed that the three clades were associated with different distances from the ice-edge, particularly MAST-1C with near-ice stations. Sites in the marginal ice-zone, including both recently ice-covered sites and ice-free sites influenced by lateral advection of meltwater and drifting ice, may be associated with high primary and/or secondary production caused by a number of different mechanisms. These include: a shallower nitracline (Tremblay et al. 2006; Coupel et al. 2012); nutrient upwelling associated with the ice-edge (Mundy et al. 2009); the release of ice-associated organic material (Fortier et al. 2002), that supports bacterial production and heterotrophic protist activity; stratification by fresher meltwater causing phytoplankton to be exposed to higher surface irradiance (Sullivan et al. 1988); and interleaving of meltwater with ambient water (Jenkins 1999) that may trap particles promoting secondary production at density interfaces (Lovejoy et al. 2002). We found a negative but non-significant effect of distance to ice edge on pycnocline depth, suggesting that in our samples stratification may have been the important mechanism. New production and associated bacteria in this zone would create favourable

conditions for MAST-1C. Lin et al. (2012) hypothesized that the positive association of MAST-1C with water of salinity < 31 was due to coastal influence. While we did not find any relationship between salinity and MAST-1C, the proximity to sea-ice suggests a tolerance for broad salinity ranges, which are also characteristic of coastal regions. This differential selection for MAST-1C in near-ice stations implies that loss of sea-ice will affect the taxonomic composition of the MAST-1 community.

3.05. Conclusion Our data indicates that there are ecological differences among the three sub-clades of MAST-1 that may affect their population dynamics at broad scales in the Arctic. MAST-1B has a smaller cell size and a greater tendency to persist at depth than MAST-1A or MAST-1C. MAST-1C is found in significantly higher concentrations near the ice edge, while for MAST-1A and MAST-1B there is a positive but non-significant effect of ice cover and open water respectively. The Arctic Ocean has witnessed unprecedented sea-ice retreat in the past decade, and may soon be seasonally ice-free (Stroeve et al. 2012). This may negatively impact the abundance of taxa such as MAST-1A and MAST-1C, which are adapted to ice-covered or near-ice environments.

3.06. Acknowledgments We would like to thank the captains and crews of the CCGS Amundsen and CCGS Louis S. St- Laurent. Flow cytometry data was kindly provided by Michel Gosselin (Université du Québec à Rimouski) and W. K. W. Li. (Bedford Institute of Oceanography) We thank Linda White (Institute of Ocean Sciences, Victoria) and Jean-Eric Tremblay and Jonathon Gagnon (Université Laval) for nutrient analysis. The Natural Science and Engineering Council of Canada (NSERC) provided much of the funding, including for ArcticNet and the following International Polar Year projects: the Circumpolar Flaw Lead Study and Canada‟s Three Oceans. Additional NSERC fellowships to MT and Discovery grants to CL, and support from Fonds de recherché du Québec (FQRNT) and Québec Océan made this study possible.

55 Table 3.1. Temperature and salinity characteristics of Arctic water masses as defined in this study. Water Mass Temperature (°C) Salinity Surface Water Variable < 32.5 Winter Water 32.5–33.5 North Baffin Bay: < 0 North Baffin Bay: 32.7–34 Beaufort Sea: < -1 Beaufort Sea: 32.1–33.5 Arctic Water (Baffin Bay) < 0 >32.5 Pacific Water (Beaufort Sea) < 0.5 32.5–33.5 Lower Halocline (Beaufort Sea) < 1 >34 Atlantic Water > 1 > 33.5 Bottom Water (Baffin Bay) < 0 > 34 Labrador Sea Water 2–5 34.8

Figure 3.1. Map of sampling stations. Shapes correspond with those in Figure 3.2: Beaufort Sea (square), Baffin Bay (circle), Canada Basin (triangle, point down), Labrador Sea (triangle, point up), Lancaster Sound (diamond). Open symbols are sites sampled July–August 2007. Closed symbols are sites sampled July–October 2008.

Figure 3.2. Concentration of: a) MAST-1A; b) MAST-1B; and c) MAST-1C in samples from water masses in different regions of the Arctic. d) Water masses referred to in text. Symbols: Beaufort Sea (square), Baffin Bay (circle), Canada Basin (triangle, point down), Labrador Sea Water (LSW); Atlantic Water (AtW); Bottom Water (BW); Lower Halocline (LH); Arctic Water (AW); Pacific Water (PW); Winter Water (WW); Surface Water (SW). The dashed line indicates the freezing point of seawater at different salinities. Curved grey lines indicate density (sigma-theta).

Figure 3.3. Ordination diagram of the first two axes of Canonical Correspondence Analysis (CCA) showing the relationship between MAST-1 sub-clades and a) environmental variables, b) water masses. Axes are constrained by abundance of MAST-1 clades and environmental variables. Distance to ice edge (squares) is included as a nominal variable. Water mass features (triangles) are projected a posteriori onto the diagram. See text and Figure 3.2D, for definition of water masses: Labrador Sea Water (LSW); Atlantic Water (AtW); Bottom Water (BW); Lower Halocline (LH); Arctic Water (AW); Pacific Water (PW); Winter Water (WW); Surface Water (SW).

Figure 3.4. Rooted maximum-likelihood phylogenies of a) MAST-1A; b) MAST-1B and c) MAST-1C sequences from the NCBI nr nucleotide database. Outgroups not shown. Scale bar indicates number of substitutions per position. Closed circles indicate nodes with bootstrap values > 50 (out of 100). Labels of end-nodes provide clone number, sampling region, and sample depth. Continued on facing page.

Figure 3.5. Rooted maximum-likelihood phylogenies of a) MAST-1A; b) MAST-1B and c) MAST-1C sequences from the NCBI nr nucleotide database. Outgroups not shown. Scale bar indicates number of substitutions per position. Closed circles indicate nodes with bootstrap values > 50 (out of 100).. Labels of end-nodes provide clone number, sampling region, and sample depth.

61 Supplementary Table S3.1. Number of cells counted for each MAST-1 sub-clade. MAST-1A MAST-1B MAST-1C Cells counted (all stations) 131 2101 1311 Cells counted per station: range 0–16 0–222 0–186 median 0 5.5 5

Chapter 4 : Distinct heterotrophic flagellate communities in different regions of the Arctic Ocean

Résumé Les flagellés hétérotrophes (HF) marins existent dans presque tous les embranchements du domaine Eukaryota; cependant, bien que les différences fonctionnelles et physiologiques entre les taxons puissent avoir des implications importantes pour les réseaux trophiques et les cycles biogéochimiques, les facteurs qui conduisent la distribution biogéographique des groupes taxonomiques majeurs sont actuellement peu connus. L‟océanographie physique et les cycles de glace annuels de l‟Océan Arctique de l‟Ouest produisent plusieurs régions avec des environnements physiques distinctifs qui pourraient sélectionner les communautés microbiennes. Nous avons regroupé des données de séquençage à haut débit provenant d‟études multiples dans l‟Océan Arctique, avec l‟ajout de nouvelles données de la Mer des Tchouktches, pour identifier les grandes tendances dans la répartition des taxons HF, ainsi que les taxons typiques des fractions de taille < 3 µm et > 3 µm. Les HF représentaient jusqu‟à 43% des séquences dans la colonne d‟eau, et jusqu‟à 62% des séquences provenant de la glace de mer. La majorité des séquences HF dans les échantillons du Bassin du Canada étaient les Telonemia et les choanoflagellés, alors que dans la Mer de Beaufort et le Golfe d‟Amundsen les MAST et les Picozoa avaient plus d‟importance. De plus, la Mer des Tchouktches ressemblait à la Mer de Beaufort mais avec une proportion plus élévée de Cryomonadida, qui étaient également le HF dominant dans la glace de mer. Nous avons trouvé une plus grande équitabilité taxonomique (« evenness ») dans le Bassin du Canada en comparaison avec les sites côtiers, qui étaient typiquement dominés par un petit nombre de taxons. Finalement, nous avons également identifié des phylotypes qui étaient spécifiques aux régions, ainsi que d‟autres qui étaient répandus à travers toutes les régions.

63 Abstract Heterotrophic marine flagellates (HF) are found in nearly all branches of the Domain Eukaryota; however, while functional and physiological differences among taxa may have important implications for food webs and biogeochemical cycles, the factors determining distributions of major taxonomic groups are poorly known. The physical oceanography and annual ice cycles of the Western Arctic Ocean result in several regions with distinct physical environments that could select for microbial communities. We re-analyzed high throughput sequencing data from multiple studies in the Arctic Ocean, in addition to new data from the Chukchi Sea, to identify broad patterns in the distribution of heterotrophic flagellate taxa as well as typical taxa of the < 3 µm and > 3 µm size fractions. HF comprised up to 43% of reads in the water column, and 62% of reads in sea-ice. The majority of HF reads in samples from the Canada Basin were Telonemia and choanoflagellates, while in the Beaufort Sea and Amundsen Gulf, MAST and Picozoa were a higher proportion of reads, and the Chukchi Sea was similar to the Beaufort Sea but with a higher proportion of Cryomonadida. Cryomonadida were the dominant HF in sea-ice. We found greater taxonomic evenness in the Canada Basin compared to coastal regions, which were typically dominated by a few taxa. Both region-specific and widespread phylotypes were identified.

4.01. Introduction Heterotrophic flagellates (HF) have a central role in marine food webs, particularly in the Arctic where they can control phytoplankton biomass (Verity et al. 2002), and modelling studies indicate they likely consume the majority of bacterial biomass (Forest et al. 2011). In other environments they have been found to be more important than viral lysis (Umani et al. 2010) or ciliate grazers (Chen and Liu 2010) for controlling bacterial growth. HF range from pico- to nano-sized cells (0.8– 20 µm), and are phylogenetically diverse, with representatives in most branches of the Eukaryota tree. Because taxon-specific differences in feeding behaviour, population dynamics and life histories may be important over broad ecosystem scales (Weisse 2002), the identification and quantification of the diverse groups can add substantially to our understanding of marine ecosystem function. However, HF taxa often have few diagnostic morphological features that would enable ready identification (e.g. Boenigk et al. 2005). Molecular based approaches, such as amplicon pyrosequencing of the V4 region of the 18S rRNA, are now commonly being used to semi- quantitatively retrieve thousands of taxonomically informative sequences from environmental samples (Bråte et al. 2010a; Comeau et al. 2011). While amplicon sequencing shares the inherent biases of other PCR-based methods (Jeon et al. 2008; Potvin and Lovejoy 2009), the high output reduces sampling bias and can be useful for detecting rarer species.

Current changes in the Arctic Ocean, including the loss of multiyear ice, are transforming marine photosynthetic protist communities, for instance by shifting the size structure toward smaller cells (Li et al. 2009). However, the consequences for HF taxa are not known, in part because of the limited understanding of even basic biogeography and environmental selective forces on different HF taxa (Monier et al. 2013). Although there have been a number of studies using V4 18S rRNA gene amplicon pyrosequencing in the Arctic (Comeau et al. 2011, 2013; Monier et al. 2013), none were focused specifically on interregional comparisons. All of these studies have detected an effect of environmental gradients on one or more HF taxa, but it is not yet understood why HF with similar putative ecological roles (e.g. bacterivory) might vary in relative abundance over space and time, and a comprehensive analysis is lacking. Our aim was to examine smaller HF taxa whose sporadic and low occurrence in individual studies has eluded statistical treatment and to increase the environmental coverage by additional sequencing of the productive Chukchi Sea, which contrasts with the more oligotrophic Beaufort Sea.

We chose to focus on HF taxa of smaller cell-size that are usually considered bacterivores and detritivores. These included the cercozoan order Cryomonadida, marine stramenopiles (MAST), Telonemia, Picozoa (formerly known as picobiliphytes, Seenivasan et al. 2013), and

65 choanoflagellates. The aim was to consider organisms in a putative single functional guild. All of these HF taxa have been detected in 18S rRNA gene clone libraries from the Canadian Arctic (e.g. Lovejoy et al. 2006; Bachy et al. 2011; Terrado et al. 2011). Katablepharids have been detected in enrichment studies in the Arctic (Vørs 1993b); however, they were rare in our samples, so they were excluded from the analysis. Although chrysophytes are detected in the Arctic (Terrado et al. 2012), this group includes both photosynthetic and heterotrophic taxa that cannot readily be distinguished from each other at this time based solely on the V4 region 18S rRNA gene sequence, and it was therefore also omitted. Our large dataset enabled us to examine the distribution of the five major taxa above at a finer taxonomic scale than previously. While MAST phylogeny is well- studied (e.g. Massana et al. 2004; Lin et al. 2012; Thaler and Lovejoy 2013, chapter 3, this thesis), and known clades effectively clustered by sequence similarity, clades from the other four groups are less well defined. Cryomonadida, Telonemia and Picozoa have very few cultured representatives, and choanoflagellate phylogeny has recently been extensively revised (Nitsche et al. 2011), requiring an update of our tools for taxonomic identification. Because these current problems with their classification render identification by sequence similarity ineffective, our approach for these less well-known groups was to map reads onto phylogenetic trees using an environmental placement algorithm (EPA). Reads placed at the same node of a phylogenetic tree were considered to belong to the same phylotype.

4.02. Materials and Methods

4.02.1. Experimental Design Data was drawn from four different studies that used pyrosequencing of the V4 variable region of the 18S rRNA gene to describe eukaryotic communities in the Canada Basin and adjacent southern Beaufort Sea from 2003–2010 (Table 4.1; Figure 4.1; Table 1.1). Studies sampled the sea-ice, surface waters, or subsurface chlorophyll maximum (SCM; Martin et al. 2010), and the Malina study included additional depths above and below the SCM. Sample collection, pyrosequencing, and data-processing are described in associated publications (Comeau et al. 2011; Comeau et al. 2013; Monier et al. 2013; Comeau et al., in preparation), and were identical for all datasets, with the exception of a few quality control steps. In the Amundsen Gulf Time Series and Sea Ice datasets, reads < 150 bp were discarded, while this cutoff was 300 bp for the Malina and Canada Basin datasets. The Amundsen Gulf Time Series and Sea Ice datasets did not have a step to check for and remove chimeras. In general, average read length has increased over time for pyrosequencing with improvements to available chemistry, such that more recent studies will have longer reads. Additional samples were also analysed from the Chukchi Sea as described below. In

most samples, 2000-8000 reads were analyzed per sample (Supplementary Table S4.1). Accession numbers for the NCBI Sequence Read Archive (SRA) are listed in Table 4.1 for all datasets. Metadata for stations from all studies, including sampling depths, is provided in Table 1.1.

4.02.2. Chukchi Sea samples Samples were also collected onboard the USCGS Healy on the Chukchi Shelf from 13 June–22 July 2010 as part of the ICESCAPE project (URL: http://www.espo.nasa.gov/icescape/). Water was collected into 30-liter Niskin-type bottles mounted onto a SeaBird carousel rosette equipped with an SBE9plus CTD. Seawater was collected into rinsed carboys. Genomic DNA was collected by sequentially filtering 5 liters of seawater through a 3-µm pore size, 47-mm diameter polycarbonate (PC) filter (Millipore) and a 0.22-µm pore size Sterivex cartridge (Fisher Scientific) in order to obtain two size fractions, 0.22–3 µm (small) and > 3 µm (large). While this method of size fractionation is imperfect, resulting samples are enriched in organisms of the targeted size class (Terrado et al. 2009). Samples were preserved in lysis buffer (50 mM Tris HCl pH 8.3, 40 mM EDTA pH 8.0, and 0.75 M sucrose), and frozen at -80 °C until they could be analyzed.

DNA was extracted from filters and Sterivex cartridges using an AllPrep DNA/RNA Mini Kit (Qiagen). Details of primers and conditions for amplification, generating pyrosequencing reads, and pre-processing and quality control followed the protocols described in Comeau et al. (2013), with modifications as described below. The 0.22–3 µm sample was unavailable for Station CHA1 (Kotzebue Sound).

New raw pyrosequencing reads have been deposited in the NCBI SRA, with accession number SRP029300. Mothur 1.29.2 (Schloss et al. 2009) was used for all sequence processing and downstream analyses. Reads were discarded if they contained Ns, homopolymers longer than 7 bp, were < 400 bp or > 600 bp, or had a bad forward primer. Final aligned reads were clustered into Operational Taxonomic Units (OTUs) at ≥ 98% similarity as in Comeau et al. (2011). OTUs with only one representative in the dataset (singletons) were removed.

4.02.3. Placement of Reads on Phylogenetic Trees For phylogenetic analysis of Cryomonadida (Chantangsi et al. 2008; Thaler and Lovejoy 2012), Telonemia (Bråte et al. 2010b), Picozoa (Seenivasan et al. 2013) and Choanoflagellida (del Campo and Massana 2011; Nitsche et al. 2011), 18S rRNA gene reference sequences were selected based on previously published phylogenies. Because there are relatively few full-length 18S rRNA gene Picozoa-related sequences in GenBank, we constructed two trees for comparison, one with only

67 full-length sequences and one which omitted the V1 and V3 variable regions but included more environmental sequences. Many of the choanoflagellate sequences contained large insertions that were omitted from the analysis, as they are not taxonomically informative.

To generate alignments of short reads, reads from all datasets were classified into taxonomic groups using Mothur with our own curated 18S rRNA gene database as template. MAST clades, Cryomonadida, Telonemia, Picozoa, and choanoflagellate sequences were split into groups of ca. 1000-3000 reads so that they could be aligned using MUSCLE (Edgar 2004) without exceeding the memory limits of the software. Alignments were checked against the reference sequences to look for potential artefacts, particularly errors in homopolymer length, which is poorly resolved using pyrosequencing (Balzer et al. 2010). Individual alignments were then assembled into a single alignment by manually adding gaps in the sequence editing program SeaView (Gouy et al. 2010). Reference and outgroup sequences were also aligned with MUSCLE, and alignments of reference sequences and reads were assembled into a single alignment by manually adding gaps. Aligned reference sequences were then extracted and used to reconstruct a reference tree using the software RAxML v7.2.7 (Randomized Accelerated Maximum Likelihood; Stamatakis 2006) with a general time reversible (GTR) model of nucleotide substitution using four discrete rate categories to approximate a gamma distribution. Short reads were mapped onto the reference tree using the EPA of RAxML (Berger et al. 2011), and the resulting tree was visualized using NJ Plot (Perrière and Gouy 1996). Only read placements with likelihood weight > 0.5 were retained.

4.03. Results

4.03.1. Pyrosequencing and HF community composition Approximately 51 000 reads from the ICESCAPE study in the Chukchi Sea passed the quality control steps for the large size fraction and 45 000 for the small size fraction (Supplementary Table S4.2). One > 3 µm Chukchi Sea sample from Station CN14 contained a high proportion of metazoan reads closely related to the copepod genus Calanus, and only 1044 non-metazoan sequences were available for downstream analysis. Overall, Chukchi Sea samples from both size fractions were dominated by alveolates.

HF groups comprised 8–62% of eukaryote sequences in all the separate datasets (Figure 4.2), with the highest percentage in the sea-ice of Amundsen Gulf, where Cryomonadida comprised the majority of eukaryote sequences. In the Chukchi Sea water column, Cryomonadida sequences were a higher proportion of reads in the > 3 µm size fraction than the < 3 µm size fraction. In the Malina study, which compared communities from different water column depths, Cryomonadida sequences

were virtually absent (< 0.5%) from all but surface samples, with the exception of Station 620 at 80 m, where they comprised 1.8% of all sequences. Overall, in the Amundsen Gulf, Beaufort and Chukchi Seas, Picozoa and MAST were the most abundant taxa, while in the Canada Basin, Telonemia and choanoflagellates became more dominant (Figure 4.2). MAST were always a greater proportion of reads in datasets from the < 3 µm fraction, and were dominated by clades MAST-1 and 7 (Figure 4.3).

4.03.2. Phylogenies and evolutionary placement of reads The reference trees of Cryomonadida, Telonemia, Picozoa and the choanoflagellates indicated the high phylogenetic diversity of the four groups, with well-supported branching orders, and usually recovered previously published clusters. Specifically, the Cryothecomonas clade (Thaler and Lovejoy 2012, chapter 2, this thesis) was recovered with high bootstrap support in the Cryomonadida phylogeny (Figure 4.4). Among Telonemia, we recovered the groups TEL1 and TEL2 described by Bråte et al. (2010b) with very high bootstrap support, along with their freshwater clades 1d and 2e (Figure 4.5). Two Picozoa phylogenies were constructed, one from an alignment of 16 sequences and 1633 characters and a second one from an alignment of 55 sequences and 1168 characters. There was good agreement between the topologies, so the tree with a shorter residue range and more sequences was used for EPA. Some of the same clades described in Seenivasan et al. (2013) were recovered, however with different branching order (Figure 4.6). In the choanoflagellate phylogeny we recovered the Acanthoecida and Crespedida clades found by Nitsche et al. (2011), although the latter had low bootstrap support (Figure 4.7). Within Acanthoecida, we recovered Stephanoecidae as paraphyletic and containing the Acanthoecidae clade. As a group, the choanoflagellates had only moderate bootstrap support, and overall the RAxML tree should be interpreted cautiously, as the 18S rRNA gene is poor at resolving deeper branches among the choanoflagellates (Nitsche et al. 2011).

Reads were mapped onto the reference RAxML trees to identify dominant taxa in different datasets. In total, 1086 Cryomonadida reads, out of an original 7800 could be placed. Fourteen of the phylotypes dectected were found mostly or exclusively in Chukchi Sea samples, often in only one of the two size fractions (Figure 4.4). Two phylotypes (nodes f and h) were restricted to sea ice samples and one phylotype (node l) was found only in the Amundsen Gulf Time Series. One phylotype comprising 137 reads, mostly from the > 3 µm Chukchi Sea sample, branched outside Cryomonadida (node r), likely with the genus Ebria, No reads from Malina could be placed.

69 For Telonemia, 2579 out of 4794 reads could be placed on the reference tree. The largest number of reads (1044) came from the southern Beaufort Sea (Malina); the lowest number (17) came from the > 3 µm size fraction of the Chukchi Sea. Five Telonemia phylotypes (nodes a, b, d, i and o) were found almost exclusively in the Canada Basin. The phylotype node r, located among the basal sequences that comprise TEL1 (Bråte et al. 2010b), was found almost exclusively in sea-ice. Over 90% of the reads from the southern Beaufort Sea and 65% of the reads from the Amundsen Gulf Time Series were placed with environmental sequence Nor26.Telo.6, in clade 2d (node j). In contrast, reads from the Canada Basin were phylogenetically more broadly distributed through all the marine clades in TEL2. In the Canada Basin, two phylotypes (nodes a and o) were found only in the western stations CB-15 and CB-17.5.

For Picozoa, 2060 out of 15 577 reads could be placed on the reference tree. The majority were from studies which exclusively sampled the < 3 µm size fraction, such as the southern Beaufort Sea (Malina; 368), the < 3 µm size fraction from the Chukchi Sea (598), and the Amundsen Gulf Time Series (844) consistent overall with the < 2 µm size range reported for Picozoa (Seenivasan et al. 2013). Like Cryomonadida and Telonemia, Picozoa contained several phylotypes that are mostly or exclusively found in the Chukchi Sea (nodes b, f, g and j), the Amundsen Gulf (node h), or the Beaufort Sea (nodes c and k). However, there were some phylotypes with a broader distribution across different regions (e.g. nodes a and d).

For the choanoflagellates, 2522 out of 4526 reads could be placed on the reference tree. The largest number of reads (825) came from the Canada Basin; the lowest numbers came from the > 3 µm size fraction from the Chukchi Sea (81). The majority of reads (1744 total) from the Chukchi Sea and southern Beaufort Sea (Malina) were placed with the tectiform acanthoecid Didymoeca costata (also referred to as Diplotheca costata in Doweld 2003; nodes f, g and h). In the Canada Basin, 41% of reads (339 total) branched with an environmental clone from Svalbard, NPK2_136 (node b; Luo et al. 2009), in the same clade as the tectiform acanthoecid Diaphanoeca grandis. This phylotype comprised the majority of choanoflagellate reads at the eastern stations PP-2 and PP-6.5 (data not shown). A few nudiform acanthoecid reads (23; node a) were detected from sea-ice, and Crespedida reads (72; nodes i and j) mostly from the Amundsen Gulf Time Series Sixty-three reads were placed at the base of the choanoflagellate tree (node k), and could not be definitely identified.

4.04. Discusssion We mined data from six pyrosequencing datasets in the Western Arctic to identify key factors determining the distribution and diversity of heterotrophic flagellates, a functional guild that

consumes bacteria and picoeukaryotes in the microbial food web (Sherr et al. 1997; Sherr et al. 2002). The distribution of different MAST clades was analyzed using simple barplots, since the taxonomy of this group is well understood (Massana et al. 2004; Lin et al. 2012). For the other four groups EPA was used to identify key phylotypes. A number of factors made it inappropriate to analyze regional trends statistically, including the inherent biases of a PCR-based method such as pyrosequencing (Jeon et al. 2008), differences between studies, and the ability of EPA to place only about a third of reads, causing a dramatic loss of information. An effort is therefore made to discuss only robust-seeming trends in a qualitative fashion.

4.04.1. Regional differences between HF communities All of the target organisms are considered to be heterotrophic and consume bacteria or picophytoplankton, with the exception of the Picozoa, which may be colloid specialists (Seenivasan et al. 2013). Particular HF groups tended to be prevalent in different regions. In the Amundsen Gulf time series and the Malina dataset, from the west of the Amundsen Gulf, dominant HF were MAST and Picozoa, with Telonemia and choanoflagellates accounting for most of the other HF in the sample. In August 2009, SCM samples from both sides of the Gulf had similar proportions of these four groups. In contrast, MAST and Picozoa were also prevalent in the July 2010 Chukchi Sea dataset, especially in the smaller size fraction, but Cryomonadida were much more frequent. Cryomonadida were in the majority in the sea-ice samples themselves, supporting the suggestion that cryothecomonads are primarily ice-dwelling organisms. Both southern Beaufort Sea and Chukchi Sea samples were collected from sites within or near the marginal ice zone. However, while the position of the ice edge in the Beaufort Sea remained relatively stable during the sampling period, the Chukchi Sea in July 2010 was characterized by widening and merging polynyas (U.S. National Ice Centre; URL: http://www.natice.noaa.gov), as is typical for this time of year (Stringer and Groves 1991). The associated ice-melt may have released sea-ice organisms into the water column.

The taxonomic composition of the HF community of Canada Basin samples was strikingly different from that of other datasets, even those which included the > 3 µm size fraction. In particular there was a higher proportion of Telonemia and choanoflagellates (Figure 4.2D), and a virtual absence of MAST-2 (Figure 4.3D) in the Canada Basin. While all other regions reported here were from along the continental shelf, the Canada Basin is offshore and considerably deeper, with the anticyclonic Beaufort Gyre dominating the physical oceanographic properties. The wind field across the gyre causes the vertical downward stacking of water masses with different densities at the center creating a bowl-like structure (Carmack and McLaughlin 2011). This effective down-welling deepens the

71 nitracline to the point that the SCM can be found at 60 m depth or more (McLaughlin and Carmack 2010), providing conditions that could select for the distinctive community found here.

Both Telonemia and choanoflagellates in the Canada Basin were not only more dominant than in other regions, but phylogenetically more diverse (Figure 4.5, 4.7). In contrast, in the southern Beaufort Sea (Malina) each of these groups was dominated by one or two phylotypes. The greater taxonomic evenness in the Canada Basin may result from overall low biomass in this region (Sherr et al. 1997), as high biomass is often associated with the growth of a few opportunistic taxa, which lowers evenness. DNA and RNA-based samples were not markedly different (Figure 4.3D), implying balance between loss and growth processes of the individual taxa, since DNA can be present in both living and dead cells, whereas rRNA is associated with more active cells (Terrado et al. 2011).

4.04.2. Size Fractionation of the HF community Many eukaryotic environmental gene surveys, including in the Arctic, have focused on the < 3 µm size fraction (Vaulot et al. 2008; Comeau et al. 2011). Size fractionation by filtration is prone to errors, as flexible cells may be able to pass through pores smaller than their longest dimension, while pores that are clogged will retain cells smaller than the pore diameter. In addition, free DNA is preserved in the environment and can be retained on the 0.2-µm filter after passing through the 3- µm filter (Sørensen et al. 2013). In practice, while size fractionation enriches for a particular size class, nucleic acids from both larger and smaller cells are inevitably recovered from both filters (Terrado et al. 2009). However, the consequences for interpreting community composition have not been extensively reported.

The Chukchi Sea dataset enabled us to compare results from high throughput sequencing of samples from different size-fractions of the protist community collected by sequential filtration. Samples from the large or mixed size fractions were enriched in Cryomonadida, consistent with the 2.5– 29 µm diameter reported for the Cryomonadida genus Cryothecomonas (Thaler and Lovejoy 2012). In addition EPA showed that some reads assigned to Cryomonadida by sequence similarity were actually the non-Cryomonadida genus Ebria, a planktonic microflagellate (length 24–34 µm) which grazes on diatoms (Hargraves 2002). Samples from the small size fraction were enriched in all HF taxa except Cryomonadida (Table 4.2; Figure 4.2E, F). The strongest enrichment was for MAST and Picozoa. In the Chukchi Sea, MAST reads were roughly 7X more abundant in the small size fraction than the large, and this was particularly marked for MAST-1B and MAST-7. The majority of MAST clades were originally recovered in the < 3 µm size fraction in open water systems, and

were therefore assumed to be picoeukaryotes (Massana et al. 2004), which has been confirmed for several clades that have been investigated using FISH. MAST-1B is reported to be 2–4 µm in diameter (Thaler and Lovejoy 2013, this thesis, chapter 3). In a study of sea-ice environments, MAST-2 has been reported to have a diameter 1.5–3 µm (Piwosz et al. 2013); in the Chukchi Sea datasets, it was enriched in the small size fraction by a factor of two, although it had a relatively high abundance in the large size fraction of stations CN3 and IE (Figure 4.3E, F). Since MAST-7 is uncultivated and no FISH data are available, to our knowledge the size range is not known; however, our results show that MAST-7 in Arctic waters are likely to be picoeukaryotes (< 3 µm). Picozoa, previously known as picobiliphytes, are phylogenetically diverse, yet mostly uncultivated. Cuvelier et al (2008) compiled data from a number of studies and concluded that what they termed biliphytes were mostly > 3 µm. However, single cell genome sequencing (Yoon et al. 2012) and the description of one isolate (Seenivasan et al. 2013) were consistent with at least some Picozoa being picoeukaryotes. In the Chukchi Sea dataset, Picozoa were 13X more abundant in the small size fraction compared to the large size fraction. In EPA, the node d phylotype contains Chukchi Sea reads only from the large size fraction, while nodes b, f, j and k contain Chukchi Sea reads only or mostly from the small size fraction (Figure 4.6), suggesting that large and small Picozoa represent different populations. Alternately, Picozoa reads in the large size fraction may come from < 3 µm Picozoa cells retained on the filter.

4.04.3. Changes in HF with depth In most of the Arctic, water columns consist of different salinity-stratified water masses (Carmack 2007), resulting in strong vertical resource gradients (Martin et al. 2010). Protist community composition in the Arctic is closely associated with water masses rather than geographic location (Hamilton et al. 2008; Lovejoy and Potvin 2011; Monier et al. 2013). Samples from the Amundsen Gulf Time Series came from the SCM, while the Chukchi Sea datasets came from surface waters, and two datasets, from the southern Beaufort Sea (Malina) and Canada Basin, compared different sampling depths. Comparison of phylotypes from the SCM and surface samples in the Canada Basin using EPA (data not shown) did not clearly separate samples by depth. Vertical structuring of the HF community by water mass in the southern Beaufort Sea has already been discussed by Monier et al. (2013), who found that samples from the same water mass were more similar to each other than samples from different water masses at the same station. In the Canada Basin, variability between communities of different water masses may not have been detected because only the > 3 µm size fraction was sampled and most of the HF taxa are found in the smaller size fraction, as discussed above.

73 4.04.4. MAST MAST is a functional category of mostly uncultivated bacterivorous stramenopiles (Massana et al. 2002). MAST often dominate in marine 18S rRNA gene clone libraries. Clades MAST-1 and 7 are globally widespread, including Mediterranean, temperate, arctic and subtropical environments (Massana et al. 2004; Terrado et al. 2011; Cheung et al. 2013), and have been reported to be the most important clades in the Arctic water column (Massana et al. 2006). Similarly, over a much wider sampling region, we found that on average they accounted for 51% and 25% respectively of all MAST reads. Grazing experiments have shown that MAST-1 consumes heterotrophic bacteria (Massana et al. 2009), but similar studies have not been done for MAST-7. A study using stable isotope probing suggests that both clades may consume cyanobacteria at a subtropical site (Frias- Lopez et al. 2009). While cyanobacteria are characteristically absent from Arctic marine environments (Waleron et al. 2007), they could possibly feed on the abundant and similarly-sized photosynthetic eukaryote Micromonas (Lovejoy et al. 2007).

The sub-clade MAST-1A had the highest proportion of reads in nearly all samples, in contrast with the cell count data of Thaler and Lovejoy (2013, this thesis, chapter 3) and Lin et al. (2012), who found MAST-1A at much lower concentrations compared to MAST-1B or -1C in the Arctic and the North Pacific respectively. PCR-based methods are known to disproportionately amplify certain taxa (Jeon et al. 2008), possibly because of preferential primer binding (Potvin and Lovejoy 2009), or variable copy number of the 18S rRNA gene (Zhu et al. 2005), either of which could favour MAST-1A.

MAST-2 was abundant in sea ice in the Arctic based on use of cell counts with FISH (Piwosz et al. 2013). Sea-ice samples from the Beaufort Sea are so dominated by Cryomonadida reads that very few MAST reads can be detected, making it difficult to determine which MAST clades are most abundant. However, an association between MAST-2 and sea ice is consistent with the fact that in the southern Beaufort Sea (Malina) the clade was only present in surface (i.e. ice-influenced) samples (Figure 4.3C).

4.04.5. Cryomonadida Cryomonadida reads dominated in sea-ice (Comeau et al. 2013), and were also found at lower abundances in the water column of all regions (Figure 4.2). In the Chukchi Sea, they were relatively more abundant in the > 3 µm size fraction, consistent with being mostly nanoplankton (Thaler and Lovejoy 2012), although they could also be detected in < 3 µm samples such as from the Amundsen Gulf. They were virtually absent from the Malina Study in the Beaufort Sea, with the exception of

reads retrieved from the 80 m deep sample from Station 620. While it possible that these sequences correspond to a deep ecotype of Cryomonadida, a previous study has shown that Cryothecomonas cells tend to be restricted to surface waters, possibly because of their association with sea-ice and melt water (Thaler and Lovejoy 2012; chapter 2, this thesis). This station at the mouth of the Mackenzie River outflow was also exceptional because the SCM was very weak compared to other stations on either side of the Mackenzie Trough. Asymmetric eddies can form in the canyon (Williams et al. 2008). During the Malina cruise, the nitracline had deepened, possibly due to such an eddy (W. Williams, personal communication), and we speculate that surface Cryomonadida may have been carried to depth with this down-welling eddy. Unfortunately the reads from this sample could not be mapped onto our phylogenetic tree with high likelihood-weight, so their taxonomic identify is uncertain.

In EPA, the Cryothecomonas clades identified by Thaler and Lovejoy (2012; chapter 2, this thesis) were restricted to the Chukchi Sea (Figure 4.4), although they have been detected in other regions using FISH (Thaler and Lovejoy 2012). No Cryomonadia reads were placed in the same clade as C. aestivalis, a species which parasitizes diatoms (Drebes et al. 1996). While cryothecomonad-like cells have been observed associated with diatoms during the spring bloom in northern Baffin Bay (C. Lovejoy, personal communication), Thaler and Lovejoy (2012; chapter 2, this thesis) found, based on FISH and phylogenetic analysis of available sequences, that Cryothecomonas in the Arctic are free-living rather than parasitic. Cryothecomonas was originally described as a free-living predator in sea-ice (Thomsen et al. 1991); however, to our knowledge no similar FISH studies using a Cryothecomonas-specific probe have been carried out in ice environments.

The node f phylotype was almost completely restricted to sea-ice samples, and contained nearly all reads from this dataset. Interestingly, no sea-ice reads were placed with reference sequence MC5-1, a cultured bacterivorous strain isolated from sea-ice in Antarctica (Chantangsi et al. 2010). The node f phylotype must have a very broad halotolerance, since it includes an environmental sequence (KRL01E39) from a brackish lake, while the salinity of brine channels within sea ice can be many times that of seawater (Thomas and Dieckmann 2002).

The node l phylotype was restricted to the Amundsen Gulf, and contained nearly all reads from this dataset. This phylotype is located in a poorly-resolved area of the Cryomonadida tree, at the base of Cryothecomonas. These sequences came from diverse environments, including an unidentified temperate marine cultured strain (Cavalier-Smith and Chao 2003), and environmental sequences from freshwater plankton (Luo et al. 2011), marine sediments (Takishita et al. 2007b), and a

75 macroalgal epiphyte (Haska et al. 2012), and are likely not a natural clade. Better taxon sampling is needed to resolve the identity of these cryothecomonad sequences.

4.04.6. Telonemia Telonemia are a monophyletic taxon with freshwater and marine members. While described species are > 3 µm in diameter (Shalchian-Tabrizi et al. 2006), Telonemia comprised a high proportion of reads from < 3 µm samples in the southern Beaufort Sea (Malina; Figure 4.5). The node s phylotype, of which the majority of reads come from sea-ice, is associated with an environmental sequence from a sediment sample and may represent a taxon adapted to interstitial environments. Few Telonemia reads were recovered from the Chukchi Sea, as area of relatively high productivity. Since Telonemia are thought to feed on cryptophytes and other nanophytoplankton (Bråte et al. 2010b), they may be more abundant in oligotrophic systems dominated by phytoflagellates than in more productive regions dominated by diatoms (Ardyna et al. 2011).

4.04.7. Picozoa In comparison with Cryomonadida and Telonemia, EPA analysis showed that Picozoa contains both geographically restricted and broadly distributed phylotypes (Figure 4.7), suggesting that this group contains both generalist and specialist taxa. The single cultured representative of Picozoa is thought to consume colloidal material and perhaps small viruses (Seenivasan et al. 2013). If so, this group might be less constrained by prey availability than other HF that may have preference for specific bacteria or phytoplankton prey, thus enabling it to grow in different regions and environments.

4.04.8. Choanoflagellates While a few choanoflagellate phylotypes were restricted to a given region (node a in sea-ice; nodes i and j in sea ice and water columns in the Beaufort Sea), most were found in all of the studied regions. There is a rich literature on the distribution of choanoflagellate taxa using microscopic methods; however; comparison with molecular-based results is complicated by historic misidentifications and a lack of cultured representatives. Most studies in polar water columns and sea-ice have focused on Acanthoecida (e.g. Buck and Garrison 1983; Thomsen et al. 1995, 1997; Ikävälko and Gradinger 1997), reflecting both the comparative wealth of diagnostic features in this loricate group, and the dominance of acanthoecids in marine planktonic environments, which is corroborated by our EPA results. Nearly all choanoflagellate reads that could be mapped onto the tree belonged to the order Acanthoecida, which are considered to be mainly planktonic. Ambiguities in the reference tree made it impossible to place reads at a species level; however, in most regions the majority were placed in the genus Didymoeca. Del Campo and Massana (2011)

identified a Didymoeca clade containing sequences from the Arctic water column, the Mediterranean, and a deep anoxic basin, indicating a possibly cosmopolitan distribution for this phylotype.

A few Crespedida species have been reported from subtropical (Vørs 1993a; Tong 1997a) and polar (Throndsen et al. 1970; Vørs 1993b; Tong et al. 1997b) marine water columns, although, with the possible exception of some anoxic water columns (Wylezich et al. 2012), they are always less abundant than acanthoecids. In freshwater plankton, Salpingoeca in particular is known to occur attached to particles, such as the frustules of living diatoms (Šimek et al. 2004).

4.05. Conclusion We found that both the size fraction and the region sampled play a role in determining the taxonomic composition of HF communities in the Arctic. Taxa such as MAST-2 and -7 and Picozoa likely fall into the small size range as they are retrieved in relatively low abundance from > 3 µm samples. Different regions had different typical HF communities. Placement on phylogenetic trees allowed reads to be identified at a high level of taxonomic resolution, revealing both regionally specific and widespread phylotypes, which may make good targets for future research as putative indicators of physical properties or water masses. In addition, this picture of the HF community will form an essential baseline to which future changes can be compared.

4.06. Acknowledgments We thank Marcel Babin (Takuvik, Centre national de la recherche scientifique and Université Laval), for acces to ICESCAPE samples. DNA samples in the Chukchi Sea were collected and extracted by Eva Ortega-Retuerta. Many thanks to André Comeau and Adam Monier for help with pyrosequencing analysis. This study was made possible by fellowships to MT and Discovery grants to CL from the Natural Science and Engineering Council of Canada (NSERC).

77 Table 4.1. References for pyro-tag sequencing data used in this paper. Total reads is given after removing low-quality reads and sub-sampling to an equal number of reads for each sample in a study. Dataset Reference Time Period Sites Number of Size Fraction Total SRA Number Depths reads

Amundsen Comeau et al. 2011 2003-2010 11 1 < 3 µm 78 821 SRA029114 Gulf Time July-November Series

Sea Ice Comeau et al. 2013 March-May 2008 5 na < 3 µm and > 3 µm 48 439 SRA054160 (pooled)

Malina Monier et al. 2013 and Monier July 2009 6 4 < 3 µm 120 560 SRA063446 et al., in preparation

Canada Comeau et al., in preparation August 2007 4 1 > 3 µm 34 452 SRA099217 Basin

Chukchi This paper June-July 2010 12 1 < 3 µm and 56 672 SRP029300 Sea > 3 µm (separate)

Table 4.2. Percentages of HF taxa in < 3 µm and > 3 µm size fractions from the Chukchi Sea. Taxon < 3 µm > 3 µm

Cryomonadida 33 67

Choanoflagellates 71 29

Telonemia 82 18

Picozoa 93 7

MAST 88 12

1A 88 12

1B 100 0

1C 79 11

2 71 29

3 85 15

7 99 1

8 100 0

Figure 4.1. Stations sampled by studies in this paper.

Figure 4.2. Heterotrophic protist groups as a proportion of all eukaryote sequences from studies in the Arctic Ocean. a) Amundsen Gulf time series (Comeau et al. 2011); b) Franklin Bay sea-ice study 2008 (Comeau et al. 2013); c) Beaufort Sea 2009 (Monier et al. 2013); d) Canada Basin 2007 (Comeau et al. unpublished); e) Chukchi Sea < 3 µm (this study); f) Chukchi Sea > 3 µm (this study). Note the different scale in panel e. Panel c x-axis labels: a = “above SCM”, b = “below SCM. „*‟ in e indicates a sample which had a lower number of non-metazoan reads (n = 1044)

Figure 4.3. Marine stramenopile clades as a proportion of all eukaryote sequences from studies in the Arctic Ocean. “Other” includes clades 4, 5, 9 and 10. a) Amundsen Gulf time series (Comeau et al. 2011); b) Franklin Bay sea-ice study 2008 (Comeau et al. 2013); c) Beaufort Sea 2009 (Monier et al. 2013); d) Canada Basin 2007 (Comeau et al. unpublished); e) Chukchi Sea < 3 µm (this study); f) Chukchi Sea > 3 µm (this study). Note the different scale in panel e. Panel c x-axis labels: a = “above SCM”, b = “below SCM. „*‟ in e indicates a sample which had a lower number of non- metazoan reads (n = 1044).

Figure 4.4. Phylogenetic mapping of Cryomonadida reads from all five studies in this paper. Rooted Cryomonadida reference phylogenetic tree was constructed using maximum likelihood from an alignment of 92 sequences and 1689 characters. Some non-Cryomonadida reference sequences have been omitted for clarity. Closed circles indicate nodes with bootstrap support > 50 (out of 100). Reads are mapped onto the nodes marked with blue circles using RAxML evolutionary placement algorithm; only placements likelihood weight > 0.5 are shown. Left scale bar indicates number of substitutions per position. Protaspis longipes (*) was formerly identified as Cryothecomonas longipes (Hoppenrath and Leander 2006) and Rhogostoma minus (**) was formerly identified as Lecythium sp. (Howe et al. 2011). Outgroups (not shown) are two radiolarian sequences and an acantharean (Spongaster tetras AB101542, Lithomelissa setosa HQ651801, Acanthometra fusca KC172856). Reference and outgroup sequences are listed in Supplementary Table S4.3

Figure 4.5. Phylogenetic mapping of Telonemia reads from all five studies in this paper. Rooted Telonemia reference phylogenetic tree was constructed using maximum likelihood from an alignment of 52 sequences and 1942 characters. Closed circles indicate nodes with bootstrap support > 50 (out of 100). Reads are mapped onto the nodes marked with blue circles using RAxML evolutionary placement algorithm; only placements likelihood weight > 0.5 are shown. Left scale bar indicates number of substitutions per position. Labelled clades correspond to Bråte et al. (2010b). Outgroups (not shown) are a haptophyte and a katablepharid (Prymnesium parvum AJ246269 and Katablepharis japonica AB231617). Reference and outgroup sequences are listed in Supplementary Table S4.4

Figure 4.6. Phylogenetic mapping of Picozoa reads from all five studies in this paper. Rooted Picozoa reference phylogenetic tree was constructed using maximum likelihood from an alignment of 55 sequences and 1168 characters. Closed circles indicate nodes with bootstrap support > 50 (out of 100). Reads are mapped onto the nodes marked with blue circles using RAxML evolutionary placement algorithm; only placements likelihood weight > 0.5 are shown. Left scale bar indicates number of substitutions per position. Clades are labelled following Seenivasan et al. 2013. Outgroups (not shown) are a haptophyte, a katablepharid, and a Telonemia (Prymnesium parvum AJ246269, Katablepharis japonica AB231617 and Telonema antarcticum (AJ564773). Reference and outgroup sequences are listed in Supplementary Table S4.5

Figure 4.7. Phylogenetic mapping of choanoflagellate reads from all five studies in this paper. Choanoflagellate reference phylogenetic tree was constructed using maximum likelihood from an alignment of 49 sequences and 1963 characters. Closed circles indicate nodes with bootstrap support > 50 (out of 100). Reads are mapped onto the nodes marked with blue circles using RAxML evolutionary placement algorithm; only placements likelihood weight > 0.5 are shown. Left scale bar indicates number of substitutions per position. Outgroups (not shown) are two metazoan sequences, Mnemiopsis leidyi (AF293700) and Beroe ovata (AF293694), a sponge (AY348876), two ichthyosporeans (Y16260 and AF232303), and Corallochytrium (L42528). Reference and outgroup sequences are listed in Supplementary Table S4.6

87 Supplementary Table S4.1. Number of reads per sample after processing

Sample Reads Sample Reads Sample Reads Amundsen Gulf Time Series: Malina: Canada Basin: October 2003 7064 670 below SCM 4849 All samples 3132 November 2003 6784 670 SCM 5128 July 2004 7247 670 above SCM 5002 Chukchi Sea < 3 µm: August 2004 7404 670 surface 4805 BS1 2378 September 2005 7021 620 below SCM 4860 AN1 5185 October 2006 6965 620 SCM 4996 KS6 4812 November 2007 6945 620 above SCM 5057 EC5 3969 July 2008 7247 620 surface 4999 HLY 4893 August 2009 7455 760 below SCM 4745 CC18 5403 October 2009 7123 760 SCM 4955 CN3 3374 October 2010 7566 760 above SCM 5200 CN14 4775 760 surface 4996 BCH7 4571 Sea-Ice: 540 below SCM 4847 IE 5209 D32 bottom 3996 540 SCM 5156 HSN5 2631 D32 top 3928 540 above SCM 5125 D41-1 bottom 4048 540 surface 5160 Chukchi Sea > 3 µm: D41-1 slurp 4110 430 below SCM 4931 BS1 4530 D41-1 top 3869 430 SCM 5237 AN1 6214 D46 bottom 4395 430 above SCM 5243 KS6 4952 D46 top 4049 430 surface 5128 CHA1 3214 F1L bottom 3966 460 below SCM 4845 EC5 5798 F1L top 4133 460 SCM 5167 HLY 5427 F1M bottom 3897 460 above SCM 5194 CC18 4832 F1M top 3987 460 surface 4935 CN3 6087 F21 bottom 4061 CN14 1044 BCH7 5184 IE 3160

Supplementary Table S4.2. Pyrosequencing raw data, filtering and OTU statistics for data from ICESCAPE 2010 study. Percentages are given relative to reads available from the preceding step. Processing Step > 3 µm size fraction 0.22–3 µm size fraction

Pre-filtering:

Total Reads 138 658 137 727

Mean Length 343 bp 308 bp

Post-filtering:

Reads retained after quality control 64 139 (46%) 49 451 (36%)

Mean Length 435 bp 431 bp

Metazoans, fungi and land plants removed 54 319 (85%) 47 594 (96%)

Chimeras and poorly aligned reads removed 53 600 (99%) 47 200 (99%)

Singletons removed 50 645 (94%) 44 643 (95%)

OTU analysis (97% level)a

OTUs all samples (non-redundant) 1 132 986

OTUs all samples (cumulative) 3 111 3 228

Mean OTUs per sample 283 293

89 Supplementary Table S4.3. Cercozoan sequences used to construct a reference tree for phylogenetic placement of Cryomonadida reads. Protaspis longipes (*) was formerly identified as Cryothecomonas longipes (Hoppenrath and Leander 2006) and Rhogostoma minus (**) was formerly identified as Lecythium sp. (Howe et al. 2011).

Sequence Name NCBI Accession Sequence Name NCBI Accession Number Number Thaumatomonas sp. U42446 BOLA383 AF372765 Heteromita globosa U42447 Cercomonas plasmodialis AF411268 Paulinella chromatophora X81811 WHOILI1-14 AF411273 Spongaster tetras AB101542 Proleptomonas faecicola AF411275 TAGIRI-1 AB191409 Bodomorpha minima AF411276 TAGIRI-2 AB191410 Metopion-like sp. AF411278 NAMAKO-3 AB252743 Rigidomastix-like sp. AF411279 NAMAKO-10 AB252750 Spongomonas minima AF411280 ATCC 50404 NAMAKO-15 AB252755 Dimorpha-like sp. ATCC AF411283 50522 NAMAKO-16 AB252756 Gymnophrys cometa AF411284 DSGM-42 AB275042 Euglypha rotunda strain AJ418784 Teneriffa DSGM-43 AB275043 Pseudodifflugia cf. gracilis AJ418794 DSGM-45 AB275045 LKM45 AJ130856 DSGM-46 AB275046 Rhogostoma minus** AJ514867 DSGM-47 AB275045 Pseudopirsonia mucosa AJ561116 P845 DSGM-49 AB275049 CH1 2A 20 AY821945 DSGM-57 AB275057 Ebria tripartita isolate 1 DQ303922 DSGM-58 AB275058 Thaumatomonas DQ211591 coloniensis strain HFCC59 CYSGM-11 AB275094 Bodomorpha sp. HFCC57 DQ211596 CYSGM-13 AB275096 Protaspis grandis DQ303924 Masisteria marina LFS1 AF174372 NOR26.10 DQ314809 Cryothecomonas aestivalis 1 AF290539 NW617.37 DQ314810 Protaspis longipes * AF290540 NOR46.14 DQ314811 Cryothecomonas aestivalis 2 AF290541 UEPACMp4 DQ369017 Thaumatomastix sp. ATCC AF411261 Thaumatomonadida env. EF023494 50350 Amb_18S_1084 Allas diplophysa AF411262 Thaumatomonas seravini EF455776 BOLA322 AF372764 NPK2_74 EU371162

Supplementary Table S4.3. Cercozoan sequences used to construct a reference tree for phylogenetic placement of Cryomonadida reads. Protaspis longipes (*) was formerly identified as Cryothecomonas longipes (Hoppenrath and Leander 2006) and Rhogostoma minus (**) was formerly identified as Lecythium sp. (Howe et al. 2011). Continued

Sequence Name NCBI Accession Sequence Name NCBI Accession Number Number Auranticordis quadriverberis EU484393 KRL01E39 JN090899 isolate 1 Protaspis obaniformis FJ824124 SHAU417 JQ222903 Protaspis oviformis FJ824125 SHAU427 JQ222907 MC5-1Cryo GQ144679 SHAU434 JQ222910 Capsellina sp. ATCC 50039 GQ377676 SHAU482 JQ222930 ME Euk FW116 GU385611 SHAU483 JQ222931 STFeb_183 HM135090 SHAU494 JQ222935 Lithomelissa setosa isolate 15 HQ651801 SHAU549 JQ222959 P1H8 Malina JF698753 SHAU556 JQ222963 P2D11 Malina JF698755 SHAU620 JQ222997 Ch8A2mA11 JF730755 SHAU651 JQ223011 North Pole SI60 153 JF826318 SHAU671 JQ223021 BF9_3A7G JN048119 SHAU702 JQ223037 BF9_3B1D JN048120 SHAU764 JQ223060 LS16_16A1D JN048123 KRL03E39 KC315817 NB30_23A9G JN048125 Acanthometra KC172856 fusca KRL01E2 JN090862

91 Supplementary Table S4.4. Telonemia sequences used to construct a reference tree for phylogenetic placement of reads. Sequence Name NCBI Accession Sequence Name NCBI Accession Number Number Katablepharis japonica AB231617 BL040126.Telo.6 GQ365796 Prymnesium parvum AJ246269 BL040126.Telo.9 GQ365798 K001 RA010412.17 AJ564767 IND31.Telo.10 GQ365799 RA000412.136 AJ564768 IND31.Telo.2 GQ365805 BL010625.25 AJ564770 IND60.Telo.3 GQ365845 RCC404.5 AJ564771 IND72.Telo.5 GQ365855 Telonema antarcticum AJ564773 IND72.Telo.9 GQ365859 IND31.100 AM418563 Nor26.Telo.10 GQ365861 SCM38C20 AY665037 Nor26.Telo.6 GQ365865 SCM27C23 AY665040 Nor26.Telo.9 GQ365867 SCM27C12 AY665041 Nor46.Telo.1 GQ365868 SCM27C46 AY665043 Nor46.Telo.3 GQ365889 M2_18G12 DQ103827 Nor46.Telo.4 GQ365900 M3_18B12 DQ103867 Dhr41.Telo.4 GU117661 PD6.20 DQ647533 Dhr41.Telo.16 GU117662 NA2_1F1 EF526892 Dhr41.Telo.1 GU117663 SA1_2A10 EF526966 Dhr41.Telo.15 GU117665 SS1_E_01_20 EU050980 Lut.Sed.50.3 GU117666 IND31.Telo.3 GQ365815 Lut.Sed.20.2 GU117667 IND31.Telo.8 GQ365836 Lut.Sed.20.9 GU117669 IND33.Telo.2 GQ365839 Lut.Telo.23 GU117672 IND33.Telo.6 GQ365842 Lut.Telo.21 GU117673 PTG4SP2005 EU162631 Lut.Telo.24 GU117675 NPK2_190 EU371188 Lut.Telo.20 GU117676 NPK97_27 EU371359 Lut.Telo.13 GU117681 NPK97_25 EU371360 Lut.Telo.15 GU117682 NPK97_119 EU371379 Pol.Telo.1 GU117683 AD6.Telo.13 GQ365764 Pol.Telo.2 GU117684 AD6.Telo.2 GQ365766 Pol.Telo.3 GU117685 AD6.Telo.20 GQ365767 Pol.Telo.4 GU117686 AD6.Telo.4 GQ365768 Pol.Telo.7 GU117687 BL040126.Telo.1 GQ365769 Svv.Telo.1 GU117690 BL040126.Telo.10 GQ365770 Svv.Telo.3 GU117691

Supplementary Table S4.5. Picozoa sequences used to construct a reference tree for phylogenetic placement of reads. Sequence Name NCBI Accession Sequence Name NCBI Accession Number Number BL000921.8 AY426835 SHAC744 HQ867420 NOR46.29 DQ060523 SHAX724 HQ868497 NW414.27 DQ060524 SHAX927 HQ868690 NW617.02 DQ060525 SHAX1019 HQ868776 NOR50.52 DQ060527 SHAX1135 HQ868882 HE001005.148 DQ222874 SHAX587 HQ869075 OR000415.159 DQ222875 SHBA597 HQ869261 RA000907.54 DQ222877 SHBF578 HQ869605 RA000907.18 DQ222879 SHBF765 HQ869778 HE000803.72 DQ222873 SHBF478 HQ869765 RA000907.33 DQ222876 “Cyanophora” clone JF791041 7532 FS01AA11_01Aug05_5m EU368003 EMC_2G08 JN693069 FS01AA94_01Aug05_5m EU368004 SHAU435 JQ222911 FS04GA95_01Aug_05_5m EU368020 SHAA389 JQ226352 FS04GA46_01Aug05_5m EU368021 AN0610_14L12A JQ956194 EN351CTD039_39m30N EU368037 Picomonas judraskeda JX988758 AI5F15RM3A09 GU822951 PICOBI01F-L52R-11 JX988759 CB1901S20 HQ222462 PICOBI01F-L52R-7 JX988760 CFL146DB13 HM561168 PICOBI01F-L52R-12 JX988761 CFL119DB12 HM561172 PICOBI01F-L52R-9 JX988762 HM595055 PICOBI01F-L52R-8 JX988763 MO.011.10m.00003 HM858787 PICOBI01F-L52R-10 JX988764 100609_15 HQ156832 PICOBI01F-L52R-18 JX988765 SHAX1043 HQ797868 PICOBI02F-L52R_14 JX988766 SHAC623 HQ867337 PICOBI02F-L52R_He JX988767 SHAC648 HQ867354

93 Supplementary Table S4.6. Choanoflagellate sequences used to construct a reference tree for phylogenetic placement of reads. Sequence Name NCBI Accession Sequence Name NCBI Accession Number Number Helgoeca nana L10823 M1_18E10 DQ103820 Diaphanoeca grandis L10824 M1_18A02 DQ103821 Corallochytrium L42528 NOR46.34 DQ120005 limacisporum Sphaeroforma arctica Y16260 NPK2_136 EU371175 Amoebidium parasiticum Y19155 Codonosigidae EF024012 ATCC 32708 Amb_18S_1490 DSGM-66 AB275066 SL118_1 EF432538 Desmarella moniliformis AF084231 Choanoflagellida sp. EF432541 SL163 D10 Acanthoeca spectabilis AF084233 NA1_1F3 EF526885 Diaphanoeca grandis AF084234 Acanthoeca spectabilis EU011922 Monosiga brevicollis AF100940 Didymoeca costata EU011923 Salpingoeca infusionum AF100941 Salpingoeca sp. EU011925 Ichthyophonus iregularis AF232303 Stephanoeca diplocostata EU011926 Australia Monosiga ovata AF271999 Savillea micropora EU011928 Polyoeca dichotoma AF272000 Salpingoeca sp. ATCC EU011929 50153 Beroe ovata AF293694 Salpingoeca sp. ATCC EU011930 50929 Mnemiopsis leidyi AF293700 Salpingoeca urceolata EU011931 OLI11013 AJ402331 UI13C07 EU446341 Choanoeca perplexa AY149896 UI13H07 EU446354 Codonosiga gracilis AY149897 cLA12G11 EU446388 Choanoeca perplexa AY149898 cLA14G03 EU446410 Chondrosia reniformis AY348876 1b-B4 FN690451 BL000921.20 AY426842 3b-F6 FN690481 SCM28C135 AY665096 TKR07E.2 GU290066 CV1_B1_36 AY821948 Salpingoeca tuba HQ026774 Diaphanoeca grandis DQ059033

Chapter 5 : Conclusions Générales

Face à la transformation qui a lieu dans l‟Arctique, il est important de documenter la présente distribution des HF afin d‟évaluer et de prévoir les changements au sein de cette communauté. L‟étude de la biogéographie des organismes marins microscopiques est rendue plus complexe par leur petite taille ainsi que par le caractère dynamique de leur environnement. Le premier objectif de la présente thèse était d‟utiliser les techniques basées sur le gène 18S ARNr pour détecter les répartitions géographiques des HF dans l‟Arctique. Nous avons conclus que les différents taxons HF ont des répartitions distinctes.

Le second objectif de cette thèse était de comprendre comment les variables environnementales déterminent ces répartitions, afin de prédire comment les changements environnementaux affecteront la composition des communautés HF. Certains facteurs ont été identifiés comme importants pour des taxons spécifiques, notamment la proximité au bord de glace pour Cryothecomonas et MAST-1C. Cependant, cette étude était par nécessité descriptive, et démêler les mécanismes derrière ces tendances est au-delà de sa portée. Comme discutée dans la section « Perspectives » ci-dessous, notre étude en soulignant les taxons et les processus qui mériteraient le plus un effort de recherche peut servir à orienter les futurs travaux descriptifs et expérimentaux. Le but ultime est non seulement de prévoir les réponses aux changements, mais d‟estimer leurs répercussions sur les autres compartiments du réseau trophique et sur le cycle de carbone.

5.01. Synthèse de l’étude Le premier article de cette thèse (chapitre 2) porte sur un seul genre, Cryothecomonas. La présence de ce genre dans les banques de clones de l‟Arctique était déjà connue (Lovejoy et al. 2006; Balzano et al. 2012), et les résultats de séquençage à haut-débit ont souligné son importance (Comeau et al. 2013; Monier et al. 2013). Mais, très peu de représentants ont été cultivés, et ils sont rarement rapportés dans les relevés microscopiques (excepte, par exemple Sime-Ngando 1997a, b; Tillmann et al. 1999). Donc, une meilleure connaissance de leur abondance, de leur répartition, ainsi que de leur mode de vie dans l‟Arctique, ajouterait substantivement à notre compréhension du réseau microbien dans cet environnement distinct.

L‟analyse phylogénétique met en évidence un clade bien défini de Cryothecomonas, contenant seulement des représentants marins. Cette analyse a montré que les séquences provenant de l‟Arctique n‟étaient pas apparentés à l‟espèce parasitoïde C. aestivalis, conforté par les expériences de broutage, et les observations microscopiques. Donc à ce jour nous supposons que les

95 Cryothecomonas dans l‟Arctique sont des prédateurs, comme cela a été rapporté pour plusieurs espèces de ce genre dans la glace de mer en Antarctique (Thomsen et al. 1991).

Notre hypothèse était que la concentration des cellules de Cryothecomonas serait corrélée aux variables environnementales physiques, tel que la salinité et la température, ou biologiques, tel que la présence des proies ou prédateurs. Une analyse statistique a démontré que 1) la proximité à la glace de mer, et 2) la biomasse photosynthétique, étaient significativement corrélées avec Cryothecomonas. De plus, ces observations semblaient se restreindre aux eaux de surface. Leur distribution verticale et l‟association avec la glace suggèrent un lien entre Cryothecomonas et les eaux influencées par la fonte de glace, en accord avec des rapports microscopiques historiques (Thomsen et al. 1991; Sime-Ngando et al. 1997b).

Le deuxième article de cette thèse (chapitre 3) porte sur trois sous-clades du taxon straménopile MAST-1, MAST-1A, -1B et -1C, déjà connus comme étant des taxons importants dans les Océans mondiaux (Lovejoy et al. 2006; Massana et al. 2006; Lin et al. 2012). Parallèlement au chapitre 2, notre hypothèse était que la répartition de ces trois sous-clades serait associée aux gradients environnementaux.

L‟analyse phylogénétique met en évidence des groupes restreints aux hautes ou basses latitudes chez le sous-clade MAST-1C, similaires aux groupes identifiés par Lin et al (2012). Bien qu‟il n‟y avait pas une forte robustesse (bootstrap) dans notre analyse, un de ces groupes se distinguait par un motif caractéristique de 25 pb dans la région variable V4 du gène 18S. Ce type de motif devient plus important pour identifier les différents clades phylogénétiques lorsque les séquences sont trop courtes pour obtenir une bonne résolution taxonomique, notamment pour le séquençage à haut débit.

Par contraste avec Cryothecomonas, le clade MAST-1 n‟était pas restreint à la surface, mais distribué dans la zone euphotique. Les trois sous-clades avaient des répartitions différentes. MAST- 1A était le moins abondant des trois clades. MAST-1B semblait avoir une meilleure survie dans les eaux profondes, et était retrouvé à une haute concentration à une profondeur de 360 m sur une des stations étudiées. L‟analyse statistique a montré que MAST-1C était significativement plus abondant aux stations près du bord de glace que les stations éloignées. Ce constat pourrait indiquer qu‟il profite de la productivité élevée typique des zones marginales de glace (Sullivan et al. 1988). MAST-1A était le moins abondant des trois clades.

Le troisième article de cette thèse (chapitre 4) diffère aux autres articles car il concerne l‟ensemble de la communauté HF. Il y a une comparaison entre divers environnements rencontrés à travers l‟Arctique, de nouvelles séquences provenant du séquençage à haut débit sont utilisées, ainsi que des données d‟études précédentes déjà publiées. Les différentes méthodologies et les régions géographiques ont mis en évidence des communautés HF distincts. En général, les études qui ont échantillonné la fraction de taille < 3 µm étaient dominées par les Picozoa et les MAST, en particulier le clade MAST-7, alors que les études qui ont échantillonné la fraction > 3 µm ont trouvé une proportion plus haut de Cryomonadida. Cependant, même en tenant compte des différences de fraction de taille, il restait des différences parmi les différentes régions. De plus, l‟ensemble des données du Bassin du Canada était caractérisé par une plus grande équitabilité des taxons, et une plus grande importance de Telonemia et des choanoflagellés. Il se pourrait que la biomasse, généralement faible dans le Bassin du Canada, agisse sur le fait qu‟il est moins de taxons dominants qui ont tendance à diminuer la diversité.

L‟embranchement des reads courts sur les arbres phylogénétiques a permis l‟identification des taxons dominants et leurs répartitions dans les régions d‟étude, et ceci à une échelle phylogénétique très fine. Dans chacun des cinq taxons, il y avait des phylotypes qui étaient abondants, mais semblaient restreints à un ou deux ensembles de données. À l‟inverse, le phylotype Didymoeca chez les choanoflagellés, était abondant dans toutes les régions, quelque soit la méthodologie. Une attention particulière pourrait être mise sur ces phylotypes clés pour de futures recherches chez les communautés Arctiques eucaryotes.

5.02. Comparaison des techniques moléculaires L‟utilisation de différentes techniques dans les trois articles de cette thèse a permis d‟obtenir une robustesse dans nos résultats et souligner quelques particularités propres à chaque technique. Par exemple, la dominance de Cryomonadida dans les échantillons de glace de mer détectée par le séquençage à haut débit était en accord avec les résultats de comptage des cellules au microscope, qui ont suggéré que les Cryothecomonas au sein la colonne d‟eau s‟associent avec l‟eau de fonte de la glace. Ainsi, la position des reads courts sur un arbre de référence de Cryomonadida a confirmé l‟absence du taxon parasitoïde C. aestivalis dans l‟Arctique, et a appuyé les observations microscopiques que les Cryothecomonas ne parasitent pas les diatomées dans cette région. Par contre, l‟importance du sous-clade MAST-1A dans les ensembles de données de séquençage à haut débit n‟était pas validée par les comptes microscopiques, qui ont montré que ce taxon était comparativement rare. Cette divergence a été probablement introduite dans l‟étape initiale de PCR

97 pour le pyroséquençage, peut-être à cause d‟une plus haute affinité de l‟amorce avec MAST-1A, ou un nombre élevé de copies du gène 18S ARNr.

L‟efficacité des techniques comme la FISH ou l‟identification des reads par la similarité des séquences dépend dès la base d‟un arbre phylogénétique complet et fiable. Nous attendons que l‟établissement de cultures pour plus de flagellés hétérotrophes fournisse des séquences de références qui rendront nos arbres plus informatifs.

5.03. Perspectives Cette étude de la répartition des HF dans l‟Arctique a mis sur place le contexte pour de futures recherches. Elle peut informer la planification des futures campagnes d‟échantillonnage pour remplir les lacunes et répondre plus efficacement aux questions des recherches, visant en particulier la relation entre les communautés de glace et de la colonne d‟eau. Notre connaissance de la communauté Arctique, et notre capacité de prévoir sa réponse aux changements climatiques, bénéficierait également des expériences visant le rôle des taxons HF spécifiques dans les réseaux trophiques et les flux de carbone.

5.03.1. Échantillonnage taillé aux questions de recherche Un grand avantage de la FISH par rapport aux banques de clones ou même le séquençage à haut débit est la capacité d‟analyser, de façon relativement rapide, un grand nombre d‟échantillons pour permettre une analyse statistique capable de répondre aux questions écologiques. Par contre, les analyses de la présente étude étaient limitées par un échantillonnage déséquilibré dû à son caractère opportuniste. Idéalement, un échantillonnage planifié et suffisamment répliqué à travers la zone marginale de glace jusqu‟à l‟eau ouverte pourrait clarifier la relation entre les taxons comme MAST-1C et Cryothecomonas et les effets interconnectés de la biomasse photosynthétique et le bord de glace.

La glace de mer elle-même contient une communauté distincte d‟organismes qui proviennent de la colonne d‟eau mais sont sélectionnés par les conditions dans la glace (Rñżańska et al. 2008). Les résultats de FISH sur la colonne d‟eau, ainsi que les études précédentes (Thomsen et al. 1991; Garrison et al. 2005; Comeau et al. 2013), suggèrent que dans l‟Arctique Cryothecomonas est un taxon de la glace de mer qui se trouve incidemment dans la colonne d‟eau, tandis que l‟inverse est vrai pour les sous clades de MAST-1. Cependant, confirmer ces constats écologiques exigera l‟observation de cellules viables dans les échantillons de glace avec la FISH. Piwosz et al. (2013) ont déjà détecté plusieurs taxons protistes, incluant les clades MAST-1, -2 et -6, dans la glace de

mer dans le détroit de Barrow. Mais, ces données sont toujours manquantes pour la plupart des groupes de flagellés hétérotrophes identifiés comme important dans la présente thèse. Les sondes d‟oligonucléotides ont déjà été conçues pour Cryothecomonas (Thaler et Lovejoy 2012, cette thèse, chapitre 2), et Picozoa (Not et al. 2007a), mais ces sondes n‟ont jamais été appliquées aux échantillons de glace, et de plus les sondes n‟ont jamais été conçues pour Telonemia et MAST-7, qui sont des taxons importants dans l‟Arctique. Pour les choanoflagellés, leur distribution dans la glace de mer a déjà été bien étudiée avec la microscopie de lumière conventionnelle (Ikävalko et Gradinger 1997; Thomsen et al. 1997), mais les inconsistances historiques dans l‟identification des taxons par comparaison avec les données moléculaires sont problématique. Pour tous ces taxons, la comparaison de leurs répartitions par la FISH dans la glace de mer et les colonnes d‟eaux améliorerait notre compréhension de leur écologie et des processus sous-jacents de leur variation saisonnière.

Finalement, la méta-analyse des données du chapitre 4 a également révélé certaines lacunes importantes dans la couverture régionale des études par le séquençage à haut débit. Par exemple, il ne couvrait pas le nord de la Mer de Baffin, une région physiquement et biologiquement bien caractérisée dont la productivité primaire soutient une importante productivité aux niveaux supérieurs du réseau trophique. Au moment de la rédaction de cette thèse, les échantillons ont été récoltés dans la Mer de Baffin et séquencés à haut débit, et leur analyse sera le sujet d‟une future publication.

5.03.2. Mesure des taux écologiques Les descriptions de la répartition des taxons ne fournissent jamais plus qu‟une connaissance indirecte des interactions qui structurent les réseaux trophiques, et le mouvement de carbone dans ces réseaux. Les expériences qui manipulent les échantillons naturels ou les souches cultivées sous des conditions contrôlées permettraient de comprendre les processus qui sous-tendent les répartitions géographiques décrites dans cette thèse et peuvent aider pour prévoir les effets des changements environnementaux.

Le chapitre 2 de cette thèse a essayé de mesurer l‟impact du broutage sur les bactéries par un taxon flagellé hétérotrophe, Cryothecomonas, en utilisant la technique des FLB, mais ne l‟a pas détecté. La mesure du broutage est assujettie à plusieurs défis. Par exemple, Massana et al. (2009) étaient seulement capable d‟obtenir des taux fiables pour MAST-1C entre les trois sous clades de MAST-1. Supposant que les précautions pour éviter l‟agrégation des FLB ou l‟égestion des cellules à cause du fixatif avaient réussi, au moins trois interprétations sont possibles pour ce résultat. En premier,

99 Cryothecomonas pourrait brouter sur les phytoplanctons au lieu des bactéries, une explication appuyée par la correspondance positive avec la biomasse photosynthétique. Deuxièmement, Cryothecomonas pourrait brouter sur les bactéries, mais les FLB, qui sont des cellules mortes, sont défavorisées par la sélection des proies. En ce cas, il serait possible d‟achever une meilleure approximation de leurs taux de broutage naturels en leur offrant comme proies les bactéries vivantes qui sont marquées par la FISH après l‟ingestion (p. ex. Massana et al. 2009). La troisième possibilité est que le nombre faible de cellules Cryothecomonas dans les échantillons pourrait avoir empêché la détection du broutage. Une étude de séquençage à haut débit (Comeau et al. 2013; cette thèse, chapitre 4) suggère que nous pourrions retrouver une plus forte concentration de Cryothecomonas dans les échantillons de glace de mer. Ces échantillons peuvent donc fournir un meilleur substrat pour les expériences de broutage. C‟est également possible augmenter la concentration de flagellés hétérotrophes dans les échantillons naturels par une incubation de l‟eau de mer dans le noir sans l‟ajout de nutriments (Massana et al. 2006b). Une ou plusieurs de ces techniques mentionnées ci-dessus pourraient ultimement permettre la mesure d‟un taux de broutage pour Cryothecomonas. Cela permettrait l‟évaluation de leur impact sur les populations bactériennes, et ajouterait au paramétrage du cycle de carbone.

Il est indispensable de savoir l‟effet des facteurs environnementaux sur les taux écologiques comme le broutage ou la croissance afin de prédire les impacts des changements environnementaux. Mais, bien que les répartitions des taxons donnent un indice des facteurs environnementaux importants, il reste difficile d‟isoler les effets des variables différentes dans les systèmes naturels. La façon la moins ambiguë pour mesurer la réponse d‟un taxon, c‟est dans les conditions contrôlées d‟une expérience avec une souche en culture. Par contre, les cultures sont difficiles à établir et maintenir car les HF présentent des défis particuliers à cause de leur petite taille et leur besoin de carbone organiques. Mais, des techniques comme le tri des cellules individus par la FCM ont réussi cultiver plusieurs taxons HF (del Campo et al. 2013).

À l‟exception des choanoflagellés (par exemple au moment de rédaction 11 souches sont disponibles sur le site web de la « American Type Culture Collection » URL : http://www.atcc.org), les taxons discutés dans cette thèse ont peu ou aucun représentants cultivés. Des souches de Cryothecomonas ont été établies trois fois en culture (Drebes et al. 1996; souche APCC MC5- 1Cryo) et par la suite perdues (L.K. Medlin, R. Gast, communications personnelles). Chez les MAST, le clade MAST-3 a été identifié avec la souche cultivée d‟un épiphyte sur les diatomées, Solenicola setigera (Gómez et al. 2011), mais à notre connaissance les autres clades restent incultivés. Picozoa et Telonemia ont une et deux souches cultivés respectivement (Klaveness et al.

100

2005; Seenivasan et al. 2013). Étant donné la grande variation phylogénétique détectée chez ces deux groupes par les méthodes indépendantes de culture, il serait naturellement souhaitable d‟avoir un plus grand nombre de souches cultivées possibles pour s‟assurer qu‟elles reflètent la variation écologique dans les échantillons naturels.

5.03.3. Impact des changements climatiques Le retrait récent de la glace de mer dans l‟Arctique affecte la communauté des eucaryotes unicellulaires à travers des changements de lumière, de salinité, et de mélange de la colonne d‟eau (Li et al. 2009). Une motivation majeure pour comprendre les facteurs environnementaux qui influencent les répartitions des taxons HF c‟est de prévoir comment ces communautés changeront dans l‟avenir. Les taxons identifiés comme ayant des répartitions restreintes (chapitre 4) devraient être particulièrement sensibles aux changements, et seront donc d‟intérêt pour de futures études. Pour certains taxons, comme Cryothecomonas et MAST-1C, il a été possible de constater que la proximité au bord de glace était un facteur environnemental conduisant ces répartitions. Le retrait de la glace fera que plusieurs régions présentement couvertes deviendront des zones marginales de glace, alors que des présentes zones marginales deviendront des eaux ouvertes. Donc jusqu‟à présent, il n‟est pas possible de déterminer si l‟effet du retrait de la glace aura un effet positif ou négatif sur les populations de ces taxons. Néanmoins, les changements dans leurs abondances peuvent servir pour signaler des changements de régime dans les écosystèmes arctiques.

101

Bibliographie

Aagaard K, Coachman LK, Carmack E (1981) On the halocline of the Arctic Ocean. Deep- Sea Res 28A: 529–545. ACIA (2005) Impacts of a warming Arctic—Arctic Climate Impact Assessment. Cambridge University Press, 1042 pages. Adl SM, Simpson AGN, Lane CE, Lukeš J, Bass D, Bowser SS, Brown MW, Burki F, Dunthorn M, Hampl V, Heiss A, Hoppenrath M, Lara E, Le Gall L, Lynn DH, McManus H, Mitchell EAD, Mozley-Stanridge SE, Parfrey LW, Pawlowski J, Rueckert S, Shadwick L, Schoch CL, Smirnov A, Spiegel FW (2012) The revised classification of Eukaryotes. J Eukaryot Microbiol 59: 429–493. Aljanabi SM, Martinez I (1997) Universal and rapid salt-extraction of high quality genomic DNA for PCR-based techniques. Nucleic Acids Res 25: 4692–4693. Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25: 3389–3402. Amann RI, Binder BJ, Olson RJ, Chisholm SW, Devereux R, Stahl DA (1990a) Combination of 16S rRNA-targeted oligonucleotide probes with flow cytometry for analyzing mixed microbial populations. Appl Environ Microbiol 56: 1919–1925. Amann RI, Krumholz L, Stahl DA (1990b) Fluorescent-oligonucleotide probing of whole cells for determinative, phylogenetic and environmental studies in microbiology. J Bacteriol 172: 762–770. Amann RI, Ludwig W, Schleifer K-H (1995) Phylogenetic identification and in situ detection of individual microbial cells without cultivation. Microbiol Rev 59: 143– 169. Ardyna M, Gosselin M, Michel C, Poulin C, Tremblay J-É (2011) Environmental forcing of phytoplankton community structure and function in the Canadian High Arctic: contrasting oligotrophic and eutrophic regions. Mar Ecol Prog Ser 442: 37–57. Arndt H, Dietrich D, Auer B, Cleven E-J, Gräfenhan T, Weitere M, Mylnikov AP (2000) Functional diversity of heterotrophic flagellates in aquatic ecosystems. In: Leadbeater, B. S. C. & Green, J. C. (ed.), The Flagellates. Taylor & Francis, London. p. 240--268. Arrigo KR, van Dijken G, Pabi S (2008) Impact of a shrinking Arctic ice cover on marine primary production. Geophys Res Lett 35: L19603. DOI: 10.1029/2008GL035028, Auer B, Arndt H (2001) Taxonomic composition and biomass of heterotrophic flagellates in relation to lake trophy and season. Freshwater Biol 46: 959–972. Azam F, Fenchel T, Field JG, Gray JS, Meyer-Reil LA, Thingstad F (1983) The ecological role of water-column microbes in the sea. Mar Ecol Prog Ser 10: 257–263. Bachy C, López-García P, Vereshchaka A, Moreira D (2011) Diversity and vertical distribution of microbial eukaryotes in the snow, sea ice and seawater near the North Pole at the end of the polar night. Front Microbiol 2:106. Bâcle J, Carmack EC, Ingram RG (2002) Water column structure and circulation under the North Water during spring transition: April–July 1998. Deep-Sea Res II 49:4907- 4925. Balzano S, Marie D, Gourvil P, Vaulot D (2012) Composition of the summer photosynthetic pico and nanoplankton communities in the Beaufort Sea assessed by

103 T-RFLP and sequences of the 18S rRNA gene from flow cytometry sorted samples. ISME J 1: 1–19. Balzer S, Malde K, Lanzén A, Sharma A, Jonassen I (2010) Characteristics of 454 pyrosequencing data—enabling realistic simulation with flowsim. Bioinformatics 26: i420–i425. Barwell-Clarke J, Whitney F (1996) Institute of ocean sciences nutrient methods and analysis. Can Tech Rep Hydrogr Ocean Sci 182:vi+43. Bass D, Howe AT, Mylnikov AP, Vickerman K, Chao EE, Smallbone JE, Snell J, Cabral C, Cavalier-Smith T (2009) Phylogeny and classification of Cercomonadida (Protozoa, Cercozoa): Cercomonas, Eocercomonas, Paracercomonas, and Cavernomonas gen. nov. Protist 160: 483–521. Bell, T, Newman JA, Silverman BW, Turner SL, Lilley AK (2005) The contribution of species richness and composition to bacterial services. Nature 436: 1157–1160. Belzile C, Brugel S, Nozais C, Gratton Y, Demers S (2008) Variations of the abundance and nucleic acid content of heterotrophic bacteria in Beaufort Shelf waters during winter and spring. J Mar Syst 74:946–956. Bennett S (2004) Solexa Ltd. Pharmacogenomics 5: 433–438. Berger SA, Krompaß D, Stamatakis A (2011) Performance, accuracy and web-server for evolutionary placement of short sequence reads under maximum-likelihood. Syst Biol 60: 291–302. Blanchet FG, Legendre P, Borcard D (2008) Forward selection of explanatory variables. Ecology 89 : 2623–2632. Boenigk J, Pfandl K, Stadler P, Chatzinotas A (2005) High diversity of the ‗Spumella-like‘ flagellates: an investigation based on the SSU rRNA gene sequences of isolates from habitats located in six different geographic regions. Environ Microbiol 7:685- 697. Box GEP, Cox DR (1964) An analysis of transformations. J R Stat Soc B 26: 211–252. Bråte J, Logares R, Berney C, Ree DK, Klaveness D, Jakobsen KS, Shalchian-Tabrizi K (2010a) Freshwater Perkinsea and marine-freshwater colonizations revealed by pyrosequencing and phylogeny of environmental rDNA. ISME J 4: 1144–1153. Bråte J, Klaveness D, Rygh T, Jakobsen KS, Shalchian-Tabrizi K (2010b) Telonemia- specific environmental 18S rDNA PCR reveals unknown diversity and multiple marine-freshwater colonizations. BMC Microbiol 10: 168. Bręk-Laitinen G, Ojala A (2011) Grazing of heterotrophic nanoflagellates on the eukaryotic picoautotroph Choricystis sp. Aquat Microbl Ecol 62: 49–59. Buck KR, Garrison DL (1983) Protists from the ice-edge region of the Weddell Sea. Deep- Sea Res 30: 1261–1277. Carmack E (2007) The alpha/beta ocean distinction: A perspective on freshwater fluxes, convection, nutrients and productivity in high-latitude seas. Deep-Sea Res II 54:2578-2598. Carmack EC, Macdonald RW (2002) Oceanography of the Canadian shelf of the Beaufort Sea: a setting for marine life. Arctic 55: 29–45. Carmack E, McLaughlin F (2011) Towards recognition of physical and geochemical change in Subarctic and Arctic Seas. Progr Oceanogr 90: 90–104. Caron DA, Countway PD, Savai P, Gast RJ, Schnetzer A, Moorthi SD, Dennet MR, Moran DM, Jones AC (2009) Defining DNA-based operational taxonomic units for microbial-eukaryote ecology. Appl Environ Microbiol 75: 5797–5808.

104

Carr M, Leadbeater BSC, Hassan R, Nelson M, Baldauf SL (2008) Molecular phylogeny of choanoflagellates, the sister group to Metazoa. PNAS 105: 16641–16646. Cavalier-Smith T (1998) A revised six-kingdom system of life. Biol Rev 73: 203–266. Cavalier-Smith T, Chao EE-Y (2003) Phylogeny and classification of Phylum Cercozoa (Protozoa). Protist 154: 341–358. Cermeño P, Falkowski PG (2009) Controls on diatom biogeography in the ocean. Science 325: 1539–1541. Chantangsi C, Esson HJ, Leander BS (2008) Morphology and molecular phylogeny of a marine interstitial tetraflagellate with putative endosymbionts: Auranticordis quadriverberis n. gen. et sp. (Cercozoa). BMC Microbiol. DOI: 10.1186/1471- 2180-8-123 Chantangsi C, Hoppenrath M, Leander BS (2010) Evolutionary relationships among marine cercozoans as inferred from combined SSU and LSU rDNA sequences and polyubiquitin insertions. Molecular Phylogenetics and Evolution 57: 518–527. Chen B, Liu H (2010) Trophic linkages between grazers and ultraplankton within the microbial food web in subtropical coastal waters. Mar Ecol Prog Ser 407: 43–53. Cheung MK, Nong W, Kwan HS, Wong CK (2013) Composition of heterotrophic flagellates in coastal waters of different trophic status. Curr Microbiol. DOI 10.1007/s00284-013-0374-x Christaki U, Vázquez-Domínguez E, Courties C, Lebaron P (2005) Grazing impact of different heterotrophic nanoflagellates on eukaryotic (Ostreococcus tauri) and prokaryotic picoautotrophs (Prochlorococcus and Synechococcus). Environ Microbiol 7: 1200–1210. Comeau, A., Li, W.K.W., Tremblay, J.-É., Carmack, E.C. and Lovejoy, C. 2011. Arctic Ocean microbial community structure before and after the 2007 record sea ice minimum. PLoS One, e27492. Comeau A, Benoît P, Thaler M, Gosselin M, Poulin M, Lovejoy C (2013) Protists in Arctic drift and land-fast sea ice. J Phycol 49 : 229–240. doi: 10.1111/jpy.12026 Countway PD, Gast RJ, Savai P, Caron DA (2005) Protistan diversity estimates based on 18S rDNA from seawater incubations in the western North Atlantic. J Eukaryot Microbiol 52: 95–106. Coupel P, Jin HY, Joo M, Horner R, Bouvet HA, Sicre M-A, Gascard J-C, Chen JF, Garçon V, Ruis-Pino D (2012) Phytoplankton distribution in unusually low sea ice cover over the Pacific Arctic. Biogeosciences 9: 4835-4850. Cuvelier ML, Orti A, Kim E, Moehlig H, Richardson DE, Heidelberg JF, Archibald JM, Worden AZ (2008) Widespread distribution of a unique marine protistan lineage. Environ Microbiol 10: 1621–1634. Dawson SC, Pace NR (2002) Novel kingdom-level eukaryotic diversity in anoxic environments. PNAS 99: 8324–8329. Dayel MJ, Alegado RA, Fairclough SR, Levin TC, Nichols SA, McDonald K, King N (2011) Cell differentiation and morphogenesis in the colony-forming choanoflagellate Salpingoeca rosetta. Developmental Biol 357: 73–82. del Campo J, Balagué V, Forn I, Lekunberri I, Massana R (2013) Culturing bias in marine heterotrophic flagellates analyzed through seawater enrichment incubations. Microb Ecol 1–11.

105 Deming J (2007) Life in ice formations at very cold temperatures. In: Gerday, C. & Glansdorff, N. (ed.), Physiology and Biochemistry of Extremophiles. ASM Press, Washington, D.C. p. 133–144. de Vernal A, Henry M, Matthiessen J, Mudie PJ, Rochon A, Boessenkool KP, Eynaud R, Grøsjeld K, Guiot J, Hamel D, Harland R, Head MJ, Kunz-Pirrung M, Levac E, Loucheur V, Peyron O, Pospelova V, Radi T, Turon J-L, Voronina E (2001) Dinoflagellate cyst assemblages as tracers of sea-surface conditions in the northern North Atlantic, Arctic and sub-Arctic seas: the new ‗n = 677‘ data base and its application for quantitative palaeoceanographic reconstruction. J. Quat. Sci 16: 681–698. Díez B, Pedrós-Alió C, Massana R (2001) Study of genetic diversity of eukaryotic picoplankton in different oceanic regions by small-subunit rRNA gene cloning and sequencing. Appl Environ Microbiol 67: 2931–2941. Dorsch MR, Veal DA (2001) Oligonucleotide probes for specific detection of Giardia lamblia cysts by fluorescent in situ hybridization. J Appl Microbiol 90: 836–842. Doweld A (2003) [Diplosoeca – a new generic name in Craspedophyceae]. [Moscow Soc Naturalist Biol Ser] 108: 59–60 (Russian) Drebes G, Kühn SF, Gmelch A, Schnepf E (1996) Cryothecomonas aestivalis sp. nov., a colourless nanoflagellate feeding on the marine centric diatom Guinardia delicatula (Cleve) Hasle. Helgol Mar Res 50: 497–515. Edgar RC (2004) MUSCLE: Multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32: 1792–1797. Elwood HJ, Olsen GJ, Sogin ML (1985) The small-subunit ribosomal-RNA gene- sequences from the hypotrichous ciliates Oxytricha-nova and Stylonychia-pustulata. Mol Biol Evol 2: 399–410. Falk-Petersen S, Pavlov V, Timofeev S, Sargent JR (2007) Climate variability and possible effects on arctic food chains: the role of Calanus. In: Ørbæk JB, Kallenborn R, Tombre I, Hegseth EN, Falk-Petersen S, Hoel AH. Arctic alpine ecosystems and people in a changing environment. Spring Berlin Heidelberg. 147–166. Fenchel T, Finlay BJ (2004) The ubiquity of small species: patterns of local and global diversity. BioScience 54: 777–784. Filker S, Stock A, Breiner H-W, Edgcomb B, Orsi W, Yakimov MM, Stoeck T (2007) Envrionmental selection of protistan plankton communities in hypersaline anoxic deep-sea basins, Easteran Mediterranean Sea. Microbiol Open 2: 54–63. Forest A, Tremblay JÉ, Gratton Y, Martin J, Gagnon J, Darnis G, Sampei M, Fortier L, Ardyna M, Gosselin M, Hattori H, Nguyen, Maranger R, Vaqué D, Marrasé C, Pedrós-Alió C, Sallon A, Michel C, Kellogg C, Deming J, Shadwick E, Thomas H, Link H, Archambault P, Piepenburg D (2011) Biogenic carbon flows through the planktonic food web of the Amundsen Gulf (Arctic Ocean): A synthesis of field measurements and inverse modelling analyses. Progr Oceanogr 91: 410–436. Fortier M, Fortier L, Michel C, Legendre L (2002) Climatic and biological forcing of the vertical flux of biogenic particles under seasonal Arctic sea ice. Mar Ecol Progr Ser 225:1-16. Fortier L, Sirois P, Michaud J, Barber D (2006) Survival of Arctic cod larvae (Boreogadus saida) in relation to sea ice and temperature in the Northeast Water Polynya (Greenland Sea). Can J Fish Aquat Sci 63: 1608–1616.

106

Foulon E, Not F, Jalabert F, Cariou T, Massana R, Simon N (2008) Ecological niche partitioning in the picoplanktonic green alga Micromonas pusilla: evidence from environmental surveys using phylogenetic probes. Environ Microbiol 10:2433- 2443. Frias-Lopez J, Thompson A, Waldbauer J, Chisholm SH (2009) Use of stable isotope- labelled cells to identify active grazers of picocyanobacteria in ocean surface waters. Envrion Microbiol 11: 512–525. Garrison DL, Gibson A, Coale SL, Gowing MM, Okolodkov YB, Fritsen CH, Jeffries MO (2005) Sea-ice microbial communities in the Ross Sea: autumn and summer biota. Mar Ecol Prog Ser 300: 39–52. Gilg IC, Amaral-Zettler LA, Countway PD, Moorthi S, Schnetzer A, Caron DA (2010) Phylogenetic affiliations of mesopelagic Acantharia and acantharian-like environmental 18S rRNA genes off the southern California coast. Protist 161: 197– 211. Gouy M, Guindon S, Gascuel O (2010) SeaView version4: a multiplatform graphical user interface for sequence alignment and phylogenetic tree building. Mol Biol Evol 27: 221–224. Granéli W, Granéli E (1991) Automatic potentiometric determination of dissolved oxygen. Mar Biol 108:341-348. Grasshoff K, Kremling K, Ehrhardt M (1976) Methods of seawater analysis. Wiley VCH, Weinheim, Germany. Grebmeier JM, Cooper LW, Feder HM, Sirenko BI (2006) Ecosystem dynamics of the Pacific-influenced Northern Bering and Chukchi Seas in the Amerasian Arctic. Progr Oceanogr 71: 331–361. Guillou L, Viprey M, Chambouvet A, Welsh RM, Kirkham AR, Massana R, Scanlan D J, Worden AZ (2008) Widespread occurrence and genetic diversity of marine parasitoids belonging to Syndiniales (Alveolata). Environ Microbiol 10: 3349–3365. Guillou L, Bachar D, Audic S, Bass D, Berney C, Bittner L et al. (2012) The Protist Ribosomal Reference database (PR2): a catalog of unicellular eukaryote small subunit rRNA sequences with curated taxonomy. Nucleic Acids Res 41:D597-D604. Guindon S, Dufayard JF, Lefort V, Anisimova M, Hordijk W, Gascuel O (2002) New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst Biol 59:307-321. Hamilton AK, Lovejoy C, Galand PE, Ingram RG (2008) Water masses and biogeography of picoeukaryote assemblages in a cold hydrographically complex system. Limnol Oceanogr 53: 922–935. Hanson CA, Fuhrman JA, Horner-Devine MC, Martiny JBH (2012) Beyond biogeographic patterns: processes shaping the microbial landscape. Nature Reviews Microbiol 10: 497–506. Harding T, Jungblut AD, Lovejoy C, Vincent WF (2011) Microbes in High Arctic snow and implications for the cold biosphere. Appl Environ Microbiol 77: 3234–3243. Hargraves PE (2002) The ebridian flagellates Ebria and Hermesinum. Plankton Biol Ecol 49: 9–16. Harrison WG, Li WKW (2007) Phytoplankton growth and regulation in the Labrador Sea: light and nutrient limitation. J Northwest Atl Fish Sci 39: 71–82.

107 Haska CL, Yarish C, Kraemer G, Blaschik N, Whitlatch R, Zhang H, Lin S (2012) Bait worm packaging as a potential vector of invasive species. Biol Invastions 14: 481– 493. Hendriks L, Goris A, Neefs J, Van de Peer Y, Hennebert G, De Wachter R (1989) The nucleotide sequence of the small ribosomal subunit RNA of the yeast Candida albicans and the evolutionary position of the fungi among the eukaryotes. Syst Appl Microbiol 12: 223–229. Hillebrand H, Dürselen C-D, Kirschtel D, Pollingher U, Zohary T (1999) Biovolume calculation for pelagic and benthic microalgae. J Phycol 35: 403–424. Hoppenrath M, Leander BS (2006) Dinoflagellate, euglenid, or cercomonad? The ultrastructure and molecular phylogenetic position of Protaspis grandis n. sp. J Eukaryot Microbiol 53: 327–342. Horner RA (1976) Sea ice organisms. Oceanogr Mar Biol Annu Rev 14: 167–182. Howe AT, Bass D, Vickerman K, Chao EE, Cavalier-Smith T (2009) Phylogeny, taxonomy, and astounding genetic diversity of Glissomonadida ord. nov., the dominant gliding zooflagellates in soil (Protozoa: Cercozoa). Protist 160: 159–189. Howe AT, Bass D, Scoble JM, Lewis R, Vickerman K, Arndt H, Cavalier-Smith T (2011) Novel cultured protists identify deep-branching environmental DNA clades of Cercozoa: new genera Tremula, Micrometopion, Minimassisteria, Nudifila, Peregrinia. Protist 162: 332–372. Howell SEL, Duguay CR, Markus T (2009) Sea ice conditions and melt season duration variability within the Canadian Arctic Archipelago: 1979–2008. Geophys Res Letters 36: L10502. Huse SM, Huber JA, Morrison HG, Sogin ML, Welch DM (2007) Accuracy and quality of massively parallel DNA pyrosequencing. Genome Biol 8: R143. Huson LW (2007) Performance of some correlation coefficients when applied to zero- clustered data. J Mod Appl Stat Meth 6: 530–536. Huson DH, Scornavacca C (2012) Dendroscope 3– An interactive viewer for rooted phylogenetic trees and networks. Syst Biol. Ikävalko J, Gradinger R (1997) Flagellates and heliozoans in the Greenland Sea ice studied alive using light microscopy. Polar Biol 17: 473–481. Jenkins A (1999) The impact of melting ice on ocean waters. J Phys Oceanogr 29: 2370– 2381. Jeon S, Bunge J, Leslin C, Stoeck T, Hong S, Epstein SS (2008) Environmental rRNA inventories miss over half of protistan diversity. BMC Microbiol 8: 222. Jeong HJ, Song JE, Kang NS, Kim S, Yoo YD, Park JY (2007) Feeding by heterotrophic dinoflagellates on the common marine heterotrophic nanflagellate Cafeteria sp. Mar Ecol Prog Ser 333: 151–160. Jürgens K, Massana, R (2008) Protistan grazing on marine bacterioplankton. In: Kirchman DL (ed) Microbial Ecology of the Oceans, 2nd edn. Wiley, New York, pp 383-441. Juul-Pedersen T, Michel C, Gosselin M (2010) Sinking export of particulate organic material from the euphotic zone in the eastern Beaufort Sea. Mar Ecol Prog Ser 410: 55–70. Katoh K, Misawa K, Kuma K, Miyata T (2002) MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res 14:3059- 3066.

108

Klaveness D, Shalchian-Tabrizi K, Thomsen HA, Eikrem W, Jakobsen KS (2005) Telonema antarcticum sp. nov., a common marine phagotrophic flagellates. Int J Syst Evol Microbiol 55: 2595–2604. Kühn SF, Lange M, Medlin LK (2000) Phylogenetic position of Cryothecomonas inferred from nuclear-encoded small subunit ribosomal RNA. Protist 151: 337–345. Kuparinen J, Bjørnsen PK (1993) Bottom-up and top-down controls of microbial food web in the Southern Ocean: experiments with manipulated microcosms. In: Hempel G, ed. Weddell Sea Ecology. Springer-Verlag. 189–195. Lagercrantz E (2008) eBiox. http://www.ebioinformatics.org/ebiox (accessed 26 May 2011) Laidre KL, Stirling I, Lowry LF, Wiig Ø, Heide-Jørgensen MP, Ferguson SH (2008) Quantifying the sensitivity of Arctic marine mammals to climate-induced habitat change. Ecological Applications 18: S97–S125. Lalande C, Forest A, Barber DG, Gratton Y, Fortier L (2009) Variability in the annual cycle of vertical particulate organic carbon export on Arctic shelves: Contrasting the Laptev Sea, Northern Baffin Bay and the Beaufort Sea. Continental Shelf Res 29:2157-2165. doi:10.1016/j.csr.2009.08.009 Langer G, Nehrke G, Probert I, Ly J, Ziveri P (2009) Strain-specific responses of Emiliania huxleyi to changing seawater carbonate chemistry. Biogeosciences 6:2637-2646. doi: 10.5194/bg-6-2637-2009 Langenheder S, Lindström ES, Tranvik LJ (2006) Structure and function of bacterial communities emerging from different sources under identical conditions. Appl Environ Microbiol 72: 212–220. Lazier J, Hendry R, Clarke A, Yashayaev I, Rhines P (2002) Convection and restratification in the Labrador Sea, 1990–2000. Deep-Sea Res I 49:1819-1835. Leadbeater BSC (2008) Choanoflagellate evolution: the morphological perspective. Protistology 5: 256–267. Lee WJ, Patterson DJ (2000) Heterotrophic flagellates (Protista) from marine sediments of Botany Bay, Australia. J Nat Hist 34: 483–562. Legendre P, Legendre L (1998) Numerical Ecology. Elsevier Science B.V., Amsterdam, The Netherlands. p. 546–551. Lewis EL, Ponton D, Legendre L, Leblanc B (1996) Springtime sensible heat, nutrients and phytoplankton in the Northwater Polynya, Canadia Arctic. Continental Shelf Res 16: 1775–1792. Li WKW, Dickie PM (2001) Monitoring phytoplankton, bacterioplankton and virioplankton in a coastal inlet (Bedford Basin) by flow cytometry. Cytometry 44:236-246. Li WKW, McLaughlin FA, Lovejoy C, Carmarck E (2009) Smallest algae thrive as the Arctic Ocean freshens. Science 326: 539. Lim EL (1996) Molecular identification of nanoplanktonic protists based on small subunit ribosomal RNA gene sequences for ecological studies. J Euk Microbiol 43: 101– 106. Lin Y-C, Campbell T, Chung-C, Gong G-C, Chiang K-P, Worden AZ (2012) Distribution patterns and phylogeny of Marine Stramenopiles in the North Pacific Ocean. Appl Environ Microbiol 78:3387-3399.

109 Logares R, Audic S, Santini S, Pernice MC, de Vargas C, Massana R (2012) Diversity patterns and activity of uncultured marine heterotrophic flagellates unveiled with pyrosequencing. ISME J 6: 1–11. Lovejoy C, Potvin M (2011) Microbial eukaryotic distribution in a dynamic Beaufort Sea and the Arctic Ocean. J Plankton Res 33: 431–444. doi: 10.1093/plankt/fbq124 Lovejoy C, Carmack EC, Legendre L, Price NM (2002) Water column interleaving: a new physical mechanism determining protist communities and bacterial states. Limnol Oceanogr 47: 1819–1831. Lovejoy C, Massana R, Pedrós-Alió (2006) Diversity and distribution of marine microbial eukaryotes in the Arctic Ocean and adjacent Seas. Appl Envrion Microbiol 72: 3085–3095. Lovejoy C, Vincent WF, Bonilla S, Roy S, Martineau M-J, Terrado R, Potvin M, Massana R, Pedrós-Alió C (2007) Distribution, phylogeny and growth of cold-adapted picoprasinophytes in Arctic seas. J Phycol 43: 78–89. Ludwig W, Strunk O, Westram R, Richter L, Meier H, Yahukumar, Buchner A, Lai T, Steppi S, Jobb G, Förster W, Brettske I, Gerber S, Ginhart AW, Gross O, Grumann S, Hermann S, Jost R, König A, Liss T, Lüßmann R, May M, Nonhoff B, Reichel B, Strehlow R, Stamatakis A, Stuckmann N, Vilbig A, Lenke M, Ludwig T, Bode A, Schleifer K-H (2004) ARB: a software environment for sequence data. Nucleic Acids Res 32: 1363–1371. Lund JWG, Kipling C, Le Cren ED (1958) The inverted microscope method of estimating algal numbers and the statistical basis of estimations by counting. Hydrobiologia 11: 143–170. Luo W, Li H, Cai M, He J (2009) Diversity of microbial eukaryotes in Kongsfjorden, Svalbard. Hydrobiologia 636: 233–248. Luo W, Bock C, Li HR, Padisák J, Krienitz L (2011) Molecular and microscopic diversity of planktonic eukaryotes in the oligotrophic Lake Stechlin (Germany). Hydrobiologia 661: 133–143. Majaneva M, Rintala J-M, Piisilä M, Fewer DP, Blomster J (2012) Comparison of wintertime eukaryotic community from sea ice and open water in the Baltic Sea, based on sequencing of the 18S rRNA gene. Polar Biol 35:875-889. Marchetti GM (2006) Independencies induced from a graphical Markov model after marginalization and conditioning: the R package ggm. J Stat Softw 15. Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, Bemben LA, Berka J, Braverman MS, Chen Y-J, Chen Z, Dewell SB, Du L, Fierro JM, Gomer XV, Godwin BC, He W, Helgesen S, Ho CH, Irzyk GP, Jando SC, Alenquer MLI, Jarvie TP, Jirage KB, Kim J-B, Knight JR, Lanza JR, Leamon JH, Lefkowitz SM, Lei M, Li J, Lohman KL, Lu H, Makhijani VB, McDade KE, McKenna MP Myers EW, Nickerson E, Nobile JR, Plant R, Puc BP, Ronan MT, Roth GT, Sarkis GJ, Simons JF, Simpson JW, Srinivasan M, Tartaro KR, Tomasz A, Vogt KA, Volkmer GA, Wang SH, Wang Y, Weiner MP, Yu P, Begley RF, Rothberg JM (2005) Genome sequencing in microfabricated high-density picolitre reactors 437: 376–380. Martin J, Tremblay J-É, Gagnon J, Tremblay F, Lapoussière A, Jose C, Poulin M, Gosselin M, Gratton Y, Michel C (2010) Prevalence, structure and properties of subsurface chlorophyll maxima in Canadian Arctic waters. Mar Ecol Progr Ser 412:69-84.

110

Massana R, Gullou L, Díez B, Pedrós-Alió C (2002) Unveiling the organisms behind novel eukaryotic ribsosomal DNA sequences from the ocean. Appl Environ Microbiol 68: 4554–4558. Massana R, Castresana J, Balagué V, Guillou L, Romari K, Groisillier A, Valentin K, Pedrós-Alió C (2004) Phylogenetic and ecological analysis of novel marine stramenopiles. Appl Environ Microbiol 70:3528-3534. Massana R, Terrado R, Forn I, Lovejoy C, Pedrós-Alió C (2006) Distribution and abundance of uncultured heterotrophic flagellates in the world oceans. Environ Microbiol 8:1515-1522. Massana R, Unrein F, Rodríguez-Martínez R, Forn I, Lefort T, Pinhassi J, Not F (2009) Grazing rates and functional diversity of uncultured heterotrophic flagellates. ISME J 3: 588–596. McLaughlin F, Carmack EC (2010) Deepening of the nutricline and chlorophyll maximum in the Canada Basin interior, 2003–2009. Geophys Res Letters 37: L24602. McLaughlin F, Carmack E, Macdonald R, Weaver AJ, Smith J (2002) The Canada Basin, 1989–1995: Upstream events and far-field effects of the Barents Sea. J Geophys Res 107. DOI: 10.1029/2001JC000904. Medlin LK, Elwood HJ, Stickel S, Sogin ML (1988) The characterization of enzymatically amplified eukaryotic 16S-like rRNA-coding regions. Gene 71: 491–499. Melling H, Moore RM (1995) Modification of halocline source waters during freezing on the Beaufort Sea shelf: evidence from oxygen isotopes and dissolved nutrients. Continental Shelf Res 15: 89–113. Melling H, Gratton Y, Ingram G (2001) Ocean circulation within the North Water polynya of Baffin Bay. Atmosphere-Ocean 39:301-325. Menden-Deuer S, Lessard EJ (2000) Carbon to volume relationships for dinoflagellates, diatoms and other protist plankton. Limnol Oceanogr 45:569-579. Monier A, Terrado R, Thaler M, Comeau A, Medrinal E, Lovejoy C (2013) Upper Arctic Ocean water masses harbour distinct communities of heterotrophic flagellates. Biogeosciences 10: 3397–3430. Montagnes DJS, Chambouvet A, Guillou L, Fenton A (2008) Responsibility of microzooplankton and parasite pressure for the demise of toxic dinoflagellate blooms. Aquat Microb Ecol 53: 211–225. Montresor M, Lovejoy C, Orsini L, Procaccini G, Roy S (2003) Bipolar distribution of the cyst-forming dinoflagellate Polarella glacialis. Polar Biol 26:186–194. Mundy CJ, Gosselin M, Ehn J, Gratton Y, Rossnagel A, Barber DG, Martin J, Tremblay J- É, Palmer M, Arrigo KR, Darnis G, Fortier L (2009) Contribution of under-ice primary production to an ice-edge upwelling phytoplankton bloom in the Canadian Beaufort Sea. Geophys Res Letters 36. DOI: 10.1029/2009GL038837 Mylnikova ZM, Mylnikov AP (2012) Structure of filose amoeba Rhogostoma minus Belar 1921 (Cryomonadida, Cercozoa) Cell. Inland Water Biol 5: 236–240. Nelles L, Fang B-L, Volckaert G, Vandenberghe A, De Wachter R (1984) Nucleotide sequence of a crustacean 18S ribosomal RNA gene and secondary structure of eukaryotic small subunit ribosomal RNAs. Nucleic Acids Res 12: 8749–8768. Nitsche F, Carr M, Arndt H, Leadbeater BSC (2011) Higher level taxonomy and molecular phylogenetic of the Choanoflagellatea. J Eukaryot Microbiol 58: 452–462

111 Not F, Valentin K, Romari K, Lovejoy C, Massana R, Töbe K, Vaulot D, Medlin LK (2007) Picobiliphytes: a marine picoplanktonic algal group with unknown affinities to other eukaryotes. Science 315: 253–255. Not F, del Campo J, Balagué V, de Vargas C, Massana R (2009) New insights into the diversity of marine picoeukaryotes. PLoS ONE 4: e7143 Nusch EA (1980) Comparison of different methods for chlorophyll and phaeopigment determination. Arch Hydrobiol Beih Ergebn Limnol 14:14–36. Orsi W, Edgcomb V, Jeon S, Leslin C, Bunge J, Taylor GT, Varela R, Epstein S (2011) Protistan microbial observatory in the Cariaco Basin, Caribbean. II. Habitat specialization. ISME J 5: 1357–1373. Orsi W, Song YC, Hallam S, Edgcomb V (2012) Effect of oxygen minimum zone formation on communities of marine protists. ISME J 6:1586-1601. Palacios L, Marín I (2008) Enzymatic permeabilization of the thecate dinoflagellate Alexandrium minutum (Dinophyceae) yields detection of intracellularly associated bacteria via catalyzed reporter deposition-fluorescence in situ hybridization. Appl Environ Microbiol 74: 2244–2247. Pernthaler J, Glöckner F-O, Schönhuber W, Amann R (2001) Fluorescence in situ hybridization (FISH) with rRNA-targeted oligonucleotide probes. In: Paul, J. H. (ed.), Marine microbiology, Volume 30. Academic Press, London. p. 207–226. Pernthaler A, Pernthaler J, Amann R (2002) Fluorescence in situ hybridization and catalyzed reporter deposition for the identification of marine bacteria. Appl Environ Microbiol 68: 3094–3101. Perrette M, Yool A, Quartly GD, Popova EE (2011) Near-ubiquity of ice-edge blooms in the Arctic. Biogeosciences 8:515-Pe524. Perrière G, Gouy M (1996) WWW-Query: An on-line retrieval system for biological sequence banks. Biochimie 78: 364–369. Piwosz K, Pernthaler J (2010) Seasonal population dynamics and trophic role of planktonic nanoflagellates in coastal surface waters of the Southern Baltic Sea. Environ Microbiol 12: 364–377. Piwosz K, Wiktor JM, Niemi A, Tatarek A, Michel C (2013) Mesoscale distribution and functional diversity of picoeukaryotes in the first-year sea ice of the Canadian Arctic. ISME J 7: 1461-1471. Porter KG, Feig YS (1980) The use of DAPI for identifying and counting aquatic microflora. Limnol Oceanogr 25:943-948. Potvin M, Lovejoy, C (2009) PCR-based diversity estimates of artificial and environmental 18S rRNA gene libraries. J Eukaryot Microbiol 56: 174–181. Prinsenberg SJ, Hamilton J (2004) Monitoring the volume, freshwater and heat fluxes passing through Lancaster Sound in the Canadian Arctic Archipelago. Atmosphere- Ocean 43:1-22. Proshutinsky A, Krishfield R, Timmermans M-L, Toole J, Carmack E, McLaughlin F, Williams WJ, Zimmermann S, Itoh M, Shimada K (2009) Beaufort Gyre freshwater reservoir: state and variability from observations. J Geophys Res 114: C00A10 von Quillfeldt CH (2000) Common diatom species in Arctic spring blooms: their distribution and abundance. Bot Mar 43: 499–516. R Development Core Team. (2008) R: A language for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.r-project.org. Accessed 14 December 2009

112

Raven JA (1998) The twelfth Tansley Lecture. Small is beautiful: the picophytoplankton. Functional Ecology 12: 503–513. Rodríguez F, Derelle E, Guillou L, Le Gall F, Vaulot D, Moreau H (2005) Ecotype diversity in the marine picoeukaryote Ostreococcus (Chlorophyta, Prasinophyceae). Environ Microbiol 7:853-859. Rodríguez-Martínez R, Rocap G, Salazar G, Massana R (2013) Biogeography of the uncultured marine picoeukaryote MAST-4: temperature-driven distribution patterns. ISME J 2013: 1–13. Rokkan Iversen KR, Seuthe L (2011) Seasonal microbial processes in a high-latitude fjord (Kongsfjorden, Svalbard): I. Heterotrophic bacteria, picoplankton and nanoflagellates. Polar Biol 34: 731–749. Ronquist F, Huelsenbeck JP (2003) MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics 19: 1572–1574. Różańska M, Poulin M, Gosselin M (2008) Protist entrapment in newly formed sea ice in the Coastal Arctic Ocean J Mar Syst 74: 887–901. Różańska M, Gosselin M, Poulin M, Wiktor JM, Michel C (2009) Influence of environmental factors on the development of bottom ice protist communities during the winter-spring transition. Mar Ecol Prog Ser 386: 43–59. Saburova M, Al-Yamani F, Polikarpov I (2009) Biodiversity of free-living flagellates in Kuwait‘s intertidal sediments. BioRisk 3: 97–110. Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, Lesniewski RA, Oakley BB, Parks DH, Robinson CJ, Sahl JW, Stres B, Thallinger GG, Van Horn DJ, Weber CF (2009) Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 75:7537-7541 Schnepf E, Kühn SF (2000) Food uptake and fine structure of Cryothecomonas longipes sp. nov., a marine nanoflagellate incertae sedis feeding phagotrophically on large diatoms. Helgol Mar Res 54: 18–32. Seenivasan R, Sausen N, Medlin LK, Melkonian M (2013) Picomonas judraskeda gen. et sp. nov: The first identified member of the Picozoa Phylum nov., a widespread group of picoeukaryotes, formerly known as ‗picobiliphytes‘. PLoS ONE 8: e59565. Shalchian-Tabrizi K, Eikrem W, Klaveness D, Vaulot D, Minge MA, Le Gall F, Romari K, Throndsen J, Botnen A, Massana R, Thomsen HA, Jakovsen KS (2006) Telonemia, a new protist phylum with affinity to chromist lineages. Proc R Soc B 273: 1833– 1842. Sherr EB, Sherr BF (2002) Significance of predation by protists in aquatic microbial food webs. Antonie van Leeuwenhoek 81:293-308. Sherr EB, Sherr BF (2009) Capacity of herbivorous protists to control initiation and development of mass phytoplankton blooms. Aquat Microb Ecol 57: 253–262. Sherr BF, Sherr EB, Fallon RD (1987) Use of monodispersed, fluorescently labeled bacteria to estimate in situ protozoan bacterivory. Appl Environ Microbiol 53: 958– 965. Sherr EB, Sherr BF, Fessenden L (1997) Heterotrophic protists in the Central Arctic Ocean. Deep-Sea Res II 44: 1665–1682.

113 Sieburth JM, Smetacek V, Lenz J (1978) Pelagic ecosystem structure: heterotrophic compartments of the plankton and their relationships to plankton size fractions. Limnol Oceanogr 23: 1256–63. Sieracki ME, Hass LW, Caron DA, Lessard EJ (1987) Effect of fixation on particle retention by microflagellates: underestimation of grazing rates. Mar Ecol Prog Ser 38: 251–258. Šimek K, Jezbera J, Horňák K, Vrba J, Sed‘a J (2004) Role of diatom-attached choanoflagellates of the genus Salpingoeca as pelagic bacterivores. Aquat Microb Ecol 36: 257–269. Sime-Ngando T, Gosselin M, Juniper SK, Levasseur M (1997a) Changes in sea-ice phagotrophic microprotists (20–200 µm) during the spring algal bloom, Canadian Arctic Archipelago. J Mar Syst 11: 163–172. Sime-Ngando T, Gosselin M, Juniper SK, Levasseur M (1997b) Changes in sea-ice phagotrophic microprotists (20–200 µm) during the spring algal bloom, Canadian Arctic Archipelago. J Mar Sys 11: 163–172. Šlapeta J, López-García P, Moreira D (2006) Present status of the molecular ecology of kathablepharids. Protist 157: 7–11. Sogin ML, Morrison HG, Huber JA, Welch DM, Huse SM, Neal PR, Arrieta JM, Herndl GJ (2006) Microbial diversity in the deep sea and the underexplored ―rare biosphere‖. PNAS 103: 12115–12120. Sørensen N, Daugbjerg N, Richardson K (2013) Choice of pore size can introduce artefacts when filtering picoeukaryotes for molecular biodiversity studies. Microb Ecol 65: 964–968. Stamatakis A (2006) RAxML-VI-HPC: Maximum Likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics 22: 2688–2690. Stirling I (1980) The biological importance of polynyas in the Canadian Arctic. Arctic 33: 303–315. Strickland MS, Lauber C, Fierer N, Bradford MA (2009) Testing the functional significance of microbial community composition. Ecology 90: 441–451. Stringer WJ, Groves JE (1991) Location and areal extent of polynyas in the Bering and Chukchi Seas. Arctic 44: 164–171. Stroeve JC, Serreze MC, Holland MM, Kay JE, Malanik J, Barrett AP (2012) The Arctic‘s rapidly shrinking sea ice cover: a research synthesis. Climatic Change 110: 1005– 1027. Sullivan CW, McClain CR, Comiso JC, Smith WO (1988) Phytoplankton standing crops within an Antarctic ice edge assessed by satellite remote sensing. J Geophys Res 93: 12487–12498. Takishita K, Tsuchiya M, Kawato M, Maruyama T (2007a) Genetic diversity of microbial eukaryotes in anoxic sediment of the saline meromictic Lake Namako-ike (Japan): on the detection of anaerobic or anoxic-tolerant lineages of eukaryotes. Protist 158: 51–64. Takishita K, Yubuki N, Kakizoe N, Inagaki Y, Maruyama T (2007b) Diversity of microbial eukaryotes in sediment at a deep-sea methane cold seep: surveys of ribosomal DNA libraries from raw sediment samples and two enrichment cultures. Extremophiles 11: 563–576. Tang CCL, Ross CK, Yao T, Petrie B, DeTracey BM, Dunlap E (2004) The circulation, water masses and sea-ice of Baffin Bay. Progr Oceanogr a63: 183–228.

114

ter Braak CJF, Šmilauer P (1998) CANOCO Reference Manual and User‘s Guide to Canoco for Windows: Software for Canonical Community Ordination (version 4). Microcomputer Power, Ithaca. Terrado R, Vincent WF, Lovejoy C (2009) Mesopelagic protists: diversity and succession in a coastal Arctic ecosystem. Aquat Microb Ecol 56: 25–40. Terrado R, Medrinal E, DaSilva C, Thaler M, Vincent WF, Lovejoy C (2011) Protist community composition during spring in an Arctic flaw lead polynya. Polar Biol 34: 1901–1914. Terrado R, Scarcella K, Thaler M, Vincent WF, Lovejoy C (2012) Small phytoplankton in Arctic seas: vulnerability to climate change. Biodiversity, 14: 1–17. Thaler M, Lovejoy C (2012) Distribution and diversity of a protist predator Cryothecomonas (Cercozoa) in Arctic Marine Waters. J Eukaryot Microbiol 59: 291–299. Thaler M, Lovejoy C (2013) Environmental selection of marine stramenopile clades in the Arctic Ocean and coastal waters. Polar Biol. doi : 10.1007/s00300-013-1435-0 Thomas DN, Dieckmann SG (2002) Antarctic sea ice—a habitat for extremophiles. Science 295: 641–644. Thompson JD, Gibson TJ, Plewniak F, Jeanmougin F, Higgins DG (1997) The ClustalX windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res 25: 4876–4882. Thompson AW, Foster RA, Krupke A, Carter BJ, Musat N, Vaulot D, Kuypers MMM, Zehr JP (2012) Unicellular cyanobacterium symbiotic with a single-celled eukaryotic alga. Science 337: 1546–1550. Thomsen HA, Buck KR, Bolt PA, Garrison DL (1991) Fine structure and biology of Cryothecomonas gen. nov. (Protista incertae sedis) from the ice biota. Can J Zool 69: 1048–1070. Thomsen HA, Østergaard JB, Hansen LE (1995) Loricate choanoflagellates from West Greenland (August 1988) including the description of Spinoeca buckii gen. et sp. nov. Europ J Protistol 31: 38–44. Thomsen HA, Garrison DL, Kosman C (1997) Choanoflagellates (Acanthoecidae, Choanoflagellida) from the Weddell Sea, Antarctica, taxonomy and community structure with particular emphasis on the ice biota; with preliminary remarks on choanoflagellates from Arctic sea ice (Northeast Water Polynya, Greenland). Arch Protistenkd 148: 77–114. Throndsen J (1970) Salpingoeca spinifera sp. nov., a new planktonic species of the craspedophyceae recorded in the arctic. Br Phycol J 5: 87–89. Tian F, Yu Y, Chen B, Li HR, Yao YF, Guo XK (2009) Bacterial, archaeal and eukaryotic diversity in Arctic sediment as revealed by 16S and 18S rRNA gene clone libraries analysis. Polar Biol 32: 93–103. Tillmann U, Hess K-J, Tillmann A (1999) Large-scale parasitic infection of diatoms in the Northfrisian Wadden Sea. J Sea Res 42: 255–261. Tong SM (1997a) Heterotrophic flagellates from the water column in Shark Bay, Western Australia. Marine Biol 128: 517–536. Tong S, Vørs N, Patterson DJ (1997b) Heterotrophic flagellates, centrohelid heliozoa and filose amoebae from marine and freshwater sites in the Antarctic. Polar Biol 18: 91– 106.

115 Tremblay J-É, Simpson K, Martin J, Miler L, Gratton Y, Barber D, Price NM (2008) Vertical stability and the annual dynamics of nutrients and chlorophyll fluorescence in the coastal, southeast Beaufort Sea. J Geophys Res 113: C07S90. Tremblay J-É, Michel C, Hobson KA, Gosselin M, Price NM (2006) Bloom dynamics in early opening waters of the Arctic Ocean. Limnol Oceanogr 51: 900–912. Umani, S. F., Malisana, E., Focaracci, F., Magagnini, M., Corinaldesi, C. & Danovaro, R. 2010. Disentangling the effect of viruses and nanoflagellates on prokaryotes in bathypelagic waters of the Mediterranean Sea. Mar Ecol Progr Ser 418: 73–85. Unrein F, Gasol JM, Massana R (2010) Dinobryon faculiferum (Chrysophyta) in coastal Mediterranean seawater: presence and grazing impact on bacteria. J Plankton Res 32: 559–564. Vaqué D, Guadayol Ò, Peters F, Felipe J, Angel-Ripoll L, Terrado R, Lovejoy C, Pedrós- Alió (2008) Seasonal changes in planktonic bacterivory rates under the ice-covered coastal Arctic Ocean. Limnol Oceanogr 53: 2427–2438. Vaulot D, Eikrem W, Viprey M, Moreau H (2008) The diversity of small eukaryotic phytoplankton (≤ 3 µm) in marine ecosystems. FEMS 32: 795–820. Verity PG, Wassmann P, Frischer ME, Howard-Jones MH, Allen AE (2002) Grazing of phytoplankton by microzooplankton in the Barents Sea during early summer. J Mar Syst 38: 109–123. Vørs N (1993a) Marine heterotrophic amoebae, flagellates and heliozoa from Belize (Central America) and Tenerife (Canary Islands), with descriptions of new species, Luffisphaera bulbochaete n. sp., L. longihasitis n. sp., L. turriformis n. sp. and Paulinella intermedia n. sp. J Euk Microbiol 40: 272–287. Vørs N (1993b) Heterotrophic amoebae, flagellates and heliozoa from Arctic marine waters (North West Territories, Canada and West Greenland). Polar Biol 13: 113–126. Waleron M, Waleron K, Vincent WF, Wilmotte A (2007) Allochthonous inputs of riverine picocyanobacteria to coastal waters in the Arctic Ocean. FEMS Microbiol Ecol 59: 356–365. Weisse T (2002) The significance of inter- and intraspecific variation in bacterivorous and herbivorous protists. Antonie van Leeuwenhoek 81: 327–341. Weisse T, Scheffel-Möser U (1991) Uncoupling the microbial loop: growth and grazing loss rates of bacteria and heterotrophic nanoflagellates in the North Atlantic. Mar Ecol Prog Ser 71: 195–205. Welch HE, Bergmann MA, Siferd TD, Martin KA, Curtis MF, Crawford RE, Conover RJ, Hop H (1992) Energy flow through the marine ecosystem of the Lancaster Sound region, Arctic Canada. Arctic 45: 343–357. Williams WJ, Carmack EC, Shimada K, Melling H, Aagaard K, Macdonald RW, Ingram RG (2006) Joint effects of wind and ice motion in forcing upwelling in Mackenzie Trough, Beaufort Sea. Continental Shelf Res 26: 2352–2366. Woodgate RA, Aagaard K, Weingartner (2005) A year in the physical oceanography of the Chukchi Sea: moored measurements from autumn 1990–1991. Deep-Sea Res II 52: 3116–3149. Woodruff JD, Donnelly JP, Okusu A (2009) Exploring typhoon variability over the mid-to- late Holocene: evidence of extreme coastal flooding from Kamikoshiki, Japan. Quat Sci Rev 28: 1–12.

116

Wylezich C, Karpov SA, Mylnikov A, Anderson R, Jürgens K (2012) Ecologically relevant choanoflagellates collected from hypoxic water masses of the Baltic Sea have untypical mitochondrial cristae. BMC Microbiol 12: 271. Yabuki A, Ishida KI (2011) Mataza hastifera n. g., n. sp.: a possible new lineage in the Thecofilosea (Cercozoa). J Eukaryot Microbiol 58: 94–102. Yoon HS, Price DC, Stepanauskas R, Rajah VD, Sieracki ME, Wilson WH, Yang EC, Duffy S, Bhattacharya D (2011) Single-cell genomics reveals organismal interactions in uncultivated marine protists. Science 332: 714–717. Zhu F, Massana R, Not F, Marie D, Vaulot D (2005) Mapping of picoeucaryotes in marine ecosystems with quantitative PCR of the 18S rRNA gene. FEMS Microbiol Ecol 52: 79–92.

117