Cyanophage Diversity Inferred from g20 Gene Analyses in the Largest Natural French Lake, Lake Bourget

Ursula Dorigo, Stéphan Jacquet and Jean-François Humbert* UMR CARRTEL, Station INRA d’Hydrobiologie Lacustre, Equipe de Microbiologie Aquatique, BP 511, 74203 Thonon Cedex, France

RT : Freshwater cyanophage diversity Section: Microbial Ecology

* Corresponding author. Mailing address: UMR CARRTEL, Station INRA d’Hydrobiologie Lacustre, Equipe de Microbiologie Aquatique, BP 511, 74203 Thonon Cedex, France. Phone: 33-4-50-26-78-09. Fax: 33.4.50.26.78.06. E-mail: [email protected]

The genetic diversity of the natural freshwater community of cyanophages and its variations over time have been investigated for the first time in the surface waters of the largest natural French lake (Lake Bourget, Western Alps). This was done by random screening of clone libraries for the g20 gene (which codes for the portal vertex protein) and by denaturing gradient gel electrophoresis (DGGE). The abundance of pelagic viruses, heterotrophic bacteria, picocyanobacteria and the bloom-forming cyanobacterium Planktothrix rubescens were also determined from September 2002 to January 2003 using flow cytometry or cell counting. The viral abundance fell from 2.6 x 108 to 5.8 x 107 part/mL, and was positively correlated with the abundance of both the heterotrophic bacterial community and the picocyanobacteria. Nucleotide sequence analysis revealed 35 distinct cyanomyovirus g20 genotypes among the 47 sequences analyzed. Phylogenetic analyses showed that these sequences fell into 7 genetically distinct OTUs (Operational Taxonomic Units). The distances between these OTUs were comparable to those reported between marine clusters. Moreover, some of these freshwater cyanophage sequences were genetically more closely related to marine cyanophage sequences than to other freshwater sequences. Both approaches on the g20 gene (sequencing and DGGE analysis) showed that there was a clear seasonal pattern of variation in the composition of the cyanophage community that could reflect changes in its biological, chemical and/or physical environment.

During the last two decades, viruses have been shown to be a key component of aquatic microbial communities because of their abundance, ubiquity and potential impact on both biogeochemical and ecological cycles through the infection and lysis of bacterial and phytoplankton communities (10, 39). Several reports have been published concerning the impact of viral lysis on the dynamics (i.e. mortality) and clonal composition of bacterial and algal host communities (see for instance 2, 23, 26, 34), as a result of the selection pressure they exert on their hosts and by mediating gene transfer between organisms, but in contrast little is yet known about the diversity of viral communities (e.g. 43). However during the last few years, significant advances have been made in assessing the diversity of natural viral communities in marine ecosystems (4, 14, 28, 40, 43), whereas we still know relatively little about the viral diversity of freshwater ecosystems (19, 42). It is the development of molecular tools and genetic techniques that have made it possible to reveal the extensive viral diversity. Until recently, this parameter had been greatly under-estimated by culture-dependent methods (typically using isolation processes and assaying the cultured host organisms) and morphological identification (7, 38). We now have methods that can target either the entire genome, such as pulsed-field gel electrophoresis (PFGE) (2, 13, 43), total community DNA-DNA hybridization (38) and restriction digestion (19, 40), or single genes, such as cloning/sequencing methods (to create clone libraries) and denaturing gradient gel electrophoresis (DGGE) (4, 21, 31). However, microbiologists attempting to study viral diversity from single genes still face a major problem: there is no "universal target", such as the rRNA genes, that occurs in both bacteria and eukaryotic microorganisms (29). Some primers targeting at least a restricted group of phages have been proposed, i.e. a highly degenerate primer set to amplify selectively DNA polymerase genes from viruses infecting members of three genera of microalgae (3), and some specific primers

targeting a viral capsid assembly protein (g20) in cyanophages (11, 45). Some of these have been used to study viral communities by DGGE (9, 31, 41). In the general context of our attempts to assess the diversity and the functioning of pelagic microbial communities in the three great sub-alpine lakes (lakes Annecy, Bourget and Geneva), it is very important to be able to evaluate the diversity and dynamics of viruses, especially of the cyanophages. Freshwater cyanobacteria play a key role within the phytoplanktonic community in these ecosystems, and what we want to know is what contribution do viruses make to cyanobacterial structure and dynamics, and their role in control and mortality during and following bloom episodes. Picocyanobacteria such as Synechococcus spp. dominate the phytoplankton community biomass in lake Annecy (oligotrophic), whereas large, filamentous, toxin-producing cyanobacteria such as Planktothrix rubescens can be predominant during much of the year in the mesotrophic lakes Bourget and Geneva (18, Jacquet unpublished). In this study, we tested the CSP1-CSP8 cyanophage primers targeting the g20 gene coding for the viral capside structure, previously defined by Zhong et al. (45) for marine viruses, in surface water samples from Lake Bourget, and we subsequently characterized the cyanophage diversity by both cloning-sequencing and DGGE. The abundance of viruses, heterotrophic bacteria, picocyanobacteria and Planktothrix rubescens was also assessed by flow cytometry or by microscopic counting. All these determinations were performed once or twice a month between September 2002 and January 2003.

MATERIAL AND METHODS Site description. Lake Bourget (45°44’N, 05°51’W, 231 m altitude) is the largest natural French lake, and is located in the eastern part of France, on the edge of the Alps. It is a

warm, meromictic and elongated (18 and 3 km in length and width respectively), north-south orientated lake, with an area of 42 x 106 m2, a total volume of 3.5 x 109 m3, maximum and average depths of 145 and 80 m respectively, and a water residence time of approx. 10 years. Sampling strategy and cyanophage isolation. Lake water was collected at the reference station located in the middle and deepest part of the lake, at a depth of approximatively 5 m, once a month from September 2002 to January 2003. 20-L of lake water was sampled, using an electric pump on a boat deck, and kept in a flask while being transported to the laboratory. The water samples were kept at 4°C in the dark for no more than 1 week before being processed. The water was then filtered through GF/F filters in order to remove both phyto- and zooplankton. The resulting filtrate was then concentrated at least 100 fold by tangential flow filtration using a mini-ultrasette with a 100 kDa cut-off membrane (Vivaflow, Vivasciences). The concentrate was stored at 4°C until PCR amplification since phage communities can be stored in these conditions without significant loss of titer within days to months (Jacquet unpublished, Rodda and Suttle unpublished). Flow cytometry analyses. Samples were analyzed using a FACSCalibur (Becton Dickinson) flow cytometer equipped with a blue laser beam fixed at 488 nm and with the original filter set up. Picocyanobacteria were analyzed without any fixative or dye, and the community was identified on the basis of its chlorophyll and phycoerythrin fluorescences and the right angle light scatter (RALS) (Fig. 1A, B). To count the heterotrophic bacteria and viruses (Fig. 1C-F), samples underwent preliminary fixing with 0.2 µm-filtered glutaraldehyde (0.25% final concentration) for 30 min in dim light conditions. For the analysis of heterotrophic bacteria, samples were diluted 50 fold with water from the lake sampled the same day and subjected to 0.2-µm filtration. For the analysis of viruses, the samples were diluted 100 fold in 0.02-µm filtered TE buffer (pH=7.8) and heated to 75°C for 10 min. Samples of these two communities were stained using the nucleic acid dye SYBR

Green I (see 20 for more details). Cellular parameters were determined relative to the values found for 1-µm beads (Molecular probes). Data were collected in listmode files and then analyzed using CYTOWIN (36, available at http://www.sb-roscoff.fr/Phyto/cyto.html). Counting of P. rubescens. At each sampling date, 300 ml of water were preserved with Lugol’s iodine solution for subsequent microscopic counts. 200-µm units of P. rubescens filaments were counted using the Utermöhl inverted microscope technique after sedimenting 25 to 50 ml of water. The number of cells was estimated assuming that the mean length of a P. rubescens cell (estimated from 100 measurements) was 5 µm. PCR amplification, cloning and sequencing. All PCR reactions were performed using the DNA Thermal Cycler T-Personal (Biometra). Three pairs of oligonucleotides were initially tested to amplify overlapping regions of the g20 gene of cyanophages belonging to the family Myoviridae, which is the dominant group of cyanophages present in marine environments (19, 21). These primers have previously been designated CPS1/CPS2, which amplifies a 165-bp region (11), CPS3/CPS4, amplifying a 860-bp segment, and CPS1/CPS8, amplifying a ca. 592-bp region (45). After several attempts (results not shown), CPS3-CPS4 was discarded, because it led to non-specific amplification. CPS1/CPS2 was also discarded because it generated fragments that were too short for phylogenetic analysis. CPS1/CPS8 was found to be suitable for phylogenetic inference, and was therefore used in our study. The 25-µl reaction mix contained 10X Taq reaction buffer (Eurobio), 2 mM MgCl2, 200 µM of each dNTP, 1 µM of each primer CPS1 and CPS8, 1.25U of Taq DNA polymerase (Eurobluetaq® , Eurobio), and 10 µl of the viral concentrate. For each set of reactions, a negative control sample was included that contained all the reagents, but without the viral DNA. PCR reactions were carried out as described in Zhong et al. (45), with the exception of the annealing temperature, which was higher. Briefly, PCR started with an initial 3-min denaturing step at 94°C, followed by 35 cycles lasting 15 sec at 94°C, 15 sec at 46°C with a

ramping step of 0.3°C/sec, 1 min at 73°C and a final 4-min extension step at 73°C. PCR products (13 µl) were subjected to electrophoresis on a 1.4 % (w/v) agarose gel in 1X TBE (89 mM Tris-base, 89 mM boric acid, 2 mM EDTA, pH 8.0) and visualized by ethidium bromide staining. Positive PCR products were ligated to the pGEM®-T System II vector (Promega) and then transformed into JM109-competent cells (Promega) following the Manufacturer’s instructions. At least 15 positive clones (white colonies) from each clone library were randomly selected and plasmid DNA was isolated by PCR, using the commercial primers SP6 and T7. PCR amplification involved a 5-min initial denaturing step at 94°C, followed by 30 cycles at 92°C for 50 sec, 55°C for 50 sec, 72°C for 55 sec, and a final extension step at 72°C for 10 min. Positive PCR products were sequenced bidirectionally with primers SP6 and T7 on an Applied Biosystems 373 automated sequencer (Perkin Elmer, Foster City, CA) according to the Supplier's instructions. Phylogenetic analyses. The sequences were aligned using the Pileup module of the GCG package (Genetics Computer Group, Inc., Madison, Wisconsin), and alignment was manually corrected using GeneDoc (24). A phylogenetic tree was constructed for the whole data set by Neighbour-Joining (NJ) on the Jukes-Cantor distances using the PHYLIP Software Package (8). The bootstrap option was used to run 1000 replicates. Several operational taxonomic units (OTUs) were defined on the basis of their bootstrap proportions. The Chao-1 and the abundance-based coverage (ACE) estimators of species richness (16) were calculated using EstimateS software (http://viceroy.eeb.uconn.edu/estimates), and a rarefaction curve was obtained using PAST software (http://folk.uio.no/ohammer/past). By way of comparison, the composition of the cyanophage communities was determined in terms of the sampling sites, and estimations of the nucleotide diversity and pairwise FST calculations were made using ARLEQUIN software v2.000 (30).

DGGE analysis. For the DGGE analysis, the CPS1 primer was altered by adding a 40-nucleotide GC-rich sequence (GC clamp) to the 5’end, and so it was named CPS1GC. The sequence was as follows: 5' CGC CCG CCG CGC CCC GCG CCC GTC CCG CCG CCC CCG CCC G-GTAG[T/A]ATTTTCTACATTGA[C/T]GTTGG3’. The 50-µL reaction mix for PCR-DGGE contained 10X Taq reaction buffer (Eurobio), 2.5 mM MgCl2, 200 µM of each dNTP, 1 µM of each primer (CPS1GC and CPS8) , 1.25U of Taq DNA polymerase (Eurobluetaq®, Eurobio), and 20 µl of viral lysate. The same PCR and electrophoresis conditions were used as described above. DGGE analysis was performed using the CBS-DGGE 2000 system (C.B.S. Scientific, company, INC.). PCR products (40 µl) were loaded onto a 1 mm, 6% polyacrylamide gel in 1X TAE (40 mM Tris acetate, pH 7.4; 20 mM sodium acetate; 1 mM Na2-EDTA) which contained a 30-70% linear denaturing gradient (100% is defined as 7 M urea plus 40% deionized formamide), as previously established for perpendicular DGGE (data not shown). Electrophoresis was performed at a constant voltage of 100 V and a temperature of 60°C for the optimal duration of 16 h (not shown). Separated PCR products were stained for 45 min in the dark with Sybr®Gold (Molecular Probes), visualized on a UV transilluminator (Tex-35M, Bioblock Scientific) and photographed with a Kodak DC290 camera. Nucleotide sequence accession numbers. The g20 nucleotide sequences have been deposited in the GenBank-EMBL database under the accession numbers AY426128 to AY426174.

RESULTS The dynamics of microbial communities. The dynamics of viruses, heterotrophic bacteria, and cyanobacteria (both picocynobacteria and P. rubescens) in Lake Bourget were monitored in the Autumn (Fall) and early Winter of 2002/2003. During this period, we observed a net

decrease in the cell (or particle) abundance of picocyanobacteria, heterotrophic bacteria and viruses, whereas the cell density of P. rubescens rose (Fig. 2). There was a clear decline in the density of the viral community throughout the period of interest (from 26 to 5.8 x 107 part/ml), apart from an isolated peak in October (Fig. 2A). The abundance of the heterotrophic bacteria was halved during the period studied, but the dynamics of this community was characterized by a succession of alternating decreasing/increasing phases until January 2003 (Fig. 2B). For picocyanobacteria, there was an initial decrease in cell density from 2.1 x 105 to 3.0 x 104 cells ml-1 in September, followed by a stationary phase until the end of October, and then by a second decrease in November (Fig. 2C). Finally, the abundance of P. rubescens rose almost 10 fold from September to November, and then decreased slowly (Fig. 2D). Viral abundance was positively correlated with that of heterotrophic bacteria (r = 0.76; P < 0.05) and that of picocyanobacteria (r = 0.77; P < 0.01). In contrast, there was no clear correlation between the abundance of viruses and of P. rubescens (r = -0.50; not significant). Nucleotide g20 sequences analysis. Among the 47 sequences obtained by random sequencing in the different clones libraries, 12, 13, 12, 6 and 4 were obtained from samples taken on September 26, October 28, November 27, December 23 and January 28 respectively. At the two last dates, only a few sequences were obtained, due to a low cloning efficiency (low number of white colonies); this was linked to the low PCR efficiency (data not shown). Consequently, the sequences obtained at these last two dates were pooled in the subsequent analyses. The 47 sequences included 35 different haplotypes. The total nucleotide diversity was not significantly different for the four sampling periods: 0.29 (+/- 0.15) in September, 0.32 (+/- 0.16) in October, 0.22 (+/- 0.12) in November and 0.34 (+/- 0.18) in December/January. Pairwise analyses of the populations FST showed values statistically different from zero (P < 0.01) only when the November populations were compared with all the other populations

(September, October and December/January), or the September populations were compared with the December/January populations. This means that there was no genetic structuration between the September and October populations, but that there was a genetic structuration between the November population and all other populations, as well as between the September/October populations and the December/January populations. Phylogenetic analyses of g20 sequences. Phylogenetic analysis revealed the existence of six clearly-distinguished clusters containing 11, 14, 4, 3, 12 and 2 sequences respectively (Fig. 3). In each of these clusters, the percentage nucleotide sequence similarity between cyanophage sequences was always > 96% (98.7% in cluster 1, 96.6% in cluster 2, 96.3% in cluster 3, 97.7% in cluster 4, 97.9% in cluster 5 and 99.0% in cluster 6). On the other hand, the similarity ranged between 54 and 60% when sequences belonging to different clusters were compared. All these clusters were highly supported by their bootstrap proportion (1000 resamplings). One sequence (Seq. 1 in Fig. 3) stood apart from all these clusters. Thus, a total of 7 OTUs were identified in this study. Both the Chao-1 and ACE richness estimators were equal to 7 ± 1 (SD), which means that we obtained a good estimation of the OTU richness in the cyanophage community of the Lake Bourget. Similarly, the asymptotic rarefaction curve (Fig. 4) confirmed the representative nature of our sequence sample. The phylogenetic distances between these freshwater cyanophage sequence clusters were of the same order as those found when they were compared to marine cyanophage sequences (Fig. 3). Interestingly, the sequences in some of our freshwater cyanophage clusters (clusters 2 and 4) were genetically more similar to some marine cyanophage sequences than to the other clusters defined in this study. For example, there was 73-74% nucleotide sequence similarity between cluster-4 sequences and marine cyanophage sequences, ay152732, ay152738 and ay152741, but less than 60% similarity with other freshwater cyanophage sequences.

Temporal variation in the cyanophage community. The distribution of the sequences belonging to the different clusters determined above (Fig. 5) revealed first that sequences belonging to cluster 1 were only obtained in September and October. Moreover, it appears that these sampling months were characterized by very similar patterns for the sequence distributions, characterized by the dominance of cluster-1 sequences, but also by the presence of cluster -2, -3 and -5 sequences. November was characterized by a high dominance of sequences belonging to cluster 2 (Fig. 5). For December and January months, sequences belonging to five of six clusters were found in quite similar proportions (Fig. 5). Only two clusters (clusters 2 and 5) were found throughout the whole season. The first one (cluster 2) showed high variations in regard to the sampling months while for the second one (cluster 5), no variation was observed. DGGE analysis. DGGE analysis was performed on the same samples than those used for the sequencing approach. On the one hand, the study of the DGGE migration profile (Fig. 6) revealed that the first two sampling months (September and October) were characterized by similar band patterns. On the other hand, considerable differences in the band intensities were observed in the migration profile obtained for the November sample (Fig. 6). During the last two sampling months (December and January), there was a low intensity in the profiles, due to a low PCR amplification efficiency. It seems however that these patterns were more similar to that obtained for the November sample, than to those for the September and October samples (Fig. 6).

DISCUSSION The purpose of this study was 1) to assess the g20 phylogenetic diversity of a natural freshwater cyanophage community, and to compare this diversity to that of known marine cyanophage communities, and 2) to evaluate the temporal variation in the diversity of this

natural freshwater cyanophage community by means of two methods (random sequencing of clone libraries and DGGE). The originality of this work is that this is the first study of the diversity and dynamics of viruses (cyanophages) in the largest natural French Lake. In addition, this study is one of the few investigating how the genetic composition of natural viruses may change over time. Our findings show that the phylogenetic diversity of natural cyanophages in the mesotrophic Lake Bourget seems to be very great. Seven OTUs were identified among the 47 sequences obtained over a limited period of time (6 months in 2002/2003). This relatively high diversity of the cyanophage community has already been reported but, as far as we are aware, this has only been shown in marine ecosystems (21, 45). Zhong et al. (45) proposed that this could be due to important genetic exchanges between phage and host, or coinfecting phages. Such horizontal transfers within the cyanophage communities were also recently suggested by Sullivan et al. (32). Another complementary hypothesis that can be proposed is that the high diversity within cyanophage community may be linked to high diversity in the host community. In picocyanobacteria in oligo- and mesotrophic lakes, Becker et al. (1) found that different lineages of the picoplankton clade sensu Urbach et al. (35) were present in Lake Constance (Germany), an ecosystem which has very similar physical, chemical and biological characteristics to Lake Bourget. Following the same approach, Crosbie et al. (6) recently showed that there are at least seven clusters within non-marine picocyanobacteria. Despite its partial nature, our study of the molecular characteristics of freshwater cyanophages suggests once again that genetic diversity may be high within this community. The genetic distances we found between the different clusters were in the same range as those found by Zhong et al. (45) for isolates and natural marine cyanophages. Very interestingly, we found that some of our freshwater cyanophage sequences were more similar to marine cyanophage sequences than to other freshwater cyanophage sequences (Fig. 3). This

finding suggests that some marine and freshwater cyanophages may have shared a common ancestor. This finding is also consistent with the fact that a close phylogenetic relationship can be found between several marine and freshwater strains of Synechococcus (15), supporting the idea of a very ancient separation between our different freshwater cyanophage lineages. A discussion of cyanophage evolution can be found elsewhere (33). It is also noteworthy that differing cyanophage communities can occur within very short distances (a few meters), suggesting that groups can develop divergently as a result of isolation by water column stratification, for instance (9, Frederickson et al. 2003). We are well aware that we probably have considerably underestimated the phylogenetic diversity of the cyanophage community in the Lake Bourget due to our choice of a restricted number of primers for the initial PCR. CSP1 and CSP8 primers allow the amplification of the g20 gene of cyanophages belonging to the family Myoviridae, which is considered to be the most abundant cyanophage family in marine ecosystems (45). However, it is important to bear in mind both that these primers do not allow the amplification of all genotypes in this family, as recently shown by Marston and Sallee (21), and also that other viruses belonging to the Podoviridae or Siphoviridae families may be important members of the cyanophage community. Thus, using this set of primers makes it possible to assess a part of the cyanophage diversity, but more sequences in the three main cyanophage groups (Myoviridae, Podoviridae and Siphoviridae) are now needed to define new sets of primers with different targets to allow us to obtain a better picture of this phage diversity. Seasonal changes recorded in the (cyano)phage community sampled in surface waters of Lake Bourget affected both the abundance and the diversity of these microorganisms. As mentioned above, we observed a clear reduction in the total viral abundance from September to January and, at the same time, a decrease in PCR efficiency for the g20 gene. This probably reflected a decrease in the target number, and thus in cyanomyophage abundance. Many

authors have reported a winter decrease of this sort in the viral abundance in aquatic ecosystems, and this has been attributed to a positive correlation between host and virioplankton abundance (see review by Wommack and Colwell, 44). Generally speaking, changes in the marine virioplankton diversity have been shown to be linked to changes in the season and water stratification, combined with physicochemical factors, such as light, nutrient availability, salinity, as well as biological processes (2, 19, 27, 43). In our study, virioplankton abundance was indeed positively correlated with that of the picobacteria (both auto- and heterotrophs). In contrast, there was no clear relationship between the viral community and the filamentous cyanobacterium P. rubescens, even though the concentration of the latter was relatively high. Several reasons can be invoked to explain such a finding. It is likely that we did not target the virus types corresponding to this cyanobacterium for the obvious reasons already mentioned. It is noteworthy that all our attempts to infect concentrate cultures of many P. rubescens strains originating from Lakes Bourget and Geneva with viruses failed during this period. The use of UV-C and mitomycin C led to the same conclusion. It is therefore possible that the titer of the cyanophage (associated with P. rubescens) was low during the period of interest, and that this can be attributed to gradients in cyanobacterial diversity, growth rates, and/or incidence of lysogeny (bacteria containing inducible prophages), plus of course the degree of phage infectivity. Viruses are obligate pathogens and require host cells in order to replicate, and in fine and in most cases they kill their hosts. Successful infection requires direct contact, which means that numerically dominant host cells are more easily infected, and thus more likely to produce a higher titer of viruses. This has been shown for example by Lu et al. (19), who found a positive correlation between the distribution of cyanophages and the total Synechococcus spp. cells in both coastal and open oceans. Taken together, these data suggest that our sequences are likely to belong only to picocyanobacterial phages and/or that

important resistance mechanisms exist for filamentous cyanobacteria, such as P. rubescens, of which major blooms without extinction episodes have been recorded (Jacquet et al. in revision). Such host resistance has often been reported for other cyanobacterial species (33, 37). With regard to the seasonal pattern of g20 phylogenetic diversity, sequencing and DGGE approaches revealed similar values in September and October, at first sight validating both methodological approaches. However, whereas the sequencing of the November sample revealed the disappearance of sequences from cluster 1 and the dominance of sequences from cluster 2 (Fig. 5), the DGGE pattern revealed shifts in the band profiles, most of which involved the relative intensity of the bands, and in a few cases, the disappearance of a few bands (Fig. 6). Such seasonal changes in the relative cyanophage g20 genotypes were also reported by Marston and Sallee (21) in coastal cyanophage communities. Using Pulsed-Field Gel Electrophoresis, Wommack et al. (43) found seasonal changes in the composition of natural virioplankton communities in Chesapeake Bay. It would have been very interesting to evaluate changes in the composition of the host communities as well in order to determine the relationships between host and virus compositions. This is one of the perspectives for future research arising from this study. From a practical point of view, this study confirmed that the DGGE fingerprinting technique is a very efficient tool for monitoring changes in the composition of natural cyanophage communities. This had previously been reported in marine cyanophage communities using another set of primers by Frederickson et al. (9) and by Wilson et al. (41). Combined with quantitative PCR, it may make it possible to assess the relative abundance of the various strains in these communities. Indeed, this approach is now currently used in clinical virology (e.g. 12, 25), and its application to aquatic viral ecology could be extremely promising.

Efforts to understand the complex interactions between viruses and their hosts in marine microbial communities are greatly impeded by the lack of studies of the genetic diversity of viruses in natural environments. Considering the ecological and evolutionary significance of cyanobacteria, it is likely that cyanophage ecology is still in its infancy. This is especially true of freshwater ecosystems, where we still know little about the role of cyanophages in regulating the abundance, distribution, productivity, and diversity of cyanobacteria, and the transformation of biomass into dissolved organic matter. Studies of the dynamics and diversity of this community should be a prerequisite to further analysis dealing with 1) lytic/lysogenic processes, since we know almost nothing about the proportion of cyanobacteria that are lysogenized in nature and the role of environmental factors in the establishment of such a lysogenic association in cyanobacteria or for triggering the lytic process (33) understanding if and why cyanophages are restricted to only particular cell types, and hence their impact on population/community dynamics and diversity.

ACKNOWLEDGEMENTS We are very grateful to F. Chen for his valuable advice about the PCR conditions for the g20 gene amplification. Monika Ghosh is acknowledged for improving the English version of the manuscript. The DGGE system was funded by la Fondation pour la Recherche Médicale. The flow cytometer was funded by l’Institut National de la Recherche Agronomique and l’Université de Savoie.

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HaV

clones

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FIG. 1. Flow cytometric analysis of natural microbial populations sampled in the surface waters of Lake Bourget. (A-B) Unstained samples revealing the picocyanobacterial community (probably Synechococcus spp.) on the basis of the chlorophyll (chl) and phycoerythrin (Pe) fluorescence and the right angle light scatter (RALS). (C-F) Samples stained with the nucleic acid dye SYBR Green I revealing the communities of heterotrophic bacteria and viruses on the basis of the green DNA fluorescence vs. the RALS or forward angle light scatter (FALS). Two groups of heterotrophic bacteria could be discriminated (CD) on the basis of DNA-dye fluorescence, and were referred to as high or low DNA bacteria (HDNA or LDNA, respectively). Three groups of viruses could also be discriminated (E-F) and are referred to as V1, V2 and V3. The 1-µm fluorescent beads were added to all the each samples apart from the ones used for the virus analysis.

FIG. 2. Temporal cha nges in the dynamics of viral (A), heterotrophic bacterial (B), picocyanobacterial (C) and P. rubescens (D) communities in Lake Bourget (France)

FIG. 3. The non-rooted neighbor-joining phylogenetic tree obtained for?? from?? partial g20 gene sequences from the cyanophage community of the Lake Bourget (France). Marine cyanophage sequences, identifed by their Genbank accession number, were also added. Only boostrap values > 80 % are indicated at the nodes of the tree.

FIG. 4. Rarefaction curve of observed OTU richness in cyanophage community of Lake Bourget (France)

FIG. 5. Temporal changes in the abundance of the six clusters defined by the phylogenetic analysis of the g20 gene sequences from the cyanophage community of Lake Bourget (France)

FIG. 6. Temporal changes in the DGGE band patterns obtained for PCR products resulting from the amplification of a 592-bp fragment of the g20 gene in the cyanophage community of Lake

Bourget

(France). Arrows indicate

the principal

differences between the

September/October and November band patterns. A and G: Mix of September/October samples; B: September sample; C: October sample; D: November sample; E: December sample; F: January sample.

A

Beads

B

Picocyanobacteria

Chl fluorescence

Chl fluorescence

Picocyanobacteria

Beads

Pe fluorescence

Beads

C

Heterotrophic bacteria

DNA-dye fluorescence

DNA-dye fluorescence

RALS

HDNA LDNA

Heterotrophic bacteria

Fig. 1

RALS

E

V2 V1 Viruses

DNA-dye fluorescence

DNA-dye fluorescence

FALS

FALS

D

Beads

Heterotrophic bacteria V3

RALS

F

8e+6

Virus conc. (part/ml)

A 6e+8

4e+8

2e+8

0

Aug 02

Het. bact. conc. (cell/ml)

8e+8

6e+6

4e+6

2e+6

0

Feb 03

B

Aug 02

Time

Time

C

2e+5

1e+5

0

Aug 02

Feb 03

Time

Fig. 2

1e+4

P. rubescens conc. (cell/ml)

Picocyano. conc. (cell/ml)

3e+5

Feb 03

D

5e+3

0

Aug 02

Feb 03

Time

AY027973

Cluster 2

AY027938

(14 sequences) AY027972

100 AY27978 AY028022

100

AF016386

Cluster 4 (3 sequences)

98.8 89.8

100

97.1

AY027986

100

AY152732 AY152738

100

AY152741

Cluster 5 (12 sequences) 100 Cluster 6 (2 sequences) 0.1

Cluster 1 (11 sequences)

Seq. 1

Cluster 3 (4 sequences)

8 7

Number of OTUs

6 5 4 3 2 1 10

Fig. 4

20 30 Number of sequences

40

Abundance

8 7 6

Cluster 1

5

Cluster 2 Cluster 3

4

Cluster 4

3

Cluster 5 Cluster 6

2 1 0 Sept 02

Fig. 5

Oct 02

Nov 02

Dec 02 / Jan 03

A

Fig. 6

B

C

D

E

F

G