Genotypic, size and morphological diversity of virioplankton in a deep oligomesotrophic freshwater lake (Lac Pavin, France)

JES-00812; No of Pages 12 J O U RN A L OF E N V I RO N ME N TA L S CI EN CE S X X (2 0 1 6 ) XX X–XXX

Available online at www.sciencedirect.com

ScienceDirect www.elsevier.com/locate/jes

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Jonathan Colombet1,⁎, Agnès Robin2 , Télesphore Sime-Ngando1

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1. Laboratory Microorganisms: Genome and Environment, Clermont University Blaise Pascal, UMR CNRS 6023, 24 avenue des Landais, BP 80026, F-63171 Aubière, France. E-mail: [email protected] 2. CIRAD, UMR Eco&Sols, 2 place Viala, 34060 Montpellier Cedex 1, France

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Genotypic, size and morphological diversity of virioplankton in a deep oligomesotrophic freshwater lake (Lac Pavin, France)

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ABSTR ACT

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Article history:

We examined changes in morphological and genomic diversities of viruses by means of 16

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Received 1 December 2015

transmission electronic microscopy and pulsed field gel electrophoresis (PFGE) over a 17

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Revised 2 May 2016

nine-month period (April–December 2005) at four different depths in the oligomesotrophic 18

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Accepted 5 May 2016

Lac Pavin. We found that the majority of viruses in this lake belonged to the family of 19

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Available online xxxx

Siphoviridae or were untailed, with capsid sizes ranging from 30 to 60 nm, and exhibited 20

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Keywords:

of the PFGE fingerprints. The highest genomic viral richness was recorded in summer 22

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Virus

(mean = 14 bands per PFGE fingerprint) and in the epilimnion (mean = 13 bands per PFGE 23

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Lac Pavin

fingerprint). Among the physico-chemical and biological variables considered, the 24

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Dynamic

availability of the hosts appeared to be the main factor regulating the variations in the 25

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Morphological diversity

viral diversity.

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Genomic diversity

© 2016 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. 27

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genome sizes ranging from 15 to 45 kb. On average, 12 different genotypes dominated each 21

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Introduction

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It is now widely accepted that viruses are the most abundant entities in aquatic ecosystems, where their abundance is about an order of magnitude greater than the number of bacteria (Weinbauer, 2004; Suttle, 2007). Viruses are ubiquitous entities in natural environments, infecting virtually every living form of life, from cellular prokaryotes to animals and plants. A given host probably has a range of different co-infectious viruses, resulting in enhanced gene exchanges between phages and hosts (Moineau et al., 1994). For example, it was suggested that bacteria and their co-infecting phages function as ‘phage factories’ and produce a variety of chimeric or mosaic phages that increase viral diversity (Ohnishi et al., 2001). Undoubtedly, environmental viruses are the largest reservoir of genetic diversity on the planet (Suttle, 2005, 2007). For viruses there are no universal molecular markers that are

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shared among all viruses, similar to molecular RNA genes for cellular organisms, that could be used to assess their diversity (Hendrix et al., 1999). In aquatic environments, only genes belonging to specific groups or families can be targeted (Culley et al., 2003). This renders the study of global viral diversity difficult by PCR-based methods. In addition to the use of transmission electronic microscopy (TEM) for estimating viral diversity based on phenotypic traits (Auguet et al., 2006; Brum and Steward, 2010; Liu et al., 2006; Weinbauer, 2004; Wommack and Colwell, 2000), metagenomic and other molecular techniques have been developed and extensively used (Angly et al., 2006; Breitbart et al., 2002; Hambly and Suttle, 2005; Williamson et al., 2008; Winget and Wommack, 2008; Wommack and Colwell, 2000). Among these, pulsed field gel electrophoresis (PFGE) is based on size fractionation of intact DNA and has the advantage of allowing easy and rapid estimation of the whole-genome fingerprint of natural

⁎ Corresponding author.

http://dx.doi.org/10.1016/j.jes.2016.05.016 1001-0742/© 2016 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.

Please cite this article as: Colombet, J., et al., Genotypic, size and morphological diversity of virioplankton in a deep oligomesotrophic freshwater lake (Lac Pavin, France), J. Environ. Sci. (2016), http://dx.doi.org/10.1016/j.jes.2016.05.016

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1. Experimental procedure

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1.1. Study site and sample collection

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Samples were collected in Lake Pavin (altitude 1197 m), a meromictic and dimictic oligomesotrophic lake located in the French Massif Central, that experiences partial overturn. It is a typical crater mountain lake characterized by a maximum depth of 92 m and low surface (44 ha) and catchment (50 ha) areas. A characteristic feature of the physical structure of Lake Pavin is the existence of an oxic/anoxic interface (i.e., oxycline) between 50 and 60 m depth. Samples were collected monthly (systematically between 09:00 am and 10:00 am) from April to December 2005 from a central location in the lake by using an 8-L Van Dorn bottle. Four different layers were sampled, corresponding to the epi- (5 m), meta(12 m) and hypolimnion (30 m), and to the oxycline (57 m) (Colombet and Sime-Ngando, 2012). This was done for all biological variables, except for picocyanobacteria and autotrophic picoeukaryotes, which were determined in the epi-, meta-, and hypolimnion. All analysis was performed in triplicate, except for genomic size profiling of samples by pulsed field gel electrophoresis.

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1.2. Virioplankton concentration

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For the diversity study of viruses, viral concentrates are required. The strategy employed for viral concentration was based on the use of polyethylene glycol (PEG), an approach that we have recently described in detail in Colombet et al. (2007). Following successive prefiltration steps, 20 L samples were filtered with 0.2 μm pore size filters. Viruses from the filtrate were concentrated by ultrafiltration, using a high performance concentration/diafiltration system (Model DC 10LA, Amicon®, Epernon, France) equipped with a reusable hollow fiber cartridge with a 30-kDa cut-off (Amicon®, Epernon, France). Concentrated viruses in the retentate were then precipitated by ‘pegylation’, i.e., PEG-treated. Polyethylene glycol 8000 (Catalog No. 81,268; Sigma, Saint-Louis, USA) together with NaCl was added to 210 mL of viral ultrafiltered retentates to final concentrations of 10% and 0.6%, respectively, and incubated at 4°C in the dark for at least 24 hr. At the end of incubation, the white phase containing crystallized

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environmental forcing factors. In this study, we have investigated the spatio-temporal dynamics of viral community diversity (based on genomic and morphological characteristics) and activity (lytic and lysogenic), concurrently with physico-chemical parameters (temperature, oxygen, chlorophyll a) and microbial community variables (bacteria, picocyanobacteria, autotrophic picoeukaryotes, autotrophic and heterotrophic nanoflagellates). We sought empirical evidence of the potential connections between the diversity of viruses and both abiotic and biotic environmental factors, at consistent seasonal and depth scales in aquatic systems. This study complements companion papers in which the standing stock of virus and microbial communities (Colombet et al., 2009) as well as grazing and viral activities (Colombet and Sime-Ngando, 2012) were examined.

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communities of viruses (Steward and Azam, 2000; Wommack et al., 1999a, 1999b). Results obtained with this method have showed that between 7 and 35 bands can be distinguished by applying PFGE to individual samples, as a minimum viral richness, with a dominance of <100 kb genomes in both marine (Jamindar et al., 2012; Weinbauer, 2004) and freshwater plankton (Auguet et al., 2006; Filippini and Middelboe, 2007; Tijdens et al., 2008). Some studies have shown that viral genomic diversity, determined from PFGE and the relative intensity of individual bands, can vary seasonally (Castberg et al., 2001; Jamindar et al., 2012; Larsen et al., 2001, 2004; Sandaa and Larsen, 2006; Wommack et al., 1999b; Zhong et al., 2014) and spatially (Auguet et al., 2006; Filippini and Middelboe, 2007; Jiang et al., 2004; Riemann and Middelboe, 2002; Steward et al., 2000; Tijdens et al., 2008; Wommack et al., 1999a). However, little is known about the factors controlling these variations, because only rare works have simultaneously studied the viral genomic composition (VGC) and the microbial community structure and environmental factors. A few authors have hypothesized that VGC changes with the structure of host communities (Auguet et al., 2006; Steward et al., 2000; Tijdens et al., 2008). Sandaa and Larsen (2006) have shown that seasonal changes in viral community composition can be related to changes in the abundances of cyanobacteria, autotrophic nano- and picoeukaryotes and heterotrophic bacteria, whereas Riemann and Middelboe (2002) and Tijdens et al. (2008) reported no clear link between temporal changes in VGC and bacterial community composition and/or phytoplankton abundance. With the exception of the work of Tijdens et al. (2008), the few data available were conducted in marine waters, but without taking into account phytoplanktonic species and protistan flagellates. Potential links between VGC and microbial community structure thus remain to be established, because there are many routes of interaction between viruses and microbial communities (Pradeep Ram and Sime-Ngando, 2008; Sime-Ngando and Pradeep-Ram, 2005). For example, in addition to representing a potential host reservoir for viruses (Massana et al., 2007), protistan flagellates could also graze bacteria and/or viruses (Bettarel et al., 2005), thereby influencing directly or indirectly the viral diversity (Weinbauer, 2004). Viral lytic or lysogenic activity could also affect VGC (Weinbauer, 2004). Parada et al. (2008) suggested that viral richness changes at time scales of hours to days linked with the lysing of specific bacterioplankton phylotypes. Since the genetic exchanges are probably higher among lysogenic than among lytic phages, the diversity of lysogenic phages is important (Chen and Lu, 2002), and higher viral diversity could be recorded during lysogen induction events. However, at the community level, no study to our knowledge has considered simultaneous changes in VGC together with lytic and lysogenic activities and with potential grazers as well. Finally, Jiang et al. (2004) have shown that VGC changed with oxygen conditions in the hypersaline Lake Mono (California, USA). Weinbauer (2004) suggested that certain physico-chemical parameters may define the niches for phages and thus influence viral diversity. Many biological or physico-chemical factors could thus potentially affect VGC, but very few attempts have been made to study these effects, leaving open many questions of ecological interest concerning the dynamics of the biodiversity within virioplankton communities and the related

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Please cite this article as: Colombet, J., et al., Genotypic, size and morphological diversity of virioplankton in a deep oligomesotrophic freshwater lake (Lac Pavin, France), J. Environ. Sci. (2016), http://dx.doi.org/10.1016/j.jes.2016.05.016

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1.4. Genomic size diversity of virioplankton

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Viral genomic composition (VGC) was analyzed by pulsed field gel electrophoresis (PFGE). Viral concentrates were first heated in a water bath at 60°C for 10 min for nucleic acid extraction (Jiang et al., 2004). Plug molds were prepared by mixing equal volumes of the viral concentrate (50 μL) and 1.5% molten (50°C) agarose (Incert agarose, FMC®, Rockland, USA) in 0.5% TBE (50 mmol/L Tris Base, 45 mmol/L Boric acid, 0.5 mmol/L EDTA, pH 8.4). Solidified plugs were punched out from the molds into 1 mL of TE buffer (20 mmol/L Tris Base, 50 mmol/L EDTA, pH 8) and stored at 4°C. Additional plugs containing phage lambda concatemers (MidRange PFG Markers, New England Biolabs, Ipswich, USA) were used as molecular markers. Viral and marker plugs were place into wells of a 1% agarose (Eurobio, Les Ulis, France) solution prepared in 0.5× TBE buffer, and PFGE was performed with a CHEF-DRIII system (Bio-Rad, Hercules, USA) at 14°C, 6 V/cm, 120° angle, and switch time of 1 to 15 sec for 22 hr, using 0.5 × TBE as running buffer. After electrophoresis, the gel was stained for 30 min in ethidium bromide (concentration 0.05 μg/mL) and rinsed for 1 hr in distilled water. The gel was digitally scanned using a gel imager (UVT-28MP, Herolab, Wiesloch, Germany), and

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The shape and size of viruses were analyzed by transmission electronic microscopy (TEM). Viruses in concentrates were collected directly onto 400-mesh Cu electron microscopy grids with carbon–coated Formvar film (Pelanne Instruments, Toulouse, France). A 60 μL aliquot of viral concentrate (stored at 4°C) was diluted in 6 mL of 0.02 μm filtered distilled deionized water, and centrifuged at 120,000 ×g for 3.5 hr, 4°C with a SW 40 Ti rotor (Optima™ LE 80 K ultracentrifuge, Beckman Coulter, Brea, USA). Three grids were observed at a magnification greater than 50,000×, and at least 300 viruses were observed and counted on each grid. During observation, viruses were classified based on two morphological criteria: the size of the capsid and the general shape of viral particles. For capsid-size classification, viruses were categorized into five size classes: <30, 30–60, 60–80, 80–100, and > 100 nm (Sime-Ngando and Colombet, 2009). For shape classification, four morphotypes were distinguished, untailed viruses and three families in the order Caudovirales, distinguished according to the morphological criterion defined by the International Committee on Taxonomy of Viruses. These families were as follows: Siphoviridae (viruses with noncontractile long tails), Myoviridae (with contractile long tails, and presence of a neck), and Podoviridae (with short tails).

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1.5. Others variables

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quantitative analysis of digital gel pictures (molecular weight and fluorescence intensity of bands) was performed with the software analysis program Image J (Scion Corporation®, Washington D.C., USA). Each gel was normalized using a molecular weight ladder run on both sides of the gel. The region bracketed by the largest and smallest DNA size standards was divided into 19 subregions (<15, 15–30, 30–45, 45–60, 60–75, 75–90, 90–105, 105–120, 120–135, 135–150, 150– 165, 165–180, 180–195, 195–210, 210–225, 225–240, 240–255, 255–290, >290 kb). Genome copy number in a subregion was determined by calculating the density within each subregion divided by an average molecular size in the subregion (Riemann and Middelboe, 2002). To facilitate comparison among samples, the copy number present in one subregion was divided by the total copy number present in the same sample according to Steward et al. (2000). Electrophoretic profiles were compared using similarity analysis based on the presence/absence of each band within each sample. The similarity matrix (Dice coefficient) allowed construction of a dendrogram following the unweighted pair group method with arithmetic means (UPGMA).

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viruses was pipetted, centrifuged at 8000 ×g for 20 min at 4°C, and resuspended in SM buffer (0.1 mol/L NaCl, 8 mmol/L MgSO4-7H2O, 50 mmol/L Tris–HCl, and 0.005% (wt/vol) glycerol) adjusted to neutral pH). 1 mol/L KCl was then added, and the mixture was incubated on ice for 20 min and centrifuged (12,000 × g, 10 min at 4°C), in order to precipitate the PEG solution slowly while leaving the free viruses behind. The supernatant with clean viruses was finally pipetted and used for diversity analysis (Colombet et al., 2007).

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The temporal and vertical variations in the water temperature, dissolved oxygen, concentrations of chlorophyll a, the abundances of viral and microbial communities (i.e., virus and heterotrophic bacteria, picocyanobacteria and autotrophic picoeukaryotes, heterotrophic and autotrophic nanoflagellates) and the grazing and viral activities (lytic and lysogenic) have been described and discussed in detail in companion papers (Colombet et al., 2009; Colombet and Sime-Ngando, 2012).

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1.6. Statistical analysis

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Normal distribution of data was checked by the Kolmogorov– Smirnov test. Because the data sets did not all follow normal distribution, we applied log transformation to meet the requirements for parametric statistics. One-way analysis of variance was used to test for differences in viral diversity parameters between seasons (i.e., spring (April to June), summer (July to September), and autumn (October to December)) and sampling depths. Potential relationships among variables were tested by Pearson correlation analysis, with the significance level considered to be p < 0.01. All statistical analysis was performed using MINITAB 12 and SYSTAT 10.

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2. Results

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2.1. Morphological diversity of viruses

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2.1.1. Frequency of distribution of capsid size

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The mean (± standard deviation) capsid size for all samples was 49 ± 4 nm, and fluctuated weakly from 47 ± 4 nm in the metalimnion to 50 ± 5 nm in the oxycline. No clear vertical trend was recorded (Table 1). Seasonal mean values were relatively lower in spring and summer than in autumn (Table 1). Particles with capsid size ranging from 30 nm to 60 nm largely dominated the viral communities, representing

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Please cite this article as: Colombet, J., et al., Genotypic, size and morphological diversity of virioplankton in a deep oligomesotrophic freshwater lake (Lac Pavin, France), J. Environ. Sci. (2016), http://dx.doi.org/10.1016/j.jes.2016.05.016

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Table 1 – Mean (coefficient of variation) genome and capsid size for each layer and season sampled in Lake Pavin.

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2.1.2. Morphological families

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Based on general morphology, viral communities were dominated by the unclassified family of untailed phages (from 54% to 68% of the total abundance), followed by Siphoviridae (27%–40%), Myoviridae (2%–6%), and Podoviridae (0.2%–2.4%) (Fig. 1). Myoviridae, Siphoviridae and untailed viruses presented significant variations with depth (ANOVA, p < 0.001), with values lowest in the hypolimnion for Myoviridae, in the epilimnion for Siphoviridae, and in the hypolimion and oxycline for untailed viruses (Fig. 1). No significant seasonal pattern was recorded (ANOVA, p > 0.05), although the relative abundances of Myoviridae and Siphoviridae were highest in autumn, contrasting with untailed viruses (Fig. 1).

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2.2. Viral genomic composition

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2.2.1. Qualitative analysis

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Analysis of viral genomic composition by pulsed field gel electrophoresis revealed the presence of 34 different viral genotypes in the sampled depths and during the entire study period (Fig. 2). Four sampling months were excluded from qualitative analysis due to insufficient discrimination between bands, i.e., the month of April in the epilimnion, June in the hypolimnion, and the months of August and October in the metalimnion. On average (± standard deviation), (12 ± 3) different bands per lane were recorded. The maximal mean number of bands per lane was recorded in summer (14 ± 3 bands), with highest mean values in August (16 bands) and in September (16 bands). The lowest values were observed in autumn (12 ± 1 bands) and in spring (10 ± 2 bands) (Fig. 2). The mean number of bands per lane increased weakly from the

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2.2.2. Quantitative analysis

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The mean (±standard deviation) genome size for all samples was (51 ± 7) kb. Mean genome size decreased clearly with depth, from (55 ± 9) kb in the epilimnion to (52 ± 5), (50 ± 5), and (48 ± 6) kb in the metalimnion, hypolimnion, and oxycline, respectively (Table 1). Mean genome size was higher in summer (55 ± 9 kb) than in spring (50 ± 6 kb) and autumn (49 ± 3 kb) (Table 1). Viruses with a genome size ranging from 15 kb to 30 kb and from 30 kb to 45 kb were dominant, averaging 32% and 29% of total abundance, respectively. Viruses with genome sizes <15 kb represented the smallest proportion.

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2.3. Correlation analysis

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Relationships between specific viral diversity descriptors and environmental parameters were described by Pearson correlation analysis. Correlation coefficients (p < 0.01) between the different tracers of viral diversity and the other variables measured are given in Table 2. Thus, viruses presenting large capsid and large genome sizes were mainly correlated with the abundance of eukaryotes. Autotrophic picoeukaryotes and Crysidalis species (Colombet et al., 2009) were correlated with almost all genome and capsid size classes, but were the sole microorganisms correlated with viruses in the largest genome (>105 kb) and capsid (>80 nm) size classes. In contrast, the abundances of prokaryotes, i.e., heterotrophic prokaryotes and picocyanobacteria (Colombet et al., 2009), were exclusively correlated with small size viruses, both in terms of genome (15–105 kb) and capsid (30–80 nm) sizes. Regarding the morphological groups of viruses, the dominant group of ‘untailed viruses’ was correlated with the abundances of all picoplankton categories, and with the Crysidalis species. Podoviridae were correlated only with Crysidalis species, as well as Myoviridae and Siphoviridae. Myoviridae and

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from 55% to 78% of the total viral abundance (Fig. 1). Viruses in the capsid size classes of < 30 nm and 60–80 nm were in equal proportion (from 6% to 26% and from 6% to 25%, respectively) (Fig. 1). Viruses with large capsid size were less abundant, ranging from 1% to 11% and from 0% to 3% of the total abundance, for 80–100 nm and > 100 nm size classes, respectively (Fig. 1). According to depth, only viruses with capsid size < 60 nm presented significant vertical changes (ANOVA, p < 0.001), with lowest values in the oxycline (Fig. 1). According to the season, only viruses > 80 nm presented significant changes (ANOVA, p < 0.01), with the lowest values in summer for the size class > 100 nm, and in spring and summer for the size class 80–100 nm (Fig. 1).

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oxycline (11 ± 2 bands) to the epilimnion (13 ± 3 bands), with intermediate values in the hypolimnion (12 ± 3 bands) and in the metalimnion (12 ± 2 bands) (Fig. 2). The analysis of the distribution of genome size classes based on presence/absence of bands showed some similarities and differences according to the sampling time or depth. Five dominant genome size classes (25–40, 55–65, 80–100, 155– 180 and 250–292 kb) were common for all sampling depths and dates (Fig. 2). Differences in fingerprinting were located in the intermediate size classes. The appearance of new bands occurred in summer and autumn, around 20 kb, in the 40– 50 kb size classes and around 75 kb (Fig. 2). Interestingly, we also observed appearance of new bands in 100–115 kb and 130–160 kb regions in summer-autumn and in summer, respectively, particularly in the epi- and metalimnion (Fig. 2). Finally, we observed a heterogeneous distribution of bands in the 190–230 kb region (Fig. 2). Based on the results of the similarity analysis (Fig. 3), we showed that temporal variability in viral genomic composition was inversely correlated to depth. Indeed, all sampled months taken in the oxycline have a coefficient of similarity > 0.60, whereas this coefficient is >0.30 in the epilimion, with hypolimnion and metalimnion showing intermediate values (> 0.54 and > 0.52 respectively). Thus VGC was more affected by temporal changes in the epiand metalimnion than in the hypolimnion and oxycline.

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Please cite this article as: Colombet, J., et al., Genotypic, size and morphological diversity of virioplankton in a deep oligomesotrophic freshwater lake (Lac Pavin, France), J. Environ. Sci. (2016), http://dx.doi.org/10.1016/j.jes.2016.05.016

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Fig. 1 – Spatiotemporal frequency distribution of capsid size class and morphology for total Virus Like Particles (VLPs). Sipho.: Siphoviridae. Myo.: Myoviridae. Podo.: Podoviridae.

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Siphoviridae were also correlated with the autotrophic groups of picocyanobacteria and picoeukaryotes. All correlation coefficients with picoeukaryotes were negative, in contrast to the other coefficients. Finally, very few correlations were noted between viruses and the biological activity variables (i.e., frequency of lytically infected cells (FIC),

frequency of lysogenically infected cells (FLC), grazing potential; see Colombet and Sime-Ngando, 2012), while temperature appeared as a significant forcing factor for the dominant < 60 nm capsid size classes of viruses, and for almost all the morphological and genome size categories distinguished, due to peaks in summer/autumn (Tables 1, 2).

Please cite this article as: Colombet, J., et al., Genotypic, size and morphological diversity of virioplankton in a deep oligomesotrophic freshwater lake (Lac Pavin, France), J. Environ. Sci. (2016), http://dx.doi.org/10.1016/j.jes.2016.05.016

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Fig. 2 – Computer-generated representations of presence/absence of bands from virioplankton PFGE fingerprints for samples obtained from April to December 2005 in Epilimnion (Epi), Metalimnion (Meta), Hypolimnion (Hypo) and Oxycline (Oxy). Months are indicated in the bottom of the representations, layer in the top of the representations and genome size on the left side of the representations. Mid: MidRange PFG markers. ND: not determinated; PFGE: pulsed field gel electrophoresis.

3. Discussion

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3.1. Methodological considerations

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Critical assumptions for the use of pulsed field gel electrophoresis (PFGE) to assess viral diversity have previously been made in various papers (Filippini and Middelboe, 2007; Riemann and Middelboe, 2002; Steward et al., 2000; Weinbauer, 2004; Wommack et al., 1999b). Among these, it is important to keep in mind that only quantitatively dominant viral genome sizes may be analyzed, because of the sensitivity of the method (≥106 viruses per band (Wommack et al., 1999b)), which means that some information on the total number of viral genotypes in a given sample can be biased. In addition, a close succession of high density-bands, differing only by few kb, sometimes results in a smear, making the distinction of individual bands in a given region difficult. Instead of providing a realistic estimation of

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total viral diversity, based on the distribution of dominant genome sizes, the PFGE approach provides an efficient, rapid and easy way to detect major differences in viral communities between environments or time-points, and gives an estimation of the minimum number of different viral genotypes (Filippini and Middelboe, 2007). These estimates were, in this study, completed by estimation of viral phenotypic diversity by transmission electron microscopy (TEM). The viral concentration method used allowed us to obtain purified viral concentrates, avoiding major interferences from organic or inorganic particles during PFGE migration or TEM observations (Colombet et al., 2007). However, during preparation of the grids for ultracentrifugation, the tails of phages may be dislocated from the capsid, resulting in an underestimation of tailed phages. In addition, positive staining may not be an optimal procedure for detecting fine structures such as the small-tailed Podoviridae (Proctor, 1997). Finally, in addition to the above drawbacks of PFGE and

Please cite this article as: Colombet, J., et al., Genotypic, size and morphological diversity of virioplankton in a deep oligomesotrophic freshwater lake (Lac Pavin, France), J. Environ. Sci. (2016), http://dx.doi.org/10.1016/j.jes.2016.05.016

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Fig. 3 – Dendogram based on the similarity matrix generated from PFGE fingerprint banding patterns at Epilimnion (Epi) and Metalimnion (Meta). Hypolimnion (Hypo) and Oxycline (Oxy) from April to December 2005. PFGE: pulsed field gel electrophoresis.

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TEM methods, preparation of viral concentrates can introduce a bias by removing large-sized viruses during prefiltration (greater than 0.2 μm) of natural samples (Auguet et al., 2006; Brum and Steward, 2010; Paul et al., 1991).

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3.2. Viral diversity and relationships with microbial communities

447

3.2.1. General morphology

448

According to general morphological traits, virioplankton in Lake Pavin appeared to be dominated by untailed viruses (from 54% to 68%), followed by Siphoviridae (from 27% to 40%).

443 444

449 450

The proportion of untailed viruses fell in the range of those previously reported in freshwater lakes (Colombet et al., 2006; Liu et al., 2006), although higher or lower proportions have been reported respectively by Auguet et al. (2006) in estuarine waters and Zhong et al. (2014) in Lake Annecy and Bourget. Interestingly, the same proportion of untailed viruses was recorded in Lake Pavin by Roux et al. (2012) using a metagenomic approach. These authors suggested that these untailed viruses were affiliated for the most part to Microviridae, Circoviridae and Nanoviridae. The dominance of Siphoviridae among tailed viruses (88% of total tailed

Please cite this article as: Colombet, J., et al., Genotypic, size and morphological diversity of virioplankton in a deep oligomesotrophic freshwater lake (Lac Pavin, France), J. Environ. Sci. (2016), http://dx.doi.org/10.1016/j.jes.2016.05.016

451 452 453 454 455 456 457 458 459 460 461

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Table 2 – Significant Pearson correlation coefficients between viral descriptors and environmental parameters.

t2:3 t2:2

Physical environment

Biological environment

Activities

t2:5 t2:4

Viral diversity

t2:6 t2:7 t2:8 t2:9 t2:10 t2:11 t2:12 t2:13 t2:14 t2:15 t2:16 t2:17 t2:18 t2:19 t2:20 t2:21 t2:22 t2:23 t2:24 t2:25 t2:26 t2:27 t2:28 t2:29 t2:30 t2:31 t2:32 t2:33 t2:34 t2:35 t2:36 t2:37 t2:38

Capsid size >100 nm 80–100 nm 60–80 nm 30–60 nm <30 nm

Genome size <15 kb 15–30 kb 30–45 kb 45–60 kb 60–75 kb 75–90 kb 90–105 kb 105–120 kb 120–135 kb 135–150 kb 150–165 kb 165–180 kb 180–195 kb 195–210 kb 210–225 kb 225–240 kb 240–255 kb 255–290 kb >290 kb

t2:39 t2:40 t2:43 t2:42 t2:41

The significance of correlations between viral descriptors and environmental parameters was tested by applying p-value, and the correlations are significant when ⁎p < 0.01 and highly significant when ⁎⁎p < 0.001. FIC: frequency of lytically infected cells; FLC: frequency of lysogenically infected cells.

Bacteria

Picocyanobacteria

Picoeukaryote

Crysidalis

0.558⁎⁎

0.647⁎⁎ 0.627⁎⁎

−0.67** −0.73** −0.75**

0.52** 0.542** 0.713** 0.355*

0.55⁎ 0.629⁎⁎

−0.5⁎ −0.82⁎⁎

0.552⁎⁎ 0.719⁎⁎ 0.595⁎⁎ 0.631⁎⁎

0.489* 0.603⁎⁎ 0.629⁎⁎

0.582⁎⁎

−0.75⁎⁎

0.453⁎ 0.628⁎⁎ 0.688⁎⁎ 0.655⁎⁎ 0.692⁎⁎ 0.622⁎⁎ 0.699⁎⁎ 0.663⁎⁎ 0.672⁎⁎ 0.606⁎⁎ 0.655⁎⁎ 0.631⁎⁎ 0.57⁎⁎ 0.591⁎⁎ 0.603⁎⁎ 0.667⁎⁎ 0.482⁎ 0.703⁎⁎

0.372⁎ 0.44⁎ 0.55⁎⁎ 0.48⁎

0.775⁎⁎ 0.57⁎ 0.6⁎ 0.59⁎ 0.53⁎ 0.52⁎

−0.67⁎⁎ −0.7⁎⁎ −0.72⁎⁎ −0.75⁎⁎ −0.71⁎⁎ −0.64⁎⁎ −0.67⁎⁎ −0.53⁎

C

P

T

E

D

0.571⁎⁎

0.557⁎⁎

0.45⁎

0.403⁎ 0.61⁎⁎ 0.571⁎⁎ 0.654⁎⁎ 0.64⁎⁎ 0.631⁎⁎ 0.568⁎⁎ 0.586⁎⁎ 0.48⁎ 0.48⁎

0.431⁎

R O

0.753⁎⁎

FLC

−0.55⁎ −0.61⁎⁎ −0.6⁎ −0.57⁎ −0.56⁎ −0.52⁎ −0.57⁎ −0.61⁎⁎

0.593⁎⁎ 0.642⁎⁎ 0.51⁎ 0.567⁎⁎ 0.52⁎ 0.53⁎ 0.51⁎ 0.51⁎

0.45⁎

0.466⁎

0.53⁎⁎

465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482

C

464

viruses) was in agreement with the study by Auguet et al. (2006) but was not found in other studies (Ackermann, 2003; Wommack et al., 1992; Zhong et al., 2014). Temporal variations in the abundances of untailed viruses and of Siphoviridae, Podoviridae, and Myoviridae were weak, suggesting a seasonal stability in viral community composition. However, the highest proportions of Myoviridae and Siphoviridae were recorded in autumn, and these morphotypes were correlated with picocyanobacteria and with Crysidalis species. This is in agreement with the data from previous studies showing that almost all viruses infecting phytoplankton, primarily cyanobacteria, were Myoviridae or Siphoviridae (Lu et al., 2001; Mann, 2003; Suttle and Chan, 1993; Waterbury and Valois, 1993; Wilson et al., 1993; Yoshida et al., 2006). Another interesting correlation was the one between untailed viruses and bacteria, which apparently contrasts with the fact that bacteriophages generally are considered to be tailed particles. A significant tail loss during sample preparation could explain this observation, suggesting that the tails of bacteriophages could be more fragile than those of algal viruses. Hence, the majority of untailed viruses in our samples could be bacteriophages. Spatial

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463 Q6

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462

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E

Morphological families Myoviridae Siphoviridae Podoviridae Untailed

Grazing

−0.5*

F

0.759⁎⁎ 0.527⁎⁎

FIC

O

Temp.

variations showed contradictory results, with the lowest proportion of Myoviridae and Siphoviridae recorded in the surface waters (epi-, metalimnion), and the lowest proportion of untailed viruses in deep layers (hypolimnion, oxycline), in which bacteria dominate. Direct or indirect (through infected cells) sedimentation can be evoked, with Siphoviridae and Myoviridae probably presenting a higher sedimentation rate compared to the untailed viruses.

483

3.2.2. Capsid size

491

Based on the assumptions (1) that typical pelagic phages in temperate aquatic systems lack pleiomorphism, and (2) that differences in the capsid size reflect differences in viral community composition, the results obtained during the present study showed that virioplankton were dominated (55% to 78% of total abundance) by viruses with capsid size between 30 nm and 60 nm. The dominance of VLPs with capsid size in this range has been previously recorded in marine and freshwater environments (Alonso et al., 2001; Auguet et al., 2006; Hennes and Simon, 1995; Liu et al., 2006; Stopar et al., 2004; Weinbauer, 2004). Exceptions are results

492

Please cite this article as: Colombet, J., et al., Genotypic, size and morphological diversity of virioplankton in a deep oligomesotrophic freshwater lake (Lac Pavin, France), J. Environ. Sci. (2016), http://dx.doi.org/10.1016/j.jes.2016.05.016

484 485 486 487 488 489 490

493 494 495 496 497 498 499 500 501 502

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516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548

552 553 554 555 556 557 558 559 560 561

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The results recorded showed that VGC was dominated by five size classes (25–40, 55–65, 80–100, 155–180 and 250–292 kb) common to all sampled depths, the two genome size classes in the range 25–65 kb being the most dominant populations. Distribution in several classes of VGC in freshwater viral communities was also demonstrated by Auguet et al. (2006), Filippini and Middelboe (2007) and Tijdens et al. (2008). Auguet et al. (2006) and Tijdens et al. (2008) reported five dominant molecular size groups (12–17, 24–29, 30–48, 50–70, >90 kb and 44, 49, 74, 78 and 163 kb respectively), while Filippini and Middelboe (2007) reported two dominant size classes (30–41,

508

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3.2.3. Genome size

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53–64 kb), with the majority of viruses exhibiting genome size <65 kb in both cases. Our results suggest that the five dominant classes in Lake Pavin were permanent members of the mixolimnic layer of the lake. The results of the similarity analysis confirmed a certain stability in the VGC, with a similarity index > 0.50 between all samples, except in July and May in the epilimnion, but also showed some variations, especially seasonal, which were much more pronounced in the epi- and metalimnion than in the hypolimnion and oxycline. In Lake Pavin, we found a total of 34 different genomic bands (i.e., all sampling depths and dates combined), ranging in size from 15 kb up to 292 kb. In marine waters, between 7 and 35 different bands can be distinguished (Weinbauer, 2004). Herein, we have recorded 6 to 18 bands per lane (mean, 12 bands per lane). Filippini and Middelboe (2007) reported 10 to 20 clearly visible bands per lane in marine coastal waters, estuarine waters and in freshwater lakes in Denmark, with the highest values in the eutrophic Lake Frederiksborg Slotssø. Auguet et al. (2006) reported only 4 ± 3 bands per lane on average, along the salinity gradient of the Charente Estuary, France, and Tijdens et al. (2008) recorded 6 to 10 different PFGE bands per sample in the shallow eutrophic Loosdrecht lake. Spatio-temporal variability in VGC was obvious from the appearance of new bands in summer and/or in autumn in the region 15–60 kb for all sampled depths, and in the regions 100–115 kb and 130–160 kb in the epi- and metalimnion. With the assumption that bands < 60 kb represented bacteriophages (Ackermann et al., 1992), occurrence of new bands in the 15–60 kb region could reflect seasonal changes in bacterial community composition (BCC). Riemann and Middelboe (2002) in coastal marine waters and Tijdens et al. (2008) in a eutrophic lake did not reported significant covariations of these two parameters. More interesting is the appearance of new bands in the 100–115 kb and 130–160 kb regions in summer–autumn and in summer respectively, concomitant with peaks in the abundances of autotrophic species, primarily picocyanobacteria and Crysidalis species (Colombet et al., 2009). It appears that variations in VGC could be linked to those in microbial communities, as additionally supported from densitometric analyses of PFGE bands. Indeed, the highest mean genome sizes were recorded during summer in the surface epi- (55 ± 9 kb) and metalimnion (52 ± 5 kb) due to peaks in viruses with genome sizes > 60 kb, which were concomitant with peaks in the abundances of autotrophic species (Colombet et al., 2009). Moreover, almost all genome size classes (up to > 290 kb) were correlated with Crysidalis species, but only the sizes classes within the 15–105 and 15– 75 kb genomic regions were correlated with picocyanobacteria and heterotrophic bacteria, respectively. This indicates that not only the phenotype size classes but also the genome size classes within viral communities increased with the increasing size and biological organization of their potential hosts, with viral genome size populations vs. potential hosts suggested as follows: >290 kb vs. eukaryotes, 15–105 kb vs. picocyanobacteria, and 15–75 kb vs. heterotrophic procaryotes. Similar indications were suggested by Sandaa and Larsen (2006) in marine waters and Zhong et al. (2014) in peri-alpine lakes, agreeing well with the data from the literature showing that the viral genome sizes increased

D

550

505

T

549

reported by Mathias et al. (1995) in the Kühwörte backwater system of the Danube River and by Brum and Steward (2010) in the hypersaline Mono Lake where viruses, with capsid size > 60 nm dominating. Our mean capsid diameter was at (49 ± 4) nm, and fell in the range (51 ± 18) of results reported by Auguet et al. (2006), but was slightly lower than those (62– 68 nm) reported by Demuth et al. (1993) in freshwater environments. In various environments, some studies have shown that the diversity of viruses estimated based on the distribution frequency of the capsid size can vary with time and space, whereas others have reported no significant variations (Weinbauer, 2004). Herein, low variability (47– 50 nm) of mean capsid size suggested spatio-temporal stability in the viral community. A few interesting variations were recorded, e.g., those in viruses with capsid size > 80 nm, which presented peak abundance in autumn. Brussaard (2004) and Dunigan et al. (2006) have reported that algal viruses presented higher capsid diameters (> 100 nm) than bacteriophages. Thus it is not surprising to find a high proportion of viruses > 80 nm in autumn, concomitant with or following the peak in phytoplanktonic species and characterized by the lowest ratio between total abundances of heterotrophic and photoautotrophic species (from 336 in spring to 169 in summer and 156 in autumn Colombet et al., 2009). This was reinforced by the positive correlation between viruses with capsid size > 80 nm and Crysidalis species. Thus we can hypothesize than viruses with capsid sizes > 80 nm could be, in majority, algal viruses. Accordingly, an investigation of intracellular viruses in a marine environment found no viruses > 110 nm within bacteria (Weinbauer and Peduzzi, 1994). In contrast, bacterial abundance was exclusively correlated with small capsid size viruses (30–60 nm) and picocyanobacteria with both small and intermediate capsid size viruses (30–80 nm). These results corroborate the findings by Weinbauer and Peduzzi (1994) and by Hennes and Suttle (1995) on the predominance of viruses with small capsid size between 30 and 60 nm within bacterioplankton, while picocyanobacteria, which are larger in size than heterotrophic bacteria, harbor larger size (40– 90 nm) viruses (Lu et al., 2001, Yoshida et al., 2006). Spatial variations showed contradictory results, with the lowest proportion of small viruses (30–60 nm) recorded in the oxycline, whereas this environment appeared to be dominated by heterotrophic bacteria (Colombet et al., 2009). Once again, this could be explained by the sedimentation of large viruses or of infected hosts from the surface waters (Danovaro et al., 2001).

504

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Please cite this article as: Colombet, J., et al., Genotypic, size and morphological diversity of virioplankton in a deep oligomesotrophic freshwater lake (Lac Pavin, France), J. Environ. Sci. (2016), http://dx.doi.org/10.1016/j.jes.2016.05.016

562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621

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628 629 630 631 632 633

3.3. Effects of potential grazing and viral activities on viral diversity

665

3.4. Effects of physico-chemical environment on viral diversity

666

Finally, spatio-temporal succession also allowed the monitoring of changes in viral community composition with changes in the physico-chemical environment (Colombet et al., 2009). Jiang et al. (2004) showed that the viral genomic composition changed with oxygen level from oxic to anoxic conditions. Weinbauer (2004) suggested that certain physico-chemical parameters may define the niches of phages and thus influence viral diversity. Wommack et al. (1999b) and Riemann and Middelboe (2002) also suggested that the structure of viral communities may be influenced by physico-chemical changes. In this study we did not find strong links between viral genomic composition or viral morphology with changes in chlorophyll a content or oxygen

642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663

667 668 669 670 671 672 673 674 675 676 677

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641

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637

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636

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635

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634

678 679 680 681 682 683 684 685 686 687 688 689 690 691

4. Conclusions

693 692

In the present study, we have shown that the main viruses in Lake Pavin had a capsid size between 30 and 60 nm, and belonged to the family of Siphoviridae or were untailed, with a genome size in one of two major size classes: 25–40 and 55– 65 kb. Although the composition of the viral community based on these criteria showed a tendency to be relatively stable, interesting spatio-temporal variations and empirical correlations were recorded. The composition of the viral community was more strongly linked to the microbial community structure than to activities (i.e., lysis, lysogeny, potential grazing) or to the chemical environment (i.e., oxygen, chlorophyll). Empirical relationships suggested the existence of three different viral communities based on the sizes of phenotypes and genotypes: (1) viruses with large capsid (> 80 nm) and genome sizes (up to > 290 kb) were related to eukaryotes, (2) viruses with intermediate capsid (30–80 nm) and genome sizes (< 105 kb) appeared to be linked to picocyanobacteria, and (3) the smallest viruses with capsid size < 60 nm and genome size < 75 kb probably were specific to heterotrophic procaryotes. The dynamics of Myoviridae and Siphoviridae showed a tendency to be forced by autotrophic microorganisms, whereas the dynamics of untailed viruses were linked to bacteria. Finally, temperature appeared as a strong forcing factor in the dynamics of viral diversity, possibly as the result of indirect interactions between temperature and the viral host availability. Overall, the present study supports a previous finding (Colombet et al., 2006) that the host availability is crucial to viral diversity, diversification, seasonal abundance, and activities.

694

Uncited references

Q7 724 723

Moineau et al., 1995 Weinbauer et al., 2003

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Acknowledgments

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664

Some authors have suggested that grazing activity or even lytic or lysogenic activity could affect viral community composition (Weinbauer, 2004). Therefore, we studied here the potential relationships between these different activities (Colombet and Sime-Ngando, 2012) and viral diversity. No link between lysogeny level and viral diversity was found. Except for a significant correlation between FIC and Siphoviridae, viruses with genome size between 120 and 135 kb and between 255 and 290 kb, no clear pattern was found with the lytic activity either, suggesting that viral activity was not a factor driving spatio-temporal changes in viral community composition. Parada et al. (2008) have shown that viral richness changed linked to viral lytic infection on a time scale of hours to days. The month to month time scale employed could have masked the detection of fine interactions between lytic and viral diversity. With regard to the grazing activity, only untailed viruses and viruses with genome size between 135 and 150 kb were linked to potential grazing. In fact, very little is known about the potential role of flagellate grazing on viral diversity (Weinbauer, 2004). A synergistic interaction between grazing by HNF and the proportion of untailed viruses and viruses with genome size between 135 and 155 kb was probable. Grazing can influence bacterial growth and the community structure of these preys (Weinbauer et al., 2007). Thus a positive change for the hosts of certain untailed phages or certain viruses with genome size between 135 and 155 kb could induce production of these phages and explain these correlations. Nevertheless, no direct link between potential grazing and viral community composition was found. Thus, the main factor driving the composition of the dominant viral community at the seasonal scale was microbial community composition rather than viral or grazing activities.

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concentration. However, an interesting result was the relation found between the different viral parameters and temperature. Indeed, except for viruses with capsid size >60 nm, Podoviridae and viruses with genome size <15 kb, all the other classes of viruses were positively correlated to temperature. In addition, the highest viral genomic diversity (numbers of different bands per lane) was found in summer and autumn at the highest temperatures. Thus some viruses could be sensitive to water temperature. A possible explanation is the covariance between temperature and the microbial community composition. Indeed, it is well known that a rise in water temperature affects some microbial species and thus changes the microbial community composition, which could change the viral community composition.

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from bacteriophages (< 60 kb (Ackermann et al., 1992)) to cyanophages (40.9–252 kb (Pope et al., 2007; Liu et al., 2007; Yoshida et al., 2006)), to eukaryotic algal viruses such as phycodnaviruses (100–560 kb (Brussaard, 2004; Dunigan et al., 2006)). The approach used in this study thus provides new and original information on the link between viral diversity assessed based on the genome size and the composition and structure of microbial communities, although a single PFGE band could not be firmly linked to a given host population.

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JC was supported by a PhD Fellowship from the Grand Duché 729 du Luxembourg (Ministry of Culture, High School, and Research). 730 Q8

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The study was partly supported by the French National Program ACI/FNS “ECCO” (VIRULAC research grant awarded to TSN, coordinator), and by the French ANR Program “Biodiversité” (AQUAPHAGE research grant to TSN, PI).

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