ARTICLE IN PRESS. Deep-Sea Research I

Transcription

1 Deep-Sea Research I 56 (09) Contents lists available at ScienceDirect Deep-Sea Research I journal homepage: Seasonal and depth-related dynamics of prokaryotes and viruses in surface and deep waters of the northwestern Mediterranean Sea Christian Winter a,b,, Marie-Emmanuelle Kerros a,b, Markus G. Weinbauer a,b a Microbial Ecology and Biogeochemistry Group, CNRS, Laboratoire d Océanographie de Villefranche, Villefranche-sur-Mer Cedex, France b Université Pierre et Marie Curie-Paris 6, Laboratoire d Océanographie de Villefranche, BP 28, Villefranche-sur-Mer Cedex, France article info Article history: Received 3 February 09 Received in revised form 1 July 09 Accepted 15 July 09 Available online 22 July 09 Keywords: Bacteriophage Virus Prokaryote Marine Deep sea Flow cytometry abstract The study site located in the northwestern Mediterranean Sea was visited nine times in to collect water samples from the epi- (5 m), meso- (0, 600 m), and bathypelagic (1000, 00 m) zone. Total abundance of prokaryotes and viruses was determined by flow cytometry (FCM). Prokaryotic abundance in the epi-, meso-, and bathypelagic varied between 0.9 and , 0.6 and , and 0.3 and ml 1, respectively. Variation of viral abundance in the epi-, meso-, and bathypelagic was between 1.2 and , 0.5 and , and 0.4 and ml 1, respectively. The fraction of low (LNA) and high (HNA) nucleic acid prokaryotes averaged 42.9% and 57.1% throughout the water column and did not differ between depth layers. Throughout the water column the fraction of low, medium, and high fluorescent viruses (Vir-LF, Vir-MF, Vir-HF) averaged 66.3%, 30.2%, and 3.5%. Vir-LF and Vir-MF did not differ between depth layers; however, Vir-HF showed a preference for surface waters. The fraction of LNA cells decreased in the epi- and increased in the bathypelagic with decreasing stratification. The fraction of Vir-LF viruses increased in the epipelagic and decreased in the bathypelagic with increasing prokaryotic abundance. Also, the relationship between viral abundance and the bacterial community was different in surface and deep waters. The data suggest that different mechanisms of interaction between viruses and their prokaryotic hosts prevail at the surface and in deep waters. & 09 Elsevier Ltd. All rights reserved. 1. Introduction Prior to the introduction of flow cytometry (FCM) into microbial ecology, the determination of prokaryotic (e.g., Hobbie et al., 1977; Porter and Feig, 1980) and viral(hennes and Suttle, 1995; Noble and Fuhrman, 1998; Weinbauer and Suttle, 1997) abundance in aquatic habitats was laborintensive and time consuming. Eventually, FCM made fast and reliable measurements of prokaryotic (Marie et al., 1996) and viral (Marie et al., 1999a)abundancepossible.Inaddition to bulk numbers of prokaryotes and viruses, FCM can also be Corresponding author at: University of Vienna, Department of Marine Biology, Althanstrasse 14, 1090 Vienna, Austria. Tel.: ; fax: address: cwjournals@mac.com (C. Winter). used to obtain a first, albeit crude, distinction of prokaryotic and viral groups based on signal strength. The capability to obtain fast and accurate measurements on single cells and more recently also on virus particles is arguably the most valuable addition of FCM to microbial ecology. Soon it was noted that the intensity of the fluorescence signal of prokaryotic cells in FCM analysis due to staining with nucleic acid dyes is proportional to their DNA content (Marie et al., 1996). Based on differences in the strength of the fluorescence signal and consequently nucleic acid content at least two populations can be distinguished in the cytograms, and they have been labeled as high (HNA) and low (LNA) nucleic acid cells. Initially, studies on marine microbial communities indicated that HNA cells represent the metabolically active fraction and are responsible for most of the activity of marine microbial communities (Gasol and del Giorgio, 00; /$ - see front matter & 09 Elsevier Ltd. All rights reserved. doi: /j.dsr

2 C. Winter et al. / Deep-Sea Research I 56 (09) Gasol et al., 1999; Lebaron et al., 01). However, more recent studies established that the LNA fraction is metabolically active as well and constitutes an integral part of marine microbial communities (Jochem et al., 04; Longnecker et al., 05; Scharek and Latasa, 07; Zubkov et al., 01). Also, it has been shown that the strength of the fluorescence signal cannot be used as a reliable estimate of metabolic activity (Morán et al., 07). Another important question in this context is whether or not HNA and LNA cells are phylogenetically distinct assemblages. Lebaron et al. (02) demonstrated that, based on batch-culture experiments with bacterial isolates, the distinction between HNA and LNA cells is not necessarily due to different taxa but instead can be based on physiological differences between cells reflecting different growth states. Also, Longnecker et al. (05) showed that there is no consistent phylogenetic difference between HNA and LNA cells. FCM can also be used to distinguish a number of different virus populations based on the fluorescence signal due to staining with nucleic acid dyes such as SYBR Green I. Between 2 and 3 different populations of viruses are commonly observed in marine environments; however, the intensity of the fluorescence signal does not correlate with genome size (Brussaard et al., 00). Nevertheless, it is evident that the distinction between the different virus populations is based on phylogenetic characteristics, that is, different virus types, as free viruses are not metabolically active. Generally, the fraction with the lowest fluorescence intensity constitutes the majority of viruses in marine systems and is assumed to be mostly composed of viruses infecting prokaryotes, whereas viruses with a stronger fluorescence signal supposedly infect phytoplankton or other eukaryotic organisms (Baudoux et al., 07; Li and Dickie, 01; Payet and Suttle, 08). In the present study we used FCM to determine prokaryotic and viral abundance in surface and deep waters at an offshore station in the northwestern Mediterranean Sea in monthly to bi-monthly intervals during an annual cycle. The first objective of this study was to relate changes in prokaryotic and viral abundance to physicochemical changes in the water column due to seasonality. The second objective was to determine if particular fractions of prokaryotes and viruses show a preference for either surface or deeper waters. The third objective was to investigate whether or not different prokaryotic and viral populations as distinguished by FCM analysis respond differently to environmental changes depending on sampling depth. The fourth objective was to use previously published data from a parallel study (Winter et al., 09) toinvestigatetherelationshipsbetweenchangesin bacterial community composition and richness and the dynamics in viral abundance reported in the present study that could have implications for understanding the influence of viruses on bacterial communities in different depth layers at the study site. 2. Methodology 2.1. Study site and sampling The study was conducted at the Dynamique des Flux de Matière en Mediterranée (DYFAMED) time series station, a former JGOFS station. DYFAMED is situated in the center of the Ligurian Basin of the Mediterranean Sea ( N, E) in m of water. The central part of the Ligurian Sea is composed of a homogenous water body largely isolated from direct coastal inputs by the Liguro-Provenc-al current and considered to be only marginally influenced by lateral advection (Lévy et al., 1998). The site was visited nine times with R.V. Tethys II in (dates: 2 July 05, 27 September 05, 25 October 05, 19 December 05, 7 February 06, 7 March 06, 2 April 06, 6 May 06, 30 June 06). Sampling was performed using 12 L Niskin bottles mounted on a carousel sampler (SBE 32; Sea-Bird Electronics) equipped with CTD sensors (SBE 911; Sea- Bird Electronics). Water samples were retrieved from 5, 600, and 00 m in July 05. During the next eight visits, between September 05 and June 06, sampling covered 5, 0, 600, 1000, and 00 m depth Enumeration of prokaryotes and viruses Samples for the enumeration of prokaryotes and viruses (2 ml) were fixed with glutaraldehyde (0.5% final concentration) immediately after sample retrieval and flash frozen in liquid nitrogen aboard ship. The samples were maintained at 80 1C until prokaryotes and viruses were enumerated on a FACSCalibur (BD Biosciences) flow cytometer using the nucleic acid stain SYBR Green I (Invitrogen-Molecular Probes) as previously described (Brussaard, 04; Marie et al., 1999b). Data analysis was performed using BD Cell Quest Pro software (version 4.0.2; BD Biosciences). In all cases, the variation of duplicate measurements was well within 10% of the average. Populations of prokaryotes and viruses differing in fluorescence intensity were distinguished on plots of side scatter versus green fluorescence (530 nm wavelength, fluorescence channel 1 of the instrument; Fig. 1). Autotrophs were not treated separately but were included in prokaryotic abundance. Prokaryotic and viral abundance was integrated over depth to calculate the total number of prokaryotes and viruses per square meter surface area of the epi- (5 0 m), meso- ( m), and bathypelagic (1000 m) zone. Integrated abundance was calculated as the sum of the areas of the trapezoids defined by depth and abundance multiplied by 1m Statistical analysis The software package Mathematica (Wolfram Research; version 5.2.2) was used for statistical analysis. Analysis of variance (ANOVA) and Tukey s post-hoc test based on the Studentized range distribution of average values was used to test for significant differences between depth layers. Student s t-tests were used to test for significant differences between the means of two populations based on the two-tailed t- distribution. Spearman rank correlation coefficients were calculated to test relationships between the parameters. Only statistically significant (pr0.05) and relevant ( 0.54r.5) correlation coefficients have been considered for further

3 1974 C. Winter et al. / Deep-Sea Research I 56 (09) Fluorescence (530 nm wavelength) LNA HNA Fluorescence (530 nm wavelength) Vir-HF Vir-MF Vir-LF Side scatter Side scatter 10 4 Fig. 1. Flow cytometric discrimination of prokaryotic and viral populations based on fluorescence intensity. Populations of high and low nucleic acid prokaryotes (A: HNA, LNA) and high, medium, and low fluorescent viruses (B: Vir-HF, Vir-MF, Vir-LF) were identified on plots of side scatter versus green fluorescence. The data shown here are from 0 m depth sampled on 19 December 05. interpretation of the results. Linear least-squares regression analysis was used to quantify the relationships between selected parameters. Key parameters were used to perform a principle component analysis (PCA) for the entire water column. Data were log-transformed, and only factors based on the Kaiser criterion (i.e. all factors with an eigenvalue 41) were retained. The coefficient of variation of selected parameters was calculated based on 100,000 bootstrap replicates in order to check for stochastic influences on the data. Mantel tests (Mantel, 1967) were used to link changes in bacterial community composition as reported by Winter et al. (09) to changes in viral abundance and the fraction of HNA and LNA cells. For this purpose, the denaturing gradient gel electrophoresis data of PCR-amplified fragments of the 16S rrna gene were converted into dissimilarity matrices by calculating Jaccard s dissimilarity coefficient. Dissimilarity matrices from viral abundance data were based on the Euclidean distance. The Mantel statistic (r m )wascalculatedas the Spearman rank correlation coefficient between the upper non-diagonal values of the dissimilarity matrices being compared. Probability values for the null hypothesis of the Mantel tests were calculated using permutation tests (Legendre and Legendre, 1998) based on 100 random permutations, sufficient to report p-values accurately to two decimal places. The results of the statistical tests were assumed to be significant at p-values r Results 3.1. Temporal and depth-related variability of parameters Vertical structure of the water column During the stratified period between July and October 05 and May and June 06 the mixed layer depth varied between 30 and m. Water column stratification started to deteriorate in December 05 and was building up in April 06. During the non-stratified period in February March 06 the water column was characterized by a uniform salinity of 38.5, temperature of 13 1C, and a potential density (s T ) of 29.1 kg m 3 throughout the water column. The build-up of a thermal stratification at the study site is indicated by a decrease in s T, particularly in the epipelagic zone. More details on the physicochemical characteristics of the water column can be found elsewhere (Winter et al., 09) Prokaryotic and viral abundance Prokaryotic abundance varied between 0.9 and ml 1 (17 ), 0.6 and ml 1 (3 ), and 0.3 and ml 1 (4 ) in the epi-, meso-, and bathypelagic, respectively (Table 1, Fig. 2). Variation of viral abundance was between 1.2 and ml 1 (48 ), 0.5 and ml 1 (7 ), and 0.4 and ml 1 (3 ) in the epi-, meso-, and bathypelagic, respectively (Table 1, Fig. 3). Prokaryotic and viral abundance were significantly higher in the epi- compared to the meso- and bathypelagic (ANOVA: prokaryotes: F- ratio ¼ 30.06, po0.0001; viruses: F-ratio ¼ 12., p ¼ ). The virus-to-prokaryote ratio (VPR) averaged 22.2, 12.8, and 13.9 in the epi-, meso-, and bathypelagic, respectively (Table 1) and was significantly higher in the epi- compared to the meso- and bathypelagic zone (ANOVA: F-ratio ¼ 5.29, p ¼ ) Prokaryotic and viral populations distinguished by FCM The fraction of LNA and HNA cells averaged 42.9% and 57.1% throughout the water column. LNA and HNA cells

4 C. Winter et al. / Deep-Sea Research I 56 (09) Table 1 Parameters measured in the three depth layers (epi-, meso-, and bathypelagial). Parameter Avg SD Minimum Maximum N Epi. Meso. Bathy. Epi. Meso. Bathy. Epi. Meso. Bathy. Epi. Meso. Bathy. Epi. Meso. Bathy. Prokaryotes Viruses VPR LNA HNA Vir-LF Vir-MF Vir-HF Prok. integrated Vir. integrated The average (Avg), standard deviation (SD), minimum, maximum, and number of samples (N) are given. Prokaryotes (N 10 5 ml 1 ), viruses (N 10 6 ml 1 ), the virus-to-prokaryote ratio (VPR), the fractions of low and high nucleic acid prokaryotes (LNA, HNA) as well as low, medium and high fluorescent viruses (Vir-LF, Vir-MF, Vir-HF) as percentage of total abundance, and depth-integrated prokaryotic (N m 2 ) and viral (N m 2 ) abundance. Prokaryotic abundance (N 10 5 ml -1 ) Jul 5 m depth 0 m depth 1000 m depth Jan Aug Sep Oct Nov Dec Jun Feb Mar Apr May Jul Time of year (months) 600 m depth 00 m depth LNA HNA Jan Aug Sep Oct Nov Dec Jun Feb Mar Apr May Fig. 2. Prokaryotic abundance. The time course of the abundance of low and high nucleic acid prokaryotes (LNA, HNA) as well as total prokaryotic abundance is shown for each sampling depth. did not differ significantly between depth layers (for both ANOVA: F-ratio ¼ 0.86, p ¼ ) and largest variation was found in the epipelagic zone (Table 1, Fig. 2). On average LNA was significantly smaller than HNA throughout the water column and in the meso- and bathypelagic zone (t-test: in all cases po0.0001) but did not differ from HNA in the epipelagic (t-test: p ¼ ). Throughout the water column the fraction of low, medium, and high fluorescent viruses (Vir-LF, Vir-MF, Vir- HF) averaged 66.3%, 30.2%, and 3.5%. Vir-LF and Vir-MF did

5 1976 C. Winter et al. / Deep-Sea Research I 56 (09) m depth Vir-LF Vir-MF Vir-HF Viral abundance (N 10 6 ml -1 ) m depth m depth Jul 0 m depth Jan Aug Sep Oct Nov Dec Jun Feb Mar Apr May Jul Time of year (months) 600 m depth Jan Aug Sep Oct Nov Dec Jun Feb Mar Apr May Fig. 3. Viral abundance. The time course of the abundance of low, medium, and high fluorescent viruses (Vir-LF, Vir-MF, Vir-HF) as well as total viral abundance is shown for each sampling depth. not differ significantly between depth layers (ANOVA: Vir- LF: F-ratio ¼ 0.23, p ¼ ; Vir-MF: F-ratio ¼ 0.14, p ¼ ), and largest variation was found in the epipelagic zone (Table 1, Fig. 3). Vir-HF was significantly higher in the epi- compared to the mesopelagic (ANOVA: F-ratio ¼ 4.68, p ¼ ). On average, the three populations of viruses differed significantly between each other in the entire water column and in the three depth layers (t-test: in all cases po0.0001) Depth-integrated prokaryotic and viral abundance Depth-integrated prokaryotic and viral abundance did not differ significantly between depth layers (ANOVA: prokaryotes: F-ratio ¼ 0.18, p ¼ 0.82; viruses: F-ratio ¼ 1.16, p ¼ ). Integrated prokaryotic abundance varied between 1.6 and m 2 (11 ), 4.4 and m 2 (2 ), and 4.9 and m 2 (3 ) in the epi-, meso-, and bathypelagic, respectively (Table 1, Fig. 4A). Integrated viral abundance ranged from 2.3 to m 2 (29 ), m 2 (3 ), and m 2 (3 ) in the epi-, meso-, and bathypelagic, respectively (Table 1, Fig. 4B). In the entire water column depth-integrated prokaryotic and viral abundance varied between 12.4 and m 2 (3 ) and 14.1 and m 2 (5 ; Fig. 4). The coefficient of variation of depthintegrated prokaryotic abundance was 62.3% (standard deviation ¼ 17.5%), 22.1% (std. dev. ¼ 7.2%), and 36.7% (std. dev. ¼ 7.1%) in the epi-, meso-, and bathypelagic, respectively. The coefficient of variation of depth-integrated viral abundance was 103.8% (std. dev. ¼ 25.5%), 39.7% (std. dev. ¼ 12.4%), and 30.4% (std. dev. ¼ 9.4%) in the epi-, meso-, and bathypelagic respectively. Total depth-integrated prokaryotic abundance decreased from September to December and remained virtually unchanged from December to February (Fig. 4A). However, from December to February, depth-integrated prokaryotic abundance dropped in the epipelagic while it increased substantially in the bathypelagic zone (Fig. 4A). Similarly, total depth-integrated viral abundance decreased from September to December followed by an increase in the bathypelagic zone from December to February while in the epi- and mesopelagic zone depth-integrated viral abundance remained essentially unchanged (Fig. 4B). Although depth-integrated prokaryotic abundance increased again in all three depth layers during April June,

6 C. Winter et al. / Deep-Sea Research I 56 (09) Prokaryotes (N m -2 ) Viruses (N m -2 ) Jul Epipelagial Mesopelagial Bathypelagial Aug Sep Oct Nov Dec Jan Time of year (months) Feb Mar Apr May Fig. 4. Depth-integrated prokaryotic and viral abundance. The time course of the depth-integrated prokaryotic and viral abundance in the epi-, meso-, and bathypelagic as well as the entire water column is shown. Jun depth-integrated viral abundance only increased in the epipelagic zone, whereas it actually decreased in the bathypelagic (Fig. 4) Relationships between parameters Biological and physicochemical parameters In the entire water column, prokaryotic and viral abundance correlated positively with temperature and negatively with s T (Table 2). In the epi- and mesopelagic zone viral abundance correlated positively with temperature and negatively with s T (Tables 3 and 4). However, in the bathypelagic zone, prokaryotic abundance correlated positively with salinity, temperature, and s T (Table 5). In the epipelagic zone LNA correlated positively with temperature and negatively with s T (Table 3; the correlation coefficients of LNA and HNA with other parameters are identical but with opposite signs). Finally, in the bathypelagic zone LNA correlated positively with s T (Table 5) Prokaryotes and viruses Throughout the water column and in all three depth layers viral abundance correlated positively with prokaryotic abundance (Tables 2 5). VPR correlated positively with Vir-LF and negatively with Vir-MF in the entire water column (Table 2), the meso- (Table 4), and bathypelagic zone (Table 5) but not in the epipelagic (Table 3). Linear least-squares regression analysis revealed that Vir-LF increased with increasing prokaryotic abundance in the epipelagial and decreased in the bathypelagial (Fig. 5). However, Vir-MF decreased with increasing prokaryotic Table 2 Spearman rank correlation coefficients for the entire water column. Sal. Temp. s T Prok. Vir. VPR LNA HNA Vir-LF Vir-MF Prokaryotes Viruses VPR LNA o HNA o Vir-LF Vir-MF Vir-HF The Spearman rank correlation coefficients between parameters measured in this study are given for the entire water column. Relevant ( 0.54r.5) and statistically significant (pr0.05) correlation coefficients are in bold. Table 3 Spearman rank correlation coefficients for the epipelagic zone. Sal. Temp. s T Prok. Vir. VPR LNA HNA Vir-LF Vir-MF Prokaryotes Viruses VPR LNA HNA Vir-LF Vir-MF Vir-HF The Spearman rank correlation coefficients between parameters measured in this study are given for the epipelagic zone. Relevant ( 0.54r.5) and statistically significant (pr0.05) correlation coefficients are in bold.

7 1978 C. Winter et al. / Deep-Sea Research I 56 (09) Table 4 Spearman rank correlation coefficients for the mesopelagic zone. Sal. Temp. s T Prok. Vir. VPR LNA HNA Vir-LF Vir-MF Prokaryotes Viruses VPR LNA HNA Vir-LF Vir-MF Vir-HF The Spearman rank correlation coefficients between parameters measured in this study are given for the mesopelagic zone. Relevant ( 0.54r.5) and statistically significant (pr0.05) correlation coefficients are in bold. Table 5 Spearman rank correlation coefficients for the bathypelagic zone. Sal. Temp. s T Prok. Vir. VPR LNA HNA Vir-LF Vir-MF Prokaryotes Viruses VPR LNA HNA Vir-LF Vir-MF Vir-HF The Spearman rank correlation coefficients between parameters measured in this study are given for the bathypelagic zone. Relevant ( 0.54r.5) and statistically significant (pr0.05) correlation coefficients are in bold. abundance in the epipelagial and increased in the bathypelagial. No relationship between Vir-LF or Vir-MF and prokaryotic abundance was found in the mesopelagial (Fig. 5). A previous study (Winter et al., 09) conducted in parallel to the current one presented data on changes in bacterial community composition (different phylotypes detected) and richness (total number of phylotypes detected) as obtained by denaturing gradient gel electrophoresis of PCR-amplified fragments of the 16S rrna gene. Because the data of Winter et al. (09) were obtained from the same water samples as data presented in the current study we are able to test for relationships between changes in bacterial communities, changes in viral abundance, and changes in the fractions of HNA and LNA cells. In the bathypelagic zone bacterial richness correlated positively with viral abundance (r ¼ 0.57, p ¼ ) but not so in the epi- and mesopelagic (epipelagic: r ¼ 0.19, p ¼ ; mesopelagic: r ¼ 0.27, p ¼ ). Mantel tests indicated a significant and relevant relationship between seasonal changes in bacterial community composition and viral abundance in the epipelagic zone (r m ¼ 0.57, po0.05) but not in deeper waters (mesopelagic: r m ¼ 0., po0.05; bathypelagic: r m ¼ 0.05, p ¼ 0.52). Furthermore, in all three depth layers changes in the fractions of HNA and LNA cells were not linked to changes in bacterial community composition (epipelagic: r m ¼ 0.23, p ¼ 0.21; mesopelagic: r m ¼ 0.23, p ¼ 0.02; bathypelagic: r m ¼ 0.04, p ¼ 0.66) Principle component analysis Based on a Spearman rank correlation analysis, 10 key parameters were selected for the PCA. PCA revealed that there were three main components, together explaining 90.4% of the total variation in the data set (Table 6). In the main component explaining 47.8% of the variation, temperature and viral abundance were negatively correlated to s T. In the second component Vir-LF was negatively related to Vir-MF and Vir-HF, explaining 28.1% of the variation. The third component explained 14.5% of the variation in the data set where LNA was negatively related to HNA and positively to depth. 4. Discussion 4.1. Viruses infecting prokaryotes Viral infection is a stochastic process, depending among other parameters on the abundance of hosts (Murray and Jackson, 1992). Viruses as obligate parasites rely entirely on the metabolism of the host for viral replication. Thus, as host abundance or productivity decreases, the abundance of viruses infecting these hosts decreases as well. The strong correlations between prokaryotic and viral abundance throughout the water column and in all three depth layers (Tables 2 5) at the study site confirm the notion that the majority of viruses found in the ocean infect prokaryotes. Especially in deep

8 C. Winter et al. / Deep-Sea Research I 56 (09) Epipelagial 90 Mesopelagial 90 Bathypelagial Vir-LF (%) Prok. abundance (N 10 5 ml -1 ) Prok. abundance (N 10 5 ml -1 ) Prok. abundance (N 10 5 ml -1 ) Epipelagial Mesopelagial Bathypelagial Vir-MF (%) Prok. abundance (N 10 5 ml -1 ) Prok. abundance (N 10 5 ml -1 ) Prok. abundance (N 10 5 ml -1 ) Fig. 5. Linear least-squares regression analysis of prokaryotic abundance versus low fluorescent viruses (Vir-LF; A) and medium fluorescent viruses (Vir- MF; B) for the three depth layers. The dashed lines represent the linear least-squares regressions and the equations are: (A) epipelagial: y ¼ 1.3x+56.7 (r 2 ¼ 0.46, p ¼ ), bathypelagial: y ¼ 12.1x+74 (r 2 ¼ 0.54, p ¼ ); (B) epipelagial: y ¼ 1.2x+38.1 (r 2 ¼ 0.48, p ¼ ), bathypelagial: y ¼ 11.2x+23.2 (r 2 ¼ 0.53, p ¼ ). Table 6 Component matrix of the principal component analysis (PCA) for the entire water column at the study site. Parameter Component Depth Temperature s T Prokaryotes LNA HNA Viruses Vir-LF Vir-MF Vir-HF Variance (%) Cumulative (%) 90.4 The data set for PCA was reduced to 10 key parameters and three components were extracted. Correlations in the component matrix. are in bold. waters at the study site a prokaryotic origin of viruses seems likely because prokaryotes decreased by 1 2 orders of magnitude and eukaryotic cells decreased by 2 3 orders of magnitude with depth (Table 1, Fig. 2; Tanaka and Rassoulzadegan, 02), whereas VPR dropped only by half (Table 1). Depth-integrated viral abundance for the three depth layers at the study site is similar to previously reported values from the Mediterranean Sea (Magagnini et al., 07). The range of VPR values in the epipelagic at the study site (Table 1) is within previously reported values for oceanic regions (Wommack and Colwell, 00). However, VPR values in the meso- and bathypelagic zone (Table 1) reached higher maxima as compared to other marine systems (Wommack and Colwell, 00). Also, temporal variation of VPR at the study site (Table 1) was substantially higher in our study as compared to previously published results from the same site (Weinbauer et al., 03). The significantly higher average VPR in the epipelagic as compared to the meso- and bathypelagic (Table 1) suggests that prokaryotes are experiencing higher stress due to viruses in surface waters (e.g., due

9 1980 C. Winter et al. / Deep-Sea Research I 56 (09) to higher metabolic activity of prokaryotes) as compared to deeper waters. Alternatively, viruses may be subject to a lower decay rate in the epipelagic zone. However, this seems unlikely since viral decay is accelerated by ultraviolet radiation in the surface area (Suttle and Chen, 1992). Previous studies also found VPR to decline with depth (e.g., Hara et al., 1996). However, a recent study reports that in the subtropical North Atlantic VPR increases from 9 at 100 m depth to 110 at m depth (Parada et al., 07). One possible reason for the discrepancy in our results could be due to the warm deep waters in the Mediterranean Sea facilitating higher viral decay rates and enzyme activity as compared to the deep North Atlantic Temporal changes in surface and deep waters The deep water of the Mediterranean Sea is unusually warm (13 1C) throughout the year, and the break-down of the thermal stratification during the winter months results in a uniform water column with the potential for deep vertical mixing (Béthoux et al., 1990; Winter et al., 09). Thus, it is not surprising to find that prokaryotic and viral abundance decreased throughout the water column as stratification broke-down (Figs. 2 and 3, negative correlations with s T, Tables 2 5), underlining the notion that prokaryotic and viral abundance generally scale with the productivity of a system as it changes with the seasons (e.g., Weinbauer, 04). Seasonal changes in prokaryotic and viral abundance were particularly pronounced in the epipelagic but also clearly visible in the meso- and bathypelagic zones (Fig. 4). However, depthintegrated prokaryotic and viral abundance in the epipelagic zone need to be treated cautiously because of the lower number of sampling points in this depth zone. A comparison of our data on the temporal changes of prokaryotic and viral abundance at the study site with a large-scale spatial study in the Mediterranean Sea reveals that the minimum values of prokaryotic and viral abundance in all three depth layers were well above the lower limits previously reported (Table 1; Magagnini et al., 07). However, temporal changes at the study site resulted in higher maximum values of prokaryotic abundance in the meso- and bathypelagic zones and of viral abundance in all three depth layers (Table 1; Magagnini et al., 07). Thus, particularly in the mesoand bathypelagic zones, temporal variation at the study site exceeds spatial variation in the same depth zones reported throughout the Mediterranean Sea. Also, Winter et al. (09) showed that bacterial community composition in all three depth layers changed seasonally and that deep water microbial communities can be as dynamic as the ones found at the surface. If vertical mixing were to be the sole source of these changes, we should have found significant and consistent negative correlations between s T and prokaryotic and viral abundance in surface and medium-depth waters, whereas in the bathypelagic numbers of prokaryotes and viruses should have significantly increased because of export of prokaryotes and viruses from other depth layers with higher abundances. However, our data give a more complex picture (Figs. 2 4, Tables 3 5). The changes in depth-integrated prokaryotic and viral abundance in the bathypelagic zone from December to February (Fig. 4) suggest that the environmental changes due to deep vertical mixing (e.g., availability of nutrients and dissolved organic carbon) in the bathypelagic zone stimulated prokaryotic growth and as a consequence also resulted in viral production in deep waters at the study site. Seasonal data on the export flux of particles bringing nutrients and carbon into the bathypelagic zone show highest values during winter and spring, supporting the interpretation of our results (Stemmann et al., 02; Sternberg et al., 07). Previously, the fraction of lytically-infected prokaryotic cells at the study site was estimated to vary between 0.8% and 16% and was 5% or less in waters below the deep chlorophyll maximum layer whereas the frequency of lysogenic cells as obtained by induction using Mitomycin C varied between 58% and 84% in waters between 800 and 00 m depth during the stratified period in June 1999 (Weinbauer et al., 03). Furthermore, model calculations estimate that 52 60% of prokaryotic biomass (based on the annual mean of integrated biomass) are lost by viral lysis in the mesopelagic layer at our study site (Tanaka et al., 05). Based on an average burst size of 32 viruses per lysed prokaryotic cell (Weinbauer et al., 03) and the observed increase in depth-integrated viral abundance in the bathypelagic zone from m 2 in December to m 2 in February, we estimate that m 2 prokaryotic cells have been lysed by viruses, corresponding to 19 38% of infected prokaryotic cells in the same period. These numbers represent conservative estimates of viral production in the bathypelagic zone due to co-occurring viral decay and suggest that viral production (due to lytic or temperate viruses) in deep waters at the study site was also occurring during the non-stratified period Populations of prokaryotes and viruses distinguished by FCM Based on previous studies showing that prokaryotic production declines with depth at the study site (Leméeet al., 02; Tanaka and Rassoulzadegan, 04) and that differences between HNA and LNA cells appear to be due to differences between growth states (Lebaron et al., 02) we expected to observe a clear difference between the depth layers in terms of the fractions of LNA and HNA cells. However, our data show that neither group is preferentially found in surface or deeper waters (Table 1), suggesting that the distinction between LNA and HNA cells does not appear to be an adaptation to particular environmental conditions found only in certain depth layers. On average HNA cells dominated the meso- and bathypelagic zone while in the epipelagic no significant difference between HNA and LNA cells was found (Table 1). It is interesting to note that the fraction of LNA cells decreased in the epipelagic and increased in the bathypelagic as stratification broke-down (correlations with s T ; Tables 3 and 5). The finding that depth was positively related to LNA and negatively to HNA in the third

10 C. Winter et al. / Deep-Sea Research I 56 (09) component of the PCA suggests an influence of depth (Table 6). Thus, LNA cells show some preference for the surface during the stratified period and for deeper waters during the non-stratified period, during which prokaryotic growth appears to have been stimulated (Fig. 4A). In agreement with previous studies (e.g., Payet and Suttle, 08), the viral community throughout the water column and in all three depth layers was dominated by Vir-LF viruses (Table 1, Fig. 3). The relative abundance of viruses decreased from the Vir-LF to the Vir-MF and finally to the Vir-HF population, and the overwhelming majority of viruses (95%) fell within the Vir-LF and Vir-MF populations. Similar to the two prokaryotic populations, Vir-LF and Vir-MF viruses showed no preference for surface or deeper waters. However, the fraction of Vir-HF viruses was significantly higher at the surface than in deeper waters. Viruses with a strong fluorescence signal in FCM analysis supposedly infect phytoplankton or other eukaryotic planktonic organisms as opposed to viruses with a weaker fluorescence signal that mostly infect prokaryotes (Brussaard et al., 00; Payet and Suttle, 08). Thus, the preference of Vir-HF viruses for the epipelagic zone at the study site supports this notion Virus host interactions in surface and deep waters Our data reveal two lines of evidence that the relationship between viruses and their prokaryotic hosts is distinctly different in the epi- and bathypelagic zone at the study site: (1) the relationships between prokaryotic abundance and the two most abundant viral populations Vir-LF and Vir-MF (Fig. 5) and (2) the relationship between the composition of the bacterial community (different phylotypes detected) and viral abundance in the epipelagic (r m ¼ 0.57, po0.05) versus the positive correlation between bacterial richness (total number of phylotypes detected) and viral abundance in the bathypelagic zone (r ¼ 0.57, p ¼ ). The mesopelagic appears to be the transition zone, since no relationships between prokaryotic abundance and a particular virus population or changes in the bacterial community and viral abundance were detected. Since differences in viral groups as distinguished by FCM analysis are based on phylogenetic differences, that is different virus types (Brussaard et al., 00), the data suggest that as prokaryotic abundance changed with the seasons the composition of the viral communities in the epi- and bathypelagic changed in a reciprocal fashion (Fig. 5). Viruses are considered to be one of the driving mechanisms in maintaining prokaryotic richness in aquatic systems by selectively infecting and killing the winners in the competition for nutrients (Thingstad, 00; Thingstad and Lignell, 1997). Recently, Bouvier and del Giorgio (07) presented evidence that the susceptibility of prokaryotes to viral infection does not depend solely on host density but also depends on additional host characteristics (e.g., growth rate, resistance to viral infection). According to these authors, the winners in the competition for nutrients under certain conditions are actually relatively rare members of the community subjected to high virus-induced mortality and, thus, their abundance remains low. Assuming that DGGE analysis detects abundant phylotypes, the relationship between the composition of the bacterial community and viral abundance in the epipelagic are compatible with the mechanism described by Bouvier and del Giorgio (07). The relationship between bacterial richness and viral abundance in the bathypelagic suggests that the bacterial community might have been influenced by the actions of viruses resulting in a more even distribution of the relative abundances of the members of the community and, thus, caused an increase in bacterial richness as suggested by the killing the winner hypothesis (Thingstad, 00; Thingstad and Lignell, 1997). Together, the data support the idea that different mechanisms of interaction between viruses and their prokaryotic hosts (e.g., lytic versus temperate viruses; Weinbauer et al., 03; Williamson et al., 08) appear to prevail at the surface and in deep waters. Acknowledgments We are grateful to Jean-Claude Marty, Jacques Chiaverini, Floriane Girard, and Stéphane Gouy for organizing the cruises to the DYFAMED site. The captains and crews of R.V. Tethys II are acknowledged for their assistance at sea. The manuscript was improved by the comments of three anonymous reviewers. Financial support for this study was provided by a Marie Curie postdoctoral fellowship from the European Commission to CW (project ILVIRO- MAB, no ). The cruises were financed by INSU- CNRS (Institut National des Sciences de l Univers-Centre National de la Recherche Scientifique). Additional support came from the project ANR-AQUAPHAGE (No. ANR 07 BDIV ; coordinated by MGW) of the french Science Ministry. References Baudoux, A.-C., Veldhuis, M.J.W., Witte, H.J., Brussaard, C.P.D., 07. Viruses as mortality agents of picophytoplankton in the deep chlorophyll maximum layer during IRONAGES III. Limnol. Oceanogr. 52, Béthoux, J.P., Gentili, B., Raunet, J., Tailliez, D., Warming trend in the western Mediterranean deep water. Nature 347, Bouvier, T., del Giorgio, P.A., 07. Key role of selective viral-induced mortality in determining marine bacterial community composition. Environ. Microbiol. 9, Brussaard, C.P.D., 04. Optimization of procedures for counting viruses by flow cytometry. Appl. Environ. Microbiol. 70, Brussaard, C.P.D., Marie, D., Bratbak, G., 00. Flow cytometric detection of viruses. J. Virol. Meth. 85, Gasol, J.M., del Giorgio, P.A., 00. Using flow cytometry for counting natural planktonic bacteria and understanding the structure of planktonic bacterial communities. Sci. Mar. 64, Gasol, J.M., Zweifel, U.L., Peters, F., Fuhrman, J.A., Hagström, Å., Significance of size and nucleic acid content heterogeneity as measured by flow cytometry in natural planktonic bacteria. Appl. Environ. Microbiol. 65, Hara, S., Koike, K., Terauchi, H., Kamiya, H., Tanoue, E., Abundance of viruses in deep oceanic waters. Mar. Ecol. Prog. Ser. 145, Hennes, K.P., Suttle, C.A., Direct counts of viruses in natural waters and laboratory cultures by epifluorescence microscopy. Limnol. Oceanogr.,

11 1982 C. Winter et al. / Deep-Sea Research I 56 (09) Hobbie, J.E., Daley, R.J., Jasper, S., Use of nucleopore filters for counting bacteria by fluorescence microscopy. Appl. Environ. Microbiol. 33, Jochem, F.J., Lavrentyev, P.J., First, M.R., 04. Growth and grazing rates of bacteria groups with different apparent DNA content in the Gulf of Mexico. Mar. Biol. 145, Lebaron, P., Servais, P., Agogué, H., Courties, C., Joux, F., 01. Does the high nucleic acid content of individual bacterial cells allow us to discriminate between active cells and inactive cells in aquatic systems? Appl. Environ. Microbiol. 67, Lebaron, P., Servais, P., Baudoux, A.-C., Bourrain, M., Courties, C., Parthuisot, N., 02. Variations of bacterial-specific activity with cell size and nucleic acid content assessed by flow cytometry. Aquat. Microb. Ecol. 28, Legendre, P., Legendre, L., Numerical Ecology, second ed. Elsevier, Amsterdam. Lemée, R., Rochelle-Newall, E., van Wambeke, F., Pizay, M.-D., Rinaldi, P., Gattuso, J.-P., 02. Seasonal variation of bacterial production, respiration and growth efficiency in the open NW Mediterranean Sea. Aquat. Microb. Ecol. 29, Lévy, M., Mémery, L., André, J.M., Simulation of primary production and export fluxes in the Northwestern Mediterranean Sea. J. Mar. Res. 56, Li, W.K.W., Dickie, P.M., 01. Monitoring phytoplankton, bacterioplankton, and virioplankton in a coastal inlet (Bedford Basin) by flow cytometry. Cytometry 44, Longnecker, K., Sherr, B.F., Sherr, E.B., 05. Activity and phylogenetic diversity of bacterial cells with high and low nucleic acid content and electron transport system activity in an upwelling ecosystem. Appl. Environ. Microbiol. 71, Magagnini, M., Corinaldesi, C., Monticelli, L.S., DeDomenico, E., Danovaro, R., 07. Viral abundance and distribution in mesopelagic and bathypelagic waters of the Mediterranean Sea. Deep-Sea Res. I 54, Mantel, N., The detection of disease clustering and a generalized regression approach. Cancer Res. 27, 9 2. Marie, D., Brussaard, C.P.D., Thyrhaug, R., Bratbak, G., Vaulot, D., 1999a. Enumeration of marine viruses in culture and natural samples by flow cytometry. Appl. Environ. Microbiol. 65, Marie, D., Partensky, F., Vaulot, D., Brussaard, C.P.D., 1999b. Enumeration of phytoplankton, bacteria, and viruses in marine samples. In: Robinson, J.P., Darzynkiewicz, Z., Dean, P.N., Orfao, A., Rabinovitch, P.S., Stewart, C.C., Tanke, H.J., Wheeless, L.L. (Eds.), Current Protocols in Cytometry. Wiley, New York, pp Marie, D., Vaulot, D., Partensky, F., Application of the novel nucleic acid dyes YOYO-1, YO-PRO-1, and PicoGreen for flow cytometric analysis of marine prokaryotes. Appl. Environ. Microbiol. 62, Morán, X.A.G., Bode, A., Suárez, L.Á., Nogueira, E., 07. Assessing the relevance of nucleic acid content as an indicator of marine bacterial activity. Aquat. Microb. Ecol. 46, Murray, A.G., Jackson, G.A., Viral dynamics: a model of the effects of size, shape, motion and abundance of single-celled planktonic organisms and other particles. Mar. Ecol. Prog. Ser. 89, Noble, R.T., Fuhrman, J.A., Use of SYBR Green I for rapid epifluorescence counts of marine viruses and bacteria. Aquat. Microb. Ecol. 14, Parada, V., Sintes, E., van Aken, H.M., Weinbauer, M.G., Herndl, G.J., 07. Viral abundance, decay, and diversity in the meso- and bathypelagic waters of the North Atlantic. Appl. Environ. Microbiol. 73, Payet, J.P., Suttle, C.A., 08. Physical and biological correlates of virus dynamics in the southern Beaufort Sea and Amundsen Gulf. J. Mar. Syst. 74, Porter, K.G., Feig, Y.S., The use of DAPI for identifying and counting aquatic microflora. Limnol. Oceanogr. 25, Scharek, R., Latasa, M., 07. Growth, grazing and carbon flux of high and low nucleic acid bacteria differ in surface and deep chlorophyll maximum layers in the NW Mediterranean Sea. Aquat. Microb. Ecol. 46, Stemmann, L., Gorsky, G., Marty, J.-C., Picheral, M., Miquel, J.-C., 02. Four-year study of large-particle vertical distribution ( m) in the NW Mediterranean in relation to hydrology, phytoplankton, and vertical flux. Deep-Sea Res. II 49, Sternberg, E., Jeandel, C., Miquel, J.-C., Gasser, B., Souhaut, M., Arraes- Mescoff, R., Francois, R., 07. Particulate barium fluxes and export production in the northwestern Mediterranean. Mar. Chem. 105, Suttle, C.A., Chen, F., Mechanisms and rates of decay of marine viruses in seawater. Appl. Environ. Microbiol. 58, Tanaka, T., Rassoulzadegan, F., 02. Full-depth profile (0 00 m) of bacteria, heterotrophic nanoflagellates and ciliates in the NW Mediterranean Sea: vertical partitioning of microbe trophic structures. Deep-Sea Res. II 49, Tanaka, T., Rassoulzadegan, F., 04. Vertical and seasonal variations of bacterial abundance and production in the mesopelagic layer of the NW Medterranean Sea: bottom-up and top-down controls. Deep-Sea Res. I 51, Tanaka, T., Rassoulzadegan, F., Thingstad, T.F., 05. Analyzing the trophic link between the mesopelagic microbial loop and zooplankton from observed depth profiles of bacteria and protozoa. Biogeosciences 2, Thingstad, T.F., 00. Elements of a theory for the mechanisms controlling abundance, diversity, and biogeochemical role of lytic bacterial viruses in aquatic systems. Limnol. Oceanogr. 45, Thingstad, T.F., Lignell, R., Theoretical models for the control of bacterial growth rate, abundance, diversity and carbon demand. Aquat. Microb. Ecol. 13, Weinbauer, M.G., 04. Ecology of prokaryotic viruses. FEMS Microbiol. Rev. 28, Weinbauer, M.G., Brettar, I., Höfle, M.G., 03. Lysogeny and virusinduced mortality of bacterioplankton in surface, deep, and anoxic marine waters. Limnol. Oceanogr. 48, Weinbauer, M.G., Suttle, C.A., Comparison of epifluorescence and transmission electron microscopy for counting viruses in natural marine waters. Aquat. Microb. Ecol. 13, Williamson, S.J., Cary, S.C., Williamson, K.E., Helton, R.R., Bench, S.R., Winget, D., Wommack, K.E., 08. Lysogenic virus host interactions predominate at deep-sea diffuse-flow hydrothermal vents. ISME J. 2, Winter, C., Kerros, M.-E., Weinbauer, M.G., 09. Seasonal changes of bacterial and archaeal communities in the dark ocean: evidence from the Mediterranean Sea. Limnol. Oceanogr. 54, Wommack, K.E., Colwell, R.R., 00. Virioplankton: viruses in aquatic ecosystems. Microbiol. Mol. Biol. Rev. 64, Zubkov, M.V., Fuchs, B.M., Burkill, P.H., Amann, R., 01. Comparison of cellular and biomass specific activities of dominant bacterioplankton groups in stratified waters of the Celtic Sea. Appl. Environ. Microbiol. 67,