# Bacterial activity and genetic richness along an estuarine gradient (Rhone River plume, France)

M. Troussellier, H. Schafer, N. Batailler, L. Bernard, C. Courties, P. Lebaron, G. Muyzer, P. Servais, J. Vives-Rego

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M. Troussellier, H. Schafer, N. Batailler, L. Bernard, C. Courties, et al.. Bacterial activity and genetic richness along an estuarine gradient (Rhone River plume, France). Aquatic Microbial Ecology, 2002, 28 (1), pp.13-24. 10.3354/ame028013. hal-01663382

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# Bacterial activity and genetic richness along an estuarine gradient (Rhone River plume, France)

M. Troussellier<fnref n="1" />,*, H. Schäfer<fnref n="2" />,**, N. Batailler<fnref n="3" />, L. Bernard<fnref n="3" />, C. Courties<fnref n="3" />, P. Lebaron<fnref n="3" />, G. Muyzer<fnref n="2" />,***, P. Servais<fnref n="4" />, J. Vives-Rego<fnref n="5" />

**ABSTRACT:** Bacterial diversity and activity were simultaneously investigated by microbial ecological and molecular biological methods along an estuarine gradient from the Rhone River to the Mediterranean Sea. Following a Lagrangian strategy, we sampled plume, frontal and marine layers. The sampled estuarine gradient exhibited large changes both in physico-chemical and in microbiological characteristics. Bacterial abundances and activities showed a more drastic decrease in the low salinity range of the gradient than expected from simple dilution models, indicating that an important fraction of freshwater bacteria disappeared in the mixing area. High specific activities, in particular for leucine, in the marine end-part of the gradient suggested important bacterial protein synthesis, which may be a sign of an active survival strategy for bacterial communities subjected to oligotrophic conditions. Bacterial genetic diversity of the sampled estuarine area, as estimated by the number of DNA-derived denaturing gradient gel electrophoresis (DGGE) bands, was high (13 to 55 bands) compared to that reported in other aquatic ecosystems. This high diversity may be the consequence of the interface position of estuaries. The proportion of active populations was estimated using the ratio of DGGE bands derived from RNA and DNA. This ratio was lower in Rhone water than in marine water, indicating that only a part of the constitutive populations were active, while the activity was distributed within a larger fraction of populations in the marine assemblage. Very few DGGE bands detected in freshwater samples were also detected in the marine end-part of the gradient, suggesting that a very limited number of freshwater bacteria could survive under marine conditions. Detection of these freshwater populations from RNA might indicate that these bacteria were able to synthesize different stress proteins as the result of a survival strategy or that these bacteria were able to maintain metabolic activity under marine conditions. The structure of marine communities was strongly affected by decreasing salinity. However, it seems that the decrease of DNA-derived bands may simply have been the consequence of the mixing of marine and freshwater. No obvious relationship between genetic richness and activity changes was observed. This lack of a relationship may be the consequence of a very short residence time of water in the mixing area studied.

**KEY WORDS:** Bacteria · Genetic diversity · Activity · Estuary · Rhone River · Mediterranean Sea · PCR-DGGE · Flow cytometry

Resale or republication not permitted without written consent of the publisher

## INTRODUCTION

In aquatic systems, bacterioplankton plays a major role in the biogeochemical cycles of major elements such as C, O, N and P, and bacterial activity has large

<footnote n="1">¹Laboratoire d'Hydrobiologie Marine - UMR CNRS 5119, Université Montpellier II, 34095 Montpellier Cedex 05, France</footnote>

<footnote n="2">²Max-Planck-Institut für Marine Mikrobiologie, 28359 Bremen, Germany</footnote>

<footnote n="3">³Observatoire Océanologique, Université Pierre et Marie Curie, UMR 7621-7628 CNRS-INSU, BP 44, 66651 Banyuls-sur-Mer Cedex, France</footnote>

<footnote n="4">⁴Ecologie des Systèmes Aquatiques, Université Libre de Bruxelles, Campus de la Plaine, CP 221, Boulevard du Triomphe, 1050 Bruxelles, Belgium</footnote>

<footnote n="5">⁵Departament de Microbiologia, Universitat de Barcelona, Av. Diagonal 645, 08028 Barcelona, Spain</footnote>

<footnote>*E-mail: troussel@hydrobio.univ-montp2.fr
Present addresses:</footnote>

<footnote>**Department of Biological Sciences, University of Warwick,
Coventry CV4 7AL, United Kingdom</footnote>

<footnote>***Kluyver Laboratory for Biotechnology, 2628 BC Delft,
The Netherlands</footnote>
# Bacterial activity and genetic richness along an estuarine gradient (Rhone River plume, France)

M. Troussellier<fnref n="1" />,*, H. Schäfer<fnref n="2" />,**, N. Batailler<fnref n="3" />, L. Bernard<fnref n="3" />, C. Courties<fnref n="3" />, P. Lebaron<fnref n="3" />, G. Muyzer<fnref n="2" />,***, P. Servais<fnref n="4" />, J. Vives-Rego<fnref n="5" />

**ABSTRACT:** Bacterial diversity and activity were simultaneously investigated by microbial ecological and molecular biological methods along an estuarine gradient from the Rhone River to the Mediterranean Sea. Following a Lagrangian strategy, we sampled plume, frontal and marine layers. The sampled estuarine gradient exhibited large changes both in physico-chemical and in microbiological characteristics. Bacterial abundances and activities showed a more drastic decrease in the low salinity range of the gradient than expected from simple dilution models, indicating that an important fraction of freshwater bacteria disappeared in the mixing area. High specific activities, in particular for leucine, in the marine end-part of the gradient suggested important bacterial protein synthesis, which may be a sign of an active survival strategy for bacterial communities subjected to oligotrophic conditions. Bacterial genetic diversity of the sampled estuarine area, as estimated by the number of DNA-derived denaturing gradient gel electrophoresis (DGGE) bands, was high (13 to 55 bands) compared to that reported in other aquatic ecosystems. This high diversity may be the consequence of the interface position of estuaries. The proportion of active populations was estimated using the ratio of DGGE bands derived from RNA and DNA. This ratio was lower in Rhone water than in marine water, indicating that only a part of the constitutive populations were active, while the activity was distributed within a larger fraction of populations in the marine assemblage. Very few DGGE bands detected in freshwater samples were also detected in the marine end-part of the gradient, suggesting that a very limited number of freshwater bacteria could survive under marine conditions. Detection of these freshwater populations from RNA might indicate that these bacteria were able to synthesize different stress proteins as the result of a survival strategy or that these bacteria were able to maintain metabolic activity under marine conditions. The structure of marine communities was strongly affected by decreasing salinity. However, it seems that the decrease of DNA-derived bands may simply have been the consequence of the mixing of marine and freshwater. No obvious relationship between genetic richness and activity changes was observed. This lack of a relationship may be the consequence of a very short residence time of water in the mixing area studied.

**KEY WORDS:** Bacteria · Genetic diversity · Activity · Estuary · Rhone River · Mediterranean Sea · PCR-DGGE · Flow cytometry

Resale or republication not permitted without written consent of the publisher

## INTRODUCTION

In aquatic systems, bacterioplankton plays a major role in the biogeochemical cycles of major elements such as C, O, N and P, and bacterial activity has large

<footnote n="1">¹Laboratoire d'Hydrobiologie Marine - UMR CNRS 5119, Université Montpellier II, 34095 Montpellier Cedex 05, France</footnote>

<footnote n="2">²Max-Planck-Institut für Marine Mikrobiologie, 28359 Bremen, Germany</footnote>

<footnote n="3">³Observatoire Océanologique, Université Pierre et Marie Curie, UMR 7621-7628 CNRS-INSU, BP 44, 66651 Banyuls-sur-Mer Cedex, France</footnote>

<footnote n="4">⁴Ecologie des Systèmes Aquatiques, Université Libre de Bruxelles, Campus de la Plaine, CP 221, Boulevard du Triomphe, 1050 Bruxelles, Belgium</footnote>

<footnote n="5">⁵Departament de Microbiologia, Universitat de Barcelona, Av. Diagonal 645, 08028 Barcelona, Spain</footnote>

<footnote>*E-mail: troussel@hydrobio.univ-montp2.fr
Present addresses:</footnote>

<footnote>**Department of Biological Sciences, University of Warwick,
Coventry CV4 7AL, United Kingdom</footnote>

<footnote>***Kluyver Laboratory for Biotechnology, 2628 BC Delft,
The Netherlands</footnote>
consequences on water quality. However, despite an increasing number of publications on bacterial diversity, little is known about (1) the effect of changes in environmental conditions on the composition and structure of bacterial communities, and about (2) the relationships between bacterial diversity and productivity or activity (Schäfer et al. 2001). This can be explained by the inadequacy of culture-based methods used to record microbial diversity. The application of molecular biological methods theoretically allows a more objective view on microbial diversity. However, so far only a few studies have tried to study bacterial diversity and activity in parallel. Such studies have been limited to very specific environments (e.g. biofilms, Santegoeds et al. 1998) or conducted in mesocosms (Lebaron et al. 1999, Schäfer et al. 2001), mainly because of difficulties in analyzing many samples simultaneously.

The aim of this study was to investigate bacterial diversity and productivity along the estuary of a large river flowing into the Mediterranean Sea (the Rhone River). Estuaries are coastal ecosystems where large changes in environmental conditions occur due to the mixture of fresh and marine waters. Inorganic nutrients and organic matter from watersheds are transported through estuaries and can be processed by different freshwater, brackish and marine populations of microorganisms. Among marine ecosystems, estuaries appear to support high mean bacterial production rates (Ducklow & Carlson 1992). Another striking aspect of estuarine bacterial production and biomass values is their large variations from both spatial and temporal points of view (Ducklow & Shiah 1993, Painchaud et al. 1995, Goosen et al. 1999). Such ecosystems thus appear to be good systems to use in parallel classical microbial ecology methods that result in bulk measurements of the community (i.e. abundance and activity) and molecular biological methods (e.g. polymerase chain reaction [PCR] denaturing gradient gel electrophoresis [DGGE]) for exploring possible links between bacterial activity and diversity. To characterize bacterial community diversity, we used DGGE, which was applied on DNA and RNA extracted from the bacterial community. DGGE results obtained from DNA are considered to reflect the presence of different bacterial populations (Schäfer & Muyzer 2001), while rRNA-derived DGGE results have been recently used to give an indication of the presence of bacterial populations that contribute to the RNA pool, i.e. potentially active populations (Schäfer et al. 2001, Winter et al. 2001).

## MATERIALS AND METHODS

**Sampling strategy.** The Rhone River plume (Gulf of Lion, northwestern Mediterranean Sea) was investigated following a Lagrangian strategy on April 20, 1998 (Fig. 1). For this experiment, a drifter (Naudin et al. 1997) was launched 1 nautical mile (1.8 km) south of the Rhone river mouth (Roustan buoy) to follow the mixing of the river plume with the marine underlying water. The drifter was tracked by the oceanographic RV 'Téthys II', on which continuous conductivity-temperature-depth (CTD) measurements were performed to select stations for sampling of water with different salinity. Five depths (0.5, 1.1, 2.2, 3.4 and 10 m) were sampled along the halocline at Stns B, C, D and E (Fig. 1). Due to the limited water depth at the mouth of the river and the high speed of the drifter, only one surface sample was obtained from this area (A). Samples were collected outside the influence of the ship using a weighted polystyrene floating plate (1 m long, 0.6 m wide) connected to the research vessel with 7 m long Teflon tubes; the system allowed very precise sampling at the desired depth (Naudin et al. 1997). Freshwater samples were collected in the Rhone River upstream from the river mouth at 3 locations (R1, R2 and R3) across the river. For all measured variables, the reported results are means determined at the 3 stations. The marine reference station (Stn S) (43° 15' N, 4° 44' E; see Fig. 1) (S) was also sampled at 3 depths (5, 30 and 60 m) except for DGGE analyses, which were performed only for 5 and 30 m depth samples. Samples were processed on board, either stored

<figure><img src="image_1.png" /><figcaption>Fig. 1. Sampling locations in the Rhone River plume</figcaption></figure>
consequences on water quality. However, despite an increasing number of publications on bacterial diversity, little is known about (1) the effect of changes in environmental conditions on the composition and structure of bacterial communities, and about (2) the relationships between bacterial diversity and productivity or activity (Schäfer et al. 2001). This can be explained by the inadequacy of culture-based methods used to record microbial diversity. The application of molecular biological methods theoretically allows a more objective view on microbial diversity. However, so far only a few studies have tried to study bacterial diversity and activity in parallel. Such studies have been limited to very specific environments (e.g. biofilms, Santegoeds et al. 1998) or conducted in mesocosms (Lebaron et al. 1999, Schäfer et al. 2001), mainly because of difficulties in analyzing many samples simultaneously.

The aim of this study was to investigate bacterial diversity and productivity along the estuary of a large river flowing into the Mediterranean Sea (the Rhone River). Estuaries are coastal ecosystems where large changes in environmental conditions occur due to the mixture of fresh and marine waters. Inorganic nutrients and organic matter from watersheds are transported through estuaries and can be processed by different freshwater, brackish and marine populations of microorganisms. Among marine ecosystems, estuaries appear to support high mean bacterial production rates (Ducklow & Carlson 1992). Another striking aspect of estuarine bacterial production and biomass values is their large variations from both spatial and temporal points of view (Ducklow & Shiah 1993, Painchaud et al. 1995, Goosen et al. 1999). Such ecosystems thus appear to be good systems to use in parallel classical microbial ecology methods that result in bulk measurements of the community (i.e. abundance and activity) and molecular biological methods (e.g. polymerase chain reaction [PCR] denaturing gradient gel electrophoresis [DGGE]) for exploring possible links between bacterial activity and diversity. To characterize bacterial community diversity, we used DGGE, which was applied on DNA and RNA extracted from the bacterial community. DGGE results obtained from DNA are considered to reflect the presence of different bacterial populations (Schäfer & Muyzer 2001), while rRNA-derived DGGE results have been recently used to give an indication of the presence of bacterial populations that contribute to the RNA pool, i.e. potentially active populations (Schäfer et al. 2001, Winter et al. 2001).

## MATERIALS AND METHODS

**Sampling strategy.** The Rhone River plume (Gulf of Lion, northwestern Mediterranean Sea) was investigated following a Lagrangian strategy on April 20, 1998 (Fig. 1). For this experiment, a drifter (Naudin et al. 1997) was launched 1 nautical mile (1.8 km) south of the Rhone river mouth (Roustan buoy) to follow the mixing of the river plume with the marine underlying water. The drifter was tracked by the oceanographic RV 'Téthys II', on which continuous conductivity-temperature-depth (CTD) measurements were performed to select stations for sampling of water with different salinity. Five depths (0.5, 1.1, 2.2, 3.4 and 10 m) were sampled along the halocline at Stns B, C, D and E (Fig. 1). Due to the limited water depth at the mouth of the river and the high speed of the drifter, only one surface sample was obtained from this area (A). Samples were collected outside the influence of the ship using a weighted polystyrene floating plate (1 m long, 0.6 m wide) connected to the research vessel with 7 m long Teflon tubes; the system allowed very precise sampling at the desired depth (Naudin et al. 1997). Freshwater samples were collected in the Rhone River upstream from the river mouth at 3 locations (R1, R2 and R3) across the river. For all measured variables, the reported results are means determined at the 3 stations. The marine reference station (Stn S) (43° 15' N, 4° 44' E; see Fig. 1) (S) was also sampled at 3 depths (5, 30 and 60 m) except for DGGE analyses, which were performed only for 5 and 30 m depth samples. Samples were processed on board, either stored

<figure><img src="image_2.png" /><figcaption>Fig. 1. Sampling locations in the Rhone River plume</figcaption></figure>
without any treatments or fixed (see below) in sterile bottles in the dark at 4°C. To avoid too long a storage, samples were transported from the research vessel to a land-based laboratory (Salins de Giraud) by a high-speed shuttle.

Rough salinities were measured on board with a portable thermo-salinometer for the determination of the sampling stations. More accurate salinity measurements (using the Practical Salinity Scale) were performed at the land-based laboratory using a Guildline 8410 salinometer with an accuracy of ±0.01.

**Ammonium concentration.** Sub-samples for ammonium analysis were directly collected on board in 100 ml glass bottles. According to Koroleff's (1976) method, the reagents were added immediately and the measurements were performed 24 h after collection by spectrophotometry. The optical density was measured on each original sample to account for turbidity and salt effects in the final concentration. The accuracy of the ammonium measurements was ±0.2 µM.

**Phytoplanktonic abundance.** Phytoplankton counted with a FACSCalibur flow cytometer (Becton Dickinson) equipped with an air-cooled argon laser (488 nm, 15 mW). Cells excited at 488 nm were detected and enumerated according to their right-angle light scattering properties (RALS) and their orange (585/42 nm) and red fluorescence (>650 nm) emissions related to phycoerythrin and chlorophyll pigments, respectively. Fluorescent beads (0.94 µm) (Polysciences) were systematically added to each sample. The ratio of mean fluorescence or RALS of a cellular population to that of 0.94 µm beads was used to normalize cell fluorescence emission and scatter values between samples. The precise volume was analyzed and subsequent cell concentrations were estimated by measuring the remaining volume and subtracting it from the initial sub-sample volume (1 ml). Since part of the measured volume was used for flushing the sample line, the outer sleeve of the sample injection port of the flow cytometer was removed.

Different phytoplanktonic groups were discriminated according to their fluorescence and scatter characteristics as described previously (Troussellier et al. 1993, Campbell et al. 1994). For this paper, we have considered only 2 phytoplanktonic groups: prokaryotic cells (*Synechococcus*-like and *Prochlorococcus*) and eukaryotic cells (picoeukaryotic and larger).

**Protozoa abundance.** The abundance of protozoa was determined by epifluorescence microscopy (Leitz, Laborlux D) after 4', 6-diamidino-2-phenylindole (DAPI) staining. Water samples (20 ml) were preserved with glutaraldehyde (0.5% [v/v] final concentration) and stained with DAPI (10 µg ml⁻¹ final concentration) for 15 min. Stained protists were collected by filtration on 0.8 µm Nuclepore black filters. The filters were

mounted on microscope slides and stored at 4°C until examination. Pico-sized (<2 µm in diameter) and nano-sized (2 to 20 µm in diameter) micro-organisms were identified, counted and measured at a magnification of 1250× and 625×, respectively, while micro-sized (20 to 200 µm in diameter) micro-organisms were analyzed at a magnification of 125×. A minimum of 100 organisms filter⁻¹ was counted. Autotrophic species were distinguished from heterotrophs by the red autofluorescence of chlorophyll a observed under blue light excitation. Data presented in this paper concern only heterotrophic protozoa.

**Bacterial abundance and cellular characteristics.** Bacterial cells were enumerated using SYTO-13 staining and flow cytometry following Troussellier et al. (1999). Briefly, 1 ml formaldehyde-fixed sub-samples were directly incubated with SYTO-13 at a final concentration of 5 µM for 10 to 15 min at room temperature in the dark. For each sub-sample, 3 replicate counts were performed with a FACSCalibur flow cytometer as described above. Stained bacterial cells, excited at 488 nm, were enumerated according to their RALS and green fluorescence (FL1) collected at 530/30 nm. These cell parameters were recorded on a 4-decade logarithmic scale mapped onto 1024 channels. Standardized RALS values (cell RALS divided by 0.94 µm beads RALS) were used as an estimate of the relative size of bacterial cells (Troussellier et al. 1999). Cell abundance was calculated as for phytoplankton (see above). TriPLICATE measurements were performed for each sample, and mean and standard deviations were computed. Coefficients of variation of the mean abundance were always less than 10% and are not reported in the figures.

**Bacterial activity.** Two methods based on radioactive incorporation assays were used to estimate bacterial activity: measurement of ³H-thymidine incorporation rate into DNA (Fuhrman & Azam 1982) and ³H-leucine incorporation rate into bacterial proteins (Kirchman et al. 1985). Incorporation of ³H-thymidine (Amersham, 84 Ci mmol⁻¹) was measured in each sample at 4 thymidine concentrations (6 to 32 nM). Four 10 ml sub-samples were incubated in the presence of the 4 different concentrations of tritiated thymidine for 1 to 2 h in the dark at *in situ* temperature. After incubation, cold trichloroacetic acid (TCA; final concentration 5% [w/v]) was added, and the samples were filtered over a 0.2 µm pore-size cellulose acetate membrane. Radioactivity associated with the filters was estimated by liquid scintillation. Incorporation rates expressed in pmol l⁻¹ h⁻¹ at the different thymidine concentrations were calculated and plotted against the added thymidine concentrations. The maximum incorporation rates were estimated by best fitting a hyperbolic function to the experimental data using software based on the least squares criterion (Servais 1995). Data presented
without any treatments or fixed (see below) in sterile bottles in the dark at 4°C. To avoid too long a storage, samples were transported from the research vessel to a land-based laboratory (Salins de Giraud) by a high-speed shuttle.

Rough salinities were measured on board with a portable thermo-salinometer for the determination of the sampling stations. More accurate salinity measurements (using the Practical Salinity Scale) were performed at the land-based laboratory using a Guildline 8410 salinometer with an accuracy of ±0.01.

**Ammonium concentration.** Sub-samples for ammonium analysis were directly collected on board in 100 ml glass bottles. According to Koroleff's (1976) method, the reagents were added immediately and the measurements were performed 24 h after collection by spectrophotometry. The optical density was measured on each original sample to account for turbidity and salt effects in the final concentration. The accuracy of the ammonium measurements was ±0.2 µM.

**Phytoplanktonic abundance.** Phytoplankton counted with a FACSCalibur flow cytometer (Becton Dickinson) equipped with an air-cooled argon laser (488 nm, 15 mW). Cells excited at 488 nm were detected and enumerated according to their right-angle light scattering properties (RALS) and their orange (585/42 nm) and red fluorescence (>650 nm) emissions related to phycoerythrin and chlorophyll pigments, respectively. Fluorescent beads (0.94 µm) (Polysciences) were systematically added to each sample. The ratio of mean fluorescence or RALS of a cellular population to that of 0.94 µm beads was used to normalize cell fluorescence emission and scatter values between samples. The precise volume was analyzed and subsequent cell concentrations were estimated by measuring the remaining volume and subtracting it from the initial sub-sample volume (1 ml). Since part of the measured volume was used for flushing the sample line, the outer sleeve of the sample injection port of the flow cytometer was removed.

Different phytoplanktonic groups were discriminated according to their fluorescence and scatter characteristics as described previously (Troussellier et al. 1993, Campbell et al. 1994). For this paper, we have considered only 2 phytoplanktonic groups: prokaryotic cells (*Synechococcus*-like and *Prochlorococcus*) and eukaryotic cells (picoeukaryotic and larger).

**Protozoa abundance.** The abundance of protozoa was determined by epifluorescence microscopy (Leitz, Laborlux D) after 4', 6-diamidino-2-phenylindole (DAPI) staining. Water samples (20 ml) were preserved with glutaraldehyde (0.5% [v/v] final concentration) and stained with DAPI (10 µg ml⁻¹ final concentration) for 15 min. Stained protists were collected by filtration on 0.8 µm Nuclepore black filters. The filters were

mounted on microscope slides and stored at 4°C until examination. Pico-sized (<2 µm in diameter) and nano-sized (2 to 20 µm in diameter) micro-organisms were identified, counted and measured at a magnification of 1250× and 625×, respectively, while micro-sized (20 to 200 µm in diameter) micro-organisms were analyzed at a magnification of 125×. A minimum of 100 organisms filter⁻¹ was counted. Autotrophic species were distinguished from heterotrophs by the red autofluorescence of chlorophyll a observed under blue light excitation. Data presented in this paper concern only heterotrophic protozoa.

**Bacterial abundance and cellular characteristics.** Bacterial cells were enumerated using SYTO-13 staining and flow cytometry following Troussellier et al. (1999). Briefly, 1 ml formaldehyde-fixed sub-samples were directly incubated with SYTO-13 at a final concentration of 5 µM for 10 to 15 min at room temperature in the dark. For each sub-sample, 3 replicate counts were performed with a FACSCalibur flow cytometer as described above. Stained bacterial cells, excited at 488 nm, were enumerated according to their RALS and green fluorescence (FL1) collected at 530/30 nm. These cell parameters were recorded on a 4-decade logarithmic scale mapped onto 1024 channels. Standardized RALS values (cell RALS divided by 0.94 µm beads RALS) were used as an estimate of the relative size of bacterial cells (Troussellier et al. 1999). Cell abundance was calculated as for phytoplankton (see above). TriPLICATE measurements were performed for each sample, and mean and standard deviations were computed. Coefficients of variation of the mean abundance were always less than 10% and are not reported in the figures.

**Bacterial activity.** Two methods based on radioactive incorporation assays were used to estimate bacterial activity: measurement of ³H-thymidine incorporation rate into DNA (Fuhrman & Azam 1982) and ³H-leucine incorporation rate into bacterial proteins (Kirchman et al. 1985). Incorporation of ³H-thymidine (Amersham, 84 Ci mmol⁻¹) was measured in each sample at 4 thymidine concentrations (6 to 32 nM). Four 10 ml sub-samples were incubated in the presence of the 4 different concentrations of tritiated thymidine for 1 to 2 h in the dark at *in situ* temperature. After incubation, cold trichloroacetic acid (TCA; final concentration 5% [w/v]) was added, and the samples were filtered over a 0.2 µm pore-size cellulose acetate membrane. Radioactivity associated with the filters was estimated by liquid scintillation. Incorporation rates expressed in pmol l⁻¹ h⁻¹ at the different thymidine concentrations were calculated and plotted against the added thymidine concentrations. The maximum incorporation rates were estimated by best fitting a hyperbolic function to the experimental data using software based on the least squares criterion (Servais 1995). Data presented
in this paper are maximum incorporation rates. Incorporation of ³H-leucine (Amersham, 151 Ci mmol⁻¹) was measured at 4 leucine concentrations ranging from 2 to 77 nM (2 nM of tritiated leucine in each case with 0 to 75 nM non-radioactive leucine; Servais 1990). Four 10 ml sub-samples were incubated in the presence of the 4 different concentrations of leucine for 1 to 2 h in the dark at *in situ* temperature. After incubation, TCA was added, and the samples were filtered over a 0.2 µm pore-size cellulose acetate membrane. Radioactivity associated with the filters was estimated by liquid scintillation. Maximum incorporation rates were calculated as for thymidine incorporation.

Nucleic acid extraction, PCR and DGGE. DGGE analysis was performed on the DNA and RNA extracted from the different water samples. Nucleic acid was prepared following the hot phenol protocol of Sahm & Berninger (1998). Bead-beating and DNase steps were omitted. Recovery of sequences of Gram-positive bacteria in previous studies has shown that the modified protocol is also suitable to obtain DNA from Gram-positive bacteria (Rossello-Mora et al. 1999). RNA preparation and reverse transcription (RT)-PCR were carried out as described previously (Schäfer & Muyzer 2001). Briefly, RNA was prepared from 5 to 15 µl of nucleic acid extract using 10 U of DNase I (RNase-free; Pharmacia) in 40 mM Tris and 6 mM MgCl₂ (pH 7.5), followed by a purification step with phenol-chloroform-isoamyl alcohol (25:24:1 vol). RNA was concentrated by ethanol precipitation. RNA was reverse transcribed into cDNA using 200 U of MMLV-reverse transcriptase (Promega). The purity of RNA preparations from contaminating (undigested) DNA was confirmed by unsuccessful amplifications of 16S rDNA from RNA preparations that had not been reverse transcribed into cDNA.

PCR amplification of 16S rDNA fragments between *Escherichia coli* positions 341 and 926 (Brosius et al. 1981) was carried out as previously described (Muyzer et al. 1998), but reactions contained 1 U of Taq polymerase and the buffering conditions recommended by the manufacturer (Pharmacia). Reverse transcription of RNA and amplification of the 16S crDNA was performed as previously described (Schäfer & Muyzer 2001). DGGE was done according to Muyzer et al. (1998) using denaturing gradients from 20 to 80% denaturants (100% denaturants is a mixture of 7 M urea and 40% [v/v] deionized formamide). Electrophoresis was performed at a constant voltage of 200 V for 3.5 h. Gels were stained in ethidium bromide (0.5 µg ml⁻¹), rinsed in Milli-Q water and scanned under UV illumination using the Fluor-S system (Biorad). The acquisition software Multi-analyst (Biorad) was used to invert images and for enhancing the sharpness using the 'sharpen in place' filter.

The ratio between the number of DGGE bands obtained from RNA (R) and from DNA (D) derived PCR products was used as an estimate of the proportion of active sequence types in the bacterial community.

**Statistical analyses.** To check for the conservative versus non-conservative behaviour of NH₄⁺ and bacteria along the salinity gradient, we computed theoretical values of these variables as expected from a simple dilution model of river and seawater. First, fraction of freshwater (*F*) and marine water (1 − *F*) at each sampling station was estimated from salinity values (*S*<sub>E</sub>) following Officer (1976):

$$F = (S_S - S_E)/S_S$$

where *S*<sub>S</sub> is the salinity at the marine reference station S.

Then, the concentration of the chosen variable for each sampling location (*C*<sub>x</sub>) was computed by the equation

$$C_x = F C_R + (1 - F) C_S$$

where *C*<sub>R</sub> and *C*<sub>S</sub> are the concentrations of the chosen variable in the Rhone River and in the marine reference stations, respectively.

Linear regression models (Statview software, Abacus Concepts) were used to characterize different linear trends detected along the salinity gradient for different variables (protozoa and phytoplankton abundances, DGGE band number).

Similarities between DGGE profiles were estimated by computation of distance values from a binary matrix representing bands that could be unambiguously identified as originating from either the marine or the freshwater bacterial communities using the Jaccard coefficient. The resulting similarity matrix was then submitted to cluster analysis by unweighted pair-group method using arithmetic averages (UPGMA) (Sneath & Sokal 1973). Similarity and clustering analyses were performed with the R software (Legendre & Vaudor 1991)

# RESULTS

## The environmental gradient

During the sampling cruise the Rhone River flow was 2500 m³ s⁻¹ (river discharge measured at Beaucaire, 65 km upstream from the river mouth). The wind velocity during the preceding days was high (10 m s⁻¹). As a consequence, the plume was not very well established. The time taken by the drifter to go from the beginning (Roustan buoy, Fig. 1) to the end of the sampling transect (Stn D, Fig. 1) was 5 h and 30 min. Nevertheless, the estuarine area showed a 3-layer system as depicted by the salinity pattern (Fig. 2). A
in this paper are maximum incorporation rates. Incorporation of ³H-leucine (Amersham, 151 Ci mmol⁻¹) was measured at 4 leucine concentrations ranging from 2 to 77 nM (2 nM of tritiated leucine in each case with 0 to 75 nM non-radioactive leucine; Servais 1990). Four 10 ml sub-samples were incubated in the presence of the 4 different concentrations of leucine for 1 to 2 h in the dark at in situ temperature. After incubation, TCA was added, and the samples were filtered over a 0.2 µm pore-size cellulose acetate membrane. Radioactivity associated with the filters was estimated by liquid scintillation. Maximum incorporation rates were calculated as for thymidine incorporation.

Nucleic acid extraction, PCR and DGGE. DGGE analysis was performed on the DNA and RNA extracted from the different water samples. Nucleic acid was prepared following the hot phenol protocol of Sahm & Berninger (1998). Bead-beating and DNase steps were omitted. Recovery of sequences of Gram-positive bacteria in previous studies has shown that the modified protocol is also suitable to obtain DNA from Gram-positive bacteria (Rossello-Mora et al. 1999). RNA preparation and reverse transcription (RT)-PCR were carried out as described previously (Schäfer & Muyzer 2001). Briefly, RNA was prepared from 5 to 15 µl of nucleic acid extract using 10 U of DNase I (RNase-free; Pharmacia) in 40 mM Tris and 6 mM MgCl₂ (pH 7.5), followed by a purification step with phenol-chloroform-isoamyl alcohol (25:24:1 vol). RNA was concentrated by ethanol precipitation. RNA was reverse transcribed into cDNA using 200 U of MMLV-reverse transcriptase (Promega). The purity of RNA preparations from contaminating (undigested) DNA was confirmed by unsuccessful amplifications of 16S rDNA from RNA preparations that had not been reverse transcribed into cDNA.

PCR amplification of 16S rDNA fragments between Escherichia coli positions 341 and 926 (Brosius et al. 1981) was carried out as previously described (Muyzer et al. 1998), but reactions contained 1 U of Taq polymerase and the buffering conditions recommended by the manufacturer (Pharmacia). Reverse transcription of RNA and amplification of the 16S crDNA was performed as previously described (Schäfer & Muyzer 2001). DGGE was done according to Muyzer et al. (1998) using denaturing gradients from 20 to 80% denaturants (100% denaturants is a mixture of 7 M urea and 40% [v/v] deionized formamide). Electrophoresis was performed at a constant voltage of 200 V for 3.5 h. Gels were stained in ethidium bromide (0.5 µg ml⁻¹), rinsed in Milli-Q water and scanned under UV illumination using the Fluor-S system (Biorad). The acquisition software Multi-analyst (Biorad) was used to invert images and for enhancing the sharpness using the 'sharpen in place' filter.

The ratio between the number of DGGE bands obtained from RNA (R) and from DNA (D) derived PCR products was used as an estimate of the proportion of active sequence types in the bacterial community.

Statistical analyses. To check for the conservative versus non-conservative behaviour of NH₄⁺ and bacteria along the salinity gradient, we computed theoretical values of these variables as expected from a simple dilution model of river and seawater. First, fraction of freshwater (F) and marine water (1 − F) at each sampling station was estimated from salinity values (Sₐ) following Officer (1976):

$$F = (S_S - S_E)/S_S$$

where S_S is the salinity at the marine reference station S.

Then, the concentration of the chosen variable for each sampling location (Cₓ) was computed by the equation

$$C_x = F C_R + (1 - F) C_S$$

where C_R and C_S are the concentrations of the chosen variable in the Rhone River and in the marine reference stations, respectively.

Linear regression models (Statview software, Abacus Concepts) were used to characterize different linear trends detected along the salinity gradient for different variables (protozoa and phytoplankton abundances, DGGE band number).

Similarities between DGGE profiles were estimated by computation of distance values from a binary matrix representing bands that could be unambiguously identified as originating from either the marine or the freshwater bacterial communities using the Jaccard coefficient. The resulting similarity matrix was then submitted to cluster analysis by unweighted pair-group method using arithmetic averages (UPGMA) (Sneath & Sokal 1973). Similarity and clustering analyses were performed with the R software (Legendre & Vaudor 1991)

# RESULTS

## The environmental gradient

During the sampling cruise the Rhone River flow was 2500 m³ s⁻¹ (river discharge measured at Beaucaire, 65 km upstream from the river mouth). The wind velocity during the preceding days was high (10 m s⁻¹). As a consequence, the plume was not very well established. The time taken by the drifter to go from the beginning (Roustan buoy, Fig. 1) to the end of the sampling transect (Stn D, Fig. 1) was 5 h and 30 min. Nevertheless, the estuarine area showed a 3-layer system as depicted by the salinity pattern (Fig. 2). A
<figure><img src="image_2.png" /><figcaption>Fig. 2. Salinity distribution during the sampling campaign</figcaption></figure>

hydrological discontinuity could be seen in the plume at Stn B, which may have been due to upwelling of deep water.

Plots of $NH_4^+$ concentration against salinity did not show significant deviations from the straight line linking river and seawater reference stations (Fig. 3a). This result indicates that the concentration of $NH_4^+$ followed the linear mixing model.

Phytoplanktonic cell numbers increased with increasing salinity (Fig. 3b). Regression analysis indicated that this increase was more important for prokaryotic than for eukaryotic cells, leading to an increase of the ratio of prokaryotes to eukaryotes. Heterotrophic protozoa counts also increased along the salinity gradient (Fig. 3c); a 2.7-fold increase was observed between the river and the first station along the gradient.

## Bacterial abundance and activity

Contrary to concentrations of $NH_4^+$, bacterial abundance showed a non-conservative pattern along the salinity gradient resulting in a decrease from the river to the mixing area (Fig. 4). Thymidine and leucine incorporation rates showed a similar decreasing pattern. Abundance, leucine and thymidine incorporation rates decreased by a factor of 1.6, 3.0 and 4.5, respectively, between the first 2 stations of the gradient.

However, when thymidine and leucine specific activities were computed, a strong decrease in thymidine specific activity was observed in the first part of the salinity gradient followed by an increase at the end-part of the gradient (Fig. 5a). Leucine specific activity also decreased from the Rhone River water to the beginning of the mixture area, but then showed a strong increase from the beginning to the end of the salinity gradient (Fig. 5b).

<figure><img src="image_3.png" /></figure>

<figure><img src="image_4.png" /></figure>

<figure><img src="image_5.png" /><figcaption>Fig. 3. (a) $NH_4^+$ concentration, (b) phytoplankton and (c) protozoa abundance versus salinity values. Line in (a) corresponds to theoretical values for $NH_4^+$ if only dilution process occurred; lines in (b) and (c) are regression lines obtained from linear regression models computed between abundance and salinity</figcaption></figure>

Apparent mean sizes of bacterial cells decreased all along the salinity gradient (Fig. 5c).

## Genetic composition and richness

The DNA-derived DGGE (D-DGGE) fingerprints of the bacterial communities from the river reference (Stn R) and from 2 depths (Sea 1: 5 m; Sea 2: 30 m) of the marine reference station were obviously different (Fig. 6a)

The dendrogram illustrating the clustering of different D-DGGE patterns confirmed that river and marine communities were distant communities (Fig. 7). It also
<figure><img src="image_3.png" /><figcaption>Fig. 2. Salinity distribution during the sampling campaign</figcaption></figure>

hydrological discontinuity could be seen in the plume at Stn B, which may have been due to upwelling of deep water.

Plots of $NH_4^+$ concentration against salinity did not show significant deviations from the straight line linking river and seawater reference stations (Fig. 3a). This result indicates that the concentration of $NH_4^+$ followed the linear mixing model.

Phytoplanktonic cell numbers increased with increasing salinity (Fig. 3b). Regression analysis indicated that this increase was more important for prokaryotic than for eukaryotic cells, leading to an increase of the ratio of prokaryotes to eukaryotes. Heterotrophic protozoa counts also increased along the salinity gradient (Fig. 3c); a 2.7-fold increase was observed between the river and the first station along the gradient.

## Bacterial abundance and activity

Contrary to concentrations of $NH_4^+$, bacterial abundance showed a non-conservative pattern along the salinity gradient resulting in a decrease from the river to the mixing area (Fig. 4). Thymidine and leucine incorporation rates showed a similar decreasing pattern. Abundance, leucine and thymidine incorporation rates decreased by a factor of 1.6, 3.0 and 4.5, respectively, between the first 2 stations of the gradient.

However, when thymidine and leucine specific activities were computed, a strong decrease in thymidine specific activity was observed in the first part of the salinity gradient followed by an increase at the end-part of the gradient (Fig. 5a). Leucine specific activity also decreased from the Rhone River water to the beginning of the mixture area, but then showed a strong increase from the beginning to the end of the salinity gradient (Fig. 5b).

<figure><img src="image_4.png" /></figure>

<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /><figcaption>Fig. 3. (a) $NH_4^+$ concentration, (b) phytoplankton and (c) protozoa abundance versus salinity values. Line in (a) corresponds to theoretical values for $NH_4^+$ if only dilution process occurred; lines in (b) and (c) are regression lines obtained from linear regression models computed between abundance and salinity</figcaption></figure>

Apparent mean sizes of bacterial cells decreased all along the salinity gradient (Fig. 5c).

## Genetic composition and richness

The DNA-derived DGGE (D-DGGE) fingerprints of the bacterial communities from the river reference (Stn R) and from 2 depths (Sea 1: 5 m; Sea 2: 30 m) of the marine reference station were obviously different (Fig. 6a)

The dendrogram illustrating the clustering of different D-DGGE patterns confirmed that river and marine communities were distant communities (Fig. 7). It also
<figure><img src="image_6.png" /><figcaption>Fig. 4. (a) Bacterial total counts, (b) leucine and (c) thymidine incorporation rates versus salinity values. Line in (a) corresponds to theoretical values for bacterial abundance if only dilution process occurred</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>Fig. 5. (a) Thymidine, (b) leucine specific activities, and (c) relative cell size of bacteria, versus salinity</figcaption></figure>

showed that 2 groups can be clearly discriminated. The separation of these 2 groups on the basis of their genetic composition can be related to the hydrological structure of sampled water masses illustrated in Fig. 2. The 2 groups appeared to belong to 2 distinct water layers: the first group (Group I in Fig. 7) was composed of samples coming from upper-layer waters with a salinity ranging from 0 to ~35; the second group (Group II in Fig. 7) was formed by samples with a salinity >35, i.e. originating from deeper layers and the seawater reference station.

The community fingerprint of the river sample showed a total of 47 discernible bands, while the fingerprint of the marine reference station displayed 35 and 34 bands for the water samples from 5 m and 30 m depths, respectively. These estimates, however, have

to be regarded as minimum values, as dissimilar sequence types may co-migrate to the same position in the gel, thus leading to a potential underestimation of the number of different sequence types. Assuming that the truly Mediterranean and Rhone bacterial communities shared no common bacterial populations, a total genetic richness, defined as the number of apparent DGGE bands across systems, accumulated to 82 different 16S rRNA sequence types. However, in a number of cases, bands from river and seawater samples were often at a similar position in the gel and could not always be unambiguously identified as river or marine bands in the patterns obtained from samples of the zone where Mediterranean and Rhone water masses were mixing. Therefore, the number of discernible DGGE bands across systems (i.e. Rhone and Mediterranean) that could unambiguously be identified as originating from marine or river communities is 21 and
<figure><img src="image_7.png" /><figcaption>Fig. 4. (a) Bacterial total counts, (b) leucine and (c) thymidine incorporation rates versus salinity values. Line in (a) corresponds to theoretical values for bacterial abundance if only dilution process occurred</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>Fig. 5. (a) Thymidine, (b) leucine specific activities, and (c) relative cell size of bacteria, versus salinity</figcaption></figure>

showed that 2 groups can be clearly discriminated. The separation of these 2 groups on the basis of their genetic composition can be related to the hydrological structure of sampled water masses illustrated in Fig. 2. The 2 groups appeared to belong to 2 distinct water layers: the first group (Group I in Fig. 7) was composed of samples coming from upper-layer waters with a salinity ranging from 0 to ~35; the second group (Group II in Fig. 7) was formed by samples with a salinity >35, i.e. originating from deeper layers and the seawater reference station.

The community fingerprint of the river sample showed a total of 47 discernible bands, while the fingerprint of the marine reference station displayed 35 and 34 bands for the water samples from 5 m and 30 m depths, respectively. These estimates, however, have

to be regarded as minimum values, as dissimilar sequence types may co-migrate to the same position in the gel, thus leading to a potential underestimation of the number of different sequence types. Assuming that the truly Mediterranean and Rhone bacterial communities shared no common bacterial populations, a total genetic richness, defined as the number of apparent DGGE bands across systems, accumulated to 82 different 16S rRNA sequence types. However, in a number of cases, bands from river and seawater samples were often at a similar position in the gel and could not always be unambiguously identified as river or marine bands in the patterns obtained from samples of the zone where Mediterranean and Rhone water masses were mixing. Therefore, the number of discernible DGGE bands across systems (i.e. Rhone and Mediterranean) that could unambiguously be identified as originating from marine or river communities is 21 and
<figure><img src="image_8.png" /><figcaption>Fig. 6. Composite figure showing the denaturing gradient gel electrophoresis (DGGE) profiles derived from either DNA (top panel) or RNA (bottom panel) of samples aligned according to salinity (increasing from left to right; values indicated between the 2 gel figures). Individual samples were run on 3 gels, so some samples are imperfectly aligned with respect to co-migrating DGGE bands (confirmed by gel electrophoresis). The theoretical contribution of freshwater bacteria biomass to the total bacterial biomass has been calculated according to the linear mixing model and the biomasses of the river and sea reference samples</figcaption></figure>

27, respectively. The following analyses were based
only on unambiguous profiles.

When the numbers of D-DGGE bands of the Rhone
River (i.e. DF bands from freshwater [F] samples) were
plotted against the salinity values, they exhibited a
linear decrease (Fig. 8a), suggesting the disappear-
ance of freshwater species.

DM bands (D-DGGE bands from marine [M] sam-
ples) showed the opposite pattern to the DF profile
(Fig. 8b), although in the marine part of the gradient
(salinity between 40 and 30) there was an exponential
decrease of the number of bands with salinity de-
crease.

The proportion of active sequence types in sampled
bacterial communities was estimated by the ratio be-
tween the number of DGGE bands obtained from R-
and D-derived PCR products (Fig. 6).

In the Rhone waters this ratio was 0.45, while in sea-
water it was 0.75. This ratio was computed for fresh-
water (F, Fig. 9a) and for marine (M, Fig. 9b) communi-

ties at each sampling station. Marine and freshwater
communities showed quite different patterns. For the
bands corresponding to the freshwater pattern (Fig. 9a),
the proportion of R-derived bands remained low in the
surface layer where river and marine waters were pro-
gressively mixed (0 to 20) and first decreased then
increased at higher salinity (>20). However, the high-
est ratio (1.00) corresponded to a very limited number
of DGGE bands (<5), suggesting that only a few popu-
lations from the freshwater community remained de-
tectable from both DNA and RNA patterns. The pro-
portion of R-derived bands from the marine community
was high and less variable in the marine part of the
salinity gradient but decreased strongly at salinity
below 15 (Fig. 9b).

No statistically significant relationship was observed
between genetic richness (i.e. the number of DGGE
bands obtained either from DNA or RNA) and bacter-
ial activity expressed by thymidine or leucine incorpo-
ration rates.
<figure><img src="image_9.png" /><figcaption>Fig. 6. Composite figure showing the denaturing gradient gel electrophoresis (DGGE) profiles derived from either DNA (top panel) or RNA (bottom panel) of samples aligned according to salinity (increasing from left to right; values indicated between the 2 gel figures). Individual samples were run on 3 gels, so some samples are imperfectly aligned with respect to co-migrating DGGE bands (confirmed by gel electrophoresis). The theoretical contribution of freshwater bacteria biomass to the total bacterial biomass has been calculated according to the linear mixing model and the biomasses of the river and sea reference samples</figcaption></figure>

27, respectively. The following analyses were based
only on unambiguous profiles.

When the numbers of D-DGGE bands of the Rhone
River (i.e. DF bands from freshwater [F] samples) were
plotted against the salinity values, they exhibited a
linear decrease (Fig. 8a), suggesting the disappear-
ance of freshwater species.

DM bands (D-DGGE bands from marine [M] sam-
ples) showed the opposite pattern to the DF profile
(Fig. 8b), although in the marine part of the gradient
(salinity between 40 and 30) there was an exponential
decrease of the number of bands with salinity de-
crease.

The proportion of active sequence types in sampled
bacterial communities was estimated by the ratio be-
tween the number of DGGE bands obtained from R-
and D-derived PCR products (Fig. 6).

In the Rhone waters this ratio was 0.45, while in sea-
water it was 0.75. This ratio was computed for fresh-
water (F, Fig. 9a) and for marine (M, Fig. 9b) communi-

ties at each sampling station. Marine and freshwater
communities showed quite different patterns. For the
bands corresponding to the freshwater pattern (Fig. 9a),
the proportion of R-derived bands remained low in the
surface layer where river and marine waters were pro-
gressively mixed (0 to 20) and first decreased then
increased at higher salinity (>20). However, the high-
est ratio (1.00) corresponded to a very limited number
of DGGE bands (<5), suggesting that only a few popu-
lations from the freshwater community remained de-
tectable from both DNA and RNA patterns. The pro-
portion of R-derived bands from the marine community
was high and less variable in the marine part of the
salinity gradient but decreased strongly at salinity
below 15 (Fig. 9b).

No statistically significant relationship was observed
between genetic richness (i.e. the number of DGGE
bands obtained either from DNA or RNA) and bacter-
ial activity expressed by thymidine or leucine incorpo-
ration rates.
<figure><img src="image_9.png" /></figure>

Fig. 7. Dendrogram showing the similarity between DNA-derived (D) DGGE patterns obtained for each sample and the 2 main groups obtained from unweighted pair-group method using arithmetic averages (UPGMA) clustering

DISCUSSION

The main objective of this study was to determine
whether a relationship exists between activity and
diversity of bacterial communities in the estuarine area
of the Rhone River in the south of France.

As expected, important changes in some environ-
mental variables, which may directly or indirectly
affect the bacterial assemblages, occurred along the
Rhone estuary. According to the salinity variations, the
sampled area was characterized by a 3-layer system
(i.e. plume, frontal and marine layers) as described by
Soto et al. (1993). Changes in NH₄⁺ concentrations fol-
lowed a simple dilution process of Rhone waters in
Mediterranean seawater without significant gain or
loss from biogeochemical processes. A similar trend
was reported by Lochet & Leveau (1990).

The increase in abundance of both phytoplanktonic
cells and heterotrophic protozoa along the salinity gra-
dient has been reported at least for the first part (i.e.
the low salinity range) of the estuarine gradient (Soto
et al. 1993). The ratio of prokaryotes to eukaryotes
increased from freshwater to seawater, indicating a
decrease in the water trophism, because prokaryotes
predominate in oligotrophic waters as a consequence

<figure><img src="image_10.png" /></figure>

$$
y = -0.5351x + 22.358 \quad R^{2} = 0.87
$$

<figure><img src="image_11.png" /></figure>

Fig. 8. Number of (a) freshwater (DF) and (b) seawater (DM) DNA derived DGGE bands versus salinity

<figure><img src="image_12.png" /></figure>

Fig. 9. Ratios between the number of RNA (R) and DNA (D) derived bands for (a) freshwater (F) and (b) marine (M) communities versus salinity
<figure><img src="image_10.png" /></figure>

Fig. 7. Dendrogram showing the similarity between DNA-derived (D) DGGE patterns obtained for each sample and the 2 main groups obtained from unweighted pair-group method using arithmetic averages (UPGMA) clustering

DISCUSSION

The main objective of this study was to determine
whether a relationship exists between activity and
diversity of bacterial communities in the estuarine area
of the Rhone River in the south of France.

As expected, important changes in some environ-
mental variables, which may directly or indirectly
affect the bacterial assemblages, occurred along the
Rhone estuary. According to the salinity variations, the
sampled area was characterized by a 3-layer system
(i.e. plume, frontal and marine layers) as described by
Soto et al. (1993). Changes in NH₄⁺ concentrations fol-
lowed a simple dilution process of Rhone waters in
Mediterranean seawater without significant gain or
loss from biogeochemical processes. A similar trend
was reported by Lochet & Leveau (1990).

The increase in abundance of both phytoplanktonic
cells and heterotrophic protozoa along the salinity gra-
dient has been reported at least for the first part (i.e.
the low salinity range) of the estuarine gradient (Soto
et al. 1993). The ratio of prokaryotes to eukaryotes
increased from freshwater to seawater, indicating a
decrease in the water trophism, because prokaryotes
predominate in oligotrophic waters as a consequence

<figure><img src="image_11.png" /></figure>

Fig. 8. Number of (a) freshwater (DF) and (b) seawater (DM) DNA derived DGGE bands versus salinity

<figure><img src="image_12.png" /></figure>

Fig. 9. Ratios between the number of RNA (R) and DNA (D) derived bands for (a) freshwater (F) and (b) marine (M) communities versus salinity
of their better efficiency in using scarce nutrients than
eukaryotes (Weisse 1993).

Observed bacterial abundance and incorporation
rates of tritiated thymidine and leucine in water sam-
ples taken along the transect were in the same range
as those previously reported in the same area (Kirch-
man et al. 1989, Martinez et al. 1991, Bianchi et al.
1994). The decrease of bacterial abundance observed
in the low salinity range of the gradient was more
important than expected if the simple mixing model
occurred between freshwater and marine bacterial
communities. This indicated a net loss of freshwater
bacterial cells when they encountered marine water.
This trend is commonly found in estuarine systems (see
Painchaud et al. 1995 and references therein). This
decrease of bacterial numbers was concomitant with
a more important loss of activity as determined
from thymidine and leucine incorporation rates. This
suggests either that the activity of freshwater cells
decreased strongly in the first part of the gradient or
that an important fraction of active cells disappeared.

The decrease of activity for individual cells can be
the consequence of environmental changes, such as
the decrease of nutrient concentration and the increas-
ing salinity. Disappearance of active cells can be the
result of a lytic process due to an osmotic stress. How-
ever, at the beginning of the gradient only a limited
change in salinity was observed. From the literature
dedicated to the survival of allochthonous bacteria in
seawater (e.g. Gauthier 2000), it seems that such a
limited salinity change does not allow a significant
decrease in total bacterial counts. Another explanation
may be that active cells were preferentially grazed by
protozoa (Del Giorgio et al. 1996, Bernard et al. 2000).
This is congruent with the increasing number of het-
erotrophic protozoa from the begin-
ning to the end of the salinity gradient.
Furthermore, the decreasing cell size
of bacteria from the river to the sea
could be a consequence of this in-
creasing grazing pressure because het-
erotrophic protozoa more intensively
grazed large cells than small cells.

At the marine end-part of the gradi-
ent, where more oligotrophic condi-
tions predominate, overall thymidine
and leucine incorporation rates were
lower than in freshwater. However,
thymidine and leucine specific activi-
ties showed that cells in the marine
part of the gradient exhibited a rela-
tively high specific activity. Leucine
specific activities increased more than
thymidine specific activities, suggest-
ing an important bacterial protein syn-

thesis, which, in temperate estuaries, has been consid-
ered to be the sign of a survival strategy of bacterial
communities when they are submitted to oligotrophic
conditions (Shiah & Ducklow 1997).

There was a clear correspondence between the hy-
drological structure of the study area and the spatial
distribution of the 2 main groups identified by UPGMA
clustering of the samples on the basis of their DGGE
profile similarities. The location where the 2 groups
were discriminated corresponded to the area where
salinity values exhibited the largest changes (i.e. the
halocline). This result showed that the physical struc-
ture of the Rhone estuary precluded a strong mixing of
river and marine bacterial communities.

The genetic richness of the Rhone River and Medi-
terranean Sea bacterial assemblages expressed by the
number of bands in a DGGE profile was high com-
pared to that reported in other aquatic ecosystems
(Table 1). Diversity estimates from our study based on
the analysis of 24 samples ranged from 13 to 55 DGGE
bands for D-derived PCR products. It has to be kept in
mind, though, that very few studies reported in Table 1
have applied an appropriate sampling strategy to esti-
mate genetic richness at the ecosystem level. Such a
high genetic diversity may be the result of the interface
position of estuaries where continental and marine
bacterial communities are mixed. A link between
diversity and activity was further investigated by com-
paring both D- and R-DGGE profiles. Many studies in
molecular microbial ecology have used RNA as a
marker of (recent) cellular metabolic activity, since
active cells usually have a higher ribosomal RNA con-
centration (MacGregor 1999, see same paper for exam-
ples). In a recent study Schäfer et al. (2001) used RT-
PCR and DGGE to detect active bacterial populations

<table><caption>Table 1. Number of denaturing gradient gel electrophoresis (DGGE) bands (bacterial genetic richness) reported for different aquatic ecosystems (studies are ranked following decreasing maximum genetic richness)</caption>
  <thead>
    <tr>
      <th>Ecosystem</th>
      <th>No. of bands</th>
      <th>Source</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>Algae-detritus</td>
      <td>54</td>
      <td>Van Hannen et al. (1999)</td>
    </tr>
    <tr>
      <td>Rhone estuary</td>
      <td>47</td>
      <td>This study</td>
    </tr>
    <tr>
      <td>Mediterranean mesocosms</td>
      <td>24–40</td>
      <td>Schäfer et al. (2001)</td>
    </tr>
    <tr>
      <td>Activated-sludge biofilm</td>
      <td>15–37</td>
      <td>Santegoeds et al. (1998)</td>
    </tr>
    <tr>
      <td>Mediterranean Sea</td>
      <td>34–35</td>
      <td>This study</td>
    </tr>
    <tr>
      <td>Aegean Sea</td>
      <td>28–36</td>
      <td>Moeseneder et al. (1999)</td>
    </tr>
    <tr>
      <td>San Francisco Bay</td>
      <td>22–31</td>
      <td>Murray et al. (1996)</td>
    </tr>
    <tr>
      <td>Mediterranean mesocosm</td>
      <td>19–29</td>
      <td>Schäfer et al. (2000)</td>
    </tr>
    <tr>
      <td>Antarctic coastal waters</td>
      <td>8–29</td>
      <td>Murray et al. (1998)</td>
    </tr>
    <tr>
      <td>Tomales Bay</td>
      <td>15–24</td>
      <td>Murray et al. (1996)</td>
    </tr>
    <tr>
      <td>Lakes</td>
      <td>8–23</td>
      <td>Konopka et al. (1999)</td>
    </tr>
    <tr>
      <td>Biofilm of bivalve shell</td>
      <td>9–21</td>
      <td>Gillan et al. (1998)</td>
    </tr>
    <tr>
      <td>Meromictic lake (oxic zone)</td>
      <td>15–20</td>
      <td>Øvreas et al. (1997)</td>
    </tr>
    <tr>
      <td>Boreal forest lake</td>
      <td>6–15</td>
      <td>Lindström (1998)</td>
    </tr>
    <tr>
      <td>Hot spring cyanobacterial mats</td>
      <td>14</td>
      <td>Santegoeds et al. (1996)</td>
    </tr>
    <tr>
      <td>Shallow eutrophic lake</td>
      <td>6–10</td>
      <td>Jaspers &amp; Overmann (1997)</td>
    </tr>
  </tbody>
</table>
of their better efficiency in using scarce nutrients than
eukaryotes (Weisse 1993).

Observed bacterial abundance and incorporation
rates of tritiated thymidine and leucine in water sam-
ples taken along the transect were in the same range
as those previously reported in the same area (Kirch-
man et al. 1989, Martinez et al. 1991, Bianchi et al.
1994). The decrease of bacterial abundance observed
in the low salinity range of the gradient was more
important than expected if the simple mixing model
occurred between freshwater and marine bacterial
communities. This indicated a net loss of freshwater
bacterial cells when they encountered marine water.
This trend is commonly found in estuarine systems (see
Painchaud et al. 1995 and references therein). This
decrease of bacterial numbers was concomitant with
a more important loss of activity as determined
from thymidine and leucine incorporation rates. This
suggests either that the activity of freshwater cells
decreased strongly in the first part of the gradient or
that an important fraction of active cells disappeared.

The decrease of activity for individual cells can be
the consequence of environmental changes, such as
the decrease of nutrient concentration and the increas-
ing salinity. Disappearance of active cells can be the
result of a lytic process due to an osmotic stress. How-
ever, at the beginning of the gradient only a limited
change in salinity was observed. From the literature
dedicated to the survival of allochthonous bacteria in
seawater (e.g. Gauthier 2000), it seems that such a
limited salinity change does not allow a significant
decrease in total bacterial counts. Another explanation
may be that active cells were preferentially grazed by
protozoa (Del Giorgio et al. 1996, Bernard et al. 2000).
This is congruent with the increasing number of het-
erotrophic protozoa from the begin-
ning to the end of the salinity gradient.
Furthermore, the decreasing cell size
of bacteria from the river to the sea
could be a consequence of this in-
creasing grazing pressure because het-
erotrophic protozoa more intensively
grazed large cells than small cells.

At the marine end-part of the gradi-
ent, where more oligotrophic condi-
tions predominate, overall thymidine
and leucine incorporation rates were
lower than in freshwater. However,
thymidine and leucine specific activi-
ties showed that cells in the marine
part of the gradient exhibited a rela-
tively high specific activity. Leucine
specific activities increased more than
thymidine specific activities, suggest-
ing an important bacterial protein syn-

thesis, which, in temperate estuaries, has been consid-
ered to be the sign of a survival strategy of bacterial
communities when they are submitted to oligotrophic
conditions (Shiah & Ducklow 1997).

There was a clear correspondence between the hy-
drological structure of the study area and the spatial
distribution of the 2 main groups identified by UPGMA
clustering of the samples on the basis of their DGGE
profile similarities. The location where the 2 groups
were discriminated corresponded to the area where
salinity values exhibited the largest changes (i.e. the
halocline). This result showed that the physical struc-
ture of the Rhone estuary precluded a strong mixing of
river and marine bacterial communities.

The genetic richness of the Rhone River and Medi-
terranean Sea bacterial assemblages expressed by the
number of bands in a DGGE profile was high com-
pared to that reported in other aquatic ecosystems
(Table 1). Diversity estimates from our study based on
the analysis of 24 samples ranged from 13 to 55 DGGE
bands for D-derived PCR products. It has to be kept in
mind, though, that very few studies reported in Table 1
have applied an appropriate sampling strategy to esti-
mate genetic richness at the ecosystem level. Such a
high genetic diversity may be the result of the interface
position of estuaries where continental and marine
bacterial communities are mixed. A link between
diversity and activity was further investigated by com-
paring both D- and R-DGGE profiles. Many studies in
molecular microbial ecology have used RNA as a
marker of (recent) cellular metabolic activity, since
active cells usually have a higher ribosomal RNA con-
centration (MacGregor 1999, see same paper for exam-
ples). In a recent study Schäfer et al. (2001) used RT-
PCR and DGGE to detect active bacterial populations

<table><caption>Table 1. Number of denaturing gradient gel electrophoresis (DGGE) bands (bacterial genetic richness) reported for different aquatic ecosystems (studies are ranked following decreasing maximum genetic richness)</caption>
  <thead>
    <tr>
      <th>Ecosystem</th>
      <th>No. of bands</th>
      <th>Source</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>Algae-detritus</td>
      <td>54</td>
      <td>Van Hannen et al. (1999)</td>
    </tr>
    <tr>
      <td>Rhone estuary</td>
      <td>47</td>
      <td>This study</td>
    </tr>
    <tr>
      <td>Mediterranean mesocosms</td>
      <td>24–40</td>
      <td>Schäfer et al. (2001)</td>
    </tr>
    <tr>
      <td>Activated-sludge biofilm</td>
      <td>15–37</td>
      <td>Santegoeds et al. (1998)</td>
    </tr>
    <tr>
      <td>Mediterranean Sea</td>
      <td>34–35</td>
      <td>This study</td>
    </tr>
    <tr>
      <td>Aegean Sea</td>
      <td>28–36</td>
      <td>Moeseneder et al. (1999)</td>
    </tr>
    <tr>
      <td>San Francisco Bay</td>
      <td>22–31</td>
      <td>Murray et al. (1996)</td>
    </tr>
    <tr>
      <td>Mediterranean mesocosm</td>
      <td>19–29</td>
      <td>Schäfer et al. (2000)</td>
    </tr>
    <tr>
      <td>Antarctic coastal waters</td>
      <td>8–29</td>
      <td>Murray et al. (1998)</td>
    </tr>
    <tr>
      <td>Tomales Bay</td>
      <td>15–24</td>
      <td>Murray et al. (1996)</td>
    </tr>
    <tr>
      <td>Lakes</td>
      <td>8–23</td>
      <td>Konopka et al. (1999)</td>
    </tr>
    <tr>
      <td>Biofilm of bivalve shell</td>
      <td>9–21</td>
      <td>Gillan et al. (1998)</td>
    </tr>
    <tr>
      <td>Meromictic lake (oxic zone)</td>
      <td>15–20</td>
      <td>Øvreas et al. (1997)</td>
    </tr>
    <tr>
      <td>Boreal forest lake</td>
      <td>6–15</td>
      <td>Lindström (1998)</td>
    </tr>
    <tr>
      <td>Hot spring cyanobacterial mats</td>
      <td>14</td>
      <td>Santegoeds et al. (1996)</td>
    </tr>
    <tr>
      <td>Shallow eutrophic lake</td>
      <td>6–10</td>
      <td>Jaspers &amp; Overmann (1997)</td>
    </tr>
  </tbody>
</table>
and follow changes in the genetic diversity of active
bacterial populations during a mesocosm experiment.
Interestingly, the number of R-DGGE bands increased
during phases with increasing bacterial productivity
(estimated by leucine incorporation); thus, the changes
in number of R-derived bands were a useful indicator
of changes in general bacterial activity.

For freshwater samples, the number of bands found
in DNA and RNA profiles was different and the ratio of
RNA to DNA was only 0.45. Assuming that bands are
representative of different species, this suggest that
only a part of the constitutive populations was active at
the time of sampling. In contrast, the RNA to DNA ratio
was 0.75 for marine communities, showing that activity
was distributed within a large diversity of populations.

The linear decrease in the number of D-derived
bands found in the profile of freshwater communities
along the salinity gradient indicated that continental
bacterial populations were not able to significantly
affect the structure and composition of marine commu-
nities. However, a few bands initially found in the
freshwater profile (n < 5) were detected in both R- and
D-DGGE patterns determined for samples from the
end of the gradient. The corresponding increase of the
RNA/DNA number of bands may be considered to be
the result of adaptive processes to survive under
adverse conditions, which may necessitate the syn-
thesis of different stress proteins and thus previous
expression of different genes. If so, this process seems
to be operated by only a limited number of species
because there was an overall decrease in the total
number of cells. The fact that these freshwater popula-
tions were also detected in the RNA profile may also
suggest that they not only survive but even maintain
metabolic activity under marine conditions. Unfortu-
nately, our results do not allow for discrimination
between the 2 explanations.

The high ratio found between the number of R- and
D-derived bands in the marine community profiles
suggests that most populations were able to grow in
oligotrophic waters. To be able to survive and eventu-
ally to grow (e.g. to be capable of an efficient uptake of
scarce substrates), it may be important that these bact-
eria are able to maintain elevated levels of mRNA and
tRNA. This hypothesis has early been suggested by
Koch (1971) and verified *in vitro* by Morita (1982).

The structure of marine communities was strongly
affected by decreasing salinity. One might hypothe-
size that the decrease of D-derived bands found in the
seawater profile with decreasing salinity originated in
a high sensitivity of some marine species to small
changes in salinity. However, most probably, this pat-
tern was a consequence of the different bacterial
abundances in river versus marine samples. If the
mean cell counts obtained from marine waters (6.15 ×

10⁵ ml⁻¹) versus freshwater (4.6 × 10⁶ ml⁻¹) are consid-
ered, it can be easily demonstrated that mixing
marine with river waters would establish an exponen-
tial decrease of the ratio between theoretical abun-
dance of marine versus freshwater bacteria. Conse-
quently, marine bacteria are quickly outnumbered
and might not be detectable as distinct bands in
DGGE patterns.

In the case of this study, the lack of a relationship
between bacterial diversity and activity measurements
can be at least partly explained by hydrodynamic con-
ditions. In fact, along the salinity gradient, we have
sampled bacterial assemblages that either appeared
very different (such as the true Rhone and Mediter-
ranean Sea communities) and adapted to their specific
environment or were extracted from a very dynamic
area (plume) in which bacterial assemblages that were
formed by the mixing of river and seawater bacteria
probably do not have enough time to adapt (the resi-
dence time of the plume was estimated to be <6 h).
Crump et al. (1999) found a residence time of 1 to 2 d in
the case of the free-living bacterial communities in the
Columbia River estuary to be insufficient for the devel-
opment of an adapted estuarine assemblage. On the
other hand, the aggregate-attached bacterial commu-
nity of the Columbia River estuary seemed to be
adapted to the distinct estuarine conditions. Adapta-
tion of the community is possible due to the prolonged
residence time of particle-attached bacterial communi-
ties in the estuary, which was estimated to be 2 to 4 wk.
We hypothesize that only in estuarine systems where
the residence time of water from the mixing area is
long enough can we observe an adapted bacterial
community that can support a relationship between
activity and diversity.

To our knowledge, this is the first study that com-
bined bacterial diversity and activity parameters in an
attempt to get insight in the behavior of bacterial pop-
ulations along a salinity gradient. Further understand-
ing the role of bacterial populations in biogeochemical
processes occurring along environmental gradients
requires provision of information on the structure of
bacterial communities (i.e. relative abundance of pop-
ulations) and not only on richness. This is essential to
really investigate the behavior of targeted species in
these environments.

*Acknowledgements.* We gratefully acknowledge Muriel Petit and Teresa Guindulain for their contribution to the field work. We also acknowledge Jean-Jacques Naudin (Biodypar program) and the crew of the RV 'Téthys II', who gave us the opportunity to sample along the Rhone estuarine gradient and provided us with data on salinity and ammonium. Special thanks also to the 'Salins du Midi' company, which offered us laboratory facilities in Salins de Giraud. This work was supported by the European Community (MAS3-CT96-0047).
and follow changes in the genetic diversity of active
bacterial populations during a mesocosm experiment.
Interestingly, the number of R-DGGE bands increased
during phases with increasing bacterial productivity
(estimated by leucine incorporation); thus, the changes
in number of R-derived bands were a useful indicator
of changes in general bacterial activity.

For freshwater samples, the number of bands found
in DNA and RNA profiles was different and the ratio of
RNA to DNA was only 0.45. Assuming that bands are
representative of different species, this suggest that
only a part of the constitutive populations was active at
the time of sampling. In contrast, the RNA to DNA ratio
was 0.75 for marine communities, showing that activity
was distributed within a large diversity of populations.

The linear decrease in the number of D-derived
bands found in the profile of freshwater communities
along the salinity gradient indicated that continental
bacterial populations were not able to significantly
affect the structure and composition of marine commu-
nities. However, a few bands initially found in the
freshwater profile (n < 5) were detected in both R- and
D-DGGE patterns determined for samples from the
end of the gradient. The corresponding increase of the
RNA/DNA number of bands may be considered to be
the result of adaptive processes to survive under
adverse conditions, which may necessitate the syn-
thesis of different stress proteins and thus previous
expression of different genes. If so, this process seems
to be operated by only a limited number of species
because there was an overall decrease in the total
number of cells. The fact that these freshwater popula-
tions were also detected in the RNA profile may also
suggest that they not only survive but even maintain
metabolic activity under marine conditions. Unfortu-
nately, our results do not allow for discrimination
between the 2 explanations.

The high ratio found between the number of R- and
D-derived bands in the marine community profiles
suggests that most populations were able to grow in
oligotrophic waters. To be able to survive and eventu-
ally to grow (e.g. to be capable of an efficient uptake of
scarce substrates), it may be important that these bact-
eria are able to maintain elevated levels of mRNA and
tRNA. This hypothesis has early been suggested by
Koch (1971) and verified *in vitro* by Morita (1982).

The structure of marine communities was strongly
affected by decreasing salinity. One might hypothe-
size that the decrease of D-derived bands found in the
seawater profile with decreasing salinity originated in
a high sensitivity of some marine species to small
changes in salinity. However, most probably, this pat-
tern was a consequence of the different bacterial
abundances in river versus marine samples. If the
mean cell counts obtained from marine waters (6.15 ×

10⁵ ml⁻¹) versus freshwater (4.6 × 10⁶ ml⁻¹) are consid-
ered, it can be easily demonstrated that mixing
marine with river waters would establish an exponen-
tial decrease of the ratio between theoretical abun-
dance of marine versus freshwater bacteria. Conse-
quently, marine bacteria are quickly outnumbered
and might not be detectable as distinct bands in
DGGE patterns.

In the case of this study, the lack of a relationship
between bacterial diversity and activity measurements
can be at least partly explained by hydrodynamic con-
ditions. In fact, along the salinity gradient, we have
sampled bacterial assemblages that either appeared
very different (such as the true Rhone and Mediter-
ranean Sea communities) and adapted to their specific
environment or were extracted from a very dynamic
area (plume) in which bacterial assemblages that were
formed by the mixing of river and seawater bacteria
probably do not have enough time to adapt (the resi-
dence time of the plume was estimated to be <6 h).
Crump et al. (1999) found a residence time of 1 to 2 d in
the case of the free-living bacterial communities in the
Columbia River estuary to be insufficient for the devel-
opment of an adapted estuarine assemblage. On the
other hand, the aggregate-attached bacterial commu-
nity of the Columbia River estuary seemed to be
adapted to the distinct estuarine conditions. Adapta-
tion of the community is possible due to the prolonged
residence time of particle-attached bacterial communi-
ties in the estuary, which was estimated to be 2 to 4 wk.
We hypothesize that only in estuarine systems where
the residence time of water from the mixing area is
long enough can we observe an adapted bacterial
community that can support a relationship between
activity and diversity.

To our knowledge, this is the first study that com-
bined bacterial diversity and activity parameters in an
attempt to get insight in the behavior of bacterial pop-
ulations along a salinity gradient. Further understand-
ing the role of bacterial populations in biogeochemical
processes occurring along environmental gradients
requires provision of information on the structure of
bacterial communities (i.e. relative abundance of pop-
ulations) and not only on richness. This is essential to
really investigate the behavior of targeted species in
these environments.

*Acknowledgements.* We gratefully acknowledge Muriel Petit and Teresa Guindulain for their contribution to the field work. We also acknowledge Jean-Jacques Naudin (Biodypar program) and the crew of the RV 'Téthys II', who gave us the opportunity to sample along the Rhone estuarine gradient and provided us with data on salinity and ammonium. Special thanks also to the 'Salins du Midi' company, which offered us laboratory facilities in Salins de Giraud. This work was supported by the European Community (MAS3-CT96-0047).
LITERATURE CITED

Bianchi M, Bonin P, Feliatra (1994) Bacterial nitrification and denitrification rates in the Rhône river plume (northwest-ern Mediterranean Sea). Mar Ecol Prog Ser 103:197-202

Bernard L, Courties C, Servais P, Troussellier M, Petit M, Lebaron P (2000) Relationships among bacterial cell size, productivity, and genetic diversity in aquatic environ-ments using cell sorting and flow cytometry. Microb Ecol 40:148-158

Brosius J, Dull TJ, Sleeter DD, Noller HF (1981) Gene organi-sation and primary structure of a ribosomal RNA operon from *Escherichia coli*. *J Bacteriol* 148:107-127

Campbell L, Nolla HA, Vaulot D (1994) The importance of *Prochlorococcus* to community structure in the central North Pacific Ocean. Limnol Oceanogr 39:954-961

Crump BC, Armbrust EV, Baross JA (1999) Phylogenetic analysis of particle-attached and free-living bacterial com-munities in the Columbia River, its estuary, and the adja-cental coastal ocean. Appl Environ Microbiol 65:3192-3204

Del Giorgio PA, Gasol JM, Vaqué D, Mura P, Agusti S, Duarte CM (1996) Bacterioplankton community structure: protists control net production and the proportion of active bacte-ria in a coastal marine community. Limnol Oceanogr 41: 1169-1179

Ducklow HW, Carlson CA (1992) Oceanic bacterial produc-tion. Adv Microbiol Ecol 12:113-181

Ducklow HW, Shiah F (1993) Bacterial production in estuar-ies. In: Ford TE (ed) Aquatic microbiology. Blackwell Scientific Publications, Boston, p 261-287

Fuhrman JA, Azam F (1982) Thymidine incorporation area measure of heterotrophic bacterioplankton evaluation in marine surface waters: evaluation and field result. Mar Biol 66:109-120

Gauthier MJ (2000) Environmental parameters associated with the viable but nonculturable state. In: Colwell RR, Grimes DJ (eds) Nonculturable microorganisms in the environment. ASM Press, Washington, DC, p 87-112

Gillan DC, Speksnijder AGCL, Zwart G, De Ridder C (1998) Genetic diversity of the biofilm covering *Montacuta fer-ruginosa* (Mollusca, Bivalvia) as evaluated by denaturat-ing gradient gel electrophoresis analysis and cloning of PCR-amplified gene fragments coding for 16S rRNA. Appl Environ Microbiol 64:3464-3472

Goosen NK, Kromkamp J, Peene J, van Rijswilk P, van Breugel P (1999) Bacterial and phytoplankton production in the maximum turbidity zone of three European estuar-ies: the Elbe, Westerschelde and Gironde. J Mar Sci 22: 151-171

Jaspers E, Overmann J (1997) Separation of bacterial cells by isoelectric focusing, a new method for analysis of com-plex microbial communities. Appl Environ Microbiol 63: 3176-3181

Kirchman D, K'Nees F, Hodson, R (1985) Leucine incorpora-tion and its potential as a measure of protein synthesis by bacteria in natural aquatic systems. Appl Environ Micro-biol 49:599-607

Kirchman D, Soto Y, Van Wambeck F, Bianchi M (1989) Bacterial production in the Rhône river plume: effect of mixing on relationships among microbial assemblages. Mar Ecol Prog Ser 53:267-275

Koch AL (1971) The adaptive responses of *Escherichia coli* to a feast and famine existence. Adv Microb Physiol 6: 147-217

Konopka A, Bercot T, Nakatsu C (1999) Bacterioplankton community diversity in a series of thermally stratified lakes. Microb Ecol 38:126-135

Koroleff F (1976) Determination of amonia. In: Grasshoff K (ed) Methods of sea water analysis. Verlag Chemie, Wein-heim, p 126-133

Lebaron P, Servais P, Troussellier M, Courties C and 6 others (1999) Changes in bacterial community structure in sea-water mesocosms differing in their nutrient status. Aquat Microb Ecol 19:255-267

Legendre P, Vaudor A (1991) The R package: multidimen-sional analysis, spatial analysis. Département des Sci-ences Biologiques, Université de Montréal

Lindström ES (1998) Bacterioplankton community composi-tion in a boreal forest lake. FEMS Microb Ecol 27:163-174

Lochet F, Leveau M (1990) Transfers between a eutrophic ecosystem, the river Rhône, and an oligotrophic eco-system, the north-western Mediterranean Sea. Hydro-biologia 207:95-103

MacGregor BJ (1999) Molecular approaches to the study of aquatic microbial communities. Curr Opin Biotechnol 10:220-224

Martinez J, Soto Y, Vives-Rego J, Bianchi M (1991) Toxicity of CU, NI and alkylbenzene sulfonate (LAS) on the naturally occurring bacteria in the Rhone river plume. Environ Toxicol Chem 10:641-647

Moeseneder MM, Arrieta JM, Muyzer G, Winter C, Herndl GJ (1999) Optimization of terminal-restriction fragment length polymorphism analysis for complex marine bacterioplankton communities and comparison with denaturing gradient gel electrophoresis. Appl Environ Microbiol 65:3518-3525

Morita RY (1982) Starvation-survival of heterotrophs in the marine environment. Adv Microb Ecol 6:171-198

Murray AE, Hollibaugh JT, Orrego C (1996) Phylogenetic compositions of bacterioplankton from two California estuaries compared by denaturing gradient gel electro-phoresis of 16S rDNA fragments. Appl Environ Microbiol 62:2676-2680

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Naudin JJ, Cauwet G, Chrétiennot-Dinet MJ, Deniaux B, Devenon JL, Pauc H (1997) River discharge and wind influence upon particulate transfer at the land-ocean interaction: case study of the Rhône river plume. Estuar Coast Shelf Sci 45:303-316

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Øvreas L, Forney L, Daae FL, Torsvik V (1997) Distribution of bacterioplankton in meromictic lake Saelenvannet, as determined by denaturing gradient gel electrophoresis of PCR-amplified gene fragments coding for 16S r RNA. Appl Environ Microbiol 63:3367-3373

Painchaud J, Lefavivre D, Therriault JC, Legendre L (1995) Physical processes controlling bacterial distribution and variability in the upper St. Lawrence estuary. Estuaries 18:433-444

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LITERATURE CITED

Bianchi M, Bonin P, Feliatra (1994) Bacterial nitrification and denitrification rates in the Rhône river plume (northwest-ern Mediterranean Sea). Mar Ecol Prog Ser 103:197-202

Bernard L, Courties C, Servais P, Troussellier M, Petit M, Lebaron P (2000) Relationships among bacterial cell size, productivity, and genetic diversity in aquatic environ-ments using cell sorting and flow cytometry. Microb Ecol 40:148-158

Brosius J, Dull TJ, Sleeter DD, Noller HF (1981) Gene organi-sation and primary structure of a ribosomal RNA operon from *Escherichia coli*. *J Bacteriol* 148:107-127

Campbell L, Nolla HA, Vaulot D (1994) The importance of *Prochlorococcus* to community structure in the central North Pacific Ocean. Limnol Oceanogr 39:954-961

Crump BC, Armbrust EV, Baross JA (1999) Phylogenetic analysis of particle-attached and free-living bacterial com-munities in the Columbia River, its estuary, and the adja-cental coastal ocean. Appl Environ Microbiol 65:3192-3204

Del Giorgio PA, Gasol JM, Vaqué D, Mura P, Agusti S, Duarte CM (1996) Bacterioplankton community structure: protists control net production and the proportion of active bacte-ria in a coastal marine community. Limnol Oceanogr 41: 1169-1179

Ducklow HW, Carlson CA (1992) Oceanic bacterial produc-tion. Adv Microbiol Ecol 12:113-181

Ducklow HW, Shiah F (1993) Bacterial production in estuar-ies. In: Ford TE (ed) Aquatic microbiology. Blackwell Scientific Publications, Boston, p 261-287

Fuhrman JA, Azam F (1982) Thymidine incorporation area measure of heterotrophic bacterioplankton evaluation in marine surface waters: evaluation and field result. Mar Biol 66:109-120

Gauthier MJ (2000) Environmental parameters associated with the viable but nonculturable state. In: Colwell RR, Grimes DJ (eds) Nonculturable microorganisms in the environment. ASM Press, Washington, DC, p 87-112

Gillan DC, Speksnijder AGCL, Zwart G, De Ridder C (1998) Genetic diversity of the biofilm covering *Montacuta fer-ruginosa* (Mollusca, Bivalvia) as evaluated by denaturat-ing gradient gel electrophoresis analysis and cloning of PCR-amplified gene fragments coding for 16S rRNA. Appl Environ Microbiol 64:3464-3472

Goosen NK, Kromkamp J, Peene J, van Rijswilk P, van Breugel P (1999) Bacterial and phytoplankton production in the maximum turbidity zone of three European estuar-ies: the Elbe, Westerschelde and Gironde. J Mar Sci 22: 151-171

Jaspers E, Overmann J (1997) Separation of bacterial cells by isoelectric focusing, a new method for analysis of com-plex microbial communities. Appl Environ Microbiol 63: 3176-3181

Kirchman D, K'Nees F, Hodson, R (1985) Leucine incorpora-tion and its potential as a measure of protein synthesis by bacteria in natural aquatic systems. Appl Environ Micro-biol 49:599-607

Kirchman D, Soto Y, Van Wambeck F, Bianchi M (1989) Bacterial production in the Rhône river plume: effect of mixing on relationships among microbial assemblages. Mar Ecol Prog Ser 53:267-275

Koch AL (1971) The adaptive responses of *Escherichia coli* to a feast and famine existence. Adv Microb Physiol 6: 147-217

Konopka A, Bercot T, Nakatsu C (1999) Bacterioplankton community diversity in a series of thermally stratified lakes. Microb Ecol 38:126-135

Koroleff F (1976) Determination of ammonia. In: Grasshoff K (ed) Methods of sea water analysis. Verlag Chemie, Wein-heim, p 126-133

Lebaron P, Servais P, Troussellier M, Courties C and 6 others (1999) Changes in bacterial community structure in sea-water mesocosms differing in their nutrient status. Aquat Microb Ecol 19:255-267

Legendre P, Vaudor A (1991) The R package: multidimen-sional analysis, spatial analysis. Département des Sci-ences Biologiques, Université de Montréal

Lindström ES (1998) Bacterioplankton community composi-tion in a boreal forest lake. FEMS Microb Ecol 27:163-174

Lochet F, Leveau M (1990) Transfers between a eutrophic ecosystem, the river Rhône, and an oligotrophic eco-system, the north-western Mediterranean Sea. Hydro-biologia 207:95-103

MacGregor BJ (1999) Molecular approaches to the study of aquatic microbial communities. Curr Opin Biotechnol 10:220-224

Martinez J, Soto Y, Vives-Rego J, Bianchi M (1991) Toxicity of CU, NI and alkylbenzene sulfonate (LAS) on the naturally occurring bacteria in the Rhone river plume. Environ Toxicol Chem 10:641-647

Moeseneder MM, Arrieta JM, Muyzer G, Winter C, Herndl GJ (1999) Optimization of terminal-restriction fragment length polymorphism analysis for complex marine bacterioplankton communities and comparison with denaturing gradient gel electrophoresis. Appl Environ Microbiol 65:3518-3525

Morita RY (1982) Starvation-survival of heterotrophs in the marine environment. Adv Microb Ecol 6:171-198

Murray AE, Hollibaugh JT, Orrego C (1996) Phylogenetic compositions of bacterioplankton from two California estuaries compared by denaturing gradient gel electro-phoresis of 16S rDNA fragments. Appl Environ Microbiol 62:2676-2680

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Winter C, Moeseneder MM, Herndl J (2001) Impact of UV radiation on bacterioplankton community composition. Appl Environ Microbiol 67:665–672
Sahm K, Berninger UG (1998) Abundance, vertical distribu-
tion, and community structure of benthic prokaryotes from
permanently cold marine sediments (Svalbard, Arctic
Ocean). Mar Ecol Prog Ser 165:71–80

Santegoeds CM, Nold SC, Ward DM (1996) Denaturing gra-
dient gel electrophoresis used to monitor the enrichment
culture of aerobic chemoorganotrophic bacteria from a
hot spring cyanobacterial mat. Appl Environ Microbiol
62:3922–3928

Santegoeds CM, Ferdelman TG, Muyzer G, De Beer D (1998) Structural and functional dynamics of sulfate-reducing populations in bacterial biofilms. Appl Environ Microbiol 64:3731–3739

Schäfer H, Muyzer G (2001) Denaturing gradient gel electrophoresis in marine microbial ecology. In: Paul J (ed) Methods in microbiology, Vol 30. Academic Press, London, p 425–468

Schäfer H, Servais P, Muyzer G (2000) Successional changes in the genetic diversity of a marine bacterial assemblage during confinement. Arch Microbiol 173:138–145

Schäfer H, Bernard L, Courties C, Lebaron P and 7 others (2001) Microbial community dynamics in Mediterranean nutrient-enriched seawater mesocosms: changes in the genetic diversity of bacterial populations. FEMS Microbiol Ecol 34:243–253

Servais P (1990) Estimation de la production bactérienne en milieu marin par mesure du taux de synthèse protéique. Oceanol Acta 13:229–235

Servais P (1995) Measurement of the incorporation rates of four amino-acids into proteins for estimating bacterial production. Microb Ecol 29:115–128

Editorial responsibility: Dittmar Hahn,
Newark, New Jersey, USA

Shiah FK, Ducklow HW (1997) Bacterioplankton growth re-
sponses to temperature and chlorophyll variations in estu-
aries measured by thymidine:leucine incorporation ratio.
Aquat Microb Ecol 13:151–159

Sneath PHA, Sokal RR (1973) Numerical taxonomy: the principles and practice of numerical classification. WH Freeman, San Francisco

Soto Y, Bianchi M, Martinez J, Vives Rego J (1993) Seasonal evolution of microplanktonic communities in the estuarine front ecosystem of the Rhône river plume (North-western Mediterranean sea). Estuar Coast Shelf Sci 37: 1–13

Trousellier M, Courties C, Vaquer A (1993) Recent applica-
tions of flow cytometry in aquatic microbial ecology. Biol
Cell 78:111–121

Trousellier M, Courties C, Lebaron P, Servais P (1999) Flow cytometric discrimination of bacterial populations in seawater based on SYTO 13 staining of nucleic acids. FEMS Microbiol Ecol 29:319–330

Van Hannen EJ, Mooij W, Van Agterveld MP, Gons HJ, Laan-
broek HJ (1999) Detritus-dependent development of the
microbial community in an experimental system: qualita-
tive analysis by denaturating gradient gel electrophoresis.
Appl Environ Microbiol 65:2478–2484

Weisse T (1993) Dynamics of autotrophic picoplankton in marine and freshwater ecosystems. In: Jones JG (ed) Advances in microbial ecology. Plenum Press, New York, p 327–370

Winter C, Moeseneder MM, Herndl J (2001) Impact of UV radiation on bacterioplankton community composition. Appl Environ Microbiol 67:665–672

Submitted: June 22, 2001; Accepted: February 13, 2002

Proofs received from author(s): April 4, 2002