Published Ahead of Print 24 January 2014. 10.1128/AEM.02916-13.

2014, 80(7):2071. DOI:Appl. Environ. Microbiol. Connie LovejoyVani Mohit, Philippe Archambault, Nicolas Toupoint and Gene SequencingRevealed via High-Throughput 16S rRNA Temperate Coastal Lagoon during Summer,Free-Living Bacterial Communities in a Phylogenetic Differences in Attached and

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Phylogenetic Differences in Attached and Free-Living BacterialCommunities in a Temperate Coastal Lagoon during Summer,Revealed via High-Throughput 16S rRNA Gene Sequencing

Vani Mohit,a Philippe Archambault,b Nicolas Toupoint,b Connie Lovejoya

Département de Biologie, Québec-Océan and Institut de Biologie Intégrative et des Systèmes, Université Laval, Québec, Québec, Canadaa; Institut des Sciences de la Mer(ISMER), Université du Québec à Rimouski (UQAR), Rimouski, Québec, Canadab

Most of what is known about coastal free-living and attached bacterial diversity is based on open coasts, with high particulateand nutrient riverine supply, terrestrial runoffs, and anthropogenic activities. The Magdalen Islands in the Gulf of St. Lawrence(Canada) are dominated by shallow lagoons with small, relatively pristine catchments and no freshwater input apart from rain.Such conditions provided an opportunity to investigate coastal free-living and attached marine bacterial diversity in the absenceof confounding effects of steep freshwater gradients. We found significant differences between the two communities and markedtemporal patterns in both. Taxonomic richness and diversity were greater in the attached than in the free-living community,increasing over summer, especially within the least abundant bacterial phyla. The highest number of reads fell within the SAR 11clade (Pelagibacter, Alphaproteobacteria), which dominated free-living communities. The attached communities had deeperphylum-level diversity than the free-living fraction. Distance-based redundancy analysis indicated that the particulate organicmatter (POM) concentration was the main variable separating early and late summer samples with salinity and temperaturechanges also significantly correlated to bacterial community structure. Our approach using high-throughput sequencing de-tected differences in free-living versus attached bacteria in the absence of riverine input, in keeping with the concept that marineattached communities are distinct from cooccurring free-living taxa. This diversity likely reflects the diverse microhabitats ofavailable particles, implying that the total bacterial diversity in coastal systems is linked to particle supply and variability, withimplications for understanding microbial biodiversity in marine systems.

In marine systems, bacteria are the main agents of carbon cyclingand nutrient regeneration, converting dissolved organic matter

to biomass, which fuels microbial food webs and transfers energyand carbon to higher trophic levels (1). Bacterioplankton are fre-quently categorized as either free living or attached to particles (2,3). Attached bacteria may have very high local concentrationscompared to free-living bacteria (4) and also provide nutrition formacroscopic filter feeders (5). However, free-living bacteria areoften more abundant than particle-attached bacteria in diversemarine (6) as well as freshwater ecosystems (7). Free-living andattached communities can differ both morphologically and phys-iologically, for example, attached bacteria are often larger (8) andare reported to have lower growth efficiency than free-living bac-teria, with comparatively less bacterial biomass produced perquantity of organic substrate taken up (9). Some studies reporthigher per-cell metabolic activity for particle-attached communi-ties compared to free-living communities (10, 11), while otherstudies report the opposite (12, 13). Interestingly, Ghiglione et al.(6) reported diel changes in bacterial activity, with the free-livingfraction being more active during the day and the attached frac-tion more active at night, consistent with different functional ca-pacities in the two communities, which may be reflected in taxon-omy. Such observations suggest that the two communities arefavored under different conditions, and understanding the dy-namics and diversity of bacterial communities is an importantstep in characterizing an ecosystem as well as developing indica-tors to study ecosystem health and function.

There have been many studies on freshwater, estuarine, openocean, and coastal ocean free-living and attached bacteria (2, 8,14). Recently, high-throughput sequencing has been used to test

whether attached and free-living communities are taxonomicallydistinct, and results have tended to indicate that along estuarinesalinity gradients, the two communities differ when salinities arelower but are similar at higher oceanic salinities (15, 16). High-throughput 16S rRNA gene surveys have also tended to supportthe notion that bacteria are strongly influenced by estuarine salin-ity gradients (17, 18), and the question arises as to whether thereare true marine bacteria that form attached communities orwhether they are fundamentally pelagic bacteria that are tempo-rarily associated with particles; if this were the case, all or themajority of attached bacteria would be represented in the pelagiccommunity in systems where such salinity gradients did not exist(19). Alternatively, attached communities that formed in coastalversus open oceans could be fundamentally different. One ap-proach to test these scenarios is to investigate enclosed coastalmarine systems, such as coastal lagoons that are not influenced orare little influenced by freshwater but maintain oceanic salinities.The microbial ecology and biodiversity of coastal lagoons are im-portant for recreational and ecosystem services but are often se-

Received 28 August 2013 Accepted 10 January 2014

Published ahead of print 24 January 2014

Editor: K. E. Wommack

Address correspondence to Connie Lovejoy, connie.lovejoy@bio.ulaval.ca.

Supplemental material for this article may be found at http://dx.doi.org/10.1128/AEM.02916-13.

Copyright © 2014, American Society for Microbiology. All Rights Reserved.

doi:10.1128/AEM.02916-13

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verely impacted by anthropogenic stressors (20), and deriving thenatural state of bacterial communities in such coastal systems isproblematic. Although there are reports on the community com-position of attached and free-living bacteria in coastal oceans (21–23), coastal lagoons, which are defined as “shallow water bodiesseparated from the ocean by a barrier, connected at least intermit-tently to the ocean by one or more restricted inlets. . .” (24), arelittle investigated (25). The few such studies were in lagoons se-verely impacted by anthropogenic activities and freshwater inputsfrom rivers or streams (25). To address this lack of data, we inves-tigated the attached and free-living communities in a lagoon in theMagdalen Island Archipelago, which is in the southern Gulf of St.Lawrence (Canada). The Magdalen Islands are a narrow archipel-ago linked by shallow lagoons with limited interchange with theGulf of St. Lawrence (26). The lagoons are relatively pristine, withno industrial development in the surrounding catchment and lit-tle agricultural activity. The Havre-aux-Maisons (HAM) lagoon,with only minor mussel farming activity (�5% of the lagoon sur-face area) (27), restricted inflow from the sea, and little freshwaterinfluence except from rainfall (28), is an ideal site to investigatedifferences between attached and free-living communities in ashallow, exclusively marine environment.

We used a high-throughput amplicon approach targeting theV6-V8 region of the 16S rRNA gene (23) to facilitate comparisonsto other marine studies (23, 29, 30). Our goals were to (i) identifythe attached and free-living communities in the water column,including the less common taxa; (ii) investigate temporal commu-nity changes during summer, given that coastal marine bacterialcommunities vary over time (6); and (iii) to identify likely driversof any temporal pattern in the distribution of these two types ofbacterial communities. For this, we examined the influence ofmeteorological events, as well as temperature, salinity, nutrients,particulates, and other environmental variables, on the commu-nities by way of constrained ordination analysis. We hypothesizedthat bacterial communities would be influenced relative to themagnitude of environmental change over time. In the Magdalenislands, persistent winds mean that the water column is wellmixed, providing no physical structure and a uniform environ-ment for free-living bacteria. In contrast, particulate material ar-

rives from many diverse sources, and particles could representmany distinct habitats for attached bacteria. We would predictincreased diversity with increasing particle concentrations if thetwo communities were not the same. If the two communities werethe same, they would be predicted to change in concert over thesummer.

MATERIALS AND METHODSSite description. Havre-aux-Maisons lagoon (Fig. 1) is a shallow lagoonwith a maximum depth of 6 m, surface area of 30 km2, and catchment areaof ca. 63 km2 (Centre d‘Expertise Hydrique du Québec). HAM is classifiedas a restricted coastal lagoon (26) with only two connections for exchange.The first is a restricted tidal inlet, where water enters from the Gulf of St.Lawrence along the southeast corner via a narrow channel. The second, inthe northeast corner, acts mostly as an outlet and is a narrow channelconnected to Grande-Entrée lagoon (GEL). Because of the lower tidalamplitude in HAM (26), it has a higher residual water level than theadjacent GEL, and water mostly flows out from HAM into the GEL. Fre-quent high winds, �15 m s�1 (28), are a defining characteristic of theMagdalen Islands, and water column mixing is mainly due to the wind-driven currents, as tides alone are not sufficient for complete water re-newal in the lagoon (31). Water residence time decreases from ca. 45 days,when only tidal action is considered, to 25 days, when prevailing windsessentially push water out toward the GEL (31). Nutrient concentrationsand phytoplankton biomass are characteristically low throughout thesummer (28, 32).

Sample collection. Because of the low spatial heterogeneity within thewell-mixed lagoon (B. Pequin and C. Lovejoy, personal communication)and logistic restraints, samples along with ancillary data were collectedfrom a single sampling site (47°25= 730�N, 61°48=832�W). Sampling wasapproximately every 2 weeks during the summer, from 16 June to 8 Sep-tember 2009. The 5-m-deep site was also part of a concurrent study ex-amining growth of juvenile mussels with 24 pearl nets, each containing 50mixed 0� and 1� age class mussels suspended 2 m from the superficialsediment. The water was collected via a submersible electric pump withinthe well-mixed water column. To avoid inadvertent contamination bymussel fecal pellets from the pearl nets, the pump was kept above the netsat 2.5 m. Oxygen saturation was measured every meter down the watercolumn using a YSI 550A oxygen profiler, and salinity and temperaturewere taken with a YSI 30/25 FT profiler (both from Yellow Springs Instru-ments Inc., OH, USA). Rainfall and wind data for the 4 days prior to andon the day of sampling were from the airport weather station located ca. 4

FIG 1 Study site in Havre-aux-Maisons (HAM) lagoon, Magdalen Islands, Gulf of St. Lawrence. The Grande-Entrée lagoon (GEL) is also indicated on themap.

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km from the study site and were available from Environment Canada(http://www.climate.weatheroffice.gc.ca). Water level measurementsabove the chart datum (water level) were from Fisheries and Oceans Can-ada (http://www.meds-sdmm.dfo-mpo.gc.ca). Day length data wereestimated using the National Research Council Canada sunrise/sunsetcalculator (http://www.nrc-cnrc.gc.ca/eng/services/sunrise/index.html).Total chlorophyll (Chl a) samples were collected by filtering 500 ml ofwater onto GF/F filters (0.7-�m pore size; Whatman, USA). For the smallfraction, water was first prefiltered through a 3.0-�m-pore-size polycar-bonate (PC) filter (Millipore, USA), and the filtrate was collected on GF/Ffilters. Chl a concentrations were determined by spectrofluorimetry (CaryEclipse, USA) before and after acidification (33). Nutrients were analyzedwith a Seal Autoanalyzer 3 (Seal Analytical, Germany) specifically fornitrite plus nitrate (referred to as nitrate) (34), soluble reactive phosphate(SRP) (35), and silicate (36). Samples for flow cytometry (FCM) were firstfixed in the dark with gluteraldehyde (final concentration, 1% [vol/vol])and stored at �80°C until analysis. High-nucleic-acid (HNA) and low-nucleic-acid (LNA) Bacteria and Archaea (referred to as bacteria) weredetected following nucleic acid staining with SYBR green (Invitrogen,USA). Chlorophyll autofluorescence was used to detect picophytoeu-karyotes (0.2 to 2 �m) and nanophytoeukaryotes (2 to 20 �m), and phy-coerythrin was used to detect pico- and nanocyanobacteria by FCM as inBelzile et al. (37). Particulate organic matter (POM) was determined bycollecting material from 2 liters of water filtered through prewashed andpreweighed GF/F filters, which were dried at 45°C for 48 h and combustedat 450°C for 4 h (38). Duplicate samples for Chl a, nutrients, and FCM andtriplicate samples for POM analysis were run.

Environmental microbial DNA was collected by filtering waterthrough a 50-�m nylon mesh to remove any fecal pellets and zooplanktonwith associated microbiomes (C. Lovejoy, unpublished data). Materialthen was sequentially filtered onto a 3-�m-pore-size PC filter and a 0.2-�m-pore-size Sterivex unit (Millipore, USA) with a peristaltic pumpingsystem at a flow rate of ca. 0.75 to 1 liter h�1. When the filtration ratedropped below this level, the volume filtered (1.5 to 2 liter) was noted andthe filtrations were stopped, since generally this indicates that the firstfilter (3 �m) is becoming obstructed. Throughout this study, we considerthe 3- to 50-�m fraction as attached and the �3-�m fraction as free living(2, 15, 23, 25). The filters were stored at �80°C in a buffer solution (40mmol liter�1 EDTA, 50 mmol liter�1 Tris, 0.75 mol liter�1 sucrose, pH8.3) until processing.

DNA extraction and pyrosequencing. Samples were treated with ly-sozyme and proteinase K (39). DNA from the 3.0-�m filters and 0.2-�mSterivex units was then extracted using a saline extraction protocol (40)with added lysozyme (1 mg/ml, final concentration), proteinase K (0.2mg/ml), and sodium dodecyl sulfate (0.01%). Following extraction, DNAwas eluted in 1� TE buffer (10 mM Tris-HCl, 1 mM EDTA, pH 7.5) andstored at �80°C. The V6 to V8 region of the 16S rRNA gene (41–43) wasamplified. PCR amplification was performed with the forward primerB969F (5=-ACGCGHNRAACCTTACC-3=), which included Roche’s mul-tiplex identifiers (MIDs), and the reverse primer BA1406R (5=-ACGGGCRGTGWGTRCAA-3=) (42). PCRs were run in triplicate in a 50-�l reac-tion mixture that consisted of 3 different concentrations of DNA templateper sample, varying from ca. 2.3 � 10�3 to 2.2 ng �l�1, in 1� Phusion HFbuffer (New England BioLabs, Inc.), 200 �M each deoxynucleosidetriphosphate (dNTP), 0.5 �M each forward and reverse primer, and 0.02U/�l Phusion DNA polymerase. Amplification of the 16S rRNA gene wasperformed on a Bio-Rad C1000 thermal cycler with the following ampli-fication program: initial denaturation at 98°C for 30 s, 30 cycles of 98°Cfor 10 s, annealing at 55°C for 30 s, extension at 72°C for 30 s, and a finalextension of 4.30 min at 72°C. PCRs were run and purified as in Comeauet al. (42). The resulting amplicon length was verified by electrophoresison 1% agarose gels, and the absence of primer dimers (�100-bp prod-ucts) was verified. Purified products were quantified spectrophotometri-cally on a Nanodrop ND 1000 (Nanodrop). Equal concentrations of PCRproducts from each of the MID-tagged amplicons were pooled and run on

a 1/4 plate of the 454 GS FLX system (Roche Applied Science, Indianap-olis, IN) at the Institut de Biologie Intégrative et des Systèmes (IBIS),Université Laval Plate-forme d’Analyses Génomiques, Québec, Canada.The target amplification product was 400 to 500 nucleotides (nt) long.

Data analysis. The resulting reads were analyzed using MOTHUR(44) and BioEdit v7.0.9 (Tom Hall, Ibis Biosciences, Carlsbad, CA).MOTHUR was run by the Calcul Canada’s CLUMEQ high-performancecomputing facility, Université Laval. Preliminary denoising wasperformed in MOTHUR. Reads less than 300 nt and those containinghomopolymers of �7 indels were removed at this point. A preliminaryclassification was done on the remaining reads using a modifiedGreenGenes97 database (greengenes.lbl.gov/); briefly, we removed se-quences with little taxonomic information (those unclassified at the phy-lum level) and added genus information based on a consensus betweenthe original GreenGenes classification and the results of the Classifier toolfrom the RDP database (45) using the 95% bootstrap cutoff value (46).Reads classed as chloroplasts were removed at this step. Reads were thencompared against the bacterial SILVA database (47) using the ksize 9parameter. Chimeras were identified using the UCHIME (48) commandin MOTHUR and removed. The remaining read alignment was verifiedusing BioEdit (49), and badly aligned reads (i.e., reads causing large gapsor many gaps, suggesting sequencing errors) were deleted. The remainingreads were grouped into operational taxonomic units (OTUs) based on97% similarity using the furthest neighbor clustering method inMOTHUR. Singletons, defined as OTUs containing only 1 read with asingle occurrence in the combined data from all samples, were removed.Finally, to provide statistical robustness when comparing diversity mea-sures among samples, the reads were randomly resampled so that all sam-ples had the same number of reads (50). The final 3,894 reads per samplewere then classified based on the modified GreenGenes97 database.Chao1 diversity and rarefaction estimates were carried out in MOTHUR.Beta diversity measures were performed using QIIME v1.7.0 (51) in whichphylogenetic information was integrated to compare microbial commu-nities. FastTree (http://www.microbesonline.org/fasttree/) was used forthe construction of test phylogenetic trees, which were further used inQIIME. The unweighted-pair group method using arithmetic means(UPGMA) clustering was performed on both weighted and unweightedUniFrac distance matrices to build a UPGMA tree. Unweighted UniFracanalysis gives greater importance to the rare taxa than weighted analysis.To determine the robustness of the UPGMA clustering, jackknife betadiversity and clustering analyses were carried out using 1,000 permuta-tions by resampling 2,920 reads per sample, which represented 75% of thetotal number of sequences per sample (52). Linear regression analysis wasused to test for significant trends in the diversity indices over the summer,and a residual plot was constructed to verify normality and homoscedas-ticity (53).

PRIMER software (v6) was used for a similarity percentage (SIMPER)(54) test to determine which taxa contributed the most to the averageBray-Curtis dissimilarity between the attached and free-living communi-ties. SIMPER calculates the overall percent contribution that each taxonmakes to the average dissimilarity between two groups and lists the taxa indecreasing order with respect to their importance in discriminating twosets of samples (54). Both abundance and presence/absence data wereused for the SIMPER analysis.

To further assess the beta diversity between attached and free-livingbacteria, a phylogenetic accumulation curve was constructed for whichthe number of OTUs was plotted against sequence similarity thresholds(80% to 100%) used to define the OTUs. The range of similarity cutoffswithin the V6 to V8 regions, 80%, 90%, 97%, and 99%, nominally esti-mates phylum, class, genus, and species within Bacteria (55, 56). Thephylogenetic diversity accumulation analysis is a way of examining thedegree of phylogenetic relatedness among taxa within each sample orcommunity (30). One-way analysis of similarity (ANOSIM) (PRIMERv6) was performed on square root-transformed data to test the null hy-pothesis that there was no difference between the phylogenetic diversity

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patterns of attached compared to free-living bacterial communities. If theR statistic (57) is closer to 1, then samples within the same category aremore similar to each other than to those of other categories.

Distance-based redundancy analysis (dbRDA) (58), which is a con-strained ordination analysis, was used to determine the influence of envi-ronmental and meteorological parameters on sample distribution. Testedexplanatory variables included temperature, oxygen, salinity, SRP, ni-trate, silicate, water level, and day length (Table 1), as well as pico- andnanocyanobacteria, pico- and nanophytoplankton, total (�0.7 �m) andsmall-fraction Chl a (0.7 to 3 �m) (Table 2), and rain and wind data forthe actual sampling day and the 4 preceding days (see Fig. S1 in the sup-plemental material). dbRDA uses sample scores from the principle coor-dinate analysis (PCoA) as the species data for the redundancy analysis(RDA). Bray-Curtis distance was calculated for the square root-trans-formed data, which were then used for the PCoA analysis. Forward selec-tion and Monte Carlo estimation were used to select the environmentalvariables that best explained the sample distribution and to test the signif-icance of those variables, respectively. Explanatory variables having sig-nificant conditional effects or partial contribution to the variation in OTUdistribution (P � 0.15) were retained. At this significance level, i.e., 0.15,elimination of variables that have a biological contribution in the model isavoided (59). A final RDA was run that included only the best explanatoryenvironmental variables. The constrained ordination analysis was per-formed using CANOCO v4.5 (60). The cumulative average values of rainand wind data for the actual sampling day and 4 preceding days (see Fig.S1 in the supplemental material) were calculated for inclusion in thedbRDA analysis. Spearman’s rho correlation with permutations was cal-culated using PAST software (http://folk.uio.no/ohammer/past/) to testfor significant relationships (P � 0.01) between environmental variablesand/or bacterial taxa. For normally distributed data, Pearson correlation

(in PAST) was also used for some of the pairwise comparisons. A 0.01significance level was chosen over a 0.05 level to reduce type I error (61).All normality tests were performed with PAST via the Shapiro-Wilk test.

SRA accession number. The raw reads have been deposited in theNCBI Sequence Read Archive (SRA; http://www.ncbi.nlm.nih.gov/sra)under the study accession number SRP027405.

RESULTSEnvironmental setting. The water column of the HAM lagoonwas well mixed on all days sampled, with no indication of strati-fication by either temperature or oxygen saturation values (notshown), and values from a depth of 2.5 m are given (Table 1). Thelagoon was well oxygenated throughout summer 2009, and thewarmest temperatures were in August. Nutrient concentrationswere low, with nitrate at �1 �mol liter�1, SRP below detection(�0.0l �mol liter�1) to 0.45 �mol liter�1, and silicate from 0.42 to1.34 �mol liter�1 (Table 1). Values for POM ranged from 0.7 to1.33 mg liter�1 and were greatest in late summer (Fig. 2). Over thesummer, total Chl a values ranged from 1.1 �g liter�1 on 16 July to2.1 �g liter�1 on 3 September. Over the summer, the �3-�m Chla fraction contributed from 24 to 95% of the total (Table 2), withthe highest proportions on 25 August (91%) and 3 September(95%). For the 16 July sample, the level for the �3-�m Chl afraction was slightly greater than the total Chl a concentration,which was likely because of sample variability at low chlorophyllconcentrations. Phytoplankton cell concentrations from FCMshowed that picophytoeukaryotes were always in excess of nano-phytoeukaryotes, except on 11 August. Similarly, concentrationsof picocyanobacteria were always greater than those for the nano-cyanobacteria (Table 2). For the bacteria, the proportion of HNAcells relative to the total bacteria increased over summer, with thelowest proportion on 16 June (39.6%) and the highest proportionon 3 September (66.1%). Total bacterial concentrations also in-creased over the summer, with a maximum of 5.26 � 106 cellsml�1 on 25 August. Spearman rank correlation and Pearson cor-

TABLE 1 Environmental dataa

DateTemp(°C)

O2

(%) SalSRP(�M)

Nitrate(�M)

Silicate(�M)

WLb

(m)DL(h)

16 June 13.3 101.0 30.4 0.16 0.98 0.42 0.69 17.2902 July 15.4 103.3 30.6 0.03 0.85 0.82 0.30 17.2016 July 18.3 102.2 30.7 0.20 0.92 1.21 0.76 16.8128 July 19.1 95.0 30.9 0.27 0.85 0.65 0.75 16.3111 Aug 19.7 88.2 30.9 0.45 0.94 1.32 1.13 15.5925 Aug 21.0 89.2 30.8 0.11 0.93 1.34 0.88 14.8103 Sept 16.2 99.6 30.7 0.03 1.02 0.71 0.96 14.2908 Sept 16.6 93.3 30.6 0.01 0.95 1.07 1.17 14.00a Data were taken at the 2.5-m sampling depth and include water level (WL) and daylength (DL). Nitrate indicates nitrate plus nitrite. Sal, salinity; SRP, soluble reactivephosphorus.b Average water level above chart datum measured between 9 and 11 a.m.

TABLE 2 Biological data

Date

Bacteria(�103 cells ml�1)

Cyanobacteria(�103 cellsml�1)

Phytoplankton(�103 cellsml�1)

Chlc

a (�g liter�1)

Total HNAa Pico Nano Pico Nano Total Smallb

16 June 1,440 573 (40) 0.3 0.0 6.6 3.2 1.7 0.4 (24)02 July 2,803 1,208 (43) 2.1 0.1 43.4 8.2 1.2 0.9 (73)16 July 2,303 1,147 (50) 4.6 0.0 77.8 7.8 1.1 1.4 (127)28 July 2,491 1,007 (40) 12.0 0.1 35.2 9.0 2.0 0.9 (47)11 August 3,316 1,233 (37) 12.7 0.2 7.3 8.8 1.9 1.1 (56)25 August 5,265 3,012 (57) 26.8 0.1 62.7 6.8 2.0 1.8 (91)03 September 5,181 3,429 (66) 56.1 0.3 73.1 14.2 2.1 2.0 (95)08 September 4,422 2,373 (54) 14 0.1 96.4 7.8 1.6 1.2 (70)

a Data in parentheses are percentages of bacteria classified as HNA.b Data in parentheses indicate the percentage of the total.c Chl a in total (�0.7 �m) and small (0.7 to 3 �m) fractions.

FIG 2 Chao1 richness of the attached and free-living bacterial communitiesand POM concentrations plotted on the secondary axis; the trend line (brokenline) shows the significant increase through summer for POM (P 0.02). Thesignificant increasing trend is shown for the attached bacteria (P 0.018)versus a nonsignificant trend (P 0.239) for free-living bacteria. Abbrevia-tions: June, JUN; July, JUL; August, AUG; September, SEP.

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relation were used to explore potential relationships among bio-logical and environmental variables with significance detected forthe following. Salinity and water temperature were strongly posi-tively correlated (Spearman’s rho 0.93; P � 0.01). Concentra-tions of nanocyanobacteria were correlated with POM (Spear-man’s rho 0.83; P � 0.01) and LNA bacteria (Spearman’s rho 0.77; P � 0.01). Concentrations of picocyanobacteria were corre-lated with LNA, HNA, and POM (Spearman’s rho 0.73 to 0.80;P � 0.01). POM was also significantly correlated with HNA cellabundance (Pearson’s r 0.89; P � 0.01).

Rainy days were infrequent during summer, with high rainevents (up to 60 mm) only occurring twice: 4 days before 16 Juneand 4 days before 3 September (see Fig. S1 in the supplementalmaterial). The total monthly rainfall recorded was 111.4 mm inJune, 72.6 mm in July, 128.4 mm in August, and 51.2 mm inSeptember. However, there was no rain on most days over thesummer. Wind was mostly from the northeast (not shown), andthe highest wind speeds were during a storm 4 days before the 3September sampling date, reaching gusts of over 90 km h�1. Highwinds were also recorded 2 days before the 25 August sample (seeFig. S1).

Diversity and richness indices. We identified 3,455 OTUsfrom the attached communities and 1,690 OTUs in the free-livingcommunities (see Table S1 in the supplemental material). Rar-efaction analysis (not shown) suggested that both the total at-tached and total free-living diversity approached that of an as-ymptote (at the 97% similarity level). Plotting Chao1 richness(Fig. 2) over the summer indicated that OTU richness increased

significantly in the attached community (by linear regression, r2 0.71; P 0.018) but not in the free-living community (Fig. 2).Attached bacterial richness was always greater than that of thefree-living bacterial communities.

Taxonomic identification and betadiversity. The attachedbacterial community was dominated by Proteobacteria and Bacte-roidetes (Fig. 3A), which together accounted for �60% of thereads. The Proteobacteria in the attached fraction were mostly Al-phaproteobacteria and Gammaproteobacteria (Fig. 3B); within theGammaproteobacteria were Oceanospirillales, Chromatiales, andEnterobacteriales (not shown). The free-living proteobacterialcommunity was dominated by Alphaproteobacteria (Fig. 3B). On25 August, 50% of the free-living bacterial reads were Cyanobac-teria (Fig. 3A), with little change in the proportions of differentProteobacteria classes (Fig. 3B). Other frequent phyla in all of thesamples were Verrucomicrobia and Actinobacteria. Less commonbacterial phyla, here defined as phyla having �1% of the totalreads of a sample, were much more prevalent in the attached bac-terial fraction (Fig. 3A).

The phylogenetic diversity accumulation curves (Fig. 4) high-light the significantly greater differences (by ANOSIM, R 0.96;P 0.001; 999 permutations) between attached and free-livingcommunities compared to differences within the two categories.Over the wide range of similarity thresholds, the phylogenetic di-versity in the attached fraction was always greater than that of thefree-living bacterial fraction, as also suggested by the Chao1 re-sults (Fig. 2). The wider distance within attached communitycurves compared to the free-living curves also indicate greater

FIG 3 (A) Phylum-level percent contribution to the total number of reads. The category “Less common” includes the phyla where the percent contribution toeach sample is less than 1%. Note that out of a total of 24 phyla, 22 occur in the attached and 10 in the free-living communities. (B) Percent contribution ofseparate classes within the Proteobacteria.

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differences between the individual attached compared to free-liv-ing communities. In addition, both unweighted (Fig. 5) andweighted UniFrac clustering (not shown) revealed a clear separa-tion between the attached and free-living bacterial communitiesbut also showed that early summer samples (June and July) dif-fered from those of late summer (August and September). Theunweighted UniFrac analysis is shown, providing information onthe influence of less common taxa compared to a weighted UniF-rac. Less common taxa were more prevalent in the attached bac-terial community, strongly contributing to the difference between

the attached and free-living communities. The unweighted UniF-rac showed the strongest temporal clustering.

At the phylum level, the greatest contribution to the dissimi-larity between the two fractions was by the less common phyla(SIMPER, unweighted analysis) that were more frequent in theattached community. Planctomycetes and Chlorobi had the largestcontribution (each 8.38%) to the dissimilarity between attachedand free-living bacterial communities (see Table S2 in the supple-mental material). Twelve genera were identified (SIMPER,weighted analysis) as contributing the most to the dissimilaritybetween the attached and free-living bacterial communities basedon relative abundance. These were plotted against communitysimilarity determined by the UniFrac analysis based on presence/absence data (Fig. 5). These 12 genera contributed 18.5% ofthe dissimilarity between the two categories, with differences in theproportion of Pelagibacter (Alphaproteobacteria) contributing themost to the dissimilarity (4.2%). Pelagibacter was the most fre-quently recovered genus in the samples, contributing up to a max-imum of 40% of reads in the attached and 74% of reads in thefree-living fractions. An approximate maximum likelihood treewas built using FastTree just with the Pelagibacter reads (notshown). Although there were a number of clades, none were dis-tinguished as exclusively or predominantly attached versus free-living Pelagibacter. In addition to Pelagibacter, Synechococcus, Ul-vibacter, Winogradskyella, Sulfitobacter, and Haliscomenobacterwere among these top 12 genera and occurred in all samples. Mostof these, including Pelagibacter and Sulfitobacter, had more vari-able relative abundances in the attached compared to the free-living fraction. Maximum Synechococcus reads were detected inthe free-living fraction in the 25 August sample, and the largestproportion of Sulfitobacter occurred in the 16 July samples forboth communities. This maximum in Synechococcus 16S rRNA

FIG 4 Phylogenetic diversity accumulation curve for the attached versus free-living bacterial communities. The proportion of OTUs (log scale) was plottedagainst the sequence similarity threshold (%) used to define the OTUs forattached (ATT) or free-living (FREE) results.

FIG 5 UPGMA tree indicating the unweighted-UniFrac clustering of the attached and free-living communities based on UniFrac phylogenetic distance.Bootstrap support values according to the Jackknife analysis are at the nodes. The bubble chart shows the top 12 genera contributing to the dissimilarity betweenattached and free-living bacterial communities (SIMPER analysis); bubble size indicates the proportion of each taxon to the total in each sample. The class is inparentheses. Attached bacteria are shown as black circles; free-living bacteria are shown as gray circles.

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gene reads did not correspond to picocyanobacterial abundancefrom the FCM data on 3 September. However, Synechococcus 16SrRNA gene reads were relatively high in both the free-living(12.2%) and attached fraction (13.5%). A separate MAFFT align-ment and phylogeny of the Synechococcus reads failed to detect anyconsistent differences between the attached and free-living Syn-echococcus (not shown). A relatively large proportion of unclassi-fied Gomphosphaeriaceae (62) was detected in the 3 Septemberattached sample. These were correlated with attached Synechococ-cus (Spearman’s rho, r2 0.88; P � 0.01). Escherichia and unclas-sified Sinobacteraceae were only found in the attached commu-nity, with the highest proportions of Escherichia reads on 2 Julyand 11 August (Fig. 5). The Escherichia reads were subjected to aseparate BLASTn search in the NCBI database (http://www.ncbi.nlm.nih.gov/), and the closest matches were to E. coli. The othertaxa which contributed significantly to the dissimilarity betweenthe attached and free-living bacterial communities were Verruco-microbium, Congregibacter genera, and unidentified genus-leveltaxa in Flammeovirgaceae and Sinobacteraceae families (Fig. 5). Allof these were more frequent in the attached fraction.

dbRDA analysis of summer samples. Out of the 25 environ-mental variables tested, POM and salinity were the only two thatwere significantly correlated to the distribution of the attachedbacterial OTUs (P � 0.05) Fig. 6A). POM and salinity had thehighest partial contributions, 24% and 18%, respectively, to thevariation in OTU abundance of the attached community. Bothalso contributed significantly to the separation between early andlate summer samples (Fig. 6A). Since Pelagibacter, which is usuallydescribed as free-living, was dominant in both attached and free-living bacterial communities, a dbRDA analysis was run with Pe-lagibacter removed, and the output was the same: POM and salin-ity were still significantly correlated with the variability in theOTU distribution (not shown).

For the free-living fraction, POM and temperature (Fig. 6B)were significantly (P � 0.05) correlated with the variation in OTUdistribution; they had the highest partial contributions of 28%and 19%, respectively, to the variation. As with the attached frac-tion, early summer (16 June, 02 July, and 16 July) and late summersamples (28 July, 11 August, 25 August, 03 September, and 08September) were separated in the ordination plot, with the great-est correlation attributed to POM.

DISCUSSIONAttached versus free living. Our pyrosequencing approach iden-tified differences between the attached and free-living communi-ties in the HAM lagoon and a temporal clustering in both com-munities with a separation of early and late summer samples. Thephylogenetic differences and seasonal patterns were evident irre-spective of the clustering method: the UniFrac weighted and un-weighted analyses indicated clear differences in phylogenetic di-versity between the two fractions. OTU abundance data and thephylogenetic accumulation analysis also showed differences be-tween the two fractions regardless of the OTU similarity cutoffsused. The SIMPER analysis detected differences in relative abun-dance of different genera as well as differences relative to presence/absence of bacterial phyla. The weighted SIMPER analysis pointedto the most common taxa contributing to the separation of theattached and free-living bacterial communities, and the un-weighted SIMPER analysis showed the importance of the lesscommon taxa. The most common reads in both fractions wereclassified as Pelagibacter from the SAR 11 clade, but these wereproportionally fewer in the attached fraction, in which Gamma-proteobacteria were also common. To our knowledge, this is thefirst report of the attached and free-living bacterial communitiesin a closed temperate coastal lagoon. By comparison, open coastalregions and estuaries are relatively well studied, for example, off-shore from the Columbia River (2), the Mediterranean sea (23),and the southwestern Bay of Fundy (22). Differences between at-tached and free-living communities were reported in all of thesestudies. Tropical and subtropical lagoons are closed systems moreoften than temperate coastal areas, but as of yet there are no stud-ies using high-throughput sequencing published to our knowl-edge. By way of comparison, clone library studies, which target themost abundant taxa, have shown that the degree of similarity be-tween the attached and free-living communities in tropical andsubtropical lagoons is linked to seasonal patterns, with greaterdifferences during the dry season in tropical regions (63) andgreater differences during the rainy season in the subtropical la-goons (25).

The dominance of Pelagibacter in the water column was notsurprising, since SAR 11 is the most abundant bacterial clade inthe world’s ocean and is usually considered free living (64, 65).There are few cultured representatives and a single described spe-

FIG 6 Distance-based RDA ordination plot representing the environmental variables that have a significant influence (arrows) on the distribution of summerattached (A) and free-living (B) bacterial communities (samples are black circles) based on OTU abundance.

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cies, Pelagibacter ubique (65), which is thought to scavenge nutri-ents at very low concentrations (66), such as those in the lagoon.Here and elsewhere, attached bacteria are defined as those that areretained on a filter of a given pore size and free-living bacteria asthose that pass though the filter (2, 67). The presence of Pelagibac-ter in the attached fraction may be a technical artifact where, forexample, the filters clog and retain smaller particles (6). The op-posite may also occur, and attached bacteria can be released intothe free-living fraction during sampling manipulation (2). Biolog-ical explanations for Pelagibacter in both fractions would includeit forming close physical associations with other cells (68) orforming colonies under certain conditions (69), in which case thebacteria are attached to each other and not necessarily to par-ticles. Steindler et al. (70) observed clumping of Pelagibacter cellsthrough pilus production in carbon-limiting and dark conditionsin cultures, suggesting that Pelagibacter cells are able to form closeassociations with each other via upregulation of the pilin gene(pilA); whether this occurs under natural conditions is unknown.Members of the SAR 11 clade, to which Pelagibacter belongs, havebeen recovered elsewhere in the attached fraction using 3-�m-pore-size filters (23) and on larger filters of up to 30-�m pore size(67); however, determining whether this is a filtration artifact isnot possible in the absence of microscopy observations. To ad-dress this, Fuchsman et al. (67) took into account the relativeabundance of taxa between the two fractions and defined free-living bacteria as those with at least 4-fold greater abundance thanthe same taxon in the attached fraction and defined SAR 11 in theBlack Sea as free living. Given the high abundance of Pelagibactercells in HAM, this taxa would have the highest probability of beingretained on clogged filters, and as it was 5-fold more abundant inthe free-living fraction, it likely belongs in that category. Synechoc-occus was also persistently recovered in both size fractions, al-though it is also considered free living (71). However, there wasonly one date (25 August) on which the difference between the 3-to 50-�m and 0.2- to 3-�m Synechococcus samples was sufficientlyhigh to categorize it as free living using the criteria of Fuchsman etal. (67). Interestingly, there are reports of Synechococcus attachedto particles (72), and Malfatti and Azam (68) observed Synechoc-occus cells attached to one or more heterotrophic bacterial cellsusing atomic force microscopy (AFM), suggesting that at leastsome Synechococcus cells are legitimate members of an attachedcommunity. Attached Synechococcus in the HAM lagoon couldbenefit from the dissolved organic carbon released by their bacte-rial partners and nutrients made available from the extracellularenzymatic activities of the associated bacteria (73). Some free-living bacteria can even spend most of their time in nutrient ag-glomerations in the surroundings of or within particles (74). Thiscould be the case for the other free-living cells found in the at-tached fraction. Some of the taxonomic overlap may also havebeen due to exchange between attached and free-living fractions,with release of cells from the aggregates that are free until theyencounter another particle and rejoin the attached bacterial frac-tion (75). Grossart (74) described bacteria as either truly free liv-ing or as those that spend most but not all of their lifestyle attachedto particles. Particles are, in fact, risky environments for attachedbacteria, given that they are more liable to be preyed upon. Onestrategy to counteract this is to attach to particles part of the time(76). Hollibaugh et al. (77) and Ghiglione et al. (6) concluded thatmost attached bacteria were also in the free-living fraction, sug-gesting little difference between the two communities. However,

methodological differences between those studies and our studymake comparisons difficult, since the earlier studies’ cutoff valuesfor the different size fractions were �1 in reference 77 and �0.8�m in reference 6 and may have included a higher proportion offree-living bacteria in the attached fraction. In addition, denatur-ing gradient gel electrophoresis (6) and capillary electrophoresis-single-strand conformation polymorphisms (77) do not capturerarer taxa (78). Overall, our use of high-throughput sequencinghighlighted the contributions of those rare taxa to the attachedbacterial communities. In HAM, the two fractions always clus-tered apart, with the attached bacterial community more diverseat all taxonomic levels, including phyla. Finally, we note thatgroups such as Flavobacteria (Bacteroidetes), especially Ulvibacterand Winogradskyella, were predominantly in the attached frac-tion, consistent with these genera being commonly attached toalgal cells (79, 80). Overall, while likely pelagic bacteria were foundin the attached fraction, the converse was not true, and within theattached fraction were groups that are exclusively associated withparticles.

Other dominant genera in the summer bacterial communi-ties. Reads matching Sulfitobacter were detected in both attachedand free-living bacterial communities. Rooney-Varga et al. (22)and Blažina et al. (73) also recorded Sulfitobacter in both commu-nities. Despite the well-oxygenated water column, the HAM sed-iments are mostly anoxic, with detectable sulfide concentrations(81, 82, and V. Mohit, personal observation). Sulfitobacter maypersist in low-oxygen microzones within particles and oxidize sul-fites (83) released into the water column by mixing or bioturba-tion of the sediment (84). Sulfitobacter has also been reportedassociated with zooplankton fecal pellets (85), consistent with ac-tive particle degradation.

Representatives of the Verrucomicrobia class were among themost common taxa in our attached community. Verrucomicrobiaare difficult to cultivate and were considered rare prior to theapplication of metagenomics. This class is now frequently re-ported, and Verrucomicrobia seem to be widely distributed in themarine environment (86). Another unusual find in the summerattached bacteria was Escherichia coli, which may be alarminggiven that attached bacteria can be assimilated by mussels (5).However, the serotype or toxicity of the strain was not resolvedhere. Other attached bacterial taxa included the bacteriochloro-phyll-containing gammaproteobacterium genus Congregibacter(87) and the cyanobacterium family Gomphosphaeriaceae. Gom-phosphaeriaceae are likely colonial (62) and are larger than 3 �m.

In this study, we estimated the diversity of bacteria in two sizefractions and compared them. Although bacteria living on�50-�m particles may have contributed to the overall diversity inthe system, others have found that most attached bacterial diver-sity is in the �40-�m fraction. Almeida and Alcantara (88) ob-served a sharp drop in the contribution of bacteria attached to�40-�m particles to 6.7% of the total attached bacterial abun-dance in a tidal lagoon, Ria de Alveiro, Portugal. Particles in thesize ranges of �3 to 10 and �10 to 40 �m had 41.3 and 44.8% ofthe total attached bacteria, respectively, compared to 7.2% forthe �1- to 3-�m particles (88). In addition, because largerparticles sediment more quickly, their persistence in the watercolumn would be more ephemeral and they would be poorlysampled in the 2-liter volumes. Since they were not sampled, itcould be that a proportion of bacterial diversity in the lagoonwas not detected.

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Environmental variables explaining the summer bacterialcommunity structure. Bacterial diversity may follow seasonalpatterns in coastal waters, e.g., in the Western English Channel(50, 89) and in the coastal lagoon in Arroyo Burro, Santa Barbara(25). These patterns have been linked over shorter time scales toenvironmental variability, including temperature, phosphate andsilicate levels (50), and rainfall (25); on longer time scales, daylength seemed to explain seasonal variation in a 6-year study (86).The phylogenetic diversity of bacterioplankton has also beenlinked to the diversity of available substrate (90). Among all envi-ronmental variables tested, we found that POM concentration inthe water column was the main factor influencing both fractions.This was especially marked for the attached bacterial community,which showed a significant increase in diversity over the summer,with POM following the same trend. Attached bacterial diversitywas also higher in the Arroyo Burro coastal lagoon (25) and wascorrelated with external sources of particles during the wet seasonor resuspension of sediment. Increased POM concentrations overthe summer is common in other coastal open waters, for example,in the northwest Mediterranean (91), the Bay of Biscay (21), andthe Ionian Sea (92). These increases are thought to be due to theaccumulation of phytoplankton following blooms, particulatematerial from runoffs following rainfall, and resuspension of sed-iment from high winds. POM is not chemically or structurallyuniform, as it is generated from many sources and with large spa-tiotemporal heterogeneity (3). Its properties can also change overtime due to bacterial activity (93). Attached bacteria produce ex-oenzymes that target specific complex molecules, and the avail-ability and stoichiometry of particulate organic matter likely se-lects for bacteria with specific degradation systems (94). Similar toother coastal lagoons (20), the eelgrass Zostera marina occurs inthe shallow regions of the Magdalen Islands lagoons (95–97). Zos-tera marina increases in biomass over the summer growing sea-son, consistent with a seasonal contribution to POM; maximumfoliar biomass is in August, and stem density increases from July toSeptember (98). Other sources of particulate material may includeinput from aquatic bird colonies mostly located along the south-ern end of HAM lagoon on the Bird Rock Sanctuary Islet, materialderived from mussel farming activity, such as mussel drop offs(27), and fecal material that can be rapidly colonized by bacteria(99). Phytoplankton can also contribute to formation of transpar-ent exopolymer particles (TEP), which is an important agent foraggregation of particles (100). Over the summer, winds are con-stant, mixing the shallow water column of the HAM lagoon (101)and contributing to persistent particle resuspension from the sed-iment. In addition, residual mean flows and water level are rele-vant for the transport of dissolved and suspended organic matter.Circulation within the HAM lagoon is restricted (26), especiallynear our sampling site at the center of the lagoon, where waterresidence time can be as long as 45 days or more when only tideaction is considered (31). These factors would result in an accu-mulation of particles in multiple states of degradation in the watercolumn, overall increasing the diversity of substrates available forattached bacteria over time. In addition, salinity, which has a di-rect link with suspended matter in the flocculation of particles,was the second most significant variable contributing to the vari-ation in attached OTU abundance. Increasing salinity decreasesthe electrostatic repulsion between particles, causing them to ap-proach close to each other, which then leads to flocculation (102)and facilitates attachment of bacterial cells to particles (103). Sa-

linity is a strong selector of bacterial taxa (104–106). It has animpact on cellular osmotic stress, and different phylogeneticgroups may react differently to this physiological stress (104). Thegradual increase in salinity over the summer and periodic input ofrain could also directly influence the character of particulate ma-terial. Slight changes in salinity were linked to the makeup of theattached bacterial communities and may have been an indirect ordirect consequence of periodic rains either by increased floccula-tion, runoff from land, or increased winds and resuspension ofparticles that accompanied rain. However, we found no signifi-cant correlation of POM with rain and wind events going back 5days prior to sampling (not shown), consistent with a gradualaccumulation of POM in the lagoon over summer (107).

There are the caveats that some of the increasing diversitycould be due to the accumulation of nonliving DNA over thesummer, since DNA from dead cells can persist in the environ-ment (108), and that the residual water level is higher in HAMthan in the adjacent GEL (26), contributing to the longer resi-dence time of cells in the system. Arguing against this as the pri-mary source of diversity was the fact that the increasing diversitywas attributable to a higher diversity of less common taxa (un-weighted SIMPER analysis) entering the pool of species, which ismore consistent with increasing numbers of niches for particulargroups. Less common taxa may act as a type of seed bank of taxathat become abundant when conditions are favorable (109) ormay always be rare if they are functional specialists (110). At-tached bacteria have a metabolic advantage in that they can min-imize time of starvation, increase the efficiency for resource ex-ploitation in terms of carbon and energy, and have a higherevolutionary success rate (74). Therefore, it is more advantageousfor a bacterial phylotype to spend part of its lifestyle as attachedcells, and this is probably why we find a higher diversity of at-tached bacteria.

The concentration of POM was also a significant factor whichappears to influence the variation in free-living communities overthe summer. The free-living community could profit from theactivity of the attached bacteria releasing dissolved organic matterinto the water via exoenzymatic activities, providing needed sub-strate for the free-living microbial community (73). In addition toPOM, temperature also appeared to influence the free-living frac-tion of the HAM. Salinity and temperature are among the mainenvironmental drivers of marine bacterial diversity (111), andeven small changes may have had an effect. Temperature andPOM quality have also been reported to directly affect free-livingbacterial abundance and production (21) but may also influencecommunity composition. Cyanobacteria, for example, thrive inwarmer waters (112), and Synechococcus populations decline withtemperature, especially when coupled to high rain events (113). InHAM, the sudden increase in Synechococcus reads coincided withthe highest temperature recorded, on August 25.

Abundance of HNA bacterial cells. The increase in the pro-portion of HNA bacteria from 25 August followed temperature,Chl a, and POM maxima and was also positively correlated topicocyanobacterial cell abundance and POM. A positive link be-tween the picocyanobacteria and HNA bacteria was previouslyreported in a study of the Iberian Peninsula (114). Several studieshave inferred that HNA content is indicative of more active bac-terial cells (115, 116), but we were not able to address this questionusing the data available. The positive correlation of HNA bacteriaand POM could be because HNA are associated with the attached

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fraction and have higher activity than LNA bacteria. Consistentwith this was the increased diversity of attached bacteria in latesummer (3 and 8 September) along with more HNA.

Concluding remarks. Our approach via pyrosequencing cap-tured sufficient bacterial diversity to clearly separate attached andfree-living communities and highlight the temporal pattern in thebacterial community structure over the summer in a coastal la-goon. The retention of POM was the best explanation for theincreasing attached bacterial diversity and temporal pattern ob-served in the bacterial community. Significant differences werefound between the attached and free-living bacterial communitiesand overall diversity in the absence of estuarine circulation andlarge freshwater inputs in the Havre-aux-Maisons lagoon. Thissuggests that multiple specialist attached bacterial taxa contributeto overall marine bacterial biodiversity, and that particles contrib-ute to overall coastal bacterial diversity in marine natural systemsthat are not under the influence of rivers.

ACKNOWLEDGMENTS

We thank Claude Belzile from ISMER (UQAR, Rimouski) and LisandreSolomon for providing the nutrient and FCM data and Bérangère Pequinfor laboratory assistance and valuable discussions. Comments from anon-ymous reviewers on earlier versions of the manuscript were greatly appre-ciated.

We acknowledge funding from the Natural Sciences and EngineeringResearch Council of Canada (NSERC) for a strategic grant led by G. Fuss-mann (McGill) and coinvestigators P.A., C.L., and others. Additionalfunds were provided by Fonds de Recherche du Québec (FQRNT) toQuébec Océan and Ressources Aquatiques Québec (RAQ).

We acknowledge the contribution from the Centre d’Innovation del’Aquaculture et des Pêches du Québec (Merinov) for laboratory spaceand access to the experimental site.

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