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ARTICLE Analysis of bacterial communities associated with the benthic amphipod Diporeia in the Laurentian Great Lakes Basin

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Andrew D. Winters, Terence L. Marsh, Travis O. Brenden, and Mohamed Faisal

Abstract: Bacterial communities play important roles in the biological functioning of crustaceans, yet little is known about their diversity, structure, and dynamics. This study was conducted to investigate the bacterial communities associated with the benthic amphipod Diporeia, an important component in the Great Lakes foodweb that has been declining over the past 3 decades. In this study, the combination of 16S rRNA gene sequencing and terminal restriction fragment length polymorphism revealed a total of 175 and 138 terminal restriction fragments (T-RFs) in Diporeia samples following treatment with the endonucleases HhaI and MspI, respectively. Relatively abundant and prevalent T-RFs were affiliated with the genera Flavobacterium and Pseudomonas and the class Betaproteobacteria. T-RFs affiliated with the order Rickettsiales were also detected. A significant difference in T-RF presence and abundance (P = 0.035) was detected among profiles generated for Diporeia collected from 4 sites in Lake Michigan. Comparison of profiles generated for Diporeia samples collected in 2 years from lakes Superior and Michigan showed a significant change in diversity for Lake Superior Diporeia but not Lake Michigan Diporeia. Profiles from one Lake Michigan site contained multiple unique T-RFs compared with other Lake Michigan Diporeia profiles, most notably one that represents the genus Methylotenera. This study generated the most extensive list of bacteria associated with Diporeia and sheds useful insights on the microbiome of Great Lakes Diporeia that may help to reveal potential causes of the decline of Diporeia populations. Key words: bacteria, Diporeia spp., Laurentian Great Lakes. Résumé : Les communautés bactériennes jouent un rôle important dans le fonctionnement biologique de crustacés, mais on sait peu de choses sur leur diversité, la structure et la dynamique. Cette étude a été menée pour étudier les communautés bactériennes associées a` la Diporeia amphipode benthique, un élément important dans la chaîne alimentaire des Grands Lacs qui a été en baisse au cours des trois dernières décennies. Dans cette étude, la combinaison de séquençage du gène de l’ARNr 16S et « terminal restriction fragment length polymorphism » a révélé un total de fragments de 175 et 138 de restriction de la borne (« T-RFs ») dans des échantillons Diporeia après le traitement par les endonucléases HhaI et MspI, respectivement. T-RFs relativement abondantes et les plus répandus étaient affiliés a` des genres Flavobacterium et Pseudomonas, et la Betaprotéobactéries de classe. T-RFs affiliés a` l’ordre des Rickettsiales ont également été détectés. Une différence significative en présence T-RF et l’abondance (P = 0,035) a été détectée chez les profils générés pour Diporeia recueillies auprès de quatre sites dans le lac Michigan. La comparaison des profils générés pour les échantillons prélevés Diporeia en deux ans des lacs Supérieur et Michigan a montré un changement significatif dans la diversité pour le lac Supérieur diporeia mais pas du lac Michigan Diporeia. Profils d’un site du lac Michigan contenaient de multiples T-RFs uniques par rapport aux autres profils lac Michigan Diporeia, notamment celui qui représente le genre Methylotenera. Cette étude a généré la liste la plus complète des bactéries associées aux Diporeia et apporte des informations utiles sur le microbiome de Grande Lacs Diporeia qui peuvent aider a` révéler les causes possibles du déclin des populations de Diporeia. Mots-clés : bactéries, Diporeia spp., des Grands Lacs Laurentiens.

Introduction Detritivorous amphipods belonging to the genus Diporeia are important food resources for numerous Great Lakes fish species (Barbiero et al. 2011) and, thus, serve as coupling mechanisms between pelagic and benthic zones of the Great Lakes. Historically, Diporeia have been the dominant benthic macroinvertebrate in the Great Lakes, averaging over 7000 individuals/m2, reaching mean densities as high as 12 216 /m2, and accounting for approximately 70% of the macrobenthic community of the Great Lakes (Nalepa 1987, 1989). However, Diporeia abundances have been declining from the majority of its habitats throughout 4 of the 5 Great Lakes (Dermott and Kerec 1997; Nalepa et al. 1998, 2005, 2007; Dermott 2001; Lozano et al. 2001; Barbiero and Tuchman

2002; Barbiero et al. 2011). As a result, there has been increased interest in studying the biology of Diporeia in the Great Lakes. The aim of the current study is make information on the bacterial communities associated with Diporeia available to the scientific community to potentially shed light on the declines. Considering the ubiquity and large abundances of crustaceans in marine and freshwater environments, tight associations between crustaceans and bacteria can widely affect bacterial behavior, growth, and biogeochemical activities (reviewed in Tang et al. 2010). Microbial communities within the Great Lakes ecosystem have been studied for many years using basic microscopy and culturing-based techniques (Inniss and Mayfield 1978; Maki and Remsen 1981; Ishii et al. 2006). However, since a large fraction of

Received 3 July 2014. Revision received 15 October 2014. Accepted 25 October 2014. A.D. Winters and T.O. Brenden. Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA. T.L. Marsh. Center for Microbial Ecology and Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI 48824, USA. M. Faisal. Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA; Department of Pathobiology and Diagnostic Investigation, 177K Food Safety and Toxicology Building, Michigan State University, East Lansing, MI 48824, USA. Corresponding author: Mohamed Faisal (e-mail: [email protected]). Can. J. Microbiol. 61: 72–81 (2015) dx.doi.org/10.1139/cjm-2014-0434

Published at www.nrcresearchpress.com/cjm on 3 November 2014.

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Fig. 1. Map of the Laurentian Great Lakes and the Finger Lakes showing sampling sites for this study. A circle indicates a sample was analyzed with terminal restriction fragment length polymorphism (T-RFLP), a triangle indicates a sample was analyzed with 16S rDNA sequencing, and a square indicates a sample was analyzed with both T-RFLP and 16S rDNA sequencing.

microbial life cannot be cultured, a severe dearth regarding the taxonomic diversity of these microbial communities currently exists. Because microbial communities can evolve rapidly in response to environmental perturbations and could be used as indicators of change, it is important to acquire baseline information against which future changes could be identified. In recent years, cultivation-independent surveys employing sequence analysis of 16S small-subunit rRNA genes within freshwater sediments have allowed for the identification of multiple bacterial phylotypes that appear to be ubiquitous in freshwater ecosystems (Zwart et al. 2002; Briée et al. 2007; Rinta-Kanto et al. 2009; Tang et al. 2009; Newton et al. 2011). Unfortunately, knowledge of the structure and function bacterial communities associated with Great Lakes Diporeia is still very limited. One culture-independent method for investigating bacterial communities in samples through fingerprinting is terminal restriction fragment length polymorphism (T-RFLP). T-RFLP is considered a cost-effective tool for assessing the diversity of complex bacterial communities and for rapidly comparing community structure and diversity among different ecosystems that is capable of recovering a resolution of bacterial community structure highly comparable to that of pyrotag sequencing (Liu et al. 1997; Pilloni et al. 2012). In the present work, the diversity of bacterial communities associated with Diporeia collected from multiple sites in lakes Superior, Michigan, and Huron, and the inland Cayuga Lake (New York) were mapped and compared using T-RFLP of 16S rRNA genes to determine if these communities vary spatially or temporally. In a second step, sequence analysis of 16S rDNA clones was applied to a total of 5 Diporeia bacterial communities from lakes Superior, Michigan, and Huron, and the inland Cayuga Lake (New York). Results of this study provide important baseline information regarding the structure of bacterial communities associated with Diporeia in the Great Lakes ecosystem.

Materials and methods Sample collection For all analyses, Diporeia samples were collected from a total of 8 locations in the Great Lakes basin and a single location in Cayuga Lake, an inland lake in New York, (Fig. 1) at depths rang-

ing from 40 to 186 m. For T-RFLP analysis, replicate samples were collected at each site in August 2007, and one site in Lake Superior (SU-23B) and one site in Lake Michigan (MI-18M) were resampled in August 2008 (Table 1). To identify bacterial taxa present in Diporeia samples, sequence analysis of cloned 16S rDNA clones was applied to a single replicate from each of the lakes mentioned above. Additionally, sequence analysis of 16S rDNA clones was applied to a single sample collected from Lake Ontario. Sediment samples were collected using a Ponar grab (sampling area: 22.86 × 22.86 mm/8.2 L). Once a sample was returned to the surface, it was sieved (mesh = 0.25 mm) and Diporeia were identified according to Edmonson (1959). Diporeia were then pooled (5 amphipods/pool), rinsed several times in sterile water to eliminate “free-living” bacteria, placed in sterile 80% ethanol in a 1.5 mL tube, and immediately stored at –20 °C until further processing. DNA isolation Genomic bacterial community DNA was extracted from Diporeia samples using the PowerSoil DNA Isolation kit (MO BIO Laboratories Inc., Carlsbad, California, USA) following the manufacturer’s protocol. DNA was quantified with a Qubit fluorometer and the Quant-it dsDNA BR Assay kit (Invitrogen Corp., Austin, Texas, USA). The isolated bacterial DNA was then used as a template for PCR amplification. The bacterial 16S gene was amplified using the universal eubacterial primer set 27F–1387R (27F: 5=AGAGTTTGATCMTGGCTCAG-3=) labeled with carboxyfluorescein (6-FAM) and 1387R (5=-GGGCGGWGTGTACAAGGC-3=) (Marchesi et al. 1998). Each 50 ␮L PCR reaction contained 25 ␮L of 2× Green GoTaq Master Mix (Promega Corporation, Madison, Wisconsin, USA), 45 ␮mol/L each primer, and ⬃100 ng of template DNA. PCR reaction conditions for amplification of partial 16S rRNA genes were as follows: initial 94 °C for 4 min, followed by 29 cycles of 94 °C for 30 s, 56 °C for 30 s, and 72 °C for 1 min, and a final extension for 7 min at 72 °C. A negative control containing no DNA was included in each set of PCR reactions. Resulting PCR products were visualized by agarose gel electrophoresis. Amplification of the proper gene fragment (⬃1.36 kb) was confirmed by comparison with a DNA size ladder. The PCR reaction was carried out in triplicate for each sample and resulting products were Published by NRC Research Press

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Table 1. Name, location, and depth of sampling sites, year of collection, and number of consensus terminal restriction fragment length polymorphism (T-RFLP) profiles generated for Diporeia for each restriction endonuclease for this study. HhaI Site

Latitude

Longitude

Depth (m)

2007

2008

2007

2008

Lake Michigan

MI-18M MI-27M MI-40 MI-47 HU-54M SU-20B SU-23B Cayuga

42.733 43.600 44.760 45.178 45.517 46.883 46.598 42.538

–87.000 –86.917 –86.967 –86.375 –83.417 –90.283 –84.807 –76.553

161 112 160 186 91 116 62 40

3 3 3 3 5 3 3 3

4 — — — — — 4 —

4 3 3 2 5 3 4 3

4 — — — — — 4 —

Lake Huron Lake Superior

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MspI

Waterbody

Cayuga Lake

Note: —, indicates a sample was not taken.

pooled and purified using a Wizard SV Gel and PCR Clean-Up System (Promega) following the manufacturer’s protocol. T-RFLP analysis To construct profiles of Diporeia bacterial communities for each restriction enzyme, 300 ng of purified fluorescently labeled PCR product were cut individually with 5 units of HhaI and MspI (New England Biolabs, Beverly, Massachusetts, USA) for 2 h at 37 °C. Digested PCR products were precipitated with 3 volumes of absolute ethanol. After 8 h of incubation at –20 °C, the precipitates were pelleted by centrifugation at 14 000 r/min (16 000g) for 15 min. Pellets were resuspended in 6 ␮L of sterile water (DEPCtreated, DNase, RNase-free). The DNA fragments were separated on an ABI 3100 Genetic Analyzer automated sequence analyzer (Applied Biosystems Instruments, Foster City, California, USA) in GeneScan mode at Michigan State University’s sequencing facility. The 5= terminal restriction fragments (T-RFs) were detected by excitation of the 6-FAM molecule attached to the forward primer. The sizes and abundance of the fragments were calculated using GeneScan 3.7 in relation to the MM1000 internal standard (BioVentures Inc., Murfreesboro, Tennessee, USA). T-RFLP data was analyzed with T-REX (http://trex.biohpc.org). T-REX software uses the methodology described by Abdo et al. (2006) and Smith et al. (2005) to identify and align true peaks, respectively. We used one standard deviation in peak area as the limit to identify true peaks and defined T-RFs by rounding off fragment sizes to nearest integer. Additionally, only profiles with a cumulative peak height of ≥5000 fluorescence units were used in the analysis. For all analyses, abundance values for both T-RFLP data sets were standardized by expressing the abundance of each OTU as a percentage of total abundance for each sample. Additionally, to account for “blind sampling” and large numbers of absences in the data sets, the data sets were transformed using the Hellinger equation as suggested by Ramette (2007). Species richness and diversity for the T-RFLP community profiles at each sampling site (for both the HhaI and MspI data sets) were calculated in R (Pinheiro et al. 2010) with the Vegan package (Oksanen et al. 2013). For calculating species richness and diversity, we assumed that the number of T-RFs present in a profile represented the operational taxonomic units (OTUs) and that the T-RF peak height represented the relative abundance of each OTU. For characterizing species diversity, we used the Shannon diversity index, which accounts for both abundance and evenness of the community at a particular site. For characterizing species evenness, we used Pielou’s Evenness index, which is based on the Shannon index and is constrained between 0.0 and 1.0, where less variation in communities between the OTU abundance approaches 1.0. We tested for significant differences in OTU composition and abundance among sites and years using permutational multivariate analysis (PERMANOVA). For the PERMANOVA, the Bray– Curtis distance matrix of Hellinger transformed OTU composition

was the response variable and site or year was the independent variable. The total number of permutations performed was 999. The PERMANOVA analysis was conducted in R using ADONIS function in the VEGAN library. Additionally, permutation tests (999 permutations) were used to test for significant differences in multivariate dispersion among sites and years using the BETADISPER function in VEGAN, which is a multivariate analogue of Levene’s test for homogeneity of variances. Since the Chao method takes the fraction of rarely present/low abundant T-RFs into account (Chao et al. 2005), it was used to define ␤ diversity. To determine whether community structure was significantly correlated with depth we used Mantel tests (Legendre and Legendre 1998) based on Pearson’s product–moment correlation. For Mantel tests, depth values were Z-score standardized, and community dissimilarities were standardized using Wisconsin standardization (dividing all species by their maxima, and then standardizing sites to unit totals). To test for differences in relative abundance of individual T-RFs among samples, MANOVA tests were conducted using the PROC GLIMMIX procedure (SAS Institute Inc., Cary, North Carolina, USA). DNA sequence analysis The PCR products generated for a total of 5 samples from lakes Superior, Michigan, Huron, and Ontario, and Cayuga Lake (SU-20B, MI-27M, HU-54M, ON-41, and Cayuga), were amplified with the unlabeled primer set (27F–1387R) and cloned using a TOPO TA Cloning kit (Invitrogen, Grand Island, Nebraska, USA) following the manufacturer’s protocol. A total of 399 clones (between 93 and 95 for the Great Lakes and 23 for Cayuga Lake) were cultured on Luria–Bertani agar plates (Fisher Scientific Inc., Waltham, Massachusetts, USA) containing 50 ␮g/mL kanamycin, as directed by the manufacturer’s protocol, and screened for positive transformation with PCR using the primer set M13F (5=GTTTTCCCAGTCACGAC-3=) and M13R (5=-CAGGAAACAGCTATGACC-3=). Transformants were then purified using a QIAprep Spin Miniprep kit (Qiagen Inc., Valencia, California, USA), and the resulting purified plasmid DNA was partially sequenced from the 5= end using either the M13F or M13R primer. All sequences generated in this study were screened for chimeras with Pintail (Ashelford et al. 2005), and deposited in GenBank (accession Nos. JQ772645–JQ773027 and KC436139–KC436264). Phylogenetic assignments were determined using the Ribosomal Database Project (RDP) (Cole et al. 2014) “Classifier” using a 95% confidence threshold and “Seqmatch” (Wang et al. 2007). Comparison of Diporeia T-RFLP profiles with profiles generated for individual 16S rDNA clones was conducted in an attempt to identify and quantify the presence of particular bacterial groups, including potential pathogens, in Diporeia populations. T-RFLP analysis was performed on a total of 10 clones, which showed high similarity (≥98%) to bacterial sequences contained in GenBank. The purified cloned DNA was digested and analyzed using T-RFLP Published by NRC Research Press

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as described above to both ensure that complete digestion of PCR products was achieved and to help determine the placement of each represented bacterial group in the Diporeia community profiles. Additionally, to obtain corresponding T-RFLP fragments, an in silico digest of clones was carried out in MEGA 5.0 (Tamura et al. 2011). Estimation of bacterial community coverage Analyzing the community structure of bacteria in Diporeia samples included estimating coverage, which is defined as an estimation of the percentage of bacterial groups or OTUs identified in a sample out of the total number of groups or OTUs. Calculating distances between known and unknown 16S rRNA sequences is important in comparing such sequences. In previous studies, distance values of 0.03 have been used to differentiate bacteria at the species level, 0.05 at the genus level, 0.10 at the family and class level, and 0.20 at the phylum level (Stackebrandt and Goebel 1994; Hugenholtz et al. 1998; Hughes et al. 2001; Sait et al. 2002). With this in mind, bacterial community coverage was calculated based on a distance value of 0.03 using the formula C ⫽ [1 ⫺ (n/N)] × 100 where n is the number of unique clones, and N is the total number of clones analyzed. To gain a better understanding of the bacterial diversity associated with Great Lakes Diporeia, an overall estimate of coverage was obtained by removing the Cayuga Lake sequences and analyzing a single composite library constructed from sequences from the 4 Great Lakes Diporeia clone libraries (SU-20B, MI-27M, HU-54M, and ON-41). Sequence alignment phylogenetic affiliation For phylogenetic analyses of cloned Diporeia sequences, Methanocaldococcus jannaschii (accession No. L77117) was used as the outgroup taxon. A total of 353 16S rRNA gene sequences and the single outgroup sequence were aligned with the Jukes–Cantor correction (Jukes and Cantor 1969) using RDP II. The mean length of sequences in the final alignment file was 719 bp. The alignment file was visually checked for alignment gaps and missing data in nucleotide positions using MEGA 5.0 (Tamura et al. 2011). The phylogenetic tree containing all 16S rRNA sequences from this study was generated using the neighbor-joining (Saitou and Nei 1987) method included in MEGA 5.0 using Maximum Composite Likelihood as a measure of genetic distance. To test for significant clustering of taxa among the 5 clone libraries based on phylogenetic relationships, the UniFrac lineagespecific analysis was used to break the tree up into the lineages at a specified distance from the root (Lozupone et al. 2006). To determine taxonomic assignments and phylogenetic relationships, additional trees were generated for cloned sequences and sequences identified as closely related reference sequences contained in RDP. Sequences were aligned and trees were generated as described above. Trees were then annotated to indicate the environment of origin for each sequence.

Results Bacterial communities of Diporeia Analysis of T-RFLP data revealed the presence of diverse bacterial communities in Diporeia samples. For the HhaI data set, a total of 175 T-RFs ranging from 50 to 983 bp in size were identified across all samples; for the MspI data set, a total of 138 T-RFs ranging from 55 to 983 bp in size were identified across all samples. For the HhaI data set, the mean (±SE) number of T-RFs identified at the sampling sites was 23.91 (±2.00) and ranged from 5 to 53 across all sites. For the MspI data set, the mean (±SE) number of T-RFs identified at the sampling sites was 21.46 (±1.25) and ranged from 7 to 35 across all sites. Species richness values and diversity indices

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(Shannon–Weiner diversity index and Pielou’s Evenness index) showed that diversity of profiles for Diporeia communities varied among each sampling event (Fig. 2). For both the HhaI and MspI data sets, the MI-18M samples from 2008 had the highest diversity and relatively high species evenness compared with the other samples analyzed. Additionally, for both the HhaI and MspI data sets the MI-18M samples from 2008 had the highest number of OTUs and the lowest species evenness. For both the HhaI and MspI data sets, a significant difference in ␤ diversity was observed among all Diporeia sampling events for all indices of similarity (HhaI MANOVA: df = 9, F = 3.583, P = 0.001; MspI MANOVA: df = 9, F = 5.6686, P = 0.001). For the HhaI data set, a significant difference in multivariate dispersions among all Diporeia sampling events was observed (df = 9, F = 4.406, P = 0.015). T-RF’s 489 HhaI, 496 HhaI, and 484 MspI occurred in 23.53%, 20.59%, and 60.00% of samples, respectively, with mean relative abundances of 7.77%, 1.67%, and 1.96%, respectively. Although T-RF 846 HhaI accounted for 3.20% of the mean relative abundance for the T-RFLP profiles, it only occurred in the 3 Cayuga Lake samples, with mean relative abundances ranging from 24.44% to 29.95%. For both the entire HhaI and MspI data sets, a significant positive correlation (Mantel test) between diversity and depth was observed for Diporeia (HhaI: P = 0.002; MspI: P = 0.001). A number of interesting findings were observed among profiles generated for Diporeia samples collected from multiple locations in Lake Michigan (MI-18M, MI-27M, MI-40, and MI-47). First, for the MspI data set, a significant difference in ␤ diversity was observed only among Lake Michigan Diporeia profiles (df = 3, F = 2.50, P = 0.035). Second, results of multivariate analysis of variance (ANOVA) showed that site MI-18M was unique in that it had higher abundances of certain T-RFs compared with the other sites. Third, for the HhaI and MspI data sets, 20 and 27 T-RFs were shown to be unique to MI-18M profiles, respectively. For the T-RFs that were unique to MI-18M in the HhaI data set, with the exception of T-RF 366 HhaI, which had an mean relative abundance of 21.15% ± 4.68%, the overall mean relative abundance was 2.03% ± 1.09%. Similarly, for the T-RFs that were unique to MI-18M in the MspI data set, the overall mean relative abundance was 1.18% ± 1.09%. No significant association was found between depth and the diversity of Lake Michigan Diporeia profiles (HhaI Mantel: P = 0.898; MspI Mantel: P = 0.892). Additionally, for both the HhaI and MspI data sets, no significant difference in variance was detected among Lake Michigan Diporeia samples. Temporal shifts in bacterial diversity For the Lake Superior site that was sampled in both years, the ␤ diversity in bacterial community structure in 2008 was found to be significantly greater than in 2007 for the HhaI data set but not the MspI data set (HhaI MANOVA: df = 1, F = 3.682, P = 0.021; MspI MANOVA: df = 1, F = 1.859, P = 0.101). However, for Lake Michigan no significant differences in ␤ diversity were found for the revisited site (HhaI MANOVA: df = 1, F = 0.171, P = 0.456; MspI MANOVA: df = 1, F = 1.766, P = 0.146). Significant differences in the abundance of particular T-RFs (MANOVA) were observed between 2007 and 2008 profiles for both SU-23B and MI-18M (Table 2). For the HhaI data set, of the 45 total T-RFs present for MI-18M, 27 were detected in samples from both 2007 and 2008, 12 were unique to 2007, and 6 were unique to 2008. For the MspI data set, of the 57 total T-RFs present for MI-18M, 37 were detected in samples from both 2007 and 2008, 11 were unique to 2007, and 9 were unique to 2008. For the HhaI data set, of the 141 total T-RFs present in SU-23B, 41 were detected in samples from both 2007 and 2008, 20 were unique to 2007, and 80 were unique to 2008. For the MspI data set, of the 75 total T-RFs present in SU-23B, 34 were detected in samples from both 2007 and 2008, 18 were unique to 2007, and 23 were unique to 2008. Published by NRC Research Press

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Fig. 2. Mean diversity index values (±SE) for 2 terminal restriction fragment length polymorphism (T-RFLP) data sets (amplified 16S rDNA digested with HhaI and MspI) generated for replicate Diporeia samples collected from lakes Michigan (MI), Superior (SU), and Huron (HU), and Cayuga Lake (New York) between 2007 and 2008. Richness is the number of operational taxonomic units, diversity is the Shannon–Weiner Diversity index, and Evenness is Pielou’s Evenness.

Table 2. Significant differences (P < 0.05) in relative peak heights (MANOVA) for both 16S rRNA terminal restriction fragment length polymorphism (T-RFLP) data sets (HhaI and MspI) generated for Diporeia samples collected from lakes Michigan and Superior between 2007 and 2008.

T-RFLP data set HhaI

MspI

Lake Michigan sites (2007)

MI-18M (2007–2008)

SU-23B (2007–2008)

T-RF

P value

T-RF

P value

T-RF

P value

60 83 330 366 127 146 167 428 534 563

0.05) based on the specified distance from the root (11.3333), a third Flavobacterium cluster characterized by an abundance of sequences from the Lake Superior library was observed. For Alphaproteobacteria (Fig. 5a), sequences belonging to the order Rhodobacteriales were from both the Lake Michigan and Cayuga Lake libraries. Sequences belonging to the order Sphingomonadales were only detected in the Lake Ontario library. Interestingly, a bacterium belonging to the order Rickettsiales was only detected in Published by NRC Research Press

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Fig. 5. Neighbor-joining consensus phylogeny of Alphaproteobacteria (a) and Betaproteobacteria (b) 16S rRNA gene sequences of clones from Diporeia and closely related reference sequences. Bootstrap values (1000 replicates) greater than 70% are indicated at the nodes. Taxa observed in Diporeia samples collected from lakes Superior, Michigan, Superior, and Ontario (Great Lakes), and Cayuga Lake (inland lake) are in bold. Triangle indicates a collapsed branch containing multiple taxa. Value to the right of triangle indicates the number of taxa in the collapsed branch.

the Lake Ontario library. However, the corresponding T-RF (450 MspI) was only detected in Diporeia samples collected from lakes Michigan and Superior, with a prevalence of 0.03% and an mean relative abundance of 1.73% ± 0.56%. For the class Betaproteobacteria (Fig. 5b), a significant clustering of sequences similar to Rhodoferax spp. and Albiferax spp. was observed, with the higher proportion of sequences from the Lake Michigan Diporeia library having the highest relative contribution to the overall differences between environments. For the class Gammaproteobacteria (Fig. 6a), a significant clustering of sequences similar to Perlucidibaca piscinae was observed, with the higher proportion of sequences from the Lake Ontario Diporeia library having the highest relative contribution to the overall differences between environments. For Grampositive bacteria belonging to the phylum Firmicutes (Fig. 6b), with the exception of the Lakes Huron library, bacteria belonging to the orders Actinomycetales and Acidimicrobiales (Actinobacteria) were detected in all libraries. A bacterium belonging to the order Bacilliales (Firmicutes) was only detected in the Lake Michigan library.

Discussion This study investigated the bacterial communities associated with Diporeia, an ecologically important organism in the Great Lakes, which has declined considerably in abundance across much of the lakes (Barbiero et al. 2011). Results of this study show that the diversity of the bacterial communities associated with Diporeia is relatively high compared with what has been previ-

ously reported for both freshwater and marine crustacean species (Møller et al. 2007; Peter and Sommaruga 2008; Grossart et al. 2009; Tang et al. 2009). Recent studies using culture-independent methods have identified as many as 6 major bacterial groups associated with freshwater crustacean species (Actinobacteria, Firmicutes, Bacteroidetes, Alpha-, Beta-, and Gammaproteobacteria). In the current study, we identified 10 major bacterial groups associated with Great Lakes Diporeia (Actinobacteria, Bacteroidetes, Chloroflexi, Firmicutes, Planctomycetes, Verrucomicrobia, Alpha-, Beta-, Gamma-, and Deltaproteobacteria). It is unknown how the composition of the bacterial community in the surrounding sediment influences that of Diporeia. However, comparison of the 16S rDNA genes associated with Diporeia observed in the current study with those reported to be associated with the surrounding Great Lakes sediment in a recent study (Winters et al. 2014) show that, while the sediment is largely dominated by Actinobacteria followed by Acidobacteria, Beta-, and Gammaproteobacteria, Diporeia is largely dominated by Bacteroidetes followed by Beta- and Gammaproteobacteria. This finding suggests that a number of the observed bacteria are intimately associated with Diporeia. While we cannot be sure which bacteria came from the surface or gut of Diporeia or how the fullness of individual guts affected the overall bacterial community structure, results of 16S rRNA sequence and T-RFLP analysis demonstrate that the bacterial communities of Diporeia were dominated by Flavobacterium spp. (Bacteroidetes) and Pseudomonas spp. (Gammaproteobacteria). Published by NRC Research Press

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Fig. 6. Neighbor-joining consensus phylogeny of Gammaproteobacteria (a) and Firmicutes (b) 16S rRNA gene sequences of clones from Diporeia and closely related reference sequences. Bootstrap values (1000 replicates) greater than 70% are indicated at the nodes. Taxa observed in Diporeia samples collected from lakes Superior, Michigan, Superior, and Ontario (Great Lakes), and Cayuga Lake (inland lake) are in bold. Triangle indicates a collapsed branch containing multiple taxa. Value to the right of triangle indicates the number of taxa in the collapsed branch.

Analysis of the phylogenetic tree using UniFrac revealed that a number of bacterial species were common among different Diporeia populations, indicating the presence of a core microbiome. Additionally, analysis of the phylogenetic tree using UniFrac revealed that a number of significant clusters were present within the composite clone library, indicating the bacterial communities associated with the surrounding sediment influenced the structure the Diporeia bacterial communities. The extent of how sediment bacterial communities influence Diporeia bacterial communities is unknown. Additionally, it is possible that amount of gut contents contained within individual Diporeia within each sample had varying effects on the observed bacterial community structure. Interestingly, in a survey of trends in Diporeia abundances throughout the Great Lakes between 1997 and 2009, Barbiero et al. (2011) showed that, although Diporeia abundances had significantly declined throughout Lake Michigan, significant declines were not observed at the 2 most southerly deep sites (MI-11 and MI-18M), which exhibited a negative (–0.60) albeit nonsignificant (P = 0.06) trend. Results of the current study showed that MI-18M profiles contained 20 (HhaI data set) and 27 (MspI data set) unique T-RFs compared with other Lake Michigan samples. Additionally, of the significantly different relative T-RF abundances for the Lake Michigan Diporeia profiles, all were enriched in samples collected from site MI-18M. Furthermore, of all the samples analyzed in this study, on average, samples from MI-18M had relatively high species diversity. Collectively, the findings of this study together with those of Barbiero et al. (2011) point to the possibility that the profiles of MI-18M Diporeia represent a healthy bacterial community.

A number of differences were observed among the profiles for Diporeia samples collected from multiple sites in Lake Michigan in 2007 (MI-18M, MI-27M, MI-40, and MI-47). The finding that the Chao similarity index revealed a significant difference in ␤ diversity among Lake Michigan profiles (MspI data set) suggests that the observed difference is due to low relative abundances of multiple bacterial species. This is further supported by the findings that MI-18M had higher species richness compared with other Lake Michigan profiles and that a high number of T-RFs with low mean relative abundances were unique to the MI-18M profiles. Altogether, these findings suggest the bacterial communities associated with Diporeia at site MI-18M are distinctly different from others in Lake Michigan. Temporal shifts were observed for Diporeia samples collected from Lake Superior (SU-23B). Whether the observed temporal shifts are due to the relatively shallow depth of this site, it’s unique location in Whitefish Bay near the Saint Mary’s River through which Lake Superior drains into Lake Huron, or some unknown limnological feature remains to be determined. The cause(s) and potential biological significance of the shifts are unknown and warrant further investigation. A highly significant correlation between depth and the diversity of Diporeia bacterial communities was observed for the composite data set, suggesting depth may play a role in regulating the bacterial communities associated with Diporeia. However, the same correlation was not observed when only Lake Michigan data were considered. It is possible that a significant correlation between depth and diversity would have been observed if a larger range of depths were sampled for Lake Michigan. Further research Published by NRC Research Press

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is required to determine the relationship between depth and the diversity of Diporeia bacterial communities. While the exact cause for the decline in Diporeia populations remains unexplained, bacterial pathogens could be a contributing factor. In the current study, we detected some bacterial groups that contain members known to be pathogens of aquatic organisms. In terms of obligate pathogens, a bacterium belonging to Rickettsiales, an order of Bacteria containing known pathogens for Diporeia and other freshwater amphipods (Federici et al. 1974; Larsson 1982; Graf 1984; Messick et al. 2004), was detected in the Lake Ontario Diporeia clone library. One T-RF representing the order Rickettsiales (449 M) had a prevalence of 0.03% and an mean relative abundance of 1.73% ± 0.56%. This would be considered a relatively high abundance for a parasite in a free-ranging organism like Diporeia and can contribute, either alone or combined with other opportunistic bacteria, to Diporeia declines (Anderson and May 1981). Additionally, Flavobacterium spp. and Pseudomonas spp. genera that are known to contain pathogens of aquatic animals were detected in Diporeia samples. Despite the constraints that can be associated with T-RFLP analysis of complex bacterial communities, such as multiple taxa sharing similar T-RFs and the possibility of pseudo T-RF formation (Egert and Friedrich 2003), the combination of analysis of multiple restriction enzyme data sets (HhaI and MspI) with T-RF pattern confirmation by in silico digestion of cloned 16S rRNA gene sequences allowed for considerable elucidation of Diporeia bacterial communities. Furthermore, the reasonably high estimate of coverage obtained for the composite Great Lakes Diporeia 16S rRNA library suggests a large portion of the bacteria associated with Diporeia in the Great Lakes was observed. Even though we did not sample to saturation (100% coverage), after 16S rRNA gene clones were analyzed with T-RFLP, a few corresponding T-RFs were not found in the community profiles. Similar findings were observed in an interlaboratory comparison for the microbial communities of seafloor basalts (Orcutt et al. 2009). With this in mind, it is likely these detected bacteria represent a rather small fraction of bacterial communities associated with the Diporeia. In conclusion, the combination of T-RFLP analysis and 16S rRNA gene sequencing proved to be a powerful tool for investigating the bacterial diversity of Diporeia. Since a similar study has never been conducted on Diporeia, this study represents the most extensive list of bacteria associated with this amphipod in relation to its surrounding environment and provides useful insights on the microbiota of Diporeia. Our hope is that the knowledge gained in this study will shed light on the potential causes of the decline of Diporeia populations and will foster the development of efficacious management strategies for the restoration and conservation of both Diporeia and other Great Lakes organisms that rely on Diporeia.

Acknowledgements We are thankful to the crew and staff of the R/V Lake Guardian for helping in sample collection. This study was partially funded by the United States Environmental Protection Agency – Great Lakes National Protection Office (grant No. GL00E36101) and the Great Lakes Fisheries Trust (grant No. 2009.1058).

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Analysis of bacterial communities associated with the benthic amphipod Diporeia in the Laurentian Great Lakes Basin.

Bacterial communities play important roles in the biological functioning of crustaceans, yet little is known about their diversity, structure, and dyn...
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