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Lakes undergoing cyanobacterial blooms often exhibit differences between free-living (FL) and cyanobacteria-associated (CA) bacterial assemblages, but previous studies have not compared distinct FL and CA communities across multiple lakes. This project investigated whether FL and CA communities differ from each other in consistent ways across lakes. FL and CA communities were collected from three Ohio (USA) lakes on two sampling dates during cyanobacterial blooms. High- throughput sequencing was used to characterize the communities, and comparisons were made of the composition and diversity of FL and CA communities within and across lakes. Diversity estimates did not vary significantly among lakes nor between CA and FL assemblages. The taxonomic composition of CA communities differed significantly from that of FL communities in Buckeye and Harsha Lakes and in Maumee Bay on one of two sampling dates. CA communities from Buckeye and Harsha Lakes were more similar to each other than to their respective FL communities. Community composition in Maumee Bay on August 18 did not differ between FL and CA habitats. As the bloom progressed, the FL community remained similar in composition to samples collected on August 18, while the CA community became significantly dissimilar. This study is the first cross-lake comparisons of CA and FL communities, uncovering the impacts of habitat type, lake, and sampling date in determining community composition. . . . Keywords Cyanobacterial bloom Community composition Free-living bacteria Cyanobacteria-associated bacteria Introduction microenvironments that make up the phycosphere, a dis- tinctive habitat which supports heterotrophic bacterial Cyanobacterial harmful algal blooms (CyanoHABs) are com- communities that generally differ from the surrounding moningrowing numbersof freshwaterecosystemsaroundthe bacterioplankton (Li et al. 2011;Louatietal. 2015;Niu world due to climate change and nutrient loading (Paerl 1996; et al. 2011; Parveen et al. 2013a, b; Shi et al. 2012). Paerl and Paul 2012). Typically, bloom-forming cyanobacteria These microenvironments are protected from physico- occur as colonies embedded in mucilaginous matrices or as chemical fluctuations in the water column (Paerl 1996) filaments within mucilaginous sheaths. The surfaces of and are rich in organic compounds, including polysaccha- cyanobacteria and their surrounding mucilage form rides (Parikh and Madamwar 2006; Pereira et al. 2009; Plude et al. 1991;Xu et al. 2013) and oligopeptides (such as microcystins and nodularins) that can be used as carbon Electronic supplementary material The online version of this article sources by some bacteria (Imanishi et al. 2005; Jones et al. (https://doi.org/10.1007/s13213-018-1354-y) contains supplementary 1994; Maruyama et al. 2003). material, which is available to authorized users. Previous studies of the composition and diversity of het- erotrophic bacteria living on mucilaginous cyanobacteria have * Leighannah N. Akins firstname.lastname@example.org focused on the differences between cyanobacteria-associated (CA) communities and free-living (FL) bacterioplankton com- 1 munities within a single lake rather than comparing CA bac- Department of Biological Sciences, Kent State University, 256 terial assemblages from different lakes (Louati et al. 2015;Niu Cunningham Hall, Kent, OH 44242, USA 494 Ann Microbiol (2018) 68:493–503 et al. 2011; Parveen et al. 2013a; Shi et al. 2012). Comparisons Methods across multiple lakes are necessary to understand whether dif- ferences between FL and CA bacterial communities are attrib- Study sites utable to innate selective properties imposed by the cyanobacteria-microhabitat. Alternatively, such differences In the summer of 2014, three lakes were examined based on may result from stochastic community assembly in combina- the occurrence of cyanoHABs as reported by the Ohio tion with differences among lakes in physicochemical condi- Environmental Protection Agency (2014) and the presence tions and pools of potential bacterial colonizers. Ultimately, of dense, visible green surface scum. High cyanobacterial cell such information will reveal whether or not CA communities counts, cell biovolumes, and gene sequence abundances in share common characteristics that could potentially serve as these lakes were also reported by Francy et al. (2015). In predictive or management tools. recent years, the selected lakes have all developed annually Composition of bacterial communities associated with mu- recurring toxic cyanobacterial blooms which typically persist cilaginous cyanobacteria varies but often includes throughout the summer and into early autumn. The lakes were Bacteroidetes and Actinobacteria (Cai et al. 2014;Li et al. located in northeast, central, and southern Ohio (Fig. 1). 2011;Louatietal. 2015;Niu et al. 2011; Parveen et al. Buckeye Lake (39.93° N, 82.48° W; mean depth 2.5 m, 2013a;Shen et al. 2011; Shi et al. 2012). Actinobacteria tend maximum depth 7 m, surface area 11.6 km ) is a reservoir to be predominantly free-living cells incidentally co-occurring in central OH (Francy et al. 2016). For most of the year, the with cyanobacteria (Louati et al. 2015; Parveen et al. 2013b), reservoir is fed by a small watershed (~ 70 km ) with 60% although some members of this phylum live within the muci- agricultural, 14% forest, and 15% urban land use (Francy lage (Zhang et al. 2016). Bacteroidetes are found embedded in et al. 2016; Taylor and Governor 2012). At times of high the mucilage (Parveen et al. 2013b) or associated with sur- precipitation, it receives overflow from the headwaters of faces of non-mucilaginous cells (Velichko et al. 2015). South Fork Licking (Taylor and Governor 2012)and run- Gammaproteobacteria, uncommonly found as free-living or- off from additional areas, draining a total of 127 km of ganisms in freshwater (Niu et al. 2011; Parveen et al. 2013a; predominately agricultural land (Francy et al. 2016;Taylor Shi et al. 2012), are often abundant in communities attached to and Governor 2012). cyanobacteria (Parveen et al. 2013a; Velichko et al. 2015). William Harsha Lake (39.02° N, 84.11° W, mean Betaproteobacteria are typically well-represented in free-liv- depth 12.9 m, maximum depth 30 m, surface area ing bacterial communities in freshwater lakes and have 8km ), formerly known as East Fork Lake, is a even higher abundances in communities associated with monomictic reservoir in southern OH (Beaulieu et al. mucilaginous cyanobacteria (Louati et al. 2015; Parveen 2014;Francyetal. 2016). Constructed on the East Fork et al. 2013a). While taxonomically coarse comparisons of the Little Miami River, it drains a watershed of about can be made among CA bacterial communities across stud- 886 km . Land use is 64% agricultural and 27% forest, ies, whether or not there is a characteristic CA bacterial with the rest lightly urbanized (Beaulieu et al. 2014; community is unknown. Francy et al. 2016). In this study, the composition and diversity of CA and FL Maumee Bay (41.68° N, 83.38° W, mean depth < 3 m, bacterial communities from three temperate lakes (OH, USA) maximum depth ~ 3 m except for a dredged shipping during toxic cyanobacterial blooms were investigated. We hy- channel of 8.5 m, surface area 70 km )isashallowem- pothesized that the protected and resource-rich microenviron- bayment on the southwestern shore of Lake Erie (mean ments associated with mucilaginous cyanobacteria would se- depth 7.4 m, max depth 19 m, surface area 19,830 km ). lect for a subset of the bacteria available in the water column. The 2014 HAB in Maumee Bay was part of a larger Thus, we anticipated that CA bacterial communities would be bloom in which cyanobacterial surface scum, consisting compositionally distinct from FL bacterial communities with- predominately of Microcystis spp., covered much of the in the same lakes and would have lower alpha diversity than lake’s western basin (3284 km ). TheMaumeeRiver FL communities as suggested by prior studies (Li et al. 2011; drains a watershed of 16,388 km , of which 73.3% is Niu et al. 2011; Parveen et al. 2013a, b; Shi et al. 2012). agricultural land and 10.6% is urban, including the city Furthermore, we anticipated that the conditions of CA micro- of Toledo, OH (Baker et al. 2014;Moorheadetal. 2008). habitats would select for a consistent subset of taxonomic The river discharges directly into Maumee Bay from the groups from among the pool of potential colonizers. southwest (Francy et al. 2015;Michalaketal. 2013, Therefore, we hypothesized that CA communities from differ- Moorhead et al. 2008). To the northeast, the bay opens ent lakes would be more similar in composition to each other onto the western basin, but water flow patterns permit than to FL communities from the same lakes and that CA little mixing within Maumee Bay, leaving the Maumee communities would exhibit a greater degree of cross-lake sim- River as the primary conduit of water, dissolved nutrients, ilarity than would FL communities. and suspended sediment into the bay. Ann Microbiol (2018) 68:493–503 495 Fig. 1 Locations of three eutrophic lakes sampled during cyanobacterial blooms in 2014 Sample collection and processing pore size) to collect small sized free-living bacterial (FL) frac- tions. Membranes were stored at − 80 °C until DNA Three replicate 1-l water samples were collected from the top extraction. 5 cm of each lake in 2014. Each lake was sampled once in the Inorganic nitrogen was measured with a Synergy 2 plate period from July to August, when the cyanobacterial bloom reader (BioTek, Winooski, VT, USA) following the indophe- season is at its height in temperate North America due to high nol blue method for ammonium and the sulfanilamide method temperatures and strong thermal stratification of lakes, and for nitrate/nitrite as adapted for microplates (Ringuet et al. again in September, when cyanobacterial blooms in the region 2011). Soluble reactive phosphorus (SRP) was assayed by are generally on the decline. Buckeye Lake was sampled on the ascorbic acid method (Murphy and Riley 1962), and ab- July 24 and September 19, William Harsha Lake was sampled sorbance measured with a DU 730 UV/visible spectrophotom- on July 17 and September 2, and Maumee Bay was sampled eter (Beckman Coulter, Brea, CA, USA). Nutrient data were on August 18 and September 28. At the time of sampling, tested for normality with the Shapiro-Wilkes test and the temperature, conductivity, and dissolved oxygen were mea- Kruskal-Wallis test was used to check for significant differ- sured with a HQ40d multiprobe (Hach, Loveland, CO, ences in the event of non-normal distribution. Statistical anal- USA). Samples were transported on ice to the lab, where they yses were carried out in JMP (SAS, Inc., Cary, NC, USA). were first filtered through 3-μm nitrocellulose membranes (Millipore, Darmstadt, Germany) under vacuum to collect Bacterial community analysis cyanobacteria-associated bacteria (CA) associated with larger sized cyanobacteria cell surfaces or embedded in DNA was extracted from filters using the Power Soil DNA cyanobacterial mucilage, and then through 0.2-μmpolycar- extraction kit (MoBio, Carlsbad, CA, USA) according to man- bonate membranes (Millipore, Darmstadt, Germany) ufacturer’s protocol. The presence of 16S rRNA genes was (modified from Li et al. 2011 by using filters with a smaller confirmed and samples were subsequently submitted for high- 496 Ann Microbiol (2018) 68:493–503 throughput 2 × 300 bp paired-end sequencing of the V4-V5 a PERMANOVA-based F value calculated from average dis- hypervariable region (Sun et al. 2013)using an Illumina tances among groups relative to average distances within MiSeq Series System (Illumina Inc., San Diego, CA, USA) groups for actual and permutated data. A pseudo-F statistic at the Ohio State University Molecular and Cellular Imaging then tested the likelihood that permutated F values were larger Center (Wooster, OH, USA). than the observed F value. Finally, differences in abun- Following sequencing, paired reads were assembled into dance values for each OTU among sampling groups and iTags (Degnan and Ochman 2012). iTags were sorted by among a posterior clusters were examined using the length, filtered for chimeras, and quality filtered in the group_significance.py command followed by the default pick_open_reference workflow with usearch61_ref as the op- non-parametric Kruskal-Wallis test of significance in erational taxonomic unit (OTU) picking and classification QIIME (Caporaso et al. 2010). The P values were adjust- method in QIIME Version 1.9.1 (Caporaso et al. 2010). ed using the False Discovery Rate (FDR) approach. OTU clustering was performed at the 97% similarity level and taxonomy assigned based on partial 16S rRNA sequences in the 16S rRNA SSU_Ref_NR_99_128.1 reference database Results (SILVA_SSU_128.1, Release date, September 29, 2016) (Caporaso et al. 2010). A total of 1,564,141 BiTags^ and Sequences of cyanobacterial taxa dominated the 3-μmpore 44,296 OTUs were obtained. Two samples with low OTU size fraction of each sample. The bloom in Buckeye Lake counts, Maumee Bay Aug. 18 FL (33 iTags) and William consisted almost entirely of Planktothrix on both sampling Harsha Lake Sept. 2 FL (52 iTags), were excluded from sub- dates. Maumee Bay was strongly Microcystis-dominated on sequent analysis. Singletons, OTUs unassigned at the basal August 18, but bloom composition shifted to a mix of level (D1), and OTUs assigned to Archaea, mitochondria, Microcystis and Dolichospermum by September 24. William chloroplast, and cyanobacteria lineages were removed from Harsha Lake had the most diverse cyanobacterial assemblage, all samples in the resulting OTU table, yielding 968,520 iTags including Cylindrospermopsis, Dolichospermum, with 19,306 OTUs. The final filtered OTU table was then sum- Synechococcus,and Microcystis, although Microcystis be- marized to 445 bacterial phylotypes at the family level. came much less abundant in September than in July. Species richness (alpha diversity) across samples was In contrast to our prediction, there were no significant dif- assessed using Shannon diversity, Simpson’s index, and the ferences in bacterial diversity (cyanobacteria excluded) be- unique OTU count (observed_species metric in QIIME), fol- tween CA and FL communities across the three lakes (OTU lowing rarefaction of the family-level OTU table to 6940 richness, Wilcoxon chi-square = 11.6, df = 11, P =0.40; iTags per sample. Samples were sorted into 12 a priori FL Shannon’s index, Wilcoxon chi-square = 9.2, df = 11, P = and CA groups representing bacterial communities collected 0.60; Simpson’s index, Wilcoxon chi-square = 10.2, df = 11, from the three lakes on two sampling dates per lake. P = 0.52), although FL community diversity indices were gen- Differences in Shannon diversity, Simpson’sindex,and erally larger than CA indices (Fig. 2). The CA community of OTU richness were evaluated using the Wilcoxon non- Maumee Bay became slightly less diverse over time, with parametric test. To estimate beta diversity, a Bray-Curtis dis- fewer unique OTUs detected in September than in August tance matrix was generated using the rarefied family-level (Fig. 2a), but the change was statistically non-significant. table (Bray and Curtis 1957; Anderson et al. 2006). A non- Community composition differed significantly among the metric multidimensional scaling (NMDS) plot was generated 12 sampling groups representing three lakes, two sampling to visualize dissimilarity in community composition among dates, and two community types ([FL and CA]; MRPP, samples following NMDS analysis on the distance matrix within-group agreement, effect size, A = 0.67, observed del- (Kruskal 1964). Differences in community composition ta = 0.18, and expected delta = 0.54, P = 0.001, 1000 permu- among samples were evaluated using the Multivariate tations; PERMANOVA, Pseudo-F = 21.5, P = 0.001, 1000 Response Permutation Procedure (MRPP) (Mielke 1984)on permutations). The sampling groups fell into four clusters, the distance matrix via the Bcompare_categories.py^ com- with cluster 1 made up of CA communities from Buckeye mand in QIIME with 1000 permutations. and Harsha Lakes and cluster 2 composed of FL communities An additional test of dissimilarity in microbial composition from the same two lakes (Fig. 3). Both CA and FL communi- among samples (permutational multivariate analysis of vari- ties sampled from Maumee Bay in August were represented ance, PERMANOVA) was performed (Anderson et al. 2006). by cluster 3, along with the FL community from Maumee Bay An underlying assumption of PERMANOVA is that all sampled in September. Cluster 4 consisted of only the CA groups are made up of replicates which exhibit the same level community from the September sampling date in Maumee of dispersion around their group centroids (Anderson and Bay. The four clusters differed significantly in community Walsh 2013). Homogeneity of within-group dispersions was composition (MRPP, within-group agreement, effect size, assessed using PERMDISP (Anderson and Walsh 2013), and A = 0.35, observed delta = 0.35, and expected delta = 0.54, Ann Microbiol (2018) 68:493–503 497 FL clusters were Alphaproteobacteria or Betaproteobacteria (Table S2). However, unassigned Acidimicrobiales (Actinobacteria), Sphingobacteriaceae (Bacteroidetes), and Leptospiraceae (Spirochaetes) were also found in the FL- dominated clusters at abundances that were, while low, still significantly greater than their abundances in clusters 1 and 4 (Table S2). No taxa that were found to be abundant in clusters 1 and 4 were significantly less abundant in clusters 2 and 3. Communities in Maumee Bay separated from communities in the two other lakes along the second NMDS axis (Fig. 3). Clusters 1 and 2 were enriched in Chthoniobacterales (Verrucomicrobia), unclassified Verrucomicrobia, Planctomycetes families Phycisphaerae and Planctomycetaceae, Rickettsiaceae (Alphaproteobacteria), Oceanospirillaceae (Gammaproteobacteria), and several families belonging to the Deltaproteobacteria orders Bdellovibrionales and Oligoflexales, whereas these taxa were much less common in clusters 3 and 4 (Table S2). Other Gammaproteobacteria families were rare overall but signifi- cantly more abundant in the Buckeye-Harsha clusters than in the Maumee Bay clusters (Table S2). In contrast, Maumee Bay clusters were relatively enriched in Caulobacteraceae and Hyphomonadaceae (Alphaproteobacteria), Nitrosomonadaceae (Betaproteobacteria), and Chromatiaceae (Gammaproteobacteria), while unassigned Rickettsiales (Alphaproteobacteria) sequences were rare but most abundant in Maumee Bay (Table S2). The abundance of unclassified Verrucomicrobia was much greater in cluster 1 than in cluster 2. Cluster 1 was further separated from all other clusters by high abundances of Fig. 2 Bar plots of average values, with standard error, of a OTU richness, b Shannon diversity, and c Simpson’s Index for free-living Blastocatellaceae (Acidobacteria), group OPB35 (black bars) and cyanobacteria-associated (white bars) bacterial commu- (Verrucomicrobia), Flavobacteriales NS9 marine group nities from William Harsha Lake, Buckeye Lake, and Maumee Bay (Bacteroidetes), and several members of the order Sphingobacterales (Bacteroidetes), especially Saprospiraceae and group env. OPS 17 (Table S2). Cluster 1 P = 0.001, 1000 permutations), confirming differences be- also had significantly more Chloroflexi than other clusters, tween FL and CA habitat types and similarities among sam- especially Caldilinaceae and unassigned Chloroflexi, but also ples within habitat types for two of three lakes. the relatively rare Anaerolineaceae (Table S2). Two families Out of 445 family-level bacterial taxa, 178 differed signif- within the Bacillales (Firmicutes), Bacillaceae and icantly in abundance among sampling groups (Table S1), in- Paenibacillaceae, also contributed to the separation of cluster cluding 80 Proteobacteria taxa (Fig. 4) and 98 other taxa 1, as did an unassigned Planctomycetes group OM190. This (Fig. 5), and 128 family-level groups differed among the four cluster was further distinguished by high abundances of a clusters in Fig. 3 at α <0.05 (Table S2). With the exception of wide variety of rare taxa, including Fusobacteriaceae the CA community collected from Maumee Bay in August, (Fusobacteria), Ignavibacteriaceae (Ignavibacteriae), unas- CA communities were separated from FL communities along signed Hydrogenedentes, Rhizobiales group A0839 the first axis of the NMDS plot (Fig. 3). Multiple taxa were (Alphaproteobacteria), unclassified Proteobacteria,and abundant in clusters 2 and 3, which consisted entirely or most- many Deltaproteobacteria such as unassigned ly of FL samples, that were relatively depleted in clusters 1 Bradymonadales, various members of the order and 4, made up exclusively of CA communities. The greatest Myxococcales, and clade Sva0485 (Table S2). difference was in the abundance of Sporichthyaceae Phycisphaerae and Planctomycetaceae were highly (Actinobacteria), a family more than ten times as abundant enriched in cluster 2 but less enriched in cluster 1 and rela- in the FL-dominated clusters than in the CA-only clusters tively depleted in clusters 3 and 4 (Table S2). Cluster 2 com- (Table S2). Most other taxa that were more abundant in the munities were also rich in unassigned Acidobacteria and 498 Ann Microbiol (2018) 68:493–503 Fig. 3 NMDS plot showing compositional similarity of bacterial diamonds for July and September samples, respectively) and Buckeye communities in free-living (FL) and cyanobacteria-associated (CA) sam- Lake (blue and green filled squares for July and September samples, ples collected from Buckeye Lake (BL), William Harsha Lake (WH), and respectively). Cluster 2 is made up of the July and September FL com- Maumee Bay (MB) based on mean NMDS scores (NMDS stress = 0.07) munities from William Harsha Lake (brown and purple open diamonds, (MRPP, within-group agreement, effect size, A = 0.67, observed delta = respectively) and Buckeye Lake (blue and green open squares, respec- 0.18 and expected delta = 0.54, P = 0.001, 1000 permutations). Samples tively). Cluster 3 is composed of August and September FL communities close to each other are more similar in composition than those farther from Maumee Bay (red and black open triangles) and the August CA apart. Four a posteriori clusters were established based on proximity of community (red filled triangle) from Maumee Bay. Cluster 4 represents samples to each other in the NMDS plot. Cluster 1 is composed of the CA the September CA community (black filled triangle) from Maumee Bay communities from William Harsha Lake (brown and purple filled several members of the Actinobacteria, including the highly rare in cluster 3 (Table S2). Another rare taxon, Candidatus abundant Acidimicrobiaceae (Acidimicrobiales), other Azambacteria (Parcubacteria), was also found mostly in this Acidimicrobiales, Mycobacteriaceae (Corynebacteriales), and cluster (Table S2). multiple family-level groups within clade PeM15 and class Few family-level groups were significantly more abundant in Thermoleophilia (Table S2). Two Gammaproteobacteria taxa, cluster 4 than any other cluster. They included the moderately the Legionellaceae family and an unassigned abundant Cytophagaceae (Bacteroidetes), Parachlamydiaceae Xanthomonadales group, were significantly more abundant in (Chlamydiae), Nitrosomonadaceae (Betaproteobacteria), and this cluster than elsewhere, as were the Delatproteobacteria Chromatiaceae (Gammaproteobacteria)(Table S2). Among groups Bacteriovoraceae and Oligoflexales 0319-6G20, plus a the rare taxa, an unassigned Bacteroidetes group, Rhizobiales group of bacterial sequences that could not be assigned to any group DUNssu044, and Desulfomonadales C8S-102 known phylum (Table S2). Rare phylotypes found at their (Deltaproteobacteria) were detected mainly in cluster 4 highest abundance in this cluster fell into unassigned groups (Table S2). within Acidobacteria, Actinobacteria, Omnitrophica, The lakes exhibited variation in temperature, DO, conduc- Alphaproteobacteria,and Gammaproteobacteria. tivity, and Secchi depth (Table 1). Inorganic P concentrations Microbacteriaceae (Actinobacteria), Cyclobacteriaceae were similar across all lakes, below 5 μg/L except for a single (Bacteroidetes), Chitinophagaceae (Bacteroidetes), sample collected from Buckeye Lake. Ammonium and nitrate/ Rhodobacteraceae (Alphaproteobacteria), Xanthomonadaceae nitrite were below detection limits in all samples. (Gammaproteobacteria), and unassigned Opitutae (Verrucomicrobia) were all abundant in cluster 3 and significant- ly less abundant in other clusters (Table S2). The SL56 marine Discussion group (Chloroflexi) and two family-level groups of Rhizobiales (Alphaproteobacteria) were moderately abundant in cluster 3 but In William Harsha Lake and Buckeye Lake, cyanobacteria- rare elsewhere (Table S2). Demequinaceae and unassigned associated communities were compositionally distinct from Micrococcales, both belonging to the same order as free-living communities but not significantly different in di- Microbacteriaceae, were rare in all clusters but significantly less versity. The CA communities from these two different lakes Ann Microbiol (2018) 68:493–503 499 Fig. 4 Relative abundances (%) of the 80 Proteobacteria families and communities collected from Buckeye Lake (BL), William Harsha Lake family-level groups that differed significantly (α < 0.05) among the 12 (WH), or Maumee Bay (MB) sampling groups of free-living (FL) or cyanobacteria-associated (CA) clustered together in NMDS analysis, while the FL commu- separation between CA and FL communities within lakes nities from the same lakes fell outside the cluster, indicating and the clustering of CA communities across lakes remained that CA communities were more similar to each other than to consistent over time. The FL communities from the same pair their respective FL communities. Although the communities of lakes also fell into a single cluster. These results support the underwent some turnover between July and September, the hypothesis that cyanobacteria would provide a microhabitat Fig. 5 Relative abundances (%) of the 98 families and family-level cyanobacteria-associated (CA) communities collected from Buckeye groups outside the Proteobacteria phylum that differed significantly (α Lake (BL), William Harsha Lake (WH), or Maumee Bay (MB) < 0.05) among the 12 sampling groups of free-living (FL) or 500 Ann Microbiol (2018) 68:493–503 Table 1 Physical and chemical data collected for all sampling locations and dates Lake Sampling date Temperature (°C) Dissolved oxygen Conductivity Secchi Soluble reactive (mg/L) (μS/cm) depth (m) phosphorus (mg/L) Mean (SE) William Harsha Lake July 17 27.3 11.53 235 0.75 1.3 (0.31) September 2 26.7 6.93 242 1.0 1.06 (0.20) Buckeye Lake July 24 25.8 7.52 270 0.25 1.65 (0.47) September 19 19.7 7.48 290 0.5 3.78 (3.78) Maumee Bay August 18 24.1 13.11 408 0.25 1.42 (0.54) September 24 23.0 13.18 374 0.5 1.77 (0.35) that selected for a different set of bacteria than those dominant the samples collected in August. The compositional changes in the water column. They did not, however, support the hy- that made this CA community different from the other pothesis that bacterial communities selected by the CA habitat Maumee Bay communities in cluster 3 also increased its dis- type would exhibit lower alpha diversity within lakes or less tance in the NMDS plot from the FL communities of cluster 2 compositional variation between lakes than FL communities. and brought it closer to the CA communities of cluster 1. Furthermore, the dissimilarity between the CA community in Differences among lakes in physicochemical conditions Maumee Bay and other CA communities was equal to or presumably contributed to differences among bacterial com- greater than the dissimilarity between the FL community in munities. In a number of ways, such as the predominantly Maumee Bay and other FL communities. Previous studies agricultural land use of the surrounding watersheds and the revealed compositional differences between CA and FL com- depletion of inorganic nutrients during the cyanobacterial munities within lakes (Li et al. 2011; Louati et al. 2015;Niu et blooms, the lakes are similar. However, other factors such as al. 2011; Parveen et al. 2013a, b; Shi et al. 2012) or differences temperature, size, and conductivity differed. During the sam- among homogenized bacterial communities sampled from pling period of this study, the range of water temperatures multiple lakes (Eiler and Bertilsson 2004), but this study is recorded in Maumee Bay was not different from that in the first, to our knowledge, to distinguish between CA and FL Buckeye Lake (Table 1). However, throughout the entire sum- communities and also compare them across multiple lakes. mer of 2014, temperatures tended to be slightly cooler in Maumee Bay had highly similar FL and CA communities Maumee Bay than in the other lakes (Francy et al. 2015). in August, unlike other lakes in this study and in prior studies Lower temperatures early in the season may have slowed the (Li et al. 2011;Louatietal. 2015; Niu et al. 2011; Parveen et development of the cyanoHAB in Maumee Bay and the dif- al. 2013a, b; Shi et al. 2012). The similarity of the FL and CA ferentiation of the CA community from the FL community. communities in this instance might be due to the relatively Another potential contributing factor is the large surface area early stage of the cyanobacterial bloom. The initial sampling of Maumee Bay. The cyanoHABs in the two reservoirs may of each lake in this study occurred after the cyanobacterial have reached high biovolume densities earlier because their bloom had developed thick green surface scums. This appear- surface waters covered roughly one-seventh of the area of ance coincided with the cyanobacterial biovolume of the Maumee Bay. Additionally, Maumee Bay had by far the 7 3 bloom reaching a density of 1 × 10 μm /mL, as reported in highest conductivity readings and the greatest range of con- Francy et al. (2015). The Maumee Bay cyanoHAB of 2014 ductivity readings (Table 1). Over the course of the season, the reached that density at the beginning of August, whereas the conductivity in Maumee Bay exhibited an even greater range, blooms in Harsha Lake and Buckeye Lake had already met or with a maximum of 727 μS/cm, more than double the maxi- exceeded that density more than a month earlier (Francy et al. mum values for the other lakes (Francy et al. 2015). Although 2015). It is possible that significant dissimilarities between the range of variation in conductivity for these freshwater communities of free-living and cyanobacteria-associated bac- lakes is small compared to brackish waters, differences in teria in other lakes were the result of processes that occurred conductivity within the range of 22–1399 μS/cm have signif- over the course of several weeks. Thus, the CA community in icant effects on the structure of bacterial communities in Maumee Bay may have had less time to become distinct from streams (Lear et al. 2009). Dissolved oxygen was elevated in its surrounding FL community, compared with the other CA Maumee Bay, especially relative to Buckeye Lake (Table 1), communities in this study. By the next sampling date in but the literature shows that this difference between lakes did September, the CA and FL communities in Maumee Bay were not persist throughout the summer (Francy et al. 2015). It is quite distinct, the CA community forming its own cluster unlikely that the separation of clusters in Fig. 2 was dependent upon differences in DO. When Harsha Lake was sampled on while the FL community remained similar in composition to Ann Microbiol (2018) 68:493–503 501 July 17, the DO reading was closer to the values for Maumee Gammaproteobacteria and Bacteroidetes were able to access Bay than to those for Buckeye Lake, yet the bacterial commu- high molecular weight organic compounds without associat- nities, both CA and FL, clustered with the Buckeye Lake com- ing with intact cyanobacteria. Widespread cell lysis would munities rather than the Maumee Bay communities (Fig. 3). release into the water cellular products that would otherwise Because mucilaginous cyanobacterial offer ready access to be exuded gradually, thus eliminating the need for bacteria complex organic molecules (Cottrell and Kirchman 2000; that metabolize these compounds to associate directly with Imanishi et al. 2005; Jones et al. 1994; Kirchman 2002), it cyanobacterial cells. Flavobacteriaceae have been known to was anticipated that CA communities would be dominated become highly abundant among free-living bacteria when by taxa that assimilate carbon and nutrients from these sources high molecular weight organic compounds occurred at high for rapid growth as is common among Gammaproteobacteria concentration in open water (Kirchman 2002), a condition and Bacteroidetes (Cottrell and Kirchman 2000; Kirchman which could follow from high abundances of bacterial 2002; Newton et al. 2011), while FL communities would ex- predators. hibit more evenness of OTU abundances and greater variation in the identities of dominant taxa. Contrary to expectations, the two clusters that contained FL communities, clusters 2 and Conclusion 3, exhibited the greatest dominance of a single family, Sporicthyaceae (Table S2,Fig. 5). The greater abundance of Results from this study support the hypothesis that the kind of this and other Actinobacteria groups in these clusters is con- microhabitat created by dense cyanoHABs selected for simi- sistent with previous studies showing that members of this larly structured assemblages of bacteria across multiple lakes, phylum were predominantly free-living (Allgaier and and that the selective pressures of this habitat type were dif- Grossart 2006; Louati et al. 2015; Parveen et al. 2013b). ferent from those in the water column. Insights gained from However, most of the Gammaproteobacteria that differed sig- this study further understanding of the ways in which nificantly among clusters and two of the highest-abundance cyanoHABs shape aquatic microbial communities. Bacteroidetes families, Cyclobacteriaceae and Cyanobacteria-associated communities from three lakes were Chitinophagaceae, were affiliated with FL-dominated clusters significantly different from free-living communities in taxo- rather than CA-only clusters. This was unexpected, given the nomic composition. The 12 bacterial communities sampled tendency of Gammaproteobacteria and Bacteroidetes to asso- fell into four clusters based on compositional similarity, with ciate with cyanobacterial particles and other large organic par- one cluster consisting of CA communities from Harsha Lake ticles in aquatic environments (Cai et al. 2014; Cottrell and and Buckeye Lake and a second cluster consisting of the FL Kirchmann 2000; Crump et al. 1999;Li etal. 2011;Louati et communities from these two lakes. Cross-lake similarities in al. 2015; Niu et al. 2011; Parveen et al. 2013a; Shi et al. 2012). the composition of CA communities or FL communities can Another unusual feature of the communities examined in be attributed to the similar sizes and physicochemical proper- this study was the importance of Deltaproteobacteria. ties of these lakes as well as to similarities of the microhabitat Bacteriovoracaceae (Bdellovibrionales) were abundant in all types. Samples from Maumee Bay formed their own distinct three lakes, and this family and Bdellovibrionaceae,alsoa clusters, one consisting of CA and FL samples collected short- member of order Bdellovibrionales, were especially abundant ly after the bloom reached its maximum density by in clusters 1 and 2. Several Deltaproteobacteria phylotypes in cyanobacterial biovolume as well as FL samples from a later the order Myxococcales were detected in cluster 1 at abun- date, while the CA samples from a later stage of the bloom dances that were significantly higher than in the other clusters. clustered separately. As the bloom progressed in Maumee Myxococcales are more characteristic of soils and sediments Bay, the FL community remained similar to the earlier sam- than of surface waters (Basak et al. 2015; Kim et al. 2016;Kou ples, while the composition of the CA community became et al. 2016; Zlatković 2017). These bacteria may have entered significantly different. The hypothesis that the CA habitat type the lakes along with sediment from surrounding agricultural would select for a less diverse set of bacteria was not support- lands. Both Bdellovibrionales and Myxococcales are highly ed, as the CA communities overall had neither significantly motile predators that attack and lyse other Gram-negative bac- lower measures of alpha diversity nor greater compositional teria (Cai et al. 2014; Davidov and Jurkevitch 2004;Rotem et similarity among lakes than did the FL communities. This is al. 2014; Velicer et al. 2014), including cyanobacteria (Caiola the first study to separate bacterial communities physically and Pellegrini 1984;Maruyama et al. 2003). Prior studies of associated with mucilaginous cyanobacterial colonies or fila- lakes undergoing cyanoHABs reported Deltaproteobacteria ments from free-living bacteria and to compare the diversity as present but not abundant (Cai et al. 2014; Eiler and and composition of the two types of communities across mul- Bertilsson 2004;Liet al. 2011;Louatietal. 2015; Niu et al. tiple lakes. Further studies are needed to explore the processes 2011). The high abundance of cell-lysing predatory bacteria in that differentiate CA from FL communities and the time scale these lakes may also explain how large numbers of on which these processes occur. 502 Ann Microbiol (2018) 68:493–503 Acknowledgements We thank Christopher Blackwood and Xiaozhen consuming low-and high-molecular-weight dissolved organic mat- Mou for comments on the methods and Alescia Roberto for technical ter. Appl Environ Microbiol 66(4):1692–1697 assistance. Crump BC, Armbrust EV, Baross JA (1999) Phylogenetic analysis of particle-attached and free-living bacterial communities in the Columbia River, its estuary, and the adjacent coastal ocean. Appl Funding Funding sources were an Integrative Graduate Education and Environ Microbiol 65(7):3192–3204 Research Traineeship grant from the National Science Foundation Davidov Y, Jurkevitch E (2004) Diversity and evolution of Bdellovibrio- (0903560) and an Art and Margaret Herrick Memorial Award from and-like organisms (BALOs), reclassification of Bacteriovorax Kent State University. starrii as Peredibacter starrii gen. nov., comb. nov., and description of the Bacteriovorax–Peredibacter clade as Bacteriovoracaceae Compliance with ethical standards fam. nov. Int J Syst Evol Microbiol 54(5):1439–1452 Degnan PH, Ochman H (2012) Illumina-based analysis of microbial Conflict of interest The authors declare that they have no conflict of community diversity. ISME J 6:183–194 interest. Eiler A, Bertilsson S (2004) Composition of freshwater bacterial commu- nities associated with cyanobacterial blooms in four Swedish lakes. Environ Microbiol 6(12):1228–1243 Research involving human participants and/or animals No human or Francy DS, Graham JL, Stelzer EA, Ecker CD, Brady AMG, Struffolino animal participants were involved in this study. P, Loftin KA (2015) Water quality, cyanobacteria, and environmen- tal factors and their relations to microcystin concentrations for use in Informed consent Informed consent rules were not applicable to this predictive models at Ohio Lake Erie and inland lake recreational research because no human participants were involved. sites, 2013–14: U.S. Geological Survey Scientific Investigations Report 2015–5120, 58 p., doi:https://doi.org/10.3133/sir20155120 Francy DS, Brady AM, Ecker CD, Graham JL, Stelzer EA, Struffolino P, Dwyer DF, Loftin KA (2016) Estimating microcystin levels at rec- References reational sites in western Lake Erie and Ohio. Harmful Algae 58:23– Allgaier M, Grossart HP (2006) Seasonal dynamics and phylogenetic Imanishi S, Kato H, Mizuno M, Tsuji K, Harada KI (2005) Bacterial degradation of microcystins and nodularin. Chem ResToxicol diversity of free-living and particle-associated bacterial communities 18(3):591–598 in four lakes in northeastern Germany. Aquat Microb Ecol 45(2): 115–128 Jones GJ, Bourne DG, Blakeley RL, Doelle H (1994) Degradation of the cyanobacterial hepatotoxin microcystin by aquatic bacteria. Nat Anderson MJ, Walsh DC (2013) PERMANOVA, ANOSIM, and the Toxins 2(4):228–235 Mantel test in the face of heterogeneous dispersions: what null hy- Kim JM, Roh AS, Choi SC, Kim EJ, Choi MT, Ahn BK, Kim SK, Lee pothesis are you testing? Ecol Monogr 83(4):557–574 YH, Joa JH, Kang SS, Lee SA, Ahn JH, Song J, Weon HY (2016) Anderson MJ, Ellingsen KE, McArdle BH (2006) Multivariate dispersion Soil pH and electrical conductivity are key edaphic factors shaping as a measure of beta diversity. Ecol Lett 9(6):683–693 bacterial communities of greenhouse soils in Korea. J Microbiol Baker DB, Confesor R, Ewing DE, Johnson LT, Kramer JW, Merryfield 54(12):838–845 BJ (2014) Phosphorus loading to Lake Erie from the Maumee, Kirchman DL (2002) The ecology of Cytophaga–Flavobacteria in aquatic Sandusky and Cuyahoga rivers: the importance of bioavailability. environments. FEMS Microbiol Ecol 39(2):91–100 J Great Lakes Res 40(3):502–517 Kou W, Zhang J, Lu X, Ma Y, Mou X, Wu L (2016) Identification of Basak P, Majumder NS, Nag S, Bhattacharyya A, Roy D, Chakraborty A, bacterial communities in sediments of Poyang Lake, the largest SenGupta S, Roy A, Mukherjee A, Pattanayak R, Ghosh A, freshwater lake in China. SpringerPlus 5(1):401 Chattopadhyay D, Bhattacharyya M (2015) Spatiotemporal analysis Kruskal JB (1964) Nonmetric multidimensional scaling: a numerical of bacterial diversity in sediments of Sundarbans using parallel 16S method. Psychometrika 29:115–129 rRNA gene tag sequencing. Microb Ecol 69(3):500–511 Lear G, Niyogi D, Harding J, Dong Y, Lewis G (2009) Biofilm bacterial Beaulieu JJ, Smolenski RL, Nietch CT, Townsend-Small A, Elovitz MS community structure in streams affected by acid mine drainage. (2014) High methane emissions from a midlatitude reservoir Appl Environ Microbiol 75(11):3455–3460 draining an agricultural watershed. Environ Sci Technol 48(19): Li H, Xing P, Chen M, Bian Y, Wu QL (2011) Short-term bacterial 11100–11108 community composition dynamics in response to accumulation Bray JR, Curtis JT (1957) An ordination of the upland forest communities and breakdown of Microcystis blooms. Water Res 45(4):1702–1710 of southern Wisconsin. Ecol Monogr 27(4):325–349 Louati I, Pascault N, Debroas D, Bernard C, Humbert J-F, Leloup J Cai H, Jiang H, Krumholz LR, Yang Z (2014) Bacterial community (2015) Structural diversity of bacterial communities associated with composition of size-fractioned aggregates within the phycosphere bloom-forming freshwater cyanobacteria differs according to the of cyanobacterial blooms in a eutrophic freshwater lake. PLoS One cyanobacterial genus. PLoS One 10(11):e0140614 9(8):e102879 Maruyama T, Kato K, Yokoyama A, Tanaka T, Hiraishi A, Park HD Caiola MG, Pellegrini S (1984) Lysis of Microcystis aeruginosa (Kütz.) (2003) Dynamics of microcystin-degrading bacteria in mucilage of by Bdellovibrio-like bacteria. J Phycol 20(4):471–475 Microcystis. Microb Ecol 46(2):279–288 Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Michalak AM, Anderson EJ, Beletsky D, Boland S, Bosch NS, Costello EK, Fierer N, Gonzalez Pena A, Goodrich JK, Gordon JI, Bridgeman TB, Chaffin JD, Cho K, Confesor R, Daloglu I, Huttley GA, Kelley ST, Knights D, Koenig JE, Ley RE, Lozupone DePinto JV, Evans MA, Fahnenstiel GL, He L, Ho JC, Jenkens L, CA, McDonald D, Muegge BD, Pirrung M, Reeder J, Sevinsky JR, Johengen TH, Kuo KC, LaPorte E, Liu X, McWilliams MR, Moore Turnbaugh PJ, Walters WA, Widman J, Yatsunenko T, Zaneveld J, MR, Posselt DJ, Richards RP, Scavia D, Steiner AL, Verhamme E, Knight R (2010) QIIME allows analysis of high-throughput com- Wright DM, Zagorski MA (2013) Record-setting algal bloom in munity sequencing data. Nat Methods 7:335–336 Lake Erie caused by agricultural and meteorological trends consis- Cottrell MT, Kirchman DL (2000) Natural assemblages of marine tent with expected future conditions. Proc Natl Acad Sci 110(16): Proteobacteria and members of the Cytophaga-Flavobacter cluster 6448–6452 Ann Microbiol (2018) 68:493–503 503 Mielke PW (1984) Meteorological applications of permutation tech- polysaccharide from the slime layer of the cyanobacterium Microcystis flos-aquae C3-40. Appl Environ Microbiol 57(6): niques based on distance functions. In: Krishnaiah PR, Sen PK th (eds) Handbook of statistics, 4 end. Elsevier Science, New York, 1696–1700 pp 813–830 Ringuet S, Sassano L, Johnson ZI (2011) A suite of microplate reader- Moorhead, D., Bridgeman, T., Morris, J. (2008). Changes in water quality based colorimetric methods to quantify ammonium, nitrate, ortho- of Maumee Bay 1928-2003. In: Munawar, M., and Heath, R. T. phosphate and silicate concentrations for aquatic nutrient monitor- (eds) Checking the Pulse of Lake Erie, Ecovision World ing. J Environ Monit 13(2):370–376 Monograph Series, AEHMS, pp. 123–158 Rotem, O., Pasternak, Z., Jurkevitch, E. (2014). Bdellovibrio and like Murphy J, Riley J (1962) A modified single solution method for deter- organisms. In: Dworkin, M., Falkow, S., Rosenberg, E., Schleifer, rd mination of phosphate in natural waters. Anal Chim Acta 37:31–36 K.-H., Stackebrandt, E. (eds) The prokaryotes, 3 edn., Springer, Newton RJ, Jones SE, Eiler A, McMahon KD, Bertilsson S, (2011).A Berlin Heidelberg pp. 3–17 guide to the natural history of freshwater lake bacteria. Microbiol Shen H, Niu Y, Xie P, Tao MIN, Yang XI (2011) Morphological and MolBiolRev 75(1):14–49 physiological changes in Microcystis aeruginosa as a result of inter- Niu Y, Shen H, Chen J, Xie P, Yang X, Tao M, Ma Z, Qi M (2011) actions with heterotrophic bacteria. Freshw Biol 56(6):1065–1080 Phytoplankton community succession shaping bacterioplankton Shi L, Cai Y, Kong F, Yu Y (2012) Specific association between bacteria community composition in Lake Taihu, China. Water Res 45(14): and buoyant Microcystis colonies compared with other bulk bacte- 4169–4182 rial communities in the eutrophic Lake Taihu, China. Environ Ohio Environmental Protection Agency, 2014. State of Ohio—harmful Microbiol Rep 4(6):669–678 algal bloom response strategy for recreational waters. http://epa. Sun DL, Jiang X, Wu QL, Zhou NY (2013) Intragenomic heterogeneity ohio.gov/habalgae.aspx (Accessed June 2014) of 16S rRNA genes causes overestimation of prokaryotic diversity. Paerl HW (1996) Microscale physiological and ecological studies of Appl Environ Microbiol 79(19):5962–5969 aquatic cyanobacteria: macroscale implications. Microsc Res Tech Taylor, M., Governor, L. (2012). Biological and water quality study of the 33(1):47–72 Licking River. Ohio EPA Division of Surface Water. http://www. Paerl HW, Paul VJ (2012) Climate change: links to global expansion of epa.state.oh.us/portals/35/documents/2008lickingtsd.pdf.Accessed harmful cyanobacteria. Water Res 46:1349–1363 11 December 2017 Parikh A, Madamwar D (2006) Partial characterization of extracellular Velicer GJ, Mendes-Soares H, Wielgoss S (2014) Whence comes social polysaccharides from cyanobacteria. Bioresour Technol 97(15): diversity? Ecological and evolutionary analysis of the myxobacteria. 1822–1827 Myxobacteria: genomics. Cell Mol Biol:1–29 Parveen B, Ravet V, Djediat C, Mary I, Quiblier C, Debroas D, Humbert Velichko N, Chernyaeva E, Averina S, Gavrilova O, Lapidus A, Pinevich JF (2013a) Bacterial communities associated with Microcystis colo- A (2015) Consortium of the ‘bichlorophyllous’ cyanobacterium nies differ from free-living communities living in the same ecosys- Prochlorothrix hollandica and chemoheterotrophic partner bacteria: tem. Environ Microbiol Rep 5(5):716–724 culture and metagenome-based description. Environ Microbiol Rep Parveen B, Mary I, Vellet A, Ravet V, Debroas D (2013b) Temporal dy- 7(4):623–633 namics and phylogenetic diversity of free-living and particle- Xu H, Yu G, Jiang H (2013) Investigation on extracellular polymeric associated Verrucomicrobia communities in relation to environmental substances from mucilaginous cyanobacterial blooms in eutrophic variables in a mesotrophic lake. FEMS Microbiol Ecol 83:189–201 freshwater lakes. Chemosphere 93(1):75–81 Pereira S, Zille A, Micheletti E, Moradas-Ferreira P, De Philippis R, Zhang BH, Salam N, Cheng J, Li HQ, Yang JY, Zha DM, Guo QG, Li WJ Tamagnini P (2009) Complexity of cyanobacterial (2016) Microbacterium lacusdiani sp. nov., a phosphate-solubilizing exopolysaccharides: composition, structures, inducing factors and novel actinobacterium isolated from mucilaginous sheath of putative genes involved in their biosynthesis and assembly. FEMS Microcystis. J Antibiot. https://doi.org/10.1038/ja.2016.125 Microbiol Revi 33(5):917–941 Zlatković S (2017) Some metabolic, diversity and toxicity aspects of Plude JL, Parker DL, Schommer OJ, Timmerman RJ, Hagstrom SA, bacterial communities life in aquatic sediments. J Microbiol Exp Joers JM, Hnasko R (1991) Chemical characterization of 5(4):00156
Annals of Microbiology – Springer Journals
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