Automated approach for ribosomal intergenic spacer analysis of microbial diversity and its application to freshwater bacterial communities.

An automated method of ribosomal intergenic spacer analysis (ARISA) was developed for the rapid estimation of microbial diversity and community composition in freshwater environments. Following isolation of total community DNA, PCR amplification of the 16S-23S intergenic spacer region in the rRNA operon was performed with a fluorescence-labeled forward primer. ARISA-PCR fragments ranging in size from 400 to 1,200 bp were next discriminated and measured by using an automated electrophoresis system. Database information on the 16S-23S intergenic spacer was also examined, to understand the potential biases in diversity estimates provided by ARISA. In the analysis of three natural freshwater bacterial communities, ARISA was rapid and sensitive and provided highly reproducible community-specific profiles at all levels of replication tested. The ARISA profiles of the freshwater communities were quantitatively compared in terms of both their relative diversity and similarity level. The three communities had distinctly different profiles but were similar in their total number of fragments (range, 34 to 41). In addition, the pattern of major amplification products in representative profiles was not significantly altered when the PCR cycle number was reduced from 30 to 15, but the number of minor products (near the limit of detection) was sensitive to changes in cycling parameters. Overall, the results suggest that ARISA is a rapid and effective community analysis technique that can be used in conjunction with more accurate but labor-intensive methods (e.g., 16S rRNA gene cloning and sequencing) when fine-scale spatial and temporal resolution is needed.     

Automated Approach for Ribosomal Intergenic Spacer Analysis of Microbial Diversity and Its Application to Freshwater Bacterial Communities

An automated method of ribosomal intergenic spacer analysis (ARISA) was developed for the rapid estimation of microbial diversity and community composition in freshwater environments. Following isolation of total community DNA, PCR amplification of the 16S-23S intergenic spacer region in the rRNA operon was performed with a fluorescence-labeled forward primer. ARISA-PCR fragments ranging in size from 400 to 1,200 bp were next discriminated and measured by using an automated electrophoresis system. Database information on the 16S-23S intergenic spacer was also examined, to understand the potential biases in diversity estimates provided by ARISA. In the analysis of three natural freshwater bacterial communities, ARISA was rapid and sensitive and provided highly reproducible community-specific profiles at all levels of replication tested. The ARISA profiles of the freshwater communities were quantitatively compared in terms of both their relative diversity and similarity level. The three communities had distinctly different profiles but were similar in their total number of fragments (range, 34 to 41). In addition, the pattern of major amplification products in representative profiles was not significantly altered when the PCR cycle number was reduced from 30 to 15, but the number of minor products (near the limit of detection) was sensitive to changes in cycling parameters. Overall, the results suggest that ARISA is a rapid and effective community analysis technique that can be used in conjunction with more accurate but labor-intensive methods (e.g., 16S rRNA gene cloning and sequencing) when fine-scale spatial and temporal resolution is needed.     

Influence of Commonly Used Primer Systems on Automated Ribosomal Intergenic Spacer Analysis of Bacterial Communities in Environmental Samples

Due to the high diversity of bacteria in many ecosystems, their slow generation times, specific but mostly unknown nutrient requirements and syntrophic interactions, isolation based approaches in microbial ecology mostly fail to describe microbial community structure. Thus, cultivation independent techniques, which rely on directly extracted nucleic acids from the environment, are a well-used alternative. For example, bacterial automated ribosomal intergenic spacer analysis (B-ARISA) is one of the widely used methods for fingerprinting bacterial communities after PCR-based amplification of selected regions of the operon coding for rRNA genes using community DNA. However, B-ARISA alone does not provide any taxonomic information and the results may be severely biased in relation to the primer set selection. Furthermore, amplified DNA stemming from mitochondrial or chloroplast templates might strongly bias the obtained fingerprints. In this study, we determined the applicability of three different B-ARISA primer sets to the study of bacterial communities. The results from in silico analysis harnessing publicly available sequence databases showed that all three primer sets tested are specific to bacteria but only two primers sets assure high bacterial taxa coverage (1406f/23Sr and ITSF/ITSReub). Considering the study of bacteria in a plant interface, the primer set ITSF/ITSReub was found to amplify (in silico) sequences of some important crop species such as Sorghum bicolor and Zea mays. Bacterial genera and plant species potentially amplified by different primer sets are given. These data were confirmed when DNA extracted from soil and plant samples were analyzed. The presented information could be useful when interpreting existing B-ARISA results and planning B-ARISA experiments, especially when plant DNA can be expected.     

Molecular characterization of fungal community dynamics in the initial stages of composting

Composting relies on a complex network of bacteria and fungi to process crude organic material. Although it is known that these organisms drive dynamic changes in temperature and pH, little is known about the temporal dynamics of fungal populations during the rise to thermophilic conditions. This study employed F-ARISA (fungal-automated rRNA intergenic spacer analysis) and 18S rRNA gene cloning and sequencing to examine changes in community structure during this period. Sequencing of the 18S rRNA portion of cloned F-ARISA products revealed the presence of four distinct fungal genera including Backusella sp., Mucoraceae, Geotrichum sp. and the yeast Pichia sp. Based on the presence and absence of these ARISA operational taxonomic units (A-OTUs), we observed a shift in fungal community structure between 48 and 60 h. This change in community structure preceded a rise in pH and coincided with an increase in temperature. Clone libraries constructed using fungi-specific 18S rRNA primers contained sequences similar to several other fungal genera including Penicillium sp., Aspergillus sp., Hamigera sp., Neurospora sp. and the yeast Candida sp. While the fungal species richness was relatively low at any time point, the community structure was dynamic and paralleled changes in bacterial community structure.     

Diversity and ecology of soil fungal communities: increased understanding through the application of molecular techniques

Fungi fulfil a range of important ecological functions, yet current understanding of fungal biodiversity in soil is limited. Direct DNA extraction from soil, coupled with polymerase chain reaction amplification and community profiling techniques, has proved successful in investigations of bacterial ecology and shows great promise for elucidating the taxonomic and functional characteristics of soil fungal communities. These community profiling techniques include denaturing gradient gel electrophoresis (DGGE), temperature gradient gel electrophoresis (TGGE), single-strand conformation polymorphism (SSCP), terminal restriction fragment length polymorphism (T-RFLP), amplified rDNA restriction analysis (ARDRA), amplified ribosomal intergenic spacer analysis (ARISA) and cloning, and are generally coupled with DNA sequencing. The techniques and their potential limitations are discussed, along with recent advances that have been made possible through their application in soil fungal ecology. It is unlikely that a single approach will be universally applicable for assessing fungal diversity in all soils or circumstances. However, judicious selection of the methodology, keeping the experimental aims in mind, and the exploitation of emerging technologies will undoubtedly increase our understanding of soil fungal communities in the future.     

Comparison of different primer sets for use in automated ribosomal intergenic spacer analysis of complex bacterial communities

ITSF and ITSReub, constituting a new primer set designed for the amplification of the 16S-23S rRNA intergenic transcribed spacers, have been compared with primer sets consisting of 1406F and 23Sr (M. M. Fisher and E. W. Triplett, Appl. Environ. Microbiol. 65:4630-4636, 1999) and S-D-Bact-1522-b-S-20 and L-D-Bact-132-a-A-18 (L. Ranjard et al., Appl. Environ. Microbiol. 67:4479-4487, 2001), previously proposed for automated ribosomal intergenic spacer analysis (ARISA) of complex bacterial communities. An agricultural soil and a polluted soil, maize silage, goat milk, a small marble sample from the facade of the Certosa of Pavia (Pavia, Italy), and brine from a deep hypersaline anoxic basin in the Mediterranean Sea were analyzed with the three primer sets. The number of peaks in the ARISA profiles, the range of peak size (width of the profile), and the reproducibility of results were used as indices to evaluate the efficiency of the three primer sets. The overall data showed that ITSF and ITSReub generated the most informative (in term of peak number) and reproducible profiles and yielded a wider range of spacer sizes (134 to 1,387) than the other primer sets, which were limited in detecting long fragments. The minimum amount of DNA template and sensitivity in detection of minor DNA populations were evaluated with artificial mixtures of defined bacterial species. ITSF and ITSReub amplified all the bacteria at DNA template concentrations from 280 to 0.14 ng microl(-1), while the other primer sets failed to detect the spacers of one or more bacterial strains. Although the primer set consisting of ITSF and ITSReub and that of S-D-Bact-1522-b-S-20 and L-D-Bact-132-a-A-18 showed similar sensitivities for the DNA of Allorhizobium undicula mixed with the DNA of other species, the S-D-Bact-1522-b-S-20 and L-D-Bact-132-a-A-18 primer set failed to detect the DNA of Pseudomonas stutzeri.     

Field and microcosm experiments to evaluate the effects of agricultural Cu treatment on the density and genetic structure of microbial communities in two different soils

The effects of Cu amendment on indigenous soil microorganisms were investigated in two soils, a calcareous silty clay (Ep) and a sandy soil (Au), by means of a 1-year field experiment and a two-month microcosm incubation. Cu was added as 'Bordeaux mixture' [CuSO(4), Ca(OH)(2)] at the standard rate used in viticulture (B1=16 kg Cu kg(-1) soil) and at a higher level of contamination (B3=48 kg Cu ha(-1) soil). More extractable Cu was observed in sandy soil (Au) than in silty soil (Ep). Furthermore, total Cu and Cu-EDTA declined with time in Au soil, whereas they remained stable in Ep soil. Quantitative modifications of the microflora were assessed by C-biomass measurements and qualitative modifications were assessed by the characterization of the genetic structure of bacterial and fungal communities from DNA directly extracted from the soil, using B- and F-ARISA (bacterial and fungal automated ribosomal intergenic spacer analysis). In the field study, no significant modifications were observed in C-biomass whereas microcosm incubation showed a decrease in B3 contamination only. ARISA fingerprinting showed slight but significant modifications of bacterial and fungal communities in field and microcosm incubation. These modifications were transient in all cases, suggesting a short-term effect of Cu stress. Microcosm experiments detected the microbial community modifications with greater precision in the short-term, while field experiments showed that the biological effects of Cu contamination may be overcome or hidden by pedo-climatic variations.     

Richness and diversity of bacterioplankton species along an estuarine gradient in Moreton Bay, Australia

Bacterioplankton community diversity was investigated in the subtropical Brisbane River-Moreton Bay estuary, Australia (27 degrees 25 minutes S, 153 degrees 5 minutes E). Bacterial communities were studied using automated rRNA intergenic spacer analysis (ARISA), which amplifies 16S-23S ribosomal DNA internally transcribed spacer regions from mixed-community DNA and detects the separated products on a fragment analyzer. Samples were collected from eight sites throughout the estuary and east to the East Australian Current (Coral Sea). Bacterioplankton communities had the highest operational taxonomic unit (OTU) richness, as measured by ARISA at eastern bay stations (S [total richness] = 84 to 85 OTU) and the lowest richness in the Coral Sea (S = 39 to 59 OTU). Richness correlated positively with bacterial abundance; however, there were no strong correlations between diversity and salinity, NO(3)(-) and PO(4)(3-) concentrations, or chlorophyll a concentration. Bacterioplankton communities at the riverine stations were different from communities in the bay or Coral Sea. The main differences in OTU richness between stations were in taxa that each represented 0.1% (the detection limit) to 0.5% of the total amplified DNA, i.e., the "tail" of the distribution. We found that some bacterioplankton taxa are specific to distinct environments while others have a ubiquitous distribution from river to sea. Bacterioplankton richness and diversity patterns in the estuary are potentially a consequence of greater niche availability, mixing of local and adjacent environment communities, or intermediate disturbance. Furthermore, these results contrast with previous reports of spatially homogeneous bacterioplankton communities in other coastal waters.     

A comparison of fungal communities from four salt marsh plants using automated ribosomal intergenic spacer analysis (ARISA)

Fungal decomposers are important contributors to the detritus-based food webs of salt marsh ecosystems. Knowing the composition of salt marsh fungal communities is essential in understanding how detritus processing is affected by changes in community dynamics. Automated ribosomal intergenic spacer analysis (ARISA) was used to examine the composition of fungal communities associated with four temperate salt marsh plants, Spartina alterniflora (short and tall forms), Juncus roemerianus, Distichlis spicata and Sarcocornia perennis. Plant tissues were homogenized and subjected to a particle-filtration protocol that yielded 106 microm particulate fractions, which were used as a source of fungal isolates and fungal DNA. Genera identified from sporulating cultures demonstrated that the 106 microm particles from each host plant were reliable sources of fungal DNA for ARISA. Analysis of ARISA data by principal component analysis (PCA), principal coordinate analysis (PCO) and species diversity comparisons indicated that the fungal communities from the two grasses, S. alterniflora and D. spicata were more similar to each other than they were to the distinct communities associated with J. roemerianus and S. perennis. Principal component analysis also showed no consistent, seasonal pattern in the composition of these fungal communities. Comparisons of ARISA fingerprints from the different fungal communities and those from pure cultures of selected Spartina ascomycetes supported the host/substrate specificity observed for the fungal communities.     

Comparison of Different Primer Sets for Use in Automated Ribosomal Intergenic Spacer Analysis of Complex Bacterial Communities

ITSF and ITSReub, constituting a new primer set designed for the amplification of the 16S-23S rRNA intergenic transcribed spacers, have been compared with primer sets consisting of 1406F and 23Sr (M. M. Fisher and E. W. Triplett, Appl. Environ. Microbiol. 65:4630-4636, 1999) and S-D-Bact-1522-b-S-20 and L-D-Bact-132-a-A-18 (L. Ranjard et al., Appl. Environ. Microbiol. 67:4479-4487, 2001), previously proposed for automated ribosomal intergenic spacer analysis (ARISA) of complex bacterial communities. An agricultural soil and a polluted soil, maize silage, goat milk, a small marble sample from the façade of the Certosa of Pavia (Pavia, Italy), and brine from a deep hypersaline anoxic basin in the Mediterranean Sea were analyzed with the three primer sets. The number of peaks in the ARISA profiles, the range of peak size (width of the profile), and the reproducibility of results were used as indices to evaluate the efficiency of the three primer sets. The overall data showed that ITSF and ITSReub generated the most informative (in term of peak number) and reproducible profiles and yielded a wider range of spacer sizes (134 to 1,387) than the other primer sets, which were limited in detecting long fragments. The minimum amount of DNA template and sensitivity in detection of minor DNA populations were evaluated with artificial mixtures of defined bacterial species. ITSF and ITSReub amplified all the bacteria at DNA template concentrations from 280 to 0.14 ng μl⁻¹, while the other primer sets failed to detect the spacers of one or more bacterial strains. Although the primer set consisting of ITSF and ITSReub and that of S-D-Bact-1522-b-S-20 and L-D-Bact-132-a-A-18 showed similar sensitivities for the DNA of Allorhizobium undicula mixed with the DNA of other species, the S-D-Bact-1522-b-S-20 and L-D-Bact-132-a-A-18 primer set failed to detect the DNA of Pseudomonas stutzeri.     

Comprehensive detection of bacterial populations by PCR amplification of the 16S-23S rRNA spacer region

PCR amplification of the spacer region between the 16S and 23S rRNA genes is commonly employed for the analysis of bacterial communities. In this analysis, the intergenic spacers are amplified by PCR using primers complementary to conserved regions in the 3' 16S rDNA and 5' 23S rDNA. By this method, the observation of every bacterial population may be limited by several causes. To explore the extent of bacterial populations overlooked by this method, we have used an empirical approach. In a sample containing about 50 colonies, we tested the capability to amplify by PCR the spacers from each colony. We also examined the ability to observe the spacers from each colony in the product obtained after amplification of the DNA extracted from the whole sample, as it is usually performed by this method. Contrarily to our expectations that a significant fraction of colonies would not yield amplification products, spacers were successfully amplified from every colony of two different samples examined. Overall, our results suggest that in spite of well-based theoretical limitations, the analysis of bacterial communities by amplification of the spacer regions can render a comprehensive representation of the more abundant bacterial clades in the sample.     

Comparison of Two Fingerprinting Techniques, Terminal Restriction Fragment Length Polymorphism and Automated Ribosomal Intergenic Spacer Analysis, for Determination of Bacterial Diversity in Aquatic Environments

We investigated bacterial diversity in different aquatic environments (including marine and lagoon sediments, coastal seawater, and groundwater), and we compared two fingerprinting techniques (terminal restriction fragment length polymorphism [T-RFLP] and automated ribosomal intergenic spacer analysis [ARISA]) which are currently utilized for estimating richness and community composition. Bacterial diversity ranged from 27 to 99 phylotypes (on average, 56) using the T-RFLP approach and from 62 to 101 genotypes (on average, 81) when the same samples were analyzed using ARISA. The total diversity encountered in all matrices analyzed was 144 phylotypes for T-RFLP and 200 genotypes for ARISA. Although the two techniques provided similar results in the analysis of community structure, bacterial richness and diversity estimates were significantly higher using ARISA. These findings suggest that ARISA is more effective than T-RFLP in detecting the presence of bacterial taxa accounting for <5% of total amplified product. ARISA enabled also distinction among aquatic bacterial isolates of Pseudomonas spp. which were indistinguishable using T-RFLP analysis. Overall, the results of this study show that ARISA is more accurate than T-RFLP analysis on the 16S rRNA gene for estimating the biodiversity of aquatic bacterial assemblages.     

Comparison of two fingerprinting techniques, terminal restriction fragment length polymorphism and automated ribosomal intergenic spacer analysis, for determination of bacterial diversity in aquatic environments

We investigated bacterial diversity in different aquatic environments (including marine and lagoon sediments, coastal seawater, and groundwater), and we compared two fingerprinting techniques (terminal restriction fragment length polymorphism [T-RFLP] and automated ribosomal intergenic spacer analysis [ARISA]) which are currently utilized for estimating richness and community composition. Bacterial diversity ranged from 27 to 99 phylotypes (on average, 56) using the T-RFLP approach and from 62 to 101 genotypes (on average, 81) when the same samples were analyzed using ARISA. The total diversity encountered in all matrices analyzed was 144 phylotypes for T-RFLP and 200 genotypes for ARISA. Although the two techniques provided similar results in the analysis of community structure, bacterial richness and diversity estimates were significantly higher using ARISA. These findings suggest that ARISA is more effective than T-RFLP in detecting the presence of bacterial taxa accounting for <5% of total amplified product. ARISA enabled also distinction among aquatic bacterial isolates of Pseudomonas spp. which were indistinguishable using T-RFLP analysis. Overall, the results of this study show that ARISA is more accurate than T-RFLP analysis on the 16S rRNA gene for estimating the biodiversity of aquatic bacterial assemblages.     

内蒙草原不同植物功能群及物种对土壤微生物组成的影响

为了分析不同植物群落组成对内蒙古典型草原土壤微生物群落组成的影响,本研究利用植物功能群剔除处理实验平台,采用荧光定量PCR(real-timePCR)和自动核糖体间隔区基因分析(automated ribosomal intergenic spacer analysis,ARISA)技术,对不同植物功能群组成的非根际土壤和常见物种的根际土壤中细菌和真菌的数量及群落结构进行了分析。结果表明,在非根际土壤中,不同植物功能群组成对细菌数量有显著影响,而对真菌数量及细菌和真菌的群落结构影响不明显;在根际土壤中,不同植物物种对细菌、真菌的数量都有显著影响。此外,聚类分析表明,不同物种的根际土中细菌和真菌的群落结构也有所不同,尤其以细菌的群落结构变化较为明显。研究结果表明不同植物物种可以通过根系影响土壤微生物群落组成。     

Combined eukaryotic and bacterial community fingerprinting of natural freshwater biofilms using automated ribosomal intergenic spacer analysis

Biofilms are complex communities playing an important role in aquatic ecosystems. Automated ribosomal intergenic spacer analysis (ARISA) has been used successfully to explore biofilm bacterial diversity. However, a gap remains to be filled as regards its application to biofilm eukaryotic populations. The aim of this study is to use ARISA to detect eukaryotic population shifts in biofilm. We designed a new set of primers to focus specifically on the ITS1-5.8S-ITS2 region of diatoms and tested it on natural biofilms. Additionally, we tested universal primers, used previously to perform ARISA on fungal communities. Cloning and sequencing showed that the universal primer set amplified various eukaryotes, whereas the new set was diatom specific. The new set amplified a wider variety of diatoms. Therefore, the universal set is appropriate to study the general eukaryotic population shifts in biofilms, whereas the new set is more appropriate to study diatoms specifically. We used both primer sets, along with a bacterial set, to study the population shifts in natural river biofilms. Principal component analysis of the ARISA fingerprints revealed seasonal shifts that did not coincide for bacterial and eukaryotic communities. Therefore, the use of both eukaryotic and bacterial primers provides a useful insight to assess microbial succession in biofilms.     

Bacterial communities associated with the rhizosphere of transgenic Bt 176 maize (Zea mays) and its non transgenic counterpart

The effect of transgenic Bt 176 maize on the rhizosphere bacterial community has been studied with a polyphasic approach by comparing the rhizosphere of Bt maize cultivated in greenhouse with that of its non transgenic counterpart grown in the same conditions. In the two plants the bacterial counts of the copiotrophic, oligotrophic and sporeforming bacteria, and the community level catabolic profiling, showed no significant differences; differences between the rhizosphere and bulk soil bacterial communities were evidenced. Automated ribosomal intergenic spacer analysis (ARISA) showed differences also in the rhizosphere communities at different plant ages, as well as between the two plant types. ARISA fingerprinting patterns of soil bacterial communities exposed to root growth solutions, collected from transgenic and non transgenic plants grown in hydroponic conditions, were grouped separately by principal component analysis suggesting that root exudates could determine the selection of different bacterial communities.     

A dynamic programming algorithm for binning microbial community profiles

MOTIVATION: A number of community profiling approaches have been widely used to study the microbial community composition and its variations in environmental ecology. Automated Ribosomal Intergenic Spacer Analysis (ARISA) is one such technique. ARISA has been used to study microbial communities using 16S-23S rRNA intergenic spacer length heterogeneity at different times and places. Owing to errors in sampling, random mutations in PCR amplification, and probably mostly variations in readings from the equipment used to analyze fragment sizes, the data read directly from the fragment analyzer should not be used for down stream statistical analysis. No optimal data preprocessing methods are available. A commonly used approach is to bin the reading lengths of the 16S-23S intergenic spacer. We have developed a dynamic programming algorithm based binning method for ARISA data analysis which minimizes the overall differences between replicates from the same sampling location and time. RESULTS: In a test example from an ocean time series sampling program, data preprocessing identified several outliers which upon re-examination were found to be because of systematic errors. Clustering analysis of the ARISA from different times based on the dynamic programming algorithm binned data revealed important features of the biodiversity of the microbial communities.     

Soil Bacterial and Fungal Community Structure Across a Range of Unimproved and Semi-Improved Upland Grasslands

Changes in soil microbial community structure due to improvement are often attributed to concurrent shifts in floristic community composition. The bacterial and fungal communities of unimproved and semi-improved (as determined by floristic classification) grassland soils were studied at five upland sites on similar geological substrata using both broad-scale (microbial activity and fungal biomass) and molecular [terminal restriction fragment length polymorphism (TRFLP), automated ribosomal intergenic spacer analysis (ARISA)] approaches. It was hypothesized that microbial community structure would be similar in soils from the same grassland type, and that grassland vegetation classifications could thus be used as predictors of microbial community structure. Microbial community measurements varied widely according to both site and grassland type, and trends in the effect of grassland improvement differed between sites. These results were consistent with those from similar studies, and indicated that floristic community composition was not a stable predictor of microbial community structure across sites. This may indicate a lack of correlation between grassland plant composition and soil microbial community structure, or that differences in soil chemistry between sites had larger impacts on soil microbial populations than plant-related effects.     

Microbial community dynamics in a humic lake: differential persistence of common freshwater phylotypes

In an effort to better understand the factors contributing to patterns in freshwater bacterioplankton community composition and diversity, we coupled automated ribosomal intergenic spacer analysis (ARISA) to analysis of 16S ribosomal RNA (rRNA) gene sequences to follow the persistence patterns of 46 individual phylotypes over 3 years in Crystal Bog Lake. Additionally, we sought to identify linkages between the observed phylotype variations and known chemical and biological drivers. Sequencing of 16S rRNA genes obtained from the water column indicated the presence of phylotypes associated with the Actinobacteria, Bacteroidetes, Firmicutes, Proteobacteria, TM7 and Verrucomicrobia phyla, as well as phylotypes with unknown affiliation. Employment of the 16S rRNA gene/ARISA method revealed that specific phylotypes varied independently of the entire bacterial community dynamics. Actinobacteria, which were present on greater than 95% of sampling dates, did not share the large temporal variability of the other identified phyla. Examination of phylotype relative abundance patterns (inferred using ARISA fragment relative fluorescence) revealed a strong correlation between the dominant phytoplankton succession and the relative abundance patterns of the majority of individual phylotypes. Further analysis revealed covariation among unique phylotypes, which formed several distinct bacterial assemblages correlated with particular phytoplankton communities. These data indicate the existence of unique persistence patterns for different common freshwater phylotypes, which may be linked to the presence of dominant phytoplankton species.