Investigating Microbial Eukaryotic Diversity from a Global Census: Insights from a Comparison of Pyrotag and Full-Length Sequences of 18S rRNA Genes

Next-generation DNA sequencing (NGS) approaches are rapidly surpassing Sanger sequencing for characterizing the diversity of natural microbial communities. Despite this rapid transition, few comparisons exist between Sanger sequences and the generally much shorter reads of NGS. Operational taxonomic units (OTUs) derived from full-length (Sanger sequencing) and pyrotag (454 sequencing of the V9 hypervariable region) sequences of 18S rRNA genes from 10 global samples were analyzed in order to compare the resulting protistan community structures and species richness. Pyrotag OTUs called at 98% sequence similarity yielded numbers of OTUs that were similar overall to those for full-length sequences when the latter were called at 97% similarity. Singleton OTUs strongly influenced estimates of species richness but not the higher-level taxonomic composition of the community. The pyrotag and full-length sequence data sets had slightly different taxonomic compositions of rhizarians, stramenopiles, cryptophytes, and haptophytes, but the two data sets had similarly high compositions of alveolates. Pyrotag-based OTUs were often derived from sequences that mapped to multiple full-length OTUs at 100% similarity. Thus, pyrotags sequenced from a single hypervariable region might not be appropriate for establishing protistan species-level OTUs. However, nonmetric multidimensional scaling plots constructed with the two data sets yielded similar clusters, indicating that beta diversity analysis results were similar for the Sanger and NGS sequences. Short pyrotag sequences can provide holistic assessments of protistan communities, although care must be taken in interpreting the results. The longer reads (>500 bp) that are now becoming available through NGS should provide powerful tools for assessing the diversity of microbial eukaryotic assemblages.     

Low sequencing efforts bias analyses of shared taxa in microbial communities

The potential for comparing microbial community population structures has been greatly enhanced by developments in next generation sequencing methods that can generate hundreds of thousands to millions of reads in a single run. Conversely, many microbial community comparisons have been published with no more than 1,000 sequences per sample. These studies have presented data on levels of shared operational taxonomic units (OTUs) between communities. Due to lack of coverage, that approach might compromise the conclusions about microbial diversity and the degree of difference between environments. In this study, we present data from recent studies that highlight this problem. Also, we analyzed datasets of 16 rRNA sequences with small and high sequence coverage from different environments to demonstrate that the level of sequencing effort used for analyzing microbial communities biases the results. We randomly sampled pyrosequencing-generated 16S rRNA gene libraries with increasing sequence effort. Sequences were used to calculate Good's coverage, the percentage of shared OTUs, and phylogenetic distance measures. Our data showed that simple counts of presence/absence of taxonomic unities do not reflect the real similarity in membership and structure of the bacterial communities and that community comparisons based on phylogenetic tests provide a way to test statistically significant differences between two or more environments without need an exhaustive sampling effort.     

Incorporating 16S Gene Copy Number Information Improves Estimates of Microbial Diversity and Abundance

The abundance of different SSU rRNA (“16S”) gene sequences in environmental samples is widely used in studies of microbial ecology as a measure of microbial community structure and diversity. However, the genomic copy number of the 16S gene varies greatly – from one in many species to up to 15 in some bacteria and to hundreds in some microbial eukaryotes. As a result of this variation the relative abundance of 16S genes in environmental samples can be attributed both to variation in the relative abundance of different organisms, and to variation in genomic 16S copy number among those organisms. Despite this fact, many studies assume that the abundance of 16S gene sequences is a surrogate measure of the relative abundance of the organisms containing those sequences. Here we present a method that uses data on sequences and genomic copy number of 16S genes along with phylogenetic placement and ancestral state estimation to estimate organismal abundances from environmental DNA sequence data. We use theory and simulations to demonstrate that 16S genomic copy number can be accurately estimated from the short reads typically obtained from high-throughput environmental sequencing of the 16S gene, and that organismal abundances in microbial communities are more strongly correlated with estimated abundances obtained from our method than with gene abundances. We re-analyze several published empirical data sets and demonstrate that the use of gene abundance versus estimated organismal abundance can lead to different inferences about community diversity and structure and the identity of the dominant taxa in microbial communities. Our approach will allow microbial ecologists to make more accurate inferences about microbial diversity and abundance based on 16S sequence data.     

Amplification by PCR artificially reduces the proportion of the rare biosphere in microbial communities

The microbial world has been shown to hold an unimaginable diversity. The use of rRNA genes and PCR amplification to assess microbial community structure and diversity present biases that need to be analyzed in order to understand the risks involved in those estimates. Herein, we show that PCR amplification of specific sequence targets within a community depends on the fractions that those sequences represent to the total DNA template. Using quantitative, real-time, multiplex PCR and specific Taqman probes, the amplification of 16S rRNA genes from four bacterial species within a laboratory community were monitored. Results indicate that the relative amplification efficiency for each bacterial species is a nonlinear function of the fraction that each of those taxa represent within a community or multispecies DNA template. Consequently, the low-proportion taxa in a community are under-represented during PCR-based surveys and a large number of sequences might need to be processed to detect some of the bacterial taxa within the 'rare biosphere'. The structure of microbial communities from PCR-based surveys is clearly biased against low abundant taxa which are required to decipher the complete extent of microbial diversity in nature.     

Analysis of environmental microbial communities by reverse sample genome probing

Development of fast and accurate methods for monitoring environmental microbial diversity is one of the great challenges in microbiology today. Oligonucleotide probes based on 16S rRNA sequences are widely used to identify bacteria in the environment. However, the successful development of a chip of immobilized 16S rRNA probes for identification of large numbers of species in a single hybridization step has not yet been reported. In reverse sample genome probing (RSGP), labelled total community DNA is hybridized to arrays in which genomes of cultured microorganisms are spotted on a solid support in denatured form. This method has provided useful information on changes in composition of the cultured component of microbial communities in oil fields, the soil rhizhosphere, hydrocarbon-contaminated soils and acid mine drainage sites. Applications and limitations of the method, as well as the prospects of extending RSGP to cover also the as yet uncultured component of microbial communities, are evaluated.     

盐城滨海滩涂湿地典型植物群落土壤微生物组成与结构特征

土壤微生物是生态系统维持正常结构与功能的重要组成部分,为探究盐城滩涂典型湿地土壤微生物群落结构特征,以江苏盐城滩涂互花米草、藨草、盐地碱蓬、芦苇及淤泥质光滩5种典型群落为对象,采用16S rRNA高通量测序技术分析0—10 cm(表层)、10—30 cm(中层)、30—60 cm(深层)土壤微生物多样性及群落结构。结果表明：(1)几种植物群落间,土壤微生物群落结构差异较大,主要体现在细菌群落结构的差异性,古菌群落结构差异相对较小。光滩与植物群落间,在土壤细菌种类及相对丰度上差异相对较大,互花米草群落与本土植物群落间,在微生物群落的细菌种类组成上存在较大差异;藨草群落土壤表层微生物群落结构与互花米草群落相似,深层与盐地碱蓬、芦苇群落相似。(2)同一群落不同层次土壤微生物群落结构相似,差异小于不同群落间土壤微生物群落的结构差异性;不同群落对应层次间,表深层土壤中五种群落土壤微生物多样性存在显著差异,中层土壤中五种群落微生物多样性差异不显著。总体上,植物群落类型对土壤微生物群落结构的影响大于土壤深度;与本土植物群落相比,互花米草群落土壤主要优势门微生物种类差异较小,但部分优势门微生物相对丰度...     

Estimating Bacterial Diversity for Ecological Studies: Methods,Metrics, and Assumptions

Methods to estimate microbial diversity have developed rapidly in an effort to understand the distribution and diversity of microorganisms in natural environments. For bacterial communities, the 16S rRNA gene is the phylogenetic marker gene of choice, but most studies select only a specific region of the 16S rRNA to estimate bacterial diversity. Whereas biases derived from from DNA extraction, primer choice and PCR amplification are well documented, we here address how the choice of variable region can influence a wide range of standard ecological metrics, such as species richness, phylogenetic diversity, β-diversity and rank-abundance distributions. We have used Illumina paired-end sequencing to estimate the bacterial diversity of 20 natural lakes across Switzerland derived from three trimmed variable 16S rRNA regions (V3, V4, V5). Species richness, phylogenetic diversity, community composition, β-diversity, and rank-abundance distributions differed significantly between 16S rRNA regions. Overall, patterns of diversity quantified by the V3 and V5 regions were more similar to one another than those assessed by the V4 region. Similar results were obtained when analyzing the datasets with different sequence similarity thresholds used during sequences clustering and when the same analysis was used on a reference dataset of sequences from the Greengenes database. In addition we also measured species richness from the same lake samples using ARISA Fingerprinting, but did not find a strong relationship between species richness estimated by Illumina and ARISA. We conclude that the selection of 16S rRNA region significantly influences the estimation of bacterial diversity and species distributions and that caution is warranted when comparing data from different variable regions as well as when using different sequencing techniques.     

Estimating similarity of communities: a parametric approach to spatio‐temporal analysis of species diversity

Several stochastic models with environmental noise generate spatio‐temporal Gaussian fields of log densities for the species in a community. Combinations of such models for many species often lead to lognormal species abundance distributions. In spatio‐temporal analysis it is often realistic to assume that the same species are expected to occur at different times and/or locations because extinctions are rare events. Spatial and temporal β‐diversity can then be analyzed by studying pairs of communities at different times or locations defined by a bivariate lognormal species abundance model in which a single correlation occurs. This correlation, which is a measure of similarity between two communities, can be estimated from samples even if the sampling intensities vary and are unknown, using the bivariate Poisson lognormal distribution. The estimators are approximately unbiased, although each specific correlation may be rather uncertain when the sampling effort is low with only a small fraction of the species represented in the samples. An important characteristic of this community correlation is that it relates to the classical Jaccard‐ or the Sørensen‐indices of similarity based on the number of species present or absent in two communities. However, these indices calculated from samples of species in a community do not necessarily reflect similarity of the communities because the observed number of species depends strongly on the sampling intensities. Thus, we propose that our community correlation should be considered as an alternative to these indices when comparing similarity of communities. We illustrate the application of the correlation method by computing the similarity between temperate bird communities.     

Soil microbial community analysis using two-dimensional polyacrylamide gel electrophoresis of the bacterial ribosomal internal transcribed spacer regions

Two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) of digested genomic DNA has been previously used in comparative genomics studies of closely related bacteria species. However, a two-dimensional gel electrophoresis approach for examining microbial community structures in environmental samples has not yet been developed. We determined that it is theoretically possible to separate internal transcribed spacer regions (ITS) of bacterial communities into hundreds of operational taxonomic units (OTUs) using 2D-PAGE. Application of 2D-PAGE for separating Bacterial ITS sequences that have been PCR-amplified from replicate soil samples taken from along a Zn gradient resulted in reproducible gels containing hundreds of spots. Clear differences in spot patterns were observed between soil samples that differed in both sampling location and Zn content. The number of OTUs detected using 2D-PAGE of ITS regions was much greater than that observed using Automated Ribosomal Internal Transcribed Spacer Analysis (ARISA), Terminal Restriction Fragment Length Polymorphism (T-RFLP), or Denaturing Gradient Gel Electrophoresis (DGGE). Principal Component Analysis (PCA) of community spot patterns resulted in similar groupings of samples as those obtained using other molecular methods, however, excised spots were found to contain a far lower diversity of different sequences than excised ITS bands of the same length, as determined by RFLP analysis of excision clone libraries and subsequent sequencing of DNA eluted from excised spots. This increase in resolution makes 2D-PAGE of Bacteria ITS fragments from complex microbial communities a viable method for detecting differences between highly similar communities, as well as in streamlining follow-on sequencing efforts by reducing the level of homoplasy (co-migration of heterogeneous sequences) often seen in band-based community fingerprinting methods.     

Archaea, Bacteria, and Algal Plastids Associated with the Reef-Building Corals Siderastrea stellata and Mussismilia hispida from Búzios, South Atlantic Ocean, Brazil

Reef-building corals may be seen as holobiont organisms, presenting diverse associated microbial communities. Best known is the symbiotic relationship with zooxanthellae, but Archaea, Bacteria, fungi, viruses, and algal plastids are also abundant. Until now, there is little information concerning microbial communities associated with Brazilian corals. The present study aims to describe the diversity of Archaea, Bacteria, and eukaryotic algal plastid communities associated with two sympatric species, Siderastrea stellata and Mussismilia hispida, from Southeastern Brazil, using 16S rRNA gene libraries. Since corals present a high number of other associated invertebrates, coral barcoding (COI) was performed to confirm the exclusive occurrence of coral DNA in our samples. Our analysis yielded 354 distinct microbial OTUs, represented mainly by novel phylotypes. Richness (Chao1 and ACE) and diversity (H') estimations of the microbial communities associated with both species were high and comparable to other studies. Rarefaction analyses showed that microbial diversity of S. stellata is higher than that of M. hispida. Libshuff comparative analyses showed that the highest microbial community similarity between the two coral species occurred in the bacterial libraries, while archaeal and plastidial communities were significantly different. Crenarchaeota dominated archaeal communities, while Proteobacteria was the most abundant bacterial phylum, dominated by alpha-Proteobacteria. Plastids were also represented by novel phylotypes and did not match with any 16S rRNA sequences of Cyanobacteria and zooxanthellae from GenBank. Our data improves the pool of available information on Brazilian coral microbes and shows corals as sources of diverse prokaryotic and picoeukaryotic communities.     

Patterns and drivers of wild bee community assembly in a Mediterranean IUCN important plant area

Recent reports of pollinator declines have stirred interest in investigating the impacts of habitat exploitation on the conservation of pollinator and plant communities. An important prerequisite to tailor conservation action is to understand the drivers and patterns of species-rich communities, and how they change in space and time during a whole season. To account for this, we surveyed wild bees and flowering plants using standardized transects in 11 natural habitat fragments of an IUCN important plant area along the coast of Israel. We used phylogeny- and taxon-based methods of community structure analyses to study the assembly processes of bee communities, and investigated the effects of several landscape parameters on bee diversity using generalized linear models (GLMs). Our results illustrate that natural habitat sites comprised significantly higher species richness compared to disturbed habitat sites, and show that even the smallest habitat fragments harbored unique bee assemblages, with significant species replacement (turnover) found in both space and time. Our GLMs indicated that flower diversity, and semi-natural habitat within 500 m of habitat fragments were important drivers of bee diversity, but we found no evidence for a species—area relationship among sites. Finally, we document a case of phylogenetic overdispersion despite low species richness, which highlights the importance of accounting for phylogenetic diversity rather than only species richness to reach a more fine-grained understanding of pollinator diversity. This, in turn, is pivotal to developing conservation actions to protect these essential pollinators and their interaction with rare and endemic plant species in this highly threatened ecosystem.     

Phylogenetic diversity of endolithic bacteria in Bole granite rock in Xinjiang

The endolithic environment is a ubiquitous microbial habitat for microorganisms, such as lichens, Cyanobacteria and fungi, and it provides mineral nutrients and growth surfaces. In extremely environments, such as hot and cold desert, endolithic communities are often the main form of life. More recently, endolithic microbial communities have been observed inhabiting a variety of rock types ranging from hard granite to porous rocks such as basalt, dolomite, limestone, sandstone and granites. Regardless of geographic location and rock type, each of these habitats is characterized by a subsurface microclimate that prevents endolithic microorganisms growth. Photosynthesis-based endolithic microbial communities commonly inhabit the outer millimeters to centimeters of rocks exposed to the surface. The ability to fix carbon dioxide and in some cases atmospheric dinitrogen, gives the Cyanobacteria a clear competitive advantage over heterotrophic bacteria, so it is been called the main primary producer. Light quality and intensity appear to be the main determinant of the maximum depth to which growth occurs in endolithic phototrophic communities. Valleys of Fantastic Rocks in Bole is close to Alashankou Port of Xinjiang which belongs to extreme continental climate. In order to investigate the structure, composition and diversity of endolithic bacterial community in exposed granitic porphyry in the Valleys of Fantastic Rocks, environmental DNA was directly extracted from granite rock, the 16S rRNA genes were amplified from the total DNA by PCR with bacterial-specific primers, and an endolithic bacterial clone library was constructed. Positive clones were randomly selected from the library and identified by Restriction Fragment Length Polymorphism (RFLP). The unique rRNA types clones were sequenced, analysised and then constructed phylogenetic tree. In total, 129 positive clones were screened and grouped into 46 operational taxonomic unites (OTUs). The clone coverage C value was 89.15%, indicating that most of the estimated endolithic bacterial diversity was sampled. BLAST analysis indicated that 46 OTUs were divided into seven phyla (Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, Cyanobacteria, Planctomycetes, Proteobacteria) and five unknown groups. Cyanobacteria (43%), especially the Gp I, form the functional basis for an endolithic bacteria community which contain a wide spectrum species of chemotrophic bacteria (33%) with mainly Actinobacteria, α-Proteobacteria, Acidobacteria. Additionally, most clones that derived from the endolithic bacteria clone library showed high similarity to the sequence deposited in GenBank database with 97%–99%. Besides, 35% of the clones showed less than 97% of sequence similarity, of which 12% sequences were affiliated to genus Rubrobacter. The results suggested that endolithic bacteria in Valleys of Fantastic Rocks in Xinjiang were highly diverse in species richness, and maybe have a diversity of potential novel species and lineages.     

A Comparison of Methods for Clustering 16S rRNA Sequences into OTUs

Recent studies of 16S rRNA sequences through next-generation sequencing have revolutionized our understanding of the microbial community composition and structure. One common approach in using these data to explore the genetic diversity in a microbial community is to cluster the 16S rRNA sequences into Operational Taxonomic Units (OTUs) based on sequence similarities. The inferred OTUs can then be used to estimate species, diversity, composition, and richness. Although a number of methods have been developed and commonly used to cluster the sequences into OTUs, relatively little guidance is available on their relative performance and the choice of key parameters for each method. In this study, we conducted a comprehensive evaluation of ten existing OTU inference methods. We found that the appropriate dissimilarity value for defining distinct OTUs is not only related with a specific method but also related with the sample complexity. For data sets with low complexity, all the algorithms need a higher dissimilarity threshold to define OTUs. Some methods, such as, CROP and SLP, are more robust to the specific choice of the threshold than other methods, especially for shorter reads. For high-complexity data sets, hierarchical cluster methods need a more strict dissimilarity threshold to define OTUs because the commonly used dissimilarity threshold of 3% often leads to an under-estimation of the number of OTUs. In general, hierarchical clustering methods perform better at lower dissimilarity thresholds. Our results show that sequence abundance plays an important role in OTU inference. We conclude that care is needed to choose both a threshold for dissimilarity and abundance for OTU inference.     

Synthetic Statistical Approach Reveals a High Degree of Richness of Microbial Eukaryotes in an Anoxic Water Column

Molecular surveys suggest that communities of microbial eukaryotes are remarkably rich, because even large clone libraries seem to capture only a minority of species. This provides a qualitative picture of protistan richness but does not measure its real extent either locally or globally. Statistical analysis can estimate a community's richness, but the specific methods used to date are not always well grounded in statistical theory. Here we study a large protistan molecular survey from an anoxic water column in the Cariaco Basin (Caribbean Sea). We group individual 18S rRNA gene sequences into operational taxonomic units (OTUs) using different cutoff values for sequence similarity (99 to 50%) and systematically apply parametric models and nonparametric estimators to the OTU frequency data to estimate the total protistan diversity. The parametric models provided statistically sound estimates of protistan richness, with biologically meaningful standard errors, maximal data usage, and extensive model diagnostics and were preferable to the available nonparametric tools. Our clone library exceeded 700 clones but still covered only a minority of species and less than half of the larger protistan clades. Our estimates of total protistan richness portray the target community as very rich at all OTU levels, with hundreds of different populations apparently co-occurring in the small (3-liter) volume of our sample, as well as dozens of clades of the highest taxonomic order. These estimates are among the first for microbial eukaryotes that are obtained using state-of-the-art statistical methods and can serve as benchmark numbers for the local diversity of protists.     

S cycling: Characterization of natural communities of sulfate-reducing bacteria by 165 rRNA sequence comparisons

Past studies of microbial communities responsible for geochemical transformations have been limited by an inability to representatively cultivate, and then identify, the constituent members. Ribosomal RNA sequences, particularly 16S-like rRNAs, provide a measure of phylogenetic relationship that can now be used to examine the structure and diversity of microbial communities. Sulfate-reducing bacteria (SRB) play an important role in the sulfur cycle and the terminal mineralization of organic matter in estuarine and marine environments. Because the Gram-negative mesophilic SRB comprise a phylogenetically coherent assemblage, their communities are well suited to explorations through rRNA sequence-based methodologies. In this study we related molecular biological methods using rRNA probes to geochemical measurements at two different sites. At an unvegetated site in northwest Florida, rates of sulfate reduction were low and SRB rRNA comprised about 5% of the total rRNA extracted from the sediment. The other site, a salt marsh in New Hampshire, had higher rates of sulfate-reduction with SRB rRNA accounting for up to 30% of the total rRNA extracted from the sediment. SRB community structure differed dramatically between the two sites with Desulfobulbus rRNA much less abundant in the unvegetated site than in the salt marsh. The differences in these SRB communities reflect differences in the ecology of their habitats.Contribution No. 917 from the Gulf Ecology Division, NHEERL, Gulf Breeze, FL. Correspondence to: R. Devereux.     

内蒙古高原针茅摹群落β多样性研究

用比较样地法调查了内蒙古高原４类地带性针茅（Ｓｔｉｐａ）草原群落的β多样性特征。结果表明,Ｗｈｉｔｔａｃｋｅｒ指数βＷＳ与尺度有关,随取样面积的增加,βＷＳ逐渐降低,取样面积相同时,４类群落的βＷＳ比较接近,各群落 的Ｃｏｄｙ指数最初也随样方面积的扩大而增大,当样方面积扩大到一定尺度时,贝加尔针茅群落和大针茅群落为〉０．５ｍ＾２,克氏针茅群落和小针茅群落为〉２ｍ＾２,Ｃｏｄｙ指数趋于稳定。同一尺度     

Synthetic statistical approach reveals a high degree of richness of microbial eukaryotes in an anoxic water column

Molecular surveys suggest that communities of microbial eukaryotes are remarkably rich, because even large clone libraries seem to capture only a minority of species. This provides a qualitative picture of protistan richness but does not measure its real extent either locally or globally. Statistical analysis can estimate a community's richness, but the specific methods used to date are not always well grounded in statistical theory. Here we study a large protistan molecular survey from an anoxic water column in the Cariaco Basin (Caribbean Sea). We group individual 18S rRNA gene sequences into operational taxonomic units (OTUs) using different cutoff values for sequence similarity (99 to 50%) and systematically apply parametric models and nonparametric estimators to the OTU frequency data to estimate the total protistan diversity. The parametric models provided statistically sound estimates of protistan richness, with biologically meaningful standard errors, maximal data usage, and extensive model diagnostics and were preferable to the available nonparametric tools. Our clone library exceeded 700 clones but still covered only a minority of species and less than half of the larger protistan clades. Our estimates of total protistan richness portray the target community as very rich at all OTU levels, with hundreds of different populations apparently co-occurring in the small (3-liter) volume of our sample, as well as dozens of clades of the highest taxonomic order. These estimates are among the first for microbial eukaryotes that are obtained using state-of-the-art statistical methods and can serve as benchmark numbers for the local diversity of protists.     

Bacterial Communities in the Rhizosphere of Biofuel Crops Grown on Marginal Lands as Evaluated by 16S rRNA Gene Pyrosequences

Microbes are key components of the soil environment and are important contributors to the sustainability of agricultural systems, which is especially significant for biofuel crops growing on marginal lands. We studied bacterial communities in the rhizosphere of five biofuel crops cultivated in four locations in Michigan to determine which factors were correlated to changes in the structure of those communities. Three of these sites were marginal lands in that two were not suitable for conventional agriculture and one was regulated as a brownfield due to prior industrial pollution. Bacterial community composition and structure were assessed by 454 sequencing of the 16S rRNA gene. A total of 387,111 sequences were used for multivariate statistical analysis and to test for correlation between community structure and environmental variables such as plant species, soil attributes, and location. The most abundant bacterial phyla found in the rhizosphere of all crops were Acidobacteria, Proteobacteria, Actinobacteria, and Verrucomicrobia. Bacterial communities grouped by location rather than by crop and their structures were correlated to soil attributes, principally pH, organic matter, and nutrients. The effect of plant species was low but significant, and interactions between locations, plant species, and soil attributes account for most of the explained variation in the structure of bacterial communities, showing a complex relationship between bacterial populations and their environment. Bacterial diversity was higher in the agricultural sites compared to adjacent forest sites, indicating that the cultivation of those biofuel crops increased the rRNA diversity.     

Community analysis of a full-scale anaerobic bioreactor treating paper mill wastewater

To get insight into the microbial community of an Upflow Anaerobic Sludge Blanket reactor treating paper mill wastewater, conventional microbiological methods were combined with 16S rRNA gene analyses. Particular attention was paid to microorganisms able to degrade propionate or butyrate in the presence or absence of sulphate. Serial enrichment dilutions allowed estimating the number of microorganisms per ml sludge that could use butyrate with or without sulphate (10(5)), propionate without sulphate (10(6)), or propionate and sulphate (10(8)). Quantitative RNA dot-blot hybridisation indicated that Archaea were two-times more abundant in the microbial community of anaerobic sludge than Bacteria. The microbial community composition was further characterised by 16S rRNA-gene-targeted Denaturing Gradient Gel Electrophoresis (DGGE) fingerprinting, and via cloning and sequencing of dominant amplicons from the bacterial and archaeal patterns. Most of the nearly full length (approximately 1.45 kb) bacterial 16S rRNA gene sequences showed less than 97% similarity to sequences present in public databases, in contrast to the archaeal clones (approximately. 1.3 kb) that were highly similar to known sequences. While Methanosaeta was found as the most abundant genus, also Crenarchaeote-relatives were identified. The microbial community was relatively stable over a period of 3 years (samples taken in July 1999, May 2001, March 2002 and June 2002) as indicated by the high similarity index calculated from DGGE profiles (81.9+/-2.7% for Bacteria and 75.1+/-3.1% for Archaea). 16S rRNA gene sequence analysis indicated the presence of unknown and yet uncultured microorganisms, but also showed that known sulphate-reducing bacteria and syntrophic fatty acid-oxidising microorganisms dominated the enrichments.