Reducing the effects of PCR amplification and sequencing artifacts on 16S rRNA-based studies

The advent of next generation sequencing has coincided with a growth in interest in using these approaches to better understand the role of the structure and function of the microbial communities in human, animal, and environmental health. Yet, use of next generation sequencing to perform 16S rRNA gene sequence surveys has resulted in considerable controversy surrounding the effects of sequencing errors on downstream analyses. We analyzed 2.7×10(6) reads distributed among 90 identical mock community samples, which were collections of genomic DNA from 21 different species with known 16S rRNA gene sequences; we observed an average error rate of 0.0060. To improve this error rate, we evaluated numerous methods of identifying bad sequence reads, identifying regions within reads of poor quality, and correcting base calls and were able to reduce the overall error rate to 0.0002. Implementation of the PyroNoise algorithm provided the best combination of error rate, sequence length, and number of sequences. Perhaps more problematic than sequencing errors was the presence of chimeras generated during PCR. Because we knew the true sequences within the mock community and the chimeras they could form, we identified 8% of the raw sequence reads as chimeric. After quality filtering the raw sequences and using the Uchime chimera detection program, the overall chimera rate decreased to 1%. The chimeras that could not be detected were largely responsible for the identification of spurious operational taxonomic units (OTUs) and genus-level phylotypes. The number of spurious OTUs and phylotypes increased with sequencing effort indicating that comparison of communities should be made using an equal number of sequences. Finally, we applied our improved quality-filtering pipeline to several benchmarking studies and observed that even with our stringent data curation pipeline, biases in the data generation pipeline and batch effects were observed that could potentially confound the interpretation of microbial community data.     

Reconstruction of ribosomal RNA genes from metagenomic data

Direct sequencing of environmental DNA (metagenomics) has a great potential for describing the 16S rRNA gene diversity of microbial communities. However current approaches using this 16S rRNA gene information to describe community diversity suffer from low taxonomic resolution or chimera problems. Here we describe a new strategy that involves stringent assembly and data filtering to reconstruct full-length 16S rRNA genes from metagenomicpyrosequencing data. Simulations showed that reconstructed 16S rRNA genes provided a true picture of the community diversity, had minimal rates of chimera formation and gave taxonomic resolution down to genus level. The strategy was furthermore compared to PCR-based methods to determine the microbial diversity in two marine sponges. This showed that about 30% of the abundant phylotypes reconstructed from metagenomic data failed to be amplified by PCR. Our approach is readily applicable to existing metagenomic datasets and is expected to lead to the discovery of new microbial phylotypes.     

Confident phylogenetic identification of uncultured prokaryotes through long read amplicon sequencing of the 16S-ITS-23S rRNA operon

Amplicon sequencing of the 16S rRNA gene is the predominant method to quantify microbial compositions and to discover novel lineages. However, traditional short amplicons often do not contain enough information to confidently resolve their phylogeny. Here we present a cost-effective protocol that amplifies a large part of the rRNA operon and sequences the amplicons with PacBio technology. We tested our method on a mock community and developed a read-curation pipeline that reduces the overall read error rate to 0.18%. Applying our method on four environmental samples, we captured near full-length rRNA operon amplicons from a large diversity of prokaryotes. The method operated at moderately high-throughput (22286–37,850 raw ccs reads) and generated a large amount of putative novel archaeal 23S rRNA gene sequences compared to the archaeal SILVA database. These long amplicons allowed for higher resolution during taxonomic classification by means of long (∼1000 bp) 16S rRNA gene fragments and for substantially more confident phylogenies by means of combined near full-length 16S and 23S rRNA gene sequences, compared to shorter traditional amplicons (250 bp of the 16S rRNA gene). We recommend our method to those who wish to cost-effectively and confidently estimate the phylogenetic diversity of prokaryotes in environmental samples at high throughput.     

Accurate taxonomy assignments from 16S rRNA sequences produced by highly parallel pyrosequencers

The recent introduction of massively parallel pyrosequencers allows rapid, inexpensive analysis of microbial community composition using 16S ribosomal RNA (rRNA) sequences. However, a major challenge is to design a workflow so that taxonomic information can be accurately and rapidly assigned to each read, so that the composition of each community can be linked back to likely ecological roles played by members of each species, genus, family or phylum. Here, we use three large 16S rRNA datasets to test whether taxonomic information based on the full-length sequences can be recaptured by short reads that simulate the pyrosequencer outputs. We find that different taxonomic assignment methods vary radically in their ability to recapture the taxonomic information in full-length 16S rRNA sequences: most methods are sensitive to the region of the 16S rRNA gene that is targeted for sequencing, but many combinations of methods and rRNA regions produce consistent and accurate results. To process large datasets of partial 16S rRNA sequences obtained from surveys of various microbial communities, including those from human body habitats, we recommend the use of Greengenes or RDP classifier with fragments of at least 250 bases, starting from one of the primers R357, R534, R798, F343 or F517.     

变性梯度凝胶电泳(DGGE)在微生物生态学中的应用

由于从环境样品中分离和培养细菌的困难,分子生物学方法已发展用来描述和鉴定微生物群落。近年来基于DNA方法的群落分析得到了迅速的发展,如PCR扩增技术,克隆文库法,荧光原位杂交法,限制性酶切片段长度多态性法,变性和温度梯度凝胶电泳法。DGGE已广泛用于分析自然环境中细菌、蓝细菌,古菌、微微型真核生物、真核生物和病毒群落的生物多样性。这一技术能够提供群落中优势种类信息和同时分析多个样品。具有可重复和容易操作等特点,适合于调查种群的时空变化,并且可通过对切下的带进行序列分析或与特异性探针杂交分析鉴定群落成员。DGGE分析微生物群落的一般步骤如下：一是核酸的提取,二是16S rRNA,18S rRNA或功能基因如可容性甲烷加单氧酶羟化酶基因(mmoX)和氨加单氧酶a一亚单位基因(amoA)片段的扩增,三是通过DGGE分析PCR产物。DGGE使用具有化学变性剂梯度的聚丙烯酰胺凝胶,该凝胶能够有区别的解链PCR扩增产物。由PCR产生的不同的DNA片段长度相同但核苷酸序列不同。因此不同的双链DNA片段由于沿着化学梯度的不同解链行为将在凝胶的不同位置上停止迁移。DNA解链行为的不同导致一个凝胶带图案,该图案是微生物群落中主要种类的一个轮廓。DGGE使用所有生物中保守的基因片段如细菌中的16S rRNA基因片段和真菌中的18S rRNA基因片段。然而同其他分子生物学方法一样,DGGE也有缺陷,其中之一是只能分离较小的片段,使用于系统发育分析比较和探针设计的序列信息量受到了限制。在某些情况下,由于所用基因的多拷贝导致一个种类多于一条带,因此不易鉴定群落结构到种的水平。此外,该技术具有内在的如单一细菌种类16S rDNA拷贝之间的异质性问题,可导致自然群落中微生物数量的过多估计。DGGE是分析微生物群落的一种有力的工具。不过为了减少DGGE和其它技术的缺陷,建议研究者结合DGGE和其它分子及微生物学方法以便更详细的观察微生物的群落结构和功能。     

Benchmarking of 16S rRNA gene databases using known strain sequences

16S rRNA gene analysis is the most convenient and robust method for microbiome studies. Inaccurate taxonomic assignment of bacterial strains could have deleterious effects as all downstream analyses rely heavily on the accurate assessment of microbial taxonomy. The use of mock communities to check the reliability of the results has been suggested. However, often the mock communities used in most of the studies represent only a small fraction of taxa and are used mostly as validation of sequencing run to estimate sequencing artifacts. Moreover, a large number of databases and tools available for classification and taxonomic assignment of the 16S rRNA gene make it challenging to select the best-suited method for a particular dataset. In the present study, we used authentic and validly published 16S rRNA gene type strain sequences (full length, V3-V4 region) and analyzed them using a widely used QIIME pipeline along with different parameters of OTU clustering and QIIME compatible databases. Data Analysis Measures (DAM) revealed a high discrepancy in ratifying the taxonomy at different taxonomic hierarchies. Beta diversity analysis showed clear segregation of different DAMs. Limited differences were observed in reference data set analysis using partial (V3-V4) and full-length 16S rRNA gene sequences, which signify the reliability of partial 16S rRNA gene sequences in microbiome studies. Our analysis also highlights common discrepancies observed at various taxonomic levels using various methods and databases.     

Development of a Dual-Index Sequencing Strategy and Curation Pipeline for Analyzing Amplicon Sequence Data on the MiSeq Illumina Sequencing Platform

Rapid advances in sequencing technology have changed the experimental landscape of microbial ecology. In the last 10 years, the field has moved from sequencing hundreds of 16S rRNA gene fragments per study using clone libraries to the sequencing of millions of fragments per study using next-generation sequencing technologies from 454 and Illumina. As these technologies advance, it is critical to assess the strengths, weaknesses, and overall suitability of these platforms for the interrogation of microbial communities. Here, we present an improved method for sequencing variable regions within the 16S rRNA gene using Illumina''s MiSeq platform, which is currently capable of producing paired 250-nucleotide reads. We evaluated three overlapping regions of the 16S rRNA gene that vary in length (i.e., V34, V4, and V45) by resequencing a mock community and natural samples from human feces, mouse feces, and soil. By titrating the concentration of 16S rRNA gene amplicons applied to the flow cell and using a quality score-based approach to correct discrepancies between reads used to construct contigs, we were able to reduce error rates by as much as two orders of magnitude. Finally, we reprocessed samples from a previous study to demonstrate that large numbers of samples could be multiplexed and sequenced in parallel with shotgun metagenomes. These analyses demonstrate that our approach can provide data that are at least as good as that generated by the 454 platform while providing considerably higher sequencing coverage for a fraction of the cost.     

Analysis,Optimization and Verification of Illumina-Generated 16S rRNA Gene Amplicon Surveys

The exploration of microbial communities by sequencing 16S rRNA genes has expanded with low-cost, high-throughput sequencing instruments. Illumina-based 16S rRNA gene sequencing has recently gained popularity over 454 pyrosequencing due to its lower costs, higher accuracy and greater throughput. Although recent reports suggest that Illumina and 454 pyrosequencing provide similar beta diversity measures, it remains to be demonstrated that pre-existing 454 pyrosequencing workflows can transfer directly from 454 to Illumina MiSeq sequencing by simply changing the sequencing adapters of the primers. In this study, we modified 454 pyrosequencing primers targeting the V4-V5 hyper-variable regions of the 16S rRNA gene to be compatible with Illumina sequencers. Microbial communities from cows, humans, leeches, mice, sewage, and termites and a mock community were analyzed by 454 and MiSeq sequencing of the V4-V5 region and MiSeq sequencing of the V4 region. Our analysis revealed that reference-based OTU clustering alone introduced biases compared to de novo clustering, preventing certain taxa from being observed in some samples. Based on this we devised and recommend an analysis pipeline that includes read merging, contaminant filtering, and reference-based clustering followed by de novo OTU clustering, which produces diversity measures consistent with de novo OTU clustering analysis. Low levels of dataset contamination with Illumina sequencing were discovered that could affect analyses that require highly sensitive approaches. While moving to Illumina-based sequencing platforms promises to provide deeper insights into the breadth and function of microbial diversity, our results show that care must be taken to ensure that sequencing and processing artifacts do not obscure true microbial diversity.     

Statistical methods for characterizing diversity of microbial communities by analysis of terminal restriction fragment length polymorphisms of 16S rRNA genes

The analysis of terminal restriction fragment length polymorphisms (T-RFLP) of 16S rRNA genes has proven to be a facile means to compare microbial communities and presumptively identify abundant members. The method provides data that can be used to compare different communities based on similarity or distance measures. Once communities have been clustered into groups, clone libraries can be prepared from sample(s) that are representative of each group in order to determine the phylogeny of the numerically abundant populations in a community. In this paper methods are introduced for the statistical analysis of T-RFLP data that include objective methods for (i) determining a baseline so that 'true' peaks in electropherograms can be identified; (ii) a means to compare electropherograms and bin fragments of similar size; (iii) clustering algorithms that can be used to identify communities that are similar to one another; and (iv) a means to select samples that are representative of a cluster that can be used to construct 16S rRNA gene clone libraries. The methods for data analysis were tested using simulated data with assumptions and parameters that corresponded to actual data. The simulation results demonstrated the usefulness of these methods in their ability to recover the true microbial community structure generated under the assumptions made. Software for implementing these methods is available at http://www.ibest.uidaho.edu/tools/trflp_stats/index.php.     

16S rRNA基因在微生物生态学中的应用

16S rRNA(Small subunit ribosomal RNA)基因是对原核微生物进行系统进化分类研究时最常用的分子标志物(Biomarker),广泛应用于微生物生态学研究中。近些年来随着高通量测序技术及数据分析方法等的不断进步,大量基于16S rRNA基因的研究使得微生物生态学得到了快速发展,然而使用16S rRNA基因作为分子标志物时也存在诸多问题,比如水平基因转移、多拷贝的异质性、基因扩增效率的差异、数据分析方法的选择等,这些问题影响了微生物群落组成和多样性分析时的准确性。对当前使用16S rRNA基因分析微生物群落组成和多样性的进展情况做一总结,重点讨论当前存在的主要问题以及各种分析方法的发展,尤其是与高通量测序技术有关的实验和数据处理问题。     

Genetic diversity of bacterial strains isolated from soils, contaminated with polycyclic aromatic hydrocarbons, by 16S rRNA gene sequencing and amplified fragment length polymorphism fingerprinting

In order to study microbial diversity in a polycyclic aromatic hydrocarbon-impacted soil, 14 bacterial strains were analyzed by 16S rRNA gene sequencing and amplified fragment length polymorphism (AFLP) analysis. Bacterial strains isolated from two different hydrocarbon-polluted sites were identified to the species level by 16S rRNA full-gene sequencing using MicroSeq 16S rRNA gene sequencing. Their genome was subsequently analyzed by high-resolution genotyping with AFLP analysis, in order to monitor species variability and to differentiate closely related strains. Cluster analysis based on AFLP fingerprinting showed intra-specific polymorphism, even among strains with 100% 16S rRNA gene sequence identity. The results show that AFLP is a powerful, highly reproducible and discriminatory tool for revealing genetic relationships in bacterial populations. The ability to differentiate and track related closely microbes is fundamental for studying structure and dynamics of microbial communities in contaminated ecosystems.     

DNA聚合酶对PacBio SMRT测序结果影响的评价

目的 评估不同DNA聚合酶是否会对以16S rRNA全长为测序靶点的肠道微生物多样性研究结果产生影响。方法 用美国太平洋公司的三代测序仪（PacBio single molecule real-time sequencing technology）对3份分别采用KAPA HiFiTM HotStart DNA聚合酶和PCRBIO HotStart DNA聚合酶扩增的军犬粪便样品进行精确至“种”水平的测序分析。结果 经配对Mann-Whitney U检验显示,不同DNA聚合酶扩增的同一样品在门、属和种水平上差异无统计学意义（P>0.05）,然而在某些相对含量较少的操作分类单元（OTU）上,其扩增效率存在差异。经基于非加权UniFrac距离的非加权组平均法聚类分析和基于加权UniFrac距离的非参数多元方差分析发现不同DNA聚合酶扩增的同一样品其多样性差异无统计学意义（P>0.05）。结论 KAPA HiFiTM HotStart DNA聚合酶和PCRBIO HotStart DNA聚合酶虽对模板DNA扩增存在一定的偏好性,但该偏好性不影响PacBio SMRT测序结果。     

PCR biases distort bacterial and archaeal community structure in pyrosequencing datasets

As 16S rRNA gene targeted massively parallel sequencing has become a common tool for microbial diversity investigations, numerous advances have been made to minimize the influence of sequencing and chimeric PCR artifacts through rigorous quality control measures. However, there has been little effort towards understanding the effect of multi-template PCR biases on microbial community structure. In this study, we used three bacterial and three archaeal mock communities consisting of, respectively, 33 bacterial and 24 archaeal 16S rRNA gene sequences combined in different proportions to compare the influences of (1) sequencing depth, (2) sequencing artifacts (sequencing errors and chimeric PCR artifacts), and (3) biases in multi-template PCR, towards the interpretation of community structure in pyrosequencing datasets. We also assessed the influence of each of these three variables on α- and β-diversity metrics that rely on the number of OTUs alone (richness) and those that include both membership and the relative abundance of detected OTUs (diversity). As part of this study, we redesigned bacterial and archaeal primer sets that target the V3-V5 region of the 16S rRNA gene, along with multiplexing barcodes, to permit simultaneous sequencing of PCR products from the two domains. We conclude that the benefits of deeper sequencing efforts extend beyond greater OTU detection and result in higher precision in β-diversity analyses by reducing the variability between replicate libraries, despite the presence of more sequencing artifacts. Additionally, spurious OTUs resulting from sequencing errors have a significant impact on richness or shared-richness based α- and β-diversity metrics, whereas metrics that utilize community structure (including both richness and relative abundance of OTUs) are minimally affected by spurious OTUs. However, the greatest obstacle towards accurately evaluating community structure are the errors in estimated mean relative abundance of each detected OTU due to biases associated with multi-template PCR reactions.     

Performance Comparison of Illumina and Ion Torrent Next-Generation Sequencing Platforms for 16S rRNA-Based Bacterial Community Profiling

High-throughput sequencing of the taxonomically informative 16S rRNA gene provides a powerful approach for exploring microbial diversity. Here we compare the performances of two common “benchtop” sequencing platforms, Illumina MiSeq and Ion Torrent Personal Genome Machine (PGM), for bacterial community profiling by 16S rRNA (V1-V2) amplicon sequencing. We benchmarked performance by using a 20-organism mock bacterial community and a collection of primary human specimens. We observed comparatively higher error rates with the Ion Torrent platform and report a pattern of premature sequence truncation specific to semiconductor sequencing. Read truncation was dependent on both the directionality of sequencing and the target species, resulting in organism-specific biases in community profiles. We found that these sequencing artifacts could be minimized by using bidirectional amplicon sequencing and an optimized flow order on the Ion Torrent platform. Results of bacterial community profiling performed on the mock community and a collection of 18 human-derived microbiological specimens were generally in good agreement for both platforms; however, in some cases, results differed significantly. Disparities could be attributed to the failure to generate full-length reads for particular organisms on the Ion Torrent platform, organism-dependent differences in sequence error rates affecting classification of certain species, or some combination of these factors. This study demonstrates the potential for differential bias in bacterial community profiles resulting from the choice of sequencing platform alone.     

基于16S rRNA基因测序分析微生物群落多样性

微生物群落多样性的研究对于挖掘微生物资源,探索微生物群落功能,阐明微生物群落与生境间的关系具有重要意义。随着宏基因组概念的提出以及测序技术的快速发展,16S rRNA基因测序在微生物群落多样性的研究中已被广泛应用。文中系统地介绍了16S rRNA基因测序分析流程中的四个重要环节,包括测序平台与扩增区的选择、测序数据预处理以及多样性分析方法,就其面临的问题与挑战进行了探讨并对未来的研究方向进行了展望,以期为微生物群落多样性相关研究提供参考。     

Microbial Communities Can Be Described by Metabolic Structure: A General Framework and Application to a Seasonally Variable,Depth-Stratified Microbial Community from the Coastal West Antarctic Peninsula

Taxonomic marker gene studies, such as the 16S rRNA gene, have been used to successfully explore microbial diversity in a variety of marine, terrestrial, and host environments. For some of these environments long term sampling programs are beginning to build a historical record of microbial community structure. Although these 16S rRNA gene datasets do not intrinsically provide information on microbial metabolism or ecosystem function, this information can be developed by identifying metabolisms associated with related, phenotyped strains. Here we introduce the concept of metabolic inference; the systematic prediction of metabolism from phylogeny, and describe a complete pipeline for predicting the metabolic pathways likely to be found in a collection of 16S rRNA gene phylotypes. This framework includes a mechanism for assigning confidence to each metabolic inference that is based on a novel method for evaluating genomic plasticity. We applied this framework to 16S rRNA gene libraries from the West Antarctic Peninsula marine environment, including surface and deep summer samples and surface winter samples. Using statistical methods commonly applied to community ecology data we found that metabolic structure differed between summer surface and winter and deep samples, comparable to an analysis of community structure by 16S rRNA gene phylotypes. While taxonomic variance between samples was primarily driven by low abundance taxa, metabolic variance was attributable to both high and low abundance pathways. This suggests that clades with a high degree of functional redundancy can occupy distinct adjacent niches. Overall our findings demonstrate that inferred metabolism can be used in place of taxonomy to describe the structure of microbial communities. Coupling metabolic inference with targeted metagenomics and an improved collection of completed genomes could be a powerful way to analyze microbial communities in a high-throughput manner that provides direct access to metabolic and ecosystem function.     

Complementary retrieval of 16S rRNA gene sequences using broad-range primers with inosine at the 3'-terminus: implications for the study of microbial diversity

We evaluated the impact of the base analogue inosine substituted at the 3'-terminus of broad-range 16S rRNA gene primers on the recovery of microbial diversity using terminal restriction fragment length polymorphism and clonal analysis. Oral plaque biofilms from 10 individuals were tested with modified and unmodified primer pairs. Besides a core overlap of shared terminal restriction fragments (T-RFs), each primer system provided unique information on the occurrence of T-RFs, with a higher number generally displayed with inosine primers. All clones sequenced were at least 99% identical to publicly available full-length sequences. Analysis of the corresponding primer-binding sites showed that most sequence types were 100% complementary to the unmodified primers so that the characteristic of inosine to bind with all four nucleotides was not crucial for the observed increase in microbial richness. Instead, differences in community compositions were correlated with the identity of the nearest-neighbor 3' of the primer-targeting region. By influencing the thermal stability of primer hybridization, this position may play a previously unrecognized role in biased amplification of 16S rRNA gene sequences. In conclusion, the combined use of inosine and unmodified primers enables the complementary retrieval of 16S rRNA gene types, thereby expanding the observed diversity of complex microbial communities.     

Use of Subtractive Hybridization To Design Habitat-Based Oligonucleotide Probes for Investigation of Natural Bacterial Communities

We describe a rapid oligonucleotide probe design strategy based on subtractive hybridization which yields probes for 16S rRNA or rRNA genes of individual members of microbial communities that are specific within the context of those communities. This strategy circumvents the need to sequence many similar or identical clones of dominant members of a community. Radioactively labeled subfragments of a cloned 16S rRNA gene sequence for which a probe is required (target) were hybridized with biotinylated total 16S ribosomal DNA (rDNA) amplified from the microbial community, and the hybrids formed were subsequently discarded. The remaining enriched fragments were used to screen a library consisting of cloned subfragments of the target sequence by colony hybridization in order to identify the variable regions of the 16S rRNA gene with the required specificity. The sequencing of random clones in one 16S rDNA library demonstrated that only those clones with 100% sequence identity with the probe fragment were detected by it. Moreover, sequencing of other, randomly selected, probe-positive clones revealed 100% sequence identity with the probe. Probes developed in this way tended to correspond to more variable regions of the 16S rRNA if the target sequences were similar to the sequences of other clones in the library and to less variable regions if the target sequences were phylogenetically isolated within the clone library. Although the absolute specificity of the latter probes, as assessed by comparison with available database sequences, was lower than the absolute specificity of the probes from the more variable regions, they were specific within the context of the environmental samples from which they were derived.     

Detection and identification of gastrointestinal Lactobacillus species by using denaturing gradient gel electrophoresis and species-specific PCR primers

Denaturing gradient gel electrophoresis (DGGE) of DNA fragments obtained by PCR amplification of the V2-V3 region of the 16S rRNA gene was used to detect the presence of Lactobacillus species in the stomach contents of mice. Lactobacillus isolates cultured from human and porcine gastrointestinal samples were identified to the species level by using a combination of DGGE and species-specific PCR primers that targeted 16S-23S rRNA intergenic spacer region or 16S rRNA gene sequences. The identifications obtained by this approach were confirmed by sequencing the V2-V3 region of the 16S rRNA gene and by a BLAST search of the GenBank database.     

A novel method for determining microflora composition using dynamic phylogenetic analysis of 16S ribosomal RNA deep sequencing data

Deep sequencing of the 16S rRNA gene provides a comprehensive view of bacterial communities in a particular environment and has expanded our ability to study the impact of the microflora on human health and disease. Current analysis methods rely on comparisons of the sequences generated with an expanding but limited set of annotated 16S rRNA sequences or phylogenic clustering of sequences based on arbitrary similarity cutoffs. We describe a novel approach to characterize bacterial composition using deep sequencing of 16S rRNA gene. Our method defines operational taxonomic units based on phylogenetic tree reconstruction and dynamic clustering of sequences using solely sequencing data. These OTUs can be used to identify differences in bacteria abundance between environments. This approach can perform better than previous phylogenetic methods and will significantly improve our understanding of the microfloral role on human diseases by providing a comprehensive analysis of the microbial composition from various bacterial communities.