Simultaneous analysis of seven 16S rRNA hypervariable gene regions increases efficiency in marine bacterial diversity detection

Environmental DNA sequencing is the gold standard to reveal microbial community structures. In most applications, a one-fragment PCR approach is applied to amplify a taxonomic marker gene, usually a hypervariable region of the 16S rRNA gene. We used a new reverse complement (RC)-PCR-based assay that amplifies seven out of the nine hypervariable regions of the 16S rRNA gene, to interrogate bacterial communities in sediment samples collected from different coastal marine sites with an impact gradient. In parallel, we employed a traditional one-fragment analysis of the hypervariable V3–V4 region to investigate whether the RC-PCR reveals more of the ‘unseen’ diversity obtained by the one-fragment approach. As a benchmark for the full deck of diversity, we subjected the samples to PCR-free metagenomic sequencing. None of the two PCR-based approaches recorded the full taxonomic repertoire obtained from the metagenomics datasets. However, the RC-PCR approach detected 2.8 times more bacterial genera compared to the near-saturation sequenced V3–V4 samples. RC-PCR is an ideal compromise between the standard one-fragment approach and metagenomics sequencing and may guide future environmental sequencing studies, in which bacterial diversity is a central subject.     

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.     

Analysis of the microbial community structure in a membrane bioreactor during initial stages of filtration

Membrane biofouling was investigated during the early stages of filtration in a laboratory-scale membrane bioreactor operated on molasses wastewater. The bacterial diversity and composition of the membrane biofilm and activated sludge were analyzed using terminal restriction fragment length polymorphism coupled with 16S rRNA clone library construction and sequencing. The amount of extracellular polymeric substances produced by bacteria was investigated using spectroscopic methods. The results reveal that the bacterial community of activated sludge differs significantly from that of the membrane biofilm, especially at the initial phase. Phylogenetic analysis based on 16S rRNA gene sequences identified 25 pioneer OTUs responsible for membrane surface colonization. Also, the relationship between the identified bacterial strains and the system specifications was explored.     

Hypervariable regions (V1–V9) of the dinoflagellate 18S rRNA using a large dataset for marker considerations

DNA sequencing methods have been used for the molecular taxonomic discrimination of dinoflagellate protists, particularly using partial 18S rRNA sequences. This study evaluated the taxonomic discrimination power of rRNA gene hypervariable regions (V1 to V9) in dinoflagellates from a large dataset. These included 77 dinoflagellate species (9 orders, 17 families, 40 genera). The complete 18S rRNA sequences of the dinoflagellates ranged from 1,787 to 1,813?bp in length, and consisted of eight V regions with a total combined length of 678 to 699?bp. Regions longer than 100?bp were recoded for V2, V4, and V8 regions; high nucleotide divergences were detected in V1, V2, and V4 regions. Statistic tests showed that the divergences of individual V regions were significantly different (t-test, P?<?0.05) compared with the complete 18S rRNA. The V2 region showed the highest score (83.5%) for PI sites. Moreover, intra-genus DNA similarities of the V2 were considerably low (<93%). Neighbor-joining analyses showed that phylogenetic resolution in the V2–V4 region was 1.32-fold higher than that of the complete 18S rRNA. These results demonstrate that V2 has the highest taxonomic resolving power within the 18S rRNA gene of dinoflagellates, suggesting the V2 and adjacent regions (e.g., V1 to V4) may be the best for marker considerations.     

Analysis of the Cystic Fibrosis Lung Microbiota via Serial Illumina Sequencing of Bacterial 16S rRNA Hypervariable Regions

The characterization of bacterial communities using DNA sequencing has revolutionized our ability to study microbes in nature and discover the ways in which microbial communities affect ecosystem functioning and human health. Here we describe Serial Illumina Sequencing (SI-Seq): a method for deep sequencing of the bacterial 16S rRNA gene using next-generation sequencing technology. SI-Seq serially sequences portions of the V5, V6 and V7 hypervariable regions from barcoded 16S rRNA amplicons using an Illumina short-read genome analyzer. SI-Seq obtains taxonomic resolution similar to 454 pyrosequencing for a fraction of the cost, and can produce hundreds of thousands of reads per sample even with very high multiplexing. We validated SI-Seq using single species and mock community controls, and via a comparison to cystic fibrosis lung microbiota sequenced using 454 FLX Titanium. Our control runs show that SI-Seq has a dynamic range of at least five orders of magnitude, can classify >96% of sequences to the genus level, and performs just as well as 454 and paired-end Illumina methods in estimation of standard microbial ecology diversity measurements. We illustrate the utility of SI-Seq in a pilot sample of central airway secretion samples from cystic fibrosis patients.     

基于分子标记的宏基因组16S rRNA基因高变区选择策略

随着新一代DNA测序技术出现,人们能够同时对多个DNA样本的宏基因组进行并行分析,尤其是以16S rRNA基因高变区为分子标记的测序已经成为微生物多样性研究最为简洁有效的方法. 目前二代高通量测序的读长不能覆盖16S rRNA基因的全长,需要选择一个有效的高变区进行测序.十多年来,对于16S rRNA基因高变区的选择策略没有统一的标准.本文分析了常用的高变区选择策略,指出不同环境条件是影响高变区选择的重要因素之一.在此基础上,提出了高变区选择的参考准则,同时建议应对选择的高变区进行有效评估.     

Variable copy number, intra-genomic heterogeneities and lateral transfers of the 16S rRNA gene in Pseudomonas

Even though the 16S rRNA gene is the most commonly used taxonomic marker in microbial ecology, its poor resolution is still not fully understood at the intra-genus level. In this work, the number of rRNA gene operons, intra-genomic heterogeneities and lateral transfers were investigated at a fine-scale resolution, throughout the Pseudomonas genus. In addition to nineteen sequenced Pseudomonas strains, we determined the 16S rRNA copy number in four other Pseudomonas strains by Southern hybridization and Pulsed-Field Gel Electrophoresis, and studied the intra-genomic heterogeneities by Denaturing Gradient Gel Electrophoresis and sequencing. Although the variable copy number (from four to seven) seems to be correlated with the evolutionary distance, some close strains in the P. fluorescens lineage showed a different number of 16S rRNA genes, whereas all the strains in the P. aeruginosa lineage displayed the same number of genes (four copies). Further study of the intra-genomic heterogeneities revealed that most of the Pseudomonas strains (15 out of 19 strains) had at least two different 16S rRNA alleles. A great difference (5 or 19 nucleotides, essentially grouped near the V1 hypervariable region) was observed only in two sequenced strains. In one of our strains studied (MFY30 strain), we found a difference of 12 nucleotides (grouped in the V3 hypervariable region) between copies of the 16S rRNA gene. Finally, occurrence of partial lateral transfers of the 16S rRNA gene was further investigated in 1803 full-length sequences of Pseudomonas available in the databases. Remarkably, we found that the two most variable regions (the V1 and V3 hypervariable regions) had probably been laterally transferred from another evolutionary distant Pseudomonas strain for at least 48.3 and 41.6% of the 16S rRNA sequences, respectively. In conclusion, we strongly recommend removing these regions of the 16S rRNA gene during the intra-genus diversity studies.     

Soil Bacterial Diversity Screening Using Single 16S rRNA Gene V Regions Coupled with Multi-Million Read Generating Sequencing Technologies

The novel multi-million read generating sequencing technologies are very promising for resolving the immense soil 16S rRNA gene bacterial diversity. Yet they have a limited maximum sequence length screening ability, restricting studies in screening DNA stretches of single 16S rRNA gene hypervariable (V) regions. The aim of the present study was to assess the effects of properties of four consecutive V regions (V3-6) on commonly applied analytical methodologies in bacterial ecology studies. Using an in silico approach, the performance of each V region was compared with the complete 16S rRNA gene stretch. We assessed related properties of the soil derived bacterial sequence collection of the Ribosomal Database Project (RDP) database and concomitantly performed simulations based on published datasets. Results indicate that overall the most prominent V region for soil bacterial diversity studies was V3, even though it was outperformed in some of the tests. Despite its high performance during most tests, V4 was less conserved along flanking sites, thus reducing its ability for bacterial diversity coverage. V5 performed well in the non-redundant RDP database based analysis. However V5 did not resemble the full-length 16S rRNA gene sequence results as well as V3 and V4 did when the natural sequence frequency and occurrence approximation was considered in the virtual experiment. Although, the highly conserved flanking sequence regions of V6 provide the ability to amplify partial 16S rRNA gene sequences from very diverse owners, it was demonstrated that V6 was the least informative compared to the rest examined V regions. Our results indicate that environment specific database exploration and theoretical assessment of the experimental approach are strongly suggested in 16S rRNA gene based bacterial diversity studies.     

Taxonomic Classification of Bacterial 16S rRNA Genes Using Short Sequencing Reads: Evaluation of Effective Study Designs

Massively parallel high throughput sequencing technologies allow us to interrogate the microbial composition of biological samples at unprecedented resolution. The typical approach is to perform high-throughout sequencing of 16S rRNA genes, which are then taxonomically classified based on similarity to known sequences in existing databases. Current technologies cause a predicament though, because although they enable deep coverage of samples, they are limited in the length of sequence they can produce. As a result, high-throughout studies of microbial communities often do not sequence the entire 16S rRNA gene. The challenge is to obtain reliable representation of bacterial communities through taxonomic classification of short 16S rRNA gene sequences. In this study we explored properties of different study designs and developed specific recommendations for effective use of short-read sequencing technologies for the purpose of interrogating bacterial communities, with a focus on classification using naïve Bayesian classifiers. To assess precision and coverage of each design, we used a collection of ∼8,500 manually curated 16S rRNA gene sequences from cultured bacteria and a set of over one million bacterial 16S rRNA gene sequences retrieved from environmental samples, respectively. We also tested different configurations of taxonomic classification approaches using short read sequencing data, and provide recommendations for optimal choice of the relevant parameters. We conclude that with a judicious selection of the sequenced region and the corresponding choice of a suitable training set for taxonomic classification, it is possible to explore bacterial communities at great depth using current technologies, with only a minimal loss of taxonomic resolution.     

The Effect of Primer Choice and Short Read Sequences on the Outcome of 16S rRNA Gene Based Diversity Studies

Different regions of the bacterial 16S rRNA gene evolve at different evolutionary rates. The scientific outcome of short read sequencing studies therefore alters with the gene region sequenced. We wanted to gain insight in the impact of primer choice on the outcome of short read sequencing efforts. All the unknowns associated with sequencing data, i.e. primer coverage rate, phylogeny, OTU-richness and taxonomic assignment, were therefore implemented in one study for ten well established universal primers (338f/r, 518f/r, 799f/r, 926f/r and 1062f/r) targeting dispersed regions of the bacterial 16S rRNA gene. All analyses were performed on nearly full length and in silico generated short read sequence libraries containing 1175 sequences that were carefully chosen as to present a representative substitute of the SILVA SSU database. The 518f and 799r primers, targeting the V4 region of the 16S rRNA gene, were found to be particularly suited for short read sequencing studies, while the primer 1062r, targeting V6, seemed to be least reliable. Our results will assist scientists in considering whether the best option for their study is to select the most informative primer, or the primer that excludes interferences by host-organelle DNA. The methodology followed can be extrapolated to other primers, allowing their evaluation prior to the experiment.     

Development of an Analysis Pipeline Characterizing Multiple Hypervariable Regions of 16S rRNA Using Mock Samples

Objectives

There is much speculation on which hypervariable region provides the highest bacterial specificity in 16S rRNA sequencing. The optimum solution to prevent bias and to obtain a comprehensive view of complex bacterial communities would be to sequence the entire 16S rRNA gene; however, this is not possible with second generation standard library design and short-read next-generation sequencing technology.

Methods

This paper examines a new process using seven hypervariable or V regions of the 16S rRNA (six amplicons: V2, V3, V4, V6-7, V8, and V9) processed simultaneously on the Ion Torrent Personal Genome Machine (Life Technologies, Grand Island, NY). Four mock samples were amplified using the 16S Ion Metagenomics Kit^™ (Life Technologies) and their sequencing data is subjected to a novel analytical pipeline.

Results

Results are presented at family and genus level. The Kullback-Leibler divergence (D_KL), a measure of the departure of the computed from the nominal bacterial distribution in the mock samples, was used to infer which region performed best at the family and genus levels. Three different hypervariable regions, V2, V4, and V6-7, produced the lowest divergence compared to the known mock sample. The V9 region gave the highest (worst) average D_KL while the V4 gave the lowest (best) average D_KL. In addition to having a high D_KL, the V9 region in both the forward and reverse directions performed the worst finding only 17% and 53% of the known family level and 12% and 47% of the genus level bacteria, while results from the forward and reverse V4 region identified all 17 family level bacteria.

Conclusions

The results of our analysis have shown that our sequencing methods using 6 hypervariable regions of the 16S rRNA and subsequent analysis is valid. This method also allowed for the assessment of how well each of the variable regions might perform simultaneously. Our findings will provide the basis for future work intended to assess microbial abundance at different time points throughout a clinical protocol.     

Discordant phylogenies within the rrn loci of Rhizobia

It is evident from complete genome sequencing results that lateral gene transfer and recombination are essential components in the evolutionary process of bacterial genomes. Since this has important implications for bacterial systematics, the primary objective of this study was to compare estimated evolutionary relationships among a representative set of alpha-Proteobacteria by sequencing analysis of three loci within their rrn operons. Tree topologies generated with 16S rRNA gene sequences were significantly different from corresponding trees assembled with 23S rRNA gene and internally transcribed space region sequences. Besides the incongruence in tree topologies, evidence that distinct segments along the 16S rRNA gene sequences of bacteria currently classified within the genera Bradyrhizobium, Mesorhizobium and Sinorhizobium have a reticulate evolutionary history was also obtained. Our data have important implications for bacterial taxonomy, because currently most taxonomic decisions are based on comparative 16S rRNA gene sequence analysis. Since phylogenetic placement based on 16S rRNA gene sequence divergence perhaps is questionable, we suggest that the proposals of bacterial nomenclature or changes in their taxonomy that have been made may not necessarily be warranted. Accordingly, a more conservative approach should be taken in the future, in which taxonomic decisions are based on the analysis of a wider variety of loci and comparative analytical methods are used to estimate phylogenetic relationships among the genomes under consideration.     

Whole genome-based assessment of the taxonomic position of the arthropod pathogenic bacterium Rickettsiella grylli

Rickettsiella grylli is an intracellular bacterial pathogen of aquatic and terrestrial arthropods. Previous determination of its 16S rRNA-encoding sequence has led to the taxonomic classification of the genus Rickettsiella in the class Gammaproteobacteria, order Legionellales, family Coxiellaceae, i.e. in close vicinity to vertebrate pathogenic bacteria of the genera Coxiella and Legionella. Here we use the additional information available from the recently published first whole genome sequence from this genus to evaluate critically the taxonomic classification of R. grylli beyond the 16S rRNA gene level. Using phylogenetic reconstruction, together with significance testing on a data basis defined by a core set of 211 previously identified families of protein-encoding genes, together with a reanalysis of 16S rRNA gene data, the present study firmly corroborates the assignment of this species to both the class Gammaproteobacteria and the order Legionellales. However, the results obtained from concatenated and single protein, single protein-encoding gene, and 16S rRNA gene data demonstrate a similar phylogenetic distance of R. grylli to both the Coxiellaceae and the Legionellaceae and are, therefore, inconsistent with its current family-level classification. Consequently, a respective reorganization of the order Legionellales is proposed.     

Quantification of Microthrix parvicella in activated sludge bacterial communities by real-time PCR

AIMS: This study was to develop a simple and reliable method for quantifying Microthrix parvicella 16S rRNA gene copies and its application to activated sludge samples collected from wastewater treatment plants (WWTP) with and without foaming problems. METHODS AND RESULTS: The relative frequency of M. parvicella was determined by combining real-time PCR assays for quantification of total bacterial 16S rRNA gene copies and M. parvicella 16S rRNA gene copies. The developed method was applied to analyse 32 activated sludge samples obtained from German WWTP. The level of M. parvicella 16S rRNA gene copies in the 18 nonfoaming samples was below 3% of the total number of 16S rRNA gene copies and in the range of 0-18% for the 14 foaming samples. CONCLUSIONS: The described method allows reliable monitoring of the amount of M. parvicella in activated sludge samples. SIGNIFICANCE AND IMPACT OF THE STUDY: The described method may become an important component of a warning system for forthcoming bulking and foaming episodes.     

A diverse bacterial community in an anoxic quinoline-degrading bioreactor determined by using pyrosequencing and clone library analysis

There is a concern of whether the structure and diversity of a microbial community can be effectively revealed by short-length pyrosequencing reads. In this study, we performed a microbial community analysis on a sample from a high-efficiency denitrifying quinoline-degrading bioreactor and compared the results generated by pyrosequencing with those generated by clone library technology. By both technologies, 16S rRNA gene analysis indicated that the bacteria in the sample were closely related to, for example, Proteobacteria, Actinobacteria, and Bacteroidetes. The sequences belonging to Rhodococcus were the most predominant, and Pseudomonas, Sphingomonas, Acidovorax, and Zoogloea were also abundant. Both methods revealed a similar overall bacterial community structure. However, the 622 pyrosequencing reads of the hypervariable V3 region of the 16S rRNA gene revealed much higher bacterial diversity than the 130 sequences from the full-length 16S rRNA gene clone library. The 92 operational taxonomic unit (OTUs) detected using pyrosequencing belonged to 45 families, whereas the 37 OTUs found in the clone library belonged to 25 families. Most sequences obtained from the clone library had equivalents in the pyrosequencing reads. However, 64 OTUs detected by pyrosequencing were not represented in the clone library. Our results demonstrate that pyrosequencing of the V3 region of the 16S rRNA gene is not only a powerful tool for discovering low-abundance bacterial populations but is also reliable for dissecting the bacterial community structure in a wastewater environment.     

Estimating Protistan Diversity Using High‐Throughput Sequencing

Sequencing hypervariable regions from the 18S rRNA gene is commonly employed to characterize protistan biodiversity, yet there are concerns that short reads do not provide the same taxonomic resolution as full‐length sequences. A total of 7,432 full‐length sequences were used to perform an in silico analysis of how sequences of various lengths and target regions impact downstream ecological interpretations. Sequences that were longer than 400 nucleotides and included the V4 hypervariable region generated results similar to those derived from full‐length 18S rRNA gene sequences. Present high‐throughput sequencing capabilities are approaching protistan diversity estimation comparable to whole gene sequences.     

RiboFR-Seq: a novel approach to linking 16S rRNA amplicon profiles to metagenomes

16S rRNA amplicon analysis and shotgun metagenome sequencing are two main culture-independent strategies to explore the genetic landscape of various microbial communities. Recently, numerous studies have employed these two approaches together, but downstream data analyses were performed separately, which always generated incongruent or conflict signals on both taxonomic and functional classifications. Here we propose a novel approach, RiboFR-Seq (Ribosomal RNA gene flanking region sequencing), for capturing both ribosomal RNA variable regions and their flanking protein-coding genes simultaneously. Through extensive testing on clonal bacterial strain, salivary microbiome and bacterial epibionts of marine kelp, we demonstrated that RiboFR-Seq could detect the vast majority of bacteria not only in well-studied microbiomes but also in novel communities with limited reference genomes. Combined with classical amplicon sequencing and shotgun metagenome sequencing, RiboFR-Seq can link the annotations of 16S rRNA and metagenomic contigs to make a consensus classification. By recognizing almost all 16S rRNA copies, the RiboFR-seq approach can effectively reduce the taxonomic abundance bias resulted from 16S rRNA copy number variation. We believe that RiboFR-Seq, which provides an integrated view of 16S rRNA profiles and metagenomes, will help us better understand diverse microbial communities.     

Biased Diversity Metrics Revealed by Bacterial 16S Pyrotags Derived from Different Primer Sets

In recent years, PCR-based pyrosequencing of 16S rRNA genes has continuously increased our understanding of complex microbial communities in various environments of the Earth. However, there is always concern on the potential biases of diversity determination using different 16S rRNA gene primer sets and covered regions. Here, we first report how bacterial 16S rRNA gene pyrotags derived from a series of different primer sets resulted in the biased diversity metrics. In total, 14 types of pyrotags were obtained from two-end pyrosequencing of 7 amplicon pools generated by 7 primer sets paired by 1 of 4 forward primers (V1F, V3F, V5F, and V7F) and 1 of 4 reverse primers (V2R, V4R, V6R, and V9R), respectively. The results revealed that: i) the activated sludge exhibited a large bacterial diversity that represented a broad range of bacterial populations and served as a good sample in this methodology research; ii) diversity metrics highly depended on the selected primer sets and covered regions; iii) paired pyrotags obtained from two-end pyrosequencing of each short amplicon displayed different diversity metrics; iv) relative abundance analysis indicated the sequencing depth affected the determination of rare bacteria but not abundant bacteria; v) the primer set of V1F and V2R significantly underestimated the diversity of activated sludge; and vi) the primer set of V3F and V4R was highly recommended for future studies due to its advantages over other primer sets. All of these findings highlight the significance of this methodology research and offer a valuable reference for peer researchers working on microbial diversity determination.     

metaxa2: improved identification and taxonomic classification of small and large subunit rRNA in metagenomic data

The ribosomal rRNA genes are widely used as genetic markers for taxonomic identification of microbes. Particularly the small subunit (SSU; 16S/18S) rRNA gene is frequently used for species‐ or genus‐level identification, but also the large subunit (LSU; 23S/28S) rRNA gene is employed in taxonomic assignment. The metaxa software tool is a popular utility for extracting partial rRNA sequences from large sequencing data sets and assigning them to an archaeal, bacterial, nuclear eukaryote, mitochondrial or chloroplast origin. This study describes a comprehensive update to metaxa – metaxa 2 – that extends the capabilities of the tool, introducing support for the LSU rRNA gene, a greatly improved classifier allowing classification down to genus or species level, as well as enhanced support for short‐read (100 bp) and paired‐end sequences, among other changes. The performance of metaxa 2 was compared to other commonly used taxonomic classifiers, showing that metaxa 2 often outperforms previous methods in terms of making correct predictions while maintaining a low misclassification rate. metaxa 2 is freely available from http://microbiology.se/software/metaxa2/ .     

基于高通量测序研究青藏高原茶卡盐湖微生物多样性

【目的】茶卡盐湖(Chaka Salt Lake,CSL)是青藏高原有名的天然结晶盐湖,具有独特的石盐盐湖矿床,盛产青盐。盐湖卤水环境中存在丰富的嗜盐菌资源和潜在的新种,细菌和古菌的群落结构特征和物种多样性尚不明确。【方法】采用Illumina高通量测序平台对茶卡盐湖水样和底泥混合物中的细菌和古菌群落进行16S r RNA基因(V3-V5区)高通量测序,检测4个样本的群落结构差异和微生物多样性。【结果】获得细菌和古菌总有效序列分别为117 192和110 571条。结果分析表明细菌和古菌的物种注释(Operational taxonomic unit,OTU)数目分别为421和317,获得分类地位明确的细菌种类为14门28纲170属,古菌为5门4纲34属。细菌的优势类群是厚壁菌门(Firmicutes),所占比例为68.37%,其次为变形菌门Proteobacteria(20.49%);优势种属依次为芽孢杆菌属Bacillus(41.94%)、海洋芽孢杆菌属Oceanobacillus(8.03%)、假单胞菌属Pseudomonas(7.67%)、盐厌氧菌属Halanaerobium(7.42%)和乳球菌属Lactococcus(7.38%);古菌的优势类群以广古菌门(Euryarchaeota)盐杆菌纲(Halobacteria)为主,优势菌是Halonotius(17.21%)和盐红菌属Halorubrum(16.23%)。【结论】揭示了茶卡盐湖中细菌和古菌的群落结构及物种多样性,为嗜盐菌的开发及后续微生物资源的挖掘提供了理论依据。