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.     

Groundtruthing next-gen sequencing for microbial ecology-biases and errors in community structure estimates from PCR amplicon pyrosequencing

Analysis of microbial communities by high-throughput pyrosequencing of SSU rRNA gene PCR amplicons has transformed microbial ecology research and led to the observation that many communities contain a diverse assortment of rare taxa-a phenomenon termed the Rare Biosphere. Multiple studies have investigated the effect of pyrosequencing read quality on operational taxonomic unit (OTU) richness for contrived communities, yet there is limited information on the fidelity of community structure estimates obtained through this approach. Given that PCR biases are widely recognized, and further unknown biases may arise from the sequencing process itself, a priori assumptions about the neutrality of the data generation process are at best unvalidated. Furthermore, post-sequencing quality control algorithms have not been explicitly evaluated for the accuracy of recovered representative sequences and its impact on downstream analyses, reducing useful discussion on pyrosequencing reads to their diversity and abundances. Here we report on community structures and sequences recovered for in vitro-simulated communities consisting of twenty 16S rRNA gene clones tiered at known proportions. PCR amplicon libraries of the V3-V4 and V6 hypervariable regions from the in vitro-simulated communities were sequenced using the Roche 454 GS FLX Titanium platform. Commonly used quality control protocols resulted in the formation of OTUs with >1% abundance composed entirely of erroneous sequences, while over-aggressive clustering approaches obfuscated real, expected OTUs. The pyrosequencing process itself did not appear to impose significant biases on overall community structure estimates, although the detection limit for rare taxa may be affected by PCR amplicon size and quality control approach employed. Meanwhile, PCR biases associated with the initial amplicon generation may impose greater distortions in the observed community structure.     

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。     

Design and Experimental Application of a Novel Non-Degenerate Universal Primer Set that Amplifies Prokaryotic 16S rRNA Genes with a Low Possibility to Amplify Eukaryotic rRNA Genes

The deep sequencing of 16S rRNA genes amplified by universal primers has revolutionized our understanding of microbial communities by allowing the characterization of the diversity of the uncultured majority. However, some universal primers also amplify eukaryotic rRNA genes, leading to a decrease in the efficiency of sequencing of prokaryotic 16S rRNA genes with possible mischaracterization of the diversity in the microbial community. In this study, we compared 16S rRNA gene sequences from genome-sequenced strains and identified candidates for non-degenerate universal primers that could be used for the amplification of prokaryotic 16S rRNA genes. The 50 identified candidates were investigated to calculate their coverage for prokaryotic and eukaryotic rRNA genes, including those from uncultured taxa and eukaryotic organelles, and a novel universal primer set, 342F-806R, covering many prokaryotic, but not eukaryotic, rRNA genes was identified. This primer set was validated by the amplification of 16S rRNA genes from a soil metagenomic sample and subsequent pyrosequencing using the Roche 454 platform. The same sample was also used for pyrosequencing of the amplicons by employing a commonly used primer set, 338F-533R, and for shotgun metagenomic sequencing using the Illumina platform. Our comparison of the taxonomic compositions inferred by the three sequencing experiments indicated that the non-degenerate 342F-806R primer set can characterize the taxonomic composition of the microbial community without substantial bias, and is highly expected to be applicable to the analysis of a wide variety of microbial communities.     

Generation of multimillion-sequence 16S rRNA gene libraries from complex microbial communities by assembling paired-end illumina reads

Microbial communities host unparalleled taxonomic diversity. Adequate characterization of environmental and host-associated samples remains a challenge for microbiologists, despite the advent of 16S rRNA gene sequencing. In order to increase the depth of sampling for diverse bacterial communities, we developed a method for sequencing and assembling millions of paired-end reads from the 16S rRNA gene (spanning the V3 region; ～200 nucleotides) by using an Illumina genome analyzer. To confirm reproducibility and to identify a suitable computational pipeline for data analysis, sequence libraries were prepared in duplicate for both a defined mixture of DNAs from known cultured bacterial isolates (>1 million postassembly sequences) and an Arctic tundra soil sample (>6 million postassembly sequences). The Illumina 16S rRNA gene libraries represent a substantial increase in number of sequences over all extant next-generation sequencing approaches (e.g., 454 pyrosequencing), while the assembly of paired-end 125-base reads offers a methodological advantage by incorporating an initial quality control step for each 16S rRNA gene sequence. This method incorporates indexed primers to enable the characterization of multiple microbial communities in a single flow cell lane, may be modified readily to target other variable regions or genes, and demonstrates unprecedented and economical access to DNAs from organisms that exist at low relative abundances.     

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.     

Microbial Community Composition and Diversity via 16S rRNA Gene Amplicons: Evaluating the Illumina Platform

As new sequencing technologies become cheaper and older ones disappear, laboratories switch vendors and platforms. Validating the new setups is a crucial part of conducting rigorous scientific research. Here we report on the reliability and biases of performing bacterial 16S rRNA gene amplicon paired-end sequencing on the MiSeq Illumina platform. We designed a protocol using 50 barcode pairs to run samples in parallel and coded a pipeline to process the data. Sequencing the same sediment sample in 248 replicates as well as 70 samples from alkaline soda lakes, we evaluated the performance of the method with regards to estimates of alpha and beta diversity. Using different purification and DNA quantification procedures we always found up to 5-fold differences in the yield of sequences between individually barcodes samples. Using either a one-step or a two-step PCR preparation resulted in significantly different estimates in both alpha and beta diversity. Comparing with a previous method based on 454 pyrosequencing, we found that our Illumina protocol performed in a similar manner – with the exception for evenness estimates where correspondence between the methods was low. We further quantified the data loss at every processing step eventually accumulating to 50% of the raw reads. When evaluating different OTU clustering methods, we observed a stark contrast between the results of QIIME with default settings and the more recent UPARSE algorithm when it comes to the number of OTUs generated. Still, overall trends in alpha and beta diversity corresponded highly using both clustering methods. Our procedure performed well considering the precisions of alpha and beta diversity estimates, with insignificant effects of individual barcodes. Comparative analyses suggest that 454 and Illumina sequence data can be combined if the same PCR protocol and bioinformatic workflows are used for describing patterns in richness, beta-diversity and taxonomic composition.     

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.     

基于MiSeq测序分析新疆泥火山土壤细菌群落多样性

【目的】以新疆乌苏泥火山土壤为研究对象,了解泥火山细菌群落结构及其时空动态变化。【方法】选择泥火山4种不同生境土壤在4、7、11月份采样,应用Illumina Mi Seq测序技术测定泥火山土壤细菌的16S r RNA基因V3–V4变异区序列,分析乌苏泥火山不同生境土壤细菌群落组成。【结果】泥火山土壤细菌在97%的相似水平下共得到OTU个数为29 005,在细菌门水平上共有38种细菌类群,Proteobacteria、Actinobacteria、Bacteroidetes为优势菌群,在属水平上共有72种细菌类群,其中含量最高的是未分类细菌;多样性分析表明生境D的丰度指数和多样性指数最高,将泥火山细菌群落多样性与理化因子结合分析,发现其多样性随着土壤养分的增加而基本降低,说明物种多样性指数与理化因子之间呈负相关关系;OTU水平的分析表明生境A的群落组成在时空动态上没有显著差异,其样品群落组成较为相似,而生境C的物种组成差异较大。【结论】相比较于传统方法,Mi Seq测序能够更全面解析环境样品中微生物多样性,揭示了乌苏泥火山群蕴含着丰富的微生物资源,这将为深入研究泥火山生态系统奠定基础,为合理利用和开发泥火山微生物资源提供指导。     

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.     

Removing Noise From Pyrosequenced Amplicons

Background  

In many environmental genomics applications a homologous region of DNA from a diverse sample is first amplified by PCR and then sequenced. The next generation sequencing technology, 454 pyrosequencing, has allowed much larger read numbers from PCR amplicons than ever before. This has revolutionised the study of microbial diversity as it is now possible to sequence a substantial fraction of the 16S rRNA genes in a community. However, there is a growing realisation that because of the large read numbers and the lack of consensus sequences it is vital to distinguish noise from true sequence diversity in this data. Otherwise this leads to inflated estimates of the number of types or operational taxonomic units (OTUs) present. Three sources of error are important: sequencing error, PCR single base substitutions and PCR chimeras. We present AmpliconNoise, a development of the PyroNoise algorithm that is capable of separately removing 454 sequencing errors and PCR single base errors. We also introduce a novel chimera removal program, Perseus, that exploits the sequence abundances associated with pyrosequencing data. We use data sets where samples of known diversity have been amplified and sequenced to quantify the effect of each of the sources of error on OTU inflation and to validate these algorithms.     

基于高通量测序对呼伦贝尔陶顺阿尔山细菌群落多样性的研究

对内蒙古呼伦贝尔陶顺阿尔山水体与沉积物的细菌群落结构和多样性，进行16S rRNA基因(V3～V5区)高通量测序。运用Illumina MiSeq高通量测序平台，共获得594 226条优化序列。结果显示，水体中最主要的细菌类群为变形菌门(Proteobacteria),而沉积物样品中的主要优势类群为盐厌氧菌门(Haloanaerobium);细菌在属分类水平上，水体中优势菌群为嗜盐单胞菌属(Halomonas)、冷弯菌属(Psychroflexus)、盐厌氧菌属(Haloanaerobium);沉积物样品中优势菌群为盐厌氧菌属、盐单胞菌属、未分类菌(no-rank-f-unclassified),其中存在大量的未知物种。陶顺阿尔山水体与沉积物中存在着丰富的微生物群落，且差异性大，未知菌种居多。本研究首次阐明了陶顺阿尔山细菌群落的多样性，为今后开发和利用陶顺阿尔山的功能菌群提供参考。     

Surveying the Microbiome of Ants: Comparing 454 Pyrosequencing with Traditional Methods To Uncover Bacterial Diversity

We are only beginning to understand the depth and breadth of microbial associations across the eukaryotic tree of life. Reliably assessing bacterial diversity is a key challenge, and next-generation sequencing approaches are facilitating this endeavor. In this study, we used 16S rRNA amplicon pyrosequencing to survey microbial diversity in ants. We compared 454 libraries with Sanger-sequenced clone libraries as well as cultivation of live bacteria. Pyrosequencing yielded 95,656 bacterial 16S rRNA reads from 19 samples derived from four colonies of one ant species. The most dominant bacterial orders in the microbiome of the turtle ant Cephalotes varians were Rhizobiales, Burkholderiales, Opitutales, Xanthomonadales, and Campylobacterales, as revealed through both 454 sequencing and cloning. Even after stringent quality filtering, pyrosequencing recovered 445 microbe operational taxonomic units (OTUs) not detected with traditional techniques. In comparing bacterial communities associated with specific tissues, we found that gut tissues had significantly higher diversity than nongut tissues, and many of the OTUs identified from these groups clustered within ant-specific lineages, indicating a deep coevolutionary history of Cephalotes ants and their associated microbes. These lineages likely function as nutritional symbionts. One of four ant colonies investigated was infected with a Spiroplasma sp. (order Entomoplasmatales), a potential ant pathogen. Our work shows that the microbiome associated with Cephalotes varians is dominated by a few dozen bacterial lineages and that 454 sequencing is a cost-efficient tool to screen ant symbiont diversity.     

Target region selection is a critical determinant of community fingerprints generated by 16S pyrosequencing

Pyrosequencing of 16S rRNA genes allows for in-depth characterization of complex microbial communities. Although it is known that primer selection can influence the profile of a community generated by sequencing, the extent and severity of this bias on deep-sequencing methodologies is not well elucidated. We tested the hypothesis that the hypervariable region targeted for sequencing and primer degeneracy play important roles in influencing the composition of 16S pyrotag communities. Subgingival plaque from deep sites of current smokers with chronic periodontitis was analyzed using Sanger sequencing and pyrosequencing using 4 primer pairs. Greater numbers of species were detected by pyrosequencing than by Sanger sequencing. Rare taxa constituted nearly 6% of each pyrotag community and less than 1% of the Sanger sequencing community. However, the different target regions selected for pyrosequencing did not demonstrate a significant difference in the number of rare and abundant taxa detected. The genera Prevotella, Fusobacterium, Streptococcus, Granulicatella, Bacteroides, Porphyromonas and Treponema were abundant when the V1-V3 region was targeted, while Streptococcus, Treponema, Prevotella, Eubacterium, Porphyromonas, Campylobacter and Enterococcus predominated in the community generated by V4-V6 primers, and the most numerous genera in the V7-V9 community were Veillonella, Streptococcus, Eubacterium, Enterococcus, Treponema, Catonella and Selenomonas. Targeting the V4-V6 region failed to detect the genus Fusobacterium, while the taxa Selenomonas, TM7 and Mycoplasma were not detected by the V7-V9 primer pairs. The communities generated by degenerate and non-degenerate primers did not demonstrate significant differences. Averaging the community fingerprints generated by V1-V3 and V7-V9 primers provided results similar to Sanger sequencing, while allowing a significantly greater depth of coverage than is possible with Sanger sequencing. It is therefore important to use primers targeted to these two regions of the 16S rRNA gene in all deep-sequencing efforts to obtain representational characterization of complex microbial communities.     

Influence of DNA Extraction Method, 16S rRNA Targeted Hypervariable Regions,and Sample Origin on Microbial Diversity Detected by 454 Pyrosequencing in Marine Chemosynthetic Ecosystems

Next-generation sequencing (NGS) opens up exciting possibilities for improving our knowledge of environmental microbial diversity, allowing rapid and cost-effective identification of both cultivated and uncultivated microorganisms. However, library preparation, sequencing, and analysis of the results can provide inaccurate representations of the studied community compositions. Therefore, all these steps need to be taken into account carefully. Here we evaluated the effects of DNA extraction methods, targeted 16S rRNA hypervariable regions, and sample origins on the diverse microbes detected by 454 pyrosequencing in marine cold seep and hydrothermal vent sediments. To assign the reads with enough taxonomic precision, we built a database with about 2,500 sequences from Archaea and Bacteria from deep-sea marine sediments, affiliated according to reference publications in the field. Thanks to statistical and diversity analyses as well as inference of operational taxonomic unit (OTU) networks, we show that (i) while DNA extraction methods do not seem to affect the results for some samples, they can lead to dramatic changes for others; and (ii) the choice of amplification and sequencing primers also considerably affects the microbial community detected in the samples. Thereby, very different proportions of pyrosequencing reads were obtained for some microbial lineages, such as the archaeal ANME-1, ANME-2c, and MBG-D and deltaproteobacterial subgroups. This work clearly indicates that the results from sequencing-based analyses, such as pyrosequencing, should be interpreted very carefully. Therefore, the combination of NGS with complementary approaches, such as fluorescence in situ hybridization (FISH)/catalyzed reporter deposition (CARD)-FISH or quantitative PCR (Q-PCR), would be desirable to gain a more comprehensive picture of environmental microbial communities.     

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.     

BIPES,a cost-effective high-throughput method for assessing microbial diversity

Pyrosequencing of 16S rRNA (16S) variable tags has become the most popular method for assessing microbial diversity, but the method remains costly for the evaluation of large numbers of environmental samples with high sequencing depths. We developed a barcoded Illumina paired-end (PE) sequencing (BIPES) method that sequences each 16S V6 tag from both ends on the Illumina HiSeq 2000, and the PE reads are then overlapped to obtain the V6 tag. The average accuracy of Illumina single-end (SE) reads was only 97.9%, which decreased from ∼99.9% at the start of the read to less than 85% at the end of the read; nevertheless, overlapping of the PE reads significantly increased the sequencing accuracy to 99.65% by verifying the 3′ end of each SE in which the sequencing quality was degraded. After the removal of tags with two or more mismatches within the medial 40–70 bases of the reads and of tags with any primer errors, the overall base sequencing accuracy of the BIPES reads was further increased to 99.93%. The BIPES reads reflected the amounts of the various tags in the initial template, but long tags and high GC tags were underestimated. The BIPES method yields 20–50 times more 16S V6 tags than does pyrosequencing in a single-flow cell run, and each of the BIPES reads costs less than 1/40 of a pyrosequencing read. As a laborsaving and cost-effective method, BIPES can be routinely used to analyze the microbial ecology of both environmental and human microbiomes.     

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.     

Evaluation of different partial 16S rRNA gene sequence regions for phylogenetic analysis of microbiomes

Operational taxonomic units (OTUs) are conventionally defined at a phylogenetic distance (0.03—species, 0.05—genus, 0.10—family) based on full-length 16S rRNA gene sequences. However, partial sequences (700 bp or shorter) have been used in most studies. This discord may affect analysis of diversity and species richness because sequence divergence is not distributed evenly along the 16S rRNA gene. In this study, we compared a set each of bacterial and archaeal 16S rRNA gene sequences of nearly full length with multiple sets of different partial 16S rRNA gene sequences derived therefrom (approximately 440-700 bp), at conventional and alternative distance levels. Our objective was to identify partial sequence region(s) and distance level(s) that allow more accurate phylogenetic analysis of partial 16S rRNA genes. Our results showed that no partial sequence region could estimate OTU richness or define OTUs as reliably as nearly full-length genes. However, the V1-V4 regions can provide more accurate estimates than others. For analysis of archaea, we recommend the V1-V3 and the V4-V7 regions and clustering of species-level OTUs at 0.03 and 0.02 distances, respectively. For analysis of bacteria, the V1-V3 and the V1-V4 regions should be targeted, with species-level OTUs being clustered at 0.04 distance in both cases.