Short pyrosequencing reads suffice for accurate microbial community analysis

By Zongzhi Z. Liu, Catherine A. Lozupone, Micah Hamady, Frederic D. Bushman, Rob Knight. Nucleic Acids Research, 2007

708 citations recorded by the source corpus.

Pyrosequencing technology allows us to characterize microbial communities using 16S ribosomal RNA (rRNA) sequences orders of magnitude faster and more cheaply than has previously been possible. However, results from different studies using pyrosequencing and traditional sequencing are often difficult to compare, because amplicons covering different regions of the rRNA might yield different conclusions. We used sequences from over 200 globally dispersed environments to test whether studies that used similar primers clustered together mistakenly, without regard to environment. We then tested whether primer choice affects sequence-based community analyses using UniFrac, our recently-developed method for comparing microbial communities. We performed three tests of primer effects. We tested whether different simulated amplicons generated the same UniFrac clustering results as near-full-length sequences for three recent large-scale studies of microbial communities in the mouse and human gut, and the Guerrero Negro microbial mat. We then repeated this analysis for short sequences (100-, 150-, 200- and 250-base reads) resembling those produced by pyrosequencing. The results show that sequencing effort is best focused on gathering more short sequences rather than fewer longer ones, provided that the primers are chosen wisely, and that community comparison methods such as UniFrac are surprisingly robust to variation in the region sequenced.

Subfields: Ecology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/506e73c750085835c12b2e16a68c5e920c051ee5

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Citations in the corpus

Pyrosequencing-Based Assessment of Soil pH as a Predictor of Soil Bacterial Community Structure at the Continental Scale (2009, neutral): “significant misclassification of sequences (30).”
Exploring Microbial Diversity and Taxonomy Using SSU rRNA Hypervariable Tag Sequencing (2008, positive): “Liu et al [34] used NAST on simulated tag sequences and found similar Unifrac clustering results from the tags as from their full-length source sequences.”
Tag-encoded pyrosequencing analysis of bacterial diversity in a single soil type as affected by management and land use (2008, methodology): “The use of pyrosequencing for evaluating microbial diversity has been described recently as promising to be less labor intensive (Cristea-Fernstrom et al., 2007; Huse et al., 2007; Liu et al., 2007; Roesch et al., 2007; Sundquist et al., 2007; Dowd et al., 2008a).”
The under-recognized dominance of Verrucomicrobia in soil bacterial communities (2011, background): “The region amplified by this primer set is well suited for accurate phylogenetic placementof bacterial sequences (Liu et al., 2007) and, as explained below, the primer set should amplify nearly all bacterial taxa with few biases.”
Examining the global distribution of dominant archaeal populations in soil (2011, background): “In spite of the short-read lengths (B250 bp), this targeted gene region should also provide sufficient resolution for the accurate taxonomic classification of microbial sequences (Liu et al., 2007).”
Bacterial Communities in Women with Bacterial Vaginosis: High Resolution Phylogenetic Analyses Reveal Relationships of Microbiota to Clinical Criteria (2012, background): “The V4 hypervariable region is reported to give the lowest error rates when assigning taxonomy [64,65] and is also suitable for community clustering [66].”
Accurate taxonomy assignments from 16S rRNA sequences produced by highly parallel pyrosequencers (2008, background): “These results are consistent with our previous analysis of pyrosequencing and community clustering (7), which showed that regions overlapping V6 (R1114, 100 bases) were much less suitable for community clustering than other regions, such as R357.”
Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample (2010, background): “Previous work has suggested that fragments of the 16S rRNA as small as 100 bp can be sufficient for resolving microbial community differences (15).”
Characterization of fecal microbial communities in patients with liver cirrhosis (2011, methodology): “Short reads of 16S ribosomal RNA (16S rRNA), such as those produced by pyrosequencing, can yield the same clustering effect as full-length 16S rRNA sequences if the correct regions are chosen.(22) In this study, we performed high-throughput 454 pyrosequencing targeting the 16S rRNA V3 region and rea”
The Effects of Alignment Quality, Distance Calculation Method, Sequence Filtering, and Region on the Analysis of 16S rRNA Gene-Based Studies (2010, methodology): “1 and 6).”
Intestinal domination and the risk of bacteremia in patients undergoing allogeneic hematopoietic stem cell transplantation. (2012, background): “Prior studies using in vitro culture methods have characterized microbial populations inhabiting the intestine [10]; more recently, massively parallel pyrosequencing of bacterial 16S ribosomal RNA (rRNA) encoding genes has provided new insights into the composition and complexity of the intestinal m”
A microbiotic survey of lichen-associated bacteria reveals a new lineage from the Rhizobiales (2009, methodology): “…of amplicons can be dissected using molecular cloning (De la Torre et al., 2003; Rondon et al., 1999; Zhiyong et al., 2007) or highthroughput metagenomic methods (Edwards et al., 2006; Ley et al., 2006; Liu et al., 2007; Margulies et al., 2005; Roesch et al., 2007; Turnbaugh et al., 2006, 2007).”
Conservative Fragments in Bacterial 16S rRNA Genes and Primer Design for 16S Ribosomal DNA Amplicons in Metagenomic Studies (2009, background): “After merging, the predicted primers were compared with known primers from previous reports [14,15,20,27].”
Digging deeper to find unique microbial communities: The strong effect of depth on the structure of bacterial and archaeal communities in soil (2012, background): “, 2011), with the amplified region well-suited for accurate phylogenetic and taxonomic placement of sequences (Liu et al., 2007).”
Simultaneous Assessment of Soil Microbial Community Structure and Function through Analysis of the Meta-Transcriptome (2008, neutral): “[24,25]).”
Comparative metagenomic, phylogenetic and physiological analyses of soil microbial communities across nitrogen gradients (2011, methodology): “the primer set 515f/806r that targets a region of the 16S rRNA gene that yields accurate phylogenetic information (Liu et al., 2007) and should have few biases against any bacterial taxa (Bates et al.”