Exploring Microbial Diversity and Taxonomy Using SSU rRNA Hypervariable Tag Sequencing

By Susan M. Huse, Les Dethlefsen, J. Huber, D. Welch, David A. Relman, Mitchell L Sogin. PLoS Genetics, 2008

1,018 citations recorded by the source corpus.

Massively parallel pyrosequencing of hypervariable regions from small subunit ribosomal RNA (SSU rRNA) genes can sample a microbial community two or three orders of magnitude more deeply per dollar and per hour than capillary sequencing of full-length SSU rRNA. As with full-length rRNA surveys, each sequence read is a tag surrogate for a single microbe. However, rather than assigning taxonomy by creating gene trees de novo that include all experimental sequences and certain reference taxa, we compare the hypervariable region tags to an extensive database of rRNA sequences and assign taxonomy based on the best match in a Global Alignment for Sequence Taxonomy (GAST) process. The resulting taxonomic census provides information on both composition and diversity of the microbial community. To determine the effectiveness of using only hypervariable region tags for assessing microbial community membership, we compared the taxonomy assigned to the V3 and V6 hypervariable regions with the taxonomy assigned to full-length SSU rRNA sequences isolated from both the human gut and a deep-sea hydrothermal vent. The hypervariable region tags and full-length rRNA sequences provided equivalent taxonomy and measures of relative abundance of microbial communities, even for tags up to 15% divergent from their nearest reference match. The greater sampling depth per dollar afforded by massively parallel pyrosequencing reveals many more members of the “rare biosphere” than does capillary sequencing of the full-length gene. In addition, tag sequencing eliminates cloning bias and the sequences are short enough to be completely sequenced in a single read, maximizing the number of organisms sampled in a run while minimizing chimera formation. This technique allows the cost-effective exploration of changes in microbial community structure, including the rare biosphere, over space and time and can be applied immediately to initiatives, such as the Human Microbiome Project.

Subfields: Ecology, Environmental Chemistry, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/88a539eb782eb591af0d0db6a904f147521a5197

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Citations in the corpus

Defining the healthy "core microbiome" of oral microbial communities (2009, methodology): “We then used the GAST algorithm [27] to calculate the percent difference between each unique sequence and its closest match in a database of 69816 unique eubacterial and 2779 unique archaeal V5-V6 sequences, representing 323499 SSU rRNA sequences from the SILVA database [28].”
Minimum entropy decomposition: Unsupervised oligotyping for sensitive partitioning of high-throughput marker gene sequences (2014, methodology): “‘Unit’ refers to the end product of a partitioning method: a GAST taxon, an OTU, an oligotype or an MED node.”
The rare bacterial biosphere. (2012, neutral): “…has generated a lively debate and has stimulated the development of different processing methods to try to minimize the number of erroneous reads (Huse et al. 2007, 2008, 2010; Huber et al. 2009; Quince et al. 2009, 2011; Reeder & Knight 2009, 2010; Engelbrektson et al. 2010; Kunin et al. 2010).”
Comparative Analysis of Pyrosequencing and a Phylogenetic Microarray for Exploring Microbial Community Structures in the Human Distal Intestine (2009, neutral): “The assignment tool GAST was recently reported [40], which uses the best BLAST hits against a reference database of V3 and V6 regions where the taxonomy is known from RDPclassification results.”
Assessing and Improving Methods Used in Operational Taxonomic Unit-Based Approaches for 16S rRNA Gene Sequence Analysis (2011, background): “Numerous studies have shown that diverse approaches to classification are robust (10, 16, 24).”
The Pervasive Effects of an Antibiotic on the Human Gut Microbiota, as Revealed by Deep 16S rRNA Sequencing (2008, methodology): “There was substantial agreement between the methods in the estimated relative abundance of specific taxa ranging from the phylum to genus level [48].”
Distribution of PAHs and the PAH-degrading bacteria in the deep-sea sediments of the high-latitude Arctic Ocean (2014, methodology): “Taxonomy assignment of the tags and OTUs was performed using the Global Alignment for Sequence Taxonomy (GAST) method (Sogin et al., 2006; Huse et al., 2008).”
Human gut microbiota in obesity and after gastric bypass (2009, result): “Our findings agree with a recent in-depth study that found equivalent taxonomic assignments by Sanger and tag pyrosequencing of V3 and V6 regions (28).”
Soil fungal communities respond compositionally to recurring frequent prescribed burning in a managed southeastern US forest ecosystem (2015, background): “The sequences were truncated to 250 bp, near identical sequences preclustered to reduce potential sequencing bias (Huse et al., 2008) and screened for chimeras (uchime; Edgar et al., 2011).”
Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies (2012, background): “The frequent use of HV region six in diversity analysis makes this pair particularly interesting for comparative analysis (35,44,45).”
Impact of training sets on classification of high-throughput bacterial 16s rRNA gene surveys (2011, neutral): “Huse et al .”
Bacterial diversity in the oral cavity of ten healthy individuals (2010, background): “resolution than hypervariable region ‘tag’ sequences was highlighted in a comparative analysis of these two types of sequence data (Huse et al., 2008).”
Alteration of the soil bacterial community during parent material maturation driven by different fertilization treatments (2016, methodology): “…sequencing adapter, a linker sequence and a unique, error-correcting barcode sequence (Ns), as previously described by Dethlefsen et al. (2008) and Huse et al. (2008), targeting the V1eV3 hypervariable region of the 16S rRNA gene were used for PCR. Amplification reactions were performed in a 20…”