Deblur Rapidly Resolves Single-Nucleotide Community Sequence Patterns

By Amnon Amir, Daniel McDonald, Jose A Navas-Molina, Evguenia Kopylova, James T. Morton, Zhenjiang Zech Xu, E. Kightley, Luke R. Thompson, Embriette R. Hyde, Antonio Gonzalez and 1 more. mSystems, 2017

1,578 citations recorded by the source corpus.

Deblur provides a rapid and sensitive means to assess ecological patterns driven by differentiation of closely related taxa. This algorithm provides a solution to the problem of identifying real ecological differences between taxa whose amplicons differ by a single base pair, is applicable in an automated fashion to large-scale sequencing data sets, and can integrate sequencing runs collected over time. ABSTRACT High-throughput sequencing of 16S ribosomal RNA gene amplicons has facilitated understanding of complex microbial communities, but the inherent noise in PCR and DNA sequencing limits differentiation of closely related bacteria. Although many scientific questions can be addressed with broad taxonomic profiles, clinical, food safety, and some ecological applications require higher specificity. Here we introduce a novel sub-operational-taxonomic-unit (sOTU) approach, Deblur, that uses error profiles to obtain putative error-free sequences from Illumina MiSeq and HiSeq sequencing platforms. Deblur substantially reduces computational demands relative to similar sOTU methods and does so with similar or better sensitivity and specificity. Using simulations, mock mixtures, and real data sets, we detected closely related bacterial sequences with single nucleotide differences while removing false positives and maintaining stability in detection, suggesting that Deblur is limited only by read length and diversity within the amplicon sequences. Because Deblur operates on a per-sample level, it scales to modern data sets and meta-analyses. To highlight Deblur’s ability to integrate data sets, we include an interactive exploration of its application to multiple distinct sequencing rounds of the American Gut Project. Deblur is open source under the Berkeley Software Distribution (BSD) license, easily installable, and downloadable from https://github.com/biocore/deblur . IMPORTANCE Deblur provides a rapid and sensitive means to assess ecological patterns driven by differentiation of closely related taxa. This algorithm provides a solution to the problem of identifying real ecological differences between taxa whose amplicons differ by a single base pair, is applicable in an automated fashion to large-scale sequencing data sets, and can integrate sequencing runs collected over time.

Subfields: Ecology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/8a3667cb304de86101233ace11bc98fc47a790f5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

In Molecular Biology

Citations in the corpus

Denoising the Denoisers: an independent evaluation of microbiome sequence error-correction approaches (2018, background): “Deblur aligns sequences together into ‘‘subOTUs’’ and, based on an upper error rate bound along with a constant probability of indels and the mean read error rate, removes predicted error-derived reads from neighboring sequences (Amir et al., 2017).”
American Gut: an Open Platform for Citizen Science Microbiome Research (2018, methodology): “2 (16), trimming to 125 nucleotides (nt) (otherwise default parameters), to maximize the specificity of 16S data; a trim of 125 nt was used because one sequencing round in the American Gut used 125 cycles while the rest used 150.”
Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice (2019, neutral): “Low quality bases were first removed from the reads and amplicon sequence variants (ASVs) were obtained using the Deblur denoising plugin (Amir et al., 2017) on reads trimmed to 120 bp present in the 16S reference dataset.”
A Novel Sparse Compositional Technique Reveals Microbial Perturbations (2019, methodology): “0) sOTU (48) picking approach, using QIIME 2 (v.”
DNA Sequencing as a Tool to Monitor Marine Ecological Status (2017, methodology): “For example, the Earth Microbiome Project (earthmicrobiome.org) employed Deblur (Amir et al., 2017) to deliver a set of unique sequences with single-nucleotide resolution, rather than representative sequences delivered by OTU clustering.”