Dataset Information

Multicenter assessment of microbial community profiling using 16S rRNA gene sequencing and shotgun metagenomic sequencing.

ABSTRACT: Introduction:Microbiome research based on high-throughput sequencing has grown exponentially in recent years, but methodological variations can easily undermine the reproducibility across studies. Objectives:To systematically evaluate the comparability of sequencing results of 16S rRNA gene sequencing (16Ss)- and shotgun metagenomic sequencing (SMs)-based microbial community profiling in laboratories under routine conditions. Methods:We designed a multicenter study across 35 participating laboratories in China using designed mock communities and homogenized fecal samples. Results:A wide range of practices and approaches was reported by the participating laboratories. The observed microbial compositions of the mock communities in 46.2% (12/26) of the 16Ss and 82.6% (19/23) of the SMs laboratories had significant correlations with the expected result (Spearman r>0.59, P <0.05). The results from laboratories with near-identical protocols showed slight interlaboratory deviations. However, a high degree of interlaboratory deviation was found in the observed abundances of specific taxa, such as Bacteroides spp. (range: 0.3%-53.5%), Enterococci spp. (range: 0.8%-43.9%) and Fusobacterium spp. (range: 0.1%-39.8%). SMs performed better than 16Ss in detecting low-abundance bacteria (B. bifidum). The differences in DNA extraction methods, amplified regions and bioinformatics analysis tools (taxonomic classifiers and database) were important factors causing interlaboratory deviations. Addressing laboratory contamination is an urgent task because various sources of unexpected microbes were found in negative control samples. Conclusions:Well-defined control samples, such as the mock communities in this study, should be routinely used in microbiome research for monitoring potential biases. The findings in this study will provide guidance in the choice of more reasonable operating procedures to minimize potential methodological biases in revealing human microbiota composition.

SUBMITTER: Han D

PROVIDER: S-EPMC7584675 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Multicenter assessment of microbial community profiling using 16S rRNA gene sequencing and shotgun metagenomic sequencing.

Han Dongsheng D Gao Peng P Li Rui R Tan Ping P Xie Jiehong J Zhang Rui R Li Jinming J

Journal of advanced research 20200721

<h4>Introduction</h4>Microbiome research based on high-throughput sequencing has grown exponentially in recent years, but methodological variations can easily undermine the reproducibility across studies.<h4>Objectives</h4>To systematically evaluate the comparability of sequencing results of 16S rRNA gene sequencing (16Ss)- and shotgun metagenomic sequencing (SMs)-based microbial community profiling in laboratories under routine conditions.<h4>Methods</h4>We designed a multicenter study across 3 ...[more]

PMID: 33133687

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Project description:BACKGROUND:The 16S rRNA gene-based amplicon sequencing analysis is widely used to determine the taxonomic composition of microbial communities. Once the taxonomic composition of each community is obtained, evolutionary relationships among taxa are inferred by a phylogenetic tree. Thus, the combined representation of taxonomic composition and phylogenetic relationships among taxa is a powerful method for understanding microbial community structure; however, applying phylogenetic tree-based representation with information on the abundance of thousands or more taxa in each community is a difficult task. For this purpose, we previously developed the tool VITCOMIC (VIsualization tool for Taxonomic COmpositions of MIcrobial Community), which is based on the genome-sequenced microbes' phylogenetic information. Here, we introduce VITCOMIC2, which incorporates substantive improvements over VITCOMIC that were necessary to address several issues associated with 16S rRNA gene-based analysis of microbial communities. RESULTS:We developed VITCOMIC2 to provide (i) sequence identity searches against broad reference taxa including uncultured taxa; (ii) normalization of 16S rRNA gene copy number differences among taxa; (iii) rapid sequence identity searches by applying the graphics processing unit-based sequence identity search tool CLAST; (iv) accurate taxonomic composition inference and nearly full-length 16S rRNA gene sequence reconstructions for metagenomic shotgun sequencing; and (v) an interactive user interface for simultaneous representation of the taxonomic composition of microbial communities and phylogenetic relationships among taxa. We validated the accuracy of processes (ii) and (iv) by using metagenomic shotgun sequencing data from a mock microbial community. CONCLUSIONS:The improvements incorporated into VITCOMIC2 enable users to acquire an intuitive understanding of microbial community composition based on the 16S rRNA gene sequence data obtained from both metagenomic shotgun and amplicon sequencing.

Project description:BackgroundSequential membrane filtration as a pre-processing step for capturing sediment-associated microorganisms could provide good quality and integrity DNA that can be preserved and kept at ambient temperatures before community profiling through culture-independent molecular techniques. However, the effects of sample pre-processing via filtration on DNA-based profiling of sediment-associated microbial community diversity and composition are poorly understood. Specifically, the influences of pre-processing on the quality and quantity of extracted DNA, high-throughput DNA sequencing reads, and detected microbial taxa need further evaluation.ResultsWe assessed the impact of pre-processing freshwater sediment samples by sequential membrane filtration (from 10, 5 to 0.22 μm pore size) for 16S rRNA-based community profiling of sediment-associated microorganisms. Specifically, we examined if there would be method-driven differences between non- and pre-processed sediment samples regarding the quality and quantity of extracted DNA, PCR amplicon, resulting high-throughput sequencing reads, microbial diversity, and community composition. We found no significant difference in the qualities and quantities of extracted DNA and PCR amplicons, and the read abundance after bioinformatics processing (i.e., denoising and chimeric-read filtering steps) between the two methods. Although the non- and pre-processed sediment samples had more unique than shared amplicon sequence variants (ASVs), we report that their shared ASVs accounted for 74% of both methods' absolute read abundance. More so, at the genus level, the final collection filter identified most of the genera (95% of the reads) captured from the non-processed samples, with a total of 51 false-negative (2%) and 59 false-positive genera (3%). We demonstrate that while there were differences in shared and unique taxa, both methods revealed comparable microbial diversity and community composition.ConclusionsOur observations highlight the feasibility of pre-processing sediment samples for community analysis and the need to further assess sampling strategies to help conceptualize appropriate study designs for sediment-associated microbial community profiling.

Dataset Information

Multicenter assessment of microbial community profiling using 16S rRNA gene sequencing and shotgun metagenomic sequencing.

Publications

Multicenter assessment of microbial community profiling using 16S rRNA gene sequencing and shotgun metagenomic sequencing.

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