Dataset Information

A human gut microbial gene catalogue established by metagenomic sequencing.

ABSTRACT: To understand the impact of gut microbes on human health and well-being it is crucial to assess their genetic potential. Here we describe the Illumina-based metagenomic sequencing, assembly and characterization of 3.3 million non-redundant microbial genes, derived from 576.7 gigabases of sequence, from faecal samples of 124 European individuals. The gene set, approximately 150 times larger than the human gene complement, contains an overwhelming majority of the prevalent (more frequent) microbial genes of the cohort and probably includes a large proportion of the prevalent human intestinal microbial genes. The genes are largely shared among individuals of the cohort. Over 99% of the genes are bacterial, indicating that the entire cohort harbours between 1,000 and 1,150 prevalent bacterial species and each individual at least 160 such species, which are also largely shared. We define and describe the minimal gut metagenome and the minimal gut bacterial genome in terms of functions present in all individuals and most bacteria, respectively.

SUBMITTER: Qin J

PROVIDER: S-EPMC3779803 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature

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A human gut microbial gene catalogue established by metagenomic sequencing.

Qin Junjie J Li Ruiqiang R Raes Jeroen J Arumugam Manimozhiyan M Burgdorf Kristoffer Solvsten KS Manichanh Chaysavanh C Nielsen Trine T Pons Nicolas N Levenez Florence F Yamada Takuji T Mende Daniel R DR Li Junhua J Xu Junming J Li Shaochuan S Li Dongfang D Cao Jianjun J Wang Bo B Liang Huiqing H Zheng Huisong H Xie Yinlong Y Tap Julien J Lepage Patricia P Bertalan Marcelo M Batto Jean-Michel JM Hansen Torben T Le Paslier Denis D Linneberg Allan A Nielsen H Bjørn HB Pelletier Eric E Renault Pierre P Sicheritz-Ponten Thomas T Turner Keith K Zhu Hongmei H Yu Chang C Li Shengting S Jian Min M Zhou Yan Y Li Yingrui Y Zhang Xiuqing X Li Songgang S Qin Nan N Yang Huanming H Wang Jian J Brunak Søren S Doré Joel J Guarner Francisco F Kristiansen Karsten K Pedersen Oluf O Parkhill Julian J Weissenbach Jean J Bork Peer P Ehrlich S Dusko SD Wang Jun J

Nature 20100301 7285

To understand the impact of gut microbes on human health and well-being it is crucial to assess their genetic potential. Here we describe the Illumina-based metagenomic sequencing, assembly and characterization of 3.3 million non-redundant microbial genes, derived from 576.7 gigabases of sequence, from faecal samples of 124 European individuals. The gene set, approximately 150 times larger than the human gene complement, contains an overwhelming majority of the prevalent (more frequent) microbia ...[more]

PMID: 20203603

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Project description: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.

Project description:BACKGROUND: Microbial life dominates the earth, but many species are difficult or even impossible to study under laboratory conditions. Sequencing DNA directly from the environment, a technique commonly referred to as metagenomics, is an important tool for cataloging microbial life. This culture-independent approach involves collecting samples that include microbes in them, extracting DNA from the samples, and sequencing the DNA. A sample may contain many different microorganisms, macroorganisms, and even free-floating environmental DNA. A fundamental challenge in metagenomics has been estimating the abundance of organisms in a sample based on the frequency with which the organism's DNA was observed in reads generated via DNA sequencing. METHODOLOGY/PRINCIPAL FINDINGS: We created mixtures of ten microbial species for which genome sequences are known. Each mixture contained an equal number of cells of each species. We then extracted DNA from the mixtures, sequenced the DNA, and measured the frequency with which genomic regions from each organism was observed in the sequenced DNA. We found that the observed frequency of reads mapping to each organism did not reflect the equal numbers of cells that were known to be included in each mixture. The relative organism abundances varied significantly depending on the DNA extraction and sequencing protocol utilized. CONCLUSIONS/SIGNIFICANCE: We describe a new data resource for measuring the accuracy of metagenomic binning methods, created by in vitro-simulation of a metagenomic community. Our in vitro simulation can be used to complement previous in silico benchmark studies. In constructing a synthetic community and sequencing its metagenome, we encountered several sources of observation bias that likely affect most metagenomic experiments to date and present challenges for comparative metagenomic studies. DNA preparation methods have a particularly profound effect in our study, implying that samples prepared with different protocols are not suitable for comparative metagenomics.

Dataset Information

A human gut microbial gene catalogue established by metagenomic sequencing.

Publications

A human gut microbial gene catalogue established by metagenomic sequencing.

Similar Datasets

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