Dataset Information

LogMPIE, pan-India profiling of the human gut microbiome using 16S rRNA sequencing.

ABSTRACT: The "Landscape Of Gut Microbiome - Pan-India Exploration", or LogMPIE study, is the first large-scale, nationwide record of the Indian gut microbiome. The primary objective of the study was to identify and map the Indian gut microbiome baseline. This observational study was conducted across 14 geographical locations in India. Enrolled subjects were uniformly distributed across geographies (north, east, west and south) and body mass index (obese and non-obese). Furthermore, factors influencing the microbiome, such as age and physical activity, were also considered in the study design. The LogMPIE study recorded data from 1004 eligible subjects and reported 993 unique microorganisms across the Indian microbiome diaspora. The data not only map the Indian gut microbiome baseline but also function as a useful resource to study, analyse and identify signatures characterizing the physiological dispositions of the subjects. Furthermore, they provide insight into the unique features describing the Indian microbiome. The data are open and may be accessed from the European Nucleotide Archive (ENA) portal of the European Bioinformatics Institute (https://www.ebi.ac.uk/ena/data/view/PRJEB25642).

SUBMITTER: Dubey AK

PROVIDER: S-EPMC6207063 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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LogMPIE, pan-India profiling of the human gut microbiome using 16S rRNA sequencing.

Dubey Ashok Kumar AK Uppadhyaya Niyati N Nilawe Pravin P Chauhan Neeraj N Kumar Santosh S Gupta Urmila Anurag UA Bhaduri Anirban A

Scientific data 20181030

The "Landscape Of Gut Microbiome - Pan-India Exploration", or LogMPIE study, is the first large-scale, nationwide record of the Indian gut microbiome. The primary objective of the study was to identify and map the Indian gut microbiome baseline. This observational study was conducted across 14 geographical locations in India. Enrolled subjects were uniformly distributed across geographies (north, east, west and south) and body mass index (obese and non-obese). Furthermore, factors influencing th ...[more]

PMID: 30375992

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Project description:The 16S rRNA gene works as a rapid and effective marker for the identification of microorganisms in complex communities; hence, a huge number of microbiomes have been surveyed by 16S amplicon-based sequencing. The resolution of the 16S rRNA gene is always considered only at the genus level; however, it has not been verified on a wide range of microbes yet. To fully explore the ability and potential of the 16S rRNA gene in microbial profiling, here, we propose Qscore, a comprehensive method to evaluate the performance of amplicons by integrating the amplification rate, multitier taxonomic annotation, sequence type, and length. Our in silico assessment by a "global view" of 35,889 microbe species across multiple reference databases summarizes the optimal sequencing strategy for 16S short reads. On the other hand, since microbes are unevenly distributed according to their habitats, we also provide the recommended configuration for 16 typical ecosystems based on the Qscores of 157,390 microbiomes in the Microbiome Search Engine (MSE). Detailed data simulation further proves that the 16S amplicons produced with Qscore-suggested parameters exhibit high precision in microbiome profiling, which is close to that of shotgun metagenomes under CAMI metrics. Therefore, by reconsidering the precision of 16S-based microbiome profiling, our work not only enables the high-quality reusability of massive sequence legacy that has already been produced but is also significant for guiding microbiome studies in the future. We have implemented the Qscore as an online service at http://qscore.single-cell.cn to parse the recommended sequencing strategy for specific habitats or expected microbial structures. IMPORTANCE 16S rRNA has long been used as a biomarker to identify distinct microbes from complex communities. However, due to the influence of the amplification region, sequencing type, sequence processing, and reference database, the accuracy of 16S rRNA has not been fully verified on a global range. More importantly, the microbial composition of different habitats varies greatly, and it is necessary to adopt different strategies according to the corresponding target microbes to achieve optimal analytical performance. Here, we developed Qscore, which evaluates the comprehensive performance of 16S amplicons from multiple perspectives, thus providing the best sequencing strategies for common ecological environments by using big data.

Dataset Information

LogMPIE, pan-India profiling of the human gut microbiome using 16S rRNA sequencing.

Publications

LogMPIE, pan-India profiling of the human gut microbiome using 16S rRNA sequencing.

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