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Shotgun metagenomic sequencing based microbial diversity assessment of Lasundra hot spring, India.

ABSTRACT: This is the first report on the metagenomic approach for unveiling the microbial diversity of Lasundra hot spring, Gujarat State, India. High-throughput sequencing of community DNA was performed on an Ion Torrent PGM platform. Metagenome consisted of 606,867 sequences represent 98,567,305 bps size with an average length of 162 bps and 46% G + C content. Metagenome sequence information is available at EBI under EBI Metagenomic database with accession no. ERP009313. MG-RAST assisted community analysis revealed that 99.21% sequences were bacterial origin, 0.43% was fit to eukaryotes and 0.11% belongs to archaea. A total of 29 bacterial, 20 eukaryotic and 4 archaeal phyla were detected. Abundant genera were Bacillus (86.7%), Geobacillus (2.4%), Paenibacillus (1.0%), Clostridium (0.7%) and Listeria (0.5%), that represent 91.52% in metagenome. In functional analysis, Cluster of Orthologous Group (COG) based annotation revealed that 45.4% was metabolism connected and 19.6% falls in poorly characterized group. Subsystem based annotation approach suggests that the 14.0% was carbohydrates, 7.0% was protein metabolism and 3.0% genes for various stress responses together with the versatile presence of commercially useful traits.

SUBMITTER: Mangrola AV

PROVIDER: S-EPMC4536006 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

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Shotgun metagenomic sequencing based microbial diversity assessment of Lasundra hot spring, India.

Mangrola Amit V AV Dudhagara Pravin P Koringa Prakash P Joshi C G CG Patel Rajesh K RK

Genomics data 20150324

This is the first report on the metagenomic approach for unveiling the microbial diversity of Lasundra hot spring, Gujarat State, India. High-throughput sequencing of community DNA was performed on an Ion Torrent PGM platform. Metagenome consisted of 606,867 sequences represent 98,567,305 bps size with an average length of 162 bps and 46% G + C content. Metagenome sequence information is available at EBI under EBI Metagenomic database with accession no. ERP009313. MG-RAST assisted community anal ...[more]

PMID: 26484181

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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:Biogeography (body site) is known to be one of the main factors influencing the composition of the skin microbial community. However, site-associated microbial variability at a fine-scale level was not well-characterized since there was a lack of high-resolution recognition of facial microbiota across kingdoms by shotgun metagenomic sequencing. To investigate the explicit microbial variance in the human face, 822 shotgun metagenomic sequencing data from Han Chinese recently published by our group, in combination with 97 North American samples from NIH Human Microbiome Project (HMP), were reassessed. Metagenomic profiling of bacteria, fungi, and bacteriophages, as well as enriched function modules from three facial sites (forehead, cheek, and the back of the nose), was analyzed. The results revealed that skin microbial features were more alike in the forehead and cheek while varied from the back of the nose in terms of taxonomy and functionality. Analysis based on biogeographic theories suggested that neutral drift with niche selection from the host could possibly give rise to the variations. Of note, the abundance of porphyrin-producing species, i.e., Cutibacterium acnes, Cutibacterium avidum, Cutibacterium granulosum, and Cutibacterium namnetense, was all the highest in the back of the nose compared with the forehead/cheek, which was consistent with the highest porphyrin level on the nose in our population. Sequentially, the site-associated microbiome variance was confirmed in American populations; however, it was not entirely consistent. Furthermore, our data revealed correlation patterns between Propionibacterium acnes bacteriophages with genus Cutibacterium at different facial sites in both populations; however, C. acnes exhibited a distinct correlation with P. acnes bacteriophages in Americans/Chinese. Taken together, in this study, we explored the fine-scale facial site-associated changes in the skin microbiome and provided insight into the ecological processes underlying facial microbial variations.

Dataset Information

Shotgun metagenomic sequencing based microbial diversity assessment of Lasundra hot spring, India.

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Shotgun metagenomic sequencing based microbial diversity assessment of Lasundra hot spring, India.

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