Dataset Information

Bacterial Diversity Profiling around the Orca Seamount in the Bransfield Strait, Antarctica, Based on 16S rRNA Gene Amplicon Sequences.

ABSTRACT: Hydrothermal vent activity is often associated with submarine volcanism. Here, we investigated the presence of microorganisms related to hydrothermal activity in the Orca seamount. Data profiling of the 16S rRNA gene amplicon sequences revealed a diversity pattern dominated mainly by the phyla Proteobacteria, Acidobacteria, Planctomycetes, and Bacteroidetes.

SUBMITTER: Serrano W

PROVIDER: S-EPMC8407734 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Bacterial Diversity Profiling around the Orca Seamount in the Bransfield Strait, Antarctica, Based on 16S rRNA Gene Amplicon Sequences.

Serrano Wilbert W Olaechea Raul M RM Cerpa Luis L Herrera Jose J Indacochea Aldo A

Microbiology resource announcements 20210107 1

Hydrothermal vent activity is often associated with submarine volcanism. Here, we investigated the presence of microorganisms related to hydrothermal activity in the Orca seamount. Data profiling of the 16S rRNA gene amplicon sequences revealed a diversity pattern dominated mainly by the phyla Proteobacteria, Acidobacteria, Planctomycetes, and Bacteroidetes. ...[more]

PMID: 33414311

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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.

Project description:Metagenomic sequencing of bacterial samples has become the gold standard for profiling microbial populations, but 16S rRNA profiling remains widely used due to advantages in sample throughput, cost, and sensitivity even though the approach is hampered by primer bias and lack of specificity. We hypothesized that a hybrid approach, that combined targeted PCR amplification with high-throughput sequencing of multiple regions of the genome, would capture many of the advantages of both approaches. We developed a method that identifies and quantifies members of bacterial communities through simultaneous analysis of multiple variable regions of the bacterial 16S rRNA gene. The method combines high-throughput microfluidics for PCR amplification, short read DNA sequencing, and a custom algorithm named MVRSION (Multiple 16S Variable Region Species-Level IdentificatiON) for optimizing taxonomic assignment. MVRSION performance was compared to single variable region analyses (V3 or V4) of five synthetic mixtures of human gut bacterial strains using existing software (QIIME), and the results of community profiling by shotgun sequencing (COPRO-Seq) of fecal DNA samples collected from gnotobiotic mice colonized with a defined, phylogenetically diverse consortium of human gut bacterial strains. Positive predictive values for MVRSION ranged from 65%-91% versus 44%-61% for single region QIIME analyses (p < .01, p < .001), while the abundance estimate r2 for MVRSION compared to COPRO-Seq was 0.77 vs. 0.46 and 0.45 for V3-QIIME and V4-QIIME, respectively. MVRSION represents a generally applicable tool for taxonomic classification that is superior to single-region 16S rRNA methods, resource efficient, highly scalable for assessing the microbial composition of up to thousands of samples concurrently, with multiple applications ranging from whole community profiling to targeted tracking of organisms of interest in diverse habitats as a function of specified variables/perturbations.

Dataset Information

Bacterial Diversity Profiling around the Orca Seamount in the Bransfield Strait, Antarctica, Based on 16S rRNA Gene Amplicon Sequences.

Publications

Bacterial Diversity Profiling around the Orca Seamount in the Bransfield Strait, Antarctica, Based on 16S rRNA Gene Amplicon Sequences.

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