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Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Published on: October 15, 2019

A comprehensive metatranscriptome analysis pipeline and its validation using human small intestine microbiota

Milkha M Leimena¹, Javier Ramiro-Garcia, Mark Davids

¹TI Food and Nutrition (TIFN), P,O, Box 557, 6700 AN, Wageningen, The Netherlands.

|August 7, 2013

Summary

Researchers developed a reliable bioinformatic pipeline for analyzing RNA sequencing (RNA-seq) data from complex microbial communities. This pipeline accurately identifies microbial functions and taxonomy, aiding in understanding ecosystem dynamics.

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Published on: October 28, 2020

Area of Science:

Microbial Ecology
Bioinformatics
Genomics

Background:

Next-generation sequencing (NGS) enables metatranscriptome analysis of microbial ecosystems via RNA sequencing (RNA-seq).
RNA-seq generates complex datasets requiring robust bioinformatic pipelines for interpretation.
This study addresses the need for a reliable pipeline for metatranscriptome data analysis.

Purpose of the Study:

To develop and validate a comprehensive bioinformatic pipeline for metatranscriptome analysis.
To assess the pipeline's effectiveness using Illumina RNA-seq data from human small intestine microbiota.

Main Methods:

Development of a bioinformatic pipeline for metatranscriptome data processing.
Validation using Illumina RNA-seq datasets from human small intestine microbiota.
Comparison of single-read versus paired-end sequencing for metatranscriptome analysis.

Main Results:

The pipeline effectively removed rRNA sequences and assigned functions and taxonomy to mRNA reads.
Phylogenetic analysis showed congruency with 16S rDNA and rRNA pyrosequencing, confirming community composition and activity.
Paired-end sequencing did not offer advantages over single-read sequencing for functional or phylogenetic insights.

Conclusions:

A reliable pipeline for metatranscriptome data analysis using RNA-seq was successfully developed and validated.
The pipeline is versatile and applicable to bacterial metatranscriptome analysis across various microbial niches.
The approach facilitates the analysis of microbial activity and the unraveling of syntrophic interactions.