Paper intensive reading (三十三)：Use of Metatranscriptomics in Microbiome Research

Title: Use of Metatranscriptomics in Microbiome Research

Bioinformatics and Biology Insights, 20 Apr 2016

stavros Bashiardes, gili Zilberman-schapira and Eran Elinav 

Department of Immunology, Weizmann Institute of Science, Rehovot, Israel.

Abstract

The human intestinal microbiome is a microbial ecosystem that expresses as many as 100 times more genes than the human host, thereby constituting an important component of the human holobiome(人类全基因组), which contributes to multiple health and disease processes. As most commensal species are difficult or impossible to culture, genomic characterization of microbiome composition and function, under various environmental conditions, comprises a central tool in understanding its roles in health and disease. The first decade of microbiome research was mainly characterized by usage of DNA sequencing-based 16S rDNA and shotgun metagenome sequencing, allowing for the elucidation of microbial composition and genome structure. Technological advances in RNA-seq have recently provided us with an ability to gain insight into the genes that are actively expressed in complex bacterial communities, enabling the elucidation of the functional changes that dictate the microbiome functions at given contexts, its interactions with the host, and functional alterations that accompany the conversion of a healthy microbiome toward a disease-driving configuration. Here, we highlight some of the key metatranscriptomics strategies that are implemented to determine microbiota gene expression and its regulation and discuss the advantages and potential challenges associated with these approaches.

Outline

1. The Microbiome

2. Characterization of the Microbiome

3. Characterization of the Metatranscriptome

4. Isolation and Processing of Microbiome mRNA

5. Computational Analysis of Metatranscriptomics Data

6. Utilization of Metatranscriptomics in Health and Disease

6.1 Assessment of microbial activity

6.2 Assessment of microbiome–immune interactions

6.3 Studying microbiome antisense RNA

6.4 Studying microbiome small noncoding RNAs

7.Limitations and Challenges of Metatranscriptomics Analysis

8. Conclusion

正文摘录

1. The Microbiome
    基因组原核基因库上，该库远远超过了人类真核基因组
    微生物：细菌，真菌，病毒   目前研究主要研究细菌
    The Nobel laureate Joshua Lederberg first termed microbiome as the combination of commensal, symbiotic, and pathogenic microorganisms that colonize the human body.1 This microbial ecosystem is composed of bacteria, fungi, and viruses, with the predominant focus of study today being on the bacterial component of this community.

    本篇review也集中在细菌群
    In this review, the term core microbiota has been used to describe commonly observed bacterial phyla. 

    5. Computational Analysis of Metatranscriptomics Data
    Another important issue in the analysis and inference of biological information from metatranscriptomics data is combining the analysis of the RNA-seq data and the whole DNA data, ie metagenomics. Analyzing these two types of data simultaneously for a sample enables us to conclude the actual expressed genes vs the potentially existing genes.
    
    7.Limitations and Challenges of Metatranscriptomics Analysis
    As such, pipelines integrating metagenomics, metatranscriptomics, metabolomics, and metaproteomics datasets may potentially enable to gain a holistic view of microbiome composition and function at multiple layers. 

    8. Conclusion
    宏转录组的优势
    Metatranscriptomics holds great potential to uncover biological information that may be otherwise obscured by other genomic methodologies. It provides an accurate snapshot, at a given moment in time and under specific conditions, of the actual gene expression profile rather than its potential, as inferred from DNA-based shotgun metagenomic sequencing.

    While metatranscriptomics microbiome analysis holds promise in enhancing our understanding of the complex community behavior of the microbiome, several challenges need to be met in order to enhance the reproducibility and general applicability of metatranscriptome analysis. Despite these challenges, metatranscriptomics analysis of the microbiome may be of great value in moving from a descriptive microbiome facet to a deeper understanding of causality in microbial contribution to homeostasis and disease susceptibility. As such, integration of metatranscriptomics into microbiome research may enable to gain better understanding of its diverse roles in mammalian physiology and integrate these data into the clinical world.