Evidence map›Paper›PMID 27127406›Full record

ReviewBioinformatics and biology insights2016

Use of Metatranscriptomics in Microbiome Research.

Stavros Bashiardes, Gili Zilberman-Schapira, Eran Elinav

Abstract readReview
In one paragraph

Review in Bioinformatics and biology insights, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 191 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
191citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

191 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  13. A Brief Review of Microbial Omics: Methods and Perspectives.Methods in molecular biology (Clifton, N.J.) · 2026
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131 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Stavros BashiardesDepartment of Immunology, Weizmann Institute of Science, Rehovot, Israel.
Gili Zilberman-SchapiraDepartment of Immunology, Weizmann Institute of Science, Rehovot, Israel.
Eran ElinavDepartment of Immunology, Weizmann Institute of Science, Rehovot, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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, 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.

Indexed as

bacteriagutmicrobiomenext generation sequencingRNA-Seqtranscriptome

Identifiers

PMID27127406
PMCPMC4839964

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.