Pulse Brain · Growing Health Evidence Index
Tier 4 — Narrative / commentaryPeer-reviewed

A Review of the Rumen Microbiota and the Different Molecular Techniques Used to Identify Microorganisms Found in the Rumen Fluid of Ruminants.

Silva ÉBRD, Silva JARD, Silva WCD, Belo TS, Sousa CEL, Santos MRPD, Neves KAL, Rodrigues TCGC, Camargo-Júnior RNC, Lourenço-Júnior JB.

Animals (Basel) · 2024

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Summary

This narrative review synthesises current knowledge of rumen microbiota composition in ruminant livestock and examines the molecular techniques employed to identify and characterise these microbial communities. The authors appraise both traditional and modern approaches, including 16S rRNA sequencing and metagenomic methods, to provide guidance on methodological selection for rumen microbiological research. The review contributes to understanding how technical choices in microbiota assessment affect research outcomes and comparative findings across studies.

UK applicability

The methodological overview is directly applicable to UK ruminant research, as the techniques reviewed are internationally standardised. However, the specific microbial profiles may vary depending on UK forage types, dietary management, and climate conditions, requiring contextual adaptation of findings.

Key measures

Rumen microbiota composition, molecular identification methods (culture-dependent and culture-independent techniques), microbial diversity metrics

Outcomes reported

The study reviewed molecular techniques used to characterise and identify microorganisms present in rumen fluid across ruminant species. It synthesised evidence on the diversity of rumen microbial communities and the methodological approaches available for their detection and classification.

Theme
Farming systems, soils & land use
Subject
Ruminant microbiology and digestive physiology
Study type
Narrative Review
Study design
Narrative review
Source type
Peer-reviewed study
Status
Published
Geography
Brazil
System type
Mixed livestock
DOI
10.3390/ani14101448
Catalogue ID
NRmo9zxr64-04m

Topic tags

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