News in livestock research - use of Omics-technologies to study the microbiota in the gastrointestinal tract of farm animals

Abstract

Technical progress in the field of next-generation sequencing, mass spectrometry and bioinformatics facilitates the study of highly complex biological samples such as taxonomic and functional characterization of microbial communities that virtually colonize all present ecological niches. Compared to the structural information obtained by metagenomic analyses, metaproteomic approaches provide, in addition, functional data about the investigated microbiota. In general, integration of the main Omics-technologies (genomics, transcriptomics, proteomics and metabolomics) in live science promises highly detailed information about the specific research object and helps to understand molecular changes in response to internal and external environmental factors. The microbial communities settled in the mammalian gastrointestinal tract are essential for the host metabolism and have a major impact on its physiology and health. The microbiotas of livestock like chicken, pig and ruminants are becoming a focus of interest for veterinaries, animal nutritionists and microbiologists. While pig is more often used as an animal model for human-related studies, the rumen microbiota harbors a diversity of enzymes converting complex carbohydrates into monomers which bears high potential for biotechnological applications. This review will provide a general overview about the recent Omics-based research of the microbiota in livestock including its major findings. Differences concerning the results of pre-Omics-approaches in livestock as well as the perspectives of this relatively new Omics-platform will be highlighted.

Keywords: Gastrointestinal tract; Livestock; Microbiota; Omics.

Fig. 1

Workflow of possible methods to study the structure and function of the microbiota in farm animals.

Fig. 2

Phylogenetic distribution of bacterial families in different GIT sections of chickens, pigs and cows. Chicken's crop, jejunum and caecum data arise from the analysis of V1–V3 16S rRNA region as performed by Videnska et al. , Stanley et al. and Sergeant et al. , respectively. All pig's data arise from the study performed by Looft et al. on V1–V3 16S rRNA region. Cow's data derive from the work performed by Wu et al. on V3–V5 16S rRNA region.

Fig. 3

Abundance of glycoside hydrolase (GH)-families in metagenomes of bovine rumen and chicken caecum. The percentage of each GH-group relative to the total number of GH-families identified in each metagenomic dataset is shown grouped according to major activity . Brulc et al. [Angus steers] — Pyrosequencing data (shotgun sequencing using GS20 from 454 Life Science) of 4 metagenomic samples; the mean of three fiber-adherent and one pooled liquid sample is shown. The average size of the metagenomes was 0.026 Gb. The samples were obtained from three 5 year old Angus Simmental Cross steers maintained on grass-legume hay. Hess et al. [Guernsey cows] — Massively parallel shotgun sequencing using Illumina GAIIx and HiSeq 2000 was applied on metagenomic samples of the fiber-adherent rumen microbiota of two Guernsey cows kept on a mixed diet containing 60% fiber. The total metagenome size was 268 Gb. Wang et al. [Jersey cows] — All samples were pooled at equal amount and pyrosequenced with the Roche GS FLX Titanium system. Average size of metagenomes was 0.49 Gb. Rumen digesta samples were collected from two Jersey cows fed mainly Timothy grass hay ad libitum. Sergeant et al. [Ross broilers] — Cecal samples were collected from 10 Ross broilers consuming a wheat based diet with 5% maize which contained ionophores but no antibiotics. Sequencing was carried out on the Illumina Miseq 2000 system.