Network analysis of temporal functionalities of the gut induced by perturbations in new-born piglets

• Published in: BMC genomics 2015-07, Vol.16 (1), p.556-556, Article 556
• Main Authors: Benis, Nirupama, Schokker, Dirkjan, Suarez-Diez, Maria, Martins Dos Santos, Vitor A P, Smidt, Hauke, Smits, Mari A
• Format: Article
• Language: English
• Subjects: adaptive immunity; Analysis; Animals; Animals, Newborn; antibiotic exposure; Bacteria - genetics; Bacteria - isolation & purification; early-life; gastrointestinal-tract; Gene Regulatory Networks; Genes; Growth; Health aspects; Host-Pathogen Interactions - genetics; immune-system; Information management; intestinal microbiota; Intestines - microbiology; microarray experiments; Microbiota; Oligonucleotide Array Sequence Analysis; Physiological aspects; protein-interaction network; resistant starch; RNA, Ribosomal, 16S - chemistry; RNA, Ribosomal, 16S - genetics; ruminococcus-bromii; Swine - microbiology; Transcriptome
• ISSN: 1471-2164; 1471-2164
• DOI: 10.1186/s12864-015-1733-8

Evidence is accumulating that perturbation of early life microbial colonization of the gut induces long-lasting adverse health effects in individuals. Understanding the mechanisms behind these effects will facilitate modulation of intestinal health. The objective of this study was to identify biological processes involved in these long lasting effects and the (molecular) factors that regulate them. We used an antibiotic and the same antibiotic in combination with stress on piglets as an early life perturbation. Then we used host gene expression data from the gut (jejunum) tissue and community-scale analysis of gut microbiota from the same location of the gut, at three different time-points to gauge the reaction to the perturbation. We analysed the data by a new combination of existing tools. First, we analysed the data in two dimensions, treatment and time, with quadratic regression analysis. Then we applied network-based data integration approaches to find correlations between host gene expression and the resident microbial species. The use of a new combination of data analysis tools allowed us to identify significant long-lasting differences in jejunal gene expression patterns resulting from the early life perturbations. In addition, we were able to identify potential key gene regulators (hubs) for these long-lasting effects. Furthermore, data integration also showed that there are a handful of bacterial groups that were associated with temporal changes in gene expression. The applied systems-biology approach allowed us to take the first steps in unravelling biological processes involved in long lasting effects in the gut due to early life perturbations. The observed data are consistent with the hypothesis that these long lasting effects are due to differences in the programming of the gut immune system as induced by the temporary early life changes in the composition and/or diversity of microbiota in the gut.