Do gut microbial communities differ in pediatric IBS and health?

Abstract

h uman gastrointestinal microbial communities are recognized as important determinants of the host health and disease status. we have recently examined the distal gut microbiota of two groups of children: healthy adolescents and those diagnosed with diarrhea-predominant irritable bowel syndrome (ibs). we have revealed the common core of phylotypes shared among all children, identified genera differentially abundant between two groups and surveyed possible relationships among intestinal microbial genera and phylotypes. in this article we explored the use of supervised and unsupervised ordination and classification methods to separate and classify child fecal samples based on their quantitative microbial profile. we observed sample separation according to the participant health status, and this separation could often be attributed to the abundance levels of several specific microbial genera. we also extended our original correlation network analysis of the relative abundances of bacterial genera across samples and determined possible association networks separately for healthy and ibs groups. interestingly, the number of significant genus abundance associations was drastically lower among the ibs samples, which can potentially be attributed to the existence of multiple routes to microbiota disbalance in ibs or to the loss of microbial interactions during ibs development. IntroductionThe human gut is rich in microbes, harboring approximately 100 trillion do gut microbial communities differ in pediatric ibs and health? Microbes participate in carbohydrate degradation, modulation of dietary lipid uptake, production of certain vitamins and short-chain fatty acids, development and proper stimulation of the immune system, modulation of gut motility and protection of the host from pathogens.3 At the same time, microbiota dysbiosis has been linked to a number of human disorders including irritable bowel syndrome (IBS), inflammatory bowel disease, obesity and colon cancer.3 Among these, IBS is a functional bowel syndrome that has varied symptoms with no sign of visible mucosal damage or intestinal inflammation. Proposed causes of IBS include altered motor function, abnormal gas handling, acute bacterial gastroenteritis, food intolerance, increased intestinal permeability and gut motility, altered intestinal immune function, as well as bacterial overgrowth of small intestine (SIBO). 4,5 While none of the potential causes has yet emerged as the established determinant of IBS development, many of the symptoms of IBS are consistent with SIBO,6 and the prevalence of SIBO was found to be higher in many previous investigations of IBS patients. [7][8][9] While the SIBO model of IBS development implicates intestinal microbiota as a major cause of this syndrome, the available studies of gut microbiota in IBS do not show a strong consensus as to which microbiota members might be responsible for the condition and whether specific ©2013 Landes Bioscience. Do not distribute 348Gut Microbes Volume 4 Issue 4Bacteroides, Clostridium, Dorea...

The networks of human gut microbe–metabolite associations are different between health and irritable bowel syndrome

“…Although many strong associations were observed in healthy samples, such interactions were significantly weaker in IBS, with none reaching the level of statistical significance (see Figure 2). A concordant loss of microbemicrobe relative abundance associations in IBS was previously revealed (Shankar et al, 2013). We offer several possible explanations of these findings.…”

“…Fecal microbe-metabolite associations in health and IBS V Shankar et al (Shankar et al, 2013). To evaluate if both principal components analyses produced congruent sample distributions, Procrustes analysis, which seeks to superimpose, align and scale multiple graphical structures (Rohlf and Slice, 1990), was performed and revealed a strong congruency of sample separations based on metabolite and microbial signatures, respectively (Po0.001, Figure 1b).…”

“…We previously reported that microbemicrobe interactions were severely limited in IBS samples (Shankar et al, 2013), therefore, metabolite-microbe associations were calculated separately for the kIBS and kHLT sample sets. Although many strong associations were discovered in the kHLT data set (Figure 2a), associations were weak in the kIBS sample cohort (Figure 2b).…”

Application of multivariate statistical techniques in microbial ecology

“…While it is typical to show PC1-vs-PC2 and/or PC2-vs-PC3 scatter plots, any two or three principal components can be chosen for visualization. Examples of PCA use in microbial ecological studies are provided by (Hong et al , 2010), (Ringel-Kulka et al , 2013), and (Shankar et al , 2013). …”

“…These technologies provided foundation to many groundbreaking advances in our understanding of microbial community organization, function, and interactions within a community and with other organisms. Examples include the assessment of marine microbiota response to the Deepwater Horizon oil spill (Mason et al , 2014), functional analysis of microbiomes in different soils (Fierer et al , 2012), identification of enterotypes in the human intestinal microbiota (Arumugam et al , 2011), detection of seasonal fluctuations in oceanic bacterioplankton (Gilbert et al , 2012), and discovery of the loss of gut microbial interactions in human gastrointestinal diseases (Shankar et al , 2013; Shankar et al , 2015). …”