IgA production in the large intestine is modulated by a different mechanism than in the small intestine: Bacteroides acidifaciens promotes IgA production in the large intestine by inducing germinal center formation and increasing the number of IgA+ B cells
“…For example, Bacteroides alleviates obesityassociated metabolic syndromes (Ridaura et al, 2013). Certain species of Bacteroides such as B. acidifaciens can promote IgA production (Yanagibashi et al, 2012). In our study, the level of Bacteroides was significantly enhanced in mice feeding with GpS or NGS.…”
“…For example, Bacteroides alleviates obesityassociated metabolic syndromes (Ridaura et al, 2013). Certain species of Bacteroides such as B. acidifaciens can promote IgA production (Yanagibashi et al, 2012). In our study, the level of Bacteroides was significantly enhanced in mice feeding with GpS or NGS.…”
“…Because obesity is a risk factor for CDI (21), it is possible that B. uniformis also provides protection against infection by C. difficile . B. acidifaciens was demonstrated to increase IgA + B cells in the large intestine (22), which may also limit the growth of gastrointestinal pathogens such as C. difficile . Overall, this shift in community structure is thought to be associated with a change in colonization resistance.…”
Antibiotic usage is the most commonly cited risk factor for hospital-acquired Clostridium difficile infections (CDI). The increased risk is due to disruption of the indigenous microbiome and a subsequent decrease in colonization resistance by the perturbed bacterial community; however, the specific changes in the microbiome that lead to increased risk are poorly understood. We developed statistical models that incorporated microbiome data with clinical and demographic data to better understand why individuals develop CDI. The 16S rRNA genes were sequenced from the feces of 338 individuals, including cases, diarrheal controls, and nondiarrheal controls. We modeled CDI and diarrheal status using multiple clinical variables, including age, antibiotic use, antacid use, and other known risk factors using logit regression. This base model was compared to models that incorporated microbiome data, using diversity metrics, community types, or specific bacterial populations, to identify characteristics of the microbiome associated with CDI susceptibility or resistance. The addition of microbiome data significantly improved our ability to distinguish CDI status when comparing cases or diarrheal controls to nondiarrheal controls. However, only when we assigned samples to community types was it possible to differentiate cases from diarrheal controls. Several bacterial species within the Ruminococcaceae, Lachnospiraceae, Bacteroides, and Porphyromonadaceae were largely absent in cases and highly associated with nondiarrheal controls. The improved discriminatory ability of our microbiome-based models confirms the theory that factors affecting the microbiome influence CDI.
“…In the colon, there were no B. acidifaciens detected in NOD mice and fewer R. gnavus. B. acidifaciens induces production of secretory IgA in the gut (Yanagibashi et al, 2013), while R. gnavus has been shown to make antiinflammatory bile acid (Lee et al, 2013). Despite the differences in microbial profiles, a causative role for the microbiota in T1D progression in NOD mice has not yet been established.…”
Accumulating evidence supports that the intestinal microbiome is involved in Type 1 diabetes (T1D) pathogenesis through the gut-pancreas nexus. Our aim was to determine whether the intestinal microbiota in the non-obese diabetic (NOD) mouse model played a role in T1D through the gut. To examine the effect of the intestinal microbiota on T1D onset, we manipulated gut microbes by: (1) the fecal transplantation between non-obese diabetic (NOD) and resistant (NOR) mice and (2) the oral antibiotic and probiotic treatment of NOD mice. We monitored diabetes onset, quantified CD4+T cells in the Peyer's patches, profiled the microbiome and measured fecal short-chain fatty acids (SCFA). The gut microbiota from NOD mice harbored more pathobionts and fewer beneficial microbes in comparison with NOR mice. Fecal transplantation of NOD microbes induced insulitis in NOR hosts suggesting that the NOD microbiome is diabetogenic. Moreover, antibiotic exposure accelerated diabetes onset in NOD mice accompanied by increased T-helper type 1 (Th1) and reduced Th17 cells in the intestinal lymphoid tissues. The diabetogenic microbiome was characterized by a metagenome altered in several metabolic gene clusters. Furthermore, diabetes susceptibility correlated with reduced fecal SCFAs. In an attempt to correct the diabetogenic microbiome, we administered VLS#3 probiotics to NOD mice but found that VSL#3 colonized the intestine poorly and did not delay diabetes. We conclude that NOD mice harbor gut microbes that induce diabetes and that their diabetogenic microbiome can be amplified early in life through antibiotic exposure. Protective microbes like VSL#3 are insufficient to overcome the effects of a diabetogenic microbiome.
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