Analysis of strain, sex, and diet-dependent modulation of gut microbiota reveals candidate keystone organisms driving microbial diversity in response to American and ketogenic diets.

BACKGROUND: The gut microbiota is modulated by a combination of diet, host genetics, and sex effects. The magnitude of these effects and interactions among them is important to understanding inter-individual variability in gut microbiota. In a previous study, mouse strain-specific responses to American and ketogenic diets were observed along with several QTLs for metabolic traits. In the current study, we searched for genetic variants underlying differences in the gut microbiota in response to American and ketogenic diets, which are high in fat and vary in carbohydrate composition, between C57BL/6 J (B6) and FVB/NJ (FVB) mouse strains. RESULTS: Genetic mapping of microbial features revealed 18 loci under the QTL model (i.e., marginal effects that are not specific to diet or sex), 12 loci under the QTL by diet model, and 1 locus under the QTL by sex model. Multiple metabolic and microbial features map to the distal part of Chr 1 and Chr 16 along with eigenvectors extracted from principal coordinate analysis of measures of ß-diversity. Bilophila, Ruminiclostridium 9, and Rikenella (Chr 1) were identified as sex- and diet-independent QTL candidate keystone organisms, and Parabacteroides (Chr 16) was identified as a diet-specific, candidate keystone organism in confirmatory factor analyses of traits mapping to these regions. For many microbial features, irrespective of which QTL model was used, diet or the interaction between diet and a genotype were the strongest predictors of the abundance of each microbial trait. Sex, while important to the analyses, was not as strong of a predictor for microbial abundances. CONCLUSIONS: These results demonstrate that sex, diet, and genetic background have different magnitudes of effects on inter-individual differences in gut microbiota. Therefore, Precision Nutrition through the integration of genetic variation, microbiota, and sex affecting microbiota variation will be important to predict response to diets varying in carbohydrate composition. Video Abstract.

Analysis of strain, sex, and diet-dependent modulation of gut microbiota reveals candidate keystone organisms driving microbial diversity in response to American and ketogenic diets.

Background The gut microbiota is modulated by a combination of diet, host genetics, and sex effects. The magnitude of these effects and interactions among them is important to understanding inter-individual variability in gut microbiota. In a previous study, mouse strain-specific responses to American and ketogenic diets were observed along with several QTL for metabolic traits. In the current study, we searched for genetic variants underlying differences in the gut microbiota in response to American and ketogenic diets, which are high in fat and vary in carbohydrate composition, between C57BL/6J (B6) and FVB/NJ (FVB) mouse strains. Results Genetic mapping of microbial features revealed 18 loci under the QTL model (i.e., marginal effects that are not specific to diet or sex), 12 loci under the QTL by diet model, and 1 locus under the QTL by sex model. Multiple metabolic and microbial features map to the distal part of Chr 1 and Chr 16 along with eigenvectors extracted from principal coordinate analysis of measures of ß-diversity. Bilophila , Ruminiclostridium 9 , and Rikenella (Chr 1) were identified as sex and diet independent QTL candidate keystone organisms and Rikenelleceae RC9 Gut Group (Chr 16) was identified as a diet-specific, candidate keystone organism in confirmatory factor analyses of traits mapping to these regions. For many microbial features, irrespective of which QTL model was used, diet or the interaction between diet and a genotype were the strongest predictors of the abundance of each microbial trait. Sex, while important to the analyses, was not as strong of a predictor for microbial abundances. Conclusions These results demonstrate that sex, diet, and genetic background have different magnitudes of effects on inter-individual differences in gut microbiota. Therefore, Precision Nutrition through the integration of genetic variation, microbiota, and sex affecting microbiota variation will be important to predict response to diets varying in carbohydrate composition.

Agr2-associated ER stress promotes adherent-invasive E. coli dysbiosis and triggers CD103+ dendritic cell IL-23-dependent ileocolitis.

Endoplasmic reticulum (ER) stress is associated with Crohn's disease (CD), but its impact on host-microbe interaction in disease pathogenesis is not well defined. Functional deficiency in the protein disulfide isomerase anterior gradient 2 (AGR2) has been linked with CD and leads to epithelial cell ER stress and ileocolitis in mice and humans. Here, we show that ileal expression of AGR2 correlates with mucosal Enterobactericeae abundance in human inflammatory bowel disease (IBD) and that Agr2 deletion leads to ER-stress-dependent expansion of mucosal-associated adherent-invasive Escherichia coli (AIEC), which drives Th17 cell ileocolitis in mice. Mechanistically, our data reveal that AIEC-induced epithelial cell ER stress triggers CD103+ dendritic cell production of interleukin-23 (IL-23) and that IL-23R is required for ileocolitis in Agr2-/- mice. Overall, these data reveal a specific and reciprocal interaction of the expansion of the CD pathobiont AIEC with ER-stress-associated ileocolitis and highlight a distinct cellular mechanism for IL-23-dependent ileocolitis.

Genetic background influences survival of infections with Salmonella enterica serovar Typhimurium in the Collaborative Cross.

Salmonella infections typically cause self-limiting gastroenteritis, but in some individuals these bacteria can spread systemically and cause disseminated disease. Salmonella Typhimurium (STm), which causes severe systemic disease in most inbred mice, has been used as a model for disseminated disease. To screen for new infection phenotypes across a range of host genetics, we orally infected 32 Collaborative Cross (CC) mouse strains with STm and monitored their disease progression for seven days by telemetry. Our data revealed a broad range of phenotypes across CC strains in many parameters including survival, bacterial colonization, tissue damage, complete blood counts (CBC), and serum cytokines. Eighteen CC strains survived to day 7, while fourteen susceptible strains succumbed to infection before day 7. Several CC strains had sex differences in survival and colonization. Surviving strains had lower pre-infection baseline temperatures and were less active during their daily active period. Core body temperature disruptions were detected earlier after STm infection than activity disruptions, making temperature a better detector of illness. All CC strains had STm in spleen and liver, but susceptible strains were more highly colonized. Tissue damage was weakly negatively correlated to survival. We identified loci associated with survival on Chromosomes (Chr) 1, 2, 4, 7. Polymorphisms in Ncf2 and Slc11a1, known to reduce survival in mice after STm infections, are located in the Chr 1 interval, and the Chr 7 association overlaps with a previously identified QTL peak called Ses2. We identified two new genetic regions on Chr 2 and 4 associated with susceptibility to STm infection. Our data reveal the diversity of responses to STm infection across a range of host genetics and identified new candidate regions for survival of STm infection.

Sex-specific genetic architecture in response to American and ketogenic diets.

BACKGROUND/OBJECTIVES: There is a growing appreciation for individual responses to diet. In a previous study, mouse strain-specific responses to American and ketogenic diets were observed. In this study, we searched for genetic variants underlying differences in the responses to American and ketogenic diets between C57BL/6J (B6) and FVB/NJ (FVB) mouse strains. RESULTS: Genetic mapping of fat and lean mass gain revealed QTLs on Chromosome (Chr) 1 at 191.6 Mb (Fmgq1) (P < 0.001, CI = 180.2-194.4 Mb), Chr5 at 73.7 Mb (Fmgq2, Lmgq1) (P < 0.001, CI = 66.1-76.6 Mb), and Chr7 at 40.5 Mb (Fmgq3) (P < 0.01, CI = 36.6-44.5 Mb). Analysis of serum HDL cholesterol concentration identified a significant (P < 0.001, CI = 160.6-176.1 Mb) QTL on Chr1 at 168.6 Mb (Hdlq1). Causal network inference suggests that HDL cholesterol and fat mass gain are both linked to Fmgq1. CONCLUSIONS: Strong sex effects were identified at both Fmgq2 and Lmgq1, which are also diet-dependent. Interestingly, Fmgq2 and Fmgq3 affect fat gain directly, while Fmgq1 influences fat gain directly and via an intermediate change in serum cholesterol. These results demonstrate how precision nutrition will be advanced through the integration of genetic variation and sex in physiological responses to diets varied in carbohydrate composition.