Antibiotic effects on gut microbiota and metabolism are host dependent

Fujisaka, Shiho; Ussar, Siegfried; Clish, Clary B.; Devkota, Suzanne; Dreyfuss, Jonathan M.; Sakaguchi, Masaji; Soto, Marion; Konishi, Masahiro; Softic, Samir; Altındiş, Emrah; Li, Ning; Gerber, Georg K.; Bry, Lynn; Kahn, C. Ronald

doi:10.1172/jci86674

Cited by 133 publications

(135 citation statements)

References 48 publications

(55 reference statements)

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“…One week later, both antibiotic-treated groups and half of the control mice were challenged with an HFD (60% fat by calories) for 4 weeks. Consistent with previous reports (Fujisaka et al, 2016; Ussar et al, 2015), body weight gain on the chow diet was greater in B6J mice than that in 129J mice, and 129T mice fell in between (Figure 1A). HFD feeding increased body weight gain, with its greatest effects in B6J > 129T > 129J, and this was not significantly affected by either vancomycin or metronidazole (Figure 1A).…”

Section: Resultssupporting

confidence: 93%

“…HFD feeding increased body weight gain, with its greatest effects in B6J > 129T > 129J, and this was not significantly affected by either vancomycin or metronidazole (Figure 1A). Blood glucose was higher in B6J mice than in either 129 strain and modestly increased by 4 weeks of HFD feeding; this did not quite reach statistical significance (Figure 1B) but does so after longer periods of HFD challenge (Fujisaka et al, 2016). We have previously shown, in 8- to 12-week studies, that antibiotics improve insulin resistance in HFD-fed B6J mice (Fujisaka et al, 2016), and, in these short-term cohorts, insulin levels and insulin resistance (homeostatic model assessment for insulin resistance [HOMA-IR]) were higher in B6J than 129 mice on a HFD and tended to be reduced by vancomycin treatment in B6J mice Figures 1C and S1).…”

Section: Resultsmentioning

confidence: 87%

“…The nature of the microbial community and its changes in response to environmental factors such as dietary nutrients, fiber, and antibiotics is dependent on the genetic background of the host (Cho et al, 2012; Fujisaka et al, 2016; Parks et al, 2015; Tamburini et al, 2016; Ussar et al, 2016). These changes in the microbiota have been linked to development of obesity, diabetes, and metabolic syndrome, and many of these phenotypes can be transferred, at least in part, via the microbiome to germ-free mice (Ridaura et al, 2013; Turnbaugh et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

“…C57BL/6J (B6J) mice from Jackson Laboratories (Jax) are obesity- and diabetes-prone, whereas 129S1/SvImJ (129J) mice from the same vendor are obesity- and diabetes-resistant (Almind and Kahn, 2004). 129S6/SvEvTac (129T) mice, which are genetically similar to 129J mice but bred at Taconic Farms, are obesity-prone but remain metabolically healthy (Fujisaka et al, 2016; Ussar et al, 2015). The better insulin sensitivity in 129T and 129J mice is explained in part by their genetically based anti-inflammatory potential (Fujisaka et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…129S6/SvEvTac (129T) mice, which are genetically similar to 129J mice but bred at Taconic Farms, are obesity-prone but remain metabolically healthy (Fujisaka et al, 2016; Ussar et al, 2015). The better insulin sensitivity in 129T and 129J mice is explained in part by their genetically based anti-inflammatory potential (Fujisaka et al, 2016). However, some of the difference between strains is due to differences in their gut microbiotas (Ussar et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

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Diet, Genetics, and the Gut Microbiome Drive Dynamic Changes in Plasma Metabolites

et al. 2018

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SUMMARY Diet, genetics, and the gut microbiome are determinants of metabolic status, in part through production of metabolites by the gut microbiota. To understand the mechanisms linking these factors, we performed LC-MS-based metabolomic analysis of cecal contents and plasma from C57BL/6J, 129S1/SvImJ, and 129S6/SvEvTac mice on chow or a high-fat diet (HFD) and HFD-treated with vancomycin or metronidazole. Prediction of the functional metagenome of gut bacteria by PICRUSt analysis of 16S sequences revealed dramatic differences in microbial metabolism. Cecal and plasma metabolites showed multifold differences reflecting the combined and integrated effects of diet, antibiotics, host background, and the gut microbiome. Eighteen plasma metabolites correlated positively or negatively with host insulin resistance across strains and diets. Over 1,000 still-unidentified metabolite peaks were also highly regulated by diet, antibiotics, and genetic background. Thus, diet, host genetics, and the gut microbiota interact to create distinct responses in plasma metabolites, which can contribute to regulation of metabolism and insulin resistance.

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Section: Resultssupporting

confidence: 93%

Section: Resultsmentioning

confidence: 87%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Diet, Genetics, and the Gut Microbiome Drive Dynamic Changes in Plasma Metabolites

et al. 2018

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The Microbiome and Diabetes

Cox,

West,

Cripps

2024

Textbook of Diabetes

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Postnatal 14D is the Key Window for Mice Intestinal Development‐ An Insight from Age‐Dependent Antibiotic‐Mediated Gut Microbial Dysbiosis Study

2023

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The postnatal period is one of the critical windows for the structure-function development of the gastrointestinal tract and associated mucosal immunity. Along with other constituent members, recent studies suggest the contribution of gut microbiota in maintaining host health, immunity, and development. Although the gut microbiota's role in maintaining barrier integrity is known, its function in early life development still needs to be better understood. To understand the details of gut microbiota's effects on intestinal integrity, epithelium development, and immune profile, the route of antibiotic-mediated perturbation is taken. Mice on days 7(P7D), 14(P14D), 21(P21D) and 28(P28D) are sacrificed and 16S rRNA metagenomic analysis is performed. The barrier integrity, tight junction proteins (TJPs) expression, intestinal epithelial cell (IEC) markers, and inflammatory cytokines are analyzed. Results reveal a postnatal age-related impact of gut microbiota perturbation, with a gradual increase in the relative abundance of Proteobacteria and a reduction in Bacteroidetes and Firmicutes. Significant barrier integrity disruption, reduced TJPs and IECs marker expression, and increased systemic inflammation at P14D of AVNM-treated mice are found. Moreover, the microbiota transplantation shows recolonization of Verrucomicrobia, proving a causal role in barrier functions. The investigation reveals P14D as a critical period for neonatal intestinal development, regulated by specific microbiota composition.

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Antibiotic effects on gut microbiota and metabolism are host dependent

Cited by 133 publications

References 48 publications

Diet, Genetics, and the Gut Microbiome Drive Dynamic Changes in Plasma Metabolites

Diet, Genetics, and the Gut Microbiome Drive Dynamic Changes in Plasma Metabolites

The Microbiome and Diabetes

Postnatal 14D is the Key Window for Mice Intestinal Development‐ An Insight from Age‐Dependent Antibiotic‐Mediated Gut Microbial Dysbiosis Study

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