The delayed effects of antibiotics in type 2 diabetes, friend or foe?

Abstract

An increasing amount of evidence suggests that the delayed effect of antibiotics (abx) on gut microbiota after its cessation is not as favorable as its immediate effect on host metabolism. However, it is not known how the diverse abx-dependent metabolic effects influence diabetic subjects and how gut microbiota is involved. Here, we treated db/db mice with abx cocktail for 12 days and discontinued for 24 days. We found that db/db mice showed decreased body weight and blood glucose after abx treatment, which rapidly caught up after abx cessation. Twenty-four days after abx withdrawal, db/db mice exhibit increased plasma, hepatic total cholesterol (TC) levels and liver weight. The gut microbiota composition at that time showed decreased relative abundances (RAs) of Desulfovibrionaceae and Rikenellaceae, increased RA of Erysipelotrichaceae and Mogibacteriaceae, which were correlating with the reduced short-chain fatty acids (SCFAs) in gut content, such as propionic acid and valeric acid and with the elevated fecal taurine-conjugated bile acids (BAs) levels. The molecular biology studies showed inhibited hepatic BA synthesis from cholesterol, impeded intracellular transportation and biliary excretion of cholesterol that all conferred to liver TC accumulation. The associations among alterations of gut microbiota composition, microbial metabolite profiles and host phenotypes suggested the existence of gut microbiota-linked mechanisms that mediate the unfavorable delayed effects of abx on db/db mice cholesterol metabolism. Thus, we call upon the caution of applying abx in diabetic animal models for studying microbiota-host interaction and in type 2 diabetes subjects for preventing chronic cardiovascular consequences.

The glucose-lowering effects of α-glucosidase inhibitor require a bile acid signal in mice

“…16S ribosomal RNA gene sequencing of the gut microbiota and quantification of bacterial DNA Bacterial DNA was extracted from colon content and faeces of mice as previously reported [25] and subjected to PCR amplification and Illumina MiSeq sequencing (San Diego, CA, USA). See ESM Methods for more details.…”

“…Triacylglycerol and cholesterol measurement Triacylglycerol and total cholesterol in both liver and plasma of mice were measured by the Quantification Colorimetric/Fluorometric Kit (Biovision, Milpitas, CA, USA), as previously reported [25]. See ESM Methods for further details.…”

“…Western blotting and antibodies Tissues of mice were lysed, quantified, and blotted, as described previously [25]. See ESM Methods for further details; antibody details are listed in ESM Table 2.…”

Spatial heterogeneity of bacterial colonization across different gut segments following inter-species microbiota transplantation

“…In our study, we observed that a portion of pig-derived microbes capable of degrading indigestible carbohydrates leading to the production of short-chain fatty acids (SCFAs), including Bacteroidetes [45], Prevotellaceae [46], and some families of Firmicutes such as Veillonellaceae [47], Lachnospiraceae [48], and Ruminococcaceae [49], had a greater preference to invade the recipient LI relative to the recipient SI. Families Erysipelotrichaceae and Mogibacteriaceae under the phylum Firmicutes, which are designated as "obesity" bacterial taxa positively correlated with the production of secondary bile acids [50][51][52], also exhibited greater relative densities in the recipient LI receiving the introduction of exogenous large-intestinal communities than those in the recipient SI. Microbes within Erysipelotrichaceae were also positively correlated with a number of parameters involved in carbohydrate digestion including dietary carbohydrate and fiber content and SCFAs production while negatively correlated with fat digestibility and protein metabolism [53][54][55].…”

Metagenomic Analysis Reveals the Distribution of Antibiotic Resistance Genes in a Large-Scale Population of Healthy Individuals and Patients With Varied Diseases

“…Furthermore, the resistome in disease states is largely unexplored. Antibiotic intervention influences some phenotypes closely related to the gut microbiome, such as metabolic disorders ( Yang et al, 2017 ; Fu et al, 2018 ), immunopathologies ( Wypych and Marsland, 2018 ), cancer ( Cao et al, 2018 ; Zhang et al, 2019 ), and hypertension. Thus, it is worthwhile to explore the characteristics of ARGs in disease states and its association with bacteria, which may provide a new perspective for the identification of disease markers.…”