Antibiotics in early life alter the murine colonic microbiome and adiposity

Department of Medicine, New York University School of Medicine, New York, New York 10016, USA.
Nature (Impact Factor: 41.46). 08/2012; 488(7413):621-6. DOI: 10.1038/nature11400
Source: PubMed


Antibiotics administered in low doses have been widely used as growth promoters in the agricultural industry since the 1950s, yet the mechanisms for this effect are unclear. Because antimicrobial agents of different classes and varying activity are effective across several vertebrate species, we proposed that such subtherapeutic administration alters the population structure of the gut microbiome as well as its metabolic capabilities. We generated a model of adiposity by giving subtherapeutic antibiotic therapy to young mice and evaluated changes in the composition and capabilities of the gut microbiome. Administration of subtherapeutic antibiotic therapy increased adiposity in young mice and increased hormone levels related to metabolism. We observed substantial taxonomic changes in the microbiome, changes in copies of key genes involved in the metabolism of carbohydrates to short-chain fatty acids, increases in colonic short-chain fatty acid levels, and alterations in the regulation of hepatic metabolism of lipids and cholesterol. In this model, we demonstrate the alteration of early-life murine metabolic homeostasis through antibiotic manipulation.

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Available from: Laura Michelle Cox, Feb 03, 2014
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    • "Infants go from the womb to abruptly encountering the full microbial diversity of their new ex-utero environment. Early microbial colonization impacts the long-term adult microbial ecosystem (Biasucci et al., 2008), and is likely a critical ecological window that influences health trajectory throughout life (Blaser & Falkow, 2009;Dominguez-bello et al., 2011;Scholtens et al., 2012;Cho et al., 2012). Infant fecal samples are commonly studied to investigate the impacts of factors such as breastfeeding on the development of the gut microbiota and subsequent health effects. "
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    ABSTRACT: Infant fecal samples are commonly studied to investigate the impacts of breastfeeding on the development of the microbiota and subsequent health effects. Comparisons of infants living in different geographic regions and environmental contexts are needed to aid our understanding of evolutionarily-selected milk adaptations. However, the preservation of fecal samples from individuals in remote locales until they can be processed can be a challenge. Freeze-drying (lyophilization) offers a cost-effective way to preserve some biological samples for transport and analysis at a later date. Currently, it is unknown what, if any, biases are introduced into various analyses by the freeze-drying process. Here, we investigated how freeze-drying affected analysis of two relevant and intertwined aspects of infant fecal samples, marker gene amplicon sequencing of the bacterial community and the fecal oligosaccharide profile (undigested human milk oligosaccharides). No differences were discovered between the fecal oligosaccharide profiles of wet and freeze-dried samples. The marker gene sequencing data showed an increase in proportional representation of Bacteriodes and a decrease in detection of bifidobacteria and members of class Bacilli after freeze-drying. This sample treatment bias may possibly be related to the cell morphology of these different taxa (Gram status). However, these effects did not overwhelm the natural variation among individuals, as the community data still strongly grouped by subject and not by freeze-drying status. We also found that compensating for sample concentration during freeze-drying, while not necessary, was also not detrimental. Freeze-drying may therefore be an acceptable method of sample preservation and mass reduction for some studies of microbial ecology and milk glycan analysis.
    Full-text · Article · Jan 2016 · PeerJ
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    • "Plots of a PCoA are commonly used in microbial ecology studies to explore relationships between samples/subjects and can be based on any dissimilarity between samples. Examples include UniFrac [42] [37] [67], DPCoA [12] [9] [47], Jenson-Shannon [13] [34] and Bray-Curtis [48] [11]. To describe our kernel regression framework, we first describe these common exploratory analyses in the general framework of " constrained ordination " . "
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    ABSTRACT: The analysis of human microbiome data is often based on dimension-reduced graphical displays and clustering derived from vectors of microbial abundances in each sample. Common to these ordination methods is the use of biologically motivated definitions of similarity. Principal coordinate analysis, in particular, is often performed using ecologically defined distances, allowing analyses to incorporate context-dependent, non-Euclidean structure. Here we describe how to take a step beyond ordination plots and incorporate this structure into high-dimensional penalized regression models. Within this framework, the estimate of a regression coefficient vector is obtained via the joint eigen properties of multiple similarity matrices, or kernels. This allows for multivariate regression models to incorporate both a matrix of microbial abundances and, for instance, a matrix of phylogenetically-informed similarities between the abundance profiles. Further, we show how this regression framework can be used to address the compositional nature of multivariate predictors comprised of relative abundances; that is, vectors whose entries sum to a constant. We illustrate this regression framework with several simulations using data from two recent studies on the gut and vaginal microbiome. We conclude with an application to our own data, where we also incorporate a significance test for the estimated coefficients that represent associations between microbial abundance and a response.
    Full-text · Article · Nov 2015
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    • "Gut contains an extremely complex and dense microbial community , and the encoding gene capacity exceeds that of the human genome by at least 100 fold (Gill et al. 2006). Gut microbiota are involved in the regulation of multiple host metabolic pathways, including signaling and immune-inflammatory axes (Kau et al. 2011) that physiologically connect the functions of gut, liver, muscle and brain (Nicholson et al. 2005; Tremaroli and Backhed 2012), which play important roles in host health (Guarner and Malagelada 2003). "
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    ABSTRACT: Antibiotics have been widely used for disease prevention and treatment of the human and animals, and for growth promotion in animal husbandry. Antibiotics can disturb the intestinal microbial community, which play a fundamental role in animals' health. Misuse or overuse of antibiotics can result in increase and spread of microbial antibiotic resistance, threatening human health and ecological safety. In this study, we used Illumina Hiseq sequencing, (1)H nuclear magnetic resonance spectroscopy and metagenomics approaches to investigate intestinal microbial community shift and antibiotic resistance alteration of the mice drinking the water containing tetracycline hydrochloride (TET). Two-week TET administration caused reduction of gut microbial diversity (from 194 to 89 genera), increase in Firmicutes abundance (from 24.9 to 39.8 %) and decrease in Bacteroidetes abundance (from 69.8 to 51.2 %). Metagenomic analysis showed that TET treatment affected the intestinal microbial functions of carbohydrate, ribosomal, cell wall/membrane/envelope and signal transduction, which is evidenced by the alteration in the metabolites of mouse serum. Meanwhile, in the mouse intestinal microbiota, TET treatment enhanced the abundance of antibiotic resistance genes (ARGs) (from 307.3 to 1492.7 ppm), plasmids (from 425.4 to 3235.1 ppm) and integrons (from 0.8 to 179.6 ppm) in mouse gut. Our results indicated that TET administration can disturb gut microbial community and physiological metabolism of mice, and increase the opportunity of ARGs and mobile genetic elements entering into the environment with feces discharge.
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