Quantitative PCR assays for mouse enteric flora reveal strain-dependent differences in composition that are influenced by the microenvironment

Abstract

The mammalian gastrointestinal (GI) tract is inhabited by over a hundred species of symbiotic bacteria. Differences among individuals in the composition of the GI flora may contribute to variation in in vivo experimental analyses and disease susceptibility. To investigate potential interindividual differences in GI flora composition, we developed real-time quantitative PCR-based assays for the detection of the eight members of the Altered Schaedler Flora (ASF) as representative members of different bacterial niches within the mammalian GI tract. Quantitative and reproducible strain-specific variations in the numbers of the ASF members were observed across 23 different barrier-housed inbred mouse strains, suggesting that the ASF assays can be used as sentinels for changes in GI flora composition. A significant cage effect was also detected. Isogenic mice that cohabited at weaning, whether from the same or different litters, showed little variation in ASF profiles. Conversely, litters split among different cages at weaning showed divergence in ASF profiles after three weeks. Individual ASF profiles, once established, were highly stable over time in the absence of environmental perturbation. Furthermore, cohabitation of different inbred strains maintained most of the interstrain variation in the GI flora, supporting a role of host genetics in determining GI flora composition.

Age and Microenvironment Outweigh Genetic Influence on the Zucker Rat Microbiome

“…In a quantitative PCR-based analysis of several germfree inbred strains of mice colonised with altered Schaedler flora (ASF), the microenvironment was found to influence the intestinal microbiota, with animals in differing cages showing divergence in ASF profiles. However, cohabitation of differing inbred strains of mice preserved most of the interstrain variation, with species variation in coprophagic behaviour suggested as a potential cause [49]. Further to this, Dimitriu and colleagues found that the response of faecal bacteria profiles to cohousing was strongly dependent on mouse genotype, with immunodeficient mice being more resistant to bacterial colonisation than wild type mice [51].…”

Nucleotide-Oligomerization-Domain-2 Affects Commensal Gut Microbiota Composition and Intracerebral Immunopathology in Acute Toxoplasma gondii Induced Murine Ileitis

“…Marked differences in the commensal intestinal microbiota composition might represent a general complication when comparing in vivo studies from different research institutions. It is well known that the colonization status of mice ultimately varies between animal facilities, units within the same facility, between rooms within the same unit and additionally between cages within the same room [36], [37], [38]. Furthermore, NOD2 has been shown to be required for orchestrating the commensal intestinal microbiota composition in mice and men [27], [39], and differences are considered to impact the early immune responses following murine infection with intestinal pathogens such as Citrobacter rodentium and Salmonella enterica Typhimurium [22], [40].…”

Temporal Dynamics of the Cecal Gut Microbiota of Juvenile Arctic Ground Squirrels: a Strong Litter Effect across the First Active Season

“…Although maternal influences have been shown to affect relative abundances of bacterial phylotypes in the gut of mice (19), differences in relative abundances among littermates are not uncommon even where litter effects are observed (20,21). Mice reared in individual cages, and thus exposed to different microenviron- (23). Host genotype is also known to affect the relative abundance of gut microbes and may further explain the variation seen among squirrels and the less robust effect of litter when relative abundance was taken into account.…”

“…Litter effects, the greater similarities in gut microbiota among littermates than among unrelated individuals, are due primarily to maternal effects (initial exposure to the mother's microbiota) (19)(20)(21). Other factors that affect variability include host genotype (18,19), immunity (19,21), diet (20,22), environmental and stochastic factors (19,23), age, and sex (19).…”