Obesity places a tremendous burden on individual health and the healthcare system. The gut microbiome (GM) influences host metabolism and behaviors affecting body weight (BW) such as feeding. The GM of mice varies between suppliers and significantly influences BW. We sought to determine whether GM-associated differences in BW are associated with differences in intake, fecal energy loss, or fetal growth. Pair-housed mice colonized with a low or high microbial richness GM were weighed, and the total and BW-adjusted intake were measured at weaning and adulthood. Pups were weighed at birth to determine the effects of the maternal microbiome on fetal growth. Fecal samples were collected to assess the fecal energy loss and to characterize differences in the microbiome. The results showed that supplier-origin microbiomes were associated with profound differences in fetal growth and excessive BW-adjusted differences in intake during adulthood, with no detected difference in fecal energy loss. Agreement between the features of the maternal microbiome associated with increased birth weight here and in recent human studies supports the value of this model to investigate the mechanisms by which the maternal microbiome regulates offspring growth and food intake.
Host genetics, sex, and other within-source factors have been associated with characteristic effects on the fecal microbiome in mice, however, the commercial source of mice remains the dominant factor. Increasing evidence indicates that supplier-specific microbiomes in particular confer differences in disease susceptibility in models of inflammatory conditions, as well as baseline behavior and body morphology. However, current knowledge regarding the compositional differences between suppliers is based on 16S rRNA amplicon sequencing data, and functional differences between these communities remain poorly defined. Here, we applied a meta-omic (metagenomic and metatranscriptomic) approach to biomolecules (DNA/RNA) extracted from murine fecal samples representative of two large U.S. suppliers of research mice, which differ in composition, and influence baseline physiology and behavior as well as disease severity in mouse models of intestinal disease. We reconstructed high-quality metagenome-assembled genomes (MAGs), frequently containing genomic content unique to each supplier. These differences were observed both within pangenomes of dominant taxa as well as the epibiont Saccharimonadaceae. Additionally, transcriptional activity and pathway analyses revealed key functional differences between the metagenomes associated with each supplier, including differences in carbohydrate enzyme activity and dissimilatory sulfate reduction by sulfate-reducing bacteria (SRB). These data provide a detailed characterization of the baseline differences in the fecal metagenome of laboratory mice from two U.S. commercial suppliers suggesting that these functional differences are influenced by differences in the initial inoculum of colony founders, as well as additional taxa gained during growth of the production colony.
Background While murine fecal collection is central to microbiome research, there are a number of practical considerations that may vary during fecal sample collection, including time to sample storage, time of day the sample is collected, and position within the colon during terminal collections. While the need to control these factors is recognized, the relative effect on microbial community of duration at room temperature, time of day, and hindgut position, in the context of a known biological variable, is unclear. To answer these questions, and assess reproducibility of results across different microbiome compositions, parallel experiments were performed to investigate the effect of those factors on the microbiome of age- and sex-matched isogenic mice colonized with two different vendor-origin microbiomes. Results 16S rRNA amplicon sequencing data from flash-frozen fecal samples showed no statistical difference in alpha or beta diversity compared to samples incubated for 1, 2, 3, 4, 6, and 9 hours at room temperature. Overall, samples collected in the AM period showed greater richness and alpha-diversity compared to samples collected in the PM period. While a significant effect of time was detected in all hindgut regions, the effect increased from cecum to distal colon. When using two vendor-origin microbiomes as a biological variable, its effect size vastly outweighed the effect size of the time samples spent at room temperature, the time of day samples were collected, and the position within the colon from which samples were collected. Conclusions This study has highlighted multiple scenarios encountered in microbiome research that may affect outcome measures of microbial diversity and composition. Unexpectedly, delayed time to sample cold storage up to nine hours did not affect the alpha or global beta diversity of fecal sample. We then presented evidence of location- and time-dependent effects within the hindgut on microbial richness, diversity, and composition. We finally demonstrated a relatively low effect size of these technical factors when compared to a primary experimental factor with large intergroup variability.
Research investigating the gut microbiome (GM) during a viral infection may necessitate inactivation of the fecal viral load. Here, we assess how common viral inactivation techniques affect 16S rRNA-based analysis of the gut microbiome. Five common viral inactivation methods were applied to cross-matched fecal samples from sixteen female CD-1 mice of the same GM background prior to fecal DNA extraction. The V4 region of the 16S rRNA gene was amplified and sequenced from extracted DNA. Treatment-dependent effects on DNA yield, genus-level taxonomic abundance, and alpha and beta diversity metrics were assessed. A sodium dodecyl sulfate (SDS)-based inactivation method and Holder pasteurization had no effect on measures of microbial richness, while two Buffer AVL-based inactivation methods resulted in a decrease in detected richness. SDS inactivation, Holder pasteurization, and the AVL-based inactivation methods had no effect on measures of alpha diversity within samples or beta diversity between samples. Fecal DNA extracted with TRIzol-treated samples failed to amplify and sequence, making it unsuitable for microbiome analysis. These results provide guidance in the 16S rRNA microbiome analysis of fecal samples requiring viral inactivation.
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