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The laboratory rat emerges as a useful tool for studying the interaction between the host and its microbiome. To advance principles relevant to the human microbiome, we systematically investigated and defined a multi-tissue full lifespan microbial biogeography for healthy Fischer 344 rats. Microbial community profiling data was extracted and integrated with host transcriptomic data from the Sequencing Quality Control (SEQC) consortium. Unsupervised machine learning, Spearman's correlation, taxonomic diversity, and abundance analyses were performed to determine and characterize the rat microbial biogeography and the identification of four inter-tissue microbial heterogeneity patterns (P1-P4). The 11 body habitats harbor a greater diversity of microbes than previously suspected. Lactic acid bacteria (LAB) abundances progressively declined in lungs from breastfeed newborn to adolescence/adult and was below detectable levels in elderly rats. LAB's presence and levels in lungs were further evaluated by PCR in the two validation datasets. The lung, testes, thymus, kidney, adrenal, and muscle niches were found to have age-dependent alterations in microbial abundance. P1 is dominated by lung samples. P2 contains the largest sample size and is enriched for environmental species. Liver and muscle samples were mostly classified into P3. Archaea species were exclusively enriched in P4. The 357 pattern-specific microbial signatures were positively correlated with host genes in cell migration and proliferation (P1), DNA damage repair and synaptic transmissions (P2), as well as DNA transcription and cell cycle in P3. Our study established a link between metabolic properties of LAB with lung microbiota maturation and development. Breastfeeding and environmental exposure influence microbiome composition and host health and longevity. The inferred rat microbial biogeography and pattern-specific microbial signatures would be useful for microbiome therapeutic approaches to human health and good quality of life.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10245737 | PMC |
| http://dx.doi.org/10.1101/2023.05.19.541527 | DOI Listing |
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