Title |
Patterns of host gene expression associated with harboring a foregut microbial community
|
---|---|
Published in |
BMC Genomics, September 2017
|
DOI | 10.1186/s12864-017-4101-z |
Pubmed ID | |
Authors |
Kevin D. Kohl, Kelly F. Oakeson, Diane Dunn, David K. Meyerholz, Colin Dale, Robert B. Weiss, M. Denise Dearing |
Abstract |
Harboring foregut microbial communities is considered a key innovation that allows herbivorous mammals to colonize new ecological niches. However, the functions of these chambers have only been well studied at the molecular level in ruminants. Here, we investigate gene expression in the foregut chamber of herbivorous rodents and ask whether these gene expression patterns are consistent with results in ruminants. We compared gene expression in foregut tissues of two rodent species: Stephen's woodrat (Neotoma stephensi), which harbors a dense foregut microbial community, and the lab rat (Rattus norvegicus), which lacks such a community. We found that woodrats have higher abundances of transcripts associated with smooth muscle processes, specifically a higher expression of the smoothelin-like 1 gene, which may assist in contractile properties of this tissue to retain food material in the foregut chamber. The expression of genes associated with keratinization and cornification exhibited a complex pattern of differences between the two species, suggesting distinct molecular mechanisms. Lab rats exhibited higher abundances of transcripts associated with immune function, likely to inhibit microbial growth in the foregut of this species. Some of our results were consistent with previous findings in ruminants (high expression of facilitative glucose transporters, lower expression of B4galnt2), suggestive of possible convergent evolution, while other results were unclear, and perhaps represent novel host-microbe interactions in rodents. Overall, our results suggest that harboring a foregut microbiota is associated with changes to the functions and host-microbe interactions of the foregut tissues. |
Twitter Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 12 | 63% |
Japan | 1 | 5% |
Unknown | 6 | 32% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 11 | 58% |
Members of the public | 6 | 32% |
Science communicators (journalists, bloggers, editors) | 1 | 5% |
Practitioners (doctors, other healthcare professionals) | 1 | 5% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 31 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 10 | 32% |
Student > Master | 5 | 16% |
Researcher | 5 | 16% |
Professor | 3 | 10% |
Unspecified | 2 | 6% |
Other | 2 | 6% |
Unknown | 4 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 14 | 45% |
Biochemistry, Genetics and Molecular Biology | 3 | 10% |
Environmental Science | 2 | 6% |
Unspecified | 2 | 6% |
Nursing and Health Professions | 2 | 6% |
Other | 4 | 13% |
Unknown | 4 | 13% |