» Articles » PMID: 28586297

Fecal Microbiota Variation Across the Lifespan of the Healthy Laboratory Rat

Overview
Journal Gut Microbes
Date 2017 Jun 7
PMID 28586297
Citations 54
Authors
Affiliations
Soon will be listed here.
Abstract

Laboratory rats are commonly used in life science research as a model for human biology and disease, but the composition and development of their gut microbiota during life is poorly understood. We determined the fecal microbiota composition of healthy Sprague Dawley laboratory rats from 3 weeks to 2 y of age, kept under controlled environmental and dietary conditions. Additionally, we determined fecal short-chain fatty acid profiles, and we compared the rat fecal microbiota with that of mice and humans. Gut microbiota and to a lesser extent SCFAs profiles separated rats into 3 different clusters according to age: before weaning, first year of life (12- to 26-week-old animals) and second year of life (52- to 104-week-old). A core of 46 bacterial species was present in all rats but its members' relative abundance progressively decreased with age. This was accompanied by an increase of microbiota α-diversity, likely due to the acquisition of environmental microorganisms during the lifespan. Contrastingly, the functional profile of the microbiota across animal species became more similar upon aging. Lastly, the microbiota of rats and mice were most similar to each other but at the same time the microbiota profile of rats was more similar to that of humans than was the microbiota profile of mice. These data offer an explanation as to why germ-free rats are more efficient recipients and retainers of human microbiota than mice. Furthermore, experimental design should take into account dynamic changes in the microbiota of model animals considering that their changing gut microbiota interacts with their physiology.

Citing Articles

The Oral Microbial Ecosystem in Age-Related Xerostomia: A Critical Review.

Pei X, Zhou L, Tsang M, Tai W, Wong S Int J Mol Sci. 2024; 25(23.

PMID: 39684528 PMC: 11640827. DOI: 10.3390/ijms252312815.


The case for microbial intervention at weaning.

Flores J, Lubin J, Silverman M Gut Microbes. 2024; 16(1):2414798.

PMID: 39468827 PMC: 11540084. DOI: 10.1080/19490976.2024.2414798.


The Future Exploring of Gut Microbiome-Immunity Interactions: From In Vivo/Vitro Models to In Silico Innovations.

Bertorello S, Cei F, Fink D, Niccolai E, Amedei A Microorganisms. 2024; 12(9).

PMID: 39338502 PMC: 11434319. DOI: 10.3390/microorganisms12091828.


The Gut Microbiome in Aging and Ovarian Cancer.

Dominique G, Hammond C, Stack M Aging Cancer. 2024; 5(1-2):14-34.

PMID: 39132604 PMC: 11309124. DOI: 10.1002/aac2.12071.


Alcohol consumption during pregnancy differentially affects the fecal microbiota of dams and offspring.

Bodnar T, Ainsworth-Cruickshank G, Billy V, Parfrey L, Weinberg J, Raineki C Sci Rep. 2024; 14(1):16121.

PMID: 38997303 PMC: 11245617. DOI: 10.1038/s41598-024-64313-z.


References
1.
Silley P . Human flora-associated rodents--does the data support the assumptions?. Microb Biotechnol. 2011; 2(1):6-14. PMC: 3815418. DOI: 10.1111/j.1751-7915.2008.00069.x. View

2.
DeSantis T, Hugenholtz P, Larsen N, Rojas M, Brodie E, Keller K . Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol. 2006; 72(7):5069-72. PMC: 1489311. DOI: 10.1128/AEM.03006-05. View

3.
Sender R, Fuchs S, Milo R . Revised Estimates for the Number of Human and Bacteria Cells in the Body. PLoS Biol. 2016; 14(8):e1002533. PMC: 4991899. DOI: 10.1371/journal.pbio.1002533. View

4.
Koh A, De Vadder F, Kovatcheva-Datchary P, Backhed F . From Dietary Fiber to Host Physiology: Short-Chain Fatty Acids as Key Bacterial Metabolites. Cell. 2016; 165(6):1332-1345. DOI: 10.1016/j.cell.2016.05.041. View

5.
Manichanh C, Reeder J, Gibert P, Varela E, Llopis M, Antolin M . Reshaping the gut microbiome with bacterial transplantation and antibiotic intake. Genome Res. 2010; 20(10):1411-9. PMC: 2945190. DOI: 10.1101/gr.107987.110. View