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Comparing Microbiome Sampling Methods in a Wild Mammal: Fecal and Intestinal Samples Record Different Signals of Host Ecology, Evolution
Open accessAbstract
The gut microbiome is a community of host-associated symbiotic microbes that fulfills multiple key roles in host metabolism, immune function, and tissue development. Given the ability of the microbiome to impact host fitness, there is increasing interest in studying the microbiome of wild animals to better understand these communities in the context of host ecology and evolution. Human microbiome research protocols are well established, but wildlife microbiome research is still a developing field. Currently, there is no standardized set of best practices guiding the collection of microbiome samples from wildlife. Gut microflora are typically sampled either by fecal collection, rectal swabbing, or by destructively sampling the intestinal contents of the host animal. Studies rarely include more than one sampling technique and no comparison of these methods currently exists for a wild mammal. Although some studies have hypothesized that the fecal microbiome is a nested subset of the intestinal microbiome, this hypothesis has not been formally tested. To address these issues, we examined guano (feces) and distal intestinal mucosa from 19 species of free-ranging bats from Lamanai, Belize, using 16S rRNA amplicon sequencing to compare microbial communities across sample types. We found that the diversity and composition of intestine and guano samples differed substantially. In addition, we conclude that signatures of host evolution are retained by studying gut microbiomes based on mucosal tissue samples, but not fecal samples. Conversely, fecal samples retained more signal of host diet than intestinal samples. These results suggest that fecal and intestinal sampling methods are not interchangeable, and that these two microbiotas record different information about the host from which they are isolated.
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“Developments in DNA sequencing technology allow a unique and non‐invasive approach to examining the health of animals in the wild, and the effects of environment and ecology through the analysis of their gut microbiomes (Bahrndorff et al., 2016; Barko et al., 2018; Ingala et al., 2018).”
From Microbiomes in Canidae (2021) · cites this paper as Ingala et al., 2018
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A Mathematical Theory of Communication
Shannon, C. E. (1948) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1948.tb01338.x · Cited by 88,486
DADA2: High–resolution sample inference from Illumina amplicon data
Callahan, B. J., McMurdie, P. J., Rosen, M. J., Han, A. W., Johnson, A. J. A., & Holmes, S. P. (2016) · Nature Methods · doi:10.1038/nmeth.3869 · Cited by 35,698
QIIME allows analysis of high-throughput community sequencing data
Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., Fierer, N., Peña, A. G., Goodrich, J. K., Gordon, J. I., et al. (2010) · Nature Methods · doi:10.1038/nmeth.f.303 · Cited by 34,887
FastTree 2 – Approximately Maximum-Likelihood Trees for Large Alignments
Price, M. N., Dehal, P. S., & Arkin, A. P. (2010) · PLoS ONE · doi:10.1371/journal.pone.0009490 · Cited by 14,894
A new method for non-parametric multivariate analysis of variance
Anderson, M. J. (2001) · Austral Ecology · doi:10.1111/j.1442-9993.2001.01070.pp.x · Cited by 13,828
Structure, function and diversity of the healthy human microbiome
The Human Microbiome Project Consortium (2012) · Nature · doi:10.1038/nature11234 · Cited by 11,726
Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB
DeSantis, T. Z., Hugenholtz, P., Larsen, N., Rojas, M., Brodie, E. L., Keller, K., Huber, T., Dalevi, D., Hu, P., & Andersen, G. L. (2006) · Applied and Environmental Microbiology · doi:10.1128/aem.03006-05 · Cited by 10,891
Diet rapidly and reproducibly alters the human gut microbiome
David, L. A., Maurice, C. F., Carmody, R. N., Gootenberg, D. B., Button, J. E., Wolfe, B. E., Ling, A. V., Devlin, A. S., Varma, Y., Fischbach, M. A., et al. (2014) · Nature · doi:10.1038/nature12820 · Cited by 10,100
Evolution of mammals and their gut microbes
Ley, R. E., Hamady, M., Lozupone, C., Turnbaugh, P. J., Ramey, R. R., Bircher, J. S., Schlegel, M. L., Tucker, T. A., Schrenzel, M. D., Knight, R., et al. (2008) · Science · doi:10.1126/science.1155725 · Cited by 3,747
The gut microbiota--masters of host development and physiology
Sommer, F., & Bäckhed, F. (2013) · Nature Reviews Microbiology · doi:10.1038/nrmicro2974 · Cited by 3,681
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Metadata
- Authors
- Ingala, M. R., Simmons, N. B., Wultsch, C., Krampis, K., Speer, K. A., & Perkins, S. L.
- Venue
- Frontiers in Microbiology
- Publisher
- Frontiers Media SA
- Published
- 2018-05-01
- Volume
- 9
- Pages
- 803-803
- ISSN
- 1664-302X (ISSN-L)
- OpenAlex
- W2796470921
- Cited by
- 501
- References
- 18
- FWCI
- 18.13
- Type
- journal article
- Language
- en
- Open access
- gold
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- Ingala, M. R., Simmons, N. B., Wultsch, C., Krampis, K., Speer, K. A., & Perkins, S. L. (2018). Comparing Microbiome Sampling Methods in a Wild Mammal: Fecal and Intestinal Samples Record Different Signals of Host Ecology, Evolution. Frontiers in Microbiology. https://doi.org/10.3389/fmicb.2018.00803
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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