The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Methods for Improving Human Gut Microbiome Data by Reducing Variability through Sample Processing and Storage of Stool
Open accessAbstract
Gut microbiome community analysis is used to understand many diseases like inflammatory bowel disease, obesity, and diabetes. Sampling methods are an important consideration for human microbiome research, yet are not emphasized in many studies. In this study, we demonstrate that the preparation, handling, and storage of human faeces are critical processes that alter the outcomes of downstream DNA-based bacterial community analyses via qPCR. We found that stool subsampling resulted in large variability of gut microbiome data due to different microenvironments harbouring various taxa within an individual stool. However, we reduced intra-sample variability by homogenizing the entire stool sample in liquid nitrogen and subsampling from the resulting crushed powder prior to DNA extraction. We experimentally determined that the bacterial taxa varied with room temperature storage beyond 15 minutes and beyond three days storage in a domestic frost-free freezer. While freeze thawing only had an effect on bacterial taxa abundance beyond four cycles, the use of samples stored in RNAlater should be avoided as overall DNA yields were reduced as well as the detection of bacterial taxa. Overall we provide solutions for processing and storing human stool samples that reduce variability of microbiome data. We recommend that stool is frozen within 15 minutes of being defecated, stored in a domestic frost-free freezer for less than three days, and homogenized prior to DNA extraction. Adoption of these simple protocols will have a significant and positive impact on future human microbiome research.
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Cites
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Cited by
Heintz‐Buschart, A., Pandey, U., Wicke, T., Sixel‐Döring, F., Janzen, A., Sittig‐Wiegand, E., Trenkwalder, C., Oertel, W. H., Mollenhauer, B., & Wilmes, P. (2018) · Movement Disorders · doi:10.1002/mds.27105 · Cited by 554
The Madness of Microbiome: Attempting To Find Consensus “Best Practice” for 16S Microbiome Studies
Pollock, J., Glendinning, L., Wisedchanwet, T., & Watson, M. (2018) · Applied and Environmental Microbiology · doi:10.1128/aem.02627-17 · Cited by 575
Primer, Pipelines, Parameters: Issues in 16S rRNA Gene Sequencing
Abellan-Schneyder, I., Matchado, M. S., Reitmeier, S., Sommer, A., Sewald, Z., Baumbach, J., List, M., & Neuhaus, K. (2021) · mSphere · doi:10.1128/msphere.01202-20 · Cited by 498
Current Sampling Methods for Gut Microbiota: A Call for More Precise Devices
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Conceição-Neto, N., Zeller, M., Lefrère, H., De Bruyn, P., Beller, L., Deboutte, W., Yinda, C. K., Lavigne, R., Maes, P., Ranst, M. V., et al. (2015) · Scientific Reports · doi:10.1038/srep16532 · Cited by 363
Metadata
- Authors
- Gorzelak, M. A., Gill, S. K., Tasnim, N., Ahmadi-Vand, Z., Jay, M., & Gibson, D. L.
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2015-08-07
- Volume
- 10
- Issue
- 8
- Pages
- e0134802
- ISSN
- 1932-6203 (ISSN-L)
- OpenAlex
- W2135623916
- Cited by
- 306
- References
- 35
- FWCI
- 10.16
- Type
- journal article
- Language
- en
- Open access
- gold
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