The DOI matches its Crossref record; 80 of the 80 references it cites were found in a registry or an index.
Rational design of a microbial consortium of mucosal sugar utilizers reduces Clostridiodes difficile colonization
Open accessAbstract
Many intestinal pathogens, including Clostridioides difficile, use mucus-derived sugars as crucial nutrients in the gut. Commensals that compete with pathogens for such nutrients are therefore ecological gatekeepers in healthy guts, and are attractive candidates for therapeutic interventions. Nevertheless, there is a poor understanding of which commensals use mucin-derived sugars in situ as well as their potential to impede pathogen colonization. Here, we identify mouse gut commensals that utilize mucus-derived monosaccharides within complex communities using single-cell stable isotope probing, Raman-activated cell sorting and mini-metagenomics. Sequencing of cell-sorted fractions reveals members of the underexplored family Muribaculaceae as major mucin monosaccharide foragers, followed by members of Lachnospiraceae, Rikenellaceae, and Bacteroidaceae families. Using this information, we assembled a five-member consortium of sialic acid and N-acetylglucosamine utilizers that impedes C. difficile’s access to these mucosal sugars and impairs pathogen colonization in antibiotic-treated mice. Our findings underscore the value of targeted approaches to identify organisms utilizing key nutrients and to rationally design effective probiotic mixtures.
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Cites
Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2−ΔΔCT Method
Livak, K. J., & Schmittgen, T. D. (2001) · Methods · doi:10.1006/meth.2001.1262 · Cited by 180,860
Gapped BLAST and PSI-BLAST: a new generation of protein database search programs
Altschul, S. (1997) · Nucleic Acids Research · doi:10.1093/nar/25.17.3389 · Cited by 73,302
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
The SILVA ribosomal RNA gene database project: improved data processing and web-based tools
Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., Peplies, J., & Glöckner, F. O. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1219 · Cited by 33,055
SPAdes: A New Genome Assembly Algorithm and Its Applications to Single-Cell Sequencing
Bankevich, A., Nurk, S., Antipov, D., Gurevich, A. A., Dvorkin, M., Kulikov, A. S., Lesin, V. M., Nikolenko, S. I., Pham, S., Prjibelski, A. D., et al. (2012) · Journal of Computational Biology · doi:10.1089/cmb.2012.0021 · Cited by 25,987
Naïve Bayesian Classifier for Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy
Wang, Q., Garrity, G. M., Tiedje, J. M., & Cole, J. R. (2007) · Applied and Environmental Microbiology · doi:10.1128/aem.00062-07 · Cited by 19,885
Schloss, P. D., Westcott, S. L., Ryabin, T., Hall, J. R., Hartmann, M., Hollister, E. B., Lesniewski, R. A., Oakley, B. B., Parks, D. H., Robinson, C. J., et al. (2009) · Applied and Environmental Microbiology · doi:10.1128/aem.01541-09 · Cited by 19,549
UPARSE: highly accurate OTU sequences from microbial amplicon reads
Edgar, R. C. (2013) · Nature Methods · doi:10.1038/nmeth.2604 · Cited by 16,707
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
Parks, D. H., Imelfort, M., Skennerton, C. T., Hugenholtz, P., & Tyson, G. W. (2015) · Genome Research · doi:10.1101/gr.186072.114 · Cited by 12,496
Cited by
Exploration of the Muribaculaceae Family in the Gut Microbiota: Diversity, Metabolism, and Function
Zhu, Y., Chen, B., Zhang, X., Akbar, M. T., Wu, T., Zhang, Y., Zhi, L., & Shen, Q. (2024) · Nutrients · doi:10.3390/nu16162660 · Cited by 596
Microbiome diversity protects against pathogens by nutrient blocking
Spragge, F., Bakkeren, E., Jahn, M. T., B. N. Araujo, E., Pearson, C. F., Wang, X., Pankhurst, L., Cunrath, O., & Foster, K. R. (2023) · Science · doi:10.1126/science.adj3502 · Cited by 435
Effects of Probiotics on Gut Microbiota: An Overview
Chandrasekaran, P., Weiskirchen, S., & Weiskirchen, R. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25116022 · Cited by 382
Liu, X., Zhang, Y., Li, W., Zhang, B., Yin, J., Liuqi, S., Wang, J., Peng, B., & Wang, S. (2022) · Journal of Agricultural and Food Chemistry · doi:10.1021/acs.jafc.2c06417 · Cited by 284
Horrocks, V., King, O. G., Yip, A. Y. G., Marques, I. M., & McDonald, J. A. K. (2023) · Microbiology · doi:10.1099/mic.0.001377 · Cited by 104
Metadata
- Authors
- Pereira, F. C., Wasmund, K., Cobankovic, I., Jehmlich, N., Herbold, C. W., Lee, K. S., Sziranyi, B., Vesely, C., Decker, T., Stocker, R., Warth, B., von Bergen, M., Wagner, M., & Berry, D.
- Venue
- Nature Communications
- Published
- 2020-10-09
- Volume
- 11
- Issue
- 1
- Pages
- 5104-5104
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W3092276385
- Cited by
- 317
- References
- 80
- FWCI
- 10.99
- Type
- journal article
- Language
- en
- Open access
- gold
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- Pereira, F. C., Wasmund, K., Cobankovic, I., Jehmlich, N., Herbold, C. W., Lee, K. S., Sziranyi, B., Vesely, C., Decker, T., Stocker, R., Warth, B., von Bergen, M., Wagner, M., & Berry, D. (2020). Rational design of a microbial consortium of mucosal sugar utilizers reduces Clostridiodes difficile colonization. Nature Communications. https://doi.org/10.1038/s41467-020-18928-1
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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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