Newly Explored Faecalibacterium Diversity Is Connected to Age, Lifestyle, Geography, and Disease
Open accessAbstract
Faecalibacterium is prevalent in the human gut and a promising microbe for the development of next-generation probiotics (NGPs) or biotherapeutics. Analyzing reference Faecalibacterium genomes and almost 3,000 Faecalibacterium-like metagenome-assembled genomes (MAGs) reconstructed from 7,907 human and 203 non-human primate gut metagenomes, we identified the presence of 22 different Faecalibacterium-like species-level genome bins (SGBs), some further divided in different strains according to the subject geographical origin. Twelve SGBs are globally spread in the human gut and show different genomic potential in the utilization of complex polysaccharides, suggesting that higher SGB diversity may be related with increased utilization of plant-based foods. Moreover, up to 11 different species may co-occur in the same subject, with lower diversity in Western populations, as well as intestinal inflammatory states and obesity. The newly explored Faecalibacterium diversity will be able to support the choice of strains suitable as NGPs, guided by the consideration of the differences existing in their functional potential.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Phylogroup or clade separation can correspond to differences in oxygen tolerance, epithelial adherence, genome plasticity, and other traits relevant to gut colonization and next-generation probiotic candidate selection.
“Such clustering is biologically meaningful because phylogroup or clade separation can correspond to differences in oxygen tolerance, epithelial adherence, genome plasticity, and other traits relevant to gut colonization and next-generation probiotic candidate selection. 12,13”
Faecalibacterium exhibited broader carbohydrate-related functions, including dietary polysaccharide utilization, glycan-degrading enzymes, trehalose-related metabolism, and extracellular polysaccharide or capsule-associated genes.
“Faecalibacterium, by comparison, exhibited broader carbohydrate-related functions, including dietary polysaccharide utilization, glycan-degrading enzymes, trehalose-related metabolism, and extracellular polysaccharide or capsule-associated genes. 13,15,32,33”
Based on this review, safety-related features mainly included antimicrobial resistance, virulence or pathogenicity markers, phage-related regions, efflux-related genes, CRISPR/Cas systems, and probiotic risk classification, but these assessments were not applied consistently across all datasets.
“Based on this review, safety-related features mainly included antimicrobial resistance, virulence or pathogenicity markers, phage-related regions, efflux-related genes, CRISPR/Cas systems, and probiotic risk classification, but these assessments were not applied consistently across all datasets. 13,15,22,23,39 -41”
Cites
MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability
Katoh, K., & Standley, D. M. (2013) · Molecular Biology and Evolution · doi:10.1093/molbev/mst010 · Cited by 46,209 · see citing works
High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries
Jain, C., Rodriguez-R, L. M., Phillippy, A. M., Konstantinidis, K. T., & Aluru, S. (2018) · Nature Communications · doi:10.1038/s41467-018-07641-9 · Cited by 5,748 · cited 4× · see citing works
“The twelve clades exhibited a median intra-clade distance ranging from 1.6% (clade L) to 3.6% (clade B), always below 5%, which is usually considered the cutoff for defining different species (Figure 1C; Data S2) [27].”
BackgroundInfluentialGlobal increase and geographic convergence in antibiotic consumption between 2000 and 2015
Klein, E. Y., Van Boeckel, T. P., Martinez, E. M., Pant, S., Gandra, S., Levin, S. A., Goossens, H., & Laxminarayan, R. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1717295115 · Cited by 3,232 · see citing works
Environment dominates over host genetics in shaping human gut microbiota
Rothschild, D., Weissbrod, O., Barkan, E., Kurilshikov, A., Korem, T., Zeevi, D., Costea, P. I., Godneva, A., Kalka, I. N., Bar, N., et al. (2018) · Nature · doi:10.1038/nature25973 · Cited by 2,859 · see citing works
Population-level analysis of gut microbiome variation
Falony, G., Joossens, M., Vieira-Silva, S., Wang, J., Darzi, Y., Faust, K., Kurilshikov, A., Bonder, M. J., Valles-Colomer, M., Vandeputte, D., et al. (2016) · Science · doi:10.1126/science.aad3503 · Cited by 2,400 · see citing works
MetaPhlAn2 for enhanced metagenomic taxonomic profiling
Truong, D. T., Franzosa, E. A., Tickle, T. L., Scholz, M., Weingart, G., Pasolli, E., Tett, A., Huttenhower, C., & Segata, N. (2015) · Nature Methods · doi:10.1038/nmeth.3589 · Cited by 2,185 · see citing works
Self-citationNext-generation probiotics: the spectrum from probiotics to live biotherapeutics
O’Toole, P. W., Marchesi, J. R., & Hill, C. (2017) · Nature Microbiology · doi:10.1038/nmicrobiol.2017.57 · Cited by 971 · see citing works
Meslier, V., Laiola, M., Roager, H. M., De Filippis, F., Roume, H., Quinquis, B., Giacco, R., Mennella, I., Ferracane, R., Pons, N., et al. (2020) · Gut · doi:10.1136/gutjnl-2019-320438 · Cited by 583 · see citing works
New Insights into the Diversity of the Genus Faecalibacterium
Benevides, L., Burman, S., Martin, R., Robert, V., Thomas, M., Miquel, S., Chain, F., Sokol, H., Bermudez-Humaran, L. G., Morrison, M., et al. (2017) · Frontiers in Microbiology · doi:10.3389/fmicb.2017.01790 · Cited by 86 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Blanco-Míguez, A., Beghini, F., Cumbo, F., McIver, L. J., Thompson, K. N., Zolfo, M., Manghi, P., Dubois, L., Huang, K. D., Thomas, A. M., et al. (2023) · Nature Biotechnology · doi:10.1038/s41587-023-01688-w · Cited by 1,442 · see citing works
Self-citationKarcher, N., Nigro, E., Punčochář, M., Blanco-Míguez, A., Ciciani, M., Manghi, P., Zolfo, M., Cumbo, F., Manara, S., Golzato, D., et al. (2021) · Genome Biology · doi:10.1186/s13059-021-02427-7 · Cited by 159 · see citing works
A gut microbial signature for combination immune checkpoint blockade across cancer types
Gunjur, A., Shao, Y., Rozday, T., Klein, O., Mu, A., Haak, B. W., Markman, B., Kee, D., Carlino, M. S., Underhill, C., et al. (2024) · Nature Medicine · doi:10.1038/s41591-024-02823-z · Cited by 165 · see citing works
Cataldi, S., Bonavolontà, V., Poli, L., Clemente, F. M., De Candia, M., Carvutto, R., Silva, A. F., Badicu, G., Greco, G., & Fischetti, F. (2022) · Biology · doi:10.3390/biology11030479 · Cited by 68 · see citing works
Maternal and food microbial sources shape the infant microbiome of a rural Ethiopian population
Manara, S., Selma-Royo, M., Huang, K. D., Asnicar, F., Armanini, F., Blanco-Miguez, A., Cumbo, F., Golzato, D., Manghi, P., Pinto, F., et al. (2023) · Current Biology · doi:10.1016/j.cub.2023.04.011 · Cited by 30 · see citing works
Self-citationLadeira, R., Tap, J., & Derrien, M. (2023) · Microbiome Research Reports · doi:10.20517/mrr.2023.01 · Cited by 19 · see citing works
Genomic and functional diversity of the human-derived isolates of Faecalibacterium
Li, W., Lin, X., Liang, H., Wu, Z., Wang, M., Sun, J., Li, X., He, W., Gao, X., Hu, T., et al. (2024) · Frontiers in Microbiology · doi:10.3389/fmicb.2024.1379500 · Cited by 17 · see citing works
Strain-Specific Anti-Inflammatory Effects of Faecalibacterium prausnitzii Strain KBL1027 in Koreans
Seo, B., Jeon, K., Kim, W.-K., Jang, Y. J., Cha, K. H., & Ko, G. (2025) · Probiotics and Antimicrobial Proteins · doi:10.1007/s12602-024-10213-7 · Cited by 12 · see citing works
Ye, Q., Sun, S., Deng, J., Chen, X., Zhang, J., Lin, S., Du, H., Gao, J., Zou, X., Lin, X., et al. (2023) · Scientific Reports · doi:10.1038/s41598-023-47760-y · Cited by 11 · see citing works
Arlan, L., Lestari, R. D., Israyusnita, F., Kotala, S., Adi, N. W., Sari, D. F., Hanifah, Z., Rudiansyah, R., Khasanah, F., Tukan, F. F. D. L., et al. (2026) · F1000Research · doi:10.12688/f1000research.186241.1
- Authors
- De Filippis, F., Pasolli, E., & Ercolini, D.
- Affiliations
- University of Naples Federico II (IT)
- Corresponding author
- Ercolini, Danilo
- Venue
- Current Biology
- Publisher
- Elsevier BV
- Published
- 2020-12
- Volume
- 30
- Issue
- 24
- Pages
- 4932-4943.e4
- ISSN
- 0960-9822 (ISSN-L)
- OpenAlex
- W3092986592
- Cited by
- 161
- References
- 9
- Citations by year
- 2026: 20 · 2025: 28 · 2024: 45 · 2023: 32 · 2022: 20 · 2021: 15 · 2020: 1
- FWCI
- 5.52
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Current Biology (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- INFM-OAR (INFN Catania) (submittedVersion, cc-by-nc-nd)
- Funders
- Horizon 2020
- Ministero delle Politiche Agricole Alimentari e Forestali
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Agricultural and Biological Sciences › Food Science › Probiotics and Fermented Foods
- Keywords
- Faecalibacterium, gut microbiota, metagenome-assembled genomes, microbial diversity, polysaccharide utilization, plant-based diet, non-human primates, intestinal inflammation, obesity, probiotics, biologic therapy, geographical origin
- MeSH terms
- Gastrointestinal Microbiome, Faecalibacterium, Adolescent, Adult, Age Factors, Aged, Animals, Child, Child, Preschool, Feces, Geography, Humans, Infant, Life Style, Macaca, Middle Aged, Phylogeny, Probiotics, Metagenome, Young Adult, Metagenomics, Dysbiosis, Datasets as Topic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
