ArticleThe ISME journal2021
Metabolic modeling predicts specific gut bacteria as key determinants for Candida albicans colonization levels.
Article in The ISME journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed, 49 citations in OpenAlex.
- Pan-Genome-Scale Metabolic Reconstruction Reveals Conserved Metabolic Functions inJournal of fungi (Basel, Switzerland) · 2026Article
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- Genome-scale metabolic modelling of the priority fungal pathogenmicroLife · 2026Article
- A multi-omics analysis unveils functional and regulatory links between hydroxybenzene and aromatic amino acid metabolism inmSystems · 2025Article
- Candida albicans colonization in the human colon correlates with a reduction in acetate- and butyrate-producing bacteria, as simulated using the M-SHIME® model.NPJ biofilms and microbiomes · 2025Article
- Multi-omics to evaluate the protective mechanisms during Akkermansia muciniphila treatment of Candida albicans colonization and subsequent infection.Journal of microbiology (Seoul, Korea) · 2025Article
- Commensalism and pathogenesis of Candida albicans at the mucosal interface.Nature reviews. Microbiology · 2025Review
- Genome-scale metabolic modeling reveals specific vaginalMicrobiology spectrum · 2025Article
- Composition, Influencing Factors, and Effects on Host Nutrient Metabolism of Fungi in Gastrointestinal Tract of Monogastric Animals.Animals : an open access journal from MDPI · 2025Review
- [The intestinal microbiota in inflammatory bowel diseases].Innere Medizin (Heidelberg, Germany) · 2025Review
- Specific Bacterial Co-abundance Groups Are Associated With Inflammatory Status in Patients With Ulcerative Colitis.Journal of Crohn's & colitis · 2025Article
- From pathogenic mechanisms to therapeutic perspectives: a review of gut microbiota and intestinal mucosal immunity in inflammatory bowel disease.Frontiers in immunology · 2025Review
- The human milk bacteriome and mycobiome and their inter-kingdom interactions viewed across geography.Frontiers in nutrition · 2025Article
- Metabolic modeling of host-microbe interactions.Computational and structural biotechnology journal · 2025Review
- The Potential Role of Boron in the Modulation of Gut Microbiota Composition: An In Vivo Pilot Study.Pharmaceuticals (Basel, Switzerland) · 2024Article
- Article
- A mouse model of immunosuppression facilitates oralFrontiers in cellular and infection microbiology · 2024Article
- Candida spp. in Human Intestinal Health and Disease: More than a Gut Feeling.Mycopathologia · 2023Review
- Microbiome and metabolome features in inflammatory bowel disease via multi-omics integration analyses across cohorts.Nature communications · 2023Article
- Genome-scale metabolic modeling of Aspergillus fumigatus strains reveals growth dependencies on the lung microbiome.Nature communications · 2023Article
Corrections and comments
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Authors and funding
15 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Candida albicans is a leading cause of life-threatening hospital-acquired infections and can lead to Candidemia with sepsis-like symptoms and high mortality rates. We reconstructed a genome-scale C. albicans metabolic model to investigate bacterial-fungal metabolic interactions in the gut as determinants of fungal abundance. We optimized the predictive capacity of our model using wild type and mutant C. albicans growth data and used it for in silico metabolic interaction predictions. Our analysis of more than 900 paired fungal-bacterial metabolic models predicted key gut bacterial species modulating C. albicans colonization levels. Among the studied microbes, Alistipes putredinis was predicted to negatively affect C. albicans levels. We confirmed these findings by metagenomic sequencing of stool samples from 24 human subjects and by fungal growth experiments in bacterial spent media. Furthermore, our pairwise simulations guided us to specific metabolites with promoting or inhibitory effect to the fungus when exposed in defined media under carbon and nitrogen limitation. Our study demonstrates that in silico metabolic prediction can lead to the identification of gut microbiome features that can significantly affect potentially harmful levels of C. albicans.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.