SBI members publishing in the prestigious ISME Journal

Metabolic modeling predicts specific gut bacteria as key determinants for Candida albicans colonization levels

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Candida albicans is a leading cause of life-threatening nosocomial infections and can lead to Candidemia with sepsis-like symptoms and high mortality rates. Mohammad H. Mirhakkak, Sascha Schäuble, Daniel Loos and Yueqiong Ni from the Systems Biology and Bioinformatics group (SBI) headed by Gianni Panagiotou analysed whether the gut provides key microbes that hamper C. albicans colonization levels. For this, SBI co-workers reconstructed a computer based metabolism map of the fungus and simulated it together with already available computer based microbe models to study their interaction. They identified that only a few microbes affect notably C. albicans growth. Especially their prediction of the gut microbe Alistipes putredinis (phylum Bacteroidetes) could be confirmed across a range of wet-lab experiments (including in vitro growth as well as human stool based metagenomics experiments). Their findings not only showed convincingly that the concept of genome-scale metabolic modeling can substantially speed up target identification, but also proposed target species that can help preventing fungal overgrowth by e.g. supplementing human diets with health beneficial ingredients or health promoting gut microbes.

Original publication:

Mirhakkak M, Schäuble S, Klassert T, Brunke S, Brandt P, Loos D, Uribe R, de Oliveira Lino FS, Ni Y, Vylkova S, Slevogt H, Hube B, Weiss G, Sommer M, Panagiotou G (2020) Metabolic modeling predicts specific gut bacteria as key determinants for Candida albicans colonization levels. ISME J. DOI