Systems Biology & Bioinformatics Unit, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute, 07745, Jena, Germany.
ZIK Septomics, Jena University Hospital, 07745, Jena, Germany.
ISME J. 2021 May;15(5):1257-1270. doi: 10.1038/s41396-020-00848-z. Epub 2020 Dec 15.
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.
白色念珠菌是一种导致危及生命的医院获得性感染的主要原因，它可能导致伴有败血症样症状和高死亡率的念珠菌血症。我们构建了一个基于基因组规模的白色念珠菌代谢模型，以研究肠道中的细菌-真菌代谢相互作用作为真菌丰度的决定因素。我们使用野生型和突变型白色念珠菌生长数据优化了我们模型的预测能力，并将其用于模拟代谢相互作用预测。我们对超过 900 对真菌-细菌代谢模型的分析预测了调节白色念珠菌定植水平的关键肠道细菌物种。在所研究的微生物中，预测腐败希瓦氏菌（Alistipes putredinis）会对白色念珠菌的水平产生负面影响。我们通过对 24 个人类粪便样本的宏基因组测序和在细菌废弃培养基中进行真菌生长实验证实了这些发现。此外，我们的成对模拟指导我们确定了在特定的碳氮限制条件下，在定义的培养基中暴露时对真菌具有促进或抑制作用的特定代谢物。我们的研究表明，基于计算机的代谢预测可以识别出肠道微生物组特征，这些特征可能会显著影响白色念珠菌的潜在有害水平。
