作者
Ci Fu, Xiang Zhang, Amanda O Veri, Kali R Iyer, Emma Lash, Alice Xue, Huijuan Yan, Nicole M Revie, Cassandra Wong, Zhen-Yuan Lin, Elizabeth J Polvi, Sean D Liston, Benjamin VanderSluis, Jing Hou, Yoko Yashiroda, Anne-Claude Gingras, Charles Boone, Teresa R O’Meara, Matthew J O’Meara, Suzanne Noble, Nicole Robbins, Chad L Myers, Leah E Cowen
发表日期
2021/11/11
期刊
Nature Communications
卷号
12
期号
1
页码范围
1-18
出版商
Nature Publishing Group
简介
Fungal pathogens pose a global threat to human health, with Candida albicans among the leading killers. Systematic analysis of essential genes provides a powerful strategy to discover potential antifungal targets. Here, we build a machine learning model to generate genome-wide gene essentiality predictions for C. albicans and expand the largest functional genomics resource in this pathogen (the GRACE collection) by 866 genes. Using this model and chemogenomic analyses, we define the function of three uncharacterized essential genes with roles in kinetochore function, mitochondrial integrity, and translation, and identify the glutaminyl-tRNA synthetase Gln4 as the target of N-pyrimidinyl-β-thiophenylacrylamide (NP-BTA), an antifungal compound.
引用总数
学术搜索中的文章