Pan-omics-based characterization and prediction of highly multidrugadapted strains from an outbreak fungal species complex  

作　　者：Xin Fan Lei Chen Min Chen Na Zhang Hong Chang Mingjie He Zhenghao Shen Lanyue Zhang Hao Ding Yuyan Xie Yemei Huang Weixin Ke Meng Xiao Xuelei Zang Heping Xu Wenxia Fang Shaojie Li Cunwei Cao Yingchun Xu Shiguang Shan Wenjuan Wu Changbin Chen Xinying Xue Linqi Wang 

机构地区：[1]Department of Infectious Diseases and Clinical Microbiology,Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital,Capital Medical University,Beijing 100020,China [2]Beijing Research Center for Respiratory Infectious Diseases,Beijing 100020,China [3]State Key Laboratory of Mycology,Institute of Microbiology,Chinese Academy of Sciences,Beijing 100101,China [4]Department of Dermatology,Shanghai Key Laboratory of Molecular Medical Mycology,Changzheng Hospital,Shanghai 200003,China [5]University of Chinese Academy of Sciences,Beijing 100049,China [6]Key Laboratory of Intelligent Information Processing,Institute of Computing Technology,Chinese Academy of Sciences,Beijing 100190,China [7]Department of Respiratory and Critical Care,Emergency and Critical Care Medical Center,Beijing Shijitan Hospital,Capital Medical University,Beijing 100038,China [8]Department of Laboratory Medicine,State Key Laboratory of Complex Severe and Rare Diseases,Peking Union Medical College Hospital,Chinese Academy of Medical Sciences,Beijing 100730,China [9]Beijing Key Laboratory for Mechanisms Research and Precision Diagnosis of Invasive Fungal Diseases,Beijing 100730,China [10]Department of Clinical Laboratory,First Affiliated Hospital of Xiamen University,Xiamen 361003,China [11]Institute of Biological Science and Technology,Guangxi Academy of Sciences,Nanning 530007,China [12]Department of Dermatology,The First Affiliated Hospital of Guangxi Medical University,Nanning 530021,China [13]Guangxi Key Laboratory of Mycosis Prevention and Treatment,Nanning 530021,China [14]Department of Laboratory Medicine,Shanghai East Hospital,Tongji University School of Medicine,Shanghai 200120,China [15]The Unit of Pathogenic Fungal Infection&Host Immunity,Shanghai Institute of Immunity and Infection,Chinese Academy of Sciences,Shanghai 200031,China [16]Nanjing Advanced Academy of Life and Health,Nanjing 211135,China [17]Department of Respiratory and Critical Care,Shandong Second Medical University,Weifang 261035,China

出　　处：《The Innovation》2024年第5期101-109,100,共10页创新（英文）

基　　金：financially supported by the National Key R&D Program of China(2021YFC2302100);the National Natural Science Foundation of China(82370005 and 82172291);the National Key R&D Program of China(2022YFC2303000 and 2021YFC230000);the CAS Interdisciplinary Innovation Team,the Beijing Research Center for Respiratory Infectious Diseases Project(BJRID2024-008 and BJRID2024-011);the R&D Program of Beijing Municipal Education Commission(KM202410025012);the Reform and Development Program of Beijing Institute of Respiratory Medicine(Ggyfz202328 and Ggyfz202418);the National Key R&D Program of China(2020YFA0907200);Shanghai Science and Technology Innovation Action Plan 2023“Basic Research Project”(23JC1404201);the Shanghai‘‘Belt and Road’’Joint Laboratory Project(22490750200);the National Natural Science Foundation of China(82370005);National High Level Hospital Clinical Research Funding(2022-PUMCH-C-052).

摘　　要：Strains from the Cryptococcus gattii species complex(CGSC)have caused the Pacific Northwest cryptococcosis outbreak,the largest cluster of lifethreatening fungal infections in otherwise healthy human hosts known to date.In this study,we utilized a pan-phenome-based method to assess the fitness outcomes of CGSC strains under 31 stress conditions,providing a comprehensive overview of 2,821 phenotype-strain associations within this pathogenic clade.Phenotypic clustering analysis revealed a strong correlation between distinct types of stress phenotypes in a subset of CGSC strains,suggesting that shared determinants coordinate their adaptations to various stresses.Notably,a specific group of strains,including the outbreak isolates,exhibited a remarkable ability to adapt to all three of the most commonly used antifungal drugs for treating cryptococcosis(amphotericin B,5-fluorocytosine,and fluconazole).By integrating pan-genomic and pan-transcriptomic analyses,we identified previously unrecognized genes that play crucial roles in conferring multidrug resistance in an outbreak strain with high multidrug adaptation.From these genes,we identified biomarkers that enable the accurate prediction of highly multidrug-adapted CGSC strains,achieving maximum accuracy and area under the curve(AUC)of 0.79 and 0.86,respectively,using machine learning algorithms.Overall,we developed a pan-omic approach to identify cryptococcal multidrug resistance determinants and predict highly multidrug-adapted CGSC strains that may pose significant clinical concern.

关 键 词：MULTIDRUG adapted PREDICTION 

分 类 号：R519[医药卫生—内科学]