The Known Unknowns of the Immune Response to Coccidioides

May 11, 2021·
R. a. ward
,
G. r. thompson
,
A. c. villani
Dr. Bo Li
Dr. Bo Li
,
M. k. mansour
,
M. wuethrich
,
J. m. tam
,
B. s. klein
,
J. m. vyas
· 0 min read
Abstract
Coccidioidomycosis, otherwise known as Valley Fever, is caused by the dimorphic fungi Coccidioides immitis and C. posadasii. While most clinical cases present with self-limiting pulmonary infection, dissemination of Coccidioides spp. results in prolonged treatment and portends higher mortality rates. While the structure, genome, and niches for Coccidioides have provided some insight into the pathogenesis of disease, the underlying immunological mechanisms of clearance or inability to contain the infection in the lung are poorly understood. This review focuses on the known innate and adaptive immune responses to Coccidioides and highlights three important areas of uncertainty and potential approaches to address them. Closing these gaps in knowledge may enable new preventative and therapeutic strategies to be pursued.
Type
Publication
Journal of Fungi
Authors
Dr. Bo Li
Authors
Principal Scientist II
Dr. Bo Li is a Principal Scientist II at AI for Biology and Translation (AIBT), Genentech, Inc. His research focuses on three major topics: Science, Technology and Computational Methods. For Science, his team works on lung cancer and especially small cell lung cancer. For Technology, his team evaluates and adopts cutting-edge high-throughput data generation technologies, such as Cellanome and SBX sequencing. For Computational Methods, his team develops novel computational and deep learning tools for enabling insight discovery from high-throughput multi-modal data. Before joining in Genentech, he was an Assistant Professor of Medicine at Harvard Medical School and the director of Bioinformatics and Computational Biology at Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital. He received his Ph.D. in computer science from UW-Madison and completed two postdoctoral trainings with Dr. Lior Pachter at UC Berkeley and Dr. Aviv Regev at Broad Institute. He is best known for developing RSEM, an impactful RNA-seq transcript quantification software. RSEM is cited 22,602 times (Google Scholar) and adopted by several big consortia such as TCGA, ENCODE, GTEx and TOPMed.
Authors
Authors