Linking Indirect Effects of Cytomegalovirus in Transplantation to Modulation of Monocyte Innate Immune Function
Apr 22, 2020·,,
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0 min read
P. sen
A. r. wilkie
F. ji
Yiming Yang
I. j. taylor
M. velazquez palafox
E. a. h. vanni
J. m. pesola
R. fernandez
H. chen
L. m. morsett
E. r. abels
M. piper
R. j. lane
S. e. hickman
T. k. means
E. s. rosenberg
R. i. sadreyev
Dr. Bo Li
D. m. coen
J. a. fishman
J. el khoury
Abstract
Cytomegalovirus (CMV) is an important cause of morbidity and mortality in the immunocompromised host. In transplant recipients, a variety of clinically important “indirect effects” are attributed to immune modulation by CMV, including increased mortality from fungal disease, allograft dysfunction and rejection in solid organ transplantation, and graft-versus-host-disease in stem cell transplantation. Monocytes, key cellular targets of CMV, are permissive to primary, latent and reactivated CMV infection. Here, pairing unbiased bulk and single cell transcriptomics with functional analyses we demonstrate that human monocytes infected with CMV do not effectively phagocytose fungal pathogens, a functional deficit which occurs with decreased expression of fungal recognition receptors. Simultaneously, CMV-infected monocytes upregulate antiviral, pro-inflammatory chemokine, and inflammasome responses associated with allograft rejection and graft-versus-host disease. Our study demonstrates that CMV modulates both immunosuppressive and immunostimulatory monocyte phenotypes, explaining in part, its paradoxical “indirect effects” in transplantation. These data could provide innate immune targets for the stratification and treatment of CMV disease.
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Science Advances
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Bioinformatics Software Engineer
Yiming Yang is a bioinformatics software engineer in Li Lab.
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Principal Scientist II
Dr. Bo Li is a Principal Scientist at Genentech, Inc. His research focuses on large-scale single-cell genomics data analysis.
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.
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