학술논문
Identification of drug candidates targeting monocyte reprogramming in people living with HIV
Document Type
article
Author
Rainer Knoll; Lorenzo Bonaguro; Jéssica C. dos Santos; Stefanie Warnat-Herresthal; Maartje C. P. Jacobs-Cleophas; Edda Blümel; Nico Reusch; Arik Horne; Miriam Herbert; Melanie Nuesch-Germano; Twan Otten; Wouter A. van der Heijden; Lisa van de Wijer; Alex K. Shalek; Kristian Händler; Matthias Becker; Marc D. Beyer; Mihai G. Netea; Leo A. B. Joosten; Andre J. A. M. van der Ven; Joachim L. Schultze; Anna C. Aschenbrenner
Source
Frontiers in Immunology, Vol 14 (2023)
Subject
Language
English
ISSN
1664-3224
Abstract
IntroductionPeople living with HIV (PLHIV) are characterized by functional reprogramming of innate immune cells even after long-term antiretroviral therapy (ART). In order to assess technical feasibility of omics technologies for application to larger cohorts, we compared multiple omics data layers.MethodsBulk and single-cell transcriptomics, flow cytometry, proteomics, chromatin landscape analysis by ATAC-seq as well as ex vivo drug stimulation were performed in a small number of blood samples derived from PLHIV and healthy controls from the 200-HIV cohort study.ResultsSingle-cell RNA-seq analysis revealed that most immune cells in peripheral blood of PLHIV are altered in their transcriptomes and that a specific functional monocyte state previously described in acute HIV infection is still existing in PLHIV while other monocyte cell states are only occurring acute infection. Further, a reverse transcriptome approach on a rather small number of PLHIV was sufficient to identify drug candidates for reversing the transcriptional phenotype of monocytes in PLHIV.DiscussionThese scientific findings and technological advancements for clinical application of single-cell transcriptomics form the basis for the larger 2000-HIV multicenter cohort study on PLHIV, for which a combination of bulk and single-cell transcriptomics will be included as the leading technology to determine disease endotypes in PLHIV and to predict disease trajectories and outcomes.