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A Reproducibility-Based Computational Framework Identifies an Inducible, Enhanced Antiviral State in Dendritic Cells from HIV-1 Elite Controllers

Author(s)
Martin-Gayo, Enrique; Cole, Michael B.; Ouyang, Zhengyu; Cronin, Jacqueline; Lichterfeld, Mathias; Walker, Bruce D.; Yosef, Nir; Yu, Xu G.; Kolb, Kellie Elizabeth; Kazer, Samuel Weisgurt; Ordovas-Montanes, Jose Manuel; Shalek, Alexander K; ... Show more Show less
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Abstract
BACKGROUND: Human immunity relies on the coordinated responses of many cellular subsets and functional states. Inter-individual variations in cellular composition and communication could thus potentially alter host protection. Here, we explore this hypothesis by applying single-cell RNA-sequencing to examine viral responses among the dendritic cells (DCs) of three elite controllers (ECs) of HIV-1 infection. RESULTS: To overcome the potentially confounding effects of donor-to-donor variability, we present a generally applicable computational framework for identifying reproducible patterns in gene expression across donors who share a unifying classification. Applying it, we discover a highly functional antiviral DC state in ECs whose fractional abundance after in vitro exposure to HIV-1 correlates with higher CD4+ T cell counts and lower HIV-1 viral loads, and that effectively primes polyfunctional T cell responses in vitro. By integrating information from existing genomic databases into our reproducibility-based analysis, we identify and validate select immunomodulators that increase the fractional abundance of this state in primary peripheral blood mononuclear cells from healthy individuals in vitro. CONCLUSIONS: Overall, our results demonstrate how single-cell approaches can reveal previously unappreciated, yet important, immune behaviors and empower rational frameworks for modulating systems-level immune responses that may prove therapeutically and prophylactically useful. Keywords: HIV-1; dendritic cell; single-cell; RNA-seq; single-cell genomics; elite controller; adjuvant; reproducibility; differential expression
Date issued
2018-01
URI
http://hdl.handle.net/1721.1/113421
Department
Massachusetts Institute of Technology. Institute for Medical Engineering & Science; Massachusetts Institute of Technology. Department of Chemistry
Journal
Genome Biology
Publisher
Biomed Central Ltd
Citation
Martin-Gayo, Enrique et al. “A Reproducibility-Based Computational Framework Identifies an Inducible, Enhanced Antiviral State in Dendritic Cells from HIV-1 Elite Controllers.” Genome Biology 19, 1 (January 2018): 10 © 2018 The Author(s)
Version: Final published version
ISSN
1474-760X

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