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Updated: Feb 15, 2026

Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3
Published on: December 27, 2010
A Reproducibility-Based Computational Framework Identifies an Inducible, Enhanced Antiviral State in Dendritic Cells
Enrique Martin-Gayo1, Michael B Cole2, Kellie E Kolb1,3,4
1Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA.
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.
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