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

Genome Biol. 2018 Jan 29;19(1):10. doi: 10.1186/s13059-017-1385-x.

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: Adjuvant; Dendritic cell; Differential expression; Elite controller; HIV-1; Reproducibility; Single-cell RNA-seq; Single-cell genomics.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Biomarkers / metabolism
  • Dendritic Cells / classification
  • Dendritic Cells / immunology*
  • Gene Expression Profiling
  • Genomics
  • HIV Infections / immunology*
  • HIV-1*
  • Humans
  • Reproducibility of Results
  • Sequence Analysis, RNA*
  • Single-Cell Analysis

Substances

  • Biomarkers

Grant support