Integrated Single-Cell Analysis of Multicellular Immune Dynamics During Hyperacute HIV-1 Infection

March 23, 2020

Publication type

Journal Article

Journal

Nature Medicine

Volume and Number

26(4)

Authors

Kazer SW, Aicher TP, Muema DM, Carroll SL, Ordovas-Montanes J, Miao VN, Tu AA, Ziegler CGK, Nyquist SK, Wong EB, Ismail N, Dong M, Moodley A, Berger B, Love JC, Dong KL, Leslie A, Ndhlovu ZM, Ndung’u T, Walker BD, Shalek AK

Abstract

Cellular immunity is critical for controlling intracellular pathogens, but individual cellular dynamics and cell-cell cooperativity in evolving human immune responses remain poorly understood. Single-cell RNA-sequencing (scRNA-seq) represents a powerful tool for dissecting complex multicellular behaviors in health and disease1,2 and nominating testable therapeutic targets3. Its application to longitudinal samples could afford an opportunity to uncover cellular factors associated with the evolution of disease progression without potentially confounding inter-individual variability4. Here, we present an experimental and computational methodology that uses scRNA-seq to characterize dynamic cellular programs and their molecular drivers, and apply it to HIV infection. By performing scRNA-seq on peripheral blood mononuclear cells from four untreated individuals before and longitudinally during acute infection5, we were powered within each to discover gene response modules that vary by time and cell subset. Beyond previously unappreciated individual- and cell-type-specific interferon-stimulated gene upregulation, we describe temporally aligned gene expression responses obscured in bulk analyses, including those involved in proinflammatory T cell differentiation, prolonged monocyte major histocompatibility complex II upregulation and persistent natural killer (NK) cell cytolytic killing. We further identify response features arising in the first weeks of infection, for example proliferating natural killer cells, which potentially may associate with future viral control. Overall, our approach provides a unified framework for characterizing multiple dynamic cellular responses and their coordination.