title: Highly multiplexed profiling of single-cell effector functions reveals deep functional heterogeneity in response to pathogenic ligands.
abstract: Despite recent advances in single-cell genomic, transcriptional, and mass-cytometric profiling, it remains a challenge to collect highly multiplexed measurements of secreted proteins from single cells for comprehensive analysis of functional states. Herein, we combine spatial and spectral encoding with polydimethylsiloxane (PDMS) microchambers for codetection of 42 immune effector proteins secreted from single cells, representing the highest multiplexing recorded to date for a single-cell secretion assay. Using this platform to profile differentiated macrophages stimulated with lipopolysaccharide (LPS), the ligand of Toll-like receptor 4 (TLR4), reveals previously unobserved deep functional heterogeneity and varying levels of pathogenic activation. Uniquely protein profiling on the same single cells before and after LPS stimulation identified a role for macrophage inhibitory factor (MIF) to potentiate the activation of LPS-induced cytokine production. Advanced clustering analysis identified functional subsets including quiescent, polyfunctional fully activated, partially activated populations with different cytokine profiles. This population architecture is conserved throughout the cell activation process and prevails as it is extended to other TLR ligands and to primary macrophages derived from a healthy donor. This work demonstrates that the phenotypically similar cell population still exhibits a large degree of intrinsic heterogeneity at the functional and cell behavior level. This technology enables full-spectrum dissection of immune functional states in response to pathogenic or environmental stimulation, and opens opportunities to quantify deep functional heterogeneity for more comprehensive and accurate immune monitoring.
authors: Department of Biomedical Engineering, Yale University, New Haven, CT 06520;
authors: Yao
authors: Y
authors: Lu
authors: Department of Biomedical Engineering, Yale University, New Haven, CT 06520;
authors: Qiong
authors: Q
authors: Xue
authors: Department of Biomedical Engineering, Yale University, New Haven, CT 06520; Institute for System Dynamics, University of Stuttgart, D-70563 Stuttgart, Germany;
authors: Markus R
authors: MR
authors: Eisele
authors: Department of Biomedical Engineering, Yale University, New Haven, CT 06520;
authors: Endah S
authors: ES
authors: Sulistijo
authors: IsoPlexis, New Haven, CT 06511;
authors: Kara
authors: K
authors: Brower
authors: Department of Biomedical Engineering, Yale University, New Haven, CT 06520;
authors: Lin
authors: L
authors: Han
authors: Department of Biological Sciences, Columbia University, New York, NY 10027;
authors: El-Ad David
authors: el-AD
authors: Amir
authors: Department of Biological Sciences, Columbia University, New York, NY 10027;
authors: Dana
authors: D
authors: Pe'er
authors: Department of Biomedical Engineering, Yale University, New Haven, CT 06520; Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520; Yale Comprehensive Cancer Center, New Haven, CT 06520; and rong.fan@yale.edu Kathryn.miller-jensen@yale.edu.
authors: Kathryn
authors: K
authors: Miller-Jensen
authors: Department of Biomedical Engineering, Yale University, New Haven, CT 06520; Yale Comprehensive Cancer Center, New Haven, CT 06520; and Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520 rong.fan@yale.edu Kathryn.miller-jensen@yale.edu.
authors: Rong
authors: R
authors: Fan
mesh_terms: D006801:Humans; D008024:Ligands; D008070:Lipopolysaccharides / Q000494:pharmacology; D008264:Macrophages / Q000187:drug effects / Q000378:metabolism; D059010:Single-Cell Analysis; D051197:Toll-Like Receptor 4 / Q000378:metabolism; D020298:U937 Cells; D014774:Virulence
chemical_list: D008024:Ligands; D008070:Lipopolysaccharides; C495345:TLR4 protein, human; D051197:Toll-Like Receptor 4
keywords: Toll-like receptor activation; cellular heterogeneity; cytokine; immune effector function; single-cell analysis
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