During tissue repair, myofibroblasts produce extracellular matrix (ECM) molecules for tissue resilience and strength. Altered ECM deposition can lead to tissue dysfunction and disease. Identification of distinct myofibroblast subsets is necessary to develop treatments for these disorders. Here, using extensive analysis of pro-fibrotic cells during mouse skin wound healing, fibrosis and aging; we identify distinct subpopulations of myofibroblasts, including cells identified as adipocyte precursors (APs). Multiple mouse models and transplantation assays demonstrate that AP proliferation, and not other myofibroblasts, is activated by CD301b-expressing macrophages through IGF1 and PDGFC. With age, wound bed APs and differential gene expression between myofibroblast subsets are reduced. Our findings identify multiple fibrotic cell populations and suggest the environment dictates functional myofibroblast heterogeneity, which is driven by fibroblast-immune interactions after wounding.

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 fullspectrum 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.single-cell analysis | cytokine | immune effector function | cellular heterogeneity | Toll-like receptor activation E merging evidence indicates that cell-to-cell variability can give rise to phenotypic differences within a genetically identical cell population (1, 2). Nongenetic heterogeneity is also emerging as a potential barrier to effective therapeutic intervention (3, 4). Recent advances in single-cell molecular profiling are beginning to address these questions. Single-cell RNA sequencing revealed dynamic and bimodal gene expression (5). Single-cell multicolor flow cytometry (6) and mass cytometry (7) can quantify phenotypic diversity and differential drug response even across the hematopoietic continuum. Although a limited number of signaling proteins can be measured using intracellular staining, most of these technologies measure transcriptional or phenotypic marker expression in single cells. It remains an unmet need to directly measure cellular functional outcomes in a highly multiplexed manner and in single cells. In the immune system, the immune effector functions are largely mediated by a panel of effector proteins (e.g., cytokines and chemokines) secreted from single cells. Due to phenotypic plasticity and functional diversity, immune cells purified for a well-defined phenot...

The fundamental components of many signalling pathways are common to all cells. However, stimulating or perturbing the intracellular network often causes distinct phenotypes that are specific to a given cell type. This 'cell specificity' presents a challenge in understanding how intracellular networks regulate cell behaviour and an obstacle to developing drugs that treat signalling dysfunctions. Here we apply a systems-modelling approach to investigate how cell-specific signalling events are integrated through effector proteins to cause cell-specific outcomes. We focus on the synergy between tumour necrosis factor and an adenoviral vector as a therapeutically relevant stimulus that induces cell-specific responses. By constructing models that estimate how kinase-signalling events are processed into phenotypes through effector substrates, we find that accurate predictions of cell specificity are possible when different cell types share a common 'effector-processing' mechanism. Partial-least-squares regression models based on common effector processing accurately predict cell-specific apoptosis, chemokine release, gene induction, and drug sensitivity across divergent epithelial cell lines. We conclude that cell specificity originates from the differential activation of kinases and other upstream transducers, which together enable different cell types to use common effectors to generate diverse outcomes. The common processing of network signals by downstream effectors points towards an important cell biological principle, which can be applied to the understanding of cell-specific responses to targeted drug therapies.

Secreted proteins dictate a range of cellular functions in human health and disease. Due to the high degree of cellular heterogeneity and, more importantly, polyfunctionality of individual cells, there is an unmet need to simultaneously measure an array of proteins from single cells and to rapidly assay a large number of single cells (more than 1000) in parallel. We describe a simple bioanalytical assay platform consisting of a large array of sub-nanoliter microchambers integrated with high-density antibody barcode microarrays for highly multiplexed protein detection from over a thousand single cells in parallel. This platform has been tested for both cell lines and complex biological samples such as primary cells from patients. We observed distinct heterogeneity among the single cell secretomic signatures that, for the first time, can be directly correlated to the cells’ physical behavior such as migration. Compared to the state-of-the-art protein secretion assay such as ELISpot and emerging microtechnology-enabled assays, our approach offers both high throughput and high multiplicity. It also has a number of clinician-friendly features such as ease of operation, low sample consumption and standardized data analysis, representing a potentially transformative tool for informative monitoring of cellular function and immunity in patients.

The HIV promoter within the viral long terminal repeat (LTR) orchestrates many aspects of the viral life cycle, from the dynamics of viral gene expression and replication to the establishment of a latent state. In particular, after viral integration into the host genome, stochastic fluctuations in viral gene expression amplified by the Tat positive feedback loop can contribute to the formation of either a productive, transactivated state or an inactive state. In a significant fraction of cells harboring an integrated copy of the HIV-1 model provirus (LTR-GFP-IRES-Tat), this bimodal gene expression profile is dynamic, as cells spontaneously and continuously flip between active (Bright) and inactive (Off) expression modes. Furthermore, these switching dynamics may contribute to the establishment and maintenance of proviral latency, because after viral integration long delays in gene expression can occur before viral transactivation. The HIV-1 promoter contains cis-acting Sp1 and NF-κB elements that regulate gene expression via the recruitment of both activating and repressing complexes. We hypothesized that interplay in the recruitment of such positive and negative factors could modulate the stability of the Bright and Off modes and thereby alter the sensitivity of viral gene expression to stochastic fluctuations in the Tat feedback loop. Using model lentivirus variants with mutations introduced in the Sp1 and NF-κB elements, we employed flow cytometry, mRNA quantification, pharmacological perturbations, and chromatin immunoprecipitation to reveal significant functional differences in contributions of each site to viral gene regulation. Specifically, the Sp1 sites apparently stabilize both the Bright and the Off states, such that their mutation promotes noisy gene expression and reduction in the regulation of histone acetylation and deacetylation. Furthermore, the NF-κB sites exhibit distinct properties, with κB site I serving a stronger activating role than κB site II. Moreover, Sp1 site III plays a particularly important role in the recruitment of both p300 and RelA to the promoter. Finally, analysis of 362 clonal cell populations infected with the viral variants revealed that mutations in any of the Sp1 sites yield a 6-fold higher frequency of clonal bifurcation compared to that of the wild-type promoter. Thus, each Sp1 and NF-κB site differentially contributes to the regulation of viral gene expression, and Sp1 sites functionally “dampen” transcriptional noise and thereby modulate the frequency and maintenance of this model of viral latency. These results may have biomedical implications for the treatment of HIV latency.

Cellular responses are mediated by heterogeneous intermediate signals that are secreted and sensed by the same cells. Cell-to-cell communication through these intermediate signals likely affects the collective response of cells within a population. We combined multiplexed, microwell-based measurements of cytokine secretion by single cells with data from the analysis of cell populations to determine the role of paracrine signaling in shaping the profile of inflammatory cytokines secreted by macrophages in response to the stimulation of Toll-like receptor 4 (TLR4) with lipopolysaccharide (LPS). Loss of paracrine signaling as a result of cell isolation substantially reduced the secretion of a subset of LPS-stimulated cytokines, including interleukin-6 (IL-6) and IL-10, by macrophage-like U937 cells and human monocyte-derived macrophages (MDMs). Graphical Gaussian modeling (GGM) of the single-cell data defined a regulatory network of paracrine signals, which was validated experimentally in the population through antibody-mediated neutralization of individual cytokines. Tumor necrosis factor-α (TNF-α) was identified as the most influential cytokine in the GGM network, and our data suggest that paracrine signaling from a small subpopulation of “high-secreting” cells, which generated most of the TNF-α produced, was necessary but not sufficient to achieve high secretion of IL-6 and IL-10 in the cell population. Decreased IL-10 secretion in isolated MDMs was linked to increased TNF-α secretion, suggesting that inhibition of the inflammatory response also depends on paracrine signaling. Our results reveal a previously uncharacterized role for cell-to-cell communication within a population in coordinating a rapid and reliable innate immune response in spite of underlying cell-to-cell heterogeneity.

SUMMARY Noisy gene expression generates diverse phenotypes, but little is known about mechanisms that modulate noise. Combining experiments and modeling, we studied how tumor necrosis factor (TNF) initiates noisy expression of latent HIV via the transcription factor nuclear factor κB (NF-κB) and how the HIV genomic integration site modulates noise to generate divergent (low-versus-high) phenotypes of viral activation. We show that TNF-induced transcriptional noise varies more than mean transcript number and that amplification of this noise explains low-versus-high viral activation. For a given integration site, live-cell imaging shows that NF-κB activation correlates with viral activation, but across integration sites, NF-κB activation cannot account for differences in transcriptional noise and phenotypes. Instead, differences in transcriptional noise are associated with differences in chromatin state and RNA polymerase II regulation. We conclude that, whereas NF-κB regulates transcript abundance in each cell, the chromatin environment modulates noise in the population to support diverse HIV activation in response to TNF.

Perry et al. show that myeloid-targeted immunotherapy with a combination of anti-CD40 and CSF-1R inhibition synergistically induces a proinflammatory microenvironment that suppresses CPI-resistant tumors in a TNF-α– and IFN-γ–dependent manner.