Immune quorum sensing dictates IFN-I response dynamics in human plasmacytoid dendritic cells.

Type I interferons (IFN-Is) are key in fighting viral infections, but also serve major roles beyond antiviral immunity. Crucial is the tight regulation of IFN-I responses, while excessive levels are harmful to the cells. In essence, immune responses are generated by single cells making their own decisions, which are based on the signals they perceive. Additionally, immune cells must anticipate the future state of their environment, thereby weighing the costs and benefits of each possible outcome, in the presence of other potentially competitive decision makers (i.e., IFN-I producing cells). A rather new cellular communication mechanism called quorum sensing describes the effect of cell density on cellular secretory behaviors, which fits well with matching the right amount of IFN-Is produced to fight an infection. More competitive decision makers must contribute relatively less and vice versa. Intrigued by this concept, we assessed the effects of immune quorum sensing in pDCs, specialized immune cells known for their ability to mass produce IFN-Is. Using conventional microwell assays and droplet-based microfluidics assays, we were able the characterize the effect of quorum sensing in human primary immune cells in vitro. These insights open new avenues to manipulate IFN-I response dynamics in pathological conditions affected by aberrant IFN-I signaling.

Cellular Heterogeneity of Activated Primary Human Macrophages and Associated Drug-Gene Networks: From Biology to Precision Therapeutics.

BACKGROUND: Interferon-γ (IFNγ) signaling plays a complex role in atherogenesis. IFNγ stimulation of macrophages permits in vitro exploration of proinflammatory mechanisms and the development of novel immune therapies. We hypothesized that the study of macrophage subpopulations could lead to anti-inflammatory interventions. METHODS: Primary human macrophages activated by IFNγ (M(IFNγ)) underwent analyses by single-cell RNA sequencing, time-course cell-cluster proteomics, metabolite consumption, immunoassays, and functional tests (phagocytic, efferocytotic, and chemotactic). RNA-sequencing data were analyzed in LINCS (Library of Integrated Network-Based Cellular Signatures) to identify compounds targeting M(IFNγ) subpopulations. The effect of compound BI-2536 was tested in human macrophages in vitro and in a murine model of atherosclerosis. RESULTS: Single-cell RNA sequencing identified 2 major clusters in M(IFNγ): inflammatory (M(IFNγ)i) and phagocytic (M(IFNγ)p). M(IFNγ)i had elevated expression of inflammatory chemokines and higher amino acid consumption compared with M(IFNγ)p. M(IFNγ)p were more phagocytotic and chemotactic with higher Krebs cycle activity and less glycolysis than M(IFNγ)i. Human carotid atherosclerotic plaques contained 2 such macrophage clusters. Bioinformatic LINCS analysis using our RNA-sequencing data identified BI-2536 as a potential compound to decrease the M(IFNγ)i subpopulation. BI-2536 in vitro decreased inflammatory chemokine expression and secretion in M(IFNγ) by shrinking the M(IFNγ)i subpopulation while expanding the M(IFNγ)p subpopulation. BI-2536 in vivo shifted the phenotype of macrophages, modulated inflammation, and decreased atherosclerosis and calcification. CONCLUSIONS: We characterized 2 clusters of macrophages in atherosclerosis and combined our cellular data with a cell-signature drug library to identify a novel compound that targets a subset of macrophages in atherosclerosis. Our approach is a precision medicine strategy to identify new drugs that target atherosclerosis and other inflammatory diseases.

Single-cell analysis reveals TLR-induced macrophage heterogeneity and quorum sensing dictate population wide anti-inflammatory feedback in response to LPS.

The role of macrophages in controlling tissue inflammation is indispensable to ensure a context-appropriate response to pathogens whilst preventing excessive tissue damage. Their initial response is largely characterized by high production of tumor necrosis factor alpha (TNFα) which primes and attracts other immune cells, thereafter, followed by production of interleukin 10 (IL-10) which inhibits cell activation and steers towards resolving of inflammation. This delicate balance is understood at a population level but how it is initiated at a single-cell level remains elusive. Here, we utilize our previously developed droplet approach to probe single-cell macrophage activation in response to toll-like receptor 4 (TLR4) stimulation, and how single-cell heterogeneity and cellular communication affect macrophage-mediated inflammatory homeostasis. We show that only a fraction of macrophages can produce IL-10 in addition to TNFα upon LPS-induced activation, and that these cells are not phenotypically different from IL-10 non-producers nor exhibit a distinct transcriptional pathway. Finally, we demonstrate that the dynamics of TNFα and IL-10 are heavily controlled by macrophage density as evidenced by 3D hydrogel cultures suggesting a potential role for quorum sensing. These exploratory results emphasize the relevance of understanding the complex communication between macrophages and other immune cells and how these amount to population-wide responses.

A Microfluidic Approach for Probing Heterogeneity in Cytotoxic T-Cells by Cell Pairing in Hydrogel Droplets.

Cytotoxic T-cells (CTLs) exhibit strong effector functions to leverage antigen-specific anti-tumoral and anti-viral immunity. When naïve CTLs are activated by antigen-presenting cells (APCs) they display various levels of functional heterogeneity. To investigate this, we developed a single-cell droplet microfluidics platform that allows for deciphering single CTL activation profiles by multi-parameter analysis. We identified and correlated functional heterogeneity based on secretion profiles of IFNγ, TNFα, IL-2, and CD69 and CD25 surface marker expression levels. Furthermore, we strengthened our approach by incorporating low-melting agarose to encapsulate pairs of single CTLs and artificial APCs in hydrogel droplets, thereby preserving spatial information over cell pairs. This approach provides a robust tool for high-throughput and single-cell analysis of CTLs compatible with flow cytometry for subsequent analysis and sorting. The ability to score CTL quality, combined with various potential downstream analyses, could pave the way for the selection of potent CTLs for cell-based therapeutic strategies.