Reframing macrophage diversity with network motifs.

A binary classification of macrophage activation as inflammatory or resolving does not capture the diversity of macrophage states observed in tissues. However, framing macrophage activation as a continuous spectrum of states overlooks the intracellular and extracellular networks that regulate and coordinate macrophage responses. Here, we suggest that the systems biology concept of network motifs, which incorporate rules of local molecular interactions, is useful for reframing macrophage activation. Because network motifs can be used to regulate distinct biological functions, they offer a simplified unit that can be compared across organismal, tissue, and disease contexts. Moreover, defining macrophage states as combinations of functional modules regulated by network motifs offers a framework to ultimately predict and target macrophage responses arising in complex environments.

Single-Cell Analysis Reveals a Subset of High IL-12p40-Secreting Dendritic Cells within Mouse Bone Marrow-Derived Macrophages Differentiated with M-CSF.

Macrophages and dendritic cells (DCs), although ontogenetically distinct, have overlapping functions and exhibit substantial cell-to-cell heterogeneity that can complicate their identification and obscure innate immune function. In this study, we report that M-CSF-differentiated murine bone marrow-derived macrophages (BMDMs) exhibit extreme heterogeneity in the production of IL-12, a key proinflammatory cytokine linking innate and adaptive immunity. A microwell secretion assay revealed that a small fraction of BMDMs stimulated with LPS secrete most IL-12p40, and we confirmed that this is due to extremely high expression of Il12b, the gene encoding IL-12p40, in a subset of cells. Using an Il12b-YFP reporter mouse, we isolated cells with high LPS-induced Il12b expression and found that this subset was enriched for genes associated with the DC lineage. Single-cell RNA sequencing data confirmed a DC-like subset that differentiates within BMDM cultures that is transcriptionally distinct but could not be isolated by surface marker expression. Although not readily apparent in the resting state, upon LPS stimulation, this subset exhibited a typical DC-associated activation program that is distinct from LPS-induced stochastic BMDM cell-to-cell heterogeneity. Overall, our findings underscore the difficulty in distinguishing macrophages and DCs even in widely used in vitro murine BMDM cultures and could affect the interpretation of some studies that use BMDMs to explore acute inflammatory responses.

A bedside to bench study of anti-PD-1, anti-CD40, and anti-CSF1R indicates that more is not necessarily better.

BACKGROUND: Stimulating inflammatory tumor associated macrophages can overcome resistance to PD-(L)1 blockade. We previously conducted a phase I trial of cabiralizumab (anti-CSF1R), sotigalimab (CD40-agonist) and nivolumab. Our current purpose was to study the activity and cellular effects of this three-drug regimen in anti-PD-1-resistant melanoma. METHODS: We employed a Simon's two-stage design and analyzed circulating immune cells from patients treated with this regimen for treatment-related changes. We assessed various dose levels of anti-CSF1R in murine melanoma models and studied the cellular and molecular effects. RESULTS: Thirteen patients were enrolled in the first stage. We observed one (7.7%) confirmed and one (7.7%) unconfirmed partial response, 5 patients had stable disease (38.5%) and 6 disease progression (42.6%). We elected not to proceed to the second stage. CyTOF analysis revealed a reduction in non-classical monocytes. Patients with prolonged stable disease or partial response who remained on study for longer had increased markers of antigen presentation after treatment compared to patients whose disease progressed rapidly. In a murine model, higher anti-CSF1R doses resulted in increased tumor growth and worse survival. Using single-cell RNA-sequencing, we identified a suppressive monocyte/macrophage population in murine tumors exposed to higher doses. CONCLUSIONS: Higher anti-CSF1R doses are inferior to lower doses in a preclinical model, inducing a suppressive macrophage population, and potentially explaining the disappointing results observed in patients. While it is impossible to directly infer human doses from murine studies, careful intra-species evaluation can provide important insight. Cabiralizumab dose optimization is necessary for this patient population with limited treatment options. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03502330.

A transcriptional cycling model recapitulates chromatin-dependent features of noisy inducible transcription.

Activation of gene expression in response to environmental cues results in substantial phenotypic heterogeneity between cells that can impact a wide range of outcomes including differentiation, viral activation, and drug resistance. An important source of gene expression noise is transcriptional bursting, or the process by which transcripts are produced during infrequent bursts of promoter activity. Chromatin accessibility impacts transcriptional bursting by regulating the assembly of transcription factor and polymerase complexes on promoters, suggesting that the effect of an activating signal on transcriptional noise will depend on the initial chromatin state at the promoter. To explore this possibility, we simulated transcriptional activation using a transcriptional cycling model with three promoter states that represent chromatin remodeling, polymerase binding and pause release. We initiated this model over a large parameter range representing target genes with different chromatin environments, and found that, upon increasing the polymerase pause release rate to activate transcription, changes in gene expression noise varied significantly across initial promoter states. This model captured phenotypic differences in activation of latent HIV viruses integrated at different chromatin locations and mediated by the transcription factor NF-κB. Activating transcription in the model via increasing one or more of the transcript production rates, as occurs following NF-κB activation, reproduced experimentally measured transcript distributions for four different latent HIV viruses, as well as the bimodal pattern of HIV protein expression that leads to a subset of reactivated virus. Importantly, the parameter 'activation path' differentially affected gene expression noise, and ultimately viral activation, in line with experimental observations. This work demonstrates how upstream signaling pathways can be connected to biological processes that underlie transcriptional bursting, resulting in target gene-specific noise profiles following stimulation of a single upstream pathway.

TNF stimulation primarily modulates transcriptional burst size of NF-κB-regulated genes.

Cell-to-cell heterogeneity is a feature of the tumor necrosis factor (TNF)-stimulated inflammatory response mediated by the transcription factor NF-κB, motivating an exploration of the underlying sources of this noise. Here, we combined single-transcript measurements with computational models to study transcriptional noise at six NF-κB-regulated inflammatory genes. In the basal state, NF-κB-target genes displayed an inverse correlation between mean and noise characteristic of transcriptional bursting. By analyzing transcript distributions with a bursting model, we found that TNF primarily activated transcription by increasing burst size while maintaining burst frequency for gene promoters with relatively high basal histone 3 acetylation (AcH3) that marks open chromatin environments. For promoters with lower basal AcH3 or when AcH3 was decreased with a small molecule drug, the contribution of burst frequency to TNF activation increased. Finally, we used a mathematical model to show that TNF positive feedback amplified gene expression noise resulting from burst size-mediated transcription, leading to a subset of cells with high TNF protein expression. Our results reveal potential sources of noise underlying intercellular heterogeneity in the TNF-mediated inflammatory response.

Fold-Change Detection of NF-κB at Target Genes with Different Transcript Outputs.

The transcription factor nuclear factor (NF)-κB promotes inflammatory and stress-responsive gene transcription across a range of cell types in response to the cytokine tumor necrosis factor (TNF). Although NF-κB signaling exhibits significant variability across single cells, some target genes supporting high levels of TNF-inducible transcription exhibit fold-change detection of NF-κB, which may buffer against stochastic variation in signaling molecules. It is unknown whether fold-change detection is maintained at NF-κB target genes with low levels of TNF-inducible transcription, for which stochastic promoter events may be more pronounced. Here, we used a microfluidic cell-trapping device to measure how TNF-induced activation of NF-κB controls transcription in single Jurkat T cells at the promoters of integrated HIV and the endogenous cytokine gene IL6, which produce only a few transcripts per cell. We tracked TNF-stimulated NF-κB RelA nuclear translocation by live-cell imaging and then quantified transcript number by RNA FISH in the same cell. We found that TNF-induced transcript abundance at 2 h for low- and high-abundance target genes correlates with similar strength with the fold change in nuclear NF-κB. A computational model of TNF-NF-κB signaling, which implements fold-change detection from competition for binding to κB motifs, could reproduce fold-change detection across the experimentally measured range of transcript outputs. However, multiple model parameters affecting transcription had to be simultaneously varied across promoters to maintain fold-change detection while also matching other trends in the single-cell data for low-abundance transcripts. Our results suggest that cells use multiple biological mechanisms to tune transcriptional output while maintaining robustness of NF-κB fold-change detection.

Tumor Necrosis Factor-α and IL-17A Activation Induces Pericyte-Mediated Basement Membrane Remodeling in Human Neutrophilic Dermatoses.

Sweet syndrome (SS) is a prototypical neutrophilic dermatosis, a class of inflammatory diseases marked by elevated levels of tumor necrosis factor (TNF)-α and IL-17A, pathologic neutrophil recruitment, and microvascular remodeling. Histologic analyses of four matrix proteins-collagen I and IV, laminin, and fibronectin-in skin biopsies of patients with SS reveal that the basement membrane of dermal postcapillary venules undergoes changes in structure and composition. Increased neutrophil recruitment in vivo was associated with increases in collagen IV, decreases in laminin, and varied changes in fibronectin. In vitro studies using TNF-α and IL-17A were conducted to dissect basement membrane remodeling. Prolonged dual activation of cultured human pericytes with TNF-α and IL-17A augmented collagen IV production, similar to in vivo remodeling. Co-activation of pericytes with TNF-α and IL-17A also elevated fibronectin levels with little direct effect on laminin. However, the expression of fibronectin- and laminin-specific matrix metalloproteinases (MMPs), particularly MMP-3, was significantly up-regulated. Interactions between pericytes and neutrophils in culture yielded even higher levels of active MMPs, facilitating fibronectin and laminin degradation, and likely contributing to the varied levels of detectable fibronectin and the decreases in laminin observed in vivo. These data indicate that pericyte-neutrophil interactions play a role in mediating microvascular changes in SS and suggest that targeting MMP-3 may be effective in protecting vascular wall integrity.

Highly multiplexed profiling of single-cell effector functions reveals deep functional heterogeneity in response to pathogenic ligands.

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.

Genetic selection for context-dependent stochastic phenotypes: Sp1 and TATA mutations increase phenotypic noise in HIV-1 gene expression.

The sequence of a promoter within a genome does not uniquely determine gene expression levels and their variability; rather, promoter sequence can additionally interact with its location in the genome, or genomic context, to shape eukaryotic gene expression. Retroviruses, such as human immunodeficiency virus-1 (HIV), integrate their genomes into those of their host and thereby provide a biomedically-relevant model system to quantitatively explore the relationship between promoter sequence, genomic context, and noise-driven variability on viral gene expression. Using an in vitro model of the HIV Tat-mediated positive-feedback loop, we previously demonstrated that fluctuations in viral Tat-transactivating protein levels generate integration-site-dependent, stochastically-driven phenotypes, in which infected cells randomly 'switch' between high and low expressing states in a manner that may be related to viral latency. Here we extended this model and designed a forward genetic screen to systematically identify genetic elements in the HIV LTR promoter that modulate the fraction of genomic integrations that specify 'Switching' phenotypes. Our screen identified mutations in core promoter regions, including Sp1 and TATA transcription factor binding sites, which increased the Switching fraction several fold. By integrating single-cell experiments with computational modeling, we further investigated the mechanism of Switching-fraction enhancement for a selected Sp1 mutation. Our experimental observations demonstrated that the Sp1 mutation both impaired Tat-transactivated expression and also altered basal expression in the absence of Tat. Computational analysis demonstrated that the observed change in basal expression could contribute significantly to the observed increase in viral integrations that specify a Switching phenotype, provided that the selected mutation affected Tat-mediated noise amplification differentially across genomic contexts. Our study thus demonstrates a methodology to identify and characterize promoter elements that affect the distribution of stochastic phenotypes over genomic contexts, and advances our understanding of how promoter mutations may control the frequency of latent HIV infection.

High-throughput secretomic analysis of single cells to assess functional cellular heterogeneity.

Secreted proteins dictate a range of cellular functions in human health and disease. Because of 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 subnanoliter 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.

Common effector processing mediates cell-specific responses to stimuli.

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.

Functionally and Metabolically Divergent Melanoma-Associated Macrophages Originate from Common Bone-Marrow Precursors.

Tumor-associated macrophages (TAMs) can be widely heterogeneous, based on their ontogeny and function, and driven by the tissue-specific niche. TAMs are highly abundant in the melanoma tumor microenvironment (TME), usually correlating with worse prognoses. However, the understanding of their diversity may be harnessed for therapeutic purposes. Here, we used the clinically relevant YUMM1.7 model to study melanoma TAM origin and dynamics during tumor progression. In i.d. YUMM1.7 tumors, we identified distinct TAM subsets based on F4/80 expression, with the F4/80high fraction increasing over time and displaying a tissue-resident-like phenotype. While skin-resident macrophages showed mixed ontogeny, F4/80+ TAM subsets in the melanoma TME originated almost exclusively from bone-marrow precursors. A multiparametric analysis of the macrophage phenotype showed a temporal divergence of the F4/80+ TAM subpopulations, which also differed from the skin-resident subsets and their monocytic precursors. Overall, the F4/80+ TAMs displayed co-expressions of M1- and M2-like canonical markers, while RNA sequencing showed differential immunosuppressive and metabolic profiles. Gene-set enrichment analysis (GSEA) revealed F4/80high TAMs to rely on oxidative phosphorylation, with increased proliferation and protein secretion, while F4/80low cells had high pro-inflammatory and intracellular signaling pathways, with lipid and polyamine metabolism. Overall, we provide an in-depth characterization of and compelling evidence for the BM-dependency of melanoma TAMs. Interestingly, the transcriptomic analysis of these BM-derived TAMs matched macrophage subsets with mixed ontogeny, which have been observed in other tumor models. Our findings may serve as a guide for identifying potential ways of targeting specific immunosuppressive TAMs in melanoma.

Functionally and metabolically divergent melanoma-associated macrophages originate from common bone-marrow precursors.

Melanomas display high numbers of tumor-associated macrophages (TAMs), which correlate with worse prognosis. Harnessing macrophages for therapeutic purposes has been particularly challenging due to their heterogeneity, based on their ontogeny and function and driven by the tissue-specific niche. In the present study, we used the YUMM1.7 model to better understand melanoma TAM origin and dynamics during tumor progression, with potential therapeutic implications. We identified distinct TAM subsets based on F4/80 expression, with the F4/80 high fraction increasing over time and displaying tissue-resident-like phenotype. While skin-resident macrophages showed mixed on-togeny, F4/80 + TAM subsets in i.d. YUMM1.7 tumors originated almost exclusively from bone-marrow precursors. Mul-tiparametric analysis of macrophage phenotype showed a temporal divergence of F4/80 + TAM subpopulations, which also differed from skin-resident subsets, and from their monocytic precursors. Overall, F4/80 + TAMs displayed co-ex-pression of M1- and M2-like canonical markers, while RNA-seq and pathway analysis showed differential immunosup-pressive and metabolic profiles. GSEA showed F4/80 high TAMs to rely on oxidative phosphorylation, with increased proliferation and protein secretion while F4/80 low cells had high pro-inflammatory and intracellular signaling pathways, with lipid and polyamine metabolism. Overall, the present in-depth characterization provides further evidence of the ontogeny of the evolving melanoma TAMs, whose gene expression profiles matched recently-identified TAM clusters in other tumor models and human cancers. These findings provide evidence for potentially targeting specific immunosup-pressive TAMs in advanced tumor stages.

Apoptosis recognition receptors regulate skin tissue repair in mice.

Apoptosis and clearance of apoptotic cells via efferocytosis are evolutionarily conserved processes that drive tissue repair. However, the mechanisms by which recognition and clearance of apoptotic cells regulate repair are not fully understood. Here, we use single-cell RNA sequencing to provide a map of the cellular dynamics during early inflammation in mouse skin wounds. We find that apoptotic pathways and efferocytosis receptors are elevated in fibroblasts and immune cells, including resident Lyve1 + macrophages, during inflammation. Interestingly, human diabetic foot wounds upregulate mRNAs for apoptotic genes and display increased and altered efferocytosis signaling via the receptor Axl. During early inflammation in mouse wounds, we detect upregulation of Axl in dendritic cells and fibroblasts via TLR3-independent mechanisms. Inhibition studies in vivo in mice reveal that Axl signaling is required for wound repair but is dispensable for efferocytosis. By contrast, inhibition of another efferocytosis receptor, Timd4, in mouse wounds decreases efferocytosis and abrogates wound repair. These data highlight the distinct mechanisms by which apoptotic cell detection coordinates tissue repair and provides potential therapeutic targets for chronic wounds in diabetic patients.

Apoptosis recognition receptors regulate skin tissue repair in mice.

Apoptosis and clearance of apoptotic cells via efferocytosis are evolutionarily conserved processes that drive tissue repair. However, the mechanisms by which recognition and clearance of apoptotic cells regulate repair are not fully understood. Here, we use single-cell RNA sequencing to provide a map of the cellular dynamics during early inflammation in mouse skin wounds. We find that apoptotic pathways and efferocytosis receptors are elevated in fibroblasts and immune cells, including resident Lyve1+ macrophages, during inflammation. Interestingly, human diabetic foot wounds upregulate mRNAs for efferocytosis pathway genes and display altered efferocytosis signaling via the receptor Axl and its ligand Gas6. During early inflammation in mouse wounds, we detect upregulation of Axl in dendritic cells and fibroblasts via TLR3-independent mechanisms. Inhibition studies in vivo in mice reveal that Axl signaling is required for wound repair but is dispensable for efferocytosis. By contrast, inhibition of another efferocytosis receptor, Timd4, in mouse wounds decreases efferocytosis and abrogates wound repair. These data highlight the distinct mechanisms by which apoptotic cell detection coordinates tissue repair and provides potential therapeutic targets for chronic wounds in diabetic patients.

Our skin is constantly exposed to potential damage from the outside world, and it is vital that any injuries are repaired quickly and effectively. Diabetes and many other health conditions can hamper wound healing, resulting in chronic wounds that are both painful and at risk of becoming infected, which can lead to serious illness and death of patients. After an injury to the skin, the wound becomes inflamed as immune cells rush to the site of injury to fight off infection and clear the wound of dead cells and debris. Some of these dead cells will have died by a highly controlled process known as apoptosis. These so-called apoptotic cells display signals on their surface that nearby healthy cells recognize. This triggers the healthy cells to eat the apoptotic cells to remove them from the wound. Previous studies have linked changes in cell death and the removal of dead cells to chronic wounds in patients with diabetes, but it remains unclear how removing dead cells from the wound affects healing. Justynski et al. used a genetic technique called single-cell RNA sequencing to study the patterns of gene activity in mouse skin cells shortly after a wound. The experiments found that, as the area around the wound started to become inflamed, the wounded cells produced signals of apoptosis that in turn triggered nearby healthy cells to remove them. Other signals relating to the removal of dead cells were also widespread in the mouse wounds and treating the wounds with drugs that inhibit these signals resulted in multiple defects in the healing process. Further experiments used the same approach to study samples of tissue taken from foot wounds in human patients with or without diabetes. This revealed that several genes involved in the removal of dead cells were more highly expressed in the wounds of diabetic patients than in the wounds of other individuals. These findings indicate that for wounds to heal properly it is crucial for the body to detect and clear apoptotic cells from the wound site. Further studies building on this work may help to explain why some diabetic patients suffer from chronic wounds and help to develop more effective treatments for them.

Combinatorial Immunotherapy with Agonistic CD40 Activates Dendritic Cells to Express IL12 and Overcomes PD-1 Resistance.

Checkpoint inhibitors have revolutionized cancer treatment, but resistance remains a significant clinical challenge. Myeloid cells within the tumor microenvironment can modulate checkpoint resistance by either supporting or suppressing adaptive immune responses. Using an anti-PD-1-resistant mouse melanoma model, we show that targeting the myeloid compartment via CD40 activation and CSF1R blockade in combination with anti-PD-1 results in complete tumor regression in a majority of mice. This triple therapy combination was primarily CD40 agonist-driven in the first 24 hours after therapy and showed a similar systemic cytokine profile in human patients as was seen in mice. Functional single-cell cytokine secretion profiling of dendritic cells (DC) using a novel microwell assay identified a CCL22+CCL5+ IL12-secreting DC subset as important early-stage effectors of triple therapy. CD4+ and CD8+ T cells are both critical effectors of treatment, and systems analysis of single-cell RNA sequencing data supported a role for DC-secreted IL12 in priming T-cell activation and recruitment. Finally, we showed that treatment with a novel IL12 mRNA therapeutic alone was sufficient to overcome PD-1 resistance and cause tumor regression. Overall, we conclude that combining myeloid-based innate immune activation and enhancement of adaptive immunity is a viable strategy to overcome anti-PD-1 resistance.

Mapping and Validation of scRNA-Seq-Derived Cell-Cell Communication Networks in the Tumor Microenvironment.

Recent advances in single-cell technologies, particularly single-cell RNA-sequencing (scRNA-seq), have permitted high throughput transcriptional profiling of a wide variety of biological systems. As scRNA-seq supports inference of cell-cell communication, this technology has and continues to anchor groundbreaking studies into the efficacy and mechanism of novel immunotherapies for cancer treatment. In this review, we will highlight methods developed to infer inter- and intracellular signaling from scRNA-seq and discuss how they have contributed to studies of immunotherapeutic intervention in the tumor microenvironment (TME). However, a central challenge remains in validating the hypothesized cell-cell interactions. Therefore, this review will also cover strategies for integration of these scRNA-seq-derived interaction networks with existing experimental and computational approaches. Integration of these networks with imaging, protein secretion measurements, and network analysis and mathematical modeling tools addresses challenges that remain with scRNA-seq to enhance studies of immunosuppressive and immunotherapy-altered signaling in the TME.

Langerhans cells are essential components of the angiogenic niche during murine skin repair.

Angiogenesis, the growth of new blood vessels from pre-existing vessels, occurs during development, injury repair, and tumorigenesis to deliver oxygen, immune cells, and nutrients to tissues. Defects in angiogenesis occur in cardiovascular and inflammatory diseases, and chronic, non-healing wounds, yet treatment options are limited. Here, we provide a map of the early angiogenic niche by analyzing single-cell RNA sequencing of mouse skin wound healing. Our data implicate Langerhans cells (LCs), phagocytic, skin-resident immune cells, in driving angiogenesis during skin repair. Using lineage-driven reportersw, three-dimensional (3D) microscopy, and mouse genetics, we show that LCs are situated at the endothelial cell leading edge in mouse skin wounds and are necessary for angiogenesis during repair. These data provide additional future avenues for the control of angiogenesis to treat disease and chronic wounds and extend the function of LCs beyond their canonical role in antigen presentation and T cell immunity.

Control of stochastic gene expression by host factors at the HIV promoter.

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-kappaB 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-kappaB 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-kappaB sites exhibit distinct properties, with kappaB site I serving a stronger activating role than kappaB 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-kappaB 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.

Single-cell secretion analysis reveals a dual role for IL-10 in restraining and resolving the TLR4-induced inflammatory response.

Following Toll-like receptor 4 (TLR4) stimulation of macrophages, negative feedback mediated by the anti-inflammatory cytokine interleukin-10 (IL-10) limits the inflammatory response. However, extensive cell-to-cell variability in TLR4-stimulated cytokine secretion raises questions about how negative feedback is robustly implemented. To explore this, we characterize the TLR4-stimulated secretion program in primary murine macrophages using a single-cell microwell assay that enables evaluation of functional autocrine IL-10 signaling. High-dimensional analysis of single-cell data reveals three tiers of TLR4-induced proinflammatory activation based on levels of cytokine secretion. Surprisingly, while IL-10 inhibits TLR4-induced activation in the highest tier, it also contributes to the TLR4-induced activation threshold by regulating which cells transition from non-secreting to secreting states. This role for IL-10 in restraining TLR4 inflammatory activation is largely mediated by intermediate interferon (IFN)-ß signaling, while TNF likely mediates response resolution by IL-10. Thus, cell-to-cell variability in cytokine regulatory motifs provides a means to tailor the TLR4-induced inflammatory response.