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Ruifeng Bai,1 Jianqiu Pei,1 Shengqiang Pei,1 Xiangfeng Cong,1 Jerold Chun,2 Fang Wang,1,3,4 Xi Chen1,3 1State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China; 2Neuroscience Drug Discovery, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA; 3Diagnostic Laboratory Service, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China; 4Department of Clinical Laboratory, Fuwai Yunnan Cardiovascular Hospital, Kunming, People’s Republic of ChinaCorrespondence: Xi Chen; Fang Wang, Email chenxifw@pumc.edu.cn; fray.163@163.comBackground: Increased endothelial permeability of pulmonary vessels is a primary pathological characteristic of septic acute lung injury (ALI). Previously, elevated lysophosphatidic acid (LPA) levels and LPA2 (an LPA receptor) expression have been found in the peripheral blood and lungs of septic mice, respectively. However, the specific role of LPA2 in septic ALI remains unclear.Methods: A lipopolysaccharide (LPS)-induced model of sepsis was established in wild-type (WT) and global LPA2 knockout (Lpar2−/−) mice. We examined mortality, lung injury, assessed endothelial permeability through Evans blue dye (EBD) assay in vivo, and transendothelial electrical resistance (TEER) of mouse lung microvascular endothelial cells (MLMECs) in vitro. Enzyme-linked immunosorbent assay (ELISA), histopathological, immunofluorescence, immunohistochemistry, and Western blot were employed to investigate the role of LPA2 in septic ALI.Results: Lpar2 deficiency increased vascular endothelial permeability, impaired lung injury, and increased mortality. Histological examination revealed aggravated inflammation, edema, hemorrhage and alveolar septal thickening in the lungs of septic Lpar2−/− mice. In vitro, loss of Lpar2 resulted in increased permeability of MLMECs. Pharmacological activation of LPA2 by the agonist DBIBB led to significantly reduced inflammation, edema and hemorrhage, as well as increased expression of the vascular endothelial tight junction (TJ) protein zonula occludens-1 (ZO-1) and claudin-5, as well as the adheren junction (AJ) protein VE-cadherin. Moreover, DBIBB treatment was found to alleviate mortality by protecting against vascular endothelial permeability. Mechanistically, we demonstrated that vascular endothelial permeability was alleviated through LPA-LPA2 signaling via the PLC-PKC-FAK pathway.Conclusion: These data provide a novel mechanism of endothelial barrier protection via PLC-PKC-FAK pathway and suggest that LPA2 may contribute to the therapeutic effects of septic ALI.Keywords: septic ALI, LPA, vascular endothelial permeability, LPA2, lung microvascular endothelial cells

The host's gene expression and gene regulatory response to pathogen exposure can be influenced by a combination of the host's genetic background, the type of and exposure time to pathogens. Here we provide a detailed dissection of this using single-cell RNA-sequencing of 1.3M peripheral blood mononuclear cells from 120 individuals, longitudinally exposed to three different pathogens. These analyses indicate that cell-type-specificity is a more prominent factor than pathogen-specificity regarding contexts that affect how genetics influences gene expression (i.e., eQTL) and co-expression (i.e., co-expression QTL). In monocytes, the strongest responder to pathogen stimulations, 71.4% of the genetic variants whose effect on gene expression is influenced by pathogen exposure (i.e., response QTL) also affect the co-expression between genes. This indicates widespread, context-specific changes in gene expression level and its regulation that are driven by genetics. Pathway analysis on the CLEC12A gene that exemplifies cell-type-, exposure-time- and genetic-background-dependent co-expression interactions, shows enrichment of the interferon (IFN) pathway specifically at 3-h post-exposure in monocytes. Similar genetic background-dependent association between IFN activity and CLEC12A co-expression patterns is confirmed in systemic lupus erythematosus by in silico analysis, which implies that CLEC12A might be an IFN-regulated gene. Altogether, this study highlights the importance of context for gaining a better understanding of the mechanisms of gene regulation in health and disease.

BackgroundSingle-cell RNA sequencing (scRNA-seq) provides high-dimensional measurements of transcript counts in individual cells. However, high assay costs and artifacts associated with analyzing samples across multiple sequencing runs limit the study of large numbers of samples. Sample multiplexing technologies such as MULTI-seq and antibody hashing using single-cell multiplexing kit (SCMK) reagents (BD Biosciences) use sample-specific sequence tags to enable individual samples to be sequenced in a pooled format, markedly lowering per-sample processing and sequencing costs while minimizing technical artifacts. Critically, however, pooling samples could introduce new artifacts, partially negating the benefits of sample multiplexing. In particular, no study to date has evaluated whether pooling peripheral blood mononuclear cells (PBMCs) from unrelated donors under standard scRNA-seq sample preparation conditions (e.g., 30 min co-incubation at 4 °C) results in significant changes in gene expression resulting from alloreactivity (i.e., response to non-self). The ability to demonstrate minimal to no alloreactivity is crucial to avoid confounded data analyses, particularly for cross-sectional studies evaluating changes in immunologic gene signatures.ResultsHere, we applied the 10x Genomics scRNA-seq platform to MULTI-seq and/or SCMK-labeled PBMCs from a single donor with and without pooling with PBMCs from unrelated donors for 30 min at 4 °C. We did not detect any alloreactivity signal between mixed and unmixed PBMCs across a variety of metrics, including alloreactivity marker gene expression in CD4+ T cells, cell type proportion shifts, and global gene expression profile comparisons using Gene Set Enrichment Analysis and Jensen-Shannon Divergence. These results were additionally mirrored in publicly-available scRNA-seq data generated using a similar experimental design. Moreover, we identified confounding gene expression signatures linked to PBMC preparation method (e.g., Trima apheresis), as well as SCMK sample classification biases against activated CD4+ T cells which were recapitulated in two other SCMK-incorporating scRNA-seq datasets.ConclusionsWe demonstrate that (i) mixing PBMCs from unrelated donors under standard scRNA-seq sample preparation conditions (e.g., 30 min co-incubation at 4 °C) does not cause an allogeneic response, and (ii) that Trima apheresis and PBMC sample multiplexing using SCMK reagents can introduce undesirable technical artifacts into scRNA-seq data. Collectively, these observations establish important benchmarks for future cross-sectional immunological scRNA-seq experiments.

Acute myeloid leukemia patients refractory to induction therapy or relapsed within one year have poor outcomes. Autocrine production of hepatocyte growth factor by myeloid blasts drives leukemogenesis in pre-clinical models. A phase Ib trial evaluated ficlatuzumab, a first-in-class anti-HGF antibody, in combination with cytarabine in this high-risk population. Dose-limiting toxicities were not observed, and 20 mg/kg was established as the recommended phase II dose. The most frequent treatment-related adverse event was febrile neutropenia. Among 17 evaluable patients, the overall response rate was 53%, all complete remissions. Phospho-proteomic mass cytometry showed potent on-target suppression of p-MET after ficlatuzumab treatment and that attenuation of p-S6 was associated with clinical response. Multiplexed single cell RNA sequencing using prospectively acquired patient specimens identified interferon response genes as adverse predictive factors. The ficlatuzumab and cytarabine combination is well-tolerated with favorable efficacy. High-dimensional analyses at single-cell resolution represent promising approaches for identifying biomarkers of response and mechanisms of resistance in prospective clinical studies.

Although infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has pleiotropic and systemic effects in some individuals1-3, many others experience milder symptoms. Here, to gain a more comprehensive understanding of the distinction between severe and mild phenotypes in the pathology of coronavirus disease 2019 (COVID-19) and its origins, we performed a whole-blood-preserving single-cell analysis protocol to integrate contributions from all major immune cell types of the blood-including neutrophils, monocytes, platelets, lymphocytes and the contents of the serum. Patients with mild COVID-19 exhibit a coordinated pattern of expression of interferon-stimulated genes (ISGs)3 across every cell population, whereas these ISG-expressing cells are systemically absent in patients with severe disease. Paradoxically, individuals with severe COVID-19 produce very high titres of anti-SARS-CoV-2 antibodies and have a lower viral load compared to individuals with mild disease. Examination of the serum from patients with severe COVID-19 shows that these patients uniquely produce antibodies that functionally block the production of the ISG-expressing cells associated with mild disease, by activating conserved signalling circuits that dampen cellular responses to interferons. Overzealous antibody responses pit the immune system against itself in many patients with COVID-19, and perhaps also in individuals with other viral infections. Our findings reveal potential targets for immunotherapies in patients with severe COVID-19 to re-engage viral defence.

COVID-19 has posed a significant threat to global health. Early data has revealed that IL-6, a key regulatory cytokine, plays an important role in the cytokine storm of COVID-19. Multiple trials are therefore looking at the effects of Tocilizumab, an IL-6 receptor antibody that inhibits IL-6 activity, on treatment of COVID-19, with promising findings. As part of a clinical trial looking at the effects of Tocilizumab treatment on kidney transplant recipients with subclinical rejection, we performed single-cell RNA sequencing of comparing stimulated PBMCs before and after Tocilizumab treatment. We leveraged this data to create an in vitro cytokine storm model, to better understand the effects of Tocilizumab in the presence of inflammation. Tocilizumab-treated cells had reduced expression of inflammatory-mediated genes and biologic pathways, particularly amongst monocytes. These results support the hypothesis that Tocilizumab may hinder the cytokine storm of COVID-19, through a demonstration of biologic impact at the single-cell level.

COVID-19 has posed a significant threat to global health. Early data has revealed that IL-6, a key regulatory cytokine, plays an important role in the cytokine storm of COVID-19. Multiple trials are therefore looking at the effects of Tocilizumab, an IL-6 receptor antibody that inhibits IL-6 activity, on treatment of COVID-19, with promising findings. As part of a clinical trial looking at the effects of Tocilizumab treatment on kidney transplant recipients with subclinical rejection, we performed single-cell RNA sequencing of comparing stimulated PBMCs before and after Tocilizumab treatment. We leveraged this data to create an in vitro cytokine storm model, to better understand the effects of Tocilizumab in the presence of inflammation. Tocilizumab-treated cells had reduced expression of inflammatory-mediated genes and biologic pathways, particularly amongst monocytes. These results support the hypothesis that Tocilizumab may hinder the cytokine storm of COVID-19, through a demonstration of biologic impact at the single-cell level.

We present Vision, a tool for annotating the sources of variation in single cell RNA-seq data in an automated and scalable manner. Vision operates directly on the manifold of cell-cell similarity and employs a flexible annotation approach that can operate either with or without preconceived stratification of the cells into groups or along a continuum. We demonstrate the utility of Vision in several case studies and show that it can derive important sources of cellular variation and link them to experimental meta-data even with relatively homogeneous sets of cells. Vision produces an interactive, low latency and feature rich web-based report that can be easily shared among researchers, thus facilitating data dissemination and collaboration.

Differentiation of proinflammatory CD4+ conventional T cells (Tconv) is critical for productive antitumor responses yet their elicitation remains poorly understood. We comprehensively characterized myeloid cells in tumor draining lymph nodes (tdLN) of mice and identified two subsets of conventional type-2 dendritic cells (cDC2) that traffic from tumor to tdLN and present tumor-derived antigens to CD4+ Tconv, but then fail to support antitumor CD4+ Tconv differentiation. Regulatory T cell (Treg) depletion enhanced their capacity to elicit strong CD4+ Tconv responses and ensuing antitumor protection. Analogous cDC2 populations were identified in patients, and as in mice, their abundance relative to Treg predicts protective ICOS+ PD-1lo CD4+ Tconv phenotypes and survival. Further, in melanoma patients with low Treg abundance, intratumoral cDC2 density alone correlates with abundant CD4+ Tconv and with responsiveness to anti-PD-1 therapy. Together, this highlights a pathway that restrains cDC2 and whose reversal enhances CD4+ Tconv abundance and controls tumor growth.

Not just differential gene expression but also differential gene regulation in immune cells account for individual differences in the immune response. Authors show here by single-cell RNA-sequencing of peripheral blood mononuclear cells from a large cohort of genetically diverse individuals that gene expression and regulatory changes in these cells depend on the context of and interactions between cell types, genetics, type of pathogen and time after exposure.

Organogenesis requires the complex interactions of multiple cell lineages that coordinate their expansion, differentiation, and maturation over time. Here, we profile the cell types within the epithelial and mesenchymal compartments of the murine pancreas across developmental time using a combination of single-cell RNA sequencing, immunofluorescence, in situ hybridization, and genetic lineage tracing. We identify previously underappreciated cellular heterogeneity of the developing mesenchyme and reconstruct potential lineage relationships among the pancreatic mesothelium and mesenchymal cell types. Within the epithelium, we find a previously undescribed endocrine progenitor population, as well as an analogous population in both human fetal tissue and human embryonic stem cells differentiating toward a pancreatic beta cell fate. Further, we identify candidate transcriptional regulators along the differentiation trajectory of this population toward the alpha or beta cell lineages. This work establishes a roadmap of pancreatic development and demonstrates the broad utility of this approach for understanding lineage dynamics in developing organs.

Over 90% of genetic variants associated with complex human traits map to non-coding regions, but little is understood about how they modulate gene regulation in health and disease. One possible mechanism is that genetic variants affect the activity of one or more cis-regulatory elements leading to gene expression variation in specific cell types. To identify such cases, we analyzed ATAC-seq and RNA-seq profiles from stimulated primary CD4+ T cells in up to 105 healthy donors. We found that regions of accessible chromatin (ATAC-peaks) are co-accessible at kilobase and megabase resolution, consistent with the three-dimensional chromatin organization measured by in situ Hi-C in T cells. Fifteen percent of genetic variants located within ATAC-peaks affected the accessibility of the corresponding peak (local-ATAC-QTLs). Local-ATAC-QTLs have the largest effects on co-accessible peaks, are associated with gene expression and are enriched for autoimmune disease variants. Our results provide insights into how natural genetic variants modulate cis-regulatory elements, in isolation or in concert, to influence gene expression.

BackgroundEpistasis and gene-environment interactions are known to contribute significantly to variation of complex phenotypes in model organisms. However, their identification in human association studies remains challenging for myriad reasons. In the case of epistatic interactions, the large number of potential interacting sets of genes presents computational, multiple hypothesis correction, and other statistical power issues. In the case of gene-environment interactions, the lack of consistently measured environmental covariates in most disease studies precludes searching for interactions and creates difficulties for replicating studies.ResultsIn this work, we develop a new statistical approach to address these issues that leverages genetic ancestry, defined as the proportion of ancestry derived from each ancestral population (e.g., the fraction of European/African ancestry in African Americans), in admixed populations. We applied our method to gene expression and methylation data from African American and Latino admixed individuals, respectively, identifying nine interactions that were significant at P

Testing for associations in big data faces the problem of multiple comparisons, wherein true signals are difficult to detect on the background of all associations queried. This difficulty is particularly salient in human genetic association studies, in which phenotypic variation is often driven by numerous variants of small effect. The current strategy to improve power to identify these weak associations consists of applying standard marginal statistical approaches and increasing study sample sizes. Although successful, this approach does not leverage the environmental and genetic factors shared among the multiple phenotypes collected in contemporary cohorts. Here we developed covariates for multiphenotype studies (CMS), an approach that improves power when correlated phenotypes are measured on the same samples. Our analyses of real and simulated data provide direct evidence that correlated phenotypes can be used to achieve increases in power to levels often surpassing the power gained by a twofold increase in sample size.

The majority of genetic variants associated with common human diseases map to enhancers, non-coding elements that shape cell-type-specific transcriptional programs and responses to extracellular cues. Systematic mapping of functional enhancers and their biological contexts is required to understand the mechanisms by which variation in non-coding genetic sequences contributes to disease. Functional enhancers can be mapped by genomic sequence disruption, but this approach is limited to the subset of enhancers that are necessary in the particular cellular context being studied. We hypothesized that recruitment of a strong transcriptional activator to an enhancer would be sufficient to drive target gene expression, even if that enhancer was not currently active in the assayed cells. Here we describe a discovery platform that can identify stimulus-responsive enhancers for a target gene independent of stimulus exposure. We used tiled CRISPR activation (CRISPRa) to synthetically recruit a transcriptional activator to sites across large genomic regions (more than 100 kilobases) surrounding two key autoimmunity risk loci, CD69 and IL2RA. We identified several CRISPRa-responsive elements with chromatin features of stimulus-responsive enhancers, including an IL2RA enhancer that harbours an autoimmunity risk variant. Using engineered mouse models, we found that sequence perturbation of the disease-associated Il2ra enhancer did not entirely block Il2ra expression, but rather delayed the timing of gene activation in response to specific extracellular signals. Enhancer deletion skewed polarization of naive T cells towards a pro-inflammatory T helper (TH17) cell state and away from a regulatory T cell state. This integrated approach identifies functional enhancers and reveals how non-coding variation associated with human immune dysfunction alters context-specific gene programs.

Immunotherapies with chimeric antigen receptor (CAR) T cells and checkpoint inhibitors (including antibodies that antagonize programmed cell death protein 1 [PD-1]) have both opened new avenues for cancer treatment, but the clinical potential of combined disruption of inhibitory checkpoints and CAR T cell therapy remains incompletely explored. Here we show that programmed death ligand 1 (PD-L1) expression on tumor cells can render human CAR T cells (anti-CD19 4-1BBζ) hypo-functional, resulting in impaired tumor clearance in a sub-cutaneous xenograft model. To overcome this suppressed anti-tumor response, we developed a protocol for combined Cas9 ribonucleoprotein (Cas9 RNP)-mediated gene editing and lentiviral transduction to generate PD-1 deficient anti-CD19 CAR T cells. Pdcd1 (PD-1) disruption augmented CAR T cell mediated killing of tumor cells in vitro and enhanced clearance of PD-L1+ tumor xenografts in vivo. This study demonstrates improved therapeutic efficacy of Cas9-edited CAR T cells and highlights the potential of precision genome engineering to enhance next-generation cell therapies.

Group 2 innate lymphoid cells (ILC2s) and CD4+ type 2 helper T cells (TH2 cells) are defined by their similar effector cytokines, which together mediate the features of allergic immunity. We found that tissue ILC2s and TH2 cells differentiated independently but shared overlapping effector function programs that were mediated by exposure to the tissue-derived cytokines interleukin 25 (IL-25), IL-33 and thymic stromal lymphopoietin (TSLP). Loss of these three tissue signals did not affect lymph node priming, but abrogated the terminal differentiation of effector TH2 cells and adaptive lung inflammation in a T cell-intrinsic manner. Our findings suggest a mechanism by which diverse perturbations can activate type 2 immunity and reveal a shared local-tissue-elicited checkpoint that can be exploited to control both innate and adaptive allergic inflammation.

The thymus supports T cell immunity by providing the environment for thymocyte differentiation. Here the authors profile human thymic stroma at the single cell level, identifying ionocytes as a new medullary population and defining tissue specific antigen expression in multiple stromal cell types.

Abstract Background Single-cell RNA sequencing (scRNA-seq) provides high-dimensional measurements of transcript counts in individual cells. However, high assay costs and artifacts associated with analyzing samples across multiple sequencing runs limit the study of large numbers of samples. Sample multiplexing technologies such as MULTI-seq and antibody hashing using single-cell multiplexing kit (SCMK) reagents (BD Biosciences) use sample-specific sequence tags to enable individual samples to be sequenced in a pooled format, markedly lowering per-sample processing and sequencing costs while minimizing technical artifacts. Critically, however, pooling samples could introduce new artifacts, partially negating the benefits of sample multiplexing. In particular, no study to date has evaluated whether pooling peripheral blood mononuclear cells (PBMCs) from unrelated donors under standard scRNA-seq sample preparation conditions (e.g., 30 min co-incubation at 4 °C) results in significant changes in gene expression resulting from alloreactivity (i.e., response to non-self). The ability to demonstrate minimal to no alloreactivity is crucial to avoid confounded data analyses, particularly for cross-sectional studies evaluating changes in immunologic gene signatures. Results Here, we applied the 10x Genomics scRNA-seq platform to MULTI-seq and/or SCMK-labeled PBMCs from a single donor with and without pooling with PBMCs from unrelated donors for 30 min at 4 °C. We did not detect any alloreactivity signal between mixed and unmixed PBMCs across a variety of metrics, including alloreactivity marker gene expression in CD4+ T cells, cell type proportion shifts, and global gene expression profile comparisons using Gene Set Enrichment Analysis and Jensen-Shannon Divergence. These results were additionally mirrored in publicly-available scRNA-seq data generated using a similar experimental design. Moreover, we identified confounding gene expression signatures linked to PBMC preparation method (e.g., Trima apheresis), as well as SCMK sample classification biases against activated CD4+ T cells which were recapitulated in two other SCMK-incorporating scRNA-seq datasets. Conclusions We demonstrate that (i) mixing PBMCs from unrelated donors under standard scRNA-seq sample preparation conditions (e.g., 30 min co-incubation at 4 °C) does not cause an allogeneic response, and (ii) that Trima apheresis and PBMC sample multiplexing using SCMK reagents can introduce undesirable technical artifacts into scRNA-seq data. Collectively, these observations establish important benchmarks for future cross-sectional immunological scRNA-seq experiments.

Introduction: The addition of durvalumab after chemoradiation therapy (CRT) in unresectable stage III NSCLC significantly improves survival. The benefit of this approach in elderly patients is controversial given the toxicity associated with CRT and, thus, may be underutilized. We sought to investigate the outcomes of elderly patients treated with CRT without or without durvalumab at our center. Methods: We reviewed all stage III patients with NSCLC treated with CRT between 2018 and 2020. Patients were analyzed on the basis of age: less than 70 years and 70 years and older. The end points evaluated were treatment patterns, toxicity, progression-free survival, and overall survival. Results: The baseline characteristics including Eastern Cooperative Oncology Group performance status and comorbidities were similar among the 115 patients (44 elderly, 71 young). Completion rates of CRT (100%, 97%) and chemotherapy dose intensity (97%, 97%) were high in elderly and young patients, respectively. There was a trend toward increased hospitalizations in elderly patients because of infections (27% versus 13%, p = 0.08). Of those who did not have primary progression after CRT, 78% of eldery and 81% of young patients received durvalumab. The incidence of grade 3 or higher immune-related adverse events was 9% in elderly and 6% in young patients (p = 0.67). The median progression-free survival was similar (15.6 versus 10.5 mo, p = 0.10), even after adjusting for comorbidities (hazard ratio = 0.6, p = 0.09). The 12-month overall survival rates were 78% in the elderly and 76% in young patients (p = 0.98). Conclusions: Well-selected elderly patients can be treated safely with CRT followed by durvalumab with similar survival benefits compared with their younger counterparts. We would advocate for the referral of all elderly patients for oncologic assessment to avoid undertreatment.

T-cell genome engineering holds great promise for cell-based therapies for cancer, HIV, primary immune deficiencies, and autoimmune diseases, but genetic manipulation of human T cells has been challenging. Improved tools are needed to efficiently "knock out" genes and "knock in" targeted genome modifications to modulate T-cell function and correct disease-associated mutations. CRISPR/Cas9 technology is facilitating genome engineering in many cell types, but in human T cells its efficiency has been limited and it has not yet proven useful for targeted nucleotide replacements. Here we report efficient genome engineering in human CD4(+) T cells using Cas9:single-guide RNA ribonucleoproteins (Cas9 RNPs). Cas9 RNPs allowed ablation of CXCR4, a coreceptor for HIV entry. Cas9 RNP electroporation caused up to ∼40% of cells to lose high-level cell-surface expression of CXCR4, and edited cells could be enriched by sorting based on low CXCR4 expression. Importantly, Cas9 RNPs paired with homology-directed repair template oligonucleotides generated a high frequency of targeted genome modifications in primary T cells. Targeted nucleotide replacement was achieved in CXCR4 and PD-1 (PDCD1), a regulator of T-cell exhaustion that is a validated target for tumor immunotherapy. Deep sequencing of a target site confirmed that Cas9 RNPs generated knock-in genome modifications with up to ∼20% efficiency, which accounted for up to approximately one-third of total editing events. These results establish Cas9 RNP technology for diverse experimental and therapeutic genome engineering applications in primary human T cells.