Scalable, compressed phenotypic screening using pooled perturbations.

High-throughput phenotypic screens using biochemical perturbations and high-content readouts are constrained by limitations of scale. To address this, we establish a method of pooling exogenous perturbations followed by computational deconvolution to reduce required sample size, labor and cost. We demonstrate the increased efficiency of compressed experimental designs compared to conventional approaches through benchmarking with a bioactive small-molecule library and a high-content imaging readout. We then apply compressed screening in two biological discovery campaigns. In the first, we use early-passage pancreatic cancer organoids to map transcriptional responses to a library of recombinant tumor microenvironment protein ligands, uncovering reproducible phenotypic shifts induced by specific ligands distinct from canonical reference signatures and correlated with clinical outcome. In the second, we identify the pleotropic modulatory effects of a chemical compound library with known mechanisms of action on primary human peripheral blood mononuclear cell immune responses. In sum, our approach empowers phenotypic screens with information-rich readouts to advance drug discovery efforts and basic biological inquiry.

Carbohydrate-Lectin Interactions Reprogram Dendritic Cells to Promote Type 1 Anti-Tumor Immunity.

Cancer vaccine development is inhibited by a lack of strategies for directing dendritic cell (DC) induction of effective tumor-specific cellular immunity. Pathogen engagement of DC lectins and toll-like receptors (TLRs) is thought to shape immunity by directing T cell function. Controlling downstream responses, however, remains a major challenge. A critical goal in advancing vaccine development involves the identification of receptors that drive type 1 cellular immunity. The immune system monitors cells for aberrant glycosylation (a sign of a foreign entity), but potent activation occurs when a second signal, such as single-stranded RNA or lipopolysaccharide, is present to activate TLR signaling. To exploit dual signaling, we engineered a glycan-costumed virus-like particle (VLP) vaccine that displays a DC-SIGN-selective aryl mannose ligand and encapsulates TLR7 agonists. These VLPs deliver programmable peptide antigens to induce robust DC activation and type 1 cellular immunity. In contrast, VLPs lacking this critical DC-SIGN ligand promoted DC-mediated humoral immunity, offering limited tumor control. Vaccination with glycan-costumed VLPs generated tumor antigen-specific Th1 CD4+ and CD8+ T cells that infiltrated solid tumors, significantly inhibiting tumor growth in a murine melanoma model. The tailored VLPs also afforded protection against the reintroduction of tumor cells. Thus, DC lectin-driven immune reprogramming, combined with the modular programmability of VLP platforms, provides a promising framework for directing cellular immunity to advance cancer immunotherapies and vaccines.

LAT encodes T cell activation pathway balance.

Immune cells transduce environmental stimuli into responses essential for host health via complex signaling cascades. T cells, in particular, leverage their unique T cell receptors (TCRs) to detect specific Human Leukocyte Antigen (HLA)-presented peptides. TCR activation is then relayed via linker for activation of T cells (LAT), a TCR-proximal disordered adapter protein, which organizes protein partners and mediates the propagation of signals down diverse pathways including NFAT and AP-1. Here, we studied how balanced downstream pathway activation is encoded in the amino acid sequence of LAT. To comprehensively profile the sequence-function relationship of LAT, we developed a pooled, single-cell, high-content screening approach in which a large series of mutants in the LAT protein were analyzed to characterize their effects on T cell activation. Measuring epigenetic, transcriptomic, and cell surface protein dynamics of single cells harboring distinct LAT mutants, we found functional regions spanning over 40% of the LAT amino acid sequence. Conserved sequence motifs for protein interactions along with charge distribution are critical sequence features, and contribute to interpretation of human genetic variation in LAT. While mutant defect severity spans from moderate to complete loss of function, nearly all defective mutants, irrespective of their position in LAT, confer balanced defects across all downstream pathways. To understand the molecular basis for this observation, we performed proximal protein labeling which demonstrated that disruption of LAT interaction with a single partner protein indirectly disrupts other partner interactions, likely through the dual roles of these proteins as effectors of downstream pathways and bridging factors between LAT molecules. Overall, we report widely distributed functional regions throughout a disordered adapter and a precise physical organization of LAT and interacting molecules which constrains signaling outputs. More broadly, we describe an approach for interrogating sequence-function relationships for proteins with complex activities across regulatory layers of the cell.

Cancer tissue of origin constrains the growth and metabolism of metastases.

Metastases arise from subsets of cancer cells that disseminate from the primary tumour1,2. The ability of cancer cells to thrive in a new tissue site is influenced by genetic and epigenetic changes that are important for disease initiation and progression, but these factors alone do not predict if and where cancers metastasize3,4. Specific cancer types metastasize to consistent subsets of tissues, suggesting that primary tumour-associated factors influence where cancers can grow. We find primary and metastatic pancreatic tumours have metabolic similarities and that the tumour-initiating capacity and proliferation of both primary-derived and metastasis-derived cells is favoured in the primary site relative to the metastatic site. Moreover, propagating cells as tumours in the lung or the liver does not enhance their relative ability to form large tumours in those sites, change their preference to grow in the primary site, nor stably alter aspects of their metabolism relative to primary tumours. Primary liver and lung cancer cells also exhibit a preference to grow in their primary site relative to metastatic sites. These data suggest cancer tissue of origin influences both primary and metastatic tumour metabolism and may impact where cancer cells can metastasize.

CD4+ T cells re-wire granuloma cellularity and regulatory networks to promote immunomodulation following Mtb reinfection.

Immunological priming-in the context of either prior infection or vaccination-elicits protective responses against subsequent Mycobacterium tuberculosis (Mtb) infection. However, the changes that occur in the lung cellular milieu post-primary Mtb infection and their contributions to protection upon reinfection remain poorly understood. Using clinical and microbiological endpoints in a non-human primate reinfection model, we demonstrated that prior Mtb infection elicited a long-lasting protective response against subsequent Mtb exposure and was CD4+ T cell dependent. By analyzing data from primary infection, reinfection, and reinfection-CD4+ T cell-depleted granulomas, we found that the presence of CD4+ T cells during reinfection resulted in a less inflammatory lung milieu characterized by reprogrammed CD8+ T cells, reduced neutrophilia, and blunted type 1 immune signaling among myeloid cells. These results open avenues for developing vaccines and therapeutics that not only target lymphocytes but also modulate innate immune cells to limit tuberculosis (TB) disease.

Distinct olfactory mucosal macrophage populations mediate neuronal maintenance and pathogen defense.

The olfactory mucosa is important for both the sense of smell and as a mucosal immune barrier to the upper airway and brain. However, little is known about how the immune system mediates the conflicting goals of neuronal maintenance and inflammation in this tissue. A number of immune cell populations reside within the olfactory mucosa and yet we have little understanding of how these resident olfactory immune cells functionally interact with the chemosensory environment. Identifying these interactions will allow therapeutic manipulations that treat disorders such as post-viral olfactory dysfunction. Macrophages are the most prevalent immune cell type in the uninflamed olfactory mucosa and here, we identify two distinct tissue macrophage populations in murine olfactory mucosa. P2ry12hi macrophages are transcriptionally specialized for neuron interactions, closely associated with olfactory neuron cell bodies, long-term tissue residents, and functionally specialized to phagocytose cells and debris, including olfactory neurons. Conversely, MHC Class IIhi macrophages are transcriptionally dedicated to cytokine production and antigen presentation, localized primarily within the olfactory lamina propria, more rapidly replaced by blood monocytes, and rapidly produce chemokines in response to viral infection. We further show that these macrophage signatures are present in human olfactory biopsies, and P2ry12-like olfactory macrophages are reduced in patients with long-term smell loss following COVID-19. Together, these data show that two olfactory macrophage populations regulate neurons and initiate the immune response, contributing to our understanding of both olfactory immunity and tissue-resident macrophage biology.

Mechanisms of resistance to oncogenic KRAS inhibition in pancreatic cancer.

KRAS inhibitors demonstrate clinical efficacy in pancreatic ductal adenocarcinoma (PDAC); however, resistance is common. Among patients with KRASG12C-mutant PDAC treated with adagrasib or sotorasib, mutations in PIK3CA and KRAS, and amplifications of KRASG12C, MYC, MET, EGFR, and CDK6 emerged at acquired resistance. In PDAC cell lines and organoid models treated with the KRASG12D inhibitor MRTX1133, epithelial-to-mesenchymal transition and PI3K-AKT-mTOR signaling associate with resistance to therapy. MRTX1133 treatment of the KrasLSL-G12D/+;Trp53LSL-R172H/+;p48-Cre (KPC) mouse model yielded deep tumor regressions, but drug resistance ultimately emerged, accompanied by amplifications of Kras, Yap1, Myc, and Cdk6/Abcb1a/b, and co-evolution of drug-resistant transcriptional programs. Moreover, in KPC and PDX models, mesenchymal and basal-like cell states displayed increased response to KRAS inhibition compared to the classical state. Combination treatment with KRASG12D inhibition and chemotherapy significantly improved tumor control in PDAC mouse models. Collectively, these data elucidate co-evolving resistance mechanisms to KRAS inhibition and support multiple combination therapy strategies.

Single-cell and spatiotemporal profile of ovulation in the mouse ovary.

Ovulation is a spatiotemporally coordinated process that involves several tightly controlled events, including oocyte meiotic maturation, cumulus expansion, follicle wall rupture and repair, and ovarian stroma remodeling. To date, no studies have detailed the precise window of ovulation at single-cell resolution. Here, we performed parallel single-cell RNA-seq and spatial transcriptomics on paired mouse ovaries across an ovulation time course to map the spatiotemporal profile of ovarian cell types. We show that major ovarian cell types exhibit time-dependent transcriptional states enriched for distinct functions and have specific localization profiles within the ovary. We also identified gene markers for ovulation-dependent cell states and validated these using orthogonal methods. Finally, we performed cell-cell interaction analyses to identify ligand-receptor pairs that may drive ovulation, revealing previously unappreciated interactions. Taken together, our data provides a rich and comprehensive resource of murine ovulation that can be mined for discovery by the scientific community.

B cell activation gene signature in blood and liver of HBeAg+ immune active chronic hepatitis B patients.

BACKGROUND: Immunological studies on chronic hepatitis B virus (HBV) infection have convincingly shown immune dysfunction involving multiple cell types. The focus of the majority of studies has been on the role of T cells and showed an impaired functional T cell response to HBV. B cells have been evaluated more recently, but in contrast to T cells, more pronounced activation of circulating B cells has been reported. To gain more insight into the activation status of B cells, we investigated the activation gene profile of B cells in the blood and liver of chronic HBV patients. METHODS: RNA-seq and flow cytometric analysis was performed on peripheral blood B cells of immune active chronic HBV patients, comparing them with samples from healthy controls. In addition, gene expression profiles of B cells in the liver were analyzed by bulk and single-cell RNA-seq. RESULTS AND CONCLUSIONS: Our data show a distinctive B cell activation gene signature in the blood of immune active chronic HBV patients, characterized by a significant upregulation of immune-related genes, including IRF1, STAT1, STAT3, TAP1, and TAPBP. This peripheral activation profile was also observed in B cells from the liver by single cell RNA-seq showing upregulation of IRF1, CD83 and significantly higher CD69 expression, with naive and memory B cell subsets being the primary carriers of the signature. Our findings suggest that B cell gene profiles reflect responsiveness to HBV infection, these findings are relevant for clinical studies evaluating immunomodulatory treatment strategies for HBV.

Mutation and cell state compatibility is required and targetable in Ph+ acute lymphoblastic leukemia minimal residual disease.

Efforts to cure BCR::ABL1 B cell acute lymphoblastic leukemia (Ph+ ALL) solely through inhibition of ABL1 kinase activity have thus far been insufficient despite the availability of tyrosine kinase inhibitors (TKIs) with broad activity against resistance mutants. The mechanisms that drive persistence within minimal residual disease (MRD) remain poorly understood and therefore untargeted. Utilizing 13 patient-derived xenograft (PDX) models and clinical trial specimens of Ph+ ALL, we examined how genetic and transcriptional features co-evolve to drive progression during prolonged TKI response. Our work reveals a landscape of cooperative mutational and transcriptional escape mechanisms that differ from those causing resistance to first generation TKIs. By analyzing MRD during remission, we show that the same resistance mutation can either increase or decrease cellular fitness depending on transcriptional state. We further demonstrate that directly targeting transcriptional state-associated vulnerabilities at MRD can overcome BCR::ABL1 independence, suggesting a new paradigm for rationally eradicating MRD prior to relapse. Finally, we illustrate how cell mass measurements of leukemia cells can be used to rapidly monitor dominant transcriptional features of Ph+ ALL to help rationally guide therapeutic selection from low-input samples.

B cell heterogeneity in human tuberculosis highlights compartment-specific phenotype and functional roles.

B cells are important in tuberculosis (TB) immunity, but their role in the human lung is understudied. Here, we characterize B cells from lung tissue and matched blood of patients with TB and found they are decreased in the blood and increased in the lungs, consistent with recruitment to infected tissue, where they are located in granuloma associated lymphoid tissue. Flow cytometry and transcriptomics identify multiple B cell populations in the lung, including those associated with tissue resident memory, germinal centers, antibody secretion, proinflammatory atypical B cells, and regulatory B cells, some of which are expanded in TB disease. Additionally, TB lungs contain high levels of Mtb-reactive antibodies, specifically IgM, which promotes Mtb phagocytosis. Overall, these data reveal the presence of functionally diverse B cell subsets in the lungs of patients with TB and suggest several potential localized roles that may represent a target for interventions to promote immunity or mitigate immunopathology.

Intrahepatic plasma cells, but not atypical memory B cells, associate with clinical phases of chronic hepatitis B.

Studies have traditionally focused on the role of T cells in chronic hepatitis B (CHB), but recent evidence supports a role for B cells. The enrichment of so-called atypical memory (AtM) B cells, which show reduced signaling and impaired differentiation, is believed to be a characteristic feature of CHB, potentially contributing to the observed dysfunctional anti-HBsAg B-cell responses. Our study, involving 62 CHB patients across clinical phases, identified AtM B cells expressing IFNLR1 and interferon-stimulated genes. Contrary to previous reports, we found relatively low frequencies of AtM B cells in the liver, comparable to peripheral blood. However, liver plasma cell frequencies were significantly higher, particularly during phases with elevated viral loads and liver enzyme levels. Liver plasma cells exhibited signs of active proliferation, especially in the immune active phase. Our findings suggest a potential role for plasma cells, alongside potential implications and consequences of local proliferation, within the livers of CHB patients. While the significance of AtM B cells remains uncertain, further investigation is warranted to determine their responsiveness to interferons and their role in CHB.

Cross-domain information fusion for enhanced cell population delineation in single-cell spatial-omics data.

Cell population delineation and identification is an essential step in single-cell and spatial-omics studies. Spatial-omics technologies can simultaneously measure information from three complementary domains related to this task: expression levels of a panel of molecular biomarkers at single-cell resolution, relative positions of cells, and images of tissue sections, but existing computational methods for performing this task on single-cell spatial-omics datasets often relinquish information from one or more domains. The additional reliance on the availability of "atlas" training or reference datasets limits cell type discovery to well-defined but limited cell population labels, thus posing major challenges for using these methods in practice. Successful integration of all three domains presents an opportunity for uncovering cell populations that are functionally stratified by their spatial contexts at cellular and tissue levels: the key motivation for employing spatial-omics technologies in the first place. In this work, we introduce Cell Spatio- and Neighborhood-informed Annotation and Patterning (CellSNAP), a self-supervised computational method that learns a representation vector for each cell in tissue samples measured by spatial-omics technologies at the single-cell or finer resolution. The learned representation vector fuses information about the corresponding cell across all three aforementioned domains. By applying CellSNAP to datasets spanning both spatial proteomic and spatial transcriptomic modalities, and across different tissue types and disease settings, we show that CellSNAP markedly enhances de novo discovery of biologically relevant cell populations at fine granularity, beyond current approaches, by fully integrating cells' molecular profiles with cellular neighborhood and tissue image information.

AAV5 Delivery of CRISPR/Cas9 Mediates Genome Editing in the Lungs of Young Rhesus Monkeys.

Genome editing has the potential to treat genetic diseases in a variety of tissues, including the lung. We have previously developed and validated a dual adeno-associated virus (AAV) CRISPR platform that supports effective editing in the airways of mice. To validate this delivery vehicle in a large animal model, we have shown that intratracheal instillation of CRISPR/Cas9 in AAV5 can edit a housekeeping gene or a disease-related gene in the lungs of young rhesus monkeys. We observed up to 8% editing of angiotensin-converting enzyme 2 (ACE2) in lung lobes after single-dose administration. Single-nuclear RNA sequencing revealed that AAV5 transduces multiple cell types in the caudal lung lobes, including alveolar cells, macrophages, fibroblasts, endothelial cells, and B cells. These results demonstrate that AAV5 is efficient in the delivery of CRISPR/Cas9 in the lung lobes of young rhesus monkeys.

B-cell-directed CAR T-cell therapy activates CD8+ cytotoxic CARneg bystander T cells in patients and nonhuman primates.

ABSTRACT: Chimeric antigen receptor (CAR) T cells hold promise as a therapy for B-cell-derived malignancies, and despite their impressive initial response rates, a significant proportion of patients ultimately experience relapse. Although recent studies have explored the mechanisms of in vivo CAR T-cell function, little is understood about the activation of surrounding CARneg bystander T cells and their potential to enhance tumor responses. We performed single-cell RNA sequencing on nonhuman primate (NHP) and patient-derived T cells to identify the phenotypic and transcriptomic hallmarks of bystander activation of CARneg T cells following B-cell-targeted CAR T-cell therapy. Using a highly translatable CD20 CAR NHP model, we observed a distinct population of activated CD8+ CARneg T cells emerging during CAR T-cell expansion. These bystander CD8+ CARneg T cells exhibited a unique transcriptional signature with upregulation of natural killer-cell markers (KIR3DL2, CD160, and KLRD1), chemokines, and chemokine receptors (CCL5, XCL1, and CCR9), and downregulation of naïve T-cell-associated genes (SELL and CD28). A transcriptionally similar population was identified in patients after a tisagenlecleucel infusion. Mechanistic studies revealed that interleukin-2 (IL-2) and IL-15 exposure induced bystander-like CD8+ T cells in a dose-dependent manner. In vitro activated and patient-derived T cells with a bystander phenotype efficiently killed leukemic cells through a T-cell receptor-independent mechanism. Collectively, to our knowledge, these data provide the first comprehensive identification and profiling of CARneg bystander CD8+ T cells following B-cell-targeting CAR T-cell therapy and suggest a novel mechanism through which CAR T-cell infusion might trigger enhanced antileukemic responses. Patient samples were obtained from the trial #NCT03369353, registered at www.ClinicalTrials.gov.

An enhanced IL17 and muted type I interferon nasal epithelial cell state characterizes severe COVID-19 with fungal coinfection.

Recent case reports and epidemiological data suggest that fungal infections represent an underappreciated complication among people with severe COVID-19. However, the frequency of fungal colonization in patients with COVID-19 and associations with specific immune responses in the airways remain incompletely defined. We previously generated a single-cell RNA-sequencing data set characterizing the upper respiratory microenvironment during COVID-19 and mapped the relationship between disease severity and the local behavior of nasal epithelial cells and infiltrating immune cells. Our previous study, in agreement with findings from related human cohorts, demonstrated that a profound deficiency in host immunity, particularly in type I and type III interferon signaling in the upper respiratory tract, is associated with rapid progression to severe disease and worse clinical outcomes. We have now performed further analysis of this cohort and identified a subset of participants with severe COVID-19 and concurrent detection of Candida species-derived transcripts within samples collected from the nasopharynx and trachea. Here, we present the clinical characteristics of these individuals. Using matched single-cell transcriptomic profiles of these individuals' respiratory mucosa, we identify epithelial immune signatures suggestive of IL17 stimulation and anti-fungal immunity. Further, we observe a significant expression of anti-fungal inflammatory cascades in the nasal and tracheal epithelium of all participants who went on to develop severe COVID-19, even among participants without detectable genetic material from fungal pathogens. Together, our data suggest that IL17 stimulation-in part driven by Candida colonization-and blunted interferon signaling represent a common feature of severe COVID-19 infection. IMPORTANCE: In this paper, we present an analysis suggesting that symptomatic and asymptomatic fungal coinfections can impact patient disease progression during COVID-19 hospitalization. By looking into the presence of other pathogens and their effect on the host immune response during COVID-19 hospitalizations, we aim to offer insight into an underestimated scenario, furthering our current knowledge of determinants of severity that could be considered for future diagnostic and intervention strategies.

Epstein-Barr Virus Orchestrates Spatial Reorganization and Immunomodulation within the Classic Hodgkin Lymphoma Tumor Microenvironment.

Classic Hodgkin Lymphoma (cHL) is a tumor composed of rare malignant Hodgkin and Reed-Sternberg (HRS) cells nested within a T-cell rich inflammatory immune infiltrate. cHL is associated with Epstein-Barr Virus (EBV) in 25% of cases. The specific contributions of EBV to the pathogenesis of cHL remain largely unknown, in part due to technical barriers in dissecting the tumor microenvironment (TME) in high detail. Herein, we applied multiplexed ion beam imaging (MIBI) spatial pro-teomics on 6 EBV-positive and 14 EBV-negative cHL samples. We identify key TME features that distinguish between EBV-positive and EBV-negative cHL, including the relative predominance of memory CD8 T cells and increased T-cell dysfunction as a function of spatial proximity to HRS cells. Building upon a larger multi-institutional cohort of 22 EBV-positive and 24 EBV-negative cHL samples, we orthogonally validated our findings through a spatial multi-omics approach, coupling whole transcriptome capture with antibody-defined cell types for tu-mor and T-cell populations within the cHL TME. We delineate contrasting transcriptomic immunological signatures between EBV-positive and EBV-negative cases that differently impact HRS cell proliferation, tumor-immune interactions, and mecha-nisms of T-cell dysregulation and dysfunction. Our multi-modal framework enabled a comprehensive dissection of EBV-linked reorganization and immune evasion within the cHL TME, and highlighted the need to elucidate the cellular and molecular fac-tors of virus-associated tumors, with potential for targeted therapeutic strategies.

A Spatial Multi-Modal Dissection of Host-Microbiome Interactions within the Colitis Tissue Microenvironment.

The intricate and dynamic interactions between the host immune system and its microbiome constituents undergo dynamic shifts in response to perturbations to the intestinal tissue environment. Our ability to study these events on the systems level is significantly limited by in situ approaches capable of generating simultaneous insights from both host and microbial communities. Here, we introduce Microbiome Cartography (MicroCart), a framework for simultaneous in situ probing of host features and its microbiome across multiple spatial modalities. We demonstrate MicroCart by comprehensively investigating the alterations in both gut host and microbiome components in a murine model of colitis by coupling MicroCart with spatial proteomics, transcriptomics, and glycomics platforms. Our findings reveal a global but systematic transformation in tissue immune responses, encompassing tissue-level remodeling in response to host immune and epithelial cell state perturbations, and bacterial population shifts, localized inflammatory responses, and metabolic process alterations during colitis. MicroCart enables a deep investigation of the intricate interplay between the host tissue and its microbiome with spatial multiomics.

Scalable nonparametric clustering with unified marker gene selection for single-cell RNA-seq data.

Clustering is commonly used in single-cell RNA-sequencing (scRNA-seq) pipelines to characterize cellular heterogeneity. However, current methods face two main limitations. First, they require user-specified heuristics which add time and complexity to bioinformatic workflows; second, they rely on post-selective differential expression analyses to identify marker genes driving cluster differences, which has been shown to be subject to inflated false discovery rates. We address these challenges by introducing nonparametric clustering of single-cell populations (NCLUSION): an infinite mixture model that leverages Bayesian sparse priors to identify marker genes while simultaneously performing clustering on single-cell expression data. NCLUSION uses a scalable variational inference algorithm to perform these analyses on datasets with up to millions of cells. By analyzing publicly available scRNA-seq studies, we demonstrate that NCLUSION (i) matches the performance of other state-of-the-art clustering techniques with significantly reduced runtime and (ii) provides statistically robust and biologically relevant transcriptomic signatures for each of the clusters it identifies. Overall, NCLUSION represents a reliable hypothesis-generating tool for understanding patterns of expression variation present in single-cell populations.