Biology subjects

Hacohen, N.

Publications and source records attributed to Hacohen, N..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Integrating spatial transcriptomics count data with Crescendo improves visualization and detection of spatial gene patterns

Spatial transcriptomics allows for the analysis of a cells gene expression in the context of its physical location. With spatial transcriptomics data, investigators often want to find genes of interest whose spatial patterns are biologically relevant in multiple samples. However, due to confounding factors in spatial data that produce noise across samples, datasets, and technologies, it is challenging to visualize genes and their spatial patterns across samples. We present Crescendo, an integration algorithm that performs correction directly on gene expression counts to reduce variation from technical confounders. We first apply Crescendo to a 3-sample spatial transcriptomics mouse brain dataset to show how Crescendo enables accurate visualization of gene expression across these spatial transcriptomic samples. We then demonstrate Crescendos scalability by integrating a 16-sample immuno-oncology dataset of 7 million cells. Finally, we show that Crescendo can perform cross-technology integration by merging a colorectal cancer (CRC) scRNA-seq dataset with two CRC spatial transcriptomics samples. By transferring information between technologies, Crescendo can impute poorly expressed genes to improve detection of gene-gene colocalization, such as ligand-receptor interactions.

bioinformatics↗

bioRxiv2023

DSMBind: SE(3) denoising score matching for unsupervised binding energy prediction and nanobody design

Modeling the binding between proteins and other molecules is pivotal to drug discovery. Geometric deep learning is a promising paradigm for protein-ligand/protein-protein binding energy prediction, but its accuracy is limited by the size of training data as high-throughput binding assays are expensive. Herein, we propose an unsupervised binding energy prediction framework, named DSMBind, which does not need experimental binding data for training. DSMBind is an energy-based model that estimates the likelihood of a protein complex via SE(3) denoising score matching (DSM). This objective, applied at both backbone and side-chain levels, builds on a novel equivariant rotation prediction network derived from Eulers Rotation Equations. We find that the learned log-likelihood of protein complexes is highly correlated with experimental binding energy across multiple benchmarks, even matching the performance of supervised models trained on experimental data. We further demonstrate DSMBinds zero-shot binder design capability through a PD-L1 nanobody design task, where we randomize all three complementarity-determining regions (CDRs) and select the best CDR sequences based on DSMBind score. We experimentally tested the designed nanobodies with ELISA binding assay and successfully discovered a novel PD-L1 binder. In summary, DSMBind offers a versatile framework for binding energy prediction and binder design. Our code is publicly available at github.com/wengong-jin/DSMBind.

bioinformatics↗

bioRxiv2023

Intrarenal myeloid subsets associated with kidney injury are comparable in mice and patients with lupus nephritis

Resident macrophages and infiltrating monocytes in kidneys of patients with lupus nephritis are altered both in frequency and function relative to their counterparts in healthy kidneys. The extent to which mouse models might be useful in developing approaches to target these cells for treating lupus nephritis is poorly understood. Here, we studied four common lupus mouse models that share clinical, serologic, and histopathologic kidney changes with humans. Using single-cell profiling and multiplex spatial imaging to analyze the intrarenal myeloid compartment with the onset of clinical disease in these models, we identified monocyte and macrophage subsets that expand or contract in kidneys with clinical nephritis. A unique subset of classical monocytes expanded with the onset of disease and expressed genes such as CD9, Spp1, Ctsd, Cd63, Apoe, and Trem2 that were previously shown to be induced by tissue injury and play a role in inflammation, lipid metabolism and tissue repair in other organs. Resident macrophages transitioned from a pro-inflammatory to a similar injury-associated state with onset of disease. To test whether these findings in mouse models were also observed in humans, we re-analyzed monocytes and macrophages in a single-cell RNAseq dataset of kidney biopsies from 155 patients with lupus nephritis and 30 healthy donors, collected by the NIH AMP RA/SLE consortium. Human monocytes and macrophages showed conserved changes in gene expression programs associated with lupus nephritis disease indices, and localized to similar kidney microenvironments as in mice. By identifying myeloid subsets and disease-associated alterations in biological processes that are conserved across species, we provide a strong rationale for functional studies of these cells and pathways in mice to uncover mechanisms and find targets relevant to human lupus nephritis. One sentence summaryThis study characterizes intrarenal myeloid cells from four lupus mouse models and 155 patients with lupus nephritis using single-cell RNA-seq and imaging, and identifies novel infiltrating and resident myeloid subsets that are conserved between mouse and human lupus nephritis, thus providing a map and strong rationale for functional studies in mice with relevance to human disease.

immunology↗

bioRxiv2023

The HLA-II immunopeptidome of SARS-CoV-2

Targeted synthetic vaccines have the potential to transform our response to viral outbreaks; yet the design of these vaccines requires a comprehensive knowledge of viral immunogens, including T-cell epitopes. Having previously mapped the SARS-CoV-2 HLA-I landscape, here we report viral peptides that are naturally processed and loaded onto HLA-II complexes in infected cells. We identified over 500 unique viral peptides from canonical proteins, as well as from overlapping internal open reading frames (ORFs), revealing, for the first time, the contribution of internal ORFs to the HLA-II peptide repertoire. Most HLA-II peptides co-localized with the known CD4+ T cell epitopes in COVID-19 patients. We also observed that two reported immunodominant regions in the SARS-CoV-2 membrane protein are formed at the level of HLA-II presentation. Overall, our analyses show that HLA-I and HLA-II pathways target distinct viral proteins, with the structural proteins accounting for most of the HLA-II peptidome and non-structural and non-canonical proteins accounting for the majority of the HLA-I peptidome. These findings highlight the need for a vaccine design that incorporates multiple viral elements harboring CD4+ and CD8+ T cell epitopes to maximize the vaccine effectiveness.

microbiology↗

bioRxiv2023

Spatial analysis of human lung cancer reveals organized immune hubs enriched for stem-like CD8 T cells and associated with immunotherapy response

The organization of immune cells in human tumors is not well understood. Immunogenic tumors harbor spatially-localized multicellular immunity hubs defined by expression of the T cell-attracting chemokines CXCL10/CXCL11 and abundant T cells. Here, we examined immunity hubs in human pre-immunotherapy lung cancer specimens, and found that they were associated with beneficial responses to PD-1-blockade. Immunity hubs were enriched for many interferon-stimulated genes, T cells in multiple differentiation states, and CXCL9/10/11+ macrophages that preferentially interact with CD8 T cells. Critically, we discovered the stem-immunity hub, a subtype of immunity hub strongly associated with favorable PD-1-blockade outcomes, distinct from mature tertiary lymphoid structures, and enriched for stem-like TCF7+PD-1+ CD8 T cells and activated CCR7+LAMP3+ dendritic cells, as well as chemokines that organize these cells. These results elucidate the spatial organization of the human intratumoral immune response and its relevance to patient immunotherapy outcomes.

immunology↗

bioRxiv2023

Cytotoxic CD4+ T cells eliminate senescent cells by targeting cytomegalovirus antigen

Senescent cell accumulation has been implicated in the pathogenesis of aging-associated diseases including cancer. The mechanism that prevents the accumulation of senescent cells in aging human organs is unclear. Here, we demonstrate that a virus-immune axis controls the senescent fibroblast accumulation in the human skin. Senescent fibroblasts increased in old compared with young skin. However, they did not increase with advancing age in the elderly. Increased CXCL9 and cytotoxic CD4+ T cell (CD4 CTL) recruitment were significantly associated with reduced senescent fibroblasts in the old skin. Senescent fibroblasts expressed human leukocyte antigen class II (HLA-II) and human cytomegalovirus glycoprotein B (HCMV-gB), becoming direct CD4 CTL targets. Skin-resident CD4 CTL eliminated HCMV-gB+ senescent fibroblasts in an HLA-II-dependent manner, and HCMV-gB activated CD4 CTL from the human skin. Collectively, our findings demonstrate HCMV reactivation in senescent cells, which can be directly eliminated by CD4 CTL through the recognition of the HCMV-gB antigen.

immunology↗

bioRxiv2023

Systematically characterizing the roles of E3-ligase family members in inflammatory responses with massively parallel Perturb-seq

E3 ligases regulate key processes, but many of their roles remain unknown. Using Perturb-seq, we interrogated the function of 1,130 E3 ligases, partners and substrates in the inflammatory response in primary dendritic cells (DCs). Dozens impacted the balance of DC1, DC2, migratory DC and macrophage states and a gradient of DC maturation. Family members grouped into co-functional modules that were enriched for physical interactions and impacted specific programs through substrate transcription factors. E3s and their adaptors co-regulated the same processes, but partnered with different substrate recognition adaptors to impact distinct aspects of the DC life cycle. Genetic interactions were more prevalent within than between modules, and a deep learning model, com{beta}VAE, predicts the outcome of new combinations by leveraging modularity. The E3 regulatory network was associated with heritable variation and aberrant gene expression in immune cells in human inflammatory diseases. Our study provides a general approach to dissect gene function.

genomics↗

bioRxiv2022

Proximity-dependent labeling identifies dendritic cells that prime the antitumor CD4+ T cell response

Dendritic cells (DCs) are uniquely capable of transporting tumoral antigens to tumor-draining lymph nodes (tdLNs), and also interact with effector T cells within the tumor microenvironment (TME) itself, mediating both natural antitumor immunity and the response to checkpoint blockade immunotherapy. Using LIPSTIC (Labeling Immune Partnerships by SorTagging Intercellular Contacts)-based single-cell transcriptomics, we identify individual DCs capable of presenting antigen to CD4+ T cells in the tdLN as well as inside the tumor microenvironment (TME). Our findings reveal that DCs with similar hyperactivated transcriptional phenotypes interact with helper T cells both within tumors and in the tdLN, and that checkpoint blockade drugs enhance these interactions. These findings show that a relatively small fraction of DCs is responsible for most of the antigen presentation within the tdLN and TME to both CD4+ and CD8+ tumor-specific T cells and that classical checkpoint blockade enhances CD40-driven DC activation at both sites.

immunology↗

bioRxiv2022

Integrative single cell and spatial transcriptomics of colorectal cancer reveals multicellular functional units that support tumor progression

While advances in single cell genomics have helped to chart the cellular components of tumor ecosystems, it has been more challenging to characterize their specific spatial organization and functional interactions. Here, we combine single cell RNA-seq, spatial transcriptomics by Slide-seq, and in situ multiplex RNA analysis, to create a detailed spatial map of healthy and dysplastic colon cellular ecosystems and their association with disease progression. We profiled inducible genetic CRC mouse models that recapitulate key features of human CRC, assigned cell types and epithelial expression programs to spatial tissue locations in tumors, and computationally used them to identify the regional features spanning different cells in the same spatial niche. We find that tumors were organized in cellular neighborhoods, each with a distinct composition of cell subtypes, expression programs, and local cellular interactions. Comparing to scRNA-seq and Slide-seq data from human CRC, we find that both cell composition and layout features were conserved between the species, with mouse neighborhoods correlating with malignancy and clinical outcome in human patient tumors, highlighting the relevance of our findings to human disease. Our work offers a comprehensive framework that is applicable across various tissues, tumors, and disease conditions, with tools for the extrapolation of findings from experimental mouse models to human diseases.

cancer biology↗

bioRxiv2022

ESCRT-dependent STING degradation curtails steady-state and cGAMP-induced signaling

STING is an intracellular sensor of cyclic di-nucleotides involved in response to pathogen- or self-derived DNA that induces protective immunity, or if dysregulated, autoimmunity. STING trafficking is tightly linked to its activity. We aimed to systematically characterize genes regulating STING trafficking and to define their impact on STING responses. Based on proximity-ligation proteomics and genetic screens, an ESCRT complex containing HGS, VPS37A and UBAP1 was found to be required for STING degradation and signaling shutdown. Analogous to phosphorylated STING creating a platform for IRF3 recruitment, oligomerization-driven STING ubiquitination by UBE2N formed a platform for ESCRT recruitment at the endosome, responsible for STING signaling shutdown. A UBAP1 mutant that underlies human spastic paraplegia and disrupts ESCRT function led to STING-dependent type I IFN responses at the steady-state, defining ESCRT as a homeostatic regulator of STING signaling.

immunology↗

bioRxiv2022

A resource for generating and manipulating human microglial states in vitro

Microglia have emerged as key players in the pathogenesis of neurodegenerative conditions such as Alzheimers disease (AD). In response to CNS stimuli, these cells adopt distinct transcriptional and functional subtypes known as states. However, an understanding of the function of these states has been elusive, especially in human microglia, due to lack of tools to model and manipulate this cell-type. Here, we provide a platform for modeling human microglia transcriptional states in vitro. Using single-cell RNA sequencing, we found that exposure of human stem-cell differentiated microglia (iMGLs) to brain-related challenges generated extensive transcriptional diversity which mapped to gene signatures identified in human brain microglia. We identified two in vitro transcriptional clusters that were analogous to human and mouse disease-associated microglia (DAMs), a state enriched in neurodegenerative disease contexts. To facilitate scalable functional analyses, we established a lentiviral approach enabling broad and highly efficient genetic transduction of microglia in vitro. Using this new technology, we demonstrated that MITF (Melanocyte Inducing Transcription Factor), an AD-enriched transcription factor in microglia, drives both a disease-associated transcriptional signature and a highly phagocytic state. Finally, we confirmed these results across iMGLs differentiated from multiple iPSC lines demonstrating the broad utility of this platform. Together, these tools provide a comprehensive resource that enables the manipulation and functional interrogation of human microglial states in both homeostatic and disease-relevant contexts.

neuroscience↗

bioRxiv2022

Integrative Analysis of Checkpoint Blockade Response in Advanced Non-Small Cell Lung Cancer

Anti-PD-1/PD-L1 agents have transformed the treatment landscape of advanced non-small cell lung cancer (NSCLC). While our understanding of the biology underlying immune checkpoint blockade in NSCLC is still incomplete, studies to date have established predictive roles for PD-L1 tumor expression and tumor mutational burden (TMB). To expand our understanding of the molecular features underlying response to checkpoint inhibitors in NSCLC, we describe here the first joint analysis of the Stand Up 2 Cancer - Mark Foundation (SU2C-MARK) Cohort, a resource of whole exome and/or RNA sequencing from 393 patients with NSCLC treated with anti-PD-(L)1 therapy, along with matched clinical response annotation. We identify a number of associations between molecular features and outcome, including: 1) favorable (e.g., ATM altered), and unfavorable (e.g., TERT amplified) genomic subgroups, 2) distinct immune infiltration signatures associated with wound healing (unfavorable) and immune activation (favorable), and 3) a novel de-differentiated tumor-intrinsic subtype characterized by expression of endodermal lineage genes, immune activation, and enhanced response rate. Taken together, results from this cohort extend our understanding of NSCLC-specific predictors, providing a rich set of molecular and immunologic hypotheses with which to further our understanding of the biology of checkpoint blockade in NSCLC.

genomics↗

bioRxiv2022

Distinct gene programs underpinning 'disease tolerance' and 'resistance' in influenza virus infection

When challenged with an invading pathogen, the host defense response is engaged to eliminate the pathogen (resistance) and to maintain health in the presence of the pathogen (disease tolerance). However, the identification of distinct molecular programs underpinning disease tolerance and resistance remained obscure. We exploited transcriptional and physiological monitoring across 33 mouse strains, during in vivo influenza virus infection, to identify two host-defense gene programs - one is associated with hallmarks of disease tolerance and the other with hallmarks of resistance. Both programs constitute generic responses in multiple mouse and human cell types. Our study describes the organizational principles of these programs and validates Arhgdia as a regulator of disease-tolerance states in epithelial cells. We further reveal that the baseline disease-tolerance state in macrophages is associated with the pathophysiological response to injury and infection. Our framework provides a paradigm for the understanding of disease tolerance and resistance at the molecular level.

systems biology↗

bioRxiv2022

Plasma proteomic biomarkers identify non-responders and reveal biological insights about the tumor microenvironment in melanoma patients after PD1 blockade

Most patients treated with immune checkpoint blockade (ICB) do not have durable treatment responses. Therefore, there is a critical need to identify early non-invasive biomarkers of response. We performed plasma proteomic analysis (>700 proteins) at three timepoints on 174 metastatic melanoma patients treated with ICB. We leverage independent training and testing cohorts to build a predictor of immunotherapy response that outperforms several tissue-based approaches. We found 217 differentially expressed proteins between ICB responders (R) and non-responders (NR), including a co-regulated module of proteins enriched in certain NR patients. By analyzing single-cell RNA-sequencing data of tumor biopsies from 32 patients, we dissected the relative contribution of cells in the tumor to proteins in circulation. The majority of proteins in the co-regulated NR module derived from tumor and myeloid cells. Amongst myeloid cells, we identified a subset of tumor-associated macrophages (TAMs) with a suppressive phenotype that expressed high levels of the co-regulated NR module, thus suggesting they are key drivers of non-response signatures. Together, our data demonstrates the utility of plasma proteomics in biomarker discovery and in understanding the biology of host response to tumors.

cancer biology↗

bioRxiv2021

Clinical implementation of single-cell RNA sequencing using liver fine needle aspirate tissue sampling and centralized processing captures compartment specific immuno-diversity

Blood samples are frequently collected in human studies of the immune system but poorly represent tissue-resident immunity. Understanding the immunopathogenesis of tissue-restricted diseases, such as chronic hepatitis B, necessitates direct investigation of local immune responses. We developed a workflow that enables frequent, minimally invasive collection of liver fine-needle aspirates in multi-site international studies and centralized single-cell RNA sequencing data generation using the Seq-Well S3 picowell-based technology. All immunological cell types were captured, including liver macrophages, and showed distinct compartmentalization and transcriptional profiles, providing a systematic assessment of the capabilities and limitations of peripheral blood samples when investigating tissue-restricted diseases. The ability to electively sample the liver of chronic viral hepatitis patients and generate high-resolution data will enable multi-site clinical studies to power fundamental and therapeutic discovery.

immunology↗

bioRxiv2021

Spatially regulated protease activity in lymph nodes renders B cell follicles a sanctuary for retention of intact antigens

The structural integrity of vaccine antigens is critical, as antigen degradation in vivo could eliminate neutralizing epitopes and create competing B cell responses against irrelevant breakdown products. Using FRET imaging and imaging zymography, we found that protease activity and antigen breakdown are spatially heterogeneous in lymph nodes. Following protein immunization, antigens are rapidly degraded in the subcapsular sinus, paracortex, and interfollicular regions of the tissue. By contrast, the follicles and follicular dendritic cell (FDC) networks exhibit low protease activity and antigen degradation rates. Immunization regimens targeting antigen rapidly to FDCs led to germinal centers (GCs) where responses to intact antigen were highly dominant, while traditional bolus immunizations led to weaker GC responses where more GC B cells bound to breakdown products than intact antigen. Thus, spatially-compartmentalized antigen proteolysis impacts humoral immunity and can be exploited to enhance vaccine-induced production of antibody responses against key pathogen structural epitopes.

immunology↗

bioRxiv2021

Longitudinal characterization of circulating neutrophils uncovers distinct phenotypes associated with disease severity in hospitalized COVID-19 patients

Multiple studies have identified an association between neutrophils and COVID-19 disease severity; however, the mechanistic basis of this association remains incompletely understood. Here we collected 781 longitudinal blood samples from 306 hospitalized COVID-19+ patients, 78 COVID-19- acute respiratory distress syndrome patients, and 8 healthy controls, and performed bulk RNA-sequencing of enriched neutrophils, plasma proteomics, cfDNA measurements and high throughput antibody profiling assays to investigate the relationship between neutrophil states and disease severity or death. We identified dynamic switches between six distinct neutrophil subtypes using non-negative matrix factorization (NMF) clustering. At days 3 and 7 post-hospitalization, patients with severe disease had an enrichment of a granulocytic myeloid derived suppressor cell-like state gene expression signature, while non-severe patients with resolved disease were enriched for a progenitor-like immature neutrophil state signature. Severe disease was associated with gene sets related to neutrophil degranulation, neutrophil extracellular trap (NET) signatures, distinct metabolic signatures, and enhanced neutrophil activation and generation of reactive oxygen species (ROS). We found that the majority of patients had a transient interferon-stimulated gene signature upon presentation to the emergency department (ED) defined here as Day 0, regardless of disease severity, which persisted only in patients who subsequently died. Humoral responses were identified as potential drivers of neutrophil effector functions, as enhanced antibody-dependent neutrophil phagocytosis and reduced NETosis was associated with elevated SARS-CoV-2-specific IgG1-to-IgA1 ratios in plasma of severe patients who survived. In vitro experiments confirmed that while patient-derived IgG antibodies mostly drove neutrophil phagocytosis and ROS production in healthy donor neutrophils, patient-derived IgA antibodies induced a predominant NETosis response. Overall, our study demonstrates neutrophil dysregulation in severe COVID-19 and a potential role for IgA-dominant responses in driving neutrophil effector functions in severe disease and mortality.

immunology↗

bioRxiv2021

High-throughput RNA isoform sequencing using programmable cDNA concatenation

Alternative splicing is a core biological process that enables profound and essential diversification of gene function. Short-read RNA sequencing approaches fail to resolve RNA isoforms and therefore primarily enable gene expression measurements - an isoform unaware representation of the transcriptome. Conversely, full-length RNA sequencing using long-read technologies are able to capture complete transcript isoforms, but their utility is deeply constrained due to throughput limitations. Here, we introduce MAS-ISO-seq, a technique for programmably concatenating cDNAs into single molecules optimal for long-read sequencing, boosting the throughput >15 fold to nearly 40 million cDNA reads per run on the Sequel IIe sequencer. We validated unambiguous isoform assignment with MAS-ISO-seq using a synthetic RNA isoform library and applied this approach to single-cell RNA sequencing of tumor-infiltrating T cells. Results demonstrated a >30 fold boosted discovery of differentially spliced genes and robust cell clustering, as well as canonical PTPRC splicing patterns across T cell subpopulations and the concerted expression of the associated hnRNPLL splicing factor. Methods such as MAS-ISO-seq will drive discovery of novel isoforms and the transition from gene expression to transcript isoform expression analyses.

genetics↗