Publications

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies with dismal prognosis and limited treatment options. The complex interplay between tumor cells and their microenvironment contributes significantly to treatment resistance, yet technological challenges have hindered comprehensive spatial characterization of immune components in PDAC tissues. Here, we performed high-dimensional spatial proteomics using multiplexed ion beam imaging (MIBI) to quantify 27 protein markers across tissues from twelve treatment-naïve PDAC patients who subsequently underwent adjuvant chemotherapy. We achieved confident single-cell phenotypic mapping of the PDAC ecosystem through deep-learning based segmentation and expert-validated phenotypic annotation. Our analysis revealed significant enrichment of immunosuppressive myeloid populations in patients who eventually experienced disease relapse. Conversely, cytotoxic CD8+ T cells were depleted in these relapse-prone tumors. Using spatial probabilistic topic modeling, we identified eight distinct cellular neighborhoods with unique compositions and functional states, including the enrichment of an immune suppressive neighborhood in relapsed patients. While immunogenic cell neighborhoods were present in both patient populations, analysis of the tumor-immune neighborhoods demonstrated altered functional marker expression profiles, suggesting distinct immune activation in patients who relapsed versus those who did not. Our findings provide a high-resolution spatial atlas of the PDAC immune landscape and identify prognostic microenvironmental signatures that may inform the development of novel immunotherapeutic strategies for this recalcitrant disease.

Epstein-Barr virus (EBV) infects 90% of the population worldwide and is associated with multiple malignancies, including Burkitt, Hodgkin and post-transplant lymphomas, nasopharyngeal and gastric carcinoma. EBV also triggers autoimmune diseases, including multiple sclerosis and systemic lupus erythematosus. While host factors important for EBV B-cell entry have been defined, including CD21/CR2, MHC class II and R9AP, much remains to be learned about host factors that support post-entry steps of EBV infection. To gain insight, we conducted a human genome-wide CRISPR-Cas9 screen. In addition to known EBV B cell receptors/co-receptors, we identified multiple new factors and pathways essential for EBV B cell infection. These included multiple B cell signaling pathways, actin cytoskeleton and nuclear import factors. Knockout of CD19, its tetraspanin chaperone CD81 or karyopherin subunit alpha 1 (KPNA1, also called importin-α5) significantly impaired establishment of EBV infection. EBV and CD19 co-localized at early stages of EBV infection, and the CD19 cytoplasmic tail was important for EBV infection, suggesting CD19 signaling supports EBV uptake. Depletion of KPNA1 significantly impaired establishment of EBV infection, but did not impair production of infectious EBV upon reactivation of latently infected B cells. Together, these results provide insights into pathways that support EBV B cell infection and identify potential therapeutic targets.

Spatial proteomics is limited by detection sensitivity, multiplexing and multimodal integration, leaving a gap between discovery and clinical assays. Here we present protein and nucleic acid serial tyramide amplification (PASTA), using horseradish peroxidase-mediated oligonucleotide deposition and cyclical imaging for high-plex, multimodal spatial profiling. Compatible with conjugated antibodies and in situ hybridization, PASTA enables simultaneous protein and RNA codetection from formalin-fixed, paraffin-embedded samples, providing a cost-effective bridge from discovery to clinical validation.

Across cancer, one of the most frequent examples of histologic transformation is the evolution of follicular lymphoma (FL) to an aggressive large cell lymphoma. Despite recent progress, understanding of the molecular and cellular underpinnings of transformation remains incomplete. Here, we dissect the interplay of tumor and microenvironment cell populations across transformation through a multimodal investigation of 95 FL and transformed FL (tFL) samples, including single-cell and bulk RNA-sequencing alongside spatial transcriptomics and proteomics, and validate findings across independent FL-tFL pairs. Upon transformation, fibroblasts and GPNMB+ macrophages increase while lymph-node organizing follicular dendritic and CCL21+ fibroblastic reticular cells were lost, resulting in an altered spatial distribution of cytokines that impacts T cell infiltration and macrophage differentiation and function. Secreted stromal and macrophage signals were further evident by non-invasive plasma proteomics. Taken together, our data reveal expansion of macrophages and fibroblasts as key features of transformation with potential diagnostic and therapeutic implications.

Spatial transcriptomics and proteomics have enabled profound insights into tissue organization, yet these technologies remain largely disparate, and emerging same-slide multi-omics approaches are limited in plex, spatial resolution, signal retention, and integrative analytics. We introduce IN-situ DEtailed Phenotyping To High-resolution transcriptomics (IN-DEPTH), a streamlined, resource-efficient, commercially compatible workflow using single-cell spatial proteomics-derived imaging to guide transcriptomic capture on the same slide without RNA signal loss. To integrate modalities beyond niche-level mapping, we developed Spectral Graph Cross-Correlation (SGCC), a proteomic-transcriptomic framework resolving spatially coordinated functional state changes across interacting cell populations. Applied to diffuse large B-cell lymphoma (DLBCL), IN-DEPTH and SGCC enabled stepwise discovery from EBV-positive and EBV-negative tumor comparisons to single-cell resolution, revealing coordinated tumor-macrophage-CD4 T-cell remodeling, immunosuppressive C1Q macrophage enrichment, CD4 T-cell dysfunction, and a candidate IL-27-STAT3 signaling axis. Collectively, IN-DEPTH enables scalable spatial multi-omics to uncover clinically relevant microenvironmental mechanisms and towards robust spatial multi-modal AI models.

Epithelial remodeling is a hallmark of host antiviral responses that strengthen barrier defenses against infection. Our current understanding of viral pathophysiology within the nasal epithelium, the initial site of most respiratory viral infections, remains incomplete due to limited understanding of the native tissue architecture and protective epithelial remodeling during immune events. Leveraging coronavirus disease 2019 (COVID-19) as a model, we applied spatial multi-omics on nasal cross-sectional tissues to characterize the immune-epithelial landscape during infection, identifying a coordinated increase in goblet cells and suppressive macrophages associated with elevated IL13 in the immune compartment. Our results further reveal that goblet cell and suppressive macrophage enrichment are spatially linked in proximity to IL13-expressing CD4 T cells, consistent with IL13-driven remodeling in situ. Using a primary human nasal air-liquid interface model, we demonstrate that IL13 alone is sufficient to remodel epithelial composition and morphology, subsequently restricting viral infection by reshaping the apical mucus barrier of the nasal epithelium. Our findings uncover a spatially organized, IL13-driven circuit for immune-epithelial remodeling as a protective barrier against respiratory viral infections.

Classic Hodgkin lymphoma (cHL) is composed of rare malignant Hodgkin and Reed-Sternberg (HRS) cells within a T-cell-rich tumor microenvironment (TME). Epstein-Barr virus (EBV) is present in ∼25% of cases, but its contribution to pathogenesis and immunomodulation remains unclear due to technical barriers. Using complementary spatial proteomics and transcriptomics across multi-institutional cohorts, we systematically map key EBV-linked TME reorganization. EBV-positive cHL exhibits distinct immunological features, including memory CD8 T cell enrichment, heightened T cell dysfunction spatially correlated with HRS proximity, and terminally exhausted T cell signatures contrasting with progenitor-exhausted patterns in EBV-negative disease. We identify EBV-encoded LMP1 as a factor in T cell dysfunction through enhanced HRS:CD8 interactions, and its expression level correlates with T cell terminal exhaustion in a distance-dependent manner. This spatial framework dissects viral-mediated immune evasion in the cHL TME, highlighting potential therapeutic opportunities to target virus-associated T cell dysfunction for precision immunotherapy in virus-associated malignancies.

Multimodal spatial omics has transformed biology by mapping molecular complexity within intact tissues, yet current technologies remain limited in the number of modalities measured simultaneously and often produce lower-quality data than single-modality assays. We present COSIE, a computational framework that generates high-resolution, multilayered molecular landscapes across tissue sections, individuals, and platforms. COSIE integrates histology, epigenome, transcriptome, proteome, and metabolome into a unified representation. Applied to 12 datasets spanning 10 spatial technologies, eight modalities, and nine tissue types, ranging from thousands of spots to millions of cells, COSIE outperforms existing methods. It resolves tissue structures, enhances noisy measurements, predicts unmeasured modalities, and captures dynamic processes. In human tumors, COSIE identifies invasive subregions linked to clinical outcomes and predicts spatial gene expression in TCGA samples using only histology images. By transforming fragmented data into comprehensive spatial maps, COSIE advances computationally complete spatial omics and the creation of digital tissue twins for biomedicine.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nonstructural protein 15 (Nsp15) is a conserved uridine-specific endoribonuclease (EndoU) and is implicated in innate immune evasion, yet its precise molecular mechanism remains incompletely understood. Here, we demonstrate that Nsp15 limits antiviral innate immune responses in part by downregulating the cGAS-STING pathway. To investigate how Nsp15 antagonizes host innate immune responses, we engineered recombinant SARS-CoV-2 bearing WT or EndoU-inactive Nsp15 (H234A). Compared with the WT virus, the Nsp15-H234A mutant exhibited a 2-log decrease in peak viral titres in interferon (IFN)-competent A549-ACE2 cells, but not in their STAT1 knockout counterparts. This attenuation was partially reversed by STING knockout or STING inhibitors, highlighting STING’s involvement in Nsp15-driven immune evasion. Transcriptomic analyses revealed the upregulation of IFNs and IFN-stimulated genes in cells infected with the Nsp15-H234A mutant virus. Notably, cGAS and STING transcripts and proteins were suppressed during WT but not mutant virus infections – even in STAT1-deficient cells – suggesting that Nsp15 contributes directly to their downregulation., Nsp15 targeted cGAS and STING transcripts in an EndoU activity-dependent manner, thereby reducing cGAS-STING-driven IFN-and NF-B reporter activation. Infection of Syrian hamsters confirmed that the Nsp15-H234A mutant virus replicated to lower titres in respiratory tissues and elicited stronger expression of innate immune-related genes. Collectively, these findings define a key strategy by which SARS-CoV-2 Nsp15 subverts the cGAS-STING pathway to facilitate viral replication and immune evasion and underscore Nsp15 EndoU activity as a potential target for future coronavirus antiviral or vaccine design.

Glycans regulate multiple physiological processes, including immune recognition and cancer progression. In disease, altered glycan landscapes are interpreted by human lectins. Functional glycan-lectin interactions are difficult to profile because glycans are not genome-encoded and their changes are poorly captured by existing multimodal methods. We present two platforms, single-cell outlining and transcriptome sequencing (scGOAT-seq) and GlycoScope, which use human lectins to enable functional glycan accessibility into single-cell and spatial multiomic measurements. ScGOAT-seq quantifies lectin-accessible glycan states with gene expression, while GlycoScope enables multiplexed in situ co-detection of glycans and proteins in tissues. Applying these approaches to immune cells, we identify stimulus-specific glycan remodeling and show that distinct Siglec-ligand-defined programs stratify immune activation states not captured by traditional methods; in follicular lymphoma, GlycoScope resolves spatial glycan programs associated with malignant B cells and localized immune microenvironments. The presented methods provide a general framework for integrating functional glycan accessibility into single-cell and spatial multiomics.

The lytic-latent balance is a major viral persistence strategy and obstacle to curing viral diseases, yet its mechanisms remain poorly understood. Following lytic infection in non-neuronal cells, herpes simplex virus (HSV) establishes latency specifically in neurons and is reactivated by stresses. Here we identify forkhead box (FOX) transcription factors that can strongly activate or repress replication of HSV-1 and other alphaherpesviruses, and show that neurons express activating Fox (e.g., Foxf) genes poorly but repressive Fox (Foxk) genes abundantly while non-neuronal or stressed neuronal cells exhibit higher expression of activating Fox genes. Remarkably, knockdown of Foxk1 or overexpression of activating Fox genes induces reactivation from latency in male mouse neuronal culture and in vivo. Of note, FOX proteins bind the viral genome globally and nonsequence-specifically and interact with epigenetic cofactors for gene regulation. FOXF1 interacts with CBP and P300 to acetylate and open viral chromatin. FOXK1 works with SIN3A, a cofactor of histone deacetylation, and MAX to suppress HSV-1 and antagonize activating FOX proteins. Therefore, the viral lytic-latent balance is controlled by the relative abundance of counteracting host transcription factors that recruit different epigenetic regulators to the viral genome.

Electronic health records (EHRs) rarely capture dietary detail, limiting diet-disease research. We aimed to develop machine learning (ML) computable phenotypes to identify high-fat diet (HFD) using variables typically available in EHRs.

We used National Health and Nutrition Examination Survey (NHANES) 1999-2020 data, where 24-h dietary recall served as ground truth. Dietary fat intake was summarized into a score (0-30) based on percent energy from fat, carbohydrate, and protein; lower scores indicated HFD. We defined HFD at cutoffs of 10, 15, and 20, and trained ML models (Extreme Gradient Boosting, logistic regression, random forest) using EHR-compatible variables (demographics, comorbidities, labs, anthropometrics). Model interpretability was assessed using Shapley Additive Explanations. To evaluate clinical relevance, we compared cancer associations using ML-predicted vs true diet labels.

Machine learning models classified HFD with good performance, strongest at broader definitions. Random forest achieved an F1-score of 0.79 (recall 0.74, precision 0.84) at cutoff 20. Key predictors included race/ethnicity, triglycerides, obesity metrics (body mass index and derived indices), and metabolic panel results.

These findings indicate that dietary patterns, though seldom recorded in EHRs, can be inferred from routinely available variables. The ability of ML-derived phenotypes to reproduce known diet-disease relationships underscore their epidemiologic validity. Top predictors also align with established biological pathways linking obesity, lipid metabolism, and cancer risk, supporting plausibility.

A high-fat dietary pattern can be inferred from EHR-compatible variables using ML-based phenotyping. This approach offers a scalable tool to integrate diet into EHR-based research and precision medicine.

[Abstract not available]

Regulatory T cell (Treg) dysfunction is a hallmark of autoimmune hepatitis (AIH), a serious hepatopathy often progressing to end-stage liver disease despite immunosuppression. Treg impairment in AIH has been linked to defective signaling through the aryl hydrocarbon receptor (AhR), a modulator of adaptive immunity. Herein, we investigated whether increased estrogen receptor alpha (ERα), an AhR non-canonical binding partner, impacts Treg immunity and contributes to the sex bias observed in AIH.

Tregs were isolated from the peripheral blood of pre-menopausal, post-menopausal and male patients with AIH, as well as controls. Their function, stability, transcriptome and response to AhR were assessed in the absence or presence of methylpiperidinopyrazole (MPP), an ERα-selective antagonist. Therapeutic effects of MPP were tested in a model of Concanavalin-A-induced liver injury in humanized mice.

ERα was upregulated in Tregs from pre-menopausal females with AIH (1.1 ± 0.3) compared with healthy pre-menopausal females (0.4 ± 0.1;= 0.038), and in pre-menopausal compared with post-menopausal females with AIH (0.3 ± 0.1;= 0.04). In pre-menopausal females with AIH, MPP enhanced Treg suppressive capacity (2.5-fold increase;= 0.001), restored response to AhR activation (2-fold increase;= 0.03), and reduced functional plasticity, evidenced by decreased IL-17A and RORC expression under pro-inflammatory conditions. MPP also ameliorated Concanavalin-A-induced hepatitis inmice reconstituted with human CD4+ ERα+ cells, as shown by reduced ALT levels (101 ± 24. 25 ± 8;= 0.024), diminished hepatic inflammation on histology, and increased intrahepatic CD4+FOXP3+ and CD4+CD39+ T-cell frequencies. Bioinformatic and inhibition analyses identified hypoxia-inducible factor-1α as a key inducer of ERα in AIH Tregs.

ERα upregulation drives Treg dysfunction in pre-menopausal females with AIH and likely contributes to the sex bias in the disease. ERα blockade stabilizes Tregs and limits inflammation, representing a promising therapeutic strategy to enhance and sustain immune tolerance in AIH.

Regulatory T cell (Treg) dysfunction plays a key role in the breakdown of immune tolerance in autoimmune hepatitis (AIH), a severe hepatopathy that often progresses to end-stage liver disease despite immunosuppression. Here we report that upregulation of estrogen receptor-alpha (ERα) alters Treg function and stability in pre-menopausal females with AIH, and that blockade of ERα using a specific antagonist stabilizes Tregs and curbs inflammation in humanized mice with liver injury. These findings implicate aberrant ERα signaling in the sex bias of AIH and support ERα inhibition as a potential therapeutic strategy to re-establish immune tolerance.

Antiretroviral therapy (ART) can effectively control human immunodeficiency virus (HIV) replication; however, lifelong treatment is required due to viral reservoirs, which fuel viral rebound. This necessitates curative interventions that can achieve either eradication of the reservoir or durable remission off ART. Advances in technology have fostered development of multi-omic techniques encompassing molecular tools, proteomic analyses, imaging, and artificial intelligence (AI)-driven data analysis to understand HIV reservoir biology and persistence. These have informed the investigation of therapeutic interventions such as broadly neutralizing antibodies, latency reversal, immune cell augmentation, antivirals, and gene therapy. From April 7-10, 2025, experts in the field convened at the Keystone Symposia conference, HIV Cure: Antiretroviral Therapy (ART)-Free Control of HIV Infection in Durban, South Africa, to discuss novel strategies for eradication and/or durable ART-free control of HIV.

Epstein-Barr virus (EBV) infects B and epithelial cells, causing various lymphomas and epithelial malignancies. Although cell-free infection of epithelial cells is inefficient, direct B-epithelial cell contact infection is highly efficient and probably the dominant route. To identify mechanisms of contact-mediated infection, we implemented a genome-wide CRISPR screen and uncovered desmocollin 2 (DSC2) as an EBV epithelial receptor and DSC3 as a co-factor for infection. DSC2 and DSC3 double knockout significantly inhibited both cell-free and cell-cell contact EBV infection of normal oral keratinocytes, while their overexpression permitted infection in receptor-negative cells. Antibodies to DSC2 blocked infection across normal oral keratinocytes, primary oral keratinocytes, and head and neck epithelial organoids. Combining DSC2 and DSC3 antibodies efficiently blocked cell-cell contact infection. Mechanistically, DSC2 interacted with the EBV gH/gL glycoprotein and facilitated epithelial fusion. Notably, EphA2 overexpression failed to restore infection in DSC2/3-deficient cells, indicating its dependence on DSC2/3. Our findings establish DSC2 as a principal EBV entry receptor and target for vaccine and therapeutic development.

A better understanding of post-exposure immune responses in vaccinated individuals, particularly infants, is needed.

Using a rhesus macaque model, we compared recipients of mRNA- or protein-based SARS-CoV-2 vaccines administered in infancy with unvaccinated controls 7 days post-SARS-CoV-2 virus challenge. Mass cytometry profiling of peripheral blood mononuclear cells and dissociated mediastinal lymph node cells at 7 days post-challenge revealed tissue-specific differences between groups, representing a snapshot of immune activity at this point.

Vaccinated animals showed lower frequencies of activated CD8+ T cells in blood and lower levels of monocyte and B cell subsets in lymph nodes, aligning with lower viral loads and milder pathology. Plasmacytoid dendritic cells-commonly depleted in circulation during severe human COVID-19-were preserved in the blood of vaccinated groups.stimulation demonstrated heightened inflammatory cell signaling from unvaccinated rhesus macaques, correlating with worse clinical outcomes.

These findings enhance our understanding of a critical nonhuman primate model and underscore the utility of single-cell, tissue-level analyses in evaluating next-generation pediatric SARS-CoV-2 vaccine strategies.

Chronic rhinosinusitis (CRS) is a common chronic inflammatory disease of the sinonasal cavity affecting millions worldwide. Its complex pathophysiology remains poorly understood, with emerging evidence implicating interactions between diverse immune and epithelial cells in disease progression. We applied single-cell RNA sequencing and spatial transcriptomics to both dissociated and intact human tissues from individuals with CRS with and without nasal polyps and compared them to controls. We revealed mechanisms of macrophage–eosinophil recruitment, CD4⁺ and CD8⁺ T cell dysregulation, and mast cell enrichment. We identified key immune-epithelial interactions in tissue remodeling, particularly involving basal progenitor and tuft cells. A distinct basal cell trajectory was implicated in nasal polyp formation. Orthogonal validation with spatial transcriptomics from >100individuals with CRS revealed conserved tissue remodeling features. Our study provides insights into CRS pathophysiology, highlighting immune-epithelial interactions as potential therapeutic targets in chronic inflammation, also serving as a resource for dissecting immune disease mechanisms.

Beyond cancer cells, the tumor microenvironment (TME) includes cells of the innate and adaptive immune systems but also non-immune cells, such as fibroblasts and endothelial cells. Depending on the cues they receive, infiltrating myeloid cells, such as monocytes, macrophages, dendritic cells and neutrophils, perform immune stimulatory or suppressive functions by educating adaptive immune cells, thereby guiding their responses to cancer cells and cancer treatment, such as immune checkpoint blockade (ICB). The increasing understanding that anti-tumor immunity goes beyond T cells with improved functionality, and the unraveling of resistance mechanisms beyond T cell exhaustion, have renewed interest in non-T cell components of the TME to identify novel therapeutic targets and improve ICB responses. Here, we review immune and non-immune cellular components of the TME that regulate adaptive cell responses and their role in ICB response and resistance.

Foundation models have begun to transform image analysis by acting as pretrained generalist backbones that can be adapted to many tasks even when post-training data are limited, yet their impact on spatial proteomics, imaging that maps proteins at single-cell resolution, remains limited. Here, we introduce KRONOS, a foundation model built for spatial proteomics. KRONOS was trained in a self-supervised manner on over 47 million image patches covering 175 protein markers, 16 tissue types, and 8 fluorescence-based imaging platforms. We introduce key architectural adaptations to address the high-dimensional, multi-channel, and heterogeneous nature of multiplex imaging. We demonstrate that KRONOS learns biologically meaningful representations across multiple scales, ranging from cellular and microenvironment to tissue levels, enabling it to address diverse downstream tasks, including cell phenotyping, region classification, and patient stratification. Evaluated across 11 independent cohorts, KRONOS achieves state-of-the-art performance across cell phenotyping, treatment response prediction, and retrieval tasks, and is highly data-efficient. KRONOS also introduces the paradigm of segmentation-free patch-level processing for efficient and scalable spatial proteomics analysis, allowing cross-institutional comparisons, and as an image reverse search engine for spatial patterns. Together, these results position KRONOS as a flexible and scalable tool for spatial proteomics.

Defective CD39 levels contribute to an imbalance between Tregs and Th17 effectors in inflammatory bowel disease (IBD). CD39 initiates an ATP hydrolysis cascade that culminates with the generation of adenosine, an immune metabolite that is key to tissue homeostasis. Human CD39 is regulated by an endogenous antisense RNA (CD39-AS) that is markedly elevated in IBD Tregs and Th17 cells. In this study, we investigated how CD39-AS affects the function of Tregs and Th17 cells in healthy subjects and IBD patients. We report that CD39-AS RNA is present in two main splice variants that are specifically expressed by Tregs or Th17 cells. Blockade of CD39-AS via self-delivering oligonucleotides targeting the splice variant expressed in Tregs results in a decrease of glucose transport and glycolysis and in enhanced Treg function and stability in IBD. In Th17 cells, silencing of CD39-AS limits oxidative responses and ameliorates mitochondrial health. These metabolic effects are also noted in a model of experimental colitis in humanized mice, along with reduced disease activity. Thus, in vivo administration of oligonucleotides targeting the Treg or Th17 cell CD39-AS variant limits disease activity, decreases the expression of GLUT1 and improves mitochondrial health in gut-derived CD4 lymphocytes. Mechanistically, activation of HIF-1α and STAT3 results in the upregulation of CD39-AS in IBD cells. In conclusion, CD39-AS is an important modulator of Treg and Th17 cell metabolism. Interference with this antisense RNA, or the factors favoring its upregulation, might contain inflammation and halt disease progression in IBD by restoring immune metabolism and Treg functional stability.

Delineating cell populations is crucial for understanding immune function in health and disease. Spatial omics technologies offer insights by capturing three complementary domains: single-cell molecular biomarker expression, cellular spatial relationships and tissue architecture. However, current computational methods often fail to fully integrate these multidimensional data, particularly for immune cell populations and intrinsic functional states. We introduce Cell Local Environment and Neighborhood Scan (CellLENS), a self-supervised computational method that learns cellular representations by fusing information across three spatial omics domains (expression, neighborhood and image). CellLENS markedly enhances de novo discovery of biologically relevant immune cell populations at fine granularity by integrating individual cells’ molecular profiles with their neighborhood context and tissue localization. By applying CellLENS to diverse spatial proteomic and transcriptomic datasets across multiple tissue types and disease settings, we uncover unique immune cell populations functionally stratified according to their spatial contexts. Our work demonstrates the power of multi-domain data integration in spatial omics to reveal insights into immune cell heterogeneity and tissue-specific functions.

Recent advances in bioanalytical and imaging technologies have revolutionized our ability to assess complex biological and pathological changes within tissue samples. Spatial omics, a rapidly evolving technology, enables the simultaneous detection of multiple biomolecules in tissue sections, allowing for high-dimensional molecular profiling within tissue microanatomical contexts. This offers a powerful opportunity for precise, multidimensional exploration of complex disease pathophysiology. The Pathology 2.0 working group within the European Society of Toxicologic Pathology (ESTP) includes a subgroup dedicated to spatial omics technologies. Their primary goal is to raise awareness about these emerging technologies and their potential applications in discovery and toxicologic pathology. This review provides an overview of commonly used, commercially available platforms for transcriptomic, proteomic, and multiomic analysis, discussing technical aspects and illustrative examples of their applications. To harness the power of spatial omics for translational drug discovery and human safety risk assessment, we emphasize the important role of pathologists at every stage of the workflow-from hypothesis generation to sample preparation, data analysis, and interpretation. Spatial omics technologies offer novel opportunities in target discovery, lead selection, preclinical assessment, and clinical development in compound development.

The intricate 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 and microbiome across multiple spatial modalities. We demonstrate MicroCart by investigating gut host and microbiome changes in a murine colitis model, using spatial proteomics, transcriptomics, and glycomics. 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, 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 multi-omics.

Spatial omics technologies decipher functional components of complex organs at cellular and subcellular resolutions. We introduce Spatial Graph Fourier Transform (SpaGFT) and apply graph signal processing to a wide range of spatial omics profiling platforms to generate their interpretable representations. This representation supports spatially variable gene identification and improves gene expression imputation, outperforming existing tools in analyzing human and mouse spatial transcriptomics data. SpaGFT can identify immunological regions for B cell maturation in human lymph nodes Visium data and characterize variations in secondary follicles using in-house human tonsil CODEX data. Furthermore, it can be integrated seamlessly into other machine learning frameworks, enhancing accuracy in spatial domain identification, cell type annotation, and subcellular feature inference by up to 40%. Notably, SpaGFT detects rare subcellular organelles, such as Cajal bodies and Set1/COMPASS complexes, in high-resolution spatial proteomics data. This approach provides an explainable graph representation method for exploring tissue biology and function.

Simultaneous detection of DNA, RNA and proteins within the native tissue microenvironment is a trifecta that promises to deliver valuable insights into fundamental aspects of the biological processes underlying health and disease. Recent technical advances in both in situ hybridization and highly multiplexed imaging have enabled this combined analysis, yet many approaches are limited by poor detection of low copy numbers or difficulties owing to protein epitope loss during tissue processing. Our approach, termed PANINI (protein and nucleic acid in situ imaging), enables the detection of low-copy nucleic acids while preserving protein epitopes in intact tissues. This is achieved by bypassing the protease digestion step, which is used in various in situ hybridization assays to increase the accessibility of target nucleic acids by disrupting the packed architecture of tissue matrices and nucleic acid-binding proteins. PANINI starts with a protease-free antigen retrieval protocol before the application of a highly sensitive custom branched-chain amplification method in which horseradish peroxidase catalyses the deposition of tyramine-linked reporter haptens for nucleic acid labelling. These labelled nucleic acid targets, in conjunction with other protein targets, can then be detected using various antibody-based imaging platforms. We demonstrated that PANINI is compatible with multiplex spatial imaging platforms, including conventional microscopes, multiplexed ion beam imaging (MIBI), co-detection by indexing (CODEX) and multispectral imaging on the Vectra Polaris platforms1.

Advancements in multiplexed tissue imaging technologies are vital in shaping our understanding of tissue microenvironmental influences in disease contexts. These technologies now allow us to relate the phenotype of individual cells to their higher-order roles in tissue organization and function. Multiplexed Ion Beam Imaging (MIBI) is one of such technologies, which uses metal isotope-labeled antibodies and secondary ion mass spectrometry (SIMS) to image more than 40 protein markers simultaneously within a single tissue section. Here, we describe an optimized MIBI workflow for high-plex analysis of Formalin-Fixed Paraffin-Embedded (FFPE) tissues following antigen retrieval, metal isotope-conjugated antibody staining, imaging using the MIBI instrument, and subsequent data processing and analysis. While this workflow is focused on imaging human FFPE samples using the MIBI, this workflow can be easily extended to model systems, biological questions, and multiplexed imaging modalities.

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.

Neuroblastoma is a pediatric cancer arising from the developing sympathoadrenal lineage with complex inter- and intra-tumoral heterogeneity. To chart this complexity, we generated a comprehensive cell atlas of 55 neuroblastoma patient tumors, collected from two pediatric cancer institutions, spanning a range of clinical, genetic, and histologic features. Our atlas combines single-cell/nucleus RNA-seq (sc/scRNA-seq), bulk RNA-seq, whole exome sequencing, DNA methylation profiling, spatial transcriptomics, and two spatial proteomic methods. Sc/snRNA-seq revealed three malignant cell states with features of sympathoadrenal lineage development. All of the neuroblastomas had malignant cells that resembled sympathoblasts and the more differentiated adrenergic cells. A subset of tumors had malignant cells in a mesenchymal cell state with molecular features of Schwann cell precursors. DNA methylation profiles defined four groupings of patients, which differ in the degree of malignant cell heterogeneity and clinical outcomes. Using spatial proteomics, we found that neuroblastomas are spatially compartmentalized, with malignant tumor cells sequestered away from immune cells. Finally, we identify spatially restricted signaling patterns in immune cells from spatial transcriptomics. To facilitate the visualization and analysis of our atlas as a resource for further research in neuroblastoma, single cell, and spatial-omics, all data are shared through the Human Tumor Atlas Network Data Commons at www.humantumoratlas.org.

Highly multiplexed protein imaging is emerging as a potent technique for analyzing protein distribution within cells and tissues in their native context. However, existing cell annotation methods utilizing high-plex spatial proteomics data are resource intensive and necessitate iterative expert input, thereby constraining their scalability and practicality for extensive datasets. We introduce MAPS (Machine learning for Analysis of Proteomics in Spatial biology), a machine learning approach facilitating rapid and precise cell type identification with human-level accuracy from spatial proteomics data. Validated on multiple in-house and publicly available MIBI and CODEX datasets, MAPS outperforms current annotation techniques in terms of speed and accuracy, achieving pathologist-level precision even for typically challenging cell types, including tumor cells of immune origin. By democratizing rapidly deployable and scalable machine learning annotation, MAPS holds significant potential to expedite advances in tissue biology and disease comprehension.

Diffuse large B-cell lymphoma, not-otherwise-specified, (DLBCL), is the most common aggressive non-Hodgkin lymphoma and a biologically heterogeneous disease. Despite the development of effective immunotherapies, the organization of the DLBCL tumor-immune microenvironment (TIME) remains poorly understood. We interrogated the intact TIME of 51 de novo DLBCLs with triplicate sampling to characterize 337,995 tumor and immune cells using a 27-plex antibody panel that captured cell lineage, architectural, and functional markers. We spatially assigned individual cells, identified local cell neighborhoods, and established their topographical organization in situ. We found that the organization of local tumor and immune cells can be modeled by six composite cell neighborhood types (CNTs). Differential CNT representation divided cases into three aggregate TIME categories: immune-deficient, dendritic-cell enriched (DC-enriched), and macrophage-enriched (Mac-enriched). Cases with immune-deficient TIMEs have tumor cell-rich CNTs wherein the few infiltrating immune cells are enriched near CD31-positive vessels in keeping with limited immune activity. Cases with DC-enriched TIMEs selectively include tumor cell-poor/immune cell-rich CNTs with high numbers of CD11c-positive dendritic cells and antigen-experienced T cells also enriched near CD31-positive vessels in keeping with increased immune activity. Cases with Mac-enriched TIMEs selectively include tumor cell-poor/immune cell-rich CNTs with high numbers of CD163-positive macrophages and CD8 T cells throughout the microenvironment, accompanied by increased IDO-1 and LAG-3 and decreased HLA-DR expression, and genetic signatures in keeping with immune evasion. Our findings reveal that the heterogenous cellular components of DLBCL are not randomly distributed but organized into CNTs that define aggregate TIMEs with distinct cellular, spatial, and functional features.

Cellular organization and functions encompass multiple scales in vivo. Emerging high-plex imaging technologies are limited in resolving subcellular biomolecular features. Expansion Microscopy (ExM) and related techniques physically expand samples for enhanced spatial resolution, but are challenging to be combined with high-plex imaging technologies to enable integrative multiscaled tissue biology insights. Here, we introduce Expand and comPRESS hydrOgels (ExPRESSO), an ExM framework that allows high-plex protein staining, physical expansion, and removal of water, while retaining the lateral tissue expansion. We demonstrate ExPRESSO imaging of archival clinical tissue samples on Multiplexed Ion Beam Imaging and Imaging Mass Cytometry platforms, with detection capabilities of > 40 markers. Application of ExPRESSO on archival human lymphoid and brain tissues resolved tissue architecture at the subcellular level, particularly that of the blood-brain barrier. ExPRESSO hence provides a platform for extending the analysis compatibility of hydrogel-expanded biospecimens to mass spectrometry, with minimal modifications to protocols and instrumentation.

Background and aims: Liver injury after COVID-19 vaccination is very rare and shows clinical and histomorphological similarities with autoimmune hepatitis (AIH). Little is known about the pathophysiology of COVID-19 vaccine-induced liver injury (VILI) and its relationship to AIH. Therefore, we compared VILI with AIH.

Methods: Formalin-fixed and paraffin-embedded liver biopsy samples from patients with VILI (n=6) and from patients with an initial diagnosis of AIH (n=9) were included. Both cohorts were compared by histomorphological evaluation, whole-transcriptome and spatial transcriptome sequencing, multiplex immunofluorescence and immune repertoire sequencing.

Results: Histomorphology was similar in both cohorts but showed more pronounced centrilobular necrosis in VILI. Gene expression profiling showed that mitochondrial metabolism and oxidative stress-related pathways were more and interferon response pathways less enriched in VILI. Multiplex analysis revealed that inflammation in VILI was dominated by CD8⁺ effector T cells, similar to drug-induced autoimmune like hepatitis (DI-AILH). In contrast, AIH showed a dominance of CD4⁺ effector T cells and CD79a⁺ B and plasma cells. T-cell receptor (TCR) and B-cell receptor (BCR) sequencing showed that T- and B-cell clones were more dominant in VILI than in AIH. In addition, many T-cell clones detected in the liver were also found in the blood. Interestingly, analysis of TCR beta chain and Ig heavy chain variable-joining gene usage further showed that TRBV6-1, TRBV5-1, TRBV7-6 and IgHV1-24 genes are used differently in VILI than in AIH.

Conclusions: Our analyses support that SARS-CoV-2 vaccination-induced liver injury is related to AIH but also shows distinct differences from AIH in histomorphology, pathway activation, cellular immune infiltrates, and TCR usage. VILI may be a separate entity, which is distinct from AIH and more closely related to DI-AILH.

Impact and implications: Little is known about the pathophysiology of COVID-19 vaccine-induced liver injury. Our analysis shows that COVID-19 vaccine-induced liver injury shares some similarities with autoimmune hepatitis, but also has distinct differences such as increased activation of metabolic pathways, a more prominent CD8+ T cell infiltrate, and an oligoclonal T and B cell response. Our findings suggest that vaccine-induced liver injury is a distinct disease entity. Therefore, there is a good chance that many patients with COVID-19 vaccine-induced liver injury will recover completely and do not develop long-term autoimmune hepatitis.

Epstein-Barr virus (EBV) immortalization of resting B lymphocytes (RBLs) to lymphoblastoid cell lines (LCLs) models human DNA tumor virus oncogenesis. RBL and LCL chromatin interaction maps are compared to identify the spatial and temporal genome architectural changes during EBV B cell transformation. EBV induces global genome reorganization where contact domains frequently merge or subdivide during transformation. Repressed B compartments in RBLs frequently switch to active A compartments in LCLs. LCLs gain 40% new contact domain boundaries. Newly gained LCL boundaries have strong CTCF binding at their borders while in RBLs, the same sites have much less CTCF binding. Some LCL CTCF sites also have EBV nuclear antigen (EBNA) leader protein EBNALP binding. LCLs have more local interactions than RBLs at LCL dependency factors and super-enhancer targets. RNA Pol II HiChIP and FISH of RBL and LCL further validate the Hi-C results. EBNA3A inactivation globally alters LCL genome interactions. EBNA3A inactivation reduces CTCF and RAD21 DNA binding. EBNA3C inactivation rewires the looping at the CDKN2A/B and AICDA loci. Disruption of a CTCF site at AICDA locus increases AICDA expression. These data suggest that EBV controls lymphocyte growth by globally reorganizing host genome architecture to facilitate the expression of key oncogenes.

The ability to align individual cellular information from multiple experimental sources is fundamental for a systems-level understanding of biological processes. However, currently available tools are mainly designed for single-cell transcriptomics matching and integration, and generally rely on a large number of shared features across datasets for cell matching. This approach underperforms when applied to single-cell proteomic datasets due to the limited number of parameters simultaneously accessed and lack of shared markers across these experiments. Here, we introduce a cell-matching algorithm, matching with partial overlap (MARIO) that accounts for both shared and distinct features, while consisting of vital filtering steps to avoid suboptimal matching. MARIO accurately matches and integrates data from different single-cell proteomic and multimodal methods, including spatial techniques and has cross-species capabilities. MARIO robustly matched tissue macrophages identified from COVID-19 lung autopsies via codetection by indexing imaging to macrophages recovered from COVID-19 bronchoalveolar lavage fluid by cellular indexing of transcriptomes and epitopes by sequencing, revealing unique immune responses within the lung microenvironment of patients with COVID.

Glucose is a universal bioenergy source; however, its role in controlling protein interactions is unappreciated, as are its actions during differentiation-associated intracellular glucose elevation. Azido-glucose click chemistry identified glucose binding to a variety of RNA binding proteins (RBPs), including the DDX21 RNA helicase, which was found to be essential for epidermal differentiation. Glucose bound the ATP-binding domain of DDX21, altering protein conformation, inhibiting helicase activity, and dissociating DDX21 dimers. Glucose elevation during differentiation was associated with DDX21 re-localization from the nucleolus to the nucleoplasm where DDX21 assembled into larger protein complexes containing RNA splicing factors. DDX21 localized to specific SCUGSDGC motif in mRNA introns in a glucose-dependent manner and promoted the splicing of key pro-differentiation genes, including GRHL3, KLF4, OVOL1, and RBPJ. These findings uncover a biochemical mechanism of action for glucose in modulating the dimerization and function of an RNA helicase essential for tissue differentiation.

Obesity, characterized by chronic low-grade inflammation of the adipose tissue, is associated with adverse coronavirus disease 2019 (COVID-19) outcomes, yet the underlying mechanism is unknown. To explore whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection of adipose tissue contributes to pathogenesis, we evaluated COVID-19 autopsy cases and deeply profiled the response of adipose tissue to SARS-CoV-2 infection in vitro. In COVID-19 autopsy cases, we identified SARS-CoV-2 RNA in adipocytes with an associated inflammatory infiltrate. We identified two distinct cellular targets of infection: adipocytes and a subset of inflammatory adipose tissue-resident macrophages. Mature adipocytes were permissive to SARS-CoV-2 infection; although macrophages were abortively infected, SARS-CoV-2 initiated inflammatory responses within both the infected macrophages and bystander preadipocytes. These data suggest that SARS-CoV-2 infection of adipose tissue could contribute to COVID-19 severity through replication of virus within adipocytes and through induction of local and systemic inflammation driven by infection of adipose tissue-resident macrophages.

How SARS-CoV-2 penetrates the airway barrier of mucus and periciliary mucins to infect nasal epithelium remains unclear. Using primary nasal epithelial organoid cultures, we found that the virus attaches to motile cilia via the ACE2 receptor. SARS-CoV-2 traverses the mucus layer, using motile cilia as tracks to access the cell body. Depleting cilia blocks infection for SARS-CoV-2 and other respiratory viruses. SARS-CoV-2 progeny attach to airway microvilli 24 h post-infection and trigger formation of apically extended and highly branched microvilli that organize viral egress from the microvilli back into the mucus layer, supporting a model of virus dispersion throughout airway tissue via mucociliary transport. Phosphoproteomics and kinase inhibition reveal that microvillar remodeling is regulated by p21-activated kinases (PAK). Importantly, Omicron variants bind with higher affinity to motile cilia and show accelerated viral entry. Our work suggests that motile cilia, microvilli, and mucociliary-dependent mucus flow are critical for efficient virus replication in nasal epithelia.

Intratumoral heterogeneity is a seminal feature of human tumors contributing to tumor progression and response to treatment. Current technologies are still largely unsuitable to accurately track phenotypes and clonal evolution within tumors, especially in response to genetic manipulations. Here, we developed epitopes for imaging using combinatorial tagging (EpicTags), which we coupled to multiplexed ion beam imaging (EpicMIBI) for in situ tracking of barcodes within tissue microenvironments. Using EpicMIBI, we dissected the spatial component of cell lineages and phenotypes in xenograft models of small cell lung cancer. We observed emergent properties from mixed clones leading to the preferential expansion of clonal patches for both neuroendocrine and non-neuroendocrine cancer cell states in these models. In a tumor model harboring a fraction of PTEN-deficient cancer cells, we observed a non-autonomous increase of clonal patch size in PTEN wild-type cancer cells. EpicMIBI facilitates in situ interrogation of cell-intrinsic and cell-extrinsic processes involved in intratumoral heterogeneity.

Highly multiplexed, single-cell imaging has revolutionized our understanding of spatial cellular interactions associated with health and disease. With ever-increasing numbers of antigens, region sizes, and sample sizes, multiplexed fluorescence imaging experiments routinely produce terabytes of data. Fast and accurate processing of these large-scale, high-dimensional imaging data is essential to ensure reliable segmentation and identification of cell types and for characterization of cellular neighborhoods and inference of mechanistic insights. Here, we describe RAPID, a Real-time, GPU-Accelerated Parallelized Image processing software for large-scale multiplexed fluorescence microscopy Data. RAPID deconvolves large-scale, high-dimensional fluorescence imaging data, stitches and registers images with axial and lateral drift correction, and minimizes tissue autofluorescence such as that introduced by erythrocytes. Incorporation of an open source CUDA-driven, GPU-assisted deconvolution produced results similar to fee-based commercial software. RAPID reduces data processing time and artifacts and improves image contrast and signal-to-noise compared to our previous image processing pipeline, thus providing a useful tool for accurate and robust analysis of large-scale, multiplexed, fluorescence imaging data.

We present here a detailed protocol for PANINI (protein and nucleic acid in situ imaging), a technique that enables the concurrent staining of protein and nucleic acids in archival tissue sections. PANINI utilizes an optimized antigen retrieval strategy that forgoes protease treatment while retaining high sensitivity of nucleic acid detection down to single genomic events. While the protocol here is geared toward standard fluorescent microscopes with 3–4 available channels, PANINI is compatible with many commercial multiplexed tissue imaging modalities.

The biological determinants underlying the range of coronavirus 2019 (COVID-19) clinical manifestations are not fully understood. Here, over 1,400 plasma proteins and 2,600 single-cell immune features comprising cell phenotype, endogenous signaling activity, and signaling responses to inflammatory ligands are cross-sectionally assessed in peripheral blood from 97 patients with mild, moderate, and severe COVID-19 and 40 uninfected patients. Using an integrated computational approach to analyze the combined plasma and single-cell proteomic data, we identify and independently validate a multi-variate model classifying COVID-19 severity (multi-class area under the curve [AUC]_training = 0.799, p = 4.2e-6; multi-class AUC_validation = 0.773, p = 7.7e-6). Examination of informative model features reveals biological signatures of COVID-19 severity, including the dysregulation of JAK/STAT, MAPK/mTOR, and nuclear factor κB (NF-κB) immune signaling networks in addition to recapitulating known hallmarks of COVID-19. These results provide a set of early determinants of COVID-19 severity that may point to therapeutic targets for prevention and/or treatment of COVID-19 progression.

Adult salivary stem/progenitor cells (SSPC) have an intrinsic property to self-renew in order to maintain tissue architecture and homeostasis. Adult salivary glands have been documented to harbor SSPC, which have been shown to play a vital role in the regeneration of the glandular structures postradiation damage. We have previously demonstrated that activation of aldehyde dehydrogenase 3A1 (ALDH3A1) after radiation reduced aldehyde accumulation in SSPC, leading to less apoptosis and improved salivary function. We subsequently found that sustained pharmacological ALDH3A1 activation is critical to enhance regeneration of murine submandibular gland after radiation damage. Further investigation shows that ALDH3A1 function is crucial for SSPC self-renewal and survival even in the absence of radiation stress. Salivary glands from Aldh3a1 ^-/- mice have fewer acinar structures than wildtype mice. ALDH3A1 deletion or pharmacological inhibition in SSPC leads to a decrease in mitochondrial DNA copy number, lower expression of mitochondrial specific genes and proteins, structural abnormalities, lower membrane potential, and reduced cellular respiration. Loss or inhibition of ALDH3A1 also elevates ROS levels, depletes glutathione pool, and accumulates ALDH3A1 substrate 4-hydroxynonenal (4-HNE, a lipid peroxidation product), leading to decreased survival of murine SSPC that can be rescued by treatment with 4-HNE specific carbonyl scavengers. Our data indicate that ALDH3A1 activity protects mitochondrial function and is important for the regeneration activity of SSPC. This knowledge will help to guide our translational strategy of applying ALDH3A1 activators in the clinic to prevent radiation-related hyposalivation in head and neck cancer patients.

Understanding the mechanisms of HIV tissue persistence necessitates the ability to visualize tissue microenvironments where infected cells reside; however, technological barriers limit our ability to dissect the cellular components of these HIV reservoirs. Here, we developed protein and nucleic acid in situ imaging (PANINI) to simultaneously quantify DNA, RNA, and protein levels within these tissue compartments. By coupling PANINI with multiplexed ion beam imaging (MIBI), we measured over 30 parameters simultaneously across archival lymphoid tissues from healthy or simian immunodeficiency virus (SIV)-infected nonhuman primates. PANINI enabled the spatial dissection of cellular phenotypes, functional markers, and viral events resulting from infection. SIV infection induced IL-10 expression in lymphoid B cells, which correlated with local macrophage M2 polarization. This highlights a potential viral mechanism for conditioning an immunosuppressive tissue environment for virion production. The spatial multimodal framework here can be extended to decipher tissue responses in other infectious diseases and tumor biology.

Master transcription factors (TFs) directly regulate present and future cell states by binding DNA regulatory elements and driving gene-expression programs. Their abundance influences epigenetic priming to different cell fates at the chromatin level, especially in the context of differentiation. In order to link TF protein abundance to changes in TF motif accessibility and open chromatin, we developed InTAC-seq, a method for simultaneous quantification of genome-wide chromatin accessibility and intracellular protein abundance in fixed cells. Our method produces high-quality data and is a cost-effective alternative to single-cell techniques. We showcase our method by purifying bone marrow (BM) progenitor cells based on GATA-1 protein levels and establish high GATA-1-expressing BM cells as both epigenetically and functionally similar to erythroid-committed progenitors.

The problem of precise characterization, analysis, and eventual identification of unknown materials arises in many fields and takes many forms, depending on the nature of the substances under study. In the first part of this paper we review common, modern mass spectrometry techniques applied to such studies. We also give an overview of improvements made to these technologies in recent years by Silicon Valley companies and other teams focused on precise biomedical research dependent upon sensitive techniques, yet applicable to a wide range of non-biological materials. In the second and third parts of the paper we review practical experiences applying these techniques to the simplest case of the characterization of solid materials (as opposed to liquids or gases) and comparing our results with previously undertaken isotopic analysis. In particular, we describe our correlations of that analysis with the patterns described by witnesses in a well-documented, still-unexplained incident, initially thought to be of aerospace origin, which gave rise to the deposition of unknown material, and by the investigators who handled it in the field and the laboratory. The lessons from this specific investigation are applicable to a wider range of issues in reverse engineering of complex, esoteric materials, and aerospace forensics.

Non-human primate (NHP) animal models are an integral part of the drug research and development process. For some biothreat pathogens, animal model challenge studies may offer the only possibility to evaluate medical countermeasure efficacy. A thorough understanding of host immune responses in such NHP models is therefore vital. However, applying antibody-based immune characterization techniques to NHP models requires extensive reagent development for species compatibility. In the case of studies involving high consequence pathogens, further optimization for use of inactivated samples may be required. Here, we describe the first optimized CO-Detection by indEXing (CODEX) multiplexed tissue imaging antibody panel for deep profiling of spatially resolved single-cell immune responses in rhesus macaques. This 21-marker panel is composed of a set of 18 antibodies that stratify major immune cell types along with a set three Ebola virus (EBOV)-specific antibodies. We validated these two sets of markers using immunohistochemistry and CODEX in fully inactivated Formalin-Fixed Paraffin-Embedded (FFPE) tissues from mock and EBOV challenged macaques respectively and provide an efficient framework for orthogonal validation of multiple antibody clones using CODEX multiplexed tissue imaging. We also provide the antibody clones and oligonucleotide tag sequences as a valuable resource for other researchers to recreate this reagent set for future studies of tissue immune responses to EBOV infection and other diseases.

Background: Emerging evidence suggests that chronic rhinosinusitis with nasal polyps (CRSwNP) is a highly heterogeneous disease with disparate inflammatory characteristics between different racial groups and geographies. Currently, little is known about possible underlying distinguishing factors between these inflammatory differences.
Objective: Our aim was to interrogate differences in CRSwNP disease between White/non-Asian patients and Japanese patients by using whole transcriptome and single-cell RNA gene expression profiling of nasal polyps (NPs).
Methods: We performed whole transcriptome RNA sequencing with endotype stratification of NPs from 8 White patients (residing in the United States) and 9 Japanese patients (residing in Japan). Reproducibility was confirmed by quantitative PCR in an independent validation set of 46 White and 31 Japanese patients. Single-cell RNA sequencing (scRNAseq) was used to stratify key cell types for contributory transcriptional signatures.
Results: Unsupervised clustering analysis identified 2 major endotypes that were present within both cohorts of patients with NPs and had previously been reported at the cytokine level: (1) type 2 endotype and (2) non-type 2 endotype. Importantly, there was a statistically significant difference in the proportion of these endotypes between these geographically distinct subgroups with NPs (P = .03). Droplet-based single-cell RNA sequencing further identified prominent type 2 inflammatory transcript expression: C-C motif chemokine ligand 13 (CCL13) and CCL18 in M2 macrophages, as well as cystatin SN (CST1) and CCL26 in basal, suprabasal, and secretory epithelial cells.
Conclusion: NPs from both racial groups harbor the same 2 major endotypes, which we have determined to be present in differing ratios between each cohort with CRSwNP disease. Distinct inflammatory and epithelial cells contribute to the type 2 inflammatory profiles observed.

Cutaneous T cell lymphomas (CTCL) are rare but aggressive cancers without effective treatments. While a subset of patients derive benefit from PD-1 blockade, there is a critically unmet need for predictive biomarkers of response. Herein, we perform CODEX multiplexed tissue imaging and RNA sequencing on 70 tumor regions from 14 advanced CTCL patients enrolled in a pembrolizumab clinical trial (NCT02243579). We find no differences in the frequencies of immune or tumor cells between responders and non-responders. Instead, we identify topographical differences between effector PD-1 CD4 T cells, tumor cells, and immunosuppressive Tregs, from which we derive a spatial biomarker, termed the SpatialScore, that correlates strongly with pembrolizumab response in CTCL. The SpatialScore coincides with differences in the functional immune state of the tumor microenvironment, T cell function, and tumor cell-specific chemokine recruitment and is validated using a simplified, clinically accessible tissue imaging platform. Collectively, these results provide a paradigm for investigating the spatial balance of effector and suppressive T cell activity and broadly leveraging this biomarker approach to inform the clinical use of immunotherapies.

Developing new influenza vaccines with improved performance and easier administration routes hinges on defining correlates of protection. Vaccine-elicited cellular correlates of protection for influenza in humans have not yet been demonstrated. A phase-2 double-blind randomized placebo and active (inactivated influenza vaccine) controlled study provides evidence that a human-adenovirus-5-based oral influenza vaccine tablet (VXA-A1.1) can protect from H1N1 virus challenge in humans. Mass cytometry characterization of vaccine-elicited cellular immune responses identified shared and vaccine-type-specific responses across B and T cells. For VXA-A1.1, the abundance of hemagglutinin-specific plasmablasts and plasmablasts positive for integrin α4β7, phosphorylated STAT5, or lacking expression of CD62L at day 8 were significantly correlated with protection from developing viral shedding following virus challenge at day 90 and contributed to an effective machine learning model of protection. These findings reveal the characteristics of vaccine-elicited cellular correlates of protection for an oral influenza vaccine.

Understanding viral tropism is an essential step toward reducing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, decreasing mortality from coronavirus disease 2019 (COVID-19) and limiting opportunities for mutant strains to arise. Currently, little is known about the extent to which distinct tissue sites in the human head and neck region and proximal respiratory tract selectively permit SARS-CoV-2 infection and replication. In this translational study, we discover key variabilities in expression of angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2), essential SARS-CoV-2 entry factors, among the mucosal tissues of the human proximal airways. We show that SARS-CoV-2 infection is present in all examined head and neck tissues, with a notable tropism for the nasal cavity and tracheal mucosa. Finally, we uncover an association between smoking and higher SARS-CoV-2 viral infection in the human proximal airway, which may explain the increased susceptibility of smokers to developing severe COVID-19. This is at least partially explained by differences in interferon (IFN)-β1 levels between smokers and non-smokers.

Simultaneous visualization of the relationship between multiple biomolecules and their ligands or small molecules at the nanometer scale in cells will enable greater understanding of how biological processes operate. We present here high-definition multiplex ion beam imaging (HD-MIBI), a secondary ion mass spectrometry approach capable of high-parameter imaging in 3D of targeted biological entities and exogenously added structurally-unmodified small molecules. With this technology, the atomic constituents of the biomolecules themselves can be used in our system as the “tag” and we demonstrate measurements down to ~30 nm lateral resolution. We correlated the subcellular localization of the chemotherapy drug cisplatin simultaneously with five subnuclear structures. Cisplatin was preferentially enriched in nuclear speckles and excluded from closed-chromatin regions, indicative of a role for cisplatin in active regions of chromatin. Unexpectedly, cells surviving multi-drug treatment with cisplatin and the BET inhibitor JQ1 demonstrated near total cisplatin exclusion from the nucleus, suggesting that selective subcellular drug relocalization may modulate resistance to this important chemotherapeutic treatment. Multiplexed high-resolution imaging techniques, such as HD-MIBI, will enable studies of biomolecules and drug distributions in biologically relevant subcellular microenvironments by visualizing the processes themselves in concert, rather than inferring mechanism through surrogate analyses.

Multiplex imaging technologies are now routinely capable of measuring more than 40 antibody-labeled parameters in single cells. However, lateral spillage of signals in densely packed tissues presents an obstacle to the assignment of high-dimensional spatial features to individual cells for accurate cell-type annotation. We devised a method to correct for lateral spillage of cell surface markers between adjacent cells termed REinforcement Dynamic Spillover EliminAtion (REDSEA). The use of REDSEA decreased contaminating signals from neighboring cells. It improved the recovery of marker signals across both isotopic (i.e., Multiplexed Ion Beam Imaging) and immunofluorescent (i.e., Cyclic Immunofluorescence) multiplexed images resulting in a marked improvement in cell-type classification.

Immunotherapies are revolutionizing cancer treatment by boosting the natural ability of the immune system. In addition to antibodies against traditional checkpoint molecules or their ligands (i.e., CTLA-4, PD-1, and PD-L1), therapies targeting molecules such as ICOS, IDO-1, LAG-3, OX40, TIM-3, and VISTA are currently in clinical trials. To better inform clinical care and the design of therapeutic combination strategies, the co-expression of immunoregulatory proteins on individual immune cells within the tumor microenvironment must be robustly characterized. Highly multiplexed tissue imaging platforms, such as CO-Detection by indEXing (CODEX), are primed to meet this need by enabling >50 markers to be simultaneously analyzed in single-cells on formalin-fixed paraffin-embedded (FFPE) tissue sections. Assembly and validation of antibody panels is particularly challenging, with respect to the specificity of antigen detection and robustness of signal over background. Herein, we report the design, development, optimization, and application of a 56-marker CODEX antibody panel to eight cutaneous T cell lymphoma (CTCL) patient samples. This panel is comprised of structural, tumor, and immune cell markers, including eight immunoregulatory proteins that are approved or currently undergoing clinical trials as immunotherapy targets. Here we provide a resource to enable extensive high-dimensional, spatially resolved characterization of the tissue microenvironment across tumor types and imaging modalities. This framework provides researchers with a readily applicable blueprint to study tumor immunology, tissue architecture, and enable mechanistic insights into immunotherapeutic targets.

Emerging evidence points toward an intricate relationship between the pandemic of coronavirus disease 2019 (COVID-19) and diabetes. While preexisting diabetes is associated with severe COVID-19, it is unclear whether COVID-19 severity is a cause or consequence of diabetes. To mechanistically link COVID-19 to diabetes, we tested whether insulin-producing pancreatic β cells can be infected by SARS-CoV-2 and cause β cell depletion. We found that the SARS-CoV-2 receptor, ACE2, and related entry factors (TMPRSS2, NRP1, and TRFC) are expressed in β cells, with selectively high expression of NRP1. We discovered that SARS-CoV-2 infects human pancreatic β cells in patients who succumbed to COVID-19 and selectively infects human islet β cells in vitro. We demonstrated that SARS-CoV-2 infection attenuates pancreatic insulin levels and secretion and induces β cell apoptosis, each rescued by NRP1 inhibition. Phosphoproteomic pathway analysis of infected islets indicates apoptotic β cell signaling, similar to that observed in type 1 diabetes (T1D). In summary, our study shows SARS-CoV-2 can directly induce β cell killing.

Multiplexed ion beam imaging (MIBI) has been previously used to profile multiple parameters in two dimensions in single cells within tissue slices. Here, a mathematical and technical framework for three-dimensional (3D) subcellular MIBI is presented. Ion-beam tomography (IBT) compiles ion beam images that are acquired iteratively across successive, multiple scans, and later assembled into a 3D format without loss of depth resolution. Algorithmic deconvolution, tailored for ion beams, is then applied to the transformed ion image series, yielding 4-fold enhanced ion beam data cubes. To further generate 3D sub-ion-beam-width precision visuals, isolated ion molecules are localized in the raw ion beam images, creating an approach coined as SILM, secondary ion beam localization microscopy, providing sub-25 nm accuracy in original ion images. Using deep learning, a parameter-free reconstruction method for ion beam tomograms with high accuracy is developed for low-density targets. In cultured cancer cells and tissues, IBT enables accessible visualization of 3D volumetric distributions of genomic regions, RNA transcripts, and protein factors with 5 nm axial resolution using isotope-enrichments and label-free elemental analyses. Multiparameter imaging of subcellular features at near macromolecular resolution is implemented by the IBT tools as a general biocomputation pipeline for imaging mass spectrometry.

Primary effusion lymphoma (PEL) has a very poor prognosis. To evaluate the contributions of enhancers/promoters interactions to PEL cell growth and survival, here we produce H3K27ac HiChIP datasets in PEL cells. This allows us to generate the PEL enhancer connectome, which links enhancers and promoters in PEL genome-wide. We identify more than 8000 genomic interactions in each PEL cell line. By incorporating HiChIP data with H3K27ac ChIP-seq data, we identify interactions between enhancers/enhancers, enhancers/promoters, and promoters/promoters. HiChIP further links PEL super-enhancers to PEL dependency factors MYC, IRF4, MCL1, CCND2, MDM2, and CFLAR. CRISPR knock out of MEF2C and IRF4 significantly reduces MYC and IRF4 super-enhancer H3K27ac signal. Knock out also reduces MYC and IRF4 expression. CRISPRi perturbation of these super-enhancers by tethering transcription repressors to enhancers significantly reduces target gene expression and reduces PEL cell growth. These data provide insights into PEL molecular pathogenesis.

Influenza is a significant cause of morbidity and mortality worldwide. Here we show changes in the abundance and activation states of more than 50 immune cell subsets in 35 individuals over 11 time points during human A/California/2009 (H1N1) virus challenge monitored using mass cytometry along with other clinical assessments. Peak change in monocyte, B cell, and T cell subset frequencies coincided with peak virus shedding, followed by marked activation of T and NK cells. Results led to the identification of CD38 as a critical regulator of plasmacytoid dendritic cell function in response to influenza virus. Machine learning using study-derived clinical parameters and single-cell data effectively classified and predicted susceptibility to infection. The coordinated immune cell dynamics defined in this study provide a framework for identifying novel correlates of protection in the evaluation of future influenza therapeutics.

The coronavirus SARS-CoV-2 is the causative agent of the ongoing severe acute respiratory disease pandemic COVID-19. Tissue and cellular tropism is one key to understanding the pathogenesis of SARS-CoV-2. We investigate the expression and subcellular localization of the SARS-CoV-2 receptor, angiotensin-converting enzyme 2 (ACE2), within the upper (nasal) and lower (pulmonary) respiratory tracts of human donors using a diverse panel of banked tissues. Here, we report our discovery that the ACE2 receptor protein robustly localizes within the motile cilia of airway epithelial cells, which likely represents the initial or early subcellular site of SARS-CoV-2 viral entry during host respiratory transmission. We further determine whether ciliary ACE2 expression in the upper airway is influenced by patient demographics, clinical characteristics, comorbidities, or medication use, and show the first mechanistic evidence that the use of angiotensin-converting enzyme inhibitors (ACEI) or angiotensin II receptor blockers (ARBs) does not increase susceptibility to SARS-CoV-2 infection through enhancing the expression of ciliary ACE2 receptor. These findings are crucial to our understanding of the transmission of SARS-CoV-2 for prevention and control of this virulent pathogen.

Since the outbreak of coronavirus disease 2019 (COVID-19), there has been a debate whether pregnant women are at a specific risk for COVID-19 and whether it might be vertically transmittable through the placenta. We present a series of five placentas of SARS coronavirus 2 (SARS-CoV-2)-positive women who had been diagnosed with mild symptoms of COVID-19 or had been asymptomatic before birth. We provide a detailed histopathologic description of morphological changes accompanied by an analysis of presence of SARS-CoV-2 in the placental tissue. All placentas were term deliveries (40th and 41st gestational weeks). One SARS-CoV-2-positive patient presented with cough and dyspnoea. This placenta showed prominent lymphohistiocytic villitis and intervillositis and signs of maternal and foetal malperfusion. Viral RNA was present in both placenta tissue and the umbilical cord and could be visualized by in situ hybridization in the decidua. SARS-CoV-2 tests were negative at the time of delivery of 3/5 women, and their placentas did not show increased inflammatory infiltrates. Signs of maternal and/or foetal malperfusion were present in 100% and 40% of cases, respectively. There was no transplacental transmission to the infants. In our cohort, we can document different time points regarding SARS-CoV-2 infection. In acute COVID-19, prominent lymphohistiocytic villitis may occur and might potentially be attributable to SARS-CoV-2 infection of the placenta. Furthermore, there are histopathological signs of maternal and foetal malperfusion, which might have a relationship to an altered coagulative or microangiopathic state induced by SARS-CoV-2, yet this cannot be proven considering a plethora of confounding factors.

To define the cellular composition and architecture of cutaneous squamous cell carcinoma (cSCC), we combined single-cell RNA sequencing with spatial transcriptomics and multiplexed ion beam imaging from a series of human cSCCs and matched normal skin. cSCC exhibited four tumor subpopulations, three recapitulating normal epidermal states, and a tumor-specific keratinocyte (TSK) population unique to cancer, which localized to a fibrovascular niche. Integration of single-cell and spatial data mapped ligand-receptor networks to specific cell types, revealing TSK cells as a hub for intercellular communication. Multiple features of potential immunosuppression were observed, including T regulatory cell (Treg) co-localization with CD8 T cells in compartmentalized tumor stroma. Finally, single-cell characterization of human tumor xenografts and in vivo CRISPR screens identified essential roles for specific tumor subpopulation-enriched gene networks in tumorigenesis. These data define cSCC tumor and stromal cell subpopulations, the spatial niches where they interact, and the communicating gene networks that they engage in cancer.

Unexplained infertility affects 2%-3% of reproductive-aged couples. One approach to identifying genes involved in infertility is to study subjects with this clinical phenotype and a de novo balanced chromosomal aberration (BCA). While BCAs may reduce fertility by production of unbalanced gametes, a chromosomal rearrangement may also disrupt or dysregulate genes important in fertility. One such subject, DGAP230, has severe oligozoospermia and 46,XY,t(20;22)(q13.3;q11.2). We identified exclusive overexpression of SYCP2 from the der(20) allele that is hypothesized to result from enhancer adoption. Modeling the dysregulation in budding yeast resulted in disrupted structural integrity of the synaptonemal complex, a common cause of defective spermatogenesis in mammals. Exome sequencing of infertile males revealed three heterozygous SYCP2 frameshift variants in additional subjects with cryptozoospermia and azoospermia. In sum, this investigation illustrates the power of precision cytogenetics for annotation of the infertile genome, suggests that these mechanisms should be considered as an alternative etiology to that of segregation of unbalanced gametes in infertile men harboring a BCA, and provides evidence of SYCP2-mediated male infertility in humans.

Epstein-Barr virus (EBV) causes infectious mononucleosis and is associated with multiple human malignancies. EBV drives B-cell proliferation, which contributes to the pathogenesis of multiple lymphomas. Yet, knowledge of how EBV subverts host biosynthetic pathways to transform resting lymphocytes into activated lymphoblasts remains incomplete. Using a temporal proteomic dataset of EBV primary human B-cell infection, we identified that cholesterol and fatty acid biosynthetic pathways were amongst the most highly EBV induced. Epstein-Barr nuclear antigen 2 (EBNA2), sterol response element binding protein (SREBP) and MYC each had important roles in cholesterol and fatty acid pathway induction. Unexpectedly, HMG-CoA reductase inhibitor chemical epistasis experiments revealed that mevalonate pathway production of geranylgeranyl pyrophosphate (GGPP), rather than cholesterol, was necessary for EBV-driven B-cell outgrowth, perhaps because EBV upregulated the low-density lipoprotein receptor in newly infected cells for cholesterol uptake. Chemical and CRISPR genetic analyses highlighted downstream GGPP roles in EBV-infected cell small G protein Rab activation. Rab13 was highly EBV-induced in an EBNA3-dependent manner and served as a chaperone critical for latent membrane protein (LMP) 1 and 2A trafficking and target gene activation in newly infected and in lymphoblastoid B-cells. Collectively, these studies identify highlight multiple potential therapeutic targets for prevention of EBV-transformed B-cell growth and survival.

Super-enhancers (SEs) are clusters of enhancers marked by extraordinarily high and broad chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) signals for H3K27ac or other transcription factors (TFs). SEs play pivotal roles in development and oncogenesis. Epstein-Barr virus (EBV) super-enhancers (ESEs) are co-occupied by all essential EBV oncogenes and EBV-activated NF-κB subunits. Perturbation of ESEs stops lymphoblastoid cell line (LCL) growth. To further characterize ESEs and identify proteins critical for ESE function, MYC ESEs were cloned upstream of a green fluorescent protein (GFP) reporter. Reporters driven by MYC ESEs 525 kb and 428 kb upstream of MYC (525ESE and 428ESE) had very high activities in LCLs but not in EBV-negative BJAB cells. EBNA2 activated MYC ESE-driven luciferase reporters. CRISPRi targeting 525ESE significantly decreased MYC expression. Genome-wide CRISPR screens identified factors essential for ESE activity. TBP-associated factor (TAF) family proteins, including TAF8, TAF11, and TAF3, were essential for the activity of the integrated 525ESE-driven reporter in LCLs. TAF8 and TAF11 knockout significantly decreased 525ESE activity and MYC transcription. MEF2C was also identified to be essential for 525ESE activity. Depletion of MEF2C decreased 525ESE reporter activity, MYC expression, and LCL growth. MEF2C cDNA resistant to CRIPSR cutting rescued MEF2C knockout and restored 525ESE reporter activity and MYC expression. MEF2C depletion decreased IRF4, EBNA2, and SPI1 binding to 525ESE in LCLs. MEF2C depletion also affected the expression of other ESE target genes, including the ETS1 and BCL2 genes. These data indicated that in addition to EBNA2, TAF family members and MEF2C are essential for ESE activity, MYC expression, and LCL growth. SEs play critical roles in cancer development. Since SEs assemble much bigger protein complexes on enhancers than typical enhancers (TEs), they are more sensitive than TEs to perturbations. Understanding the protein composition of SEs that are linked to key oncogenes may identify novel therapeutic targets. A genome-wide CRISPR screen specifically identified proteins essential for MYC ESE activity but not simian virus 40 (SV40) enhancer. These proteins not only were essential for the reporter activity but also were also important for MYC expression and LCL growth. Targeting these proteins may lead to new therapies for EBV-associated cancers.

CD40 has major roles in B cell development, activation, and germinal center responses. CD40 hypoactivity causes immunodeficiency whereas its overexpression causes autoimmunity and lymphomagenesis. To systematically identify B cell autonomous CD40 regulators, we use CRISPR/Cas9 genome-scale screens in Daudi B cells stimulated by multimeric CD40 ligand. These highlight known CD40 pathway components and reveal multiple additional mechanisms regulating CD40. The nuclear ubiquitin ligase FBXO11 supports CD40 expression by targeting repressors CTBP1 and BCL6. FBXO11 knockout decreases primary B cell CD40 abundance and impairs class-switch recombination, suggesting that frequent lymphoma monoallelic FBXO11 mutations may balance BCL6 increase with CD40 loss. At the mRNA level, CELF1 controls exon splicing critical for CD40 activity, while the N6-adenosine methyltransferase WTAP negatively regulates CD40 mRNA abundance. At the protein level, ESCRT negatively regulates activated CD40 levels while the negative feedback phosphatase DUSP10 limits downstream MAPK responses. These results serve as a resource for future studies and highlight potential therapeutic targets.

Epstein-Barr virus (EBV) infection of human primary resting B lymphocytes (RBLs) leads to the establishment of lymphoblastoid cell lines (LCLs) that can grow indefinitely EBV transforms RBLs through the expression of viral latency genes, and these genes alter host transcription programs. To globally measure the transcriptome changes during EBV transformation, primary human resting B lymphocytes (RBLs) were infected with B95.8 EBV for 0, 2, 4, 7, 14, 21, and 28 days, and poly(A) plus RNAs were analyzed by transcriptome sequencing (RNA-seq). Analyses of variance (ANOVAs) found 3,669 protein-coding genes that were differentially expressed (false-discovery rate [FDR] < 0.01). Ninety-four percent of LCL genes that are essential for LCL growth and survival were differentially expressed. Pathway analyses identified a significant enrichment of pathways involved in cell proliferation, DNA repair, metabolism, and antiviral responses. RNA-seq also identified long noncoding RNAs (lncRNAs) differentially expressed during EBV infection. Clustered regularly interspaced short palindromic repeat (CRISPR) interference (CRISPRi) and CRISPR activation (CRISPRa) found that CYTOR and NORAD lncRNAs were important for LCL growth. During EBV infection, type III EBV latency genes were expressed rapidly after infection. Immediately after LCL establishment, EBV lytic genes were also expressed in LCLs, and ∼4% of the LCLs express gp350. Chromatin immune precipitation followed by deep sequencing (ChIP-seq) and POLR2A chromatin interaction analysis followed by paired-end tag sequencing (ChIA-PET) data linked EBV enhancers to 90% of EBV-regulated genes. Many genes were linked to enhancers occupied by multiple EBNAs or NF-κB subunits. Incorporating these assays, we generated a comprehensive EBV regulome in LCLs. Epstein-Barr virus (EBV) immortalization of resting B lymphocytes (RBLs) is a useful model system to study EBV oncogenesis. By incorporating transcriptome sequencing (RNA-seq), chromatin immune precipitation followed by deep sequencing (ChIP-seq), chromatin interaction analysis followed by paired-end tag sequencing (ChIA-PET), and genome-wide clustered regularly interspaced short palindromic repeat (CRISPR) screen, we identified key pathways that EBV usurps to enable B cell growth and transformation. Multiple layers of regulation could be achieved by cooperations between multiple EBV transcription factors binding to the same enhancers. EBV manipulated the expression of most cell genes essential for lymphoblastoid cell line (LCL) growth and survival. In addition to proteins, long noncoding RNAs (lncRNAs) regulated by EBV also contributed to LCL growth and survival. The data presented in this paper not only allowed us to further define the molecular pathogenesis of EBV but also serve as a useful resource to the EBV research community.

Early diagnosis of nasopharyngeal carcinoma (NPC) is difficult because of a lack of specific symptoms. Many patients have advanced disease at diagnosis, and these patients respond poorly to treatment. New treatments are therefore needed to improve the outcome of NPC. To better understand the molecular pathogenesis of NPC, here we used an NPC cell line in a genome-wide CRISPR-based knockout screen to identify the cellular factors and pathways essential for NPC ( dependence factors). This screen identified the Moz, Ybf2/Sas3, Sas2, Tip60 histone acetyl transferase complex, NF-κB signaling, purine synthesis, and linear ubiquitination pathways; and MDM2 proto-oncogene as NPC dependence factors/pathways. Using gene knock out, complementary DNA rescue, and inhibitor assays, we found that perturbation of these pathways greatly reduces the growth of NPC cell lines but does not affect growth of SV40-immortalized normal nasopharyngeal epithelial cells. These results suggest that targeting these pathways/proteins may hold promise for achieving better treatment of patients with NPC.

Epstein-Barr virus (EBV) transforms small resting primary B cells into large lymphoblastoid cells which are able to grow and survive in vitro indefinitely. These cells represent a model for oncogenesis. In this unit, variants of conventional clustered regularly interspaced short palindromic repeats (CRISPR), namely the CRISPR activation (CRISPRa) and CRISPR interference (CRISPRi) methods, are discussed in the context of gene regulation at genomic DNA promoter and enhancer elements. Lymphoblastoid B cell lines (LCLs) stably expressing nuclease-deficient Cas9 (dCas9)-VP64 (Cas9 associated with CRISPRa) or dCas9-KRAB (Cas9 associated with CRISPRi) are transduced with lentivirus that encodes a single guide RNA (sgRNA) that targets a specific gene locus. The ribonucleoprotein complex formed by the dCas9 molecule and its cognate sgRNA enables sequence-specific binding at a promoter or enhancer of interest to affect the expression of genes regulated by the targeted promoter or enhancer. © 2018 by John Wiley & Sons, Inc.

Epstein-Barr virus (EBV) efficiently transforms primary human B cells into immortalized lymphoblastoid cell lines (LCLs), which are extensively used in human genetic, immunological and virological studies. LCLs provide unlimited sources of DNA for genetic investigation, but can be difficult to manipulate, for instance because low retroviral or lentiviral transduction frequencies hinder experiments that require co-expression of multiple components. This unit details Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 engineering for robust LCL genome editing. We describe the generation and delivery of single-guide RNAs (sgRNAs), or dual-targeting sgRNAs, via lentiviral transduction of LCLs that stably express Cas9 protein. CRISPR/Cas9 editing allows LCL loss-of-function studies, including knock-out of protein-coding genes or deletion of DNA regulatory elements, and can be adapted for large-scale screening approaches. Low transfection efficiencies are a second barrier to performing CRISPR editing in LCLs, which are not typically lipid-transfectable. To circumvent this barrier, we provide an optimized protocol for LCL nucleofection of Cas9/sgRNA ribonucleoprotein complexes (RNPs) as an alternative route to achieve genome editing in LCLs. These editing approaches can also be employed in other B-cell lines, including Burkitt lymphoma and diffuse large B-cell lymphoma cells, and are highly reproducible. © 2018 by John Wiley & Sons, Inc.

Epstein-Barr virus latent membrane protein 1 (LMP1) is expressed in multiple human malignancies, including nasopharyngeal carcinoma and Hodgkin and immunosuppression-associated lymphomas. LMP1 mimics CD40 signaling to activate multiple growth and survival pathways, in particular, NF-κB. LMP1 has critical roles in Epstein-Barr virus (EBV)-driven B-cell transformation, and its expression causes fatal lymphoproliferative disease in immunosuppressed mice. Here, we review recent developments in studies of LMP1 signaling, LMP1-induced host dependency factors, mouse models of LMP1 lymphomagenesis, and anti-LMP1 immunotherapy approaches.

Epstein-Barr virus (EBV) transforms B cells to continuously proliferating lymphoblastoid cell lines (LCLs), which represent an experimental model for EBV-associated cancers. EBV nuclear antigens (EBNAs) and LMP1 are EBV transcriptional regulators that are essential for LCL establishment, proliferation, and survival. Starting with the 3D genome organization map of LCL, we constructed a comprehensive EBV regulome encompassing 1,992 viral/cellular genes and enhancers. Approximately 30% of genes essential for LCL growth were linked to EBV enhancers. Deleting EBNA2 sites significantly reduced their target gene expression. Additional EBV super-enhancer (ESE) targets included MCL1, IRF4, and EBF. MYC ESE looping to the transcriptional stat site of MYC was dependent on EBNAs. Deleting MYC ESEs greatly reduced MYC expression and LCL growth. EBNA3A/3C altered CDKN2A/B spatial organization to suppress senescence. EZH2 inhibition decreased the looping at the CDKN2A/B loci and reduced LCL growth. This study provides a comprehensive view of the spatial organization of chromatin during EBV-driven cellular transformation.

Epstein-Barr virus (EBV) causes endemic Burkitt lymphoma (BL) and immunosuppression-related lymphomas. These B cell malignancies arise by distinct transformation pathways and have divergent viral and host expression programs. To identify host dependency factors resulting from these EBV+, B cell-transformed cell states, we performed parallel genome-wide CRISPR/Cas9 loss-of-function screens in BL and lymphoblastoid cell lines (LCLs). These highlighted 57 BL and 87 LCL genes uniquely important for their growth and survival. LCL hits were enriched for EBV-induced genes, including viral super-enhancer targets. Our systematic approach uncovered key mechanisms by which EBV oncoproteins activate the PI3K/AKT pathway and evade tumor suppressor responses. LMP1-induced cFLIP was found to be critical for LCL defense against TNFα-mediated programmed cell death, whereas EBV-induced BATF/IRF4 were critical for BIM suppression and MYC induction in LCLs. Finally, EBV super-enhancer-targeted IRF2 protected LCLs against Blimp1-mediated tumor suppression. Our results identify viral transformation-driven synthetic lethal targets for therapeutic intervention.

Super-enhancers are clusters of gene-regulatory sites bound by multiple transcription factors that govern cell transcription, development, phenotype, and oncogenesis. By examining Epstein-Barr virus (EBV)-transformed lymphoblastoid cell lines (LCLs), we identified four EBV oncoproteins and five EBV-activated NF-κB subunits co-occupying ∼1,800 enhancer sites. Of these, 187 had markedly higher and broader histone H3K27ac signals, characteristic of super-enhancers, and were designated “EBV super-enhancers.” EBV super-enhancer-associated genes included the MYC and BCL2 oncogenes, which enable LCL proliferation and survival. EBV super-enhancers were enriched for B cell transcription factor motifs and had high co-occupancy of STAT5 and NFAT transcription factors (TFs). EBV super-enhancer-associated genes were more highly expressed than other LCL genes. Disrupting EBV super-enhancers by the bromodomain inhibitor JQ1 or conditionally inactivating an EBV oncoprotein or NF-κB decreased MYC or BCL2 expression and arrested LCL growth. These findings provide insight into mechanisms of EBV-induced lymphoproliferation and identify potential therapeutic interventions.

Epstein-Barr Virus (EBV) conversion of B-lymphocytes to Lymphoblastoid Cell Lines (LCLs) requires four EBV nuclear antigen (EBNA) oncoproteins: EBNA2, EBNALP, EBNA3A, and EBNA3C. EBNA2 and EBNALP associate with EBV and cell enhancers, up-regulate the EBNA promoter, MYC, and EBV Latent infection Membrane Proteins (LMPs), which up-regulate BCL2 to protect EBV-infected B-cells from MYC proliferation-induced cell death. LCL proliferation induces p16(INK4A) and p14(ARF)-mediated cell senescence. EBNA3A and EBNA3C jointly suppress p16(INK4A) and p14(ARF), enabling continuous cell proliferation. Analyses of the EBNA3A human genome-wide ChIP-seq landscape revealed 37% of 10,000 EBNA3A sites to be at strong enhancers; 28% to be at weak enhancers; 4.4% to be at active promoters; and 6.9% to be at weak and poised promoters. EBNA3A colocalized with BATF-IRF4, ETS-IRF4, RUNX3, and other B-cell Transcription Factors (TFs). EBNA3A sites clustered into seven unique groups, with differing B-cell TFs and epigenetic marks. EBNA3A coincidence with BATF-IRF4 or RUNX3 was associated with stronger EBNA3A ChIP-Seq signals. EBNA3A was at MYC, CDKN2A/B, CCND2, CXCL9/10, and BCL2, together with RUNX3, BATF, IRF4, and SPI1. ChIP-re-ChIP revealed complexes of EBNA3A on DNA with BATF. These data strongly support a model in which EBNA3A is tethered to DNA through a BATF-containing protein complexes to enable continuous cell proliferation.

The nuclear factor κB (NF-κΒ) subunits RelA, RelB, cRel, p50, and p52 are each critical for B cell development and function. To systematically characterize their responses to canonical and noncanonical NF-κB pathway activity, we performed chromatin immunoprecipitation followed by high-throughput DNA sequencing (ChIP-seq) analysis in lymphoblastoid B cell lines (LCLs). We found a complex NF-κB-binding landscape, which did not readily reflect the two NF-κB pathway paradigms. Instead, 10 subunit-binding patterns were observed at promoters and 11 at enhancers. Nearly one-third of NF-κB-binding sites lacked κB motifs and were instead enriched for alternative motifs. The oncogenic forkhead box protein FOXM1 co-occupied nearly half of NF-κB-binding sites and was identified in protein complexes with NF-κB on DNA. FOXM1 knockdown decreased NF-κB target gene expression and ultimately induced apoptosis, highlighting FOXM1 as a synthetic lethal target in B cell malignancy. These studies provide a resource for understanding mechanisms that underlie NF-κB nuclear activity and highlight opportunities for selective NF-κB blockade.

Epstein-Barr virus nuclear antigen 3C (EBNA3C) repression of CDKN2A p14(ARF) and p16(INK4A) is essential for immortal human B-lymphoblastoid cell line (LCL) growth. EBNA3C ChIP-sequencing identified >13,000 EBNA3C sites in LCL DNA. Most EBNA3C sites were associated with active transcription; 64% were strong H3K4me1- and H3K27ac-marked enhancers and 16% were active promoters marked by H3K4me3 and H3K9ac. Using ENCODE LCL transcription factor ChIP-sequencing data, EBNA3C sites coincided (±250 bp) with RUNX3 (64%), BATF (55%), ATF2 (51%), IRF4 (41%), MEF2A (35%), PAX5 (34%), SPI1 (29%), BCL11a (28%), SP1 (26%), TCF12 (23%), NF-κB (23%), POU2F2 (23%), and RBPJ (16%). EBNA3C sites separated into five distinct clusters: (i) Sin3A, (ii) EBNA2/RBPJ, (iii) SPI1, and (iv) strong or (v) weak BATF/IRF4. EBNA3C signals were positively affected by RUNX3, BATF/IRF4 (AICE) and SPI1/IRF4 (EICE) cooccupancy. Gene set enrichment analyses correlated EBNA3C/Sin3A promoter sites with transcription down-regulation (P < 1.6 × 10(-4)). EBNA3C signals were strongest at BATF/IRF4 and SPI1/IRF4 composite sites. EBNA3C bound strongly to the p14(ARF) promoter through SPI1/IRF4/BATF/RUNX3, establishing RBPJ-, Sin3A-, and REST-mediated repression. EBNA3C immune precipitated with Sin3A and conditional EBNA3C inactivation significantly decreased Sin3A binding at the p14(ARF) promoter (P < 0.05). These data support a model in which EBNA3C binds strongly to BATF/IRF4/SPI1/RUNX3 sites to enhance transcription and recruits RBPJ/Sin3A- and REST/NRSF-repressive complexes to repress p14(ARF) and p16(INK4A) expression.

Epstein-Barr virus (EBV) nuclear antigens EBNALP (LP) and EBNA2 (E2) are coexpressed in EBV-infected B lymphocytes and are critical for lymphoblastoid cell line outgrowth. LP removes NCOR and RBPJ repressive complexes from promoters, enhancers, and matrix-associated deacetylase bodies, whereas E2 activates transcription from distal enhancers. LP ChIP-seq analyses identified 19,224 LP sites of which ~50% were ± 2 kb of a transcriptional start site. LP sites were enriched for B-cell transcription factors (TFs), YY1, SP1, PAX5, BATF, IRF4, ETS1, RAD21, PU.1, CTCF, RBPJ, ZNF143, SMC3, NFκB, TBLR, and EBF. E2 sites were also highly enriched for LP-associated cell TFs and were more highly occupied by RBPJ and EBF. LP sites were highly marked by H3K4me3, H3K27ac, H2Az, H3K9ac, RNAPII, and P300, indicative of activated transcription. LP sites were 29% colocalized with E2 (LP/E2). LP/E2 sites were more similar to LP than to E2 sites in associated cell TFs, RNAPII, P300, and histone H3K4me3, H3K9ac, H3K27ac, and H2Az occupancy, and were more highly transcribed than LP or E2 sites. Gene affected by CTCF and LP cooccupancy were more highly expressed than genes affected by CTCF alone. LP was at myc enhancers and promoters and of MYC regulated ccnd2, 23 med complex components, and MYC regulated cell survival genes, igf2r and bcl2. These data implicate LP and associated TFs and DNA looping factors CTCF, RAD21, SMC3, and YY1/INO80 chromatin-remodeling complexes in repressor depletion and gene activation necessary for lymphoblastoid cell line growth and survival.

Inhibitors of DNA binding and differentiation (ID) proteins, a dominant-negative group of helix-loop-helix (HLH) transcription regulators, are well-characterized key players in cellular fate determination during development in mammals as well as Drosophila. Although not oncogenes themselves, their upregulation by various oncogenic proteins (such as Ras, Myc) and their inhibitory effects on cell cycle proteins (such as pRb) hint at their possible roles in tumorigenesis. Furthermore, their potency as inhibitors of cellular differentiation, through their heterodimerization with subsequent inactivation of the ubiquitous E proteins, suggest possible novel roles in engineering induced pluripotent stem cells (iPSCs). We present the high-resolution 2.1Å crystal structure of ID2 (HLH domain), coupled with novel biochemical insights in the presence of a divalent ion, possibly calcium (Ca2+), in the loop of ID proteins, which appear to be crucial for the structure and activity of ID proteins. These new insights will pave the way for new rational drug designs, in addition to current synthetic peptide options, against this potent player in tumorigenesis as well as more efficient ways for stem cells reprogramming.

Zfp206 (also named as Zscan10) belongs to the subfamily of C(2)H(2) zinc finger transcription factors, which is characterized by the N-terminal SCAN domain. The SCAN domain mediates self-association and association between the members of SCAN family transcription factors, but the structural basis and selectivity determinants for complex formation is unknown. Zfp206 is important for maintaining the pluripotency of embryonic stem cells presumably by combinatorial assembly of itself or other SCAN family members on enhancer regions. To gain insights into the folding topology and selectivity determinants for SCAN dimerization, we solved the 1.85 Å crystal structure of the SCAN domain of Zfp206. In vitro binding studies using a panel of 20 SCAN proteins indicate that the SCAN domain Zfp206 can selectively associate with other members of SCAN family transcription factors. Deletion mutations showed that the N-terminal helix 1 is critical for heterodimerization. Double mutations and multiple mutations based on the Zfp206SCAN-Zfp110SCAN model suggested that domain swapped topology is a possible preference for Zfp206SCAN-Zfp110SCAN heterodimer. Together, we demonstrate that the Zfp206SCAN constitutes a protein module that enables C(2)H(2) transcription factor dimerization in a highly selective manner using a domain-swapped interface architecture and identify novel partners for Zfp206 during embryonal development.