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Wilk, A. J.

Publications and source records attributed to Wilk, A. J..

12 recordsLinked to original sources

Dissecting the epigenome dynamics in human immune cells upon viral and chemical exposure by multimodal single-cell profiling

Environmental and pathogen exposure can lead to profound remodeling of the gene-regulatory landscape across human immune cell populations. Here, we present a single-nucleus chromatin accessibility atlas of human immune cells comprising 271,299 cells and 319,420 candidate regulatory elements from individuals exposed to HIV-1, COVID-19, Influenza virus, organophosphates, as well as healthy controls. Our longitudinal HIV cohort reveals epigenetic signatures of T cell exhaustion manifested in changes in the accessibility at binding sites for the FOXP family transcription factors. Upon severe exposure to SARS-Cov2 we identified changes in chromatin accessibility manifesting in a regulatory switch in cytokine networks characterized by the downregulation of the NF-{kappa}B motif family, alongside concordant changes in AP-1 and IRF factor networks in CD14+ classical monocytes. By integrating single-cell profiles of DNA methylation from matched samples, we created a multimodal epigenome atlas of human immune cell states using the accessibility-derived candidate regulatory elements. Both modalities exhibit complementary epigenetic signatures at transcription factor binding sites associated with cell state, as exemplified in the process of memory formation in T-cells, where BATF, AP-1, and ETS motifs exhibit significant epigenetic covariance across both epigenomic layers. Finally, by linking potentially regulatory DNA methylation signatures to changes in chromatin accessibility in monocytes, we observe that severe COVID-19 involves selective, multiomics remodeling of epigenetic profiles at TF binding sites manifested in concordant DNA methylation and accessibility dynamics at inflammation-associated regulatory TFs.

bioinformatics↗

CellVoyager: AI CompBio Agent Generates New Insights by Autonomously Analyzing Biological Data

Modern biology increasingly relies on complex, high dimensional datasets such as single-cell RNA sequencing (scRNA-seq). However, the richness of such data means that conventional analyses may only scratch its surface. Extracting meaningful insights from these datasets often requires advanced computational methods and domain expertise. Current AI agents for biology are primarily focused on executing user-specified commands and are therefore limited by the users creativity and familiarity with which kinds of analyses are useful. Furthermore, these agents do not account for prior analyses already attempted by researchers, reducing their ability to build upon existing work. To address these limitations, we introduce CellVoyager, an AI agent that autonomously explores scRNA-seq datasets in novel directions conditioned on prior user-ran analyses. Built on large language models, CellVoyager ingests both the dataset and a record of prior analyses to generate and test new hypotheses within a Jupyter notebook environment. We evaluate CellVoyager on CellBench, a new benchmark based on 50 published scRNA-seq studies encompassing 483 analyses. Given only the background sections of these papers, CellVoyager outperformed GPT-4o and o3-mini by up to 20% in predicting which analyses the authors eventually conducted. We then carried out three in-depth case studies where CellVoyager is given previously published papers with their scRNA-seq datasets and conducts analyses to generate new findings. The original authors of each study evaluated these findings and consistently rated them as creative and sound; 80% of the agents hypotheses were deemed scientifically interesting. For example, in one case study, the agent found that CD8+ T cells in COVID-19 infection are more primed for pyroptosis, which was not explored by the original researchers. CellVoyager also reanalyzed a brain aging dataset to discover a previously unreported association between increased transcriptional noise and aging in the subventricular zone of the brain. These results demonstrate that CellVoyager can act both autonomously and collaboratively to accelerate hypothesis generation and computational biology. It also highlights the potential of agents like CellVoyager to unlock new biological insights by reanalyzing the vast existing biological data at scale.

bioinformatics↗

Interferon-mediated NK cell activation is associated with limited neutralization breadth during SARS-CoV-2 infection

Best known for their ability to kill infected or malignant cells, natural killer (NK) cells are also underappreciated regulators of the antibody response to viral infection. In mice, NK cells can kill T follicular helper (Tfh) cells, decreasing somatic hypermutation and vaccine responses. Although human NK cell activation correlates with poor vaccine response, the mechanisms of human NK cell regulation of adaptive immunity are poorly understood. We found that in human ancestral SARS-CoV-2 infection, broad neutralizers, who were capable of neutralizing Alpha, Beta, and Delta, had fewer NK cells that expressed inhibitory and immaturity markers whereas NK cells from narrow neutralizers were highly activated and expressed interferon-stimulated genes (ISGs). ISG-mediated activation in NK cells from healthy donors increased cytotoxicity and functional responses to induced Tfh-like cells. This work reveals that NK cell activation and dysregulated inflammation may play a role in poor antibody response to SARS-CoV-2 and opens exciting avenues for designing improved vaccines and adjuvants to target emerging pathogens.

immunology↗

NK cell-monocyte crosstalk underlies NK cell activation in severe COVID-19

NK cells in the peripheral blood of severe COVID-19 patients exhibit a unique profile characterized by activation and dysfunction. Previous studies have identified soluble factors, including type I interferon and TGF{beta}, that underlie this dysregulation. However, the role of cell-cell interactions in mediating changes in NK cell function during COVID-19 remains unclear. To address this question, we combined cell-cell communication analysis on existing single-cell RNA sequencing data with in vitro primary cell co-culture experiments to dissect the mechanisms underlying NK cell dysfunction in COVID-19. We found that NK cells are predicted to interact most strongly with monocytes and that this occurs via both soluble factors and direct interactions. To validate these findings, we performed in vitro co-cultures in which NK cells from healthy donors were incubated with monocytes from COVID-19+ or healthy donors. Co-culture of healthy NK cells with monocytes from COVID-19 patients recapitulated aspects of the NK cell phenotype observed in severe COVID-19, including decreased expression of NKG2D, increased expression of activation markers, and increased proliferation. When these experiments were performed in a transwell setting, we found that only CD56bright CD16- NK cells were activated in the presence of severe COVID-19 patient monocytes. O-link analysis of supernatants from transwell co-cultures revealed that cultures containing severe COVID-19 patient monocytes had significantly elevated levels of proinflammatory cytokines and chemokines as well as TGF{beta}. Collectively, these results demonstrate that interactions between NK cells and monocytes in the peripheral blood of COVID-19 patients contribute to NK cell activation and dysfunction in severe COVID-19. BACKGROUNDNatural killer (NK) cells are innate lymphocytes that are critical antiviral effectors. Because of their role in controlling acute viral infections, multiple studies have evaluated the role of NK cells in SARS-CoV-2 infection. Such studies revealed that NK cell phenotype and function are significantly altered by severe COVID-19; the peripheral NK cells of severe COVID-19 patients are highly activated and proliferative(1-5), with increased expression of cytotoxic molecules, Ki-67, and several surface markers of activation(3, 5-8). However, these NK cells also have dysfunctional cytotoxic responses to both tumor target cells(1, 2, 9, 10) and SARS-CoV-2-infected target cells(9, 10). Given that peripheral NK cells are thought to migrate to the lung during COVID-19(11-13), these results suggest that the NK cells of severe COVID-19 patients may be incapable of mounting a successful antiviral response to SARS-CoV-2 infection. Although the unique phenotype and dysfunctionality of NK cells in severe COVID-19 has been well-characterized, the processes underlying these phenomena have not. Only one study has conducted in vitro mechanistic experiments to identify a possible cause of NK cell dysfunction: Witkowski et al. identified serum-derived TGF{beta} as a suppressor of NK cell functionality in severe COVID-19 patients(9). However, this study did not identify the source of serum TGF{beta}. Additionally, given the high degree of complexity within the immune system, there are likely other causes of NK cell dysfunction in COVID-19 that have thus far remain unexplored. One such mechanism may be the myriad of interactions between NK cells and other peripheral immune cells. NK cells are known to interact with CD4 and CD8 T cells, dendritic cells, neutrophils, and macrophages/monocytes(14), which can prime NK cell cytotoxicity or induce tolerance. Previous work by our lab suggested the potential for NK cell-monocyte crosstalk in severe COVID-19 through the expression of ligands for NK cell activating receptors on the monocytes of these patients(3). Crosstalk between NK cells and monocytes plays a role in regulating the NK cell response to other infections, including HIV-1(15, 16), mouse(17) and human cytomegalovirus(18), and malaria(19) through mechanisms including secretion of NK cell-regulating cytokines by monocytes. In this study, we used a combination of computational and in vitro methods to dissect the interactions between NK cells and monocytes in severe COVID-19. We utilized primary NK cells and monocytes from a large cohort of COVID-19 patients to demonstrate that co-culture of healthy NK cells with monocytes from severe COVID-19 donors can partially recapitulate the activated phenotype observed in the NK cells from COVID-19 patients. We then interrogated the mechanisms by which this activation occurs by performing NK cell-monocyte co-cultures in a transwell setting and using O-link to analyze the cytokines present in this system. Collectively, our work identifies monocytes as a driver of NK cell activation in severe COVID-19 and reveals interactions between NK cells and monocytes that may underlie this process.

immunology↗

Disrupted memory T cell expansion in HIV-exposed uninfected infants is preceded by premature skewing of T cell receptor clonality.

While preventing vertical HIV transmission has been very successful, the increasing number of HIV-exposed uninfected infants (iHEU) experience an elevated risk to infections compared to HIV-unexposed and uninfected infants (iHUU). Immune developmental differences between iHEU and iHUU remains poorly understood and here we present a longitudinal multimodal analysis of infant immune ontogeny that highlights the impact of HIV/ARV exposure. Using mass cytometry, we show alterations and differences in the emergence of NK cell populations and T cell memory differentiation between iHEU and iHUU. Specific NK cells observed at birth were also predictive of acellular pertussis and rotavirus vaccine-induced IgG and IgA responses, respectively, at 3 and 9 months of life. T cell receptor V{beta} clonotypic diversity was significantly and persistently lower in iHEU preceding the expansion of T cell memory. Our findings show that HIV/ARV exposure disrupts innate and adaptive immunity from birth which may underlie relative vulnerability to infections.

immunology↗

Pro-inflammatory feedback loops define immune responses to pathogenic lentivirus infection

HIV causes chronic inflammation and AIDS in humans, though the rate of disease progression varies between individuals. Similarly, simian lentiviruses vary in their pathogenicity based on characteristics of both the host (simian species) and virus strain. Here, we profile immune responses in pig-tailed macaques infected with variants of SIV that differ in virulence to understand the immune mechanisms underlying lentiviral pathogenicity. Compared to a minimally pathogenic lentiviral variant, infection with a highly pathogenic variant results in a more delayed, broad, and sustained activation of inflammatory pathways, including an extensive global interferon signature. Conversely, individual cells infected with highly pathogenic lentivirus upregulated fewer interferon-stimulated genes at a lower magnitude, indicating that highly pathogenic lentivirus has evolved to partially escape from interferon responses. Further, we identified distinct gene co-expression patterns and cell-cell communication pathways that implicate CXCL10 and CXCL16 as important molecular drivers of inflammatory pathways specifically in response to highly pathogenic lentivirus infection. Immune responses to highly pathogenic lentivirus infection are characterized by amplifying regulatory circuits of pro-inflammatory cytokines with dense longitudinal connectivity. Our work presents a model of lentiviral pathogenicity where failures in early viral control mechanisms lead to delayed, sustained, and amplifying pro-inflammatory circuits, which has implications for other viral infections with highly variable disease courses.

immunology↗

Activated interstitial macrophages are a predominant target of viral takeover and focus of inflammation in COVID-19 initiation in human lung

Early stages of deadly respiratory diseases such as COVID-19 have been challenging to elucidate due to lack of an experimental system that recapitulates the cellular and structural complexity of the human lung while allowing precise control over disease initiation and systematic interrogation of molecular events at cellular resolution. Here we show healthy human lung slices cultured ex vivo can be productively infected with SARS-CoV-2, and the cellular tropism of the virus and its distinct and dynamic effects on host cell gene expression can be determined by single cell RNA sequencing and reconstruction of "infection pseudotime" for individual lung cell types. This revealed that the prominent SARS-CoV-2 target is a population of activated interstitial macrophages (IMs), which as infection proceeds accumulate thousands of viral RNA molecules per cell, comprising up to 60% of the cellular transcriptome and including canonical and novel subgenomic RNAs. During viral takeover of IMs, there is cell-autonomous induction of a pro-fibrotic program (TGFB1, SPP1), and an inflammatory program characterized by the early interferon response, chemokines (CCL2, 7, 8, 13, CXCL10) and cytokines (IL6, IL10), along with destruction of cellular architecture and formation of dense viral genomic RNA bodies revealed by super-resolution microscopy. In contrast, alveolar macrophages (AMs) showed neither viral takeover nor induction of a substantial inflammatory response, although both purified AMs and IMs supported production of infectious virions. Spike-dependent viral entry into AMs was neutralized by blockade of ACE2 or Sialoadhesin/CD169, whereas IM entry was neutralized only by DC-SIGN/CD209 blockade. These results provide a molecular characterization of the initiation of COVID-19 in human lung tissue, identify activated IMs as a prominent site of viral takeover and focus of inflammation and fibrosis, and suggest therapeutic targeting of the DC-SIGN/CD209 entry mechanism to prevent IM infection, destruction and early pathology in COVID-19 pneumonia. Our approach can be generalized to define the initiation program and evaluate therapeutics for any human lung infection at cellular resolution.

genomics↗

Comparative analysis of cell-cell communication at single-cell resolution

Inference of cell-cell communication (CCC) from single-cell RNA-sequencing data is a powerful technique to uncover putative axes of multicellular coordination, yet existing methods perform this analysis at the level of the cell type or cluster, discarding single-cell level information. Here we present Scriabin - a flexible and scalable framework for comparative analysis of CCC at single-cell resolution. We leverage multiple published datasets to show that Scriabin recovers expected CCC edges and use spatial transcriptomic data, genetic perturbation screens, and direct experimental manipulation of receptor-ligand interactions to validate that the recovered edges are biologically meaningful. We then apply Scriabin to uncover co-expressed programs of CCC from atlas-scale datasets, validating known communication pathways required for maintaining the intestinal stem cell niche and revealing species-specific communication pathways. Finally, we utilize single-cell communication networks calculated using Scriabin to follow communication pathways that operate between timepoints in longitudinal datasets, highlighting bystander cells as important initiators of inflammatory reactions in acute SARS-CoV-2 infection. Our approach represents a broadly applicable strategy to leverage single-cell resolution data maximally toward uncovering CCC circuitry and rich niche-phenotype relationships in health and disease.

cell biology↗

Multi-omic profiling reveals widespread dysregulation of innate immunity and hematopoiesis in COVID-19

Our understanding of protective vs. pathologic immune responses to SARS-CoV-2, the virus that causes Coronavirus disease 2019 (COVID-19), is limited by inadequate profiling of patients at the extremes of the disease severity spectrum. Here, we performed multi-omic single-cell immune profiling of 64 COVID-19 patients across the full range of disease severity, from outpatients with mild disease to fatal cases. Our transcriptomic, epigenomic, and proteomic analyses reveal widespread dysfunction of peripheral innate immunity in severe and fatal COVID-19, with the most profound disturbances including a prominent neutrophil hyperactivation signature and monocytes with anti-inflammatory features. We further demonstrate that emergency myelopoiesis is a prominent feature of fatal COVID-19. Collectively, our results reveal disease severity-associated immune phenotypes in COVID-19 and identify pathogenesis-associated pathways that are potential targets for therapeutic intervention. One Sentence SummarySingle-cell profiling demonstrates multifarious dysregulation of innate immune phenotype associated with COVID-19 severity.

immunology↗

Additional analyses exploring the hypothesized transdifferentiation of plasmablasts to developing neutrophils in severe COVID-19

We thank Alquicira-Hernandez et al. for their reanalysis of our single-cell transcriptomic dataset profiling peripheral immune responses to severe COVID-19. We agree that careful analysis of single-cell sequencing data is important for generating cogent hypotheses but find several aspects of their criticism of our analysis to be problematic. Here we respond briefly to misunderstandings and inaccuracies in their commentary that may have led to misinformed interpretation of our results.

immunology↗

Integrated analysis of multimodal single-cell data

The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single-cell genomics and necessitates new computational methods that can define cellular states based on multiple data types. Here, we introduce weighted-nearest neighbor analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of hundreds of thousands of human white blood cells alongside a panel of 228 antibodies to construct a multimodal reference atlas of the circulating immune system. We demonstrate that integrative analysis substantially improves our ability to resolve cell states and validate the presence of previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets, and to interpret immune responses to vaccination and COVID-19. Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets, including paired measurements of RNA and chromatin state, and to look beyond the transcriptome towards a unified and multimodal definition of cellular identity. AvailabilityInstallation instructions, documentation, tutorials, and CITE-seq datasets are available at http://www.satijalab.org/seurat

genomics↗

Charge-Altering Releasable Transporters enable specific phenotypic manipulation of resting primary natural killer cells

Natural killer (NK) cells are capable of rapid and robust cytotoxicity, making them excellent tools for immunotherapy. However, their recalcitrance to standard transfection techniques has limited both mechanistic studies and clinical applications. Current approaches for NK cell manipulation rely on viral transduction or methods requiring NK cell activation, which can alter NK cell function. Here, we report that non-viral Charge-Altering Releasable Transporters (CARTs) efficiently transfect primary human NK cells with mRNA without relying on NK cell activation. Compared to electroporation, CARTs transfect NK cells two orders of magnitude more efficiently, better preserve cell viability, and cause minimal reconfiguration of NK cell phenotype and function. Finally, we use CARTs to generate highly cytotoxic primary human chimeric antigen receptor NK cells, indicating potential therapeutic utility of this technique. To our knowledge, CARTs represent the first efficacious transfection technique for resting primary NK cells that preserves NK cell phenotype, and can drive new biological discoveries and clinical applications of this understudied lymphocyte subset.

immunology↗