Biology subjects

Painter, M. M.

Publications and source records attributed to Painter, M. M..

15 recordsLinked to original sources

bioRxiv2026

Persistently activated virus-specific CD8 T cells indicate antigen-driven immune aberrations in long COVID

Long COVID (LC) affects millions of people worldwide, yet its driving mechanisms remain incompletely defined and no treatment has been approved. Persistence of SARS-CoV-2 and reactivation of herpesviruses have been implicated in LC, but direct detection of these viral antigens in blood and tissues has been challenging. T cells are exquisitely sensitive to viral antigens, survey organs throughout the body, and can be readily sampled in peripheral blood. Using high-dimensional spectral flow cytometry and single-cell sequencing approaches with multiplexed peptide/HLA tetramers, we profiled virus-specific T cells from hundreds of people with LC and recovered controls. We identified a subset of people with LC that maintained elevated activation of CD8 T cells targeting SARS-CoV-2 spike and/or lytic antigens from Epstein-Barr virus, but not other viral specificities. Spike-specific cells in LC expressed genes linked to TCR stimulation, terminal effector differentiation, and exhaustion and demonstrated reduced functionality upon cognate peptide stimulation ex vivo. Thus, T cells from a subset of people with LC are likely chronically stimulated by persistent SARS-CoV-2 antigens. These findings establish the use of T cells as biosensors of persisting antigen in LC and other disease settings and may help develop new therapeutic strategies for LC.

immunology↗

bioRxiv2026

Vaccine imprinting drives increased SARS-CoV-2 variant infection in children

Virus exposure history, particularly first exposure, is believed to shape vaccine efficacy and infection susceptibility; however, evidence for mechanistic links between immune responses in individuals and epidemiological outcome in populations is scarce. Recent co-circulation of SARS-CoV-2 variants XFG and BA.3.2 has revealed a striking enrichment in BA.3.2 cases among children. By combining epidemiological modeling, serology and monoclonal antibody analysis in children and adults, we show the dependence of effective variant-specific antibodies on vaccination history which may explain birth-year influence on differential susceptibility to these co-circulating variants. Ancestral cross-reactive site I antibodies frequently neutralize BA.3.2, but not XFG. By contrast, Omicron type-specific site I/III and III antibodies frequently neutralize XFG but not BA.3.2, revealing a tradeoff in the ability to neutralize these two co-circulating strains. These findings mechanistically link immune history, variant neutralization, antibody repertoire and variant infection risk, and suggest that vaccination regimens in children should prioritize neutralization breadth.

immunology↗

bioRxiv2026

Deep learning representations of human Immune Health for precision immunology

The human immune system is composed of [~]30-50 distinct cell types, each of which can exist in different states of activation or differentiation. Indeed, the mammalian immune system has evolved to sense and respond to infections, cancers, injuries, and changes in tissue or host homeostasis (1). Moreover, an increasingly large fraction of approved drugs target the immune system directly, and/or cause immune changes (2-4). A key feature of the immune system is to store some of this information, for example as innate or adaptive immune memory (5). In addition, rewiring of immune network architecture induced by disease, environmental exposures, drug treatments, and/or chronological age allows the immune system to store information in the pattern of connections and activity across populations of immune cells. This ensemble information storage, in addition to changes to individual cells, functions as a major way the immune system encodes aspects of immune history and future potential. Genetic information can identify inherited risk alleles, but cannot capture the continual remodeling of the immune system shaped by exposures, infection, inflammation, therapy, and aging (6, 7). To define and use such ensemble immunotypes, we developed a self-supervised deep learning framework that transforms high-dimensional immune profiles into representations of immune health. MAESTRO (MAsked Encoding Set TRansformer with self-distillatiOn) encodes a set of cells from an individual into an embedding that captures immune cell population-level organization. Pretrained on 1,792 peripheral blood samples comprising over 418 million immune cells across 13 clinical diagnoses, MAESTRO learns immune fingerprints that are stable within individuals yet diverse across populations, states of health, disease, and treatment, providing a quantitative basis for comparing immune states across individuals and over time. These fingerprints capture immune architecture beyond coarse cell type proportions, enabling patient-efficient clinical prediction using simple task specific models. MAESTRO model embeddings retain a temporal dimension of immune history and potential, reflecting signatures of past exposures and baseline features that predict future immune responses. Finally, we demonstrate a translational precision immunotherapy application by testing this approach in metastatic Pancreatic Ductal Adenocarcinoma (PDAC), where pretreatment immune landscape circuitry maps enable patient stratification and therapeutic response prediction. Overall, we developed a large, attention-based model that captures deep network architecture of immune states through self- supervised representations of immune cytometry data as a reusable foundation for precision immunology, converting immune complexity into clinically actionable embeddings for diagnosis, monitoring, and therapy selection.

immunology↗

bioRxiv2026

Therapeutic scheduling of WEE1 inhibition preserves T cell function and promotes immune control of HPV⁺ tumors

Human papillomavirus-associated oropharyngeal squamous cell carcinoma (HPV OPC) is driven by viral E6 and E7 oncoproteins, which disrupt G1 checkpoint control and impose selective dependency on WEE1-mediated G2/M regulation. While this vulnerability confers sensitivity to WEE1 inhibition, its immunologic consequences remain poorly defined, and the challenge of eliciting antitumor immunity without compromising immune fitness has limited clinical translation. Here, we show that WEE1 inhibition elicits durable antitumor immunity in immunocompetent models of HPV OPC. Using murine and human preclinical systems, we demonstrate that the WEE1 inhibitor azenosertib (ZN-c3) mediates tumor control through both cell-autonomous cytotoxicity and immune-dependent mechanisms requiring T cells and conventional dendritic cells. Mechanistically, HPV tumor cells are deficient in STING signaling and fail to mount canonical type I interferon responses. Instead, tumor cell-intrinsic cGAS drives immune activation through STING-competent host cells within the tumor microenvironment, revealing a non-cell-autonomous relay that circumvents viral immune evasion. Intermittent WEE1 inhibition preserves T cell fitness while maintaining antitumor efficacy, and mice achieving complete responses develop immunologic memory capable of rejecting tumor rechallenge. These findings establish intermittent WEE1 inhibition as an immune-permissive therapeutic strategy that enables antigen-specific T cell responses in HPV-driven malignancies and provides a mechanistic rationale for combination with immunotherapy.

cancer biology↗

bioRxiv2026

Mechanisms of HIV Latency in Hematopoietic Progenitors: GFI1 as a Key Regulator

Durable control of HIV infection is challenged by persistent latent reservoirs, including hematopoietic stem and progenitor cells (HSPCs), which provide a unique niche for proviral silencing. Mechanisms of HIV latency in HSPCs remain poorly studied. Here, we utilized a dual-reporter HIV (89.6 VT1) and single-cell RNA sequencing to identify host factors governing latency in HSPCs. Transcriptomic profiling revealed elevated expression of several genes in latently infected cells, among them the transcriptional repressor GFI1. Functional studies showed that GFI1 suppresses HIV gene expression by binding a conserved sequence near the primer binding site within the long terminal repeat (LTR). Disruption of GFI1 DNA-binding or corepressor recruitment domains diminished its silencing effect. GFI1 also antagonized Tat and NF-{kappa}B-mediated activation, and reversal of GFI1-mediated suppression was most robust with combined HDAC inhibition and NF-{kappa}B activation. These findings position GFI1 as an important regulator of HIV latency in HSPCs.

microbiology↗

bioRxiv2025

Divergent ontogeny of Tissue Resident Memory and Tissue Resident Exhausted CD8+ T cells underlies distinct functional potential

Persistent antigen stimulation promotes differentiation of exhausted CD8+ T (TEX) cells. TEX cells are distinct from circulating memory T (TCIRCM) cells but share many features with tissue-resident memory (TRM) cells established following infection resolution. CD8+ T cells co-expressing residency- and exhaustion-associated molecules in chronic diseases often correlate with clinical outcomes. However, the relationship between these cells and conventional TRM or TEX cells remains unclear. Here, we show that chronic antigen stimulation drives development of tissue-resident TEX (TR-TEX) cells that are ontologically and functionally distinct from TRM cells generated after antigen clearance. TR-TEX phenotypically resembled TRM cells but were regulated by distinct transcriptional networks and were uniquely dependent on Tox for residency programming. Although TEX progenitor cells acquired residency features upon entering chronically infected tissues, they failed to generate conventional TRM cells after antigen withdrawal. Conversely, TRM cells were able to differentiate into TEX cells during chronic antigen stimulation. Deriving cell-state specific transcriptional signatures revealed a selective association of TR-TEX cells with patient responses to immune checkpoint blockade, and only TR-TEX but not TRM cells responded to PD-1 pathway inhibition in vivo. These data suggest that TR-TEX and TRM cells are developmentally distinct cell types that share a tissue-residency program but have distinct roles in disease control.

immunology↗

bioRxiv2025

Cleanet: robust doublet detection in cytometry data based on protein expression patterns

Flow and mass cytometry experiments are essential for profiling immune cells at single cell resolution. Better understanding of human immunology increasingly involves analyzing studies at the scale of hundreds or thousands of samples, with data analysis a significant bottleneck. This trend increases the demand for automated analysis methods. In particular, a common preprocessing step in cytometry data analysis is distinguishing single cells from doublets (or multiplets), events in which two (or more) cells pass simultaneously through the detector. Typically, doublets are identified on two-dimensional density plots, using their high measured values for DNA intercalators (mass cytometry) or scattering channels (flow cytometry). Despite its popularity, this bivariate gating method is sometimes imprecise: for example, we show that bivariate gating of mass cytometry data can mistake single eosinophils for doublets, due to their high DNA content. Taking inspiration from methods already used in single cell transcriptomics, but not in the cytometry community, we propose an alternative approach. Our method, called Cleanet, first simulates doublet events, then identifies true events with protein expression similar to the simulated doublets. This simple method is completely automated and detects both homotypic and heterotypic doublets. We validate it in datasets acquired with mass and flow cytometry; moreover, we verify with imaging flow cytometry that events predicted to be doublets truly consist of multiple cells. Cleanet can also classify doublets based on their component cell types, which potentially enables the study of cell-cell interactions, mining extra information out of doublet events that would otherwise be discarded. As a proof of concept, we demonstrate that Cleanet can detect a treatment-specific increase in interactions between two cell lines. By automating doublet detection and classification, we aim to streamline the data analysis in large cytometry studies and provide a more accurate picture of both immune cell populations and cell-cell interactions.

bioinformatics↗

bioRxiv2024

Automated Cytometric Gating with Human-Level Performance Using Bivariate Segmentation

Recent advances in cytometry technology have enabled high-throughput data collection with multiple single-cell protein expression measurements. The significant biological and technical variance between samples in cytometry has long posed a formidable challenge during the gating process, especially for the initial gates which deal with unpredictable events, such as debris and technical artifacts. Even with the same experimental machine and protocol, the target population, as well as the cell population that needs to be excluded, may vary across different measurements. To address this challenge and mitigate the labor-intensive manual gating process, we propose a deep learning framework UNITO to rigorously identify the hierarchical cytometric subpopulations. The UNITO framework transformed a cell-level classification task into an image-based semantic segmentation problem. For reproducibility purposes, the framework was applied to three independent cohorts and successfully detected initial gates that were required to identify single cellular events as well as subsequent cell gates. We validated the UNITO framework by comparing its results with previous automated methods and the consensus of at least four experienced immunologists. UNITO outperformed existing automated methods and differed from human consensus by no more than each individual human. Most critically, UNITO framework functions as a fully automated pipeline after training and does not require human hints or prior knowledge. Unlike existing multi-channel classification or clustering pipelines, UNITO can reproduce a similar contour compared to manual gating for each intermediate gating to achieve better interpretability and provide post hoc visual inspection. Beyond acting as a pioneering framework that uses image segmentation to do auto-gating, UNITO gives a fast and interpretable way to assign the cell subtype membership, and the speed of UNITO will not be impacted by the number of cells from each sample. The pre-gating and gating inference takes approximately 2 minutes for each sample using our pre-defined 9 gates system, and it can also adapt to any sequential prediction with different configurations.

immunology↗

bioRxiv2024

Single-cell Masked Autoencoder: An Accurate and Interpretable Automated Immunophenotyper

High-throughput single-cell cytometry data are crucial for understanding involvement of immune system in diseases and responses to treatment. Traditional methods for annotating cytometry data, specifically manual gating and clustering, face challenges in scalability, robustness, and accuracy. In this study, we propose a cytometry masked autoencoder (cyMAE), which offers an automated solution for immunophenotyping tasks including cell type annotation. The cyMAE model is designed to uphold user-defined cell type definitions, thereby facilitating easier interpretation and cross-study comparisons. The cyMAE model operates on a pre-train and fine-tune approach. In the pre-training phase, cyMAE employs Masked Cytometry Modelling (MCM) to learn relationships between protein markers in immune cells solely based on protein expression, without relying on prior information such as cell identity and cell type-specific marker proteins. Subsequently, the pre-trained cyMAE is fine-tuned on multiple specialized tasks via task-specific supervised learning. The pre-trained cyMAE addresses the shortcomings of manual gating and clustering methods by providing accurate and interpretable predictions. Through validation across multiple cohorts, we demonstrate that cyMAE effectively identifies co-occurrence patterns of bound labeled antibodies, delivers accurate and interpretable cellular immunophenotyping, and improves the prediction of subject metadata status. Specifically, we evaluated cyMAE for cell type annotation and imputation at the cellular-level and SARS-CoV-2 infection prediction, secondary immune response prediction against COVID-19, and prediction of the infection stage in COVID-19 progression at the subject-level. The introduction of cyMAE marks a significant step forward in immunology research, particularly in large-scale and high-throughput human immune profiling. This approach offers new possibilities for predicting and interpreting cellular-level and subject-level phenotypes in both health and disease.

bioinformatics↗

bioRxiv2023

Prior vaccination enhances immune responses during SARS-CoV-2 breakthrough infection with early activation of memory T cells followed by production of potent neutralizing antibodies

SARS-CoV-2 infection of vaccinated individuals is increasingly common but rarely results in severe disease, likely due to the enhanced potency and accelerated kinetics of memory immune responses. However, there have been few opportunities to rigorously study early recall responses during human viral infection. To better understand human immune memory and identify potential mediators of lasting vaccine efficacy, we used high-dimensional flow cytometry and SARS-CoV-2 antigen probes to examine immune responses in longitudinal samples from vaccinated individuals infected during the Omicron wave. These studies revealed heightened Spike-specific responses during infection of vaccinated compared to unvaccinated individuals. Spike-specific CD4 T cells and plasmablasts expanded and CD8 T cells were robustly activated during the first week. In contrast, memory B cell activation, neutralizing antibody production, and primary responses to non-Spike antigens occurred during the second week. Collectively, these data demonstrate the functionality of vaccine-primed immune memory and highlight memory T cells as rapid responders during SARS-CoV-2 infection.

immunology↗

bioRxiv2022

A long interval between priming and boosting SARS-CoV-2 mRNA vaccine doses enhances B cell responses with limited impact on T cell immunity

Spacing the first two doses of SARS-CoV-2 mRNA vaccines beyond 3-4 weeks raised initial concerns about vaccine efficacy. While studies have since shown that long-interval regimens induce robust antibody responses, their impact on B and T cell immunity is poorly known. Here, we compare in SARS-CoV-2 naive donors B and T cell responses to two mRNA vaccine doses administered 3-4 versus 16 weeks apart. After boost, the longer interval results in higher magnitude and a more mature phenotype of RBD-specific B cells. While the two geographically distinct cohorts present quantitative and qualitative differences in T cell responses at baseline and after priming, the second dose led to convergent features with overall similar magnitude, phenotype and function of CD4+ and CD8+ T cell responses at post-boost memory timepoints. Therefore, compared to standard regimens, a 16-week interval has a favorable impact on the B cell compartment but minimally affects T cell immunity.

immunology↗

bioRxiv2022

Longitudinal single cell transcriptional and epigenetic mapping of effector, memory, and exhausted CD8 T cells reveals shared biological circuits across distinct cell fates

Naive CD8 T cells can differentiate into effector (TEFF), memory (TMEM), or exhausted (TEX) CD8 T cells. These developmental pathways are associated with distinct transcriptional and epigenetic changes that endow cells with different functional capacities and therefore therapeutic potential. The molecular circuitry underlying these developmental trajectories and the extent of heterogeneity within TEFF, TMEM, TEX populations remain poorly understood. Here, we used the lymphocytic choriomeningitis virus model of acutely-resolved and chronic infection and addressed these gaps by applying longitudinal scRNA-seq and scATAC-seq analysis. These analyses uncovered new subsets, including a subpopulation of TEX expressing NK cell-associated genes, as well as multiple distinct TCF1+ stem/progenitor-like subsets in acute and chronic infection. These data also revealed insights into the reshaping of TEX subsets following PD1 pathway blockade and identified a key role for the cell stress regulator, Btg1, in TEX differentiation. Finally, these results highlighted how the same biological circuits such as cytotoxicity or stem/progenitor pathways can be used by CD8 T cells with highly divergent underlying chromatin landscapes. Thus, this transcriptional and chromatin accessibility landscape map elucidates developmental biology and underlying mechanisms governing TEFF, TMEM, and TEX differentiation.

immunology↗

bioRxiv2022

Efficient recall of Omicron-reactive B cell memory after a third dose of SARS-CoV-2 mRNA vaccine

Despite a clear role in protective immunity, the durability and quality of antibody and memory B cell responses induced by mRNA vaccination, particularly by a 3rd dose of vaccine, remains unclear. Here, we examined antibody and memory B cell responses in a cohort of individuals sampled longitudinally for [~]9-10 months after the primary 2-dose mRNA vaccine series, as well as for [~]3 months after a 3rd mRNA vaccine dose. Notably, antibody decay slowed significantly between 6- and 9-months post-primary vaccination, essentially stabilizing at the time of the 3rd dose. Antibody quality also continued to improve for at least 9 months after primary 2-dose vaccination. Spike- and RBD-specific memory B cells were stable through 9 months post-vaccination with no evidence of decline over time, and [~]40-50% of RBD-specific memory B cells were capable of simultaneously recognizing the Alpha, Beta, Delta, and Omicron variants. Omicron-binding memory B cells induced by the first 2 doses of mRNA vaccine were boosted significantly by a 3rd dose and the magnitude of this boosting was similar to memory B cells specific for other variants. Pre-3rd dose memory B cell frequencies correlated with the increase in neutralizing antibody titers after the 3rd dose. In contrast, pre-3rd dose antibody titers inversely correlated with the fold-change of antibody boosting, suggesting that high levels of circulating antibodies may limit reactivation of immunological memory and constrain further antibody boosting by mRNA vaccines. These data provide a deeper understanding of how the quantity and quality of antibody and memory B cell responses change over time and number of antigen exposures. These data also provide insight into potential immune dynamics following recall responses to additional vaccine doses or post-vaccination infections. Graphical Summary O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=123 SRC="FIGDIR/small/481163v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@123d2d9org.highwire.dtl.DTLVardef@e7db82org.highwire.dtl.DTLVardef@1fc73deorg.highwire.dtl.DTLVardef@11b21f9_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2021

mRNA Vaccination Induces Durable Immune Memory to SARS-CoV-2 with Continued Evolution to Variants of Concern

SARS-CoV-2 mRNA vaccines have shown remarkable efficacy, especially in preventing severe illness and hospitalization. However, the emergence of several variants of concern and reports of declining antibody levels have raised uncertainty about the durability of immune memory following vaccination. In this study, we longitudinally profiled both antibody and cellular immune responses in SARS-CoV-2 naive and recovered individuals from pre-vaccine baseline to 6 months post-mRNA vaccination. Antibody and neutralizing titers decayed from peak levels but remained detectable in all subjects at 6 months post-vaccination. Functional memory B cell responses, including those specific for the receptor binding domain (RBD) of the Alpha (B.1.1.7), Beta (B.1.351), and Delta (B.1.617.2) variants, were also efficiently generated by mRNA vaccination and continued to increase in frequency between 3 and 6 months post-vaccination. Notably, most memory B cells induced by mRNA vaccines were capable of cross-binding variants of concern, and B cell receptor sequencing revealed significantly more hypermutation in these RBD variant-binding clones compared to clones that exclusively bound wild-type RBD. Moreover, the percent of variant cross-binding memory B cells was higher in vaccinees than individuals who recovered from mild COVID-19. mRNA vaccination also generated antigen-specific CD8+ T cells and durable memory CD4+ T cells in most individuals, with early CD4+ T cell responses correlating with humoral immunity at later timepoints. These findings demonstrate robust, multi-component humoral and cellular immune memory to SARS-CoV-2 and current variants of concern for at least 6 months after mRNA vaccination. Finally, we observed that boosting of pre-existing immunity with mRNA vaccination in SARS-CoV-2 recovered individuals primarily increased antibody responses in the short-term without significantly altering antibody decay rates or long-term B and T cell memory. Together, this study provides insights into the generation and evolution of vaccine-induced immunity to SARS-CoV-2, including variants of concern, and has implications for future booster strategies. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=146 HEIGHT=200 SRC="FIGDIR/small/457229v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@16c64b1org.highwire.dtl.DTLVardef@146ca3aorg.highwire.dtl.DTLVardef@86b7edorg.highwire.dtl.DTLVardef@956879_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2021

Rapid induction of antigen-specific CD4+ T cells guides coordinated humoral and cellular immune responses to SARS-CoV-2 mRNA vaccination

The SARS-CoV-2 mRNA vaccines have shown remarkable clinical efficacy, but questions remain about the nature and kinetics of T cell priming. We performed longitudinal antigen-specific T cell analyses in healthy individuals following mRNA vaccination. Vaccination induced rapid near-maximal antigen-specific CD4+ T cell responses in all subjects after the first vaccine dose. CD8+ T cell responses developed gradually after the first and second dose and were variable. Vaccine-induced T cells had central memory characteristics and included both Tfh and Th1 subsets, similar to natural infection. Th1 and Tfh responses following the first dose predicted post-boost CD8+ T cell and neutralizing antibody levels, respectively. Integrated analysis of 26 antigen-specific T cell and humoral responses revealed coordinated features of the immune response to vaccination. Lastly, whereas booster vaccination improved CD4+ and CD8+ T cell responses in SARS-CoV-2 naive subjects, the second vaccine dose had little effect on T cell responses in SARS-CoV-2 recovered individuals. Thus, longitudinal analysis revealed robust T cell responses to mRNA vaccination and highlighted early induction of antigen-specific CD4+ T cells. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=192 HEIGHT=200 SRC="FIGDIR/small/440862v1_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@db812dorg.highwire.dtl.DTLVardef@fdc549org.highwire.dtl.DTLVardef@a34663org.highwire.dtl.DTLVardef@1621e52_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗