Biology subjects

Sette, A.

Publications and source records attributed to Sette, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Andes virus from the MV Hondius outbreak is highly pathogenic in hamsters and airborne shed

In May 2026, an outbreak of hantavirus pulmonary syndrome (HPS) caused by Andes virus (ANDV) was detected aboard the cruise ship MV Hondius, sparking public health measures in multiple countries. ANDV infections in humans are mostly sporadic, most often linked to exposure to infected rodents in South America, although small clusters of human cases, like the 2026 outbreak on the MV Hondius occur as well. It is not known whether virological factors may contribute to this distinct epidemiology, and no phenotypic characterisation of the newly emerged ANDV (ANDV2026) has been carried out to date. Here, using an ANDV isolate from a presymptomatic patient from the MV Hondius, we studied pathogenesis, identified sites of viral replication, characterized innate and adaptive immune responses, and quantified shedding in golden Syrian hamsters. ANDV2026 proved to be highly pathogenic in hamsters, causing severe pulmonary disease reminiscent of HPS. ANDV2026 triggered a delayed type-I IFN response and inflammatory response in the lungs consistent with the key pathological features of HPS, and we detected viral replication in both respiratory and extra-respiratory tissues, including the brain. Infected animals mounted neutralising antibodies and T cell responses, the latter directed predominantly against the L and N proteins. Importantly, ANDV2026-infected animals shed virus through multiple routes, and we detected infectious virus in air samplers connected to cages housing ANDV2026-infected hamsters. In contrast, control hamsters infected with a rodent-derived ANDV isolate (ANDV9717869) shed little virus and air samples were consistently negative. These findings consolidate established features of ANDV pathogenesis, while revealing properties not previously described. Phenotypic characterisation of patient-derived ANDV isolates in animal models can strengthen outbreak preparedness, identify markers of disease severity, and support the development of medical countermeasures.

microbiology↗

bioRxiv2026

Durability and diversity of human upper airway T cell memory

T cells are major contributors to protective immunity against pathogens and cancers. Immune memory is a central feature of protective adaptive immunity, and mucosal barrier tissues are major sites of pathogen invasion. Yet, fundamental gaps remain in our knowledge of human T cell immune memory durability in mucosal barrier sites. Here, we employed minimally invasive nasal swab sampling to directly detect, and longitudinally assess, human antigen-specific T cells in two upper airway tissue sites (~ 900 samples) and peripheral blood. Antigen-specific memory CD8 and CD4 T cells were detected in upper airway tissue of > 95% of individuals. Both memory CD8 and CD4 T cells were sustained in both mucosal epithelial and mucosal lymphoid tissue over the course of 18+ months, with monthly sampling, and no clear evidence of decline. Virus-specific upper airway CD8 and CD4 T cells were predominantly resident memory T cells (TRM) throughout the 18+ month period of observation. These findings can inform future T cell vaccines and therapeutics.

immunology↗

bioRxiv2026

Sustained Delivery of a SARS-CoV-2 Subunit Vaccine in An Adjuvanted Hydrogel Depot Enhances Vaccine Responses in Nonhuman Primates

While natural infections expose the immune system for days to weeks of inflammation and antigen presentation, immunizations with conventional bolus vaccines often lead to rapid clearance of antigens and adjuvants. Prolonged exposure to vaccines using controlled delivery devices or repeated dosing regimens has been shown to enhance germinal center reactions, leading to improved humoral responses, including increased magnitude of antibody titers and enhanced neutralizing activity. Herein, we report the use of injectable polymer-nanoparticle (PNP) hydrogels as a vaccine depot technology for sustained delivery of the clinically relevant SARS-CoV-2 Hexapro subunit antigen and a toll-like receptor agonist adjuvant. In mice, we demonstrated that PNP hydrogel vaccines enhanced germinal center responses and antibody responses relative to bolus vaccination. In nonhuman primates, hydrogel vaccines induced enhanced and durable antibody responses against wildtype and variants of concern such as Omicron BA.5 compared to bolus vaccination. We report the first use of a biomaterials-based approach for sustained delivery of vaccines in nonhuman primates, further advancing toward clinical translation.

bioengineering↗

bioRxiv2026

Revised Adaptive Immune Receptor Data in the Immune Epitope Database

The Immune Epitope Database (IEDB, iedb.org) is a freely available resource that catalogs experimentally defined immune epitopes and - if available - the immune receptors that recognize them. Currently, the IEDB records [~]185, 000 T cell receptors and [~]5, 000 B cell receptors/antibodies with experimentally verified epitope specificity. Because these receptor data were manually curated from [~]3, 300 references spanning decades, nomenclature inconsistencies present challenges for computational analyses and user queries. To support integrated analysis of the entire dataset, we revised the IEDB receptor data standardization and validation pipeline to flag and correct inaccuracies. Anomalous receptors from over 800 studies were flagged for re-curation. The updated receptor dataset shows greater conformity through consistent gene nomenclature formatting and harmonized CDR sequence delimitation. Taking advantage of the increased receptor data consistency, the IEDB web interface was expanded to include receptor search features directly on the homepage, support V/J gene and species options in the refined receptor search, and allow direct data export in the Adaptive Immune Receptor Repertoire (AIRR) format. We anticipate that the improved receptor data quality will simplify bioinformatics analyses, and facilitate integration of IEDB data into cross-repository data resources, such as the AIRR Knowledge Commons.

bioinformatics↗

bioRxiv2026

CD1a-Mediated Presentation of Canonical Microbial Peptides to T Cells

Langerhans cells express the nonpolymorphic antigen-presenting molecule CD1a, positioning them as contributors to host immunity against Mycobacterium leprae in human leprosy. CD1a was originally shown to present non-canonical lipopeptide antigens such as dideoxymycobactin and chemically diverse hydrophobic ligands. Here, we generated CD4 T cell lines from leprosy lesions that recognized M. leprae in a CD1a-restricted manner. Unexpectedly, antigen recognition was protease-sensitive, prompting biochemical purification that identified two microbial protein antigens: LppX, a 25-kDa lipoglycoprotein, and Ag85A, a 30-kDa secreted protein with no known lipid modification. Recombinant proteins activated the corresponding T cell lines in a CD1a-dependent manner. Epitope mapping identified 12-mer peptides that fully reconstituted antigenicity, were conserved between M. leprae and M. tuberculosis, and elicited robust, dose-dependent IFN-{gamma} production and T cell proliferation, establishing that DNA-encoded, ribosomally translated peptides serve as CD1a-restricted cognate antigens. Biochemical analyses showed peptide binding to CD1a, supported by isoelectric focusing and surface plasmon resonance (KD [~]75 M for Ag85A). CD1a-peptide tetramers specifically stained cognate T cells, soluble CD1a was sufficient to present peptide antigen, and transfer of the LppX-specific TCR into naive T cells restored antigen responsiveness. Using CD1a-peptide tetramers, we identified antigen-specific T cells enriched in patients undergoing reversal reactions compared with patients with lepromatous leprosy and healthy donors. The CD1a-restricted T cell lines secreted IFN-{gamma} and IL-26, cytokines with established antimicrobial activity. Together, these findings demonstrate that CD1a can present canonical microbial peptides as part of a cell-mediated immune response in leprosy, extending the known spectrum of CD1a ligands. Because CD1a is nonpolymorphic and presents antigens to antimicrobial T cells, CD1a-peptide complexes may provide a broadly applicable platform for studying, detecting, and potentially targeting mycobacterial immunity.

immunology↗

bioRxiv2026

COMBO-RATE: An experimentally validated bioinformatic tool to identify promiscuous HLA restrictions

Defining HLA restriction of T cell epitopes is essential for understanding immune responses in infectious disease, autoimmunity, and vaccine design. Current bioinformatic programs, including the IEDB RATE tool, enable inference of single-HLA restrictions from immune response data of HLA-typed donors. However, T cell epitopes are frequently presented by multiple HLA alleles, a phenomenon termed promiscuous restriction, limiting the utility of single-allele approaches. To address this limitation, we developed COMBO-RATE, an extension of RATE that systematically evaluates combinations of HLA alleles to identify multi-allelic restriction patterns. Analysis of three independent datasets spanning distinct antigen systems and different epitope discovery strategies revealed that promiscuous restriction is a near-universal feature of immunodominant epitopes. Focusing on the 43 immunodominant CD4 T cell epitopes identified in a B. pertussis genome-wide screen, COMBO-RATE outperformed conventional RATE, identifying restrictions for 35 of 43 epitopes, compared to 24 by RATE alone, and uncovered 64 additional allele restrictions, including 29 unique alleles. Experimental validation using single-HLA transfected cell lines and antigen presentation assays confirmed COMBO-RATE-inferred restrictions, demonstrating that a single epitope can be independently presented by distinct HLA alleles. Overall, COMBO-RATE provides a robust and scalable framework for defining complete HLA restriction profiles from existing population response data, with important implications for the design of vaccines requiring broad HLA coverage across genetically diverse populations. This pipeline is available as both a Python package and a user-friendly web application.

immunology↗

bioRxiv2026

Curation at Scale with EPITOME: Extraction Pipeline for Immunological Texts and Open-Source Multimodal Enquiry

The Immune Epitope Database (IEDB, iedb.org) has manually curated epitope data from over 26,000 publications across two decades. With PubMed adding [~]5,000 articles daily, traditional curation methods face scalability challenges. Given the multimodality of data contained in scientific papers, we have sought to build an open-source vision language model (VLM)-based tool that human curators can use to speed up and automate biological data curation. Here we present a multimodal document ingestion and Question-Answering (QnA) pipeline that ties traditional Optical Character Recognition (OCR) and text matching with Vision-Language Model (VLM) capabilities. The system, which we call EPITOME, implements three-stage processing: regex-based epitope and MHC molecule identification, visual element extraction from PDFs, and contextual indexing that links peptide sequences, MHC molecules, and assays to their locations across text, tables, and figures. This indexing is used to supply context for further VLM QnA. Our preliminary results from EPITOME demonstrate promising zero-shot performance of open-source VLMs that suggest promise for accelerating biocuration through a curator-in-the-loop process, with our evaluation identifying strategic points where curator-in-the-loop intervention can enhance overall system accuracy.

bioinformatics↗

bioRxiv2026

NetMHCIIphosPan: a machine learning tool for predictingHLA class II antigen presentation of phosphorylated peptides.

Phosphorylated peptides presented by human leukocyte antigen (HLA) class II molecules play pivotal roles in immune regulation, yet their characterization and prediction remain challenging due to data noise and limited HLA coverage. Here, we introduce NetMHCIIphosPan, a prediction method for HLA-II antigen presentation of phosphorylated peptides, developed using mass spectrometry (MS)-based immunopeptidomics datasets. Employing a refined peptide identification workflow, we reanalyzed earlier HLA-II phospholigand datasets and trained predictive models, achieving superior performance compared to models trained on original data. Binding motif analysis revealed that HLA-specific preferences for phospholigands closely aligned with those of unmodified ligands. Incorporating unmodified ligands into training further enhanced predictive accuracy, particularly for HLA-DP and HLA-DQ molecules. NetMHCIIphosPan outperformed existing tools, such as NetMHCIIpan-4.3 and MixMHC2pred-1.3, for prediction of HLA antigen presentation of phosphorylated peptides demonstrating robustness and utility. This work establishes NetMHCIIphosPan as a state-of-the-art tool for understanding the HLA-II phospholigandome, with potential applications in immunotherapy and vaccine design.

bioinformatics↗

bioRxiv2025

Computational design of HLA class I superbinders for broad T cell immunogenicity

Human leukocyte antigen (HLA) class I molecules are highly polymorphic, restricting peptide binding to narrow sequence subsets. Designing peptides that bind multiple HLA supertypes-- termed superbinders--offers a promising strategy for broad-spectrum T-cell vaccines and immunotherapies. Here we present superHLA, a computational framework that combines Markov Chain Monte Carlo optimization with state-of-the-art MHC binding predictors to design synthetic 9-mer peptides with broad HLA-binding profiles. Using superHLA, we generated over 190,000 candidate superbinders predicted to bind 8-12 HLA class I alleles across distinct supertypes. A multi-tier filtering pipeline--incorporating sequence clustering, synthesis feasibility, cross-predictor validation, and self-peptidome exclusion--yielded a final panel of 100 peptides for experimental testing. Of these, 21 bound [≥]4 supertypes in vitro, including one that bound 9. Superbinders displayed distinct anchor residue preferences and showed minimal similarity to human peptides. These results suggest that HLA superbinders are more abundant than previously recognized and can be rationally designed at scale. This approach supports development of pan-HLA immunogens with broad population coverage and potential applications in vaccine design, neoantigen discovery, and immunotherapy.

immunology↗

bioRxiv2025

Characterizing antibodies binding to the same epitope reveals limited contribution by heavy chain CDR3 sequences relative to other CDRs

The antigen specificity of antibodies is defined mainly by their highly-variable complementarity-determining regions (CDRs), of which the CDR3 is considered to be the most important. Similar antibodies are expected to bind the same epitope on an antigen, but how this similarity should be quantified is unclear. Here, we utilized a large body of publicly available data to identify features that are most informative in predicting if two antibodies are likely to bind to the same epitope. We examined features such as pairwise sequence identities, CDR structural similarity, and geometrical similarity of antibody paratopes. We found that, for antibodies with high overall sequence similarity, the CDR sequence identity alone is sufficient to predict if a pair of antibodies binds to the same epitope. Strikingly, the sequence identity of CDR1 and CDR2 had as much or more predictive power than CDR3, which is commonly thought of as the main determinant of antibody specificity. In addition, for antibody pairs with lower overall sequence identity, including structural information led to significant improvements in predictive performance. Guided by these results, we developed BCRMatch (https://github.com/IEDB/BCRMatch) which uses an ensemble machine-learning approach to predict if pairs of antibodies target the same epitope based on antibody sequence alone. This can be applied to identify potential targets of an antibody of interest by comparing it to antibodies with known specificities.

bioinformatics↗

bioRxiv2025

Peptide Driven Identification of TCRs (PDI-TCR) reveals dynamics and phenotypes of CD4 T cells in tuberculosis

Assigning antigen specificity to T cell receptor (TCR) sequences is challenging due to the TCR repertoires diversity and the complexity of TCR:antigen recognition. We developed the Peptide-Driven Identification of TCRs (PDI-TCR) assay that combines in vitro expansion of cells with peptide pools, bulk TCR sequencing, and statistical analysis to identify antigen-specific TCRs from human blood. A key feature of PDI-TCR is the ability to distinguish true antigen-specific TCR clonotypes from TCRs associated with unspecific bystander activation by comparing responses to non-overlapping peptide pools. We applied PDI-TCR to Tuberculosis (TB) patients, sampling blood at diagnosis and throughout treatment, and Mycobacterium tuberculosis (Mtb)-sensitized healthy individuals (IGRA+). We identified hundreds of Mtb-specific TCRs, as well as unspecific TCRs, and characterized their phenotype in each cohort by single-cell RNA sequencing ex vivo. Mtb-specific T cells were highly diverse, with short-lived effector phenotypes only present in TB at diagnosis, while memory phenotypes were maintained through treatment. In contrast, unspecific expanded T cells were more clonally restricted, had a cytotoxic phenotype, and were maintained throughout treatment. This showcases PDI-TCR as a powerful tool for identifying antigen-specific TCRs, which enables direct ex vivo identification and monitoring of antigen-specific T cells.

immunology↗

bioRxiv2025

Differential memory enrichment of cytotoxic CD4 T cells in Parkinson's disease patients reactive to α-synuclein

Parkinsons disease (PD) is a complex neurodegenerative disease with a largely unknown etiology. Although the loss of dopaminergic neurons in the substantia nigra pars compacta is the pathological hallmark of PD, neuroinflammation also plays a fundamental role in PD pathology. We have previously reported that PD patients have increased frequencies of T cell reactive to peptides from -synuclein (-syn). However, not all PD participants respond to -syn. Furthermore, we have previously found that CD4 T cells from PD participants responding to -syn (PD_R) are transcriptionally distinct from PD participants not responding to -syn (PD_NR). To gain further insight into the pathology of PD_R participants, we investigated surface protein expression of 11 proteins whose genes had previously been found to be differentially expressed when comparing PD_R and healthy control participants not responding to -syn (HC_NR). We found that Cadherin EGF LAG seven-pass G-type receptor 2 (CELSR2) was expressed on a significantly higher proportion of CD4 effector memory T cells (TEM) in PD_R compared to HC_NR. Single-cell RNA sequencing analysis of cells expressing or not expressing CELSR2 revealed that PD_R participants have elevated frequencies of activated TEM subsets and an almost complete loss of cytotoxic TEM cells. Flow cytometry analyses confirmed that Granulysin+ CD4 cytotoxic TEM cells are reduced in PD_R. Taken together, these results provide further insight into the perturbation of T cell subsets in PD_R, and highlights the need for further investigation into the role of Granulysin+ CD4 cytotoxic TEM in PD pathology.

neuroscience↗

bioRxiv2025

T cell responses towards PINK1 and α-synuclein are elevated in prodromal Parkinson's disease

A role of the immune system in Parkinsons disease (PD) progression has long been suspected due to the increased frequency of activated glial cells and infiltrating T cells into the substantia nigra. It was previously reported that PD donors have increased T cell responses towards PINK1 and -synuclein (-syn), two Lewy body-associated proteins. Further, T cell reactivity towards -syn was highest closer to disease onset, highlighting that autoreactive T cells might play a role in PD pathogenesis. However, whether T cell autoreactivity is present during prodromal PD is unknown. Here, we investigated T cell responses towards PINK1 and -syn in donors at high risk of developing PD (i.e. prodromal PD: genetic risk, hyposmia, and or REM sleep behavior disorder), in comparison to PD and healthy control donors. T cell reactivity to these two autoantigens was detected in prodromal PD at levels comparable to those detected in individuals with clinically diagnosed PD. Aligned with the increased incidence of PD in males, we found that males with PD, but not females, had elevated T cell reactivity compared to healthy controls. However, among prodromal PD donors, males and females had elevated T cell responses. These differing trends in reactivity highlights the need for further studies of the impact of biological sex on neuroinflammation and PD progression.

neuroscience↗

bioRxiv2025

Human memory CD4+ T cells recognize Mycobacterium tuberculosis-infected macrophages amid broader pathogen-specific responses

Recognition of macrophages infected with Mycobacterium tuberculosis (Mtb) is essential for CD4+ T cells to prevent tuberculosis (TB). Yet not all antigen-specific T cells recognize infected macrophages in human and murine models. Using monocyte-derived macrophages (MDMs) and autologous memory CD4+ T cells from individuals with latent Mtb infection (LTBI), we quantify T cell activation in response to infected macrophages. T cell antigen receptor (TCR) sequencing revealed >70% of unique and >90% of total Mtb-specific TCR clonotypes in stable LTBI are linked to recognition of infected macrophages, while a subset required exogenous antigen exposure, suggesting incomplete recognition. Clonotypes specific for multiple Mtb antigens and other pathogens were identified, indicating Mtb-specific and non-specific activation. Single-cell transcriptomics demonstrates Mtb-specific T cells express signature effector functions dominated by IFN{gamma}, TNF, IL-2, and GM-CSF or chemokine production and signaling. We propose TB vaccines that elicit T cells capable of recognizing infected macrophages and expressing these canonical effector functions will offer protection against TB.

immunology↗

bioRxiv2025

Evolution of SARS-CoV-2 T cell responses as a function of multiple COVID-19 boosters

The long-term effects of repeated COVID-19 vaccinations on adaptive immunity remain incompletely understood. Here, we conducted a comprehensive three-year longitudinal study examining T cell and antibody responses in 78 vaccinated individuals without reported symptomatic infections. We observed distinct dynamics in Spike-specific humoral and cellular immune responses across multiple vaccine doses. While antibody titers incrementally increased and stabilized with each booster, T cell responses rapidly plateaued, maintaining remarkable stability across CD4+ and CD8+ subsets. Notably, approximately 30% of participants showed CD4+ T cell reactivity to non-Spike antigens, consistent with asymptomatic infections. Single-cell RNA sequencing revealed a diverse landscape of Spike-specific T cell phenotypes, with no evidence of increased exhaustion or significant functional impairment. However, qualitative changes were observed in individuals with evidence of asymptomatic infection, exhibiting unique immunological characteristics, including increased frequencies of Th17-like CD4+ T cells and GZMKhi/IFNR CD8+ T cell subsets. Remarkably, repeated vaccinations in this group were associated with a progressive increase in regulatory T cells, potentially indicating a balanced immune response that may mitigate immunopathology. By regularly stimulating T cell memory, boosters contribute to a stable and enhanced immune response, which may provide better protection against symptomatic infections.

immunology↗

bioRxiv2024

Predicting Immunogenic CD4+ T Cell Epitopes in Bacteria Using Antigen and Peptide Features

BackgroundT cell epitope prediction methods have been broadly utilized to facilitate epitope discovery in infectious agents and help design reagents, diagnostics, and vaccines. Current prediction methods are mainly focused on peptide presentation by MHC molecules, which is a necessary but not sufficient requirement for an epitope. For complex pathogens such as bacteria, it would be desirable to make such predictions more specific to limit the number of candidates that have to be experimentally tested. ObjectiveTo develop a machine learning-based prediction model that integrates both peptide-level and antigen-level features to improve the specificity of CD4+ T cell epitope predictions for bacteria. MethodsWe used a dataset of 20,216 peptides from Mycobacterium tuberculosis (Mtb), tested for T cell recognition in Mtb-infected participants, that led to the discovery of n = 144 peptide epitopes. For each peptide, we calculated six peptide-level features (e.g. MHC class II binding predictions and conservation scores) and six antigen-level features (e.g. including RNA expression levels and subcellular localization scores). Three machine learning algorithms--Random Forest, Gradient Boosting, and XGBoost--were trained using stratified, 5-fold cross-validation and combined into an ensemble model. Experimental validation was performed on Streptococcus pneumoniae peptides, using ex vivo IFN{gamma} assays to confirm the predictive performance. ResultsThe ensemble model achieved an ROC-AUC of 0.91 in predicting immunogenic peptides in the Mycobacterium tuberculosis (Mtb) dataset. Gene expression and conservation were identified as the most impactful features, followed by MHC class II binding predictions. When validated on an independent Bordetella pertussis dataset, the model demonstrated accurate predictive capability, especially for peptides with broad recognition in the participant cohort (ROC-AUC up to 0.82). Prospectively applying the model to Streptococcus pneumoniae, we synthesized peptides predicted by our ensemble model to be immunogenic or non-immunogenic. Ex vivo testing with PBMCs from healthy participants showed that peptides predicted to be immunogenic elicited significantly higher IFN{gamma} responses than non-immunogenic peptides, validating the model. ConclusionsOur machine learning approach, integrating both peptide and antigen features, effectively predicts immunogenic CD4+ T cell epitopes across different bacterial pathogens. This method enhances epitope selection efficiency, aiding vaccine development and immunological research by reducing the need for extensive experimental screening.

immunology↗

bioRxiv2024

Identification of immunogenic and cross-reactive chikungunya virus-specific CD4+ T cell epitopes in chronic chikungunya viral arthritic disease in humans

Chikungunya virus (CHIKV), a mosquito-borne alphavirus, causes acute febrile illness that can progress into chronic chikungunya virus disease (CHIKVD) marked by persistent debilitating arthralgia. At present, the exact cause of chronic CHIKVD is not understood, and in humans, the targets of CD4+ T cells in CHIKV are currently unknown. Here, by stimulating peripheral blood mononuclear cells (PBMCs) collected from patients suffering from chronic CHIKVD with peptides spanning the entire CHIKV genome, we provide a comprehensive landscape of CHIKV CD4+ T cell epitopes. We identified 123 novel CD4+ T cell epitopes and three immunodominant regions in E1, nsP1 and CP proteins. The immunodominance of these E1, nsP1 and CP regions was mapped to optimal epitopes, characterized by the capacity to bind to many common HLA class II allelic variants. In addition, we designed and validated a new CHIKV-specific CD4+ T cell epitope megapool, spanning both structural and non-structural proteins, which can be a useful tool to study CHIKV-specific T cell responses in small blood volumes, typically available in pediatric or clinical samples. Finally, by in silico assessment of the conservation of the CHIKV proteome in a diverse set of alphaviruses, we defined CHIKV epitopes conserved across arthritogenic and encephalitic viruses. Overall, our work is the first to identify CD4+ T cell targets of CHIKV in humans, expanding our capacity to study the role of T cells in CHIKV pathogenesis and mapping targets of alphaviruses for vaccine design.

immunology↗

bioRxiv2024

A novel method for characterizing cell-cell interactions at single-cell resolution reveals unique signatures in blood T cell-monocyte complexes during infection

Communication between immune cells through direct contact is a critical feature of immune responses. Here, we developed a novel high-throughput method to study the transcriptome and adaptive immune receptor repertoire of single cells forming complexes without needing bioinformatic deconvolution. We found that T cells and monocytes forming complexes in blood during active tuberculosis (TB) and dengue hold unique transcriptomic signatures indicative of TCR/MCH-II immune synapses. Additionally, T cells in complexes showed enrichment for effector phenotypes, imaging and transcriptomic features of active TCR signaling, and increased immune activity at diagnosis compared to after anti-TB therapy. We also found evidence for bidirectional RNA exchange between T cells and monocytes, since complexes were markedly enriched for "dual-expressing" cells (i.e., co-expressing T cell and monocyte genes). Thus, studying immune cell complexes at a single-cell resolution offers novel perspectives on immune synaptic interactions occurring in blood during infection. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=59 SRC="FIGDIR/small/612103v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@f90023org.highwire.dtl.DTLVardef@178007corg.highwire.dtl.DTLVardef@167e53corg.highwire.dtl.DTLVardef@1faff48_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗