Biology subjects

Martinez, D.

Publications and source records attributed to Martinez, D..

At least 19 recordsLinked to original sources

bioRxiv2026

A Full Spectrum Fibroblast Profiling Panel Reveals Phenotypic and Metabolic Heterogeneity of Cancer-Associated Fibroblasts at the Single-Cell Level

Cancer-associated fibroblasts (CAFs) exhibit extensive transcriptional and phenotypic heterogeneity and are highly plastic. Routine approaches to resolving CAF heterogeneity at the single-cell and protein levels are lacking, making it difficult to assess changes in CAF state in response to perturbations. Here, we present an optimized 28-marker spectral flow cytometry panel that uses unsupervised clustering to resolve CAF states across in vivo and in vitro models. Using this new fibroblast profiling panel (FPP), we show that LRRC15+ CAFs in murine pancreatic ductal adenocarcinoma are phenotypically distinct from canonical SMA+ myofibroblasts, rather than representing a subset of this population. We find that marker expression is graded rather than discrete across clusters, indicating that CAF identity spans a continuum rather than fixed states. Metabolic profiling further shows that hypoxic CAFs were enriched for glucose uptake and an inflammatory phenotype. Using in vitro models, we further demonstrate how the FPP can resolve plasticity outcomes. In a 3D organoid co-culture model, direct contact between tumor cells and fibroblasts, but not organoid-derived factors alone, induces a stem-like CAF state also observed in vivo. In 2D, TGF{beta} and inflammatory/hypoxic stimuli each enrich distinct, pre-existing CAF states rather than generating new ones. These findings establish our FPP as a practical method for resolving fibroblast heterogeneity at the protein level in cancer and beyond.

cell biology↗

bioRxiv2026

VLab4Mic: prediction of structural resolvability in super-resolution microscopy

Determining whether a microscopy experiment can resolve a specific feature of a protein assembly remains difficult because researchers must balance imaging modality, labelling strategy, and probe choice. We present VLab4Mic, a simulation platform that predicts structural resolvability before experiments. Starting from atomic models from the PDB or AlphaFold predictions, VLab4Mic places antibodies, nanobodies, chemical linkers, or fluorescent proteins on epitopes, applies stochastic labelling and steric constraints, and generates virtual samples for widefield, confocal, AiryScan, Stimulated Emission Depletion (STED), and Single-Molecule Localisation Microscopy (SMLM). Simulations of nuclear pore complexes agree with experimental data across all five modalities. In case studies, HIV capsid appearance depended strongly on orientation, and STED and SMLM separated domed from flat clathrin lattices where confocal and AiryScan did not. VLab4Mic therefore lets researchers judge which biological questions a given imaging configuration can answer before spending time tuning parameters at the microscope.

bioinformatics↗

bioRxiv2026

NucVerse3D: Generalizable 3D nuclear instance segmentation across heterogeneous microscopy modalities

Accurate three-dimensional (3D) nuclear instance segmentation is a prerequisite for quantitative phenotyping in volumetric microscopy, yet remains challenging in densely packed tissues, irregular nuclear morphologies, and across heterogeneous imaging modalities. Here we present NucVerse3D, a deep-learning framework for generalized 3D nuclei instance segmentation that combines a residual attention 3D U-Net architecture with a reversible gradient-field representation for robust centroid-aware instance reconstruction. NucVerse3D is trained end to end in 3D using modality-agnostic preprocessing and isotropic scale normalization, enabling deployment across confocal microscopy, two-photon microscopy, light-sheet microscopy, micro-computed tomography, and scanning electron microscopy volumes. We benchmarked NucVerse3D on seven volumetric datasets spanning multiple species and tissues, comprising more than forty thousand manually annotated nuclei, including newly released ground-truth datasets of mouse liver tissue (control and hepatocellular carcinoma) and Drosophila brain glial nuclei. Across datasets, NucVerse3D achieved consistently high precision, recall, F1-score, and average precision, and outperformed the state-of-the-art methods particularly in dense and irregular settings, while remaining competitive on simpler cases. A single generalized model trained on pooled data matched the performance of dataset-specific models, and ablation experiments demonstrated that preprocessing and scale normalization substantially contribute to performance under strict intersection-over-union criteria. To demonstrate the biomedical utility of NucVerse3D, we applied it to three-dimensional liver images from a mouse model of hepatocellular carcinoma (HCC). High-fidelity, nucleus-by-nucleus segmentation enabled the quantification of the Nuclear Decoupling Score (NDS), which captures deviations in nuclear DNA-volume coupling at the single-nucleus level. NDS analysis revealed a progressive increase in nuclear abnormalities within tumor regions, forming spatially coherent domains of dysregulated nuclei and highlighting NDS as a potential quantitative biomarker of dysplastic and tumor tissue. Together, NucVerse3D provides a robust and generalizable solution for 3D nuclear instance segmentation and enables quantitative nuclear phenotyping across imaging modalities. Highlights- NucVerse3D provides accurate 3D nuclear instance segmentation across modalities - Residual attention and gradient fields enable robust separation of dense nuclei - New 3D annotated datasets of mouse liver and Drosophila brain are released - A generalized model achieves performance comparable to dataset-specific training - 3D nuclear phenotyping reveals spatially organized nuclear abnormalities in HCC

cell biology↗

bioRxiv2026

CRISPR screens identify targets to rescue age-related T cell dysfunction in cancer

Immune aging is being increasingly recognized as a critical barrier to effective cancer immunotherapy, as the aged tumor microenvironment (TME) drives T cell dysfunction and impairs immune control of cancer1-4. However, the key molecular drivers of this process as well as potential targets to rescue T cell dysfunction in aged tumors remain incompletely understood. Therefore, we performed in vivo single-cell CRISPR screens in CD8 T cells within aged tumors and tumor-draining lymph nodes (tdLNs). We identified Dusp5 and Zfp219 as key regulators of T cell persistence and effector differentiation in aged hosts. Loss of Dusp5, a negative regulator of ERK signaling, increased ERK1/2 phosphorylation and enhanced T cell proliferation in both young and aged tumors. In contrast, loss of Zfp219, a transcriptional repressor, induced epigenetic reprogramming of cytotoxic gene programs, thereby increasing granzyme secretion and enhancing antitumor immunity. Moreover, expression of the human ortholog gene ZNF219 is increased within intratumoral CD8 T cells in older cancer patients. High ZNF219 expression correlates with poorer survival following immune checkpoint blockade (ICB) and reduces persistence of human intratumoral T cells. Notably, Zfp219 ablation synergized with anti-PD-1 blockade in mice to expand effector-like CD8 T cells, leading to significantly enhanced anti-tumor immunity and tumor clearance in aged hosts. Together, these findings highlight Dusp5 and Zfp219 as critical drivers of age-related T cell dysfunction and as potential therapeutic targets to rejuvenate T cell antitumor immunity in older cancer patients.

immunology↗

bioRxiv2026

An ancestral haplotype of P2RX5 yields a B-cell surface marker and a promising multi-lineage immunotherapy target

While CD19- and BCMA-directed immunotherapies have improved outcomes for B-lymphoid and plasma cell malignancies, frequent relapses with antigen loss/downregulation highlight the need for new targets. Here, using transcriptomic datasets and newly-developed monoclonal antibodies, we show that P2RX5, long considered a pseudogene in humans, encodes a stable protein in 80% of individuals of African descent carrying the ancestral haplotype. Like CD19, P2RX5 displays B-cell lineage-restricted expression in normal tissues. Unlike CD19, P2RX5 is expressed not only in B-cell neoplasms, but also in T-cell leukemia (T-ALL) and multiple myeloma (MM). We developed P2RX5-directed bispecific T-cell engagers and CAR T cells, which killed T-ALL cells with no evidence of T-cell fratricide. These agents were non-inferior to FDA-approved CD19- and BCMA-directed immunotherapeutics in cell culture and xenograft models of Burkitt lymphoma and MM, while maintaining potency against CD19- and BCMA-negative variants. Hence, P2RX5 is a unique multi-lineage target for frontline or salvage immunotherapy.

cancer biology↗

bioRxiv2025

Predicting strain-specific metabolic capabilities in the Genus Pseudomonas using a Flux-to-AI approach unravels hidden cell envelope properties.

Bacteria from the Pseudomonas genus are omnipresent in air, soil, and water. They have been widely studied for their broad metabolic versatility and presence in the epidemiological chain, bioproduction, bioremediation, and disease processes. Each year, more genomic sequences are reported in databases and repositories. However, the relationship between the genomic variability of Pseudomonas strains and the diversity in their metabolic capabilities under environmentally relevant phenotypes remains unknown. Additionally, predictive tools for the analysis of different strains in a systematic framework are limited. Here, we reconstructed genome-scale metabolic models (GEMs) of 44 Pseudomonas strains from various environments and investigated their capabilities to metabolize different carbon sources and metabolic intermediaries. By systematically testing the substrate utilization of the models, we demonstrate how GEM-predicted capabilities can differentiate between strains and that high metabolic versatility is associated with the ability of the strains to remove toxic compounds while maintaining core functionalities. Hundreds of model simulations were used as input for a classification schema that uses machine learning algorithms, resulting in the identification of metabolic capabilities that better differentiate between species. Interestingly, transcription and expression models validated these findings by showing how pathways in which those metabolites are members change their proteome allocation across strains (e.g. phenylalanine metabolism as well as in the carbohydrate metabolism). Author summaryA central challenge in understanding how Pseudomonas strains can play symbiotic, competitive, and pathogenic roles depending on their environment can be potentially addressed with advanced computational tools that combine systems biology and machine learning approaches. Remarkable progress in understanding relationships between metabolism and phenotypes of Pseudomonas has been achieved through the collection of multi-omics datasets (e.g. genomic, transcriptomic, proteomics, fluxomics, etc.) from different settings such as air, clinical, soil, and water. However, maximum utilization of those tools has been limited by the lack of computational tools that can capture the metabolism at genome-scale. In this work, we are making available source genome-scale metabolic models for the most studied Pseudomonas strains and generated flux predictions across 44 strains under 425 different growth conditions by changing the carbon source in turn. Predicted growth phenotypes were used as input for machine learning to identify critical metabolic activities that change among strains. Computational resources leveraged here will enable deeper understanding of the commonalities and differences triggering the metabolic capabilities of Pseudomonas strains.

systems biology↗

bioRxiv2025

Age-related degradation of behavioral and network features of Aplysia escape locomotion

Aplysia californica has been a useful model system for studies of the neural basis of behavior, learning, and aging. While the latter topic has been explored with respect to several of its simple reflex behaviors, this study represents the first examination of how one of Aplysias more complex behaviors, escape locomotion, is affected in animals nearing the end of their natural lifespan. Old animals (12-13mo) showed a greatly reduced gallop response compared with middle-aged adults (5-7mo), together with a loss of locomotion onset latency sensitization. Large-scale VSD imaging was used to record motor programs in isolated brain preparations from middle-aged vs. elderly animals. Old brains displayed the same loss of onset latency sensitization seen in the intact old animal behavior, and also a reduced number of cycles per locomotion episode. Brains from middle-aged animals showed an unchanged number of motor program cycles from that observed in intact animals, but a much more transient motor program onset latency sensitization. A further age-related finding was that while in middle-aged brains repeatedly eliciting the motor program led to progressively increasing cumulative activity across trials, in old brains this same procedure led to progressively decreasing activity. Some of our results are consistent with peripheral processes working in concert with the CNS as animals age to support healthy locomotion behavior and its modification by learning, or with early changes in the brain that are not yet expressed in behavior.

neuroscience↗

bioRxiv2025

Advancing Fair and Explainable Machine Learning for Neuroimaging Dementia Pattern Classification in Multi-Ethnic Populations

Dementia, a degenerative disease affecting millions globally, is projected to triple by 2050. Early and precise diagnosis is essential for effective treatment and improved quality of life. However, current diagnostic approaches frequently demonstrate inconsistent precision and impartiality, particularly among diverse cultural groups. This study investigates performance discrepancies in dementia classification among White American, African American, and Hispanic populations. We reveal significant cross-group bias, particularly when models trained on one group are tested on another. To address this, we introduce a novel combination of few-shot learning and domain alignment to improve model adaptability across underrepresented populations. Our results show that these techniques substantially reduce inter-group performance gaps, especially between White American and Hispanic cohorts. This finding highlights the crucial need for fairness-aware strategies and the inclusion of diverse populations in training data to ensure accurate and equitable dementia diagnoses.

neuroscience↗

bioRxiv2025

Neuronal cell adhesion molecule (NRCAM) variant defined by microexon skipping is an essential, antigenically distinct, and targetable surface proteoform in high-grade glioma

To overcome the paucity of known tumor-specific surface antigens in pediatric high-grade glioma (pHGG), we contrasted splicing patterns in pHGGs and normal brain samples. Among alternative splicing events affecting extracellular protein domains, the most pervasive alteration was the skipping of [≤]30 nucleotide-long exons. Several of these skipped microexons mapped to L1-IgCAM family members, such as NRCAM. Bulk and single-nuclei short- and long-read RNA-seq revealed uniform skipping of NRCAM microexons 5 and 19 in virtually every pHGG sample. Importantly, the {Delta}ex5{Delta}ex19 (but not the full-length) NRCAM proteoform was essential for pHGG cell migration and invasion in vitro and tumor growth in vivo. We developed a monoclonal antibody selective for {Delta}ex5{Delta}ex19 NRCAM and demonstrated that "painting" of pHGG cells with this antibody enables killing by T cells armed with an FcRI-based universal immune receptor. Thus, pHGG-specific NRCAM and possibly other L1-IgCAM proteoforms are promising and highly selective targets for adoptive immunotherapies.

cancer biology↗

bioRxiv2024

Identification of DLK1, a Notch ligand, as an immunotherapeutic target and regulator of tumor cell plasticity and chemoresistance in adrenocortical carcinoma

Immunotherapeutic targeting of cell surface proteins is an increasingly effective cancer therapy. However, given the limited number of current targets, the identification of new surface proteins, particularly those with biological importance, is critical. Here, we uncover delta-like non-canonical Notch ligand 1 (DLK1) as a cell surface protein with limited normal tissue expression and high expression in multiple refractory adult metastatic cancers including small cell lung cancer (SCLC) and adrenocortical carcinoma (ACC), a rare cancer with few effective therapies. In ACC, ADCT-701, a DLK1 targeting antibody-drug conjugate (ADC), shows potent in vitro activity among established cell lines and a new cohort of patient-derived organoids as well as robust in vivo anti-tumor responses in cell line-derived and patient-derived xenografts. However, ADCT-701 efficacy is overall limited in ACC due to high expression and activity of the drug efflux protein ABCB1 (MDR1, P-glycoprotein). In contrast, ADCT-701 is extremely potent and induces complete responses in DLK1+ ACC and SCLC in vivo models with low or no ABCB1 expression. Genetic deletion of DLK1 in ACC dramatically downregulates ABCB1 and increases ADC payload and chemotherapy sensitivity through NOTCH1-mediated adrenocortical de-differentiation. Single cell RNA-seq of ACC metastatic tumors reveals significantly decreased adrenocortical differentiation in DLK low or negative cells compared to DLK1 positive cells. This works identifies DLK1 as a novel immunotherapeutic target that regulates tumor cell plasticity and chemoresistance in ACC. Our data support targeting DLK1 with an ADC in ACC and neuroendocrine neoplasms in an active first-in-human phase I clinical trial (NCT06041516).

cancer biology↗

bioRxiv2024

Spatial and Single Cell Mapping of Castleman Disease Reveals Key Stromal Cell Types and Cytokine Pathways

Castleman disease (CD) is inflammatory lymphoproliferative disorder of unclear etiology. To determine the cellular and molecular basis of CD, we analyzed the spatial proteome of 4,485,009 single cells, transcriptome of 50,117 single nuclei, immune repertoire of 8187 single nuclei, and pathogenic mutations in Unicentric CD, idiopathic Multicentric CD, HHV8-associated MCD, and reactive lymph nodes. CD was characterized by increased non-lymphoid and stromal cells that formed unique microenvironments where they interacted with lymphoid cells. Interaction of activated follicular dendritic cell (FDC) cytoplasmic meshworks with mantle zone B cells was associated with B cell activation and differentiation. VEGF, IL-6, MAPK, and extracellular matrix pathways were elevated in stromal cells of CD. CXCL13+ FDCs, PDGFRA+ T-zone reticular cells (TRC), and ACTA2-positive perivascular reticular cells (PRC) were identified as the predominant source of increased VEGF expression and IL-6 signaling in CD. VEGF expression by FDCs was associated with peri-follicular neovascularization. FDC, TRC and PRC of CD activated JAK-STAT, TGF{beta}, and MAPK pathways via ligand-receptor interactions involving collagen, integrins, complement components, and VEGF receptors. T, B and plasma cells were polyclonal but showed class-switched and somatically hypermutated IgG1+ plasma cells consistent with stromal cell-driven germinal center activation. In conclusion, our findings show that stromal cell activation and associated B-cell activation and differentiation, neovascularization and stromal remodeling underlie CD and suggest new targets for treatment. Key pointsO_LICastleman Disease is characterized by activation and proliferation of CXCL13+ FDCs, PDGFRA+ reticular cells, and ACTA2-positive PRCs. C_LIO_LIVEGF and IL-6 from lymph node stromal cells are associated with B-cell activation and differentiation, endothelial proliferation, and inflammation in CD C_LI

pathology↗

bioRxiv2024

BPTF cooperates with MYCN and MYC to link neuroblastoma cell cycle control to epigenetic cellular states

The nucleosome remodeling factor BPTF is required for the deployment of the MYC-driven transcriptional program. Deletion of one Bptf allele delays tumor progression in mouse models of pancreatic cancer and lymphoma. In neuroblastoma, MYCN cooperates with the transcriptional core regulatory circuitry (CRC). High BPTF levels are associated with high-risk features and decreased survival. BPTF depletion results in a dramatic decrease of cell proliferation. Bulk RNA-seq, single-cell sequencing, and tissue microarrays reveal a positive correlation of BPTF and CRC transcription factor expression. Immunoprecipitation/mass spectrometry shows that BPTF interacts with MYCN and the CRC proteins. Genome-wide distribution analysis of BPTF and CRC in neuroblastoma reveals a dual role for BPTF: 1) it co-localizes with MYCN/MYC at the promoter of genes involved in cell cycle and 2) it co-localizes with the CRC at super-enhancers to regulate cell identity. The critical role of BPTF across neuroblastoma subtypes supports its relevance as a therapeutic target.

genomics↗

bioRxiv2023

A proteogenomic surfaceome study identifies DLK1 as an immunotherapeutic target in neuroblastoma

Cancer immunotherapies have produced remarkable results in B-cell malignancies; however, optimal cell surface targets for many solid cancers remain elusive. Here, we present an integrative proteomic, transcriptomic, and epigenomic analysis of tumor specimens along with normal tissues to identify biologically relevant cell surface proteins that can serve as immunotherapeutic targets for neuroblastoma, an often-fatal childhood cancer of the developing nervous system. We apply this approach to human-derived cell lines (N=9) and cell/patient-derived xenograft (N=12) models of neuroblastoma. Plasma membrane-enriched mass spectrometry identified 1,461 cell surface proteins in cell lines and 1,401 in xenograft models, respectively. Additional proteogenomic analyses revealed 60 high-confidence candidate immunotherapeutic targets and we prioritized Delta-like canonical notch ligand 1 (DLK1) for further study. High expression of DLK1 directly correlated with the presence of a super-enhancer spanning the DLK1 locus. Robust cell surface expression of DLK1 was validated by immunofluorescence, flow cytometry, and immunohistochemistry. Short hairpin RNA mediated silencing of DLK1 in neuroblastoma cells resulted in increased cellular differentiation. ADCT-701, a DLK1-targeting antibody-drug conjugate (ADC), showed potent and specific cytotoxicity in DLK1-expressing neuroblastoma xenograft models. Moreover, DLK1 is highly expressed in several adult cancer types, including adrenocortical carcinoma (ACC), pheochromocytoma/paraganglioma (PCPG), hepatoblastoma, and small cell lung cancer (SCLC), suggesting potential clinical benefit beyond neuroblastoma. Taken together, our study demonstrates the utility of comprehensive cancer surfaceome characterization and credentials DLK1 as an immunotherapeutic target. HighlightsO_LIPlasma membrane enriched proteomics defines surfaceome of neuroblastoma C_LIO_LIMulti-omic data integration prioritizes DLK1 as a candidate immunotherapeutic target in neuroblastoma and other cancers C_LIO_LIDLK1 expression is driven by a super-enhancer C_LIO_LIDLK1 silencing in neuroblastoma cells results in cellular differentiation C_LIO_LIADCT-701, a DLK1-targeting antibody-drug conjugate, shows potent and specific cytotoxicity in DLK1-expressing neuroblastoma preclinical models C_LI

cancer biology↗

bioRxiv2023

Vaccine-mediated protection against merbecovirus and sarbecovirus challenge in mice

The emergence of three distinct highly pathogenic human coronaviruses - SARS-CoV in 2003, MERS-CoV in 2012, and SARS-CoV-2 in 2019 - underlines the need to develop broadly active vaccines against the Merbecovirus and Sarbecovirus betacoronavirus subgenera. While SARS-CoV-2 vaccines are highly protective against severe COVID-19 disease, they do not protect against other sarbecoviruses or merbecoviruses. Here, we vaccinate mice with a trivalent sortase-conjugate nanoparticle (scNP) vaccine containing the SARS-CoV-2, RsSHC014, and MERS-CoV receptor binding domains (RBDs), which elicited live-virus neutralizing antibody responses and broad protection. Specifically, a monovalent SARS-CoV-2 RBD scNP vaccine only protected against sarbecovirus challenge, whereas the trivalent RBD scNP vaccine protected against both merbecovirus and sarbecovirus challenge in highly pathogenic and lethal mouse models. Moreover, the trivalent RBD scNP elicited serum neutralizing antibodies against SARS-CoV, MERS-CoV and SARS-CoV-2 BA.1 live viruses. Our findings show that a trivalent RBD nanoparticle vaccine displaying merbecovirus and sarbecovirus immunogens elicits immunity that broadly protects mice against disease. This study demonstrates proof-of-concept for a single pan-betacoronavirus vaccine to protect against three highly pathogenic human coronaviruses spanning two betacoronavirus subgenera.

immunology↗

bioRxiv2023

Hep3D: A 3D single-cell digital atlas of the liver to study spatio-temporal tissue architecture

Three dimensional (3D) geometrical models are not only a powerful tool for quantitatively characterizing complex tissues but also useful for probing structure-function relationships in a tissue. However, these models are generally incomplete due to experimental limitations in acquiring multiple (>4) fluorescent channels simultaneously. Indeed, predictive geometrical and functional models of the liver have been restricted to few tissue and cellular components, excluding important cellular populations such as hepatic stellate cells (HSCs) and Kupffer cells (KCs). Here, we performed deep-tissue immunostaining, multiphoton microscopy, deeplearning techniques, and 3D image processing to computationally expand the number of simultaneously reconstructed tissue structures. We then generated a spatio-temporal singlecell atlas of hepatic architecture (Hep3D), including all main tissue and cellular components at different stages of post-natal development in mice. We used Hep3D to quantitatively study 1) hepatic morphodynamics from early post-natal development to adulthood, and 2) the structural role of KCs in the murine liver homeostasis. In addition to a complete description of bile canaliculi and sinusoidal network remodeling, our analysis uncovered unexpected spatiotemporal patterns of non-parenchymal cells and hepatocytes differing in size, number of nuclei, and DNA content. Surprisingly, we found that the specific depletion of KCs alters the number and morphology of the HSCs. These findings reveal novel characteristics of liver heterogeneity and have important implications for both the structural organization of liver tissue and its function. Our next-gen 3D single-cell atlas is a powerful tool to understand liver tissue architecture, under both physiological and pathological conditions.

cell biology↗

bioRxiv2022

Targeting Spike Glycans to Inhibit SARS-CoV2 Viral Entry

SARS-CoV-2 Spike harbors glycans which function as ligands for lectins. Therefore, it should be possible to exploit lectins to target SARS-CoV-2 and inhibit cellular entry by binding glycans on the Spike protein. Burkholderia oklahomensis agglutinin (BOA) is an antiviral lectin that interacts with viral glycoproteins via N-linked high mannose glycans. Here, we show that BOA binds to the Spike protein and is a potent inhibitor of SARS-CoV-2 viral entry at nanomolar concentrations. Using a variety of biophysical tools, we demonstrate that the interaction is avidity driven and that BOA crosslinks the Spike protein into soluble aggregates. Furthermore, using virus neutralization assays, we demonstrate that BOA effectively inhibits all tested variants of concern as well as SARS-CoV 2003, establishing that glycan-targeting molecules have the potential to be pan-coronavirus inhibitors.

biochemistry↗

bioRxiv2022

Quantitative analyses of T cell motion in tissue reveals factors driving T cell search in tissues

T cells are required to clear infection, moving first in lymph nodes to interact with antigen bearing dendritic cells leading to activation. T cells then move to sites of infection to find and clear infection. T cell motion plays a role in how quickly a T cell finds its target, from initial naive T cell activation by a dendritic cell to interaction with target cells in infected tissue. To better understand how different tissue environments might affect T cell motility, we compared multiple features of T cell motion including speed, persistence, turning angle, directionality, and confinement of motion from T cells moving in multiple tissues using tracks collected with microscopy from murine tissues. We quantitatively analyzed naive T cell motility within the lymph node and compared motility parameters with activated CD8 T cells moving within the villi of small intestine and lung under different activation conditions. Our motility analysis found that while the speeds and the overall displacement of T cells vary within all tissues analyzed, T cells in all tissues tended to persist at the same speed, particularly if the previous speed is very slow (less than 2 {micro}m/min) or very fast (greater than 8 {micro}m/min) with the exception of T cells in the villi for speeds greater than 10 {micro}m/min. Interestingly, we found that turning angles of T cells in the lung show a marked population of T cells turning at close to 180o, while T cells in lymph nodes and villi do not exhibit this "reversing" movement. Additionally, T cells in the lung showed significantly decreased meandering ratios and increased confinement compared to T cells in lymph nodes and villi. The combination of these differences in motility patterns led to a decrease in the total volume scanned by T cells in lung compared to T cells in lymph node and villi. These results suggest that the tissue environment in which T cells move can impact the type of motility and ultimately, the efficiency of T cell search for target cells within specialized tissues such as the lung.

immunology↗

bioRxiv2022

A Multitrait Locus Regulates Sarbecovirus Pathogenesis

Infectious diseases have shaped the human population genetic structure, and genetic variation influences the susceptibility to many viral diseases. However, a variety of challenges have made the implementation of traditional human Genome-wide Association Studies (GWAS) approaches to study these infectious outcomes challenging. In contrast, mouse models of infectious diseases provide an experimental control and precision, which facilitates analyses and mechanistic studies of the role of genetic variation on infection. Here we use a genetic mapping cross between two distinct Collaborative Cross mouse strains with respect to SARS-CoV disease outcomes. We find several loci control differential disease outcome for a variety of traits in the context of SARS-CoV infection. Importantly, we identify a locus on mouse Chromosome 9 that shows conserved synteny with a human GWAS locus for SARS-CoV-2 severe disease. We follow-up and confirm a role for this locus, and identify two candidate genes, CCR9 and CXCR6 that both play a key role in regulating the severity of SARS-CoV, SARS-CoV-2 and a distantly related bat sarbecovirus disease outcomes. As such we provide a template for using experimental mouse crosses to identify and characterize multitrait loci that regulate pathogenic infectious outcomes across species.

microbiology↗