Biology subjects

Sun, E.

Publications and source records attributed to Sun, E..

At least 19 recordsLinked to original sources

bioRxiv2026

Systems-Scale Structural Modeling Reveals the Germline Architecture of Immunodominance

The adaptive immune system generates diverse antibodies to protect against infection, yet responses often focus on a limited number of antigenic sites, a phenomenon called immunodominance. Using the SARS-CoV-2 receptor-binding domain as a model, this study combines large-scale antibody sequencing, deep mutational scanning, and AlphaFold 3 structural modeling to investigate the basis of immunodominant epitope selection. The results show that germline-encoded antibody features are a primary driver of immunodominance. Specifically, 76% of RBD-targeting antibodies display conserved gene segment usage and/or germline-encoded HCDR3 motifs. Structural analyses identified recurrent germline-encoded residues within these regions that interact with immunodominant epitopes, and mutating these residues eliminated binding. Mutations in SARS-CoV-2 variants frequently disrupt these interactions and are associated with immune escape; other mutations enable germline-mediated recognition and generate new immunodominant epitopes. These findings indicate that innate features, rather than diverse somatic mutations, determine binding specificity for the large majority of the antibody response and underlie antibody immunodominance.

immunology↗

bioRxiv2026

Protozoan predation selects for key symbiotic traits in an environmentally transmitted beneficial symbiosis

AbstractBeneficial associations between bobtail squids (Cephalopoda: Sepiolidae) and Vibrio bacteria encompass a unique association where symbionts are obtained environmentally from the surrounding environment. Vibrio symbionts are susceptible to a number of ecological pressures such as protozoan grazing whilst in their free-living state. Impacts of grazing have several consequences for symbiosis characteristics such as biofilm formation, a trait crucial for survival both in and outside the squid. Therefore, in order to ascertain how biotic factors such as grazing in the environment effect symbiotic success, two V. fischeri strains, ES114 and ETBB1-C were experimentally evolved in separate biofilm grazing experiments with the amoeba, Acanthamoeba castellanii and ciliate Tetrahymena pyriformis. Both ES114 and ETBB1-C biofilms were evolved up to 50 generations through serial passaging. At 50 generations, ES114 biofilms displayed variability in response to predation by both predators, whereas ETBB1-C biofilms were more stable across generations of grazing. A. castellanii decreased in population numbers when co-inoculated with ETBB1-C, whereas T. pyriformis increased in numbers with biofilm growth. Growth of V. fischeri biofilms in the presence of grazers such as T. pyriformis has an important role in inducing biofilm growth by acting as a chaperone for recycling nutrients back into the environment. Additionally, V. fischeri colonization fitness in the host was dependent on which grazer was used to evolve the biofilms. Such variation in response by V. fischeri to different types of predation demonstrates the versatility of this symbiont in its free living state and has subsequent impacts on the eventual association with squids. ImportanceThis manuscript demonstrates the importance of biotic factors (such as protozoan grazing) in the environment that effect host colonization in a beneficial symbiosis. Using an experimental evolution approach, this work demonstrates how symbiotic biofilms can adapt to pressures such as grazing that subsequently influences the ability to colonize its invertebrate host.

microbiology↗

bioRxiv2026

Periplasmic gatekeeping of phage DNA entry by rSAM enzyme-mediated maturation of an effector with His-X-Ser repeats

In the relentless arms race between bacteria and phages, bacteria have evolved a variety of defense strategies to combat phage infection. However, no bacterial system has been identified that specifically target the phage DNA entry phase. Here, we present a novel bacterial antiphage system, termed HXS, which provides broad-spectrum and robust antiphage activity by interfering with phage DNA entry. The HXS system consists of two radical S-adenosylmethionine (rSAM) enzymes (HxsB and HxsC), a small protein (HxsD), and the effector HxsA with a peptidoglycan-binding domain and five His-Xaa-Ser (HXS) repeats. HxsB/HxsC catalyze rSAM enzyme-dependent maturation of HxsA, including N-terminal processing and a site-specific +8 Da modification, thereby producing a periplasmic effector required for HXS defense. Biochemical evidence supports a model in which the matured effector likely engages incoming DNA electrostatically to arrest entry, establishing an rSAM enzyme-modified protein effector in antiphage defense.

microbiology↗

bioRxiv2025

BrainBridge Characterizes Key Factors affecting Alzheimer's Disease and Associated Phenotypes

Single-cell RNA sequencing (scRNA-seq) has significantly advanced our understanding of Alzheimers disease and aging by revealing cellular heterogeneity and shifts in cell-type composition between diseased/old and healthy/young individuals. However, few existing studies utilize the rich information in single-cell transcriptomic atlases for robust patient-level modeling and biological feature selection. To address this gap, we present BrainBridge, a deep learning-based framework designed to integrate atlas-scale single-cell transcriptomic data with phenotypic information to model the biomolecular complexity of the human brain. BrainBridge functions both as a powerful predictor and an embedding model for representing sample-level expression profiles and covariates through comprehensive benchmarking. We also demonstrate its effectiveness in prioritizing key genes and cell types associated with disease progression, aging, and sex differences. We further validate our findings using external resources, including genome-wide and epigenome-wide association studies (GWAS and EWAS), spatial transcriptomics, and perturb-seq experiments. Finally, we deploy BrainBridge within an interactive, agent-powered interface that enables intuitive and user-friendly model interactions, promoting broader accessibility and application in biomedical research.

bioinformatics↗

bioRxiv2025

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↗

bioRxiv2025

Scaling Large Language Models for Next-Generation Single-Cell Analysis

AO_SCPLOWBSTRACTC_SCPLOWSingle-cell RNA sequencing has transformed our understanding of cellular diversity, yet current single-cell foundation models (scFMs) remain limited in their scalability, flexibility across diverse tasks, and ability to natively integrate textual information. In this work, we build upon the Cell2Sentence (C2S) framework, which represents scRNA-seq profiles as textual "cell sentences," to train Large Language Models (LLMs) on a corpus comprising over one billion tokens of transcriptomic data, biological text, and metadata. Scaling the model to 27 billion parameters yields consistent improvements in predictive and generative capabilities and supports advanced downstream tasks that require synthesis of information across multi-cellular contexts. Targeted fine-tuning with modern reinforcement learning techniques produces strong performance in perturbation response prediction, natural language interpretation, and complex biological reasoning. This predictive strength enabled a dual-context virtual screen that nominated the kinase inhibitor silmitasertib (CX-4945) as a candidate for context-selective upregulation of antigen presentation. Experimental assessment in human cell models unseen during training supported this prediction, demonstrating that C2S-Scale can effectively guide the discovery of context-conditioned biology. C2S-Scale unifies transcriptomic and textual data at unprecedented scales, surpassing both specialized single-cell models and general-purpose LLMs to provide a platform for next-generation single-cell analysis and the development of "virtual cells."

bioinformatics↗

bioRxiv2025

Allosteric inhibition rescues hydrocephalus caused by catalytically inactive Shp2

SHP2, a protein tyrosine phosphatase (PTP) crucial in Ras-MAPK signaling, is associated with various human congenital diseases and cancers. Here, we show that the catalytically inactive Shp2C459S mutation results in communicating hydrocephalus, similar to the catalytically activating Shp2E76K and Mek1DD mutants. Unlike previous mutants, however, Shp2C459S/+ mutation uniquely affects ciliary development rather than neurogenesis, leading to reduced cilia density and impaired ciliary motility. Differential scanning fluorimetry revealed that SHP2C459S, SHP2E76K and SHP2C459S/E76K mutations all induce an open SHP2 conformation, but only SHP2C459S leads to aberrant GAB1 phosphorylation in cells expressing wild-type SHP2. This distinctive signaling pattern correlates with our observations in brain ventricular tissues of Shp2C459S/+ mice, where Erk and Stat3 activities remain normal but Gab1 phosphorylation is elevated. Critically, we show that the hydrocephalus phenotype in Shp2C459S mice can be mitigated by allosteric inhibition of Shp2. These findings suggest that Shp2-associated hydrocephalus is driven by conformational changes rather than altered catalytic activity. Our results underscore the therapeutic potential of conformation-specific allosteric inhibitors in targeting both catalytically active and inactive SHP2 mutants.

pathology↗

bioRxiv2025

Antidepressants promote developmental-like plasticity through remodeling of extracellular matrix

Antidepressants are widely used to treat mood and anxiety disorders, yet the cellular and molecular mechanisms underlying their therapeutic effects remain poorly understood. Here, we show that the selective serotonin reuptake inhibitor (SSRI) fluoxetine rejuvenates the dentate gyrus (DG) by reactivating a latent developmental plasticity program in mature neurons, which is required for re-engaging critical period-like synaptic remodeling and antidepressant-like behavioral effects. Single nuclei transcriptomic profiling across all hippocampal cell types revealed a strikingly selective response in the DG, where mature neurons re-engaged a developmental-like transcriptional state, an effect distinct from adult neurogenesis. Chronic fluoxetine treatment induced expression of SOX11, a developmental transcription factor involved in neurodevelopment and axonal regeneration that is normally silenced in the adult brain. Reactivation of SOX11 in mature DG neurons was necessary for both the antidepressant-like behavioral effects of fluoxetine and the re-engagement of critical period-like synaptic remodeling. Notably, SOX11 reactivation was also induced by physiological stimuli, including environmental enrichment and peripheral axon regeneration, suggesting that mature neurons retain access to a conserved developmental plasticity program throughout adulthood. We further identified evidence of this form of developmental plasticity in the adult human brain, an effect distinct from adult neurogenesis. At the structural level, fluoxetine remodeled novel extracellular matrix (ECM) structures within the DG distinct from canonical perineuronal nets, and targeted ECM degradation was sufficient to reactivate SOX11 in mature neurons, identifying the ECM as a key regulator of neuronal rejuvenation. Altogether, these findings demonstrate that mature neurons retain an intrinsic capacity to re-engage dormant developmental programs, and that antidepressants harness this regenerative plasticity to drive neural circuit remodeling and antidepressant-like effects.

neuroscience↗

bioRxiv2024

MITOCHONDRIAL ANTIVIRAL PATHWAYS CONTROL ANTI-HIV RESPONSES AND ISCHEMIC STROKE OUTCOMES VIA THE RIG-1 SIGNALING AND INNATE IMMUNITY MECHANISMS

Occludin (ocln) is one of the main regulatory cells of the blood-brain barrier (BBB). Ocln silencing resulted in alterations of the gene expression signatures of a variety of genes of the innate immunity system, including IFN-stimulated genes (ISGs) and the antiviral retinoic acid-inducible gene-1 (RIG-1) signaling pathway, which functions as a regulator of the cytoplasmic sensors upstream of the mitochondrial antiviral signaling protein (MAVS). Indeed, we observed dysfunctional mitochondrial bioenergetics, dynamics, and autophagy in our system. Alterations of mitochondrial bioenergetics and innate immune protection translated into worsened ischemic stroke outcomes in EcoHIV-infected ocln deficient mice. Overall, these results allow for a better understanding of the molecular mechanisms of viral infection in the brain and describe a previously unrecognized role of ocln as a key factor in the control of innate immune responses and mitochondrial dynamics, which affect cerebral vascular diseases such as ischemic stroke.

neuroscience↗

bioRxiv2024

Freeform robotic optical coherence tomography beyond the optical field-of-view limit

Imaging complex, non-planar anatomies with optical coherence tomography (OCT) is limited by the optical field of view (FOV) in a single volumetric acquisition. Combining linear mechanical translation with OCT extends the FOV but suffers from inflexibility in imaging non-planar anatomies. We report the freeform robotic OCT to fill this gap. To address challenges in volumetric reconstruction associated with the robotic movement accuracy being two orders of magnitudes worse than OCT imaging resolution, we developed a volumetric registration algorithm based on simultaneous localization and mapping (SLAM) to overcome this limitation. We imaged the entire aqueous humor outflow pathway, whose imaging has the potential to customize glaucoma surgeries but is typically constrained by the FOV, circumferentially in mice as a test. We acquired volumetric OCT data at different robotic poses and reconstructed the entire anterior segment of the eye. The reconstructed volumes showed heterogeneous Schlemms canal (SC) morphology in the reconstructed anterior segment and revealed a segmental nature in the circumferential distribution of collector channels (CC) with spatial features as small as a few micrometers.

bioengineering↗

bioRxiv2024

Genome-Wide Identification and Expression Pattern of the N-acetylserotonin deacetylase (ASDAC) Gene Family in Orchidaceae

Orchids are a kind of horticultural plant with highly ornamental and medical value. N-acetylserotonin deacetylase (ASDAC) is the only reverse enzyme of the melatonin biosynthesis pathway, and plays an important role in regulating the balance of melatonin. Melatonin as a multifunctional molecule, is typically involved in plant growth and development regulation, as well as abiotic stress tolerance. Here, we aimed at identifying ASDAC genes from the orchid genome to provide valuable information for further study of the role of melatonin in orchids. In this study, a total of 7 ASDAC genes were identified from the 7 orchid genome with one member in each species. The 7 orchid ASDACs have an HDAC functional domain, and cluster together with functionally confirmed OsHDAC10 and AtHDAC14, it shows that these members may have function of N-acetylserotonin deacetylase. Furthermore, based on the phylogenetic, motif, and gene structure analysis, the same clusters orchid ASDAC or ASDAC-like genes generally contained similar introns and motifs, suggesting the distribution pattern of exons/introns and motifs were strongly related to phylogeny on an evolutionary basis. Interestingly, homologous genes of OsHDAC10 and AtHDAC14 in Gastrodia elata have low homology and not cluster together with rice and A.thaliana ASDACs, showing that ASDAC gene family may lost in the holomycoheterotrophic orchids. The Ka/Ks ratios of ASDAC gene pairs from lower plant to higher plant were less than one, suggested that ASDAC genes have undergone purifying selection during the evolution process. Cis-acting element analysis results showed that the promoter regions of orchid ASDAC genes contained plant growth and development, phytohormone, and stress-responsive elements. Moreover, most orchid ASDACs were expressed in the roots, stems, leaves, flowers, and seeds. Combined cis-acting element and tissue expression analysis, indicating orchid ASDAC genes are involved in melatonin regulation of growth and development, as well as melatonin responding to various stresses in orchids. These findings of orchid ASDAC genes may provide valuable information for further study of the role of melatonin in orchids.

bioinformatics↗

bioRxiv2024

A proteome-wide quantitative guide for nanoscale spatially resolved extraction of membrane proteins into native nanodiscs

The intricate molecular environment of the native membrane profoundly influences every aspect of membrane protein (MP) biology. Despite this, the most prevalent method of studying MPs uses detergent-like molecules that disrupt and remove this vital local membrane context. This severely impedes our ability to quantitatively decipher the local molecular context and comprehend its regulatory role in the structure, function, and biogenesis of MPs. Using a library of membrane-active polymers we have developed a platform for the high-throughput analysis of the membrane proteome. The platform enables near-complete spatially resolved extraction of target MPs directly from their endogenous membranes into native nanodiscs that maintain the local membrane context. We accompany this advancement with an open-access database that quantifies the polymer-specific extraction variability for 2065 unique mammalian MPs and provides the most optimized condition for each of them. Our method enables rapid and near-complete extraction and purification of target MPs directly from their endogenous organellar membranes at physiological expression levels while maintaining the nanoscale local membrane environment. Going beyond the plasma membrane proteome, our platform enables extraction from any target organellar membrane including the endoplasmic reticulum, mitochondria, lysosome, Golgi, and even transient organelles such as the autophagosome. To further validate this platform, we took several independent MPs and demonstrated how our resource can enable rapid extraction and purification of target MPs from different organellar membranes with high efficiency and purity. Further, taking two synaptic vesicle MPs, we show how the database can be extended to capture multiprotein complexes between overexpressed MPs. We expect these publicly available resources to empower researchers across disciplines to efficiently capture membrane nano-scoops containing a target MP and interface with structural, functional, and other bioanalytical approaches. We demonstrate an example of this by combining our extraction platform with single-molecule TIRF imaging to demonstrate how it can enable rapid determination of homo-oligomeric states of target MPs in native cell membranes.

biophysics↗

bioRxiv2023

TISSUE: uncertainty-calibrated prediction of single-cell spatial transcriptomics improves downstream analyses

Whole-transcriptome spatial profiling of genes at single-cell resolution remains a challenge. To address this limitation, spatial gene expression prediction methods have been developed to infer the spatial expression of unmeasured transcripts, but the quality of these predictions can vary greatly. Here we present TISSUE (Transcript Imputation with Spatial Single-cell Uncertainty Estimation) as a general framework for estimating uncertainty for spatial gene expression predictions and providing uncertainty-aware methods for downstream inference. Across eleven benchmark datasets, TISSUE provides well-calibrated prediction intervals for predicted expression values. Moreover it consistently reduces false discovery rates for differential gene expression analysis, improves clustering and visualization of predicted spatial transcriptomics, and improves the performance of supervised learning models trained on predicted gene expression profiles. Applying TISSUE to a MERFISH spatial transcriptomics dataset of the adult mouse subventricular zone, we identified subtypes within the neural stem cell lineage and developed subtype-specific regional classifiers. TISSUE is publicly available as a flexible wrapper method for existing spatial gene expression prediction methods to assist researchers with implementing uncertainty-aware analyses of spatial transcriptomics data.

bioinformatics↗

bioRxiv2022

The complex roles of genomic DNA modifications of bacteriophage T4 in resistance to nuclease-based defense systems of E. coli

The interplay between defense and counter-defense systems of bacteria and phages is a major driver of evolution of both organisms, leading to their greatest genetic diversity. Bacterial restriction-modification (R-M) and CRISPR-Cas are two well-known defense systems that target phage DNAs through their nuclease activities, whereas phages have developed counter-defense systems through covalent modifications of their genomes. Recent studies have revealed many novel nuclease-containing antiphage systems, which leads to the question of whats the role of phage genome modifications in countering these systems. Here, we scanned Escherichia coli genome sequences available in the NCBI databases and found abundant nuclease-containing defense systems, indicating that phage genomic DNA could be a major target for E. coli to restrict infection. From a collection of 816 E. coli strains, we cloned and validated 14 systems. Particularly, Gabija and type III Druantia systems have broad antiphage activities. Using wild-type phage T4 and its mutants, T4 (hmC) and T4 (C), which contain glucosyl-5-hydroxymethylcytosines, 5-hydroxymethylcytosines, and unmodified cytosines in the genomic DNA respectively, we revealed the complex roles of genomic modification of phage T4 in countering the nuclease-containing defense systems other than simply blocking the degradation of genomic DNA by nuclease.

microbiology↗

bioRxiv2022

Cell type-specific aging clocks to quantify aging and rejuvenation in regenerative regions of the brain

Aging manifests as progressive dysfunction culminating in death. The diversity of cell types is a challenge to the precise quantification of aging and its reversal. Here we develop a suite of aging clocks based on single cell transcriptomic data to characterize cell type-specific aging and rejuvenation strategies. The subventricular zone (SVZ) neurogenic region contains many cell types and provides an excellent system to study cell-level tissue aging and regeneration. We generated 21,458 single-cell transcriptomes from the neurogenic regions of 28 mice, tiling ages from young to old. With these data, we trained a suite of single cell-based regression models (aging clocks) to predict both chronological age (passage of time) and biological age (fitness, in this case the proliferative capacity of the neurogenic region). Both types of clocks perform well on independent cohorts of mice. Genes underlying the single cell-based aging clocks are mostly cell-type specific, but also include a few shared genes in the interferon and lipid metabolism pathways. We used these single cell-based aging clocks to measure transcriptomic rejuvenation, by generating single cell RNA-seq datasets of SVZ neurogenic regions for two interventions - heterochronic parabiosis (young blood) and exercise. Interestingly, the use of aging clocks reveals that both heterochronic parabiosis and exercise reverse transcriptomic aging in the niche, but in different ways across cell types and genes. This study represents the first development of high-resolution aging clocks from single cell transcriptomic data and demonstrates their application to quantify transcriptomic rejuvenation.

genomics↗

bioRxiv2021

A temperate Siphoviridae bacteriophage isolate from Siberian tiger enhances the virulence of Methicillin-resistant Staphylococcus aureus through distinct mechanisms

The emergence and worldwide spread of Methicillin-resistant Staphylococcus aureus (MRSA) poses a threat to human health. While bacteriophages are recognized as an effective alternative to treat infections caused by drug resistant pathogens, some bacteriophages in particular the temperate bacteriophage may also influence the virulence of the host bacteria in distinct ways. In this study, we isolated a bacteriophage vB_Saus_PHB21 from an epidermal sample of Siberian tiger (Panthera tigris altaica) using a MRSA strain SA14 as the indicator. Our following laboratory tests and whole genome sequencing analyses revealed that vB_Saus_PHB21 was a temperate bacteriophage belonging to the Siphoviridae family, and this bacteriophage did not contain any virulence genes. However, the integration of PHB21 genome into the host MRSA increased the bacterial capacities of cell adhesion, cell invasion, anti-phagocytosis and biofilm formation. Challenge of the lysogenic strain (SA14+) caused severer mortalities in both Galleria mellonella and mouse models. Mice challenged with SA14+ showed more serious organ lesions and produced higher inflammatory cytokines (IL-8, IFN-{gamma} and TNF-) compared to those challenged with SA14. In mechanism, we found the integration of PHB21 genome caused the upregulated expression of many genes encoding products involved in bacterial biofilm formation, adherence and invasion to host cells, anti-phagocytosis, and virulence. This study may provide novel knowledge of "bacteria-phage-interactions" in MRSA. IMPORTANCEThe interaction between bacteriophage and bacteria is like a "double-edged sword": phages can either kill bacteria, or they may contribute to the bacterial fitness and virulence. In general, phages have positive impacts on bacterial fitness and virulence mainly because they carry antimicrobial resistance genes (ARGs) and/or virulence factors encoding genes (VFGs) and they can spread these harmful genes to the host bacteria. However, we found those phages which do not harbor ARGs and/or VFGs may also enhance the bacterial fitness and virulence. In addition, we also found the integration of phage genomes may lead to the upregulated expression of virulence associated genes in bacteria. Our study may provide new insights to redefine the relationship between phage and bacteria, and the results may also remind a cautious way to set phage-therapy for bacterial infections, before which the safety of a phage intends to be used should be fully evaluated.

microbiology↗

bioRxiv2021

High-Throughput and High-Dimensional Single Cell Analysis of Antigen-Specific CD8+ T cells

Although critical to T cell function, antigen specificity is often omitted in high-throughput multi-omics based T cell profiling due to technical challenges. We describe a high-dimensional, tetramer-associated T cell receptor sequencing (TetTCR-SeqHD) method to simultaneously profile TCR sequences, cognate antigen specificities, targeted gene-expression, and surface-protein expression from tens of thousands of single cells. Using polyclonal CD8+ T cells with known antigen specificity and TCR sequences, we demonstrated over 98% precision for detecting the correct antigen specificity. We also evaluated gene-expression and phenotypic differences among antigen-specific CD8+ T cells and characterized phenotype signatures of influenza- and EBV-specific CD8+ T cells that are unique to their pathogen targets. Moreover, with the high-throughput capacity of profiling hundreds of antigens simultaneously, we applied TetTCR-SeqHD to identify antigens that preferentially enrich cognate CD8+ T cells in type 1 diabetes patients compared to healthy controls, and discovered a TCR that cross reacts between diabetic and microbiome antigens. TetTCR-SeqHD is a powerful approach for profiling T cell responses.

immunology↗

bioRxiv2018

High-throughput determination of the antigen specificities of T cell receptors in single cells

We present tetramer-associated T-cell receptor sequencing (TetTCR-Seq), a method to link T cell receptor (TCR) sequences to their cognate antigens in single cells at high throughput. Binding is determined using a library of DNA-barcoded antigen tetramers that is rapidly generated by in vitro transcription and translation. We applied TetTCR-Seq to identify patterns in TCR cross-reactivity with cancer neo-antigens and to rapidly isolate neo-antigen-specific TCRs with no cross-reactivity to the wild-type antigen.

immunology↗