Biology subjects

Schober, K.

Publications and source records attributed to Schober, K..

15 recordsLinked to original sources

bioRxiv2026

A pro-inflammatory effector-memory T cell program links peripheral EBV priming to CNS autoimmunity

T and B cell-mediated immunosurveillance of the central nervous system (CNS) can become maladaptive in multiple sclerosis (MS). Epstein-Barr virus (EBV) is a likely driver of MS, yet how exactly EBV-specific T cells contribute remains unclear. We generated an antigen-resolved atlas of blood and cerebrospinal fluid (CSF) T cells from untreated MS patients and controls. T cell clones carrying a GZMK effector-memory program in blood were CSF-biased, particularly in MS, and associated with EBV reactivity. In CSF, EBV-reactive GZMK CD8 T cells engaged B lineage cells. Activated CD8 T cells promoted atypical B cell and plasmablast formation, whereas GZMK-enriched effector-memory cells induced IL-6 and IL-8 release from myeloid cells. Together, these findings identify an infection-imprinted, CNS-biased state and support a model in which EBV-specific CD8 T cells contribute to inflammation through a non-canonical mode of B cell and myeloid cell activation.

immunology↗

bioRxiv2026

Germline-encoded V(D)J gene usage does not impose strict constraints on the epitope-specificity of T cell receptors

The theoretical diversity of T cell receptors (TCRs), generated through V(D)J recombination, is enormous, yet the diversity of TCRs capable of recognizing the same epitope remains unknown. Defining this TCR solution space is essential for uncovering basic principles that govern TCR specificity. Using single-cell RNA and TCR sequencing, we generated ultra-deep (more than 4000 unique TCRs per epitope) epitope-specific TCR libraries derived from 560 immunized C57BL/6 mice, identifying over 27,000 unique epitope-reactive TCRs across three distinct CD8+ T cell epitopes presented by two major histocompatibility complex (MHC) class I alleles. Saturation analyses indicated that the solution space for all studied epitopes comprises many tens of thousands of unique TCRs. Despite highly skewed and peptide-dependent VJ-usage patterns, nearly the entire set of functional germline V/ and J/ segments was detected at least once within each epitope-specific repertoire. Therefore, diversity of epitope-specific TCRs is not limited by distinct germline combinations but rather can emerge from a near-to-complete combinatorial space of - and -chain, V and J segments paired with compatible CDR3 sequences.

immunology↗

bioRxiv2026

DextraDemixer enables accurate identification of antigen-specific T cells from pMHC multimer experiments

Antigen specificity of T cells defines the adaptive immune response, yet the vast majority of known T cell receptors (TCRs) lack annotated antigen targets. Single-cell peptide-MHC (pMHC) multimer assays offer a scalable approach to map TCR-antigen interactions. Still, their utility is limited by pervasive non-specific binding and severe overlap between signal and noise, which confound the accurate identification of antigen-specific cells. To address these limitations, we present DextraDemixer, a Bayesian hierarchical mixture model that disentangles antigen-specific T cells from background noise in pMHC multimer data. The model integrates information from negative controls and clonotype structure while providing calibrated uncertainty estimates for classification. We further introduce a dynamic thresholding scheme that enables credible interval-bounded control of the false discovery rate. Extensive benchmarking on simulated datasets and antigen-specific spike-in experiments demonstrated the models robustness and improved accuracy over established methods. In a longitudinal SARS-CoV-2 vaccine study, DextraDemixer identified antigen-specific TCRs characterized by high sequence similarity, elevated antigen-specificity prediction scores, and strong clonal purity. Annotations showed high concordance with external validation data and supported the identification of antigen-specific motifs. Overall, DextraDemixer provides a principled probabilistic framework for reliable identification of antigen-specific TCRs from single-cell pMHC-multimer assays.

bioinformatics↗

bioRxiv2025

Antigen-reactive CD4+ T cells after SARS-CoV-2 vaccination show divergent phenotypic states with or without restimulation bias

Understanding antigen reactivity is crucial for characterizing CD4+ T helper (Th) cell fate, yet conventional peptide restimulation assays introduce phenotypic bias by activating cells ex vivo. However, by performing single-cell RNA and T cell receptor (TCR) sequencing on both antigen-stimulated and unstimulated samples, clonotypes can be tracked across conditions to identify antigen-reactive CD4+ T cells and simultaneously be assessed for their phenotypes in the unperturbed state. Using this reverse phenotyping strategy, complemented by DNA-barcoded peptide-HLA (pHLA) class II multimers, we here tracked SARS-CoV-2 spike-reactive CD4+ T cells longitudinally after repeated mRNA vaccination. Without stimulation, reactive clones showed more Th-neutral features and less of an activated Th1-like state than would be assessed after antigen restimulation. Furthermore, transgenic TCR re-expression guided separation of antigen-specific from bystander-activated clones. These results uncover unbiased phenotypes of antigen-reactive CD4+ T cells and highlight that cell state classification can differ fundamentally when judged by phenotype versus function.

immunology↗

bioRxiv2025

TCR activation impairs CAR-T cytotoxicity against separate target cells

Chimeric antigen receptor T cells (CAR-T) are effective therapeutics against cancer and autoimmunity, but whether the endogenous T-cell receptor (TCR) is beneficial, detrimental or irrelevant for CAR-T function and patient outcome remains unclear. We here traced anti-CD19 CAR-T clonotypes in patients with B-cell malignancies pre- and post-infusion using single-cell RNA-, TCR-, and CITE-sequencing. A cytotoxic phenotype, but not CAR-mediated in vitro reactivity to tumor cells, predicted CAR-T persistence. To test the functional impact of endogenous TCR activity on CAR-T behavior, we combined CAR transduction with orthotopic TCR replacement. This revealed that TCR signaling adds to activation of CAR-T cells, but gradually compromises CAR-mediated cytotoxicity, when TCR and CAR antigens are presented by different target cells. Therefore, spatial antigen separation alters TCR/CAR interplay with implications for therapeutic CAR-T design.

immunology↗

bioRxiv2025

Glycolytic flux sustains human Th1 identity and effector function via STAT1 glycosylation

Fate decisions of T helper (Th) cells are tightly linked to their metabolic states, but precise mechanistic links remain unknown, especially in humans. Using in vitro stimulation in combination with gene editing we studied how metabolic regulation shapes human Th1 cell identity and effector function. Differentiated Th1 cells displayed elevated STAT1 phosphorylation at Tyr701 and Ser727 as well as heightened T-bet and IFN{gamma} expression, which were dampened by CRISPR/Cas9-mediated STAT1 deletion. Metabolic profiling revealed enhanced glycolytic activity in Th1 in comparison to Act.T cells, evidenced by increased extracellular acidification rate, ATP production via glycolysis, glucose uptake, lactate secretion and NADH abundance. SCENITH analysis demonstrated elevated glycolysis-dependent anabolic activity of Th1 cells. Inhibition of glycolysis reduced IFN{gamma} production and STAT1 phosphorylation independent of JAK1/2 activity, STAT1 abundance or SHP-2 activity, implicating glycolysis directly in sustaining STAT1-mediated Th1 functionality. Mechanistically, O-Glycosylation, facilitated by O-Glycosyltransferase, emerged as pivotal in modulating STAT1 activity, as evident through immunoprecipitation and Western blot analysis. Pharmaceutical O-Glycosyltransferase inhibition prevented Th1 differentiation as well as STAT1 O-glycosylation. CRISPR/Cas9 mediated mutation of the O-glycosylation sites Ser499 and Thr510 sites diminished STAT1 Ser727 phosphorylation and IFN{gamma} synthesis. Together, this study highlights glycolysis as key regulator of human Th1 cell identity and effector function, with STAT1 O-Glycosylation selectively maintaining Th1 effector capacity. This mechanism could be explored to safeguard Th1 cells in antiviral immunity and autoimmunity. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/636644v1_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@1ee58aeorg.highwire.dtl.DTLVardef@1001af6org.highwire.dtl.DTLVardef@1ea2ed7org.highwire.dtl.DTLVardef@1a943fc_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2024

Benchmarking of T-Cell Receptor - Epitope Predictors with ePytope-TCR

Understanding the recognition of disease-derived epitopes through T-cell receptors (TCRs) has the potential to serve as a stepping stone for the development of efficient immunotherapies and vaccines. While a plethora of sequence-based prediction methods for TCR-epitope binding exists, their available pre-trained models have not been comparatively evaluated on standardized datasets and evaluation settings. Furthermore, technical problems such as non-standardized input and output formats of these prediction tools hinder interoperability and broad usage in applied research. To alleviate these shortcomings, we introduce ePytope-TCR, an extension of the vaccine design and immuno-prediction framework ePytope. We integrated 18 TCR-epitope prediction methods into this common framework offering interoperable interfaces with standard TCR repertoire data formats. We showcase the applicability of ePytope-TCR by evaluating the performance of the prediction methods on two challenging datasets for annotating single-cell repertoires and predicting TCR cross-reactivity towards mutated epitopes. While novel predictors successfully predicted binding to frequently observed epitopes, all methods failed for less observed epitopes. Further, we detected a strong bias in the prediction scores between different epitope classes. We envision this benchmark to guide researchers in their choice of a predictor for a given setting. Further, we aspire to accelerate the development of novel prediction models by allowing fast benchmarking against existing approaches through common interfaces and defining standardized evaluation settings.

bioinformatics↗

bioRxiv2024

Quality of vaccination-induced T cell responses is conveyed by polyclonality and high, but not maximum, antigen receptor avidity

While the quantity of vaccination-induced T cells represents a routine immunogenicity parameter, the quality of such responses is poorly understood. Here, we report on a clinical cohort of 29 human healthy individuals who received three mRNA vaccinations against SARS-CoV-2 before any breakthrough infection. We characterized the magnitude, phenotype and clonal composition of CD8 T cell responses against 16 epitope specificities by ELISpot, flow cytometry as well as single-cell RNA, TCR and surface protein sequencing. To test the functionality of identified clonotypes, 106 T cell receptors (TCR) from five epitope-specific repertoires were re-expressed and tested for peptide sensitivity. While recruited repertoires were overall enriched for high-avidity TCRs, differential clonal expansion was not linked to fine avidity differences. Instead, maintenance of polyclonality ensured robustness in counteracting mutational escape of epitopes. Our findings on the induction and maintenance of high-functionality polyclonal T cell repertoires shed light on T cell quality as a neglected criterion in the assessment of vaccine immunogenicity. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/620795v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@f48079org.highwire.dtl.DTLVardef@1eaa46org.highwire.dtl.DTLVardef@13cfb93org.highwire.dtl.DTLVardef@a8a6e5_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2024

Deconstructing CTL-mediated autoimmunity through weak TCR-cross-reactivity towards highly abundant self-antigen

T-cell antigen receptors (TCRs) exhibit inherent cross-reactivity which broadens the spectrum of epitopes that are recognizable by a finite TCR-repertoire but also carries the risk of autoimmunity. However, TCRs support also a high level of antigen specificity as they allow T-cells to discriminate single antigenic peptide/MHC complexes (pMHCs) against millions of structurally related self-pMHCs, in some cases based on the absence or presence of a single methyl-group. How TCRs manage to convey such seemingly contrary properties and why some T-cells become over time autoreactive despite negative thymic selection, has remained elusive. Here, we devised a non-invasive molecular live cell imaging platform to investigate the biophysical parameters governing stimulatory TCR:pMHC interactions in settings of autoreactivity and anti-viral responses - two extremes in T-cell antigen recognition. We show that CMV-specific CD8+ RA14-T-cells respond effectively to even a single HLA-A2/CMV (A2/CMV) antigen, with synaptic TCR:pMHC lifetimes lasting seconds. In contrast, cross-reactivity of type 1 diabetes (T1D)-associated CD8+ 1E6 T-cells towards HLA-A2/preproinsulin (A2/PPI) self-epitopes involved ten-fold less stable synaptic TCR interactions resulting in severely attenuated ZAP70 recruitment and downstream signaling. Compared to A2/CMV-engaged RA14 T-cells, 1E6-T-cells required for activation 4000 or more A2/PPI and at least 100-times as many simultaneously pMHC-engaged TCRs. In support of antigen discrimination, CD8 co-engagement of MHC class I (MHCI) strengthened both settings of TCR:pMHC interactions equally but was essential only for sensitized virus detection but not autorecognition (1000-versus 5-fold enhancement). We conclude that the binding dynamics of TCRs and CD8 with pMHC shape the boundaries of central tolerance in the physiological context of the phenomenal yet also differential T-cell antigen detection capacity, TCR-cross-reactivity and self-antigen abundance. Gained insights are integral to a molecular and quantitative understanding of CD8+ T-cell mediated autoimmunity and protective immunity against infections and cancer. ONE SENTENCE SUMMARYWith the use of newly devised molecular live-cell imaging modalities we measured with unprecedented precision T-cell antigen recognition dynamics in human T-cells in settings of anti-viral immunity and autoimmunity-causing cross-reactivity. These two extremes within the spectrum of T-cell antigen detection differed substantially with regard to synaptic TCR: antigen-engagement, the level of sensitization through the CD8-coreceptor and the overall efficiency of ensuing downstream signaling. Our results demarcate limits of central tolerance and protective immunity and set quantitative boundaries on the occurrence of autoimmunity with direct implications for T-cell-based designs of immunotherapies.

immunology↗

bioRxiv2023

DNA methylation profiling identifies TBKBP1 as potent amplifier of cytotoxic activity in CMV-specific human CD8+ T cells

Epigenetic mechanisms stabilize gene expression patterns during CD8+ T cell differentiation. However, although adoptive transfer of virus-specific T cells is clinically applied to reduce the risk of virus infection or reactivation in immunocompromised individuals, the DNA methylation pattern of virus-specific CD8+ T cells is largely unknown. Hence, we here performed whole-genome bisulfite sequencing of cytomegalovirus-specific human CD8+ T cells and found that they display a unique DNA methylation pattern consisting of 79 differentially methylated regions when compared to bulk memory CD8+ T cells. Among them was TBKBP1, coding for TBK-binding protein 1 that can interact with TANK-binding kinase 1 (TBK1) and mediate pro-inflammatory responses in innate immune cells downstream of intracellular virus sensing. Since TBKBP1 has not yet been reported in T cells, we aimed to unravel its role in virus-specific CD8+ T cells. TBKBP1 demethylation in terminal effector CD8+ T cells correlated with TBKBP1 expression and was stable upon long-term in vitro culture. TBKBP1 overexpression resulted in enhanced TBK1 phosphorylation upon stimulation of CD8+ T cells and significantly improved their virus neutralization capacity. Collectively, our data demonstrate that TBKBP1 modulates virus-specific CD8+ T cell responses and could be exploited as therapeutic target to improve adoptive T cell therapies.

immunology↗

bioRxiv2023

Miniaturized CAR knocked onto CD3epsilon extends TCR function with CAR specificity under control of endogenous TCR signaling cascade

Immunotherapy using TCR and especially CAR transgenic T cells is a rapidly advancing field with the potential to become standard of care for the treatment of multiple diseases. While all current FDA approved CAR T cell products are generated using lentiviral gene transfer, extensive work is put into CRISPR/Cas mediated gene delivery to develop the next generation of safer and more potent cell products. One limitation of all editing systems is the size restriction of the knock-in cargo. Targeted integration under control of an endogenous promotor and/or signaling cascades opens the possibility to reduce CAR gene size to absolute minimum. Here we demonstrate that a first-generation CAR payload can be reduced to its minimum component - the antigen-binding domain - by targeted integration under control of the CD3{varepsilon} promoter generating a CAR-CD3{varepsilon} fusion protein that exploits the endogenous TCR signaling cascade. Miniaturizing CAR payload in this way results in potent CAR activity while simultaneously retaining the primary antigen recognition function of the TCR. Introducing CAR-specificity using a CAR binder only while maintaining endogenous TCR function may be an appealing design for future autologous CAR T cell therapies.

bioengineering↗

bioRxiv2023

Predicting T Cell Receptor Functionality against Mutant Epitopes

Cancer cells or pathogens can escape recognition by T cell receptors (TCRs) through mutations of immunogenic epitopes. TCR cross-reactivity, i.e., recognition of multiple epitopes with sequence similarities, can be a factor to counteract such mutational escape. However, cross-reactivity of cell-based immunotherapies may also cause severe side effects when self-antigens are targeted. Therefore, the ability to predict the effect of mutations in the epitope sequence on T cell functionality in silico would greatly benefit the safety and effectiveness of newly-developed immunotherapies and vaccines. We here present "Predicting T cell Epitope-specific Activation against Mutant versions" (P-TEAM), a Random Forest-based model which predicts the effect of point mutations of an epitope on T cell functionality. We first trained and tested P-TEAM on a comprehensive dataset of 36 unique murine TCRs in response to systematic single-amino acid mutations of their target epitope (representing 5.472 unique TCR-epitope interactions). The model was able to classify T cell reactivities, corresponding to in vivo recruitment of T cells, and quantitatively predict T cell functionalities for unobserved single-point mutated altered peptide ligands (APLs), or even unseen TCRs, with consistently high performance. Further, we present an active learning framework to guide experimental design for assessing TCR functionality against novel epitopes, minimizing primary data acquisition costs. Finally, we applied P-TEAM to a novel dataset of 7 human TCRs reactive to the tumor neoantigen VPSVWRSSL. We observed a similarly robust performance for these human TCRs as for the murine TCRs recognizing SIINFEKL, thus providing evidence that our approach is applicable to therapeutically relevant TCRs as well as across species. Overall, P-TEAM provides an effective computational tool to study T cell responses against mutated epitopes.

bioinformatics↗

bioRxiv2023

TCR/CD3-based synthetic antigen receptors (TCC) convey superior antigen sensitivity combined with high fidelity of activation

Low antigen sensitivity and a gradual loss of effector functions limit the clinical applicability of chimeric antigen receptor (CAR)-modified T-cells and call for alternative antigen receptor designs for effective T-cell-based cancer immunotherapy. Here we applied advanced microscopy to demonstrate that TCR/CD3-based synthetic constructs (TCC) outperform second-generation CAR formats with regard to conveyed antigen sensitivities by up to a thousand-fold. TCC-based antigen recognition occurred without adverse non-specific signaling, which is typically observed in CAR-T-cells, and did not depend - unlike sensitized peptide/MHC detection by conventional T-cells - on CD4- or CD8- coreceptor engagement. TCC-endowed signaling properties may prove critical when targeting antigens in low abundance and aiming for a durable anti-cancer response.

immunology↗

bioRxiv2022

Activation-inducible CAR expression enables precise control over engineered CAR T cell function

CAR T cell therapy is a rapidly growing area of oncological treatments having a potential of becoming standard care for multiple indications. Coincidently, CRISPR/Cas gene-editing technology is entering next-generation CAR T cell product manufacturing with the promise of more precise and more controllable cell modification methodology. The intersection of these medical and molecular advancements creates an opportunity for completely new ways of designing engineered cells to help overcome current limitations of cell therapy. In this manuscript we present proof-of-concept data for a novel engineered feedback loop. We manufactured activation-inducible CAR T cells with the help of CRISPR-mediated targeted integration. This new type of engineered T cells expresses the CAR gene dependent on their activation status. This artifice opens new possibilities to regulate CAR T cell function both in vitro and in vivo. We believe that such a physiological control system can be a powerful addition to the currently available toolbox of next-generation CAR constructs.

immunology↗

bioRxiv2017

Systematic identification of cancer-specific MHC-binding peptides with RAVEN

Immunotherapy can revolutionize anti-cancer therapy if specific targets are available. Recurrent somatic mutations in the exome can create highly specific neo-antigens. However, especially pediatric cancers are oligo-mutated and hardly exhibit recurrent neo-antigens. Yet, immunogenic peptides encoded by cancer-specific genes (CSGs), which are virtually not expressed in normal tissues, may enable a targeted immunotherapy of such cancers. Here, we describe an algorithm and provide a user-friendly software named RAVEN (Rich Analysis of Variable gene Expressions in Numerous tissues), which automatizes the systematic and fast identification of CSG-encoded peptides highly affine to Major Histocompatibility Complexes (MHC) starting from publicly available gene expression data. We applied RAVEN to a dataset assembled from more than 2,700 simultaneously normalized gene expression microarrays comprising 50 tumor entities, with a focus on sarcomas and pediatric cancers, and 71 normal tissue types. RAVEN performed a transcriptome-wide scan in each cancer entity for gender-specific CSGs. As a proof-of-concept we identified several established CSGs, but also many novel candidates potentially suitable for targeting multiple cancer types. The specific expression of the most promising CSGs was validated by qRT-PCR in cancer cell lines and by immunohistochemistry in a comprehensive tissue-microarray comprising 412 samples. Subsequently, RAVEN identified likely immunogenic peptides encoded by these CSGs by predicting the affinity to MHCs. Putative highly affine peptides were automatically crosschecked with the UniProt protein-database to exclude sequence identity with abundantly expressed proteins. The predicted affinity of selected peptides was validated in T2-cell peptide-binding assays in which many showed similar kinetics to a very immunogenic influenza control peptide.\n\nCollectively, we provide a comprehensive, exquisitely curated and validated catalogue of cancer-specific and highly MHC-affine peptides across 50 cancer entities. In addition, we developed an intuitive and freely available software to easily apply our algorithm to any gene expression dataset (https://github.com/JSGerke/RAVENsoftware). We anticipate that our peptide libraries and software constitute a rich resource to accelerate the development of novel immunotherapies.

immunology↗