Biology subjects

Bacher, P.

Publications and source records attributed to Bacher, P..

6 recordsLinked to original sources

bioRxiv2025

Mapping adaptive immune responses toward fungal antigens in inflammatory bowel disease using T cell repertoire sequencing and phage-immunoprecipitation sequencing

Inflammatory bowel disease (IBD) is an idiopathic, immune-mediated chronic inflammatory disease of the gut with two primary clinical forms, Crohns disease (CD) and ulcerative colitis (UC). Several genetic susceptibility variants have been associated with IBD, such as ATG16L, NOD2, and several human leukocyte antigen (HLA) alleles, nonetheless, the actual disease causes remain unknown. Whereas previous findings have shown elevated responses toward fungal antigens in individuals with IBD, e.g., elevated anti-Saccharomyces cerevisiae antibody (ASCA) levels, an exhaustive mapping of immune responses toward fungal antigens remains incomplete. Thus, we analyzed the fungal mycobiome profiled using internal transcribed spacer 2 (ITS2)-sequencing simultaneously with the T cell repertoire of 637 individuals with IBD from the SPARC IBD cohort, which enabled us to identify 31 T cell clonotypes targeting several prevalent members of the gut mycobiome. Subsequently, we developed a novel phage-immunoprecipitation sequencing (PhIP-Seq) library covering 12,000 potential antigens from the proteome of S. cerevisiae and screened for antibody responses in 100 individuals with CD and 60 healthy controls with known ASCA status, enabling us to identify public and private antibody responses against several S. cerevisiae proteins. In conclusion, we corroborated previous findings showing elevated T cell responses against fungal antigens in individuals with IBD and identified multiple antigenic proteins from the proteome of S. cerevisiae that are targeted by the immune system of individuals with and without CD.

immunology↗

bioRxiv2024

Competitive fungal commensalism mitigates candidiasis pathology

The mycobiota are a critical part of the gut microbiome, but host-fungal interactions and specific functional contributions of commensal fungi to host fitness remain incompletely understood. Here we report the identification of a new fungal commensal, Kazachstania heterogenica var. weizmannii, isolated from murine intestines. K. weizmannii exposure prevented Candida albicans colonization and significantly reduced the commensal C. albicans burden in colonized animals. Following immunosuppression of C. albicans colonized mice, competitive fungal commensalism thereby mitigated fatal candidiasis. Metagenome analysis revealed K. weizmannii presence among human commensals. Our results reveal competitive fungal commensalism within the intestinal microbiota, independent of bacteria and immune responses, that could bear potential therapeutic value for the management of C. albicans-mediated diseases.

immunology↗

bioRxiv2022

Predicting Peptide HLA-II Presentation Using Immunopeptidomics, Transcriptomics and Deep Multimodal Learning

The human leukocyte antigen (HLA) class II proteins present peptides to CD4+ T cells through an interaction with T cell receptors (TCRs). Thus, HLA proteins are key players in shaping immunogenicity and immunodominance. Nevertheless, factors governing peptide presentation by HLA-II proteins are still poorly understood. To address this problem, we profiled the blood transcriptome and immunopeptidome of 20 healthy individuals and integrated the profiles with publicly available immunopeptidomics datasets. In depth multi-omics analysis identified expression levels and subcellular locations as import sequence-independent features governing presentation. Levering this knowledge, we developed the Peptide Immune Annotator Multimodal (PIA-M) tool, as a novel pan multimodal transformer-based framework that utilises sequence-dependent along with sequence-independent features to model presentation by HLA-II proteins. PIA-M illustrated a consistently superior performance relative to existing tools across two independent test datasets (area under the curve: 0.93 vs. 0.84 and 0.95 vs. 0.86), respectively. Besides achieving a higher predictive accuracy, PIA-M with its Rust-based pre-processing engine, had significantly shorter runtimes. PIA-M is freely available with a permissive licence as a standalone pipeline and as a webserver (https://hybridcomputing.ikmb.uni-kiel.de/pia). In conclusion, PIA-M enables a new state-of-the-art accuracy in predicting peptide presentation by HLA-II proteins in vivo.

bioinformatics↗

bioRxiv2021

Characterization of SARS-CoV-2 public CD4+ αβ T cell clonotypes through reverse epitope discovery

The amount of scientific data and level of public sharing produced as a consequence of the COVID-19 pandemic, as well as the speed at which these data were produced, far exceeds any previous effort against a specific disease condition. This unprecedented situation allows for development and application of new research approaches. One of the major technical hurdles in immunology is the characterization of HLA-antigen-T cell receptor (TCR) specificities. Most approaches aim to identify reactive T cells starting from known antigens using functional assays. However, the need for a reverse approach identifying the antigen specificity of orphan TCRs is increasing. Utilizing large public single-cell gene expression and TCR datasets, we identified highly public CD4+ T cell responses to SARS-CoV-2, covering >75% of the analysed population. We performed an integrative meta-analysis to deeply characterize these clonotypes by TCR sequence, gene expression, HLA-restriction, and antigen-specificity, identifying strong and public CD4+ immunodominant responses with confirmed specificity. CD4+ COVID-enriched clonotypes show T follicular helper functional features, while clonotypes depleted in SARS-CoV-2 individuals preferentially had a central memory phenotype. In total we identify more than 1200 highly public CD4+ T cell clonotypes reactive to SARS-CoV-2. TCR similarity analysis showed six prominent TCR clusters, for which we predicted both HLA-restriction and cognate SARS-CoV-2 immunodominant epitopes. To validate our predictions we used an independent cohort of TCR repertoires before and after vaccination with ChAdOx1, a replication-deficient simian adenovirus-vectored vaccine, encoding the SARS-CoV-2 spike protein. We find statistically significant enrichment of the predicted spike-reactive TCRs after vaccination with ChAdOx1, while the frequency of TCRs specific to other SARS-CoV-2 proteins remains stable. Thus, the CD4-associated TCR repertoire differentiates vaccination from natural infection. In conclusion, our study presents a novel reverse epitope discovery approach that can be used to infer HLA- and antigen-specificity of orphan TCRs in any context, such as viral infections, antitumor immune responses, or autoimmune disease. HighlightsO_LIIdentification of highly public CD4+ T cell responses to SARS-CoV-2 C_LIO_LISystematic prediction of exact immunogenic HLA class II epitopes for CD4+ T cell response C_LIO_LIMethodological framework for reverse epitope discovery, which can be applied to other disease contexts and may provide essential insights for future studies and clinical applications C_LI O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

immunology↗

bioRxiv2020

Rapid T cell receptor interaction grouping with ting

MotivationClustering of antigen-specific T cell receptor repertoire (TCRR) sequences is challenging. The recently published tool GLIPH aims to solve this problem. However, clustering large repertoires takes several days to weeks, making its use impractical in larger studies. In addition, the methodology used in GLIPH suffers from several shortcomings, including non-determinism, potential loss of significant antigen-specific sequences or inclusion of too many unspecific sequences. ResultsWe present an algorithm for clustering TCRR sequences that scales efficiently to large repertoires. We clustered 26 real datasets with up to 62 000 unique CDR3{beta} sequences using both GLIPH and an implementation of our method called ting. While GLIPH required multiple weeks, ting only needed about one hour for the same task. In addition, we found that in naive repertoires, where no or very few antigen-specific CDR3 sequences or clusters should exist, our method indeed selects fewer sequences. AvailabilityOur method has been implemented in Python as a tool called ting, using numpy and NetworkX. It is available on GitHub (https://github.com/FelixMoelder/ting) and on PyPI under the MIT license. Contactfelix.moelder@uni-due.de or sven.rahmann@uni-due.de

bioinformatics↗

bioRxiv2019

Comprehensive analysis of antiviral adaptive immunity formation and reactivation down to single-cell level

The diverse repertoire of T-cell receptors (TCR) plays a key role in the adaptive immune response to infections. Previous studies show that secondary responses to the yellow fever vaccine -- the model for acute infection in humans -- are weaker than primary ones, but only quantitative measurements can describe the concentration changes and lineage fates for distinct T-cell clones in vivo over time. Using TCR alpha and beta repertoire sequencing for T-cell subsets, as well as single-cell RNAseq and TCRseq, we track the concentrations and phenotypes of individual T-cell clones in response to primary and secondary yellow fever immunization showing their large diversity. We confirm the secondary response is an order of magnitude weaker, albeit 10 days faster than the primary one. Estimating the fraction of the T-cell response directed against the single immunodominant epitope, we identify the sequence features of TCRs that define the high precursor frequency of the two major TCR motifs specific for this particular epitope. We also show the consistency of clonal expansion dynamics between bulk alpha and beta repertoires, using a new methodology to reconstruct alpha-beta pairings from clonal trajectories.

immunology↗