Biology subjects

Schuck, J.

Publications and source records attributed to Schuck, J..

3 recordsLinked to original sources

bioRxiv2026

Consistent consensus-based annotation of spatial adaptive immune receptor repertoires from long-read sequencing using LongAIRR

The combination of spatial transcriptomics with long-read sequencing enables spatial characterization of full-length transcripts within solid tissue sections. However, standardized computational analysis frameworks are lacking, and it remains unclear whether available long-read sequencing platforms from Oxford Nanopore Technologies and Pacific Biosciences yield comparable results. Here, we present a computational strategy for spatial full-length transcript analysis, focusing on the spatial profiling of adaptive immune receptor repertoires (AIRR). Our approach introduces an adaptive filtering strategy that dynamically refines read selection and significantly improves consensus accuracy, enabling high-confidence sequence reconstruction independent of platform-specific sequencing error profiles. We further derive evidence-based guidelines tailored to the consistent and robust analysis of spatial AIRR data. The resulting software LongAIRR is modular and interoperable with existing spatial transcriptomics and AIRR analysis frameworks. This work establishes a methodological foundation for spatial immunology, enabling precise mapping of immune repertoires within their native tissue microenvironments.

bioinformatics↗

bioRxiv2024

A comprehensive workflow for allele-specific immune gene quantification and expression analysis in single-cell RNA-seq data

MotivationImmune molecules such as B and T cell receptors, human leukocyte antigens (HLAs), or killer Ig-like receptors (KIRs) are encoded in the most genetically diverse loci of the human genome. Many of these immune genes exhibit remarkable allelic diversity across populations. While computational methods for HLA typing from bulk RNA sequencing data have emerged, streamlined solutions for allele-specific quantification in single-cell RNA sequencing (scRNA-seq) are lacking. Moreover, no standardized data structure or analytical framework has been established to handle allele-specific immune gene expression data at single-cell level. ResultsWe present a comprehensive workflow to (1) automate allele-typing and allele-specific expression quantification of HLA transcripts in scRNA-seq data using a Snakemake workflow, scIGD (single-cell ImmunoGenomic Diversity), and (2) represent and interactively explore immune gene expression at different annotation levels using a multi-layer data structure implemented as an R/Bioconductor software package, SingleCellAlleleExperiment. We validated our approach on a diverse spectrum of scRNA-seq datasets, and found that it performs consistently across different sequencing platforms and experimental setups. We illustrate how our method can be utilized to study loss of HLA expression in tumor cells or discover differential HLA allele expression in specific immune cell subtypes. By capturing such allele-specific expression patterns and their variation, our workflow offers novel insights into human immunogenomic diversity. Availability and implementationscIGD is available under the MIT license at: https://github.com/AGImkeller/scIGD. SingleCellAlleleExperiment is available under the MIT license at: https://bioconductor.org/packages/SingleCellAlleleExperiment. scaeData provides validation datasets and is available under the MIT license at: https://bioconductor.org/packages/scaeData. Data processed with scIGD are available at: https://doi.org/10.5281/zenodo.14033960. ContactKatharina Imkeller. E-mail: imkeller@rz.uni-frankfurt.de. Supplementary informationSupplementary data are available within the same submission.

bioinformatics↗

bioRxiv2024

Modulation of the ATP-adenosine signaling axis combined with radiotherapy facilitates anti-cancer immunity in brain metastasis

The immunosuppressive microenvironment in the brain poses a major limitation to successful therapy for brain metastases. Here we report that blockade of the ATP-to-adenosine-converting enzymes CD39 and CD73 and the adenosine receptor A2AR in combination with radiotherapy attenuates tumor progression in a breast-to-brain metastasis model by facilitating anti-cancer immunity. Immunophenotyping revealed loss of exhausted T cells and higher abundance of anti-cancer effector T cell populations. This effect was accompanied by a decrease of immunosuppressive lipid-laden macrophages and an expansion of CD14CD33high macrophages associated with antigen presentation. Analyses of human brain metastases samples supports a role of the ATP-adenosine signaling axis in modulating tumor inflammation and identified expression of CD39 and adenosine deaminase as predictive markers for patient survival and/or immune infiltration. Our findings demonstrate that the adenosine axis represents a druggable pathway to achieve local immunomodulation and treatment response, opening a new therapeutic avenue for brain metastases patients.

cancer biology↗