Publications by authors named "Sebastiaan Valkiers"
Single-cell techniques allow concurrent study of gene activity and T cell receptor (TCR) sequences, identifying connections between TCR structure and cell traits. Expanding on our CoNGA software, we present a "metaCoNGA" analysis of 6 million T cells from 91 diverse studies, mapping TCR sequence similarity across tissues and diseases. This approach exposes shared TCR features within specific T cell subsets, including those associated with infection, cancer, and autoimmunity.
View Article and Find Full Text PDFArticle Synopsis
- T cells and their receptors (TCRs) are essential for understanding immune responses but are often overlooked in single-cell analysis, which typically focuses on gene expression.
- The authors created a comprehensive T cell atlas from 12 major studies, involving 500,000 T cells across various diseases, and found challenges in accurately labeling cell types using standard methods.
- They propose a TCR-first approach, using a semi-supervised method, to better identify T cell characteristics and dynamics, potentially enhancing immunotherapy and diagnostic strategies.
The role of T cell receptor (TCR) diversity in infectious disease susceptibility is not well understood. We use a systems immunology approach on three cohorts of herpes zoster (HZ) patients and controls to investigate whether TCR diversity against varicella-zoster virus (VZV) influences the risk of HZ. We show that CD4 T cell TCR diversity against VZV glycoprotein E (gE) and immediate early 63 protein (IE63) after 1-week culture is more restricted in HZ patients.
View Article and Find Full Text PDFCurrent annotation strategies for T cell phenotyping of single-cell RNA-seq data.
Front Immunol
January 2024
Article Synopsis
- Single-cell RNA sequencing (scRNA-seq) is a powerful technique for analyzing gene expression diversity in cells, particularly useful for studying complex cell populations like T cells.
- Unlike bulk RNA sequencing, scRNA-seq can identify specific subtypes within these populations and recently enables simultaneous analysis of T-cell receptor (TCR) sequences alongside gene expression.
- However, the analysis of scRNA-seq data faces challenges due to the lack of reliable methods for accurately annotating T-cell subtypes, as existing tools struggle to differentiate between the various T-cell populations effectively.
Article Synopsis
- The diversity of T cell receptors (TCRs) plays a key role in the immune response against various pathogens and is vital for the adaptive immune system.
- When T cells encounter infections, they activate to fight these intruders, making the TCR repertoire a valuable source of information about past and current infections as well as vaccine responses.
- The study utilizes machine learning techniques to analyze TCR data, specifically focusing on a yellow fever virus vaccination study, to identify specific TCRs that respond to the virus before and after vaccination.
Article Synopsis
- Scientists created a new tool called ClusTCR to help group T-cell receptors (TCRs) more quickly and efficiently, even when there are millions of them.
- ClusTCR works really fast and is as accurate as other methods, helping researchers understand how T-cells recognize different parts of viruses or bacteria.
- You can get ClusTCR for free online, and it works with Python, making it easy for scientists to use in their studies.