Publications by authors named "D Hamelin"
Next-generation T-cell-directed vaccines for COVID-19 focus on establishing lasting T-cell immunity against current and emerging SARS-CoV-2 variants. Precise identification of conserved T-cell epitopes is critical for designing effective vaccines. Here we introduce a comprehensive computational framework incorporating a machine learning algorithm-MHCvalidator-to enhance mass spectrometry-based immunopeptidomics sensitivity.
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- * A set of genomic surveillance tools based on population genetics has been developed to analyze the virus's genetic diversity, utilizing data from 329,854 sequences in the GISAID database from the early pandemic phase.
- * Innovative methods like haplotype networks and principal component analysis (PCA) allow for efficient lineage identification and visualization of mutation patterns, aiding in real-time monitoring and understanding of SARS-CoV-2 evolution.
Article Synopsis
- - The study analyzes the MHC-I immunopeptidome from multiple human and mouse tissues, revealing that different HLA allotypes influence its composition differently across tissues.
- - It distinguishes between tissue-specific MHC-I peptides and those that are more universally expressed, highlighting their unique characteristics.
- - The research identifies evolutionarily conserved proteins as key contributors to the MHC-I immunopeptidome and introduces new components involved in antigen processing, enhancing our understanding of antigen presentation across mammals.
Developing a deep and comprehensive understanding of the collection of peptides presented by class I human leukocyte antigens (HLA ), collectively referred to as the immunopeptidome , is conducive to the success of a wide range of immunotherapies. The development of tools that enable the deconvolution of immunopeptidomes in the context of disease can help improve the specificity and effectiveness of therapeutic strategies targeting these peptides, such as adoptive T-cell therapy and vaccines. Here, we describe a computational workflow that facilitates the processing and interpretation of data-independent acquisition mass spectrometry (DIA-MS).
View Article and Find Full Text PDFMS-based immunopeptidomics is maturing into an automatized and high-throughput technology, producing small- to large-scale datasets of clinically relevant major histocompatibility complex (MHC) class I-associated and class II-associated peptides. Consequently, the development of quality control (QC) and quality assurance systems capable of detecting sample and/or measurement issues is important for instrument operators and scientists in charge of downstream data interpretation. Here, we created MhcVizPipe (MVP), a semiautomated QC software tool that enables rapid and simultaneous assessment of multiple MHC class I and II immunopeptidomic datasets generated by MS, including datasets generated from large sample cohorts.
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