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Saab, F.

Publications and source records attributed to Saab, F..

3 recordsLinked to original sources

Distinct colorectal cancer genotypes shape microbial ecosystems and reveal stage-specific microbiota dependencies

The gut microbiota has emerged as an important modifier of colorectal cancer (CRC), yet how tumor genotype influences host-microbiota interactions and whether microbial signals are required throughout tumor progression remain unclear. Here, we combined genetically engineered mouse models, microbial multi-omics and a germ-free-compatible orthotopic transplantation system to define the functional contribution of the microbiota across distinct stages of CRC evolution. Across multiple CRC genotypes, we identified tumor-associated microbial ecosystem states characterized by distinct taxonomic, functional and metabolic configurations. To directly test their contribution to tumor progression, we established the first orthotopic CRC transplantation platform compatible with long-term experimentation in germ-free mice, enabling side-by-side comparison of genetically identical tumors in the presence or absence of microbiota. Using organoids spanning low-grade adenoma, high-grade adenoma and adenocarcinoma states, we found that the dependence on the presence of microbiota progressively decreases during malignant evolution. Whereas adenoma-derived organoids exhibited profound dependence on microbial exposure and failed or were markedly impaired in establishing tumors under germ-free conditions, adenocarcinoma organoids engrafted and metastasized in both germ-free and specific pathogen-free (SPF) hosts. Unexpectedly, comprehensive histological, immunological and transcriptomic analyses revealed highly similar tumor ecosystem states in advanced tumors arising under both microbial conditions, arguing against broad immune or epithelial defects as a primary explanation for the observed phenotype. Together, our findings demonstrate that distinct oncogenic drivers establish specific microbial ecosystem states and reveal a stage-dependent role of the microbiota during colorectal tumorigenesis. Whereas microbial signals are critical during early stages of tumor progression and may promote malignant transformation, advanced tumors progressively acquire microbiota-independent growth programs and increasingly impose genotype-specific ecological signatures on the surrounding microbial ecosystem. More broadly, we establish a versatile framework for the causal dissection of tumor-microbiota interactions in cancer.

cancer biology↗

The mutational landscape of SARS-CoV-2 variants diversifies T cell targets in an HLA supertype-dependent manner

The rapid, global dispersion of SARS-CoV-2 since its initial identification in December 2019 has led to the emergence of a diverse range of variants. The initial concerns regarding the virus were quickly compounded with concerns relating to the impact of its mutated forms on viral infectivity, pathogenicity and immunogenicity. To address the latter, we seek to understand how the mutational landscape of SARS-CoV-2 has shaped HLA-restricted T cell immunity at the population level during the first year of the pandemic, before mass vaccination. We analyzed a total of 330,246 high quality SARS-CoV-2 genome assemblies sampled across 143 countries and all major continents. Strikingly, we found that specific mutational patterns in SARS-CoV-2 diversify T cell epitopes in an HLA supertype-dependent manner. In fact, we observed that proline residues are preferentially removed from the proteome of prevalent mutants, leading to a predicted global loss of SARS-CoV-2 T cell epitopes in individuals expressing HLA-B alleles of the B7 supertype family. In addition, we show that this predicted global loss of epitopes is largely driven by a dominant C-to-U mutation type at the RNA level. These results indicate that B7 supertype-associated epitopes, including the most immunodominant ones, were more likely to escape CD8+ T cell immunosurveillance during the first year of the pandemic. Together, our study lays the foundation to help understand how SARS-CoV-2 mutants shape the repertoire of T cell targets and T cell immunity across human populations. The proposed theoretical framework has implications in viral evolution, disease severity, vaccine resistance and herd immunity.

immunology↗

Immunopeptidomics for Dummies: Detailed Experimental Protocols and Rapid, User-Friendly Visualization of MHC I and II Ligand Datasets with MhcVizPipe

Immunopeptidomics refers to the science of investigating the composition and dynamics of peptides presented by major histocompatibility complex (MHC) class I and class II molecules using mass spectrometry (MS). Here, we aim to provide a technical report to any non-expert in the field wishing to establish and/or optimize an immunopeptidomic workflow with relatively limited computational knowledge and resources. To this end, we thoroughly describe step-by-step instructions to isolate MHC class I and II-associated peptides from various biological sources, including mouse and human biospecimens. Most notably, we created MhcVizPipe (MVP) (https://github.com/CaronLab/MhcVizPipe), a new and easy-to-use open-source software tool to rapidly assess the quality and the specific enrichment of immunopeptidomic datasets upon the establishment of new workflows. In fact, MVP enables intuitive visualization of multiple immunopeptidomic datasets upon testing sample preparation protocols and new antibodies for the isolation of MHC class I and II peptides. In addition, MVP enables the identification of unexpected binding motifs and facilitates the analysis of non-canonical MHC peptides. We anticipate that the experimental and bioinformatic resources provided herein will represent a great starting point for any non-expert and will therefore foster the accessibility and expansion of the field to ultimately boost its maturity and impact.

bioinformatics↗