Misclassified: identification of zoonotic transition biomarker candidates for influenza A viruses using deep neural network.

Zoonotic transition of Influenza A viruses is the cause of epidemics with high rates of morbidity and mortality. Predicting which viral strains are likely to transition from their genetic sequence could help in the prevention and response against these zoonotic strains. We hypothesized that features predictive of viral hosts could be leveraged to identify biomarkers of zoonotic viral transition.

CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation.

MHC-I associated peptides (MAPs) play a central role in the elimination of virus-infected and neoplastic cells by CD8 T cells. However, accurately predicting the MAP repertoire remains difficult, because only a fraction of the transcriptome generates MAPs. In this study, we investigated whether codon arrangement (usage and placement) regulates MAP biogenesis.

MAPDP: A Cloud-Based Computational Platform for Immunopeptidomics Analyses.

The immunopeptidome corresponds to the repertoire of peptides presented at the cell surface by the major histocompatibility complex (MHC) molecules. Cytotoxic T cells scan this repertoire to identify nonself antigens that can arise from tumors or infected cells. The identification of actionable antigenic targets is key to the development of therapeutic cancer vaccines, T-cell therapy, and other T-cell receptor-based biologics.

Qualitative Changes in Cortical Thymic Epithelial Cells Drive Postpartum Thymic Regeneration.

During gestation, sex hormones cause a significant thymic involution which enhances fertility. This thymic involution is rapidly corrected following parturition. As thymic epithelial cells (TECs) are responsible for the regulation of thymopoiesis, we analyzed the sequential phenotypic and transcriptomic changes in TECs during the postpartum period in order to identify mechanisms triggering postpartum thymic regeneration.

MHC class I-associated peptides derive from selective regions of the human genome.

MHC class I-associated peptides (MAPs) define the immune self for CD8+ T lymphocytes and are key targets of cancer immunosurveillance. Here, the goals of our work were to determine whether the entire set of protein-coding genes could generate MAPs and whether specific features influence the ability of discrete genes to generate MAPs. Using proteogenomics, we have identified 25,270 MAPs isolated from the B lymphocytes of 18 individuals who collectively expressed 27 high-frequency HLA-A,B allotypes.

pyGeno: A Python package for precision medicine and proteogenomics.

pyGeno is a Python package mainly intended for precision medicine applications that revolve around genomics and proteomics. It integrates reference sequences and annotations from Ensembl, genomic polymorphisms from the dbSNP database and data from next-gen sequencing into an easy to use, memory-efficient and fast framework, therefore allowing the user to easily explore subject-specific genomes and proteomes. Compared to a standalone program, pyGeno gives the user access to the complete expressivity of Python, a general programming language.

Global proteogenomic analysis of human MHC class I-associated peptides derived from non-canonical reading frames.

In view of recent reports documenting pervasive translation outside of canonical protein-coding sequences, we wished to determine the proportion of major histocompatibility complex (MHC) class I-associated peptides (MAPs) derived from non-canonical reading frames. Here we perform proteogenomic analyses of MAPs eluted from human B cells using high-throughput mass spectrometry to probe the six-frame translation of the B-cell transcriptome. We report that ∼ 10% of MAPs originate from allegedly noncoding genomic sequences or exonic out-of-frame translation.

Impact of genomic polymorphisms on the repertoire of human MHC class I-associated peptides.

For decades, the global impact of genomic polymorphisms on the repertoire of peptides presented by major histocompatibility complex (MHC) has remained a matter of speculation. Here we present a novel approach that enables high-throughput discovery of polymorphic MHC class I-associated peptides (MIPs), which play a major role in allorecognition. On the basis of comprehensive analyses of the genomic landscape of MIPs eluted from B lymphoblasts of two MHC-identical siblings, we show that 0.

MHC I-associated peptides preferentially derive from transcripts bearing miRNA response elements.

MHC I-associated peptides (MIPs) play an essential role in normal homeostasis and diverse pathologic conditions. MIPs derive mainly from defective ribosomal products (DRiPs), a subset of nascent proteins that fail to achieve a proper conformation and the physical nature of which remains elusive. In the present study, we used high-throughput proteomic and transcriptomic methods to unravel the structure and biogenesis of MIPs presented by HLA-A and HLA-B molecules on human EBV-infected B lymphocytes from 4 patients.