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The MHC class I peptide repertoire is molded by the transcriptome.

ABSTRACT: Under steady-state conditions, major histocompatibility complex (MHC) I molecules are associated with self-peptides that are collectively referred to as the MHC class I peptide (MIP) repertoire. Very little is known about the genesis and molecular composition of the MIP repertoire. We developed a novel high-throughput mass spectrometry approach that yields an accurate definition of the nature and relative abundance of unlabeled peptides presented by MHC I molecules. We identified 189 and 196 MHC I-associated peptides from normal and neoplastic mouse thymocytes, respectively. By integrating our peptidomic data with global profiling of the transcriptome, we reached two conclusions. The MIP repertoire of primary mouse thymocytes is biased toward peptides derived from highly abundant transcripts and is enriched in peptides derived from cyclins/cyclin-dependent kinases and helicases. Furthermore, we found that approximately 25% of MHC I-associated peptides were differentially expressed on normal versus neoplastic thymocytes. Approximately half of those peptides are derived from molecules directly implicated in neoplastic transformation (e.g., components of the PI3K-AKT-mTOR pathway). In most cases, overexpression of MHC I peptides on cancer cells entailed posttranscriptional mechanisms. Our results show that high-throughput analysis and sequencing of MHC I-associated peptides yields unique insights into the genesis of the MIP repertoire in normal and neoplastic cells.

SUBMITTER: Fortier MH

PROVIDER: S-EPMC2275383 | biostudies-literature | 2008 Mar

REPOSITORIES: biostudies-literature

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The MHC class I peptide repertoire is molded by the transcriptome.

Fortier Marie-Hélène MH Caron Etienne E Hardy Marie-Pierre MP Voisin Grégory G Lemieux Sébastien S Perreault Claude C Thibault Pierre P

The Journal of experimental medicine 20080225 3

Under steady-state conditions, major histocompatibility complex (MHC) I molecules are associated with self-peptides that are collectively referred to as the MHC class I peptide (MIP) repertoire. Very little is known about the genesis and molecular composition of the MIP repertoire. We developed a novel high-throughput mass spectrometry approach that yields an accurate definition of the nature and relative abundance of unlabeled peptides presented by MHC I molecules. We identified 189 and 196 MHC ...[more]

PMID: 18299400

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Project description:Major Histocompatibility Complex (MHC) class I molecules enable cytotoxic T lymphocytes to destroy virus-infected or cancerous cells, thereby preventing disease progression. MHC class I molecules provide a snapshot of the contents of a cell by binding to protein fragments arising from intracellular protein turnover and presenting these fragments at the cell surface. Competing fragments (peptides) are selected for cell-surface presentation on the basis of their ability to form a stable complex with MHC class I, by a process known as peptide optimization. A better understanding of the optimization process is important for our understanding of immunodominance, the predominance of some T lymphocyte specificities over others, which can determine the efficacy of an immune response, the danger of immune evasion, and the success of vaccination strategies. In this paper we present a dynamical systems model of peptide optimization by MHC class I. We incorporate the chaperone molecule tapasin, which has been shown to enhance peptide optimization to different extents for different MHC class I alleles. Using a combination of published and novel experimental data to parameterize the model, we arrive at a relation of peptide filtering, which quantifies peptide optimization as a function of peptide supply and peptide unbinding rates. From this relation, we find that tapasin enhances peptide unbinding to improve peptide optimization without significantly delaying the transit of MHC to the cell surface, and differences in peptide optimization across MHC class I alleles can be explained by allele-specific differences in peptide binding. Importantly, our filtering relation may be used to dynamically predict the cell surface abundance of any number of competing peptides by MHC class I alleles, providing a quantitative basis to investigate viral infection or disease at the cellular level. We exemplify this by simulating optimization of the distribution of peptides derived from Human Immunodeficiency Virus Gag-Pol polyprotein.

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The MHC class I peptide repertoire is molded by the transcriptome.

Publications

The MHC class I peptide repertoire is molded by the transcriptome.

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