Dataset Information

Proteome of naive and TCR activated wild-type, Myc-deficient and Slc7a5-deficient T cells

ABSTRACT: T cell clonal expansion and differentiation are critically dependent on the transcription factor c-Myc (Myc). Herein we use quantitative mass-spectrometry to reveal how Myc controls antigen receptor driven cell growth and proteome restructuring in CD4+ and CD8+ T cells. Quantitative proteomics was performed on naive wild-type (WT) and 24 hr T cell receptor (TCR) activated Myc WT and Myc-deficient T cells. Analysis of copy numbers per cell of >7000 proteins provides new understanding of the selective role of Myc in controlling the protein machinery that shapes T cell fate. The data identify both Myc dependent and independent metabolic processes in immune activated T cells. We uncover that a primary function of Myc is to induce amino acid transporter expression. Quantitative proteomics of 24 hr TCR activated Slc7a5 WT and Slc7a5-deficient CD4 T cells reveals that loss of a single Myc-controlled amino transporter, Slc7a5, can effectively phenocopy the impact of Myc deletion. This study thus provides a comprehensive map of how Myc selectively shapes T cell phenotypes and reveals that Myc induction of amino acid transport is pivotal for subsequent bioenergetic and biosynthetic programs.

INSTRUMENT(S): LTQ Orbitrap Velos, Q Exactive

ORGANISM(S): Mus Musculus (mouse)

TISSUE(S): T Cell, Lymph Node

SUBMITTER: Julia Marchingo

LAB HEAD: Doreen Ann Cantrell

PROVIDER: PXD016105 | Pride | 2020-02-25

REPOSITORIES: Pride

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Quantitative analysis of how Myc controls T cell proteomes and metabolic pathways during T cell activation.

Marchingo Julia M JM Sinclair Linda V LV Howden Andrew Jm AJ Cantrell Doreen A DA

eLife 20200205

T cell expansion and differentiation are critically dependent on the transcription factor c-Myc (Myc). Herein we use quantitative mass-spectrometry to reveal how Myc controls antigen receptor driven cell growth and proteome restructuring in murine T cells. Analysis of copy numbers per cell of >7000 proteins provides new understanding of the selective role of Myc in controlling the protein machinery that govern T cell fate. The data identify both Myc dependent and independent metabolic processes ...[more]

PMID: 32022686

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Project description:A recently identified unconventional T cell population known as mucosal-associated invariant T (MAIT) cells are characterized by the expression of semi-invariant T cell receptor (TCR) with a canonical TRAV1-2/TRAJ33 (Vα7.2/Jα33). These evolutionary conserved, innate-like T cells recognize vitamin B metabolites, derived from some bacteria and fungi. Due to their presence not only in the T cell repertoire of mucosal surfaces but also in peripheral blood and liver, and their significant involvement in a wide range of diseases, in-depth characterization of human MAIT cells is a timely requirement. Studies that examined the transcriptome, immunoproteome, and whole-cell proteome characterized the role of cytotoxic molecules and cytokines in effector functions of MAIT cells and their relationship with some other immune cell subsets. As MAIT cells are classified under the CD3+ T cell compartment and the majority express surface receptor CD8, identifying their proteomic relationship with CD3+ and CD8+ T cells is pivotal. Thus, a high-resolution dataset was generated using the cell populations sorted from peripheral blood mononuclear cells of three healthy volunteers to describe the whole cell proteomes of MAIT, CD3+, and CD8+ T cells. Trypsin-digested peptide samples obtained from the methanol co-precipitation method were analyzed using an Orbitrap FusionTM TribridTM mass spectrometer (Thermo Fisher Scientific, USA) inline coupled to nanoACQUITY ultra-performance liquid chromatography system (Waters, USA) to acquire data-dependent shotgun proteomic data (DDA-MS) for label-free quantification. Analysis of raw DDA-MS data using MaxQuant software and maxLFQ identified and quantified 4,442 protein groups at a 1% false discovery rate. Further analysis identified 3,680 proteins which were detected with a single UniProt accession and a minimum of 2 unique or razor peptides. Thus this proteomic dataset can be used as a reference proteome for future studies on human MAIT cells.

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