1,2,3, MHC: a review of mass-spectrometry-based immunopeptidomics methods for relative and absolute quantification of pMHCs

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Quantitative mass-spectrometry-based methods to perform relative and absolute quantification of peptides in the immunopeptidome are growing in popularity as researchers aim to measure the dynamic nature of the peptide major histocompatibility complex repertoire and make copies-per-cell estimations of target antigens of interest. Multiple methods to carry out these experiments have been reported, each with unique advantages and limitations. This article describes existing methods and recent applications, offering guidance for improving quantitative accuracy and selecting an appropriate experimental set-up to maximize data quality and quantity.

Highlights

•

Existing methods for quantitative immunopeptidomic analysis are described.
•

Guidance to improve quantitative accuracy is offered.
•

Experimental design guidance is provided to maximize data quality and quantity.

Related collections

Most cited references 53

Record: found
Abstract: found
Article: not found

Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics.

Shao-En Ong, Blagoy Blagoev, Irina Kratchmarova … (2002)

Quantitative proteomics has traditionally been performed by two-dimensional gel electrophoresis, but recently, mass spectrometric methods based on stable isotope quantitation have shown great promise for the simultaneous and automated identification and quantitation of complex protein mixtures. Here we describe a method, termed SILAC, for stable isotope labeling by amino acids in cell culture, for the in vivo incorporation of specific amino acids into all mammalian proteins. Mammalian cell lines are grown in media lacking a standard essential amino acid but supplemented with a non-radioactive, isotopically labeled form of that amino acid, in this case deuterated leucine (Leu-d3). We find that growth of cells maintained in these media is no different from growth in normal media as evidenced by cell morphology, doubling time, and ability to differentiate. Complete incorporation of Leu-d3 occurred after five doublings in the cell lines and proteins studied. Protein populations from experimental and control samples are mixed directly after harvesting, and mass spectrometric identification is straightforward as every leucine-containing peptide incorporates either all normal leucine or all Leu-d3. We have applied this technique to the relative quantitation of changes in protein expression during the process of muscle cell differentiation. Proteins that were found to be up-regulated during this process include glyceraldehyde-3-phosphate dehydrogenase, fibronectin, and pyruvate kinase M2. SILAC is a simple, inexpensive, and accurate procedure that can be used as a quantitative proteomic approach in any cell culture system.

0 comments Cited 1047 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Skyline: an open source document editor for creating and analyzing targeted proteomics experiments.

Brendan Maclean, Daniela Tomazela, Nicholas Shulman … (2010)

Skyline is a Windows client application for targeted proteomics method creation and quantitative data analysis. It is open source and freely available for academic and commercial use. The Skyline user interface simplifies the development of mass spectrometer methods and the analysis of data from targeted proteomics experiments performed using selected reaction monitoring (SRM). Skyline supports using and creating MS/MS spectral libraries from a wide variety of sources to choose SRM filters and verify results based on previously observed ion trap data. Skyline exports transition lists to and imports the native output files from Agilent, Applied Biosystems, Thermo Fisher Scientific and Waters triple quadrupole instruments, seamlessly connecting mass spectrometer output back to the experimental design document. The fast and compact Skyline file format is easily shared, even for experiments requiring many sample injections. A rich array of graphs displays results and provides powerful tools for inspecting data integrity as data are acquired, helping instrument operators to identify problems early. The Skyline dynamic report designer exports tabular data from the Skyline document model for in-depth analysis with common statistical tools. Single-click, self-updating web installation is available at http://proteome.gs.washington.edu/software/skyline. This web site also provides access to instructional videos, a support board, an issues list and a link to the source code project.

0 comments Cited 827 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

NetMHCpan-4.0: Improved Peptide-MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data.

Morten Nielsen, Vanessa Jurtz, Sinu Paul … (2017)

Cytotoxic T cells are of central importance in the immune system's response to disease. They recognize defective cells by binding to peptides presented on the cell surface by MHC class I molecules. Peptide binding to MHC molecules is the single most selective step in the Ag-presentation pathway. Therefore, in the quest for T cell epitopes, the prediction of peptide binding to MHC molecules has attracted widespread attention. In the past, predictors of peptide-MHC interactions have primarily been trained on binding affinity data. Recently, an increasing number of MHC-presented peptides identified by mass spectrometry have been reported containing information about peptide-processing steps in the presentation pathway and the length distribution of naturally presented peptides. In this article, we present NetMHCpan-4.0, a method trained on binding affinity and eluted ligand data leveraging the information from both data types. Large-scale benchmarking of the method demonstrates an increase in predictive performance compared with state-of-the-art methods when it comes to identification of naturally processed ligands, cancer neoantigens, and T cell epitopes.

0 comments Cited 599 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

F.M. White

Journal

Journal ID (nlm-ta): Immunooncol Technol

Journal ID (iso-abbrev): Immunooncol Technol

Title: Immuno-Oncology Technology

Publisher: Elsevier

ISSN (Electronic): 2590-0188

Publication date PMC-release: 13 October 2021

Publication date Collection: October 2021

Publication date (Electronic): 13 October 2021

Volume: 11

Electronic Location Identifier: 100042

Affiliations

[1 ]Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, USA

[2 ]Koch Institute for Integrative Cancer Research, Center for Precision Cancer Medicine, Massachusetts Institute of Technology, Cambridge, USA

[3 ]Program in Health Sciences and Technology, Harvard Medical School and Massachusetts Institute of Technology, Boston, USA

Author notes

[∗ ] Correspondence to: Prof. Forest M. White, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. Tel: 617-258-8949 fwhite@ 123456mit.edu

Article

Publisher Item ID: S2590-0188(21)00017-4 Publisher ID: 100042

DOI: 10.1016/j.iotech.2021.100042

PMC ID: 9216433

PubMed ID: 35756972

SO-VID: 49e7a20b-897d-4ee7-ad93-9b0855ca0984

License:

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

1,2,3, MHC: a review of mass-spectrometry-based immunopeptidomics methods for relative and absolute quantification of pMHCs

Read this article at

Abstract

Highlights

Related collections

NeuroImaging Methods

Most cited references 53

Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics.

Skyline: an open source document editor for creating and analyzing targeted proteomics experiments.

NetMHCpan-4.0: Improved Peptide-MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data.

Author and article information

Contributors

Journal

Affiliations

Author notes

Article

History

Categories

Comments

Comment on this article

Similar content 141

Cited by 8

Most referenced authors 5,840