Literature DB >> 34326850

Is the Immunopeptidome Getting Darker?: A Commentary on the Discussion around Mishto et al., 2019.

Anthony W Purcell1.   

Abstract

Entities:  

Keywords:  HLA; immunopeptidome; mass spectrometry - LC-MS/MS; proteasome; spliced peptides

Year:  2021        PMID: 34326850      PMCID: PMC8315041          DOI: 10.3389/fimmu.2021.720811

Source DB:  PubMed          Journal:  Front Immunol        ISSN: 1664-3224            Impact factor:   7.561


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Introduction

The immune system is perhaps the most ancient practitioner of proteomics; and as we delve into the more nuanced aspects of antigen processing and presentation, we learn more of the complexity of this essential process and Into a debate amongst the human practitioners of immunopeptidomics threatens to boil over and confer reputational damage to both the field and the investigators who use this technique. Traditionally the art of proteomics has used the identification of tryptic peptides to infer protein expression, a process termed “bottom-up” proteomics. Notably, an analogous process is used by antigen presenting cells to alert the immune system to the presence of infectious micro-organisms, malignancy and other abnormalities within the body. This process known as antigen processing and presentation relies on the selection of peptide fragments of antigens and their presentation on the surface of cells as a bound complex with Major Histocompatibility Complex (MHC) molecules. The isolation and characterisation of these MHC-bound peptides, most commonly through the use of liquid chromatography and mass spectrometry, is a rapidly growing field coined immunopeptidomics. Immunopeptidomics as a field has rapidly matured in the past decade and has moved from the domain of just a handful of specialised laboratories to now being more generally applied by the proteomics and immunology communities. The genesis of immunopeptidomics can be traced back to early work of the groups of Don Hunt with Victor Englehard and Alessandro Sette (1–5) and Hans-Georg Rammensee (6–9). It was in the early 90’s that I joined the field and was immediately struck by the generosity and encouragement of the established investigators – sharing anecdotes, methods and solutions to problems with a focus on growing the discipline and answering key questions of immune specificity whilst untangling the complexity of antigen presentation. This is something I have never forgotten and it has inspired me to “give back” to the field happily training the numerous visitors to my laboratory and publishing our methodology widely and in great depth (10, 11). Fast forwarding a few decades there have been drastic and exciting changes to the immunopeptidomics field. Improvements in instrumentation, nanoscale separation sciences and data acquisition have provided extremely rich datasets. The maturation of informatic approaches to handle this challenging data has also facilitated routine analysis of these non-tryptic peptides allowing thousands of confident identifications to be made. However, it is clear that there are still informatic challenges in the peptide-centric data analysis pipelines (12, 13) with a much lower proportion of spectra confidently assigned from immunopeptidomics data compared with more conventional samples such as tryptic digests of cell lysates. The search to explain these dark elements of the immunopeptidome has driven differences in interpretation and peptide sequence assignments to these MS/MS spectra (12, 14–25). These issues are most apparent when it comes to the presence of post-translationally spliced peptides in the immunopeptidome. Their presence in the immunopeptidome first came to note with pioneering work from Jonathan Yewdell and James Yang (26) and Nathalie Vigneron and Benoit van den Eynde (27–31) linking these peptides with immune responses primarily in cancer, as also confirmed by others (21, 32). Conventional wisdom immediately decreed their existence and the proteasomal generation of such spliced peptides as being a rare event. Their presence in several other disease states has recently been reviewed (23, 33) but perhaps most surprisingly (and controversially) the frequency of these peptides in the HLA class I immunopeptidome was reported to be up to one third of all peptides identified isolated HLA peptide ligands (15). This ground-breaking study from Liepe and colleagues (15, 19) has been confirmed by some (16) and disputed by others (17). But what are the outcomes from this study and the subsequent response by the field? It has certainly shone a spotlight on the uncomfortably large proportion of peptides in the immunopeptidome that cannot be readily assigned using reference proteomes. It has also driven developments in the informatics used to search immunopeptidomics data with improvements in assignments of post-translational modifications (34, 35), incorporation of proteogenomics databases (36) and a series of alternative workflows to address the presence of spliced peptides (16, 18, 20–22, 24, 25, 37–42). However, no consensus has been reached with somewhere between 0 and 45% of peptides in the immunopeptidome believed to be spliced. As a field where we go from here is critical – we could polarize to one extreme or the other, sit on the fence or actually address the question of what is the source of these peptide antigens that comprise the dark immunopeptidome. It is clear that several possibilities are emerging to explain a proportion of these peptides (in addition to a proportion of spliced peptides) including unanticipated post-translational modifications (24); the presence of poorly annotated non-canonical sources of antigen such as small open reading frames, translated 5′ UTRs, exon–exon junctions, intronic regions, non-canonical reading frames or antisense transcripts all of which can potentially generate immunogenic non-canonical peptides (36, 43); endogenous retroviral elements (44), the presence of microbial peptides (45). Each source of non-canonical peptide will have its supporters and detractors but perhaps none are essentially wrong and the major limitation at present is the ability to differentiate between the various explanations for the experimentally acquired MS/MS data we generate? It is also time as a field that we decide how we debate these issues and in my opinion time to stop subjectively re-searching others data but to design and implement our own experiments to more definitely corroborate or repudiate various sources of antigenic peptides in the immunopeptidome. Our field has made great strides and can look back at great community initiatives: the human immunopeptidome project (46) that strives to advance the documentation of peptides available for immune recognition in a variety of healthy and diseased states; minimal information requirements for an immunopeptidomics experiment (47) and HLA peptide atlases (48, 49) and data repositories (50) that have driven improvements in predictive algorithms and will provide the data required for the next generation of AI-based informatic tools (25). Let’s use this same spirit to explore the immunopeptidome and illuminate its dark side as a community united in this purpose.

Author Contributions

AWP wrote this commentary.

Conflict of Interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
  50 in total

1.  Mass spectrometry-based identification of MHC-bound peptides for immunopeptidomics.

Authors:  Anthony W Purcell; Sri H Ramarathinam; Nicola Ternette
Journal:  Nat Protoc       Date:  2019-05-15       Impact factor: 13.491

2.  Isolation of HLA Bound Peptides by Immunoaffinity Capture and Identification by Mass Spectrometry.

Authors:  Kirti Pandey; Sri H Ramarathinam; Anthony W Purcell
Journal:  Curr Protoc       Date:  2021-03

3.  A subset of HLA-I peptides are not genomically templated: Evidence for cis- and trans-spliced peptide ligands.

Authors:  Pouya Faridi; Chen Li; Sri H Ramarathinam; Julian P Vivian; Patricia T Illing; Nicole A Mifsud; Rochelle Ayala; Jiangning Song; Linden J Gearing; Paul J Hertzog; Nicola Ternette; Jamie Rossjohn; Nathan P Croft; Anthony W Purcell
Journal:  Sci Immunol       Date:  2018-10-12

4.  Splicing of distant peptide fragments occurs in the proteasome by transpeptidation and produces the spliced antigenic peptide derived from fibroblast growth factor-5.

Authors:  Alexandre Dalet; Nathalie Vigneron; Vincent Stroobant; Ken-Ichi Hanada; Benoît J Van den Eynde
Journal:  J Immunol       Date:  2010-02-12       Impact factor: 5.422

5.  Spliced Peptides and Cytokine-Driven Changes in the Immunopeptidome of Melanoma.

Authors:  Pouya Faridi; Katherine Woods; Simone Ostrouska; Cyril Deceneux; Ritchlynn Aranha; Divya Duscharla; Stephen Q Wong; Weisan Chen; Sri H Ramarathinam; Terry C C Lim Kam Sian; Nathan P Croft; Chen Li; Rochelle Ayala; Jonathan S Cebon; Anthony W Purcell; Ralf B Schittenhelm; Andreas Behren
Journal:  Cancer Immunol Res       Date:  2020-09-16       Impact factor: 11.151

6.  Global Identification of Post-Translationally Spliced Peptides with Neo-Fusion.

Authors:  Zach Rolfs; Stefan K Solntsev; Michael R Shortreed; Brian L Frey; Lloyd M Smith
Journal:  J Proteome Res       Date:  2018-10-31       Impact factor: 4.466

7.  Identification of naturally processed viral nonapeptides allows their quantification in infected cells and suggests an allele-specific T cell epitope forecast.

Authors:  K Falk; O Rötzschke; K Deres; J Metzger; G Jung; H G Rammensee
Journal:  J Exp Med       Date:  1991-08-01       Impact factor: 14.307

8.  MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry-based proteomics.

Authors:  Andy T Kong; Felipe V Leprevost; Dmitry M Avtonomov; Dattatreya Mellacheruvu; Alexey I Nesvizhskii
Journal:  Nat Methods       Date:  2017-04-10       Impact factor: 28.547

Review 9.  The Immune Epitope Database and Analysis Resource Program 2003-2018: reflections and outlook.

Authors:  Sheridan Martini; Morten Nielsen; Bjoern Peters; Alessandro Sette
Journal:  Immunogenetics       Date:  2019-11-25       Impact factor: 2.846

10.  Are There Indeed Spliced Peptides in the Immunopeptidome?

Authors:  Arie Admon
Journal:  Mol Cell Proteomics       Date:  2021-05-20       Impact factor: 5.911

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  3 in total

1.  Database search engines and target database features impinge upon the identification of post-translationally cis-spliced peptides in HLA class I immunopeptidomes.

Authors:  Michele Mishto; Yehor Horokhovskyi; John A Cormican; Xiaoping Yang; Steven Lynham; Henning Urlaub; Juliane Liepe
Journal:  Proteomics       Date:  2022-03-03       Impact factor: 5.393

2.  Commentary: Are There Indeed Spliced Peptides in the Immunopeptidome?

Authors:  Michele Mishto
Journal:  Mol Cell Proteomics       Date:  2021-10-02       Impact factor: 5.911

Review 3.  Mechanistic diversity in MHC class I antigen recognition.

Authors:  Camila R R Barbosa; Justin Barton; Adrian J Shepherd; Michele Mishto
Journal:  Biochem J       Date:  2021-12-22       Impact factor: 3.857

  3 in total

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