A Potential Golden Age to Come—Current Tools, Recent Use Cases, and Future Avenues for De Novo Sequencing in Proteomics

Muth, Thilo; Hartkopf, Felix; Vaudel, Marc; Renard, Bernhard Y.

doi:10.1002/pmic.201700150

Cited by 52 publications

(58 citation statements)

References 149 publications

(199 reference statements)

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“…Sequence coverage of these 52 PSMs was 65 %, which is slightly below the sequence coverage obtained via de novo searching. This confirms that spectral clustering helped to maximize the signal-to-noise ratio of the consensus spectra, as sequence database searching is typically expected to outperform de novo searching [7]. A small caveat in comparing these search results is that the de novo search results were manually validated taking the problem statement into account, i.e.…”

Section: Validation Using Sequence Database Searchingmentioning

confidence: 60%

“…Both of these approaches depend on the availability of a ground truth reference set to which the unknown spectra are compared, either in the form of a sequence database or a spectral library. Alternatively, if such prior information is not available, such as, for example, during antibody sequencing or for non-model organisms whose genome has not been sequenced yet, de novo searching can be used to directly derive peptide sequences from the unknown MS/MS spectra based on the mass differences between pairs of their fragment ion peaks [7].…”

Section: Introductionmentioning

confidence: 99%

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2018 YPIC Challenge: A case study in characterizing an unknown protein sample

Pino

Lin

Bittremieux

2019

Preprint

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For the 2018 YPIC Challenge contestants were invited to try to decipher two unknown English questions encoded by a synthetic protein expressed in Escherichia coli. In addition to deciphering the sentence, contestants were asked to determine the 3D structure and detect any post-translation modifications left by the host organism. We present our experimental and computational strategy to characterize this sample by identifying the unknown protein sequence and detecting the presence of post-translational modifications. The sample was acquired with dynamic exclusion disabled to increase the signal-to-noise ratio of the measured molecules, after which spectral clustering was used to generate high-quality consensus spectra. De novo spectrum identification was used to determine the synthetic protein sequence, and any post-translational modifications introduced by E. coli on the synthetic protein were analyzed via spectral networking. This workflow resulted in a de novo sequence coverage of 70%, on par with sequence database searching performance. Additionally, the spectral networking analysis indicated that no systematic modifications were introduced on the synthetic protein by E. coli. The strategy presented here can be directly used to analyze samples for which no protein sequence information is available or when the identity of the sample is unknown. All software and code to perform the bioinformatics analysis is available as open source, and self-contained Jupyter notebooks are provided to fully recreate the analysis.

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Section: Validation Using Sequence Database Searchingmentioning

confidence: 60%

Section: Introductionmentioning

confidence: 99%

2018 YPIC Challenge: A case study in characterizing an unknown protein sample

Pino

Lin

Bittremieux

2019

Preprint

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“…Recently, de novo LC-MS/MS has rapidly developed and is widely used in peptide sequencing. De novo LC-MS/MS can execute sequencing directly from MS/MS and does not depend on databases, as it can use the fragment ion information from MS/MS in an unbiased manner (61). It completely avoids the large problems of low identification rates (low sensitivity) and high false-discovery rates (low accuracy) of existing database search tools originating from the static search space (62).…”

Section: Discussionmentioning

confidence: 99%

Structure and Peptidome of the Bat MHC Class I Molecule Reveal a Novel Mechanism Leading to High-Affinity Peptide Binding

et al. 2019

The Journal of Immunology

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Bats are natural reservoir hosts, harboring more than 100 viruses, some of which are lethal to humans. The asymptomatic coexistence with viruses is thought to be connected to the unique immune system of bats. MHC class I (MHC I) presentation is closely related to cytotoxic lymphocyte immunity, which plays an important role in viral resistance. To investigate the characteristics of MHC I presentation in bats, the crystal structures of peptide–MHC I complexes of Pteropus alecto, Ptal-N*01:01/HEV-1 (DFANTFLP) and Ptal-N*01:01/HEV-2 (DYINTNLVP), and two related mutants, Ptal-N*01:01/HEV-1PΩL (DFANTFLL) and Ptal-N*01:01ΔMDL/HEV-1, were determined. Through structural analysis, we found that Ptal-N*01:01 had a multi-Ala–assembled pocket B and a flexible hydrophobic pocket F, which could accommodate variable anchor residues and allow Ptal-N*01:01 to bind numerous peptides. Three sequential amino acids, Met, Asp, and Leu, absent from the α1 domain of the H chain in other mammals, were present in this domain in the bat. Upon deleting these amino acids and determining the structure in p/Ptal-N*01:01ΔMDL/HEV-1, we found they helped form an extra salt-bridge chain between the H chain and the N-terminal aspartic acid of the peptide. By introducing an MHC I random peptide library for de novo liquid chromatography–tandem mass spectrometry analysis, we found that this insertion module, present in all types of bats, can promote MHC I presentation of peptides with high affinity during the peptide exchange process. This study will help us better understand how bat MHC I presents high-affinity peptides from an extensive binding peptidome and provides a foundation to understand the cellular immunity of bats.

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“…The portion of spliced peptides in the immunopeptidome is not known, but some reports suggest that it may be up to 30% [76]. The de novo sequencing of HLA ligands cannot be done manually, due to the large amount of created data; therefore, recently, automated tools started to become available with examples of the most popular software tools as PEAKS and PepNovo+ [77]. There was significant progress in this field in recent years due to the availability of MS instruments capable of high-speed acquisition with high-resolution MS/MS spectra, as well as developments in computational methods, such as the introduction of deep learning-based workflows for peptide sequencing.…”

Section: Detection and Identification Of Immunopeptides With Mass Spementioning

confidence: 99%

Mass Spectrometry-Based Identification of MHC-Associated Peptides

Kote

Piróg

Bedran

et al. 2020

Cancers

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Neoantigen-based immunotherapies promise to improve patient outcomes over the current standard of care. However, detecting these cancer-specific antigens is one of the significant challenges in the field of mass spectrometry. Even though the first sequencing of the immunopeptides was done decades ago, today there is still a diversity of the protocols used for neoantigen isolation from the cell surface. This heterogeneity makes it difficult to compare results between the laboratories and the studies. Isolation of the neoantigens from the cell surface is usually done by mild acid elution (MAE) or immunoprecipitation (IP) protocol. However, limited amounts of the neoantigens present on the cell surface impose a challenge and require instrumentation with enough sensitivity and accuracy for their detection. Detecting these neopeptides from small amounts of available patient tissue limits the scope of most of the studies to cell cultures. Here, we summarize protocols for the extraction and identification of the major histocompatibility complex (MHC) class I and II peptides. We aimed to evaluate existing methods in terms of the appropriateness of the isolation procedure, as well as instrumental parameters used for neoantigen detection. We also focus on the amount of the material used in the protocols as the critical factor to consider when analyzing neoantigens. Beyond experimental aspects, there are numerous readily available proteomics suits/tools applicable for neoantigen discovery; however, experimental validation is still necessary for neoantigen characterization.

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A Potential Golden Age to Come—Current Tools, Recent Use Cases, and Future Avenues for De Novo Sequencing in Proteomics

Cited by 52 publications

References 149 publications

2018 YPIC Challenge: A case study in characterizing an unknown protein sample

2018 YPIC Challenge: A case study in characterizing an unknown protein sample

Structure and Peptidome of the Bat MHC Class I Molecule Reveal a Novel Mechanism Leading to High-Affinity Peptide Binding

Mass Spectrometry-Based Identification of MHC-Associated Peptides

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