One-stop analysis of DIA proteomics data using MSFragger-DIA and FragPipe computational platform

Yu, Fengchao; Teo, Guo Ci; Kong, Andy T.; Li, Ginny Xiaohe; Demichev, Vadim; Nesvizhskii, Alexey I.

doi:10.1101/2022.10.28.514272

Cited by 21 publications

(27 citation statements)

References 74 publications

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“…The same DIA approach and LC-MS/MS data acquisition strategy was used as described above. Data analysis was similar, but instead of EncyclopeDIA, demultiplexed mzML files were processed with FragPipe using the MSFragger-DIA and DIA-NN ( 66 , 67 ) for quantitative analysis with default settings. Data were further processed with Perseus as described above: protein intensity values were log 2 transformed before further analysis, proteins with measured values for all three replicates with at least one condition were retained, and missing values were imputed from a normal distribution with a width of 0.3 and a downshift value of 2.5.…”

Section: Methodsmentioning

confidence: 99%

Elucidating the cellular determinants of targeted membrane protein degradation by lysosome-targeting chimeras

Ahn,

Riley,

Kamber

et al. 2023

Science

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Targeted protein degradation can provide advantages over inhibition approaches in the development of therapeutic strategies. Lysosome-targeting chimeras (LYTACs) harness receptors, such as the cation-independent mannose 6–phosphate receptor (CI-M6PR), to direct extracellular proteins to lysosomes. In this work, we used a genome-wide CRISPR knockout approach to identify modulators of LYTAC-mediated membrane protein degradation in human cells. We found that disrupting retromer genes improved target degradation by reducing LYTAC recycling to the plasma membrane. Neddylated cullin-3 facilitated LYTAC-complex lysosomal maturation and was a predictive marker for LYTAC efficacy. A substantial fraction of cell surface CI-M6PR remains occupied by endogenous M6P-modified glycoproteins. Thus, inhibition of M6P biosynthesis increased the internalization of LYTAC-target complexes. Our findings inform design strategies for next-generation LYTACs and elucidate aspects of cell surface receptor occupancy and trafficking.

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Section: Methodsmentioning

confidence: 99%

Elucidating the cellular determinants of targeted membrane protein degradation by lysosome-targeting chimeras

Ahn,

Riley,

Kamber

et al. 2023

Science

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“…For staggered DIA files, filters peakPicking at vendor msLevel 1- and demultiplex with optimization overlap_only and massError 10 ppm were used. Database and spectral library search was performed using FragPipe v18 (Yu et al , 2022) with a FASTA file combining yeast and human kinases (wild-type and kinase dead) downloaded from Uniprot on 2021-11-08. DDA, DDA-GPF and DIA-GPF files were used to create a spectral library in FragPipe.…”

Section: Methodsmentioning

confidence: 99%

The fitness cost of spurious phosphorylation

Bradley,

Hogrebe,

Dandage

et al. 2023

Preprint

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The fidelity of signal transduction requires the binding of regulatory molecules to their cognate targets. However, the crowded cell interior risks off-target interactions between proteins that are functionally unrelated. How such off-target interactions impact fitness is not generally known, but quantifying this is required to understand the constraints faced by cell systems as they evolve. Here, we use the model organismS. cerevisiaeto inducibly express tyrosine kinases. Because yeast lacksbona fidetyrosine kinases, most of the resulting tyrosine phosphorylation is spurious. This provides a suitable system to measure the impact of artificial protein interactions on fitness. We engineered 44 yeast strains each expressing a tyrosine kinase, and quantitatively analysed their phosphoproteomes. This analysis resulted in ∼30,000 phosphosites mapping to ∼3,500 proteins. Examination of the fitness costs in each strain revealed a strong correlation between the number of spurious pY sites and decreased growth. Moreover, the analysis of pY effects on protein structure and on protein function revealed over 1000 pY events that we predict to be deleterious. However, we also find that a large number of the spurious pY sites have a negligible effect on fitness, possibly because of their low stoichiometry. This result is consistent with our evolutionary analyses demonstrating a lack of phosphotyrosine counter-selection in species withbona fidetyrosine kinases. Taken together, our results suggest that, alongside the risk for toxicity, the cell can tolerate a large degree of non-functional crosstalk as interaction networks evolve.

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“…The search scripts of MSFragger and FragPipe, together with machine learning nodes of MSBooster and MSFragger-Glyco, have been developed recently to enhance the identification of immunopeptides and glycosylated immunopeptides, respectively. [60][61][62][63][64] For more variations of immunopeptides with post-translational modifications (PTMs), PROMISE has been developed, which delineated the preference of the PTMs in a certain HLA allotype. 65 Not only these kinds of boosting systems for peptide search but also de novo sequencing is gaining attention due to its potential in exploratory immunopeptidomics for NCPs.…”

Section: Implementation Impacts Of Deep/ Machine Learning and De Novo...mentioning

confidence: 99%

Emerging potential of immunopeptidomics by mass spectrometry in cancer immunotherapy

Minegishi,

Haga,

Ueda

2024

Cancer Science

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With significant advances in analytical technologies, research in the field of cancer immunotherapy, such as adoptive T cell therapy, cancer vaccine, and immune checkpoint blockade (ICB), is currently gaining tremendous momentum. Since the efficacy of cancer immunotherapy is recognized only by a minority of patients, more potent tumor‐specific antigens (TSAs, also known as neoantigens) and predictive markers for treatment response are of great interest. In cancer immunity, immunopeptides, presented by human leukocyte antigen (HLA) class I, play a role as initiating mediators of immunogenicity. The latest advancement in the interdisciplinary multiomics approach has rapidly enlightened us about the identity of the “dark matter” of cancer and the associated immunopeptides. In this field, mass spectrometry (MS) is a viable option to select because of the naturally processed and actually presented TSA candidates in order to grasp the whole picture of the immunopeptidome. In the past few years the search space has been enlarged by the multiomics approach, the sensitivity of mass spectrometers has been improved, and deep/machine‐learning‐supported peptide search algorithms have taken immunopeptidomics to the next level. In this review, along with the introduction of key technical advancements in immunopeptidomics, the potential and further directions of immunopeptidomics will be reviewed from the perspective of cancer immunotherapy.

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One-stop analysis of DIA proteomics data using MSFragger-DIA and FragPipe computational platform

Cited by 21 publications

References 74 publications

Elucidating the cellular determinants of targeted membrane protein degradation by lysosome-targeting chimeras

Elucidating the cellular determinants of targeted membrane protein degradation by lysosome-targeting chimeras

The fitness cost of spurious phosphorylation

Emerging potential of immunopeptidomics by mass spectrometry in cancer immunotherapy

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