Dataset Information

Evaluating False Transfer Rates from the Match-Between-Runs algorithm with a two-proteome model

ABSTRACT: Stochasticity between independent LC-MS/MS runs is a challenging problem in the field of proteomics resulting in significant missing values (i.e., abundance measurements) among observed peptides. To address this issue, several approaches have been developed including computational methods such as MaxQuant’s Match-Between-Runs (MBR) algorithm. Often dozens of runs are all considered at once by MBR, transferring identifications from any one run to any of the others. To evaluate the error associated with these transfer events, we created a two-sample/two-proteome approach. In this way, samples containing no yeast lysates were assessed for false identification transfers from samples containing yeast. Overall, transfers from any of 20 runs with yeast were assessed to any of 20 runs without yeast were measured. While MBR increased the total number of spectral identifications by ~40%, we also found that 44% of all identified yeast proteins had identifications transferred to at least one sample without yeast. However, of these only 2.7% remained in the final dataset after applying the MaxQuant LFQ algorithm. We conclude that false transfers by MBR are plentiful, but likely have only a small impact on the final dataset due to downstream removal.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Homo Sapiens (human) Saccharomyces Cerevisiae (baker's Yeast)

SUBMITTER: Joao Paulo

LAB HEAD: Steven P. Gygi

PROVIDER: PXD014415 | Pride | 2019-09-25

REPOSITORIES: Pride

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Publications

Evaluating False Transfer Rates from the Match-between-Runs Algorithm with a Two-Proteome Model.

Lim Matthew Y MY Paulo João A JA Gygi Steven P SP

Journal of proteome research 20191002 11

Stochasticity between independent LC-MS/MS runs is a challenging problem in the field of proteomics, resulting in significant missing values (i.e., abundance measurements) among observed peptides. To address this issue, several approaches have been developed including computational methods such as MaxQuant's match-between-runs (MBR) algorithm. Often dozens of runs are all considered at once by MBR, transferring identifications from any one run to any of the others. To evaluate the error associat ...[more]

PMID: 31547658

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Project description:Yeast remains an important model for systems biology and for evaluating proteomics strategies. In-depth shotgun proteomics studies have reached nearly comprehensive coverage, and rapid, targeted approaches have been developed for this organism. Recently, we demonstrated that single LC-MS/MS analysis using long columns and gradients coupled to a linear ion trap Orbitrap instrument had an unexpectedly large dynamic range of protein identification (Thakur, S. S., Geiger, T., Chatterjee, B., Bandilla, P., Frohlich, F., Cox, J., and Mann, M. (2011) Deep and highly sensitive proteome coverage by LC-MS/MS without prefractionation. Mol. Cell Proteomics 10, 10.1074/mcp.M110.003699). Here we couple an ultra high pressure liquid chromatography system to a novel bench top Orbitrap mass spectrometer (Q Exactive) with the goal of nearly complete, rapid, and robust analysis of the yeast proteome. Single runs of filter-aided sample preparation (FASP)-prepared and LysC-digested yeast cell lysates identified an average of 3923 proteins. Combined analysis of six single runs improved these values to more than 4000 identified proteins/run, close to the total number of proteins expressed under standard conditions, with median sequence coverage of 23%. Because of the absence of fractionation steps, only minuscule amounts of sample are required. Thus the yeast model proteome can now largely be covered within a few hours of measurement time and at high sensitivity. Median coverage of proteins in Kyoto Encyclopedia of Genes and Genomes pathways with at least 10 members was 88%, and pathways not covered were not expected to be active under the conditions used. To study perturbations of the yeast proteome, we developed an external, heavy lysine-labeled SILAC yeast standard representing different proteome states. This spike-in standard was employed to measure the heat shock response of the yeast proteome. Bioinformatic analysis of the heat shock response revealed that translation-related functions were down-regulated prominently, including nucleolar processes. Conversely, stress-related pathways were up-regulated. The proteomic technology described here is straightforward, rapid, and robust, potentially enabling widespread use in the yeast and other biological research communities. Data analysis: The raw files were processed using MaxQuant version 1.2.0.34. The fragmentation spectra were searched against the yeast ORF database (release date of February 3, 2011; 6752 entries) using the Andromeda search engine with the initial precursor and fragment mass tolerances set to 7 and 20 ppm, respectively, and with up to two missed cleavages. Carabamidomethlyation of cysteine was set as a fixed modification, and oxidation of methionine and protein N-terminal acetylation were chosen as variable modifications for database searching. Both peptide and protein identifications were filtered at 1% false discovery rate and thus were not dependent on the peptide score. Bioinformatics analysis was performed using the Perseus tools available in the MaxQuant environment.

Dataset Information

Evaluating False Transfer Rates from the Match-Between-Runs algorithm with a two-proteome model

Publications

Evaluating False Transfer Rates from the Match-between-Runs Algorithm with a Two-Proteome Model.

Similar Datasets

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