MassIVE MSV000091200

Partial Public PXD039855

Real-time spectral library matching for sample multiplexed quantitative proteomics

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Description

Sample multiplexed quantitative proteomics has proved to be a highly versatile means to assay molecular phenotypes. Yet, stochastic precursor selection and precursor coisolation can dramatically reduce the efficiency of data acquisition and quantitative accuracy. To address this, intelligent data acquisition (IDA) strategies have recently been developed to improve instrument efficiency and quantitative accuracy for both discovery and targeted methods. To this end we sought to develop and implement a new real-time library searching (RTLS) workflow that could enable intelligent scan triggering and peak selection within milliseconds of scan acquisition. To ensure ease of use and general applicability, we built an application to read in diverse spectral libraries and file types from both empirical and predicted spectral libraries. We demonstrate that RTLS methods enable improved quantitation of multiplexed samples, particularly with consideration for quantitation from chimeric fragment spectra. We used RTLS to profile proteome responses to small molecule perturbations and were able to quantify up to 15% more significantly regulated proteins in half the gradient time as traditional methods. [doi:10.25345/C5833N781] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: Proteomics ; Real-time library search ; Intelligent data acquisition

Contact

Principal Investigators:
(in alphabetical order) 		Devin Schweppe, University of Washington, United States
Submitting User: cmcgann

Publications

McGann CD, Barshop WD, Canterbury JD, Lin C, Gabriel W, Huang J, Bergen D, Zabrouskov V, Melani RD, Wilhelm M, McAlister GC, Schweppe DK.
Real-Time Spectral Library Matching for Sample Multiplexed Quantitative Proteomics.
J Proteome Res. 2023 Sep 1;22(9):2836-2846. Epub 2023 Aug 9.

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Number of distinct conditions across all analyses (original submission and reanalyses) associated with this dataset.

Distinct condition labels are counted across all files submitted in the "Metadata" category having a "Condition" column in this dataset.

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Number of distinct biological replicates across all analyses (original submission and reanalyses) associated with this dataset.

Distinct replicate labels are counted across all files submitted in the "Metadata" category having a "BioReplicate" or "Replicate" column in this dataset.

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Number of distinct technical replicates across all analyses (original submission and reanalyses) associated with this dataset.

The technical replicate count is defined as the maximum number of times any one distinct combination of condition and biological replicate was analyzed across all files submitted in the "Metadata" category. In the case of fractionated experiments, only the first fraction is considered.

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Originally identified proteins that were automatically remapped by MassIVE to proteins in the SwissProt human reference database.

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Number of distinct protein accessions reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct peptide sequences (including modified variants or peptidoforms) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Total number of peptide-spectrum matches (i.e. spectrum identifications) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct proteins quantified across all analyses (original submission and reanalyses) associated with this dataset.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

A protein is differentially abundant if its change in abundance across conditions is found to be statistically significant with an adjusted p-value <= 0.05 and lists no issues associated with statistical tests for differential abundance.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

"N/A" means no results of this type were submitted.
This dataset may not contain all raw spectra data as originally deposited in PRIDE. It has been imported to MassIVE for reanalysis purposes, so its spectra data here may consist solely of processed peak lists suitable for reanalysis with most software.