Dataset Information

Efficient Parsing and Quantification of Native Mass Spectrometer Files with RawQuant

ABSTRACT: Effective analysis of protein samples by mass spectrometry (MS) instrumentation requires careful selection and optimization of a range experimental parameters. As the output from the primary detection device, the ‘raw’ MS data file can be used to gauge the success of a given sample analysis. However, the closed-source nature of the standard raw MS file can complicate effective parsing of the data contained within. To overcome this challenge, the RawQuant tool was developed to enable parsing of raw MS files to yield meta and scan data in an openly readable text format. RawQuant can be commanded to export user-friendly files containing MS1, MS2, and MS3 meta data, as well as matrices of quantification values based on isobaric tagging approaches. In this study, RawQuant is demonstrated through application in a combination of scenarios: 1. Re-analysis of shotgun proteomics data aimed at identification of the human proteome, 2. Re-analysis of experiments utilizing isobaric tagging for whole-proteome quantification, 3. Analysis of a novel bacterial proteome and synthetic peptide mixture for assessing quantification accuracy when using isobaric tags. Together, these analyses successfully demonstrate RawQuant for the efficient parsing and quantification of data from raw MS files acquired in a range common proteomics experiments. In addition, the individual analyses using RawQuant highlights parametric considerations in the different experimental sets, and suggests targetable areas to improve depth of coverage in identification-focused studies, and quantification accuracy when using isobaric tags.

INSTRUMENT(S): Orbitrap Fusion ETD, Orbitrap Fusion Lumos, Q Exactive

ORGANISM(S): Homo Sapiens (human) Escherichia Coli

SUBMITTER: Christopher Hughes

LAB HEAD: Gregg Morin

PROVIDER: PXD008787 | Pride | 2018-05-07

REPOSITORIES: pride

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Dataset's files

Source:

			Action	DRS
	20140418_QE7_UPLC9_RJC_DEV_HeLaFrac10_02.raw	Raw
	20140418_QE7_UPLC9_RJC_DEV_HeLaFrac10_02_MGF.mgf	Mgf
	20140418_QE7_UPLC9_RJC_DEV_HeLaFrac10_02_MGF.pride.mgf.gz	Mgf
	20140418_QE7_UPLC9_RJC_DEV_HeLaFrac10_02_MGF_searchgui_out.zip	Other
	20140418_QE7_UPLC9_RJC_DEV_HeLaFrac10_02_MGF_searchgui_out.zip.out.cpsx	Other

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Publications

Parsing and Quantification of Raw Orbitrap Mass Spectrometer Data Using RawQuant.

Kovalchik Kevin A KA Moggridge Sophie S Chen David D Y DDY Morin Gregg B GB Hughes Christopher S CS

Journal of proteome research 20180426 6

Effective analysis of protein samples by mass spectrometry (MS) requires careful selection and optimization of a range of experimental parameters. As the output from the primary detection device, the "raw" MS data file can be used to gauge the success of a given sample analysis. However, the closed-source nature of the standard raw MS file can complicate effective parsing of the data contained within. To ease and increase the range of analyses possible, the RawQuant tool was developed to enable ...[more]

PMID: 29682972

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Project description:Being inspired by metabolomic data processing, we have developed a bioinformatic pipeline that optimizes the processing of mass spectral data obtained from isobaric Tandem Mass Tag (TMT) experiments. Our method focuses on the tandem mass spectral level by first quantifying and then identifying (QtI), while preserving unidentified spectra for further investigations. The raw datasets were previously generated [1, 2]. Two-proteome model experiments were considered where identical pools of human CSF or plasma samples were mixed with E. coli samples at different concentrations. E. coli protein extract was spiked in 400 µL of CSF at amounts of 0, 2, 3, 5, 6.25, and 7.5 µg. Such sets of 6 spiked CSF samples were prepared in triplicate for comparison using sixplex isobaric tagging and analyzed in triplicates on two independent but identical LC MS/MS, for a total of 18 raw files [1]; this experiment is called “CSF-E.coli”. E. coli protein extract was spiked at 0, 2.5, 5, 6.25, 12.5, and 25 µg in 30 µL human plasma. Such sets of 6 spiked plasma samples were prepared in quadruplicate for comparison using sixplex isobaric tagging and analyzed in triplicates on one LC MS/MS, for a total of 12 raw files [2]; this experiment is referred as “Plasma-E.coli”.The so-called “96samples-CSF” experiment consists of 16 replicate TMT sixplex experiments measuring identical CSF samples from the pool described above [2], analyzed in triplicates on one LCMS/MS for a total of 48 raw files. The so-called “96samples-plasma” experiment consists of 16 replicate TMT sixplex experiments measuring identical plasma samples from the pool described before, analyzed in triplicates on one LC MS/MS for a total of 48 raw files [1]. References: [1] Dayon, L., Núñez Galindo, A., Corthésy, J., Cominetti, O. & Kussmann, M. Comprehensive and scalable highly automated MS-based proteomic workflow for clinical biomarker discovery in human plasma. J. Proteome Res. 13, 3837-3845 (2014). [2] Núñez Galindo, A., Kussmann, M. & Dayon, L. Proteomics of Cerebrospinal Fluid: Throughput and Robustness Using a Scalable Automated Analysis Pipeline for Biomarker Discovery. Anal. Chem. 87, 10755-10761 (2015).