Dataset Information

Systematic Evaluation of Data-Independent Acquisition for Sensitive and Reproducible Proteomics – a Prototype Design for a Single Injection Assay

ABSTRACT: This dataset includes twelve DIA methods with various mass-isolation windows that analyze precursor ranges from 400-1250 m/z as well as shotgun acquired data with the same instrument and LC gradient. The mass-isolation windows analyzed included 3, 6, and 26 m/z widths. Each 3 m/z window method analyzed a 140 precursor m/z range, 6 m/z windows analyzed either a 200 or 280 precursor m/z range, and the 26 m/z isolation window method analyzed an 800 precursor m/z range from 400-1200 m/z. All data were collected with a 5600+ Sciex QTOF with a 70 minute reverse phase gradient. Shotgun analyses were collected with the sample samples, instrument, and gradient.

INSTRUMENT(S): TripleTOF 5600

ORGANISM(S): Escherichia Coli

TISSUE(S): Cell Culture

SUBMITTER: Michael Heaven

LAB HEAD: Kenneth D. Greis

PROVIDER: PXD002688 | Pride | 2015-12-02

REPOSITORIES: pride

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Dataset's files

Source:

			Action	DRS
	26mzwindowsfrom400-1200precursormz.zip	Other
	3combinedprecursorrangesfrom410-1250mzanalyzedwith6mzwindows.zip	Other
	3mzwindowsfrom1110-1250precursormz.zip	Other
	3mzwindowsfrom410-550precursormz.zip	Other
	3mzwindowsfrom550-690precursormz.zip	Other

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Publications

Systematic evaluation of data-independent acquisition for sensitive and reproducible proteomics-a prototype design for a single injection assay.

Heaven Michael R MR Funk Adam J AJ Cobbs Archie L AL Haffey Wendy D WD Norris Jeremy L JL McCullumsmith Robert E RE Greis Kenneth D KD

Journal of mass spectrometry : JMS 20160101 1

Data-independent acquisition (DIA)-based proteomics has become increasingly complicated in recent years because of the vast number of workflows described, coupled with a lack of studies indicating a rational framework for selecting effective settings to use. To address this issue and provide a resource for the proteomics community, we compared 12 DIA methods that assay tryptic peptides using various mass-isolation windows. Our findings indicate that the most sensitive single injection LC-DIA met ...[more]

PMID: 26757066

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Project description:The sensitivity of single-cell proteomics (SCP) has increased dramatically in recent years due to advances in experimental design, sample preparation, separations and mass spectrometry instrumentation. However, further increasing the sensitivity of SCP methods and instrumentation will enable the study of proteins within single cells that are expressed at copy numbers too small to be measured by current methods. Here we further increase SCP sensitivity by combining efficient nanoPOTS sample preparation and ultra-low-flow liquid chromatography with a newly developed data acquisition and analysis scheme termed wide window acquisition (WWA) to extend the achievable proteome coverage for single cells to >3,000 for single-cell data analyses. WWA is based on data-dependent acquisition (DDA) but employs larger precursor isolation windows to intentionally co-isolate and co-fragment additional precursors along with the selected precursor. The resulting chimeric MS2 spectra are then resolved using the CHIMERYS search engine within Proteome Discoverer 3.0. Compared to standard DDA workflows, WWA employing isolation windows of 8-12 Th increases peptide and proteome coverage by ~28% and ~39%, respectively. For a 40 min LC gradient operated at ~15 nL/min, we identified an average of 2,150 proteins per single-cell-sized aliquots of protein digest directly from MS2 spectra, which increased to an average 3,524 proteins including proteins identified with MS1-level feature matching. Reducing the active gradient to 20 min resulted in only a 10% decrease in proteome coverage. We also compared performance of WWA with DIA underperformed relative to WWA in terms of proteome coverage, especially with faster separations. Average proteome coverage for single HeLa and K562 cells was respectively 1,758 and 1,642 based on MS2 identifications with 1% false discovery rate and 3042 and 2891 with MS1 feature matching. As such, WWA combined with efficient sample preparation and rapid separations extends the depths of the proteome that can be studied at the single-cell level.