Dataset Information

Yeast calibration curve dataset

ABSTRACT: The yeast calibration curve dataset was acquired to compare the accuracy of DIA tools with decreasing contents of target peptides. Four samples (Y1, Y2, Y3 and Y4) with decreasing contents (200, 100, 50 and 25 ng, respectively) of analytes (yeast tryptic peptides) and a high content of background peptides (800 ng human tryptic peptides constantly) were analyzed in triplicate using LC-DIA-MS/MS. The DIA data were processed by different DIA tools based on the spectral library generated from the DDA data. The accuracy of different DIA tools was compared.

INSTRUMENT(S): LTQ Orbitrap Elite

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

SUBMITTER: Binjun Yan

LAB HEAD: B. Yan

PROVIDER: PXD039399 | Pride | 2023-10-25

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	0927_0B90B_20ms30CE_1020DDAR1.raw	Raw
	0927_0B90B_20ms30CE_1020DDAR2.raw	Raw
	0927_0B90B_20ms30CE_1020DDAR3.raw	Raw
	0930Y1H_R1.raw	Raw
	0930Y1H_R2.raw	Raw

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Project description:A comprehensive proteome map is essential to elucidate molecular pathways and protein functions. Although great improvements in sample preparation, instrumentation and data analysis already yield-ed impressive results, current studies suffer from a limited proteomic depth and dynamic range there-fore lacking low abundant or highly hydrophobic proteins. Here, we combine and benchmark advanced micro pillar array columns (µPAC) operated at nanoflow with wide window acquisition (WWA) and the AI-based CHIMERYS search engine for data analysis to maximize chromatographic separation power, sensitivity and proteome coverage. The wide window acquisition method merges the strengths of DDA and DIA. WWA uses a broad isolation window (≥4 Th) for data-dependent precursor selection. Similar to DIA, precursor ions close to those selected are co-fragmented, producing chimeric spectra that boost IDs and improve coverage of low-abundance peptides, which would otherwise be missed. WWA is particularly powerful when combined with the AI-driven CHIMERYS search algorithm, which allows confident identification of up to eleven peptides from a single chimeric spectrum. Developed by MSAID, the CHIMERYS algorithm makes use of accurate fragment spectrum predictions trained on millions of spectra, which allows to utilize additional spectral properties such as relative signal intensities for drastically improved identification rates. Entrapment experiments were conducted searching mouse immunoprecipitation samples with MS Amanda 2.0 and CHIMERYS by applying an additional custom-made decoy database, which demonstrated excellent protein, peptide and PSM FDR control from 1% upwards for both search engines. Combining wide precursor isolation widths of 4-12 Th with the CHIMERYS search engine identified 51-74% more proteins and 59-150% more peptides for single cell, immunoprecipitation and multi-species samples in comparison to a standard proteomics workflow employing MS Amanda 2.0 and an isolation width of 1 Th. Application of different isolation widths revealed that the optimal isolation window size varies according to sample amount and complexity with 12 Th resulting in the highest number of identifications for single cell-equivalent injection amounts, while 4 Th provided best results for classical bulk inputs of 400ng. Evaluation of coefficients of variation also yielded improved results for WWA over classical DDA when assessing single cell, 40 cell and 250pg bulk HeLa lysates. Overall, WWA and CHIMERYS resulted in substantially improved proteomic depth and quantification for all sample types tested and will provide a highly valuable toolset for the proteomics community.

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Yeast calibration curve dataset

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