Dataset Information

High accurate and precise quantification analysis of GeLC-MS/MS with dimethyl labeling (label efficiency).

ABSTRACT: Dataset of light-dimethyl labeling of Mouse brain samples.

ORGANISM(S): Mus Musculus (mouse)

SUBMITTER: Yoshio Kodera, Center for Disease Proteomics, Kitasato University School of Science

PROVIDER: PXD022591 | JPOST Repository | Thu Nov 18 00:00:00 GMT 2021

REPOSITORIES: jPOST

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			Action	DRS
	Akon120_205_cMB10_0o036ug_3uL_T60.raw	Raw
	Akon120_206_cMB30_0o05ug_3uL_T60.raw	Raw
	Akon121_001_cMB10_DM1_0o051ug_3uL_T60.raw	Raw
	Akon121_002_cMB10_DM2_0o051ug_3uL_T60.raw	Raw
	Akon121_003_cMB30_DM1_0o048ug_3uL_T60.raw	Raw

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Project description:BackgroundQuantitative measurements of specific protein phosphorylation sites, as presented here, can be used to investigate signal transduction pathways, which is an important aspect of cell dynamics. The presented method quantitatively compares peptide abundances from experiments using 18O/16O labeling starting from elaborated MS spectra. It was originally developed to study signaling cascades activated by amyloid-beta treatment of neurons used as a cellular model system with relevance to Alzheimer's disease, but is generally applicable.ResultsThe presented method assesses, in complete cell lysates, the degree of phosphorylation of specific peptide residues from MS spectra using 18O/16O labeling. The abundance of each observed phospho-peptide from two cell states was estimated from three overlapping isotope contours. The influence of peptide-specific labeling efficiency was removed by performing a label swapped experiment and assuming that the labeling efficiency was unchanged upon label swapping. Different degrees of phosphorylation were reported using the fold change measure which was extended with a confidence interval found to reflect the quality of the underlying spectra. Furthermore a new way of method assessment using simulated data is presented. Using simulated data generated in a manner mimicking real data it was possible to show the method's robustness both with increasing noise levels and with decreasing labeling efficiency.ConclusionThe fold change error assessable on simulated data was on average 0.16 (median 0.10) with an error-to-signal ratio and labeling efficiency distributions similar to the ones found in the experimentally observed spectra. Applied to experimentally observed spectra a very good match was found to the model (<10% error for 85% of spectra) with a high degree of robustness, as assessed by data removal. This new method can thus be used for quantitative signal cascade analysis of total cell extracts in a high throughput mode.

Dataset Information

High accurate and precise quantification analysis of GeLC-MS/MS with dimethyl labeling (label efficiency).

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