Dataset Information

DIA+: A novel data-independent acquisition method combines multiple precursor charges to boost peptide signal.

ABSTRACT: Data-independent acquisition (DIA) methods aim to expand the benefits of low-throughput targeted proteomics to proteome-wide analyses. These methods rely on the use of several broadband isolation windows that select and fragment all peptide ions within a cycle. Isolation windows differ in that (I) they exhibit different widths, (ii) they are acquired either sequentially or in a non-consecutive order, and (iii) they are either juxtaposed or overlapped. Here we present DIA+, a novel DIA multiplexing scheme with isolation windows that combine signals from identical peptides with different charges. DIA+ is based on the co-isolation of charge +2 and +3 precursor ions from identical peptide sequences to combine their signal and therefore, increase the number of MS2 peptide fragment ions detected. DIA+ combines three non-consecutive m/z ranges, based on the mass difference between charge +2 and +3 peptides, into a composite 24 Da isolation window. Forty of these combined 24 Da windows cover a range of 400-1350 m/z. The performance of DIA+ was compared with other reference methods in the field, and with a DIA+ control method in which each 24 Da isolation window results from the combination of three consecutive m/z ranges. The combination of improved signal-to-noise and sequence coverage increases the confidence on peptide identification and results in a significant increase in the number of identified peptides and proteins.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Eduard Sabidó

LAB HEAD: Eduard Sabidó

PROVIDER: PXD010210 | Pride | 2018-10-11

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	170411_S_EBES_01_CHARGE_01_2ug.raw	Raw
	170411_S_EBES_01_CHARGE_02_2ug.raw	Raw
	170411_S_EBES_01_CHARGE_03_2ug.raw	Raw
	170411_S_EBES_01_CTRLCHR_01_2ug.raw	Raw
	170411_S_EBES_01_CTRLCHR_02_2ug.raw	Raw

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Publications

DIA+: A Data-Independent Acquisition Method Combining Multiple Precursor Charges to Improve Peptide Signal.

Borràs Eva E Sabidó Eduard E

Analytical chemistry 20181011 21

Data-independent acquisition methods that acquire fragment ions from virtually any peptide in a sample have expanded the benefits of low-throughput targeted proteomics to proteome-wide analyses. While these methods have increased the reproducibility of peptide quantification across multiple samples, their sensitivity is still limited, and the quantification of complete proteomes remains a challenge. Here we present DIA+, a DIA method that combines signals from identical peptides with different c ...[more]

PMID: 30295461

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Project description:Data independent acquisition-mass spectrometry (DIA-MS) coupled with liquid chromatography is a promising approach for rapid, automatic sampling of MS/MS data in untargeted metabolomics. However, wide isolation windows in DIA-MS generate MS/MS spectra containing a mixed population of fragment ions together with their precursor ions. This precursor-fragment ion map in a comprehensive MS/MS spectral library is crucial for relative quantification of fragment ions uniquely representative of each precursor ion. However, existing reference libraries are not sufficient for this purpose since the fragmentation patterns of small molecules can vary in different instrument setups. Here we developed a bioinformatics workflow called MetaboDIA to build customized MS/MS spectral libraries using a user's own data dependent acquisition (DDA) data and to perform MS/MS-based quantification with DIA data, thus complementing conventional MS1-based quantification. MetaboDIA also allows users to build a spectral library directly from DIA data in studies of a large sample size. Using a marine algae data set, we show that quantification of fragment ions extracted with a customized MS/MS library can provide as reliable quantitative data as the direct quantification of precursor ions based on MS1 data. To test its applicability in complex samples, we applied MetaboDIA to a clinical serum metabolomics data set, where we built a DDA-based spectral library containing consensus spectra for 1829 compounds. We performed fragment ion quantification using DIA data using this library, yielding sensitive differential expression analysis. </br></br> Serum metabolome of 40 age-related macular degeneration patients and 20 control samples was analyzed using untargeted mass spectrometry. We used data dependent acquisition data to build a MS/MS spectral assay library for more than 1,000 compounds and performed targeted extraction of MS2 ion chromatograms from data independent acquisition analysis.