Dataset Information

Human serum spectral library for DIA mass spectrometry

ABSTRACT: For comprehensive human serum proteome analysis, we attempted to construct a serum spectral library for DIA-MS. Consequently, the customized spectral DIA library contained information on 23,196 peptides derived from 1,534 human serum proteins. We expect that this customized spectral DIA library will be used for comprehensive proteomic analysis of human serum.

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Yayoi Kimura

PROVIDER: PXD027635 | JPOST Repository | Wed Nov 10 00:00:00 GMT 2021

REPOSITORIES: jPOST

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Publications

Identification of serum prognostic biomarkers of severe COVID-19 using a quantitative proteomic approach.

Kimura Yayoi Y Nakai Yusuke Y Shin Jihye J Hara Miyui M Takeda Yuriko Y Kubo Sousuke S Jeremiah Sundararaj Stanleyraj SS Ino Yoko Y Akiyama Tomoko T Moriyama Kayano K Sakai Kazuya K Saji Ryo R Nishii Mototsugu M Kitamura Hideya H Murohashi Kota K Yamamoto Kouji K Kaneko Takeshi T Takeuchi Ichiro I Hagiwara Eri E Ogura Takashi T Hasegawa Hideki H Tamura Tomohiko T Yamanaka Takeharu T Ryo Akihide A

Scientific reports 20211019 1

The COVID-19 pandemic is an unprecedented threat to humanity that has provoked global health concerns. Since the etiopathogenesis of this illness is not fully characterized, the prognostic factors enabling treatment decisions have not been well documented. Accurately predicting the progression of the disease would aid in appropriate patient categorization and thus help determine the best treatment option. Here, we have introduced a proteomic approach utilizing data-independent acquisition mass s ...[more]

PMID: 34667241

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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.

Dataset Information

Human serum spectral library for DIA mass spectrometry

Publications

Identification of serum prognostic biomarkers of severe COVID-19 using a quantitative proteomic approach.

Similar Datasets

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