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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Dataset's files

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			Action	DRS
	200424QE_Mars_Offgel_1.raw	Raw
	200424QE_Mars_Offgel_10.raw	Raw
	200424QE_Mars_Offgel_11.raw	Raw
	200424QE_Mars_Offgel_12.raw	Raw
	200424QE_Mars_Offgel_13.raw	Raw

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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. 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.

Project description:We have developed MetaboKit, a comprehensive software package for compound identification and relative quantification in mass spectrometry-based untargeted metabolomics analysis. In data dependent acquisition (DDA) analysis, MetaboKit constructs a customized spectral library with compound identities from reference spectral libraries, adducts, dimers, in-source fragments (ISF), MS/MS fragmentation spectra, and more importantly the retention time information unique to the chromatography system used in the experiment. Using the customized library, the software performs targeted peak integration for precursor ions in DDA analysis and for precursor and product ions in data independent acquisition (DIA) analysis. With its stringent identification algorithm requiring matches by both MS and MS/MS data, MetaboKit provides identification results with significantly greater specificity than the competing software packages without loss in sensitivity. The proposed MS/MS-based screening of ISFs also reduces the chance of unverifiable identification of ISFs considerably. MetaboKit's quantification module produced peak area values highly correlated with known concentrations in a DIA analysis of the metabolite standards at both MS1 and MS2 levels. Moreover, the analysis of Cdk1Liv-/- mouse livers showed that MetaboKit can identify a wide range of lipid species and their ISFs, and quantitatively reconstitute the well-characterized fatty liver phenotype in these mice. In DIA data, the MS1-level and MS2-level peak area data produced similar fold change estimates in the differential abundance analysis, and the MS2-level peak area data allowed for quantitative comparisons in compounds whose precursor ion chromatogram was too noisy for peak integration. Standard mixture assay is reported in the current study <a href='https://www.ebi.ac.uk/metabolights/MTBLS1311' rel='noopener noreferrer' target='_blank'>MTBLS1311</a>.Mouse liver assays are reported in <a href='https://www.ebi.ac.uk/metabolights/MTBLS1266' rel='noopener noreferrer' target='_blank'>MTBLS1266</a>.