Dataset Information

MaxDIA enables highly sensitive and accurate library-based and library-free data-independent acquisition proteomics (DDA data)

ABSTRACT: MaxDIA is a universal platform for analyzing data-independent acquisition proteomics data within the MaxQuant software environment. Using spectral libraries, MaxDIA achieves cutting-edge proteome coverage with significantly better coefficients of variation in protein quantification than other software. MaxDIA is equipped with accurate false discovery rate estimates on both library-to-DIA match and protein levels, also when using whole-proteome predicted spectral libraries. This is the foundation of discovery DIA – a framework for the hypothesis-free analysis of DIA samples without library and with reliable FDR control. MaxDIA performs three- or four-dimensional feature detection of fragment data and scoring of matches is augmented by machine learning on the features of an identification. MaxDIA’s novel bootstrap-DIA workflow performs multiple rounds of matching with increasing quality of recalibration and stringency of matching to the library. Combining MaxDIA with two new technologies, BoxCar acquisition and trapped ion mobility spectrometry, both lead to deep and accurate proteome quantification.

INSTRUMENT(S): 6410 Triple Quadrupole LC/MS, Q Exactive HF, QSTAR

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

SUBMITTER: Yasset Perez-Riverol

LAB HEAD: Jurgen Cox

PROVIDER: PXD022582 | Pride | 2021-07-09

REPOSITORIES: Pride

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Publications

MaxDIA enables library-based and library-free data-independent acquisition proteomics.

Sinitcyn Pavel P Hamzeiy Hamid H Salinas Soto Favio F Itzhak Daniel D McCarthy Frank F Wichmann Christoph C Steger Martin M Ohmayer Uli U Distler Ute U Kaspar-Schoenefeld Stephanie S Prianichnikov Nikita N Yılmaz Şule Ş Rudolph Jan Daniel JD Tenzer Stefan S Perez-Riverol Yasset Y Nagaraj Nagarjuna N Humphrey Sean J SJ Cox Jürgen J

Nature biotechnology 20210708 12

MaxDIA is a software platform for analyzing data-independent acquisition (DIA) proteomics data within the MaxQuant software environment. Using spectral libraries, MaxDIA achieves deep proteome coverage with substantially better coefficients of variation in protein quantification than other software. MaxDIA is equipped with accurate false discovery rate (FDR) estimates on both library-to-DIA match and protein levels, including when using whole-proteome predicted spectral libraries. This is the fo ...[more]

PMID: 34239088

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Project description:Data independent acquisition (DIA or DIA/SWATH ) mass spectrometry has emerged as a primary measurement strategy in the field of quantitative proteomics. diaPASEF is a recent adaptation that leverages trapped ion mobility spectrometry (TIMS) to improve selectivity and increase sensitivity. The complex fragmentation spectra generated by co-isolation of peptides in DIA mode are most typically analyzed with reference to prior knowledge in the form of spectral libraries. The best established method for generating libraries uses data dependent acquisition (DDA) mode, or DIA mode if appropriately deconvoluted, often including offline fractionation to increase depth of coverage,to create spectral libraries. More recently strategies for spectral library generation based on gas phase fractionation (GPF), where a representative sample is injected serially using narrow window DIA methods designed to cover different slices of the precursor space, have been introduced and performed comparably to deep offline fractionation-based libraries for DIA data analysis. Here, we investigated whether an analogous GPF-based library building approach that accounts for the ion mobility (IM) dimension is useful for the analysis of diaPASEF data and can remove the need for offline fractionation. To enable a rapid library development approach for diaPASEF we designed a GPF acquisition scheme covering the majority of multiply charged precursors in the m/z vs 1/K0 space requiring 7 injections of a representative sample and compared this with libraries generated by direct deconvolution-based analysis of diaPASEF data or by deep offline fractionation and ddaPASEF. . We found that the GPF based library outperformed library generation by direct deconvolution of the diaPASEF data, and performed comparably to deep offline fractionation libraries, when analysing diaPASEF data acquired from 200ng of commercial HeLa digest. With the ion mobility integrated GPF scheme we establish a pragmatic approach to rapid and comprehensive library generation for the analysis of diaPASEF data.

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>.

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. Mouse liver assays are reported in the current study <a href='https://www.ebi.ac.uk/metabolights/MTBLS1266' rel='noopener noreferrer' target='_blank'>MTBLS1266</a>.Standard mixture assay is reported in <a href='https://www.ebi.ac.uk/metabolights/MTBLS1311' rel='noopener noreferrer' target='_blank'>MTBLS1311</a>.

Dataset Information

MaxDIA enables highly sensitive and accurate library-based and library-free data-independent acquisition proteomics (DDA data)

Publications

MaxDIA enables library-based and library-free data-independent acquisition proteomics.

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