DIANA—algorithmic improvements for analysis of data-independent acquisition MS data

Teleman, Johan; Röst, Hannes L.; Rosenberger, George; Schmitt, Uwe; Malmström, Lars; Malmström, Johan; Levander, Fredrik

doi:10.1093/bioinformatics/btu686

Cited by 99 publications

(103 citation statements)

References 37 publications

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“…SWATH/DIA data were analyzed via targeted, peptide‐centric analysis, querying 204,545 precursors based on the combined human assay library (CAL; Rosenberger et al , ) in the SWATH fragment ion chromatograms, using a modified OpenSWATH (Röst et al , ), PyProphet (Reiter et al , ; Teleman et al , ), and TRIC (Röst et al , ) workflow and the iPortal framework (Kunszt et al , ). Specifically, a global PyProphet scoring function was trained on a master sample of the unfractionated HEK293 lysate with tryptic digest and SWATH/DIA data acquisition equivalent to the fractionated samples.…”

Section: Methodsmentioning

confidence: 99%

Complex‐centric proteome profiling by SEC ‐ SWATH ‐ MS

Heusel

Bludau

Rosenberger

et al. 2019

Molecular Systems Biology

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114

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Proteins are major effectors and regulators of biological processes that can elicit multiple functions depending on their interaction with other proteins. The organization of proteins into macromolecular complexes and their quantitative distribution across these complexes is, therefore, of great biological and clinical significance. In this paper, we describe an integrated experimental and computational technique to quantify hundreds of protein complexes in a single operation. The method consists of size exclusion chromatography (SEC) to fractionate native protein complexes, SWATH/DIA mass spectrometry to precisely quantify the proteins in each SEC fraction, and the computational framework CCprofiler to detect and quantify protein complexes by error‐controlled, complex‐centric analysis using prior information from generic protein interaction maps. Our analysis of the HEK293 cell line proteome delineates 462 complexes composed of 2,127 protein subunits. The technique identifies novel sub‐complexes and assembly intermediates of central regulatory complexes while assessing the quantitative subunit distribution across them. We make the toolset CCprofiler freely accessible and provide a web platform, SECexplorer, for custom exploration of the HEK293 proteome modularity.

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Section: Methodsmentioning

confidence: 99%

Complex‐centric proteome profiling by SEC ‐ SWATH ‐ MS

Heusel

Bludau

Rosenberger

et al. 2019

Molecular Systems Biology

Self Cite

124

114

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“…The SWATH data was analyzed using OpenSWATH (version 29995b387c238fdc58b 195b0390aadcb2b355aa6) (31) with the following parameters: Chromatograms were extracted with 50 ppm around the expected mass of the fragment ions and with an extraction window of Ϯ5 min around the expected retention time after iRT alignment. The best model to separate true from false positives (per run) was determined by pyprophet (version 0.9.1) with 10 cross-validation runs (42). The pyprophet software re-implements the mProphet algorithm (43), which uses target and decoy signals to compute an optimal discriminant score which is then applied to all peak groups.…”

Section: Methodsmentioning

confidence: 99%

Systems-level Proteomics of Two Ubiquitous Leaf Commensals Reveals Complementary Adaptive Traits for Phyllosphere Colonization

Müller

Schubert

Röst

et al. 2016

Molecular & Cellular Proteomics

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Plants are colonized by a diverse community of microorganisms, the plant microbiota, exhibiting a defined and conserved taxonomic structure. Niche separation based on spatial segregation and complementary adaptation strategies likely forms the basis for coexistence of the various microorganisms in the plant environment. To gain insights into organism-specific adaptations on a molecular level, we selected two exemplary community members of the core leaf microbiota and profiled their proteomes upon Arabidopsis phyllosphere colonization. The highly quantitative mass spectrometric technique SWATH MS was used and allowed for the analysis of over two thousand proteins spanning more than three orders of magnitude in abundance for each of the model strains. The data suggest that Sphingomonas melonis utilizes amino acids and hydrocarbon compounds during colonization of leaves whereas Methylobacterium extorquens relies on methanol metabolism in addition to oxalate metabolism, aerobic anoxygenic photosynthesis and alkanesulfonate utilization. Comparative genomic analyses indicates that utilization of oxalate and alkanesulfonates is widespread among leaf microbiota members whereas, aerobic anoxygenic photosynthesis is almost exclusively found in Methylobacteria. Despite the apparent niche separation between these two strains we also found a relatively small subset of proteins to be coregulated, indicating common mechanisms, underlying successful leaf colonization. Overall, our results reveal for two ubiquitous phyllosphere commensals speciesspecific adaptations to the host environment and provide evidence for niche separation within the plant microbiota. Molecular & Cellular Proteomics 15: 10.1074/mcp.M116.058164, 3256-3269, 2016.

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“…Therefore, it is important for the deconvolution to acquire a sufficiently large number of MS/MS data points across chromatographic peaks. Other software tools such as OpenSWATH, DIANA, pSMART, Biognosys Spectronaut, or DIA‐Umpire are targeted toward the proteomics community and cannot be directly used for small molecule identifications for two reasons: first, in proteomics, SWATH‐MS/MS‐based identification relies solely on the MS/MS data. The fact that precursor ions are isolated with narrow Q1 isolation windows helps reducing the complexity of MS/MS spectra but MS 1 information about the precursor ions is not used at all.…”

Section: Instrumental Settings For Tandem Mass Spectrometersmentioning

confidence: 99%

Identification of small molecules using accurate mass MS/MS search

Kind

Tsugawa

Čajka

et al. 2017

Mass Spectrometry Reviews

356

325

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Tandem mass spectral library search (MS/MS) is the fastest way to correctly annotate MS/MS spectra from screening small molecules in fields such as environmental analysis, drug screening, lipid analysis, and metabolomics. The confidence in MS/MS-based annotation of chemical structures is impacted by instrumental settings and requirements, data acquisition modes including data-dependent and data-independent methods, library scoring algorithms, as well as post-curation steps. We critically discuss parameters that influence search results, such as mass accuracy, precursor ion isolation width, intensity thresholds, centroiding algorithms, and acquisition speed. A range of publicly and commercially available MS/MS databases such as NIST, MassBank, MoNA, LipidBlast, Wiley MSforID, and METLIN are surveyed. In addition, software tools including NIST MS Search, MS-DIAL, Mass Frontier, SmileMS, Mass++, and XCMS to perform fast MS/MS search are discussed. MS/MS scoring algorithms and challenges during compound annotation are reviewed. Advanced methods such as the in silico generation of tandem mass spectra using quantum chemistry and machine learning methods are covered. Community efforts for curation and sharing of tandem mass spectra that will allow for faster distribution of scientific discoveries are discussed.

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DIANA—algorithmic improvements for analysis of data-independent acquisition MS data

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 99 publications

References 37 publications

Complex‐centric proteome profiling by SEC ‐ SWATH ‐ MS

Complex‐centric proteome profiling by SEC ‐ SWATH ‐ MS

Systems-level Proteomics of Two Ubiquitous Leaf Commensals Reveals Complementary Adaptive Traits for Phyllosphere Colonization

Identification of small molecules using accurate mass MS/MS search

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