Hybrid Data Acquisition and Processing Strategies with Increased Throughput and Selectivity: pSMART Analysis for Global Qualitative and Quantitative Analysis

Prakash, Amol; Peterman, Scott; Ahmad, Shadab; Sarracino, David; Frewen, Barbara; Vogelsang, Maryann S.; Byram, Gregory; Krastins, Bryan; Vadali, Gouri; Lopez, Mary F.

doi:10.1021/pr5003017

Cited by 44 publications

(48 citation statements)

References 35 publications

(90 reference statements)

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“…22), and alternative approaches such as the MSX method 12 . The highly flexible design of the DIA-Umpire computational framework (importantly, with a full support for MS1 feature detection and quantification) should allow us to quickly adapt the algorithms to take advantage of new approaches and technological improvements, including emerging hybrid DIA/DDA strategies 38 . Finally, the pseudo MS/MS spectra generated by DIA-Umpire can be used to build spectral libraries for use with external tools, e.g.…”

Section: Discussionmentioning

confidence: 99%

DIA-Umpire: comprehensive computational framework for data-independent acquisition proteomics

et al. 2015

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Due to recent improvements in mass spectrometry (MS), there is an increased interest in data independent acquisition (DIA) strategies in which all peptides are systematically fragmented using wide mass isolation windows (“multiplex fragmentation”). DIA-Umpire (http://diaumpire.sourceforge.net/), a comprehensive computational workflow and open-source software for DIA data, detects precursor and fragment chromatographic features and assembles them into pseudo MS/MS spectra. These spectra can be identified using conventional database searching and protein inference tools, allowing sensitive untargeted analysis of DIA data without the need for a spectral library. Quantification is obtained using both precursor and fragment ion intensities. Furthermore, DIA-Umpire enables targeted extraction of quantitative information based on peptides initially identified in only a subset of the samples, resulting in more consistent quantification across multiple samples. We demonstrate the performance of the method using control samples of varying complexity, and publicly available glycoproteomics and affinity purification - mass spectrometry data.

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Section: Discussionmentioning

confidence: 99%

DIA-Umpire: comprehensive computational framework for data-independent acquisition proteomics

et al. 2015

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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

329

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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“…All precursor ions are fragmented into product ions which can be employed as detection ions (transitions). Using this approach, a nearly complete digital display of the trypsin digestion of biological samples can be obtained, as also described earlier …”

Section: Introductionmentioning

confidence: 99%

Data‐independent acquisition‐based quantitative proteomic analysis reveals differences in host immune response of peripheral blood mononuclear cells to sepsis

Tong

et al. 2019

Scand J Immunol

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This study was aimed to uncover proteins that are differentially expressed in sepsis. Data‐independent acquisition (DIA) was used for analysis to identify differentially expressed proteins in peripheral blood mononuclear cells (PBMCs) of patients. A total of 24 non‐septic intensive care unit (ICU) patients, 11 septic shock patients and 27 patients diagnosed with sepsis were recruited for the mass spectrometry (MS) discovery. PBMCs were isolated from routine blood samples and digested into peptides. A DIA workflow was developed using a quadrupole‐Orbitrap liquid chromatography LC‐MS system, and mass spectra peaks were extracted by Skyline software. Orthogonal partial least‐squares discriminant analysis (OPLS‐DA) and partial least‐squares discriminant analysis (PLS‐DA) were applied to distinguish the patient groups at the level of fragment ion and peptide. Differentially expressed proteins in the patient groups were verified by enzyme‐linked immunosorbent assay (ELISA). Receiver‐operating characteristic (ROC) curves were used to evaluate the protein expression. A total of 1062 fragment ions and 122 proteins were identified in the MS‐DIA analysis conducted by Skyline software. Using gene ontology clustering analysis, we discovered that 51 of the 122 identified proteins were associated with biological processes, including carbon metabolism, biosynthesis of antibiotics, platelet activation, bacterial invasion of epithelial cells and complement, and coagulation cascades. Among them, five proteins (high‐mobility group box1 [HMGB1], matrix metalloproteinase 8 [MMP8], neutrophil gelatinase‐associated lipocalin [NGAL], lactotransferrin [LTF] and grancalcin [GCA]) were identified by ELISA as closely related to the development of sepsis. The ROC curves displayed good sensitivity and specificity.

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Hybrid Data Acquisition and Processing Strategies with Increased Throughput and Selectivity: pSMART Analysis for Global Qualitative and Quantitative Analysis

Cited by 44 publications

References 35 publications

DIA-Umpire: comprehensive computational framework for data-independent acquisition proteomics

DIA-Umpire: comprehensive computational framework for data-independent acquisition proteomics

Identification of small molecules using accurate mass MS/MS search

Data‐independent acquisition‐based quantitative proteomic analysis reveals differences in host immune response of peripheral blood mononuclear cells to sepsis

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