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Rapid Development of Improved Data-Dependent Acquisition Strategies.

ABSTRACT: Tandem mass spectrometry (LC-MS/MS) is widely used to identify unknown ions in untargeted metabolomics. Data-dependent acquisition (DDA) chooses which ions to fragment based upon intensities observed in MS1 survey scans and typically only fragments a small subset of the ions present. Despite this inefficiency, relatively little work has addressed the development of new DDA methods, partly due to the high overhead associated with running the many extracts necessary to optimize approaches in busy MS facilities. In this work, we first provide theoretical results that show how much improvement is possible over current DDA strategies. We then describe an in silico framework for fast and cost-efficient development of new DDA strategies using a previously developed virtual metabolomics mass spectrometer (ViMMS). Additional functionality is added to ViMMS to allow methods to be used both in simulation and on real samples via an Instrument Application Programming Interface (IAPI). We demonstrate this framework through the development and optimization of two new DDA methods that introduce new advanced ion prioritization strategies. Upon application of these developed methods to two complex metabolite mixtures, our results show that they are able to fragment more unique ions than standard DDA strategies.

SUBMITTER: Davies V

PROVIDER: S-EPMC8047769 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundDedicated cone-beam breast computed tomography (CBBCT) using short-scan acquisition is being actively investigated to potentially reduce the radiation dose to the breast. This would require determining the optimal x-ray source trajectory for such short-scan acquisition.PurposeTo quantify the projection angle-dependent normalized glandular dose coefficient ( DgNCT$Dg{N^{CT}}$ ) in CBBCT, referred to as angular DgNCT$Dg{N^{CT}}$ , so that the x-ray ray source trajectory that minimizes the radiation dose to the breast for short-scan acquisition can be determined.Materials and methodsA cohort of 75 CBBCT clinical datasets was segmented and used to generate three breast models - (I) patient-specific breast with heterogeneous fibroglandular tissue distribution and real breast shape, (II) patient-specific breast shape with homogeneous tissue distribution and matched fibroglandular weight fraction, and (III) homogeneous semi-ellipsoidal breast with patient-specific breast dimensions and matched fibroglandular weight fraction, which corresponds to the breast model used in current radiation dosimetry protocols. For each clinical dataset, the angular DgNCT$Dg{N^{CT}}$ was obtained at 10 discrete angles, spaced 36° apart, for full-scan, circular, x-ray source trajectory from Monte Carlo simulations. Model III is used for validating the Monte Carlo simulation results. Models II and III are used to determine if breast shape contributes to the observed trends in angular DgNCT$Dg{N^{CT}}$ . A geometry-based theory in conjunction with center-of-mass ( COM$COM$ ) based distribution analysis is used to explain the projection angle-dependent variation in angular DgNCT$Dg{N^{CT}}$ .ResultsThe theoretical model predicted that the angular DgNCT$Dg{N^{CT}}$ will follow a sinusoidal pattern and the amplitude of the sinusoid increases when the center-of-mass of fibroglandular tissue ( COMf$CO{M_f}$ ) is farther from the center-of-mass of the breast ( COMb$CO{M_b}$ ). It also predicted that the angular DgNCT$Dg{N^{CT}}$ will be minimized at x-ray source positions complementary to the COMf$CO{M_f}$ . The COMf$CO{M_f}$ was superior to the COMb$CO{M_b}$ in 80% (60/75) of the breasts. From Monte Carlo simulations and for homogeneous breasts (models II and III), the deviation in breast shape from a semi-ellipsoid had minimal effect on angular DgNCT$Dg{N^{CT}}$ and showed less than 4% variation. From Monte Carlo simulations and for model I, as predicted by our theory, the angular DgNCT$Dg{N^{CT}}$ followed a sinusoidal pattern with maxima and minima at x-ray source positions superior and inferior to the breast, respectively. For model I, the projection angle-dependent variation in angular DgNCT$Dg{N^{CT}}$ was 16.4%.ConclusionThe heterogeneous tissue distribution affected the angular DgNCT$Dg{N^{CT}}$ more than the breast shape. For model I, the angular DgNCT$Dg{N^{CT}}$ was lowest when the x-ray source was inferior to the breast. Hence, for short-scan CBBCT acquisition with COMb$CO{M_b}$ aligned with axis-of-rotation, an x-ray source trajectory inferior to the breast is preferable and such an acquisition spanning 205° can potentially reduce the mean glandular dose by up to 52%.

Project description:Quantitative proteomics strategies - which are playing important roles in the expanding field of plant molecular systems biology - are traditionally designated as either hypothesis driven or non-hypothesis driven. Many of these strategies aim to select individual peptide ions for tandem mass spectrometry (MS/MS), and to do this mixed hypothesis driven and non-hypothesis driven approaches are theoretically simple to implement. In-depth investigations into the efficacies of such approaches have, however, yet to be described. In this study, using combined samples of unlabeled and metabolically 15N-labeled Arabidopsis thaliana proteins, we investigate the mixed use of targeted data acquisition (TDA) and data dependent acquisition (DDA) - referred to as TDA/DDA - to facilitate both hypothesis driven and non-hypothesis driven quantitative data collection in individual LC-MS/MS experiments. To investigate TDA/DDA for hypothesis driven data collection, 7 miRNA target proteins of differing size and abundance were targeted using inclusion lists comprised of 1558 m/z values, using 3 different TDA/DDA experimental designs. In samples in which targeted peptide ions were of particularly low abundance (i.e., predominantly only marginally above mass analyser detection limits), TDA/DDA produced statistically significant increases in the number of targeted peptides identified (230 ± 8 versus 80 ± 3 for DDA; p = 1.1 × 10-3) and quantified (35 ± 3 versus 21 ± 2 for DDA; p = 0.038) per experiment relative to the use of DDA only. These expected improvements in hypothesis driven data collection were observed alongside unexpected improvements in non-hypothesis driven data collection. Untargeted peptide ions with m/z values matching those in inclusion lists were repeatedly identified and quantified across technical replicate TDA/DDA experiments, resulting in significant increases in the percentages of proteins repeatedly quantified in TDA/DDA experiments only relative to DDA experiments only (33.0 ± 2.6% versus 8.0 ± 2.7%, respectively; p = 0.011). These results were observed together with uncompromised broad-scale MS/MS data collection in TDA/DDA experiments relative to DDA experiments. Using our observations we provide guidelines for TDA/DDA method design for quantitative plant proteomics studies, and suggest that TDA/DDA is a broadly underutilized proteomics data acquisition strategy.

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Rapid Development of Improved Data-Dependent Acquisition Strategies.

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