Rapid development of improved data-dependent acquisition strategies

Davies, V. , Wandy, J., Weidt, S., van der Hooft, J. J.J. , Miller, A. , Daly, R. and Rogers, S. (2021) Rapid development of improved data-dependent acquisition strategies. Analytical Chemistry, 93(14), pp. 5676-5683. (doi: 10.1021/acs.analchem.0c03895) (PMID:33784814) (PMCID:PMC8047769)

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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.

Item Type:Articles
Additional Information:V.D., J.W., S.W., R.D., and S.R. acknowledge EPSRC Project EP/R018634/1 on “Closed-loop data science for complex, computationally and data-intensive analytics”. J.J.J.v.d.H. was partly funded by an ASDI eScience Grant, ASDI.2017.030, from The Netherlands eScience Center (NLeSC).
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Weidt, Dr Stefan and Daly, Dr Ronan and Wandy, Dr Joe and Davies, Dr Vinny and Van Der Hooft, Mr Justin and Rogers, Dr Simon and Miller, Professor Alice
Authors: Davies, V., Wandy, J., Weidt, S., van der Hooft, J. J.J., Miller, A., Daly, R., and Rogers, S.
College/School:College of Medical Veterinary and Life Sciences > Institute of Cancer Sciences
College of Medical Veterinary and Life Sciences > Institute of Infection Immunity and Inflammation
College of Science and Engineering > School of Computing Science
Journal Name:Analytical Chemistry
Publisher:American Chemical Society
ISSN:0003-2700
ISSN (Online):1520-6882
Published Online:30 March 2021
Copyright Holders:Copyright © 2021 The Authors
First Published:First published in Analytical Chemistry 93(14): 5676-5683
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
300982Exploiting Closed-Loop Aspects in Computationally and Data Intensive AnalyticsRoderick Murray-SmithEngineering and Physical Sciences Research Council (EPSRC)EP/R018634/1Computing Science