Strategy for Optimizing LC-MS Data Processing in Metabolomics: A Design of Experiments Approach

Eliasson, Mattias; Rännar, Stefan; Madsen, Rasmus Bødker; Donten, Magdalena; Marsden-Edwards, Emma; Moritz, Thomas; Shockcor, John P.; Johansson, Erik; Trygg, Johan

doi:10.1021/ac301482k

Cited by 97 publications

(79 citation statements)

References 15 publications

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“…Typical DoE workflows start with screening objectives, where the most important factors and their appropriate ranges are chosen and subsequently optimized iteratively. DoE has been used in optimizing other steps of the typical metabolomics workflow, including sample preparation and data processing (A et al 2005; Eliasson et al 2012; Zheng et al 2013). LC-MS methods have also been improved in this manner, however the response of interest has typically been targeted to one metabolite or a single class of compounds (Zhou et al 2009; Székely et al 2012; Kostić et al 2013; Riter et al 2005).…”

Section: Introductionmentioning

confidence: 99%

Comprehensive optimization of LC–MS metabolomics methods using design of experiments (COLMeD)

Rhoades

Weljie

2016

Metabolomics

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Introduction Both reverse-phase and HILIC chemistries are deployed for liquid-chromatography mass spectrometry (LC-MS) metabolomics analyses, however HILIC methods lag behind reverse-phase methods in reproducibility and versatility. Comprehensive metabolomics analysis is additionally complicated by the physiochemical diversity of metabolites and array of tunable analytical parameters. Objective Our aim was to rationally and efficiently design complementary HILIC-based polar metabolomics methods on multiple instruments using Design of Experiments (DoE). Methods We iteratively tuned LC and MS conditions on ion-switching triple quadrupole (QqQ) and quadrupole-time-of-flight (qTOF) mass spectrometers through multiple rounds of a workflow we term COLMeD (Comprehensive optimization of LC-MS metabolomics methods using design of experiments). Multivariate statistical analysis guided our decision process in the method optimizations. Results LC-MS/MS tuning for the QqQ method on serum metabolites yielded a median response increase of 161.5% (p<0.0001) over initial conditions with a 13.3% increase in metabolite coverage. The COLMeD output was benchmarked against two widely used polar metabolomics methods, demonstrating total ion current increases of 105.8% and 57.3%, with median metabolite response increases of 106.1% and 10.3% (p<0.0001 and p<0.05 respectively). For our optimized qTOF method, 22 solvent systems were compared on a standard mix of physiochemically diverse metabolites, followed by COLMeD optimization, yielding a median 29.8% response increase (p<0.0001) over initial conditions. Conclusions The COLMeD process elucidated response tradeoffs, facilitating improved chromatography and MS response without compromising separation of isobars. COLMeD is efficient, requiring no more than 20 injections in a given DoE round, and flexible, capable of class-specific optimization as demonstrated through acylcarnitine optimization within the QqQ method.

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Section: Introductionmentioning

confidence: 99%

Comprehensive optimization of LC–MS metabolomics methods using design of experiments (COLMeD)

Rhoades

Weljie

2016

Metabolomics

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“…The standardization of data preprocessing based on bioinformatics expertise is necessary to ensure a robust methodology [190][191][192][193]. The main risk of high-throughput exploration is the management of big and complex data which needs to be simplified without loss of relevant data.…”

Section: Expert Commentarymentioning

confidence: 99%

Further development of biomarkers in amyotrophic lateral sclerosis

Blasco

Vourc’h

et al. 2016

Expert Review of Molecular Diagnostics

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In this review, we specifically focus on biology and imaging markers. We detail the innovative field of 'omics' approach and imaging and explain their limits to be useful in routine practice. We describe the most relevant biomarkers and suggest some perspectives for biomarker research. Expert commentary: The successive failures of clinical trials in ALS underline the need for new strategy based on innovative tools to stratify patients and to evaluate their responses to treatment. Biomarker data may be useful to improve the designs of clinical trials. Biomarkers are also needed to better investigate disease pathophysiology, to identify new therapeutic targets, and to improve the performance of clinical assessments for diagnosis and prognosis in the clinical setting. A consensus on the best management of neuroimaging and 'omics' methods is necessary and a systematic independent validation of findings may add robustness to future studies.

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“…The experimental design, extraction and data acquisition methods depend on the aim of the investigation, on the material used for analysis and the available instrumentation [16]. Several recent studies have considered the challenge of data processing in untargeted metabolomics, which has benefited enormously from the development of automated procedures [15, 17]. Recent data-processing tools such as MetAlign (http://www.metalign.wur.nl), MZmine (http://mzmine.sourceforge.net/) and XCMS (http://metlin.scripps.edu/download/) [18] are designed to extract relevant information automatically from batches of crude chromatographic data, allowing the rapid processing of thousands of data points, which transforms the concept of untargeted metabolomics into practical reality.…”

Section: ) Lc-ms Untargeted Metabolomics Allows the Comprehensive Anmentioning

confidence: 99%

Untargeted Metabolomics: An Emerging Approach to Determine the Composition of Herbal Products

Commisso

Strazzer

Toffali

et al. 2013

Computational and Structural Biotechnology Journal

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Natural remedies, such as those based on traditional Chinese medicines, have become more popular also in western countries over the last 10 years. The composition of these herbal products is largely unknown and difficult to determine. Moreover, since plants respond to their environment changing the metabolome, the composition of plant material can vary depending on the plant growth conditions.However, there is a growing need of a deeper knowledge on such natural remedies also in view of the growing number of reports of toxicity following the consumption of herbal supplements. Untargeted metabolomics is a useful approach for the simultaneous analysis of many compounds in herbal products. In particular, liquid chromatography/mass spectrometry (LC-MS) can determine presence, amount and sometime structures of plant metabolites in complex herbal mixtures, with significant advantages over techniques such as nuclear magnetic resonance (NMR) spectroscopy and gas chromatography/mass spectrometry (GC-MS).

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Strategy for Optimizing LC-MS Data Processing in Metabolomics: A Design of Experiments Approach

Cited by 97 publications

References 15 publications

Comprehensive optimization of LC–MS metabolomics methods using design of experiments (COLMeD)

Comprehensive optimization of LC–MS metabolomics methods using design of experiments (COLMeD)

Further development of biomarkers in amyotrophic lateral sclerosis

Untargeted Metabolomics: An Emerging Approach to Determine the Composition of Herbal Products

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