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Detecting and removing data artifacts in Hadamard transform ion mobility-mass spectrometry measurements.

ABSTRACT: Applying Hadamard transform multiplexing to ion mobility separations (IMS) can significantly improve the signal-to-noise ratio and throughput for IMS coupled mass spectrometry (MS) measurements by increasing the ion utilization efficiency. However, it has been determined that fluctuations in ion intensity as well as spatial shifts in the multiplexed data lower the signal-to-noise ratios and appear as noise in downstream processing of the data. To address this problem, we have developed a novel algorithm that discovers and eliminates data artifacts. The algorithm employs an analytical approach to identify and remove artifacts from the data, decreasing the likelihood of false identifications in subsequent data processing. Following application of the algorithm, IMS-MS measurement sensitivity is greatly increased and artifacts that previously limited the utility of applying the Hadamard transform to IMS are avoided. Figure ?

SUBMITTER: Prost SA

PROVIDER: S-EPMC4223016 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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Detecting and removing data artifacts in Hadamard transform ion mobility-mass spectrometry measurements.

Prost Spencer A SA Crowell Kevin L KL Baker Erin S ES Ibrahim Yehia M YM Clowers Brian H BH Monroe Matthew E ME Anderson Gordon A GA Smith Richard D RD Payne Samuel H SH

Journal of the American Society for Mass Spectrometry 20140506 12

Applying Hadamard transform multiplexing to ion mobility separations (IMS) can significantly improve the signal-to-noise ratio and throughput for IMS coupled mass spectrometry (MS) measurements by increasing the ion utilization efficiency. However, it has been determined that fluctuations in ion intensity as well as spatial shifts in the multiplexed data lower the signal-to-noise ratios and appear as noise in downstream processing of the data. To address this problem, we have developed a novel a ...[more]

PMID: 24796262

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Project description:Metabolomics is an interdisciplinary field that aims to study all metabolites < 1500 Da that are ubiquitously found within all organisms. Metabolomics is experiencing exponential growth and commonly relies on high-resolution mass spectrometry (HRMS). Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is a form of HRMS that is particularly well suited for metabolomics research due to its exceptionally high resolution (105-106) and sensitivity with a mass accuracy in parts per billion (ppb). In this regard, FT-ICR-MS can provide valuable insights into the metabolomics analysis of complex biological systems due to unique capabilities such as the easy separation of isobaric and isomeric species, isotopic fine structure analysis, spatial resolution of metabolites in cells and tissues, and a high confidence (<1 ppm mass error) in metabolite identification. Alternatively, the large and complex data sets, long acquisition times, high cost, and limited access mainly through national mass spectrometry facilities may impede the routine adoption of FT-ICR-MS by metabolomics researchers. This review examines recent applications of FT-ICR-MS metabolomics in the search for clinical and non-human biomarkers; for the analysis of food, beverage, and environmental samples; and for the high-resolution imaging of tissues and other biological samples. We provide recent examples of metabolomics studies that highlight the advantages of FT-ICR-MS for the detailed and reliable characterization of the metabolome. Additionally, we offer some practical considerations for implementing FT-ICR-MS into a research program by providing a list of FT-ICR-MS facilities and by identifying different high-throughput interfaces, varieties of sample types, analysis methods (e.g., van Krevelen diagrams, Kendrick mass defect plot, etc.), and sample preparation and handling protocols used in FT-ICR-MS experiments. Overall, FT-ICR-MS holds great promise as a vital research tool for advancing metabolomics investigations.

Dataset Information

Detecting and removing data artifacts in Hadamard transform ion mobility-mass spectrometry measurements.

Publications

Detecting and removing data artifacts in Hadamard transform ion mobility-mass spectrometry measurements.

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