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Evaluation of intensity drift correction strategies using MetaboDrift, a normalization tool for multi-batch metabolomics data.

ABSTRACT: In recent years, mass spectrometry-based metabolomics has increasingly been applied to large-scale epidemiological studies of human subjects. However, the successful use of metabolomics in this context is subject to the challenge of detecting biologically significant effects despite substantial intensity drift that often occurs when data are acquired over a long period or in multiple batches. Numerous computational strategies and software tools have been developed to aid in correcting for intensity drift in metabolomics data, but most of these techniques are implemented using command-line driven software and custom scripts which are not accessible to all end users of metabolomics data. Further, it has not yet become routine practice to assess the quantitative accuracy of drift correction against techniques which enable true absolute quantitation such as isotope dilution mass spectrometry. We developed an Excel-based tool, MetaboDrift, to visually evaluate and correct for intensity drift in a multi-batch liquid chromatography - mass spectrometry (LC-MS) metabolomics dataset. The tool enables drift correction based on either quality control (QC) samples analyzed throughout the batches or using QC-sample independent methods. We applied MetaboDrift to an original set of clinical metabolomics data from a mixed-meal tolerance test (MMTT). The performance of the method was evaluated for multiple classes of metabolites by comparison with normalization using isotope-labeled internal standards. QC sample-based intensity drift correction significantly improved correlation with IS-normalized data, and resulted in detection of additional metabolites with significant physiological response to the MMTT. The relative merits of different QC-sample curve fitting strategies are discussed in the context of batch size and drift pattern complexity. Our drift correction tool offers a practical, simplified approach to drift correction and batch combination in large metabolomics studies.

SUBMITTER: Thonusin C

PROVIDER: S-EPMC5788449 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Evaluation of intensity drift correction strategies using MetaboDrift, a normalization tool for multi-batch metabolomics data.

Thonusin Chanisa C IglayReger Heidi B HB Soni Tanu T Rothberg Amy E AE Burant Charles F CF Evans Charles R CR

Journal of chromatography. A 20170909

In recent years, mass spectrometry-based metabolomics has increasingly been applied to large-scale epidemiological studies of human subjects. However, the successful use of metabolomics in this context is subject to the challenge of detecting biologically significant effects despite substantial intensity drift that often occurs when data are acquired over a long period or in multiple batches. Numerous computational strategies and software tools have been developed to aid in correcting for intens ...[more]

PMID: 28927937

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Project description:Total internal reflection fluorescence microscopy (TIRFM) is becoming an increasingly common methodology to narrow the illumination excitation thickness to study cellular process such as exocytosis, endocytosis, and membrane dynamics. It is also frequently used as a method to improve signal/noise in other techniques such as in vitro single-molecule imaging, stochastic optical reconstruction microscopy/photoactivated localization microscopy imaging, and fluorescence resonance energy transfer imaging. The unique illumination geometry of TIRFM also enables a distinct method to create an excitation field for selectively exciting fluorophores that are aligned either parallel or perpendicular to the optical axis. This selectivity has been used to study orientation of cell membranes and cellular proteins. Unfortunately, the coherent nature of laser light, the typical excitation source in TIRFM, often creates spatial interference fringes across the illuminated area. These fringes are particularly problematic when imaging large cellular areas or when accurate quantification is necessary. Methods have been developed to minimize these fringes by modulating the TIRFM field during a frame capture period; however, these approaches eliminate the possibility to simultaneously excite with a specific polarization. A new, to our knowledge, technique is presented, which compensates for spatial fringes while simultaneously permitting rapid image acquisition of both parallel and perpendicular excitation directions in ~25 ms. In addition, a back reflection detection scheme was developed that enables quick and accurate alignment of the excitation laser. The detector also facilitates focus drift compensation, a common problem in TIRFM due to the narrow excitation depth, particularly when imaging over long time courses or when using a perfusion flow chamber. The capabilities of this instrument were demonstrated by imaging membrane orientation using DiO on live cells and on lipid bilayers that were supported on a glass slide (supported lipid bilayer). The use of the approach to biological problems was illustrated by examining the temporal and spatial dynamics of exocytic vesicles.

Dataset Information

Evaluation of intensity drift correction strategies using MetaboDrift, a normalization tool for multi-batch metabolomics data.

Publications

Evaluation of intensity drift correction strategies using MetaboDrift, a normalization tool for multi-batch metabolomics data.

Similar Datasets

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