LC‐MS Data Processing with MAVEN: A Metabolomic Analysis and Visualization Engine

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Abstract
Table of Contents
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Abstract

MAVEN is an open?source software program for interactive processing of LC?MS?based metabolomics data. MAVEN enables rapid and reliable metabolite quantitation from multiple reaction monitoring data or high?resolution full?scan mass spectrometry data. It automatically detects and reports peak intensities for isotope?labeled metabolites. Menu?driven, click?based navigation allows visualization of raw and analyzed data. Here we provide a User Guide for MAVEN. Step?by?step instructions are provided for data import, peak alignment across samples, identification of metabolites that differ strongly between biological conditions, quantitation and visualization of isotope?labeling patterns, and export of tables of metabolite?specific peak intensities. Together, these instructions describe a workflow that allows efficient processing of raw LC?MS data into a form ready for biological analysis. Curr. Protoc. Bioinform. 37:14.11.1?14.11.23. © 2012 by John Wiley & Sons, Inc.

Keywords: metabolomics; liquid chromatography?mass spectrometry; pathway visualization and mapping; stable isotope labeling; metabolic flux analysis; kinetic flux profiling

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Introduction
Strategic Planning
Basic Protocol 1: Loading LC‐MS Data into MAVEN
Basic Protocol 2: Peak Alignment and Visualization
Basic Protocol 3: Untargeted Analysis of Full‐Scan LC‐MS Data
Basic Protocol 4: Targeted Metabolite Quantitation
Basic Protocol 5: Targeted Analysis of Full‐Scan LC‐MS Data with Isotopic Labeling
Guidelines for Understanding Results
Commentary
Literature Cited
Figures

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Materials

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Figures

Figure 14.11.1 MAVEN workflow. Multiple cycles of peak detection, grouping, quality scoring, and alignment may be performed prior to biological analyses such as pathway‐based data visualization. The user can easily navigate back‐and‐forth from raw data analysis to biological analyses. Validated data tables can be readily exported to other software.

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Figure 14.11.2 Chromatographic alignment of data is accomplished within MAVEN by selecting high‐intensity peaks, grouping across samples, then iteratively fitting a nonlinear retention time model.

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Figure 14.11.3 Basic MAVEN interface, where loaded samples are displayed in the samples tab, and glucose 6‐phosphate and its isomers have been extracted with a 7.5‐ppm window.

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Figure 14.11.4 Peak Detection box in MAVEN and associated user settings.

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Figure 14.11.5 Generating a scatter plot to compare groups. (A ) Rename Set name in Samples tab to reflect sample groupings. (B ) Adjust parameters for pair‐wise comparison of grouped data. (C ) View results as scatter plot, where the size of each circle represents the fold change between the two samples sets.

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Figure 14.11.6 Sample spectrum displaying isotopic pattern associated with highlighted peak of interest from Figure C. Δ m / z between ¹² C and ¹³ C peaks is close to the expected value of 1.003355. The intensity of the ¹³ C peak is displayed (5.78%).

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Figure 14.11.7 Known metabolite quantitation from a preloaded compound list. The remainder of the detection parameters are depicted in Figure , and described in , steps 2 to 7.

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Figure 14.11.8 Rapid manual peak group acceptance or rejection (categorization as “good” or “bad”) within a list of peak groups corresponding to known metabolite m / z . The EICs displayed correspond to the highlighted row in the compound list. Clicking the green check mark or red X within the EIC window will designate the peak group as good or bad.

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Figure 14.11.9 Retraining MAVEN's neural network model for peak quality scoring. Prior to re‐training, it is necessary to manually designate at least 100 peak groups as “good” or “bad.” (A ) Window as it appears before training. The neural network algorithm assigns a probability of being “good” to each peak group. False negatives (FN) are peak groups that the user designated as “good” that receive a probability <0.5; true positives (TP) are designated good peak groups and that receive a probability >0.5; true negatives (TN) are designated bad peak groups and receive a probability <0.5; and false positives (FP) are designated bad peak groups that receive a probability >0.5. (B ) Training accuracy is reflected in the FN, TP, TN, FP, and % accuracy scores.

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Figure 14.11.10 Metabolic pathway map with pie charts indicating the extent of incorporation of uniformly ¹³ C labeled glucose into glycolytic metabolites. Unlabeled metabolites are depicted in blue, and the sums of all labeled forms are depicted in red. The sample name is listed adjacent to the slide bar.

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Figure 14.11.11 MAVEN screenshot displaying isotope labeling. In this example, yeast were switched from unlabeled to uniformly ¹³ C‐labeled glucose. Data shown are for fructose 1,6‐bisphosphate (FBP) from yeast expressing either the normal (wt) or a decreased (DAmP) concentration of the enzyme responsible for the reversible reaction between FBP and two triose phosphates, fructose bisphosphate aldolase (encoded by fba1 ). The bar chart with the cursor on it provides information on the extent of isotope labeling. Upon mousing over the orange bar, MAVEN reveals that it reflects the ¹³ C₃ ‐ form of FBP. This form is uniquely abundant at earlier time points in the wt strain, consistent with reverse aldolase flux joining together one labeled and one unlabeled triose.

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