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. 2020 Apr 3;19(4):1447-1458.
doi: 10.1021/acs.jproteome.9b00640. Epub 2020 Mar 26.

Skyline for Small Molecules: A Unifying Software Package for Quantitative Metabolomics

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Free PMC article

Skyline for Small Molecules: A Unifying Software Package for Quantitative Metabolomics

Kendra J Adams et al. J Proteome Res. .
Free PMC article

Abstract

Vendor-independent software tools for quantification of small molecules and metabolites are lacking, especially for targeted analysis workflows. Skyline is a freely available, open-source software tool for targeted quantitative mass spectrometry method development and data processing with a 10 year history supporting six major instrument vendors. Designed initially for proteomics analysis, we describe the expansion of Skyline to data for small molecule analysis, including selected reaction monitoring, high-resolution mass spectrometry, and calibrated quantification. This fundamental expansion of Skyline from a peptide-sequence-centric tool to a molecule-centric tool makes it agnostic to the source of the molecule while retaining Skyline features critical for workflows in both peptide and more general biomolecular research. The data visualization and interrogation features already available in Skyline, such as peak picking, chromatographic alignment, and transition selection, have been adapted to support small molecule data, including metabolomics. Herein, we explain the conceptual workflow for small molecule analysis using Skyline, demonstrate Skyline performance benchmarked against a comparable instrument vendor software tool, and present additional real-world applications. Further, we include step-by-step instructions on using Skyline for small molecule quantitative method development and data analysis on data acquired with a variety of mass spectrometers from multiple instrument vendors.

Keywords: Skyline; data analysis; liquid chromatography; metabolite; metabolomics; quantitative; small molecules; tandem mass spectrometry; targeted.

Figures

Figure 1.
Figure 1.
A generalized workflow for small molecule analysis in Skyline
Figure 2.
Figure 2.
Unique Skyline visualizations helpful for data interrogation. Left-hand panes demonstrate a hypothetical example of when incorrect retention time is selected for a single acquisition, while right-hand panes demonstrate correct integration. A) Skyline molecule tree for MTA showing precursor and product ions for the light and heavy isotopes B) retention time replicate display C) chromatogram traces for integrated MTA. The vertical lines indicate where the peak integration was placed D) peak area replicate display E) calibration curve display.
Figure 3.
Figure 3.
Comparison of clinical serum concentrations obtained for 19 amino acids in the Biocrates p180 assay. (A) Correlation of reanalysis of published data using Skyline results (x-axis) versus published concentrations measured in TargetLynx (y-axis) (B) Relative accuracy for each analyte comparing Skyline to published concentrations from TargetLynx, sorted low to high analyte concentration left to right.
Figure 4.
Figure 4.
Method development for custom polyamines assay. A) Comparison of concurrent transition count at different scheduling windows B) utilization of collision energy optimization for two analytes, spermidine (upper) and acetylspermine (lower).
Figure 5.
Figure 5.
Targeted LC-SRM-MS analysis for purine and pyrimidine analysis using positive/negative switching. A) Molecular structure of cyclic-GMP and Skyline targets tree including molecule annotations and Q1/Q3 transitions, B) combined ion chromatogram showing data in negative ion mode [M-1] at m/z 344 and in positive ion mode [M+1] at m/z 346 and C) split graph representation for ion chromatograms in negative ion mode with Q1/Q3 transition pair 344/(150 and 133) (upper panel), and in positive ion mode with Q1/Q3 transition pair 346/(152 and 135) (lower panel).
Figure 6.
Figure 6.
Analysis of high-resolution metabolomics data in Skyline, in particular for a lipidomics analysis of diacylglycerol 32:0 (DAG 32:0) (A) Extracted ion chromatograms for the M and M+1 isotopes of DAG 32:0 [M+NH4]+ adduct (B) Mass spectrum zoomed to show 585 to 590 m/z viewed in Skyline of the DAG 32:0 [M+NH4]+ adduct ion (C) Extracted ion chromatogram totals of M and M+1 overlay of DAG 32:0 [M+NH4]+ and [M-H2O+H]+ adducts, and (D) Grouped comparison peak area view within Skyline of 5 replicates of each biological condition comparing means and standard deviations of control and FASN-inhibitor treated cells.

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