Application of Skyline software for detecting prohibited substances in doping control analysis

• Published in: PloS one 2023-12, Vol.18 (12), p.e0295065-e0295065
• Main Authors: Lee, Hyeon-Jeong, Jeon, Mijin, Seo, Yoondam, Kang, Inseon, Jeong, Wooyeon, Son, Junghyun, Yi, Eugene C, Min, Hophil
• Format: Article
• Language: English
• Subjects: Acids; Analytical methods; Biology and Life Sciences; Chromatography; Chromatography, Liquid - methods; Complications and side effects; Computer and Information Sciences; Data processing; Debugging; Doping; Doping in Sports - prevention & control; Drug development; Engineering and Technology; Evaluation; Fenoterol; Lipids; Liquid chromatography; Mass spectrometry; Mass spectroscopy; Medicine and Health Sciences; Methods; Open source software; Optimization; Patient outcomes; People and Places; Peptides; Physical Sciences; Proteomics; Proteomics - methods; Quality control; Quality standards; Quantitative analysis; Research and Analysis Methods; Science Policy; Sensors; Software; Software engineering; Tandem Mass Spectrometry - methods; Urine; Workloads
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0295065

As the number of prohibited drugs has been progressively increasing and analytical methods for detecting such substances are renewed continuously for doping control, the need for more sensitive and accurate doping analysis has increased. To address the urgent need for high throughput and accurate analysis, liquid chromatography with tandem mass spectrometry is actively utilized in case of most of the newly designated prohibited substances. However, because all mass spectrometer vendors provide data processing software that is incapable of handling other instrumental data, it is difficult to cover all doping analysis procedures, from method development to result reporting, on one platform. Skyline is an open-source and vendor-neutral software program invented for the method development and data processing of targeted proteomics. Recently, the utilization of Skyline has been expanding for the quantitative analysis of small molecules and lipids. Herein, we demonstrated Skyline as a simple platform for unifying overall doping control, including the optimization of analytical methods, monitoring of data quality, discovery of suspected doping samples, and validation of analytical methods for detecting newly prohibited substances. For method optimization, we selected the optimal collision energies for 339 prohibited substances. Notably, 195 substances exhibited a signal intensity increase of >110% compared with the signal intensity of the original collision energy. All data related to method validation and quantitative analysis were efficiently visualized, extracted, or calculated using Skyline. Moreover, a comparison of the time consumed and the number of suspicious samples screened in the initial test procedure highlighted the advantages of using Skyline over the commercially available software TraceFinder in doping control.