Back to Search
Start Over
Mass spectrometry based metabolomics for in vitro systems pharmacology: pitfalls, challenges, and computational solutions.
- Source :
- Metabolomics; Jul2017, Vol. 13 Issue 7, p1-12, 12p
- Publication Year :
- 2017
-
Abstract
- Introduction: Mass spectrometry based metabolomics has become a promising complement and alternative to transcriptomics and proteomics in many fields including in vitro systems pharmacology. Despite several merits, metabolomics based on liquid chromatography mass spectrometry (LC-MS) is a developing area that is yet attached to several pitfalls and challenges. To reach a level of high reliability and robustness, these issues need to be tackled by implementation of refined experimental and computational protocols. Objectives: This study illustrates some key pitfalls in LC-MS based metabolomics and introduces an automated computational procedure to compensate for them. Method: Non-cancerous mammary gland derived cells were exposed to 27 chemicals from four pharmacological classes plus a set of six pesticides. Changes in the metabolome of cell lysates were assessed after 24 h using LC-MS. A data processing pipeline was established and evaluated to handle issues including contaminants, carry over effects, intensity decay and inherent methodology variability and biases. A key component in this pipeline is a latent variable method called OOS-DA (optimal orthonormal system for discriminant analysis), being theoretically more easily motivated than PLS-DA in this context, as it is rooted in pattern classification rather than regression modeling. Result: The pipeline is shown to reduce experimental variability/biases and is used to confirm that LC-MS spectra hold drug class specific information. Conclusion: LC-MS based metabolomics is a promising methodology, but comes with pitfalls and challenges. Key difficulties can be largely overcome by means of a computational procedure of the kind introduced and demonstrated here. The pipeline is freely available on . [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15733882
- Volume :
- 13
- Issue :
- 7
- Database :
- Complementary Index
- Journal :
- Metabolomics
- Publication Type :
- Academic Journal
- Accession number :
- 123903860
- Full Text :
- https://doi.org/10.1007/s11306-017-1213-z