Mass spectrometry based metabolomics for in vitro systems pharmacology: Pitfalls, challenges, and computational solutions

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.

METHODS: Non-cancerous mammary gland derived cells were exposed to 21 chemicals from four pharmacological classes plus a set of 6 pesticides. Changes in the metabolome of cell lysates were assessed after 24h 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.

RESULTS: The pipeline is shown to reduce experimental variability/biases and is used to confirm that LC-MS spectra hold drug class specific information.

CONCLUSIONS: 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 www.github.com/stephanieherman/MS-data-processing.

OTHER RELATED OMICS DATASETS IN: PXD018322 PXD006154

INSTRUMENT(S): Exactive (Thermo Scientific)

SUBMITTER: Stephanie Herman 

PROVIDER: MTBLS401 | MetaboLights | 2017-08-23

REPOSITORIES: MetaboLights