Recent advances in applying mass spectrometry and systems biology to determine brain dynamics. (3rd June 2017)

• Record Type: Journal Article
• Authors: Scifo, Enzo; Calza, Giulio; Fuhrmann, Martin; Soliymani, Rabah; Baumann, Marc; Lalowski, Maciej
• Is Part Of: Expert review of proteomics. Volume 14:Number 6(2017)
• Page Start: 545
• Page End: 559
• Publication Date: 2017-06-03
• Subjects: Brain -- mass spectrometry -- laser capture microdissection -- liquid chromatography mass spectrometry -- LC-MSE -- MS imaging -- neurodegeneration -- neuropsychiatric disorders; Proteins -- Biotechnology -- Periodicals; Proteomics -- Periodicals; 572.6
• DOI: 10.1080/14789450.2017.1335200
• Languages: English
• ISSNs: 1478-9450

Abstract

ABSTRACT: Introduction : Neurological disorders encompass various pathologies which disrupt normal brain physiology and function. Poor understanding of their underlying molecular mechanisms and their societal burden argues for the necessity of novel prevention strategies, early diagnostic techniques and alternative treatment options to reduce the scale of their expected increase. Areas covered : This review scrutinizes mass spectrometry based approaches used to investigate brain dynamics in various conditions, including neurodegenerative and neuropsychiatric disorders. Different proteomics workflows for isolation/enrichment of specific cell populations or brain regions, sample processing; mass spectrometry technologies, for differential proteome quantitation, analysis of post-translational modifications and imaging approaches in the brain are critically deliberated. Future directions, including analysis of cellular sub-compartments, targeted MS platforms (selected/parallel reaction monitoring) and use of mass cytometry are also discussed. Expert commentary : Here, we summarize and evaluate current mass spectrometry based approaches for determining brain dynamics in health and diseases states, with a focus on neurological disorders. Furthermore, we provide insight on current trends and new MS technologies with potential to improve this analysis.