Black-Box Data Analysis for Spatial Metabolomics
Automated and reliable tools for spatially annotating metabolites from imaging mass spectrometry data are essential.
Andrew Palmer, Theodore Alexandrov |
In recent years, metabolomics has been recognized as a field of major importance that promises to advance our understanding of cell biology, physiology, and medicine. Metabolites are the ‘small cogs’ in the cellular machinery and consist of small molecules that are ingested, altered, and catalyzed within the cellular machinery, including not only those molecules synthesized within cells but also those gained from the environment, such as vitamins and nutrients. Such molecules are indicative of cellular processes both from the underlying genetics, cell differentiation and the immediate environmental pressures – and they provide a real-time read out of the state of individual cells and cell populations. Cellular activity can be highly spatially localized and so being able to image markers of metabolic activity may provide researchers with new perspectives on biological problems. Traditional methods often treat samples as homogeneous bulk materials, but this risks missing important biological information; for example, the degree of penetration of an anti-cancer drug into a tumor or a secretion of an antibiotic in proximity to invading bacteria.
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