Spatial and single-cell proteomics of metabolic disorders

Mitochondrial metabolism is constrained by the available resources within its host cells and surrounding tissue.

Enzymatic sets are dynamically expressed upon internal and external stimuli in accordance with nutrient and oxygen availability.

Failure to do so severely affects the function of some cell types, while others remain resilient, manifesting in a wide array of clinical outcomes including organ failure, immunodeficiency, or cancer.

This cell-type specificity of mitochondrial dysfunction is not well understood, yet could be key to targeted and more successful clinical intervention.

Proteomics offers a robust method to explore mitochondrial processes, especially as many proteins are stabilized in large complexes and are inaccurately quantified by other omics approaches.

In particular, the emerging field of spatial single-cell proteomics by mass spectrometry provides multi-dimensional information on the tissue context of cells. Given recent technological advances, spatial proteomics is rapidly gaining momentum.

In the next four years, my research team will (1) implement spatial and single-cell proteomics technologies, (2) build a digital model of the mitochondrial proteome utilizing machine learning, and (3) the cell-type specificity and spatial biology of mitochondrial dysfunction in intact patient tissue.

Through spatial proteomics analysis of intact patient samples, this research holds the promise of yielding novel insights into mitochondrial function and disease.