SystemDirectMS · A Native Mass Spectrometry Systemic View of Cellular Structural Biology

Protein structure and consequently function is influenced by the cellular content. The array of splice variants, post-translational modifications, cleavages and the ability to bind cofactors and drugs, is governed by the surrounding cellular milieu. This is determined by internal and external cues such as cell type, developmental stage, stress conditions, disease and aging, which give rise to an ensemble of distinct protein entities. To study this diversity, there is a need for methods that enable structural studies under “close-to-life” conditions, maintaining the natural environment and biological diversity, features that are often lost during biochemical purifications. Our recent discovery that native MS can be conducted within crude cellular lysates (direct-MS), while preserving the biological context, offers many new experimental avenues for investigating protein interactions and diversity. Here, we propose to take native MS to a new dimension: enabling a systemic view of cellular structure biology by endorsing technological, computational and methodological developments. To do this we will: (i) Establish a platform for high-throughput screening of protein interactions. (ii) Unravel protein interactions in human and other eukaryotic cells; (iii) Develop a method for whole-organ direct-MS analysis, unravelling the tissue-specific proteoform landscape. Each of our three independent but complementary aims involves a different biological system, going from bacteria through human cells to intact tissues. Together, these advances, in conjunction with the high-resolution and sensitivity afforded by current mass spectrometers, has the potential to advance a plethora of fields, including cell biology, pharmacology and biotechnology. Overall, we anticipate this project will promote the integration of direct-MS into the cellular structural biology toolkit, providing valuable insights not attained by other structural biology methods or artificial intelligence algorithms.