Systematic in vivo proteomic survey of nascent chain co-translational folding by limited proteolysis-mass spectrometry and selective ribosome profiling

• Applicant: Mang Zhu, Ph.D.
• Subject Area: Biochemistry ; Structural Biology ; Cell Biology
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 549989417

Cells in our body synthesize proteins using a large enzyme called ribosome by joining amino acids one after another according to the template laid out by their corresponding gene. This results in linear products of proteins that must fold into proper 3D structures to carry out their functions in cells. The folding of protein can already start the same time as it emerges from the exit tunnel of the ribosome while the rest of the same protein still undergoes synthesis. This is referred to as co-translational folding of nascent chains (NC). Most of our understanding of NC folding comes from studying them in test tubes where minimal components from the cells are present. While this provided crucial understanding of NC folding, it is still unclear how things really happen in the cells that are 1000x more crowded with proteins. This study intends to shed more light on how NC folding happens during synthesis inside the cell by examining the structure of NC using a non-specific proteinase which will digest away preferentially the unfolded region of NC. The remnant of the NC will be detected by a mass spectrometer, thus giving us the folding state of the NC. This method is called LiP-MS. We will first study NC folding of firefly luciferase (Fluc); a model protein with multiple sub-structure to be folded before it reaches its final folded state. We will engineer different versions of Fluc that will stall on the ribosome at different locations of the protein as it is being synthesized. This will mimic different states during synthesis and allow us to understand how folding happens as protein is being synthesized using LiP-MS. To apply this method to study NC folding of all proteins inside the cell, we will need to know the synthesis state of a given NC at a given time. To achieve this, we will synchronize the beginning of all protein synthesis in the cell with a drug called harringtonine, and synthesis will be stopped by ribosome inhibitor cycloheximide after different periods of time. The amount of synthesis happened during this time can be determined by ribosome profiling and the corresponding folding state of NC will be determined by LiP-MS. Combining the two datasets, we will be able to generate a complete profile of the folding kinetics of every detectable protein inside the cells. By regulating the cellular level of chaperone proteins, which assists folding of other proteins, we can also determine how chaperones affect NC folding. Using the NC folding kinetics profile data, we will train a machine learning model that can predict folding kinetics of an unseen protein.

• DFG Programme: WBP Position