Global Analysis of Protein Synthesis and Degradation in Escherichia coli

Author: MacKrell, Elliot James

Year: 2025

Degree: Dissertation (Ph.D.)

Advisor: Tirrell, David A.

Committee Members: Ismagilov, Rustem F.; Shapiro, Mikhail G.; Newman, Dianne K.; Tirrell, David A.

Option: Chemical Engineering

DOI: 10.7907/n97w-ch36

Abstract

Protein synthesis and degradation shape the cellular proteome to drive homeostasis and physiological adaptation. Many fundamental aspects of protein regulation have been elucidated through investigation of the Gram-negative bacterium Escherichia coli, which remains a fruitful model organism for uncovering conserved regulatory mechanisms relevant to cell biology, biotechnology, and medicine. Here, we used bioorthogonal noncanonical amino acid tagging (BONCAT) for the time-resolved analysis of protein synthesis and degradation in this organism in several contexts. We profiled protein degradation on a proteome-wide scale in growing and growth-arrested cells, identifying instability in a diverse panel of regulators. Our identifications served as training data in the validation and deployment of a machine learning classifier of in vivo protein stability, which highlighted the role of active degradation in motility and surface adhesion. We then utilized an efficient system of active degradation in this organism to engineer the instability of the mutant methionyl-tRNA synthetase NLL-MetRS for the analysis of protein synthesis in transient physiological states. Destabilized NLL-MetRS variants exhibited half-lives on the order of hours, which improved the fidelity of metabolic labeling in growth-arrested cells. Additionally, we leveraged the sensitivity of BONCAT to investigate protein synthesis in growth-arrested cells expressing a well-studied but controversial member of the widespread toxin-antitoxin family, MazF. Our proteomic profiling suggests this toxin activates several endogenous stress response systems, most notably the cold shock response system. Taken together, these investigations highlight the advantage of time-resolved proteomics in characterizing proteome dynamics.

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