AbstractIdentification and quantitation of newly synthesized proteins (NSPs) are critical to understanding protein dynamics in development and disease. Probing the nascent proteome can be achieved using non-canonical amino acids (ncAAs) to selectively label the NSPs utilizing endogenous translation machinery, which can then be quantitated with mass spectrometry. Since its conception, ncAA labeling has been applied to study many in vitro systems and more recently the in vivo proteomes of complex organisms such as rodents. In vivo labeling is typically achieved by introducing ncAAs into diet, which requires extended labeling times. We have previously demonstrated that labeling the murine proteome is feasible via injection of azidohomoalanine (Aha), a ncAA and methionine (Met) analog, without the need for Met depletion. With the ability to isolate NSPs without applying stress from dietary changes, Aha labeling can address biological questions wherein temporal protein dynamics are significant. However, accessing this temporal resolution requires a more complete understanding of Aha distribution kinetics in tissues. Furthermore, studies of physiological effects of ncAA administration have been limited to gross observation of animal appearance. To address these gaps, we created a deterministic, compartmental model of the biokinetic transport and incorporation of Aha in mice. Parameters were informed from literature and experimentally. Model results demonstrate the ability to predict Aha distribution and labeling under a variety of dosing paradigms and confirms the use of the model as a tool for design of future studies. To establish the suitability of the method for in vivo studies, we investigated the impact of Aha administration on normal physiology by analyzing the plasma metabolome following Aha injection. We show that Aha administration does not significantly perturb cellular functions as reflected by an unchanged plasma metabolome compared to non-injected controls.Author SummaryAs the machinery of life, proteins play a key role in dynamic processes within an organism. As such, the response of the proteome to perturbation is increasingly becoming a critical component of biological and medical studies. Dysregulation of protein mechanisms following exposure to experimental treatment conditions can implicate physiological mechanisms of health and disease, elucidate toxin/drug response, and highlight potential targets for novel therapies. Traditionally, these questions have been probed by studying perturbations in total proteins following an experimental treatment. However, the proteome is expansive and noisy, often an early response can be indiscernible against the background of unperturbed proteins. Here, we apply a technique to selectively label newly synthesized proteins, which enables capturing early changes in protein behavior. We utilize an amino acid analog that naturally incorporates into proteins, and investigate the tissue distribution, protein labeling efficiency, and potential physiological impact of this analog in mice. Our results demonstrate that we can reproducibly predict protein labeling and that the administration of this analog does not significantly alter in vivo physiology over the course of our experimental study. We further present a computational model that can be used to guide future experiments utilizing this technique to study proteomic responses to stimuli.
