Quantifying protein kinetics in vivo: influence of precursor dynamics on product labeling - Yao, Huifang; Kelley, Seamus; Zhou, Dan; VanSickle, Sophie; Wang, Sheng-Ping; Piesvaux, Jennifer; Zhou, Haihong; Chen, Hao; McKenney, David; McLaren, David G; Ballard, Jeanine E; Previs, Stephen F (American journal of physiology: endocrinology and metabolism, 2025)
Protein kinetics can be quantified by coupling stable isotope tracer methods with mass spectrometry readouts; however, interconnected decision points in the experimental design affect the complexity of the workflow and impact data interpretations. For example, choosing between a single bolus (pulse-chase) or a continuous exposure protocol influences subsequent decisions regarding when to measure and how to model the temporal labeling of a target protein. Herein, we examine the merits of in vivo tracer protocols, and we direct attention toward stable isotope tracer experiments that rely on administering a single bolus since these are generally more practical to use as compared with continuous administration protocols. We demonstrate how the interplay between precursor and product kinetics impacts downstream analytics and calculations by contrasting fast versus slow turnover precursors (e.g., C-leucine vs. H-water, respectively). Although the data collected here underscore certain advantages of using longer-lived precursors (e.g., H- or O-water), the results also highlight the influence of tracer recycling on measures of protein turnover. We discuss the impact of tracer recycling and consider how the sampling interval is critical for interpreting studies. Finally, we demonstrate that tracer recycling does not limit the ability to perform back-to-back studies of protein kinetics. It is possible to run experiments in which subjects are used as their own controls even though the precursor and product remain labeled following an initial tracer dosing. We demonstrate a simple and robust protocol for measuring protein synthesis, the work considers problems encountered in experimental design. The logic can enable biologists with limited resources and/or can facilitate scenarios where higher throughput experiments are needed.