Recycling, channeling and heterogeneous protein turnover estimation using a model of whole-body protein turnover based on leucine kinetics in rodents

Use of Mechanistic Nutrition Models to Identify Sustainable Food Animal Production

To feed people in the coming decades, an increase in sustainable animal food production is required. The efficiency of the global food production system is dependent on the knowledge and improvement of its submodels, such as food animal production. Scientists use statistical models to interpret their data, but models are also used to understand systems and to integrate their components. However, empirical models cannot explain systems. Mechanistic models yield insight into the mechanism and provide guidance regarding the exploration of the system. This review offers an overview of models, from simple empirical to more mechanistic models. We demonstrate their applications to amino acid transport, mass balance, whole-tissue metabolism, digestion and absorption, growth curves, lactation, and nutrient excretion. These mechanistic models need to be integrated into a full model using big data from sensors, which represents a new challenge. Soon, training in quantitative and computer science skills will be required to develop, test, and maintain advanced food system models.

Protein turnover on the scale of the proteome

Protein turnover is a neglected dimension in postgenomic studies, defining the dynamics of changes in protein expression and forging a link between transcriptome, proteome and metabolome. Recent advances in postgenomic technologies have led to the development of new proteomic techniques to measure protein turnover on a proteome-wide scale. These methods are driven by stable isotope metabolic labeling of cells in culture or in intact animals. This review considers the merits and difficulties of different methods that allow access to proteome dynamics.

Isotopic and modeling investigation of long-term protein turnover in rat tissues

Fractional synthesis rates (FSR) of tissue proteins (P) are usually measured using labeled amino acid (AA) tracer methods over short periods of time under acute, particular conditions. By combining the long-term and non-steady-state (15)N labeling of AA and P tissue fractions with compartmental modeling, we have developed a new isotopic approach to investigate the degree of compartmentation of P turnover in tissues and to estimate long-term FSR values under sustained and averaged nutritional and physiological conditions. We measured the rise-to-plateau kinetics of nitrogen isotopic enrichments (δ(15)N) in the AA and P fractions of various tissues in rats for 2 mo following a slight increase in diet δ(15)N. Using these δ(15)N kinetics and a numerical method based on a two-compartment model, we determined reliable FSR estimates for tissues in which P turnover is adequately represented by such a simple precursor-product model. This was the case for kidney, liver, plasma, and muscle, where FSR estimates were 103, 101, 58, and 11%/day, respectively. Conversely, we identified tissues, namely, skin and small intestine, where P turnover proved to be too complex to be represented by a simple two-compartment model, evidencing the higher level of subcompartmentation of the P and/or AA metabolism in these tissues. The present results support the value of this new approach in gaining cognitive and practical insights into tissue P turnover and propose new and integrated FSR values over all individual precursor AA and all diurnal variations in P kinetics.

Proteomics moves from expression to turnover: update and future perspective

Proteomics is a rapidly developing discipline that seeks to understand the role of proteins in the wider biological context. In order to take a holistic view of a biological system, it is vital that we can elucidate the dynamics of the proteome. In this article, we have outlined the recent advances in experimental strategies for measuring protein synthesis and degradation on a proteome-wide scale. The application of mass spectrometry and non-mass spectrometric-based approaches in this field of research has been discussed. The article also explores the challenges associated with these types of analyses and the development of appropriate bioinformatic resources for interrogating the complex datasets that are generated.

Challenging the Assumptions in Estimating Protein Fractional Synthesis Rate Using a Model of Rodent Protein Turnover

Published estimates of protein fractional synthetic rate vary widely (Johnson et al., 1999a). Contributing to the large standard deviation for FSR are physiological and methodological differences that do not account for changes in specific radioactivities of I, E, T, and P. Current methods for estimating FSR are based on four assumptions which may not be valid. The first assumption, that the free amino acid pool is homogenous and reflects the specific radioactivity of the true precursor pool (aminoacyl tRNA), can cause FSR estimates to increase by up to 8%/d. The second assumption, that recycling has an insignificant effect on FSR estimates, could result in decreases in estimates of FSR from 10 to 20%/d. The third assumption, that the protein pool is homogeneous and will not change over time, results in a 4-10%/d change using the flooding dose method. The fourth assumption, that growth will not affect estimated FSR over a short experimental time, is true if aminoacyl tRNA specific radioactivity is used to estimate FSR. Otherwise, estimates can vary 4-5%/d. Although specific radioactivity of aminoacyl tRNA is difficult to measure, the first and fourth assumptions are valid if aminoacyl tRNA specific radioactivity is used. Using a model of protein turnover, as described in this paper, to interpret specific radioactivity data allows the inclusion of all four assumptions and the potential to better quantify changes in FSR under different physiological conditions.

A rodent model of protein turnover used to design an experiment for measuring the rates of channeling, recycling and protein synthesis

We described previously a mechanistic model of whole-body protein turnover in rodents. Channeling was defined as the flow of amino acids from the extracellular compartment to aminoacyl tRNA and protein synthesis. Recycling was defined as the flow of amino acids from protein degradation to aminoacyl tRNA (protein synthesis) without mixing with the intracellular pool of amino acids. In this paper, the model is applied to tissues and whole body and is used to develop an experimental protocol for estimating protein fractional synthesis rate, recycling and channeling. Channeling, recycling and protein synthesis must be estimated simultaneously because changes in specific radioactivities over time are highly dependent on the rate of protein synthesis. Injection-specific radioactivities, body weights and experimental variation were used with the model to generate data at different rates of recycling and channeling. The data generated were then used to determine the best time points and experimental method to estimate percentages of recycling, channeling and protein synthesis rate by the iterative Method of Maximum Likelihood. Specific radioactivity at each time point was based on simulated data from three rodents at each of six time points. Predicted protein synthesis rates were within 5%/d of observed rates for all methods. Predicted rates of recycling and channeling were generally within 15% of observed rates except recycling in muscle at high channeling and high recycling. Standard deviations of the predictions of percentages of channeling and recycling were between 0.148 and 44.5% for the pulse dose method, 0.0655 and 197% for the continuous infusion method and 0.351 and 962% for the flooding dose method. The experimental design that yields the best estimates of channeling, recycling and protein synthesis is the pulse dose. Changes in amino acid specific radioactivities in the extracellular, aminoacyl tRNA and protein pools were greatest and should be measured at 2, 6, 10, 40, 70 and 100 min in the pulse method.

Recycling, channeling and heterogeneous protein turnover estimation using a model of whole-body protein turnover based on leucine kinetics in rodents

In the companion paper, a whole-body, mechanistic model of protein turnover in a rodent was described and evaluated with independent data sets that used the flooding dose method. On the basis of fitted fluxes, the model was able to predict specific radioactivity changes in the protein and free leucine pools and whole-body protein fractional synthesis rate (FSR). In this paper, results of model simulations of specific radioactivity changes in the flooding dose, pulse dose and continuous infusion methods were compared and the influence of recycling, channeling and multiple protein pools on model behavior were analyzed. For all methods, the percentage of channeling must be estimated to determine whether the extracellular or intracellular pool specific radioactivities better approximate the aminoacyl tRNA pool specific radioactivity. Recycling also affects the specific radioactivity of the aminoacyl-tRNA pool and therefore must be estimated. An analysis of fits of the flooding dose data indicated that 100% channeling was occurring, but the percentage of recycling could not be determined. Multiple protein pools turning over at different rates overestimated FSR by 2-3% at early time points (5 min) and underestimated FSR by 3-6% at 60 min in the flooding dose method. For the pulse dose method, FSR was underestimated by 40-50% at 5 min and underestimated by 9-10% at 60 min. An increase in time to measure FSR caused a decrease in the estimate of FSR (18% over 3 h) for the flooding dose method and an increase in the estimate of FSR (144% over 3 h) for the pulse dose method.