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Am J Physiol Endocrinol Metab 281: E248-E260, 2001;
0193-1849/01 $5.00
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Vol. 281, Issue 2, E248-E260, August 2001

Energy nutrients modulate the splanchnic sequestration of dietary nitrogen in humans: a compartmental analysis

H. Fouillet, C. Gaudichon, F. Mariotti, C. Bos, J. F. Huneau, and D. Tomé

Unité Mixte de Recherche de Physiologie de la Nutrition et du Comportement Alimentaire, Institut National de la Recherche Agronomique-Institut National Agronomique Paris-Grignon, F-75231 Paris, France


    ABSTRACT
TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES

We used a previously developed compartmental model to assess the postprandial distribution and metabolism of dietary nitrogen (N) in the splanchnic and peripheral areas after the ingestion of a single meal containing milk protein either alone (MP) or with additional sucrose (SMP) or fat (FMP). The addition of fat was predicted to enhance splanchnic dietary N anabolism only transiently, without significantly affecting the global kinetics of splanchnic retention and peripheral uptake. In contrast, the addition of sucrose, which induced hyperinsulinemia, was predicted to enhance dietary N retention and anabolism in the splanchnic bed, thus leading to reduced peripheral dietary amino acid availability and anabolism. The incorporation of dietary N into splanchnic proteins was thus predicted to reach 18, 24, and 35% of ingested N 8 h after MP, FMP, and SMP, respectively. Such a model provides insight into the dynamics of the system in the nonsteady postprandial state and constitutes a useful, explanatory tool to determine the region-specific utilization of dietary N under different nutritional conditions.

protein metabolism; postprandial period; insulin; mathematical model; parameter estimation


    INTRODUCTION
TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES

CONSIDERABLE ATTENTION has been paid to interactions between energy nutrients and nitrogen (N) metabolism, leading to the conclusion that carbohydrate (CHO) is more likely than fat to exert a sparing effect on body protein (25, 30, 33, 42). Certain studies have addressed the effects of dietary CHO (33, 48) or insulin availability (32) on splanchnic N anabolism in the fed state, whereas others have aimed at studying the effects of amino acids (AA), CHO, and/or insulin on the stimulation of muscle protein synthesis (5, 11, 41, 44). However, little is still known, particularly in humans, about the dietary N partitioning between splanchnic and peripheral tissues and its immediate orientation in the anabolic and catabolic pathways of different organs after protein ingestion. The acute response to a meal is known to involve a cascade of transient metabolic processes, where the rate of dietary AA and energy nutrient absorption and the resulting pattern of their postprandial concentrations in tissues are potent modulators of protein synthesis, breakdown, and oxidation (8). The balance between dietary AA anabolic and catabolic pathways depends on the tissue under consideration and varies as a function of dietary factors, especially protein or energy intake (2, 49). Liver and muscle, the most important tissues involved in postprandial protein turnover, do not participate in these metabolic processes in the same way because of their different specificity (high rate of protein turnover in the liver vs. large mass of the muscle protein pool) (33).

The aim of the present study was to further investigate whether fat and/or sucrose differentially affects the postprandial partitioning of dietary N between splanchnic and peripheral organs and its regional metabolic fate under the dependence of AA absorption kinetics and insulin response. For this purpose, we used a compartmental modeling tool that we had previously developed to specifically follow ingested N in the fed state and determine its dynamic fate through free and protein-bound AA from the splanchnic and peripheral organs in humans (24). It consists of an 11-compartment model, the behavior of which has been validated using experimental measurements of 15N kinetics in ileum, blood, and urine after the ingestion of a single 15N-labeled dietary protein meal (MP) in humans. This modeling approach mimics the absorption and physiological fate of dietary N in the postprandial nonsteady state, whereas no such information could usually be obtained with regard to the kinetic aspects of AA disposal or release during classical steady-state studies of N metabolism (7, 26, 35, 36, 45, 50). Furthermore, the model allows the simulation of both regional dietary N distribution in the postprandial phase and the relative ability of a protein meal to promote protein synthesis in either the splanchnic or peripheral areas. In contrast, organ balance studies (23, 32, 38, 43) allowed determination of only the net organ balance of AA, without discriminating between dietary and endogenous AA metabolism (7, 35), whereas the multiple-tracer approach (6, 7, 27) addressed the splanchnic extraction of dietary AA without distinguishing that part used for protein synthesis from the remaining deaminated part of the splanchnic uptake (7).


    MATERIALS AND METHODS
TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES

Collection of experimental data. Experimental data were collected as described previously (25). The protocol was approved by the Institutional Review Board for Saint-Germain-en-Laye Hospital, and informed consent was obtained from each subject. After an overnight fast, healthy humans equipped with an ileal tube ingested a liquid meal made up of 30 g of 15N-labeled milk protein either alone (MP group, n = 8), or with additional energy in the form of either 100 g of sucrose (SMP group, n = 9) or 43 g of milk fat (FMP group, n = 9). The energy content of the diets ranged from 500 kJ for MP to ~2,150 kJ for SMP and FMP. Over a period of 8 h after the meal, samples of intestinal effluents were collected on a continuous basis, with blood samples being drawn hourly and urine collected under mineral oil every 2 h. Analytical methods and calculations have been described in full detail elsewhere (25). Briefly, urinary urea and ammonia, as well as plasma urea and free AA, were separated using cation exchange resins. Urea and ammonia in urine and plasma were determined on clinical analyzers and N in ileal samples by use of an elemental analyzer. Plasma insulin was measured by a radioimmunoassay method. 15N enrichments in ileal effluents, plasma free AA and urea, and urinary urea and ammonia were determined by isotope ratio mass spectrometry. Dietary N in the samples was then determined using isotope dilution equations (for a full description, see Ref. 25). Ileal flow rates were assessed using a slow-marker technique (28). Body urea was calculated from plasma urea by the consideration that urea mixes uniformly in total body water, the total body water value being determined using the equations developed by Watson et al. (47). The amount of dietary N present in plasma free AA was calculated by assuming that the plasma AA concentration was 100 mg/l and the mean plasma volume was 5% of the body mass (24). All data (dietary N recovered from cumulated ileal effluents, plasma free AA, body urea, cumulated urinary urea, and cumulated urinary ammonia) were converted into percentages of ingested N. Urinary data were interpolated, and ileal effluent data were pooled in such a way as to obtain the same 1-h data step size.

Linear compartmental model. The linear compartmental model was previously selected using SIMUSOLV software and was validated at each stage of its development by testing successively its a priori (theoretical) and a posteriori (numerical) identifiability (24). This model consisted of 11 compartments representing distinct amounts of dietary N and 15 different pathways of exchange between these compartments, each being characterized by a constant diffusion coefficient, ki,j (Fig. 1). These exchange rate constants, ki,j, represented the fraction of dietary N in compartment j transferred to compartment i per unit of time (min). The model, developed using average data values for the MP meal, described the transfer of dietary N through the gastrointestinal tract, the elimination of absorbed dietary N in the urine, and the distribution of retained dietary N in the body. The model structure included three subsystems to cover all experimental data: the gastrointestinal tract subsystem built using ileal effluent data, the deamination subsystem covering body urea, urinary urea and urinary ammonia data, and the retention subsystem built using plasma free AA data. The retention subsystem was structured with the aim of clarifying N distribution between splanchnic and peripheral tissues, and this selected structure distinguished between free and protein-bound AA in both areas. Parsimonious modeling was applied to the choice of each subsystem structure so that it would be the minimum necessary to fit the sampled compartments.


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  		Fig. 1.   The selected model. Circles indicate compartments representing kinetically distinct pools of dietary nitrogen (N); arrows between the compartments represent transfer pathways; and numbers by the arrows indicate transfer rate constants (ki,j). Bullets indicate the compartments sampled. Samples s1-s5 represent cumulative ileal effluents, plasma free amino acids, body urea, and cumulative urinary urea and ammonia, respectively, and are associated with compartments 3, 5, 9, 10 and 11. A unidirectional chain of 3 compartments was used to describe the gastrointestinal tract: bolus input is assumed to take place in compartment 1, representing the gastric N content; compartment 2 corresponds to the intestinal lumen N content and compartment 3 to entry into the cecum (ileal effluents) from which fecal losses take place. Compartment 4, belonging to the retention subsystem, corresponds to splanchnic free AA exchanging bidirectionally with the intestine (absorption and release into the intestinal lumen). Two irreversible losses occur from compartment 4, one through the body urea (compartment 9), from which urinary urea is irreversibly lost (compartment 10), and the other representing urinary ammonia losses (compartment 11), these last 3 compartments composing the deamination subsystem. Compartment 4 (SA) exhibits more bidirectional exchanges with 2 other compartments of the retention subsystem, 5 and 7. Compartment 7 corresponds to the splanchnic protein pool, and reversible pathways between 4 and 7 traduce the synthesis and degradation phenomena that occur in the splanchnic bed. Compartment 5 represents plasma free AA, exhibiting more bidirectional exchanges in a catenary structure with compartments 6 and 8 of the retention subsystem, representing peripheral free AA and peripheral protein, respectively.

Parameter estimation. This compartmental model was confronted with the experimental data obtained after the ingestion of MP, SMP, and FMP meals. SIMUSOLV software was used to estimate those parameter values that would produce the closest model predictions for each meal by adjusting the rate constant values until the model predictions fitted the data for all sampled compartments simultaneously. The objective function iteratively maximized during the parameter estimation process under SIMUSOLV was the log of the likelihood function, which represents the joint probability of obtaining our experimental data for each sampled pool in the context of a given set of fitted parameters, taking account of the fact that an experimental error is always associated with experimental measurements (20, 24). First, we explored a broad range of variations for all parameters, allowing values to change individually or in various combinations to fit each meal. The correlation matrix provided from statistical output showed that the two parameters of certain bidirectional pathways were always strongly correlated. We therefore decided to keep one of these parameters for each pair (k2,4, k4,5, k5,6, and k6,8) constant and equal to a value determined during the previous step of parameter estimation, changes to other parameter values being both necessary and sufficient to explain the observed differences in kinetics. In this way, by making minor adjustments to the smallest set of parameters, we took advantage of Berman's minimal change postulate (4). In the context of our study, this implies that we could characterize the changes ensuing from our experimental perturbation (presence and type of additional energy content in the meal) by exploring the minimal change to the "reference" model (MP meal), thus bringing the new predictions into line with the new data. These parameters, in which changes were identified as contributing most to the difference in the meals, were considered as regulatory steps involved in the metabolic response to variations in meal composition. Moreover, different values for initial parameter estimates were tested to reduce the probability of falling into a local optimum if the starting point was not in the neighborhood of the global optimum. Final parameter estimates were verified as providing the best possible fit and not a local optimum. Thus, for each meal, the model was quantified for each subject and for the mean of individual data by use of parameter estimation. Results concerning dietary N postprandial distribution after each meal were obtained by optimization with the use of the mean of individual data for each meal, whereas individual fits were used to assess the discriminatory capacity of the model and the statistical differences between meals.

Sensitivity analysis. Sensitivity analysis of the model was performed by evaluating the effect of a 1% change in parameter value on the prediction of a variable response, i.e., by calculating a sensitivity coefficient for each pair: delta (model response)/delta (model parameters). However, to eliminate the bias caused by the magnitude in parameter values, the sensitivity coefficients were log normalized and calculated using the direct decoupled method under SIMUSOLV (20). Sensitivity analysis was performed on the parameter estimate values obtained for each meal by evaluating their influence on the model responses for each compartment and also for the retention subsystem.

Statistical analysis and other calculations. The discriminatory capacity of the model was tested by discriminant analysis by means of the SYSTAT statistical package (SYSTAT, Evanston, IL), and predicted differences in the distribution kinetics between dietary groups (i.e., meals) were analyzed by repeated-measures ANOVA using a general linear model procedure (SAS/STAT 6.03, SAS Institute, Cary, NC). Differences with P values <0.05 were considered statistically significant.

Peripheral protein synthesis efficiency, defined as the fraction of the intracellular AA rate of appearance that is incorporated into protein, was calculated as the flux of dietary N incorporation into the peripheral protein compartment (PP) divided by the flux of dietary N appearance in the peripheral free AA compartment (PA) (45), i.e., (k8,6 · PA)/[(k6,5 · AA)+(k6,8 · PP)].


    RESULTS
TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES

Parameter estimation and numerical validation. For each meal, the model was quantified for each subject and for the mean of individual data by use of parameter estimation. The model fitted all subjects satisfactorily, but a better fit was obtained for each compartment with the use of the mean of individual data (Fig. 2). The corresponding optimization criteria and parameter estimate values for each meal are given in Tables 1 and 2. The distribution of parameter estimates did not differ significantly when obtained using the mean of individually fitted parameters or when directly fitting the mean of individual data (Wilcoxon matched-pair signed-ranks test, two-tailed P >=  0.95).


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  		Fig. 2.   Fits obtained after optimization with use of the mean data for each meal: observed vs. predicted values for each sampled compartment. Each observed datum is plotted by value ± 2 SD, the weighting scheme being determined by SIMUSOLV software during optimization. A, B, C, D, and E: cumulative ileal effluents, kinetics of body urea, kinetics of plasma free AA, and cumulative urinary urea and urinary ammonia, respectively, after milk protein (MP), MP + milk fat (FMP), and MP + sucrose (SMP) meals. Lines, computer simulations: bold, after MP; solid, after FMP; dotted, after SMP. Points, experimental data: , after MP; black-triangle, after FMP; , after SMP.


                              
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  		Table 1.   LLF values and percentage variations explained after each meal and detailed for each sampled compartment


                              
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  		Table 2.   Parameter estimates and their precision for each meal

For each meal, the numerical identifiability of the model was tested successively by checking the goodness of fit, the randomness of residual errors, and the reliability of parameter estimates (15). Goodness of fit, which appeared very acceptable from a visual inspection of a plot of model predictions vs. experimental data (Fig. 2), was further assessed by an analysis of residuals to check the underlying assumptions of both the normality and the randomness of the data error distribution involved in optimization (24). If the assumption of normality is valid, standardized residuals, i.e., the difference between a datum and its model prediction divided by the standard deviation of the datum, should follow a normal distribution, with a mean of 0 and a variance of 1. Thus 95% of standardized residuals should lie within the range -1.96 to +1.96 (24). For each meal, the standardized residuals of sampled compartments were within or close to the 95% interval range (93% for MP and 98% for FMP and SMP). To ensure that datum points were scattered randomly around the fitted curve, nonrandomness in the residuals was tested formally using the runs test, which counts the number of consecutive residuals with the same sign and compares it with the number of runs expected if the residuals were randomly scattered (24). The residuals of each sampled compartment were generally consistent with the hypothesis of randomness [P value of runs tests >0.75 (15)], except for UA in the FMP group and E in the SMP group (P < 0.15). These systematic but slight deviations between experimental data and model predictions for UA in the FMP group and E in the SMP group suggested that the model is too simple to fit these data sets accurately under these particular nutritional conditions and may require more compartments than those postulated (14, 15). For example, delayed intestinal transit in the presence of sucrose (after SMP) may require at least one more compartment to fit the ileal effluent data more adequately. However, we were satisfied with the model response, even in these two less adequately fitted compartments, because these two sampled compartments constitute traps from which there is no return of dietary N to any compartment outside the trap; this lack of structural influence on the remainder of the system limits the consequence of the committed error. The precision of fitted parameters is commonly expressed in terms of a coefficient of variation (CV), calculated as the ratio of the standard deviation of a parameter to its value, parameter values with a CV <50% usually being judged as adequately estimated (24). As shown in Table 2, the highest CV for fitted parameters was lower than 8, 17, and 40% for MP, FMP, and SMP meals, respectively, indicating that the parameters were estimated with very good precision.

Discriminatory capacity of the model and sensitivity analysis. The discriminatory capacity of the model was tested using a discriminant analysis that optimally separates all individual sets of ki,j into groups of closer characteristics on the basis of linear combinations of the parameters. The discriminatory capacity of the model was assessed by determining the extent to which subjects who received the same meal were a posteriori correctly grouped together. Whatever the comparison (i.e., when comparing two meals: MP vs. SMP, MP vs. FMP, SMP vs. FMP, or the three meals together: MP vs. FMP vs. SMP), 100% of subjects were correctly replaced in their original group. The discriminant analysis further indicated that k2,1, the gastric emptying rate, k7,4, the splanchnic protein incorporation rate, and k6,5, the peripheral tissue transfer rate, accounted for most of the differences between/among meals.

As previously reported for the pure MP meal (24), the results of the sensitivity analysis, which enabled identification of those parameters with the greatest influence on the system, agreed with the model structure and our knowledge of system behavior. Whatever the compartment and subsystem, k2,1 and k4,2 exhibited considerable initial influence, which then declined more slowly after FMP than after MP and even more slowly after SMP than after FMP. After all three meals, the retention subsystem was rapidly positively sensitive to k5,4, whereas it was negatively influenced by variations in k9,4 and k3,2 in descending order, these trends increasing over time (results not shown). Furthermore, the positive influence of k7,4 and k2,1 on the retention subsystem was further predicted for SMP. Figure 3 shows the relative influence of fitted parameters on the regional protein compartments (SP and PP). As shown in Fig. 3, A and B, after both MP and FMP, SP was most positively sensitive to variations in k7,4 and negatively sensitive to k4,7 and, to a lesser extent, to variations in k5,4 and k9,4. After SMP, both a greater positive influence of k2,1 and a lower negative influence of k4,7 were predicted on SP (Fig. 3C). Moreover, after MP and FMP, PP was positively sensitive to variations in k5,4 and k8,6, in descending order, and negatively to those in k7,4 and k9,4, these latter trends increasing over time (Fig. 3, D and E). After SMP, both a stronger positive influence of k2,1 and a stronger negative influence of k7,4 were predicted on PP (Fig. 3F). To summarize, k2,1 and k4,2 on the one hand, and k5,4, k9,4, and k7,4 on the other hand were systematically identified as important governing parameters, as previously reported for the MP meal (24). Nevertheless, for the SMP meal, the gastric emptying (k2,1) and splanchnic protein synthesis (k7,4) rates exerted greater influence on the metabolic fate of dietary N. 


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  		Fig. 3.   Relative sensitivity of fitted parameters (k2,1, k3,2, k4,2, k4,7, k5,4, k6,5, k7,4, k8,6, k9,4, k10,9, k11,4) to dietary N incorporation into the splanchnic protein compartment (SP) after optimization with use of data obtained with MP (A), FMP (B), and SMP (C), and into the peripheral protein compartment (PP) after optimization using data on MP (D), FMP (E), and SMP (F).

Predicted kinetics of dietary N absorption and transfer to splanchnic and peripheral organs. The model enabled simulation of the successive transfers of dietary N between different compartments after each meal. By achieving a very good fit with the data for each meal, the model reported, as experimentally measured, the same digestibility of ~95% of dietary N at 8 h whatever the meal, with global deamination (= BU + UU + UA) that was similar after MP and FMP meals (any statistical difference at each point and regarding the global kinetics) but significantly lowered after SMP, which was the only meal that was seen to induce a significant postmeal insulinemic response (Fig. 4) (25). The model simulated an N gastric emptying half-time that rose from ~20 min after MP to ~50 min after FMP and to 100 min after SMP (Fig. 5).


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  		Fig. 4.   Incremental plasma insulin responses to MP (, n = 8), FMP (black-triangle, n = 9) and SMP (, n = 9) meals. Values are means ± SE; dagger significantly different from the basal value (t-test, P < 0.05). Differences between meals were tested using a general linear model (GLM) procedure for repeated measures: P < 0.05 SMP vs. MP; *P < 0.05 SMP vs. FMP.



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  		Fig. 5.   Model predictions for the kinetics of dietary N in the gastric compartment (G), in %ingested N over time after each meal. Lines, model predictions: bold, after MP; solid, after FMP; dotted, after SMP. Values are obtained by optimization with use of the mean of individual data. Differences between meals were tested using a GLM procedure for repeated measures: black-triangleP < 0.05 MP vs. FMP; P < 0.05 MP vs. SMP; *P < 0.05 FMP vs. SMP.

Unlike experimental data, the simulation enabled evaluation of the partitioning of retained dietary N between and within the splanchnic and peripheral areas. The retention of dietary N in the splanchnic bed (= SA + SP) occurred rapidly and transiently after MP, with a high and acute peak at ~1 h after the meal, whereas FMP, and particularly SMP, induced slower, lower, and more prolonged splanchnic retention with a peak achieved at ~2.5 and ~6 h after FMP and SMP, respectively (Fig. 6A). Despite delayed and transiently higher retention between 4 and 8 h, the splanchnic retention pattern after FMP was closer to that of MP, leading to a global kinetic of dietary N splanchnic retention that was not significantly affected by the addition of fat. In contrast, splanchnic retention after SMP was found to be significantly higher than after MP as early as 5 h and in terms of global kinetics. These differences in splanchnic retention were due mainly to the pattern of dietary N incorporation into splanchnic protein, which fell after ~5 and ~4 h with MP and FMP, respectively, with corresponding maximum values for ingested N of 21 and 32%, respectively, whereas the level was still rising after 12 h with SMP, reaching a maximum value of 37% of ingested N at this time (Fig. 6C). Like the retention, the transfer of dietary N to the splanchnic protein compartment (SP) in the presence of sucrose was significantly higher after 5 h and for the global kinetic when compared with MP, whereas fat significantly increased splanchnic dietary N incorporation but only during the first 7 h. Concurrently, the transient incorporation of dietary N to the splanchnic free AA compartment (SA) decreased after ~1, ~1.5, and ~2 h after MP, FMP, and SMP, respectively, with corresponding maximum values for ingested N of 47, 27, and 22%, respectively (Fig. 6B). These delaying and lowering effects of sucrose, and to a lesser extent of fat, on dietary N accumulation in the SA compartment were significant in both cases, but only during the first 2 or 3 h after the meal.


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  		Fig. 6.   Model predictions for the kinetics of the splanchnic retention of dietary N (A) and its partition between free AA (B) and proteins (C) after each meal. Lines, model predictions: bold, after MP; solid, after FMP; dotted, after SMP. Values are obtained by optimization with use of the mean of individual data. Differences between meals were tested using a GLM procedure for repeated measures: black-triangleP < 0.05 MP vs. FMP; P < 0.05 MP vs. SMP; *P < 0.05 FMP vs. SMP.

Splanchnic retention and anabolism, facilitated during the earlier phase of the feeding period, were followed by a redistribution of dietary N from these to peripheral tissues during the later feeding period and on into the postabsorptive phase. The peripheral uptake of dietary N (= PA + PP) was thus still increasing 12 h after the three meals, with maximum peripheral retention values achieved over the simulation period of 51, 46.5, and 38% of ingested N for MP, FMP, and SMP, respectively (Fig. 7A). The lowering effect of sucrose on dietary N transfer to peripheral tissues was found to be significant at each time point and for the global kinetic, whereas it was significant during only the first 8 h in the presence of fat. Similarly, incorporation into the peripheral protein compartment (PP) was still increasing 12 h after the three meals, reaching maximum values at this time of 43, 37.5, and 33% of ingested N in the MP, FMP, and SMP groups, respectively (Fig. 7C). This lowering effect was found to be significant at each time point and for the global kinetic in the presence of sucrose, but not of fat. The dietary N content in the peripheral free AA compartment (PA) decreased after ~3.5, ~4, and ~5 h after MP, FMP, and SMP, respectively, with corresponding maximum ingested N values of 21.5, 16, and 12.5%, respectively (Fig. 7B). This delaying and lowering effect on PA was found to be significant only during the first 5 h after the meal containing fat, whereas it was significant at each time point and for the global kinetic in the presence of sucrose. Moreover, the peripheral protein synthesis efficiency (PSE) significantly increased from ~25% after both MP and FMP to 31% after SMP ingestion.


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  		Fig. 7.   Model predictions for the kinetics of the peripheral retention of dietary N (A) and its partition between free AA (B) and proteins (C) after each meal. Lines, model predictions: bold, after MP; solid, after FMP; dotted, after SMP. Values are obtained by optimization with use of the mean of individual data. Differences between meals were tested using a GLM procedure for repeated measures: black-triangleP < 0.05 MP vs. FMP; P < 0.05 MP vs. SMP; *P < 0.05 FMP vs. SMP.


    DISCUSSION
TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES

The purpose of this study was to model the specific effect of dietary energy nutrients (fat or sucrose) on the dynamic exchange of dietary N between splanchnic and peripheral organs and on its regional metabolism in the fed state. The consumption of three different meals, MP, FMP, and SMP, enabled the study of three combinations between the insulin and AA levels. 1) MP, which was rapidly absorbed, led to the rapid, high, and transient appearance of dietary N in the splanchnic and peripheral free AA pools without insulin activation; 2) FMP, which was more slowly absorbed, led to a slightly slower and lesser appearance of dietary N in the splanchnic and peripheral free AA pools without insulin activation; and 3) SMP, which was very slowly absorbed, reduced to a greater extent the speed and amplitude of dietary N appearance in free AA pools, with a concomitant acute hyperinsulinemic postmeal response (25). Compartmental analysis of these data thus enabled simulation of the partitioning kinetics of retained dietary N between free AA and proteins in both the splanchnic and peripheral areas (Fig. 8). The model thus made it possible to determine that the higher whole body retention of dietary N experimentally observed in the presence of sucrose was associated with its higher and prolonged sequestration into the splanchnic tissues, leading to a delayed release to the periphery. Furthermore, it provided new evidence indicating that fat transiently enhances splanchnic dietary N incorporation into protein, an outcome that could not be deduced directly from experimental results. The physiological relevance of our model is supported by the consistency of its predictions with respect to our current knowledge of the system and by its ability to discriminate between different nutritional conditions, since it highlighted significant differences between the meals. The modeling approach thus proved to be a useful tool with possible applications to several nutritional conditions and with the aim of optimizing diet formulation in various physiological conditions.


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  		Fig. 8.   Kinetics of the distribution of retained dietary N (between free and bound AA in visceral or peripheral regions) and of lost dietary N (both deamination and ileal losses). Values (areas in the figure represent respective parts of total dietary N retention or loss) were obtained by optimization with use of the mean of individual data after MP (A), FMP (B), and SMP (C) meals.

This modeling tool enabled a precise description of the dynamics of dietary N distribution during the postprandial state. The model simulated rapid emptying of the gastric N content after the ingestion of a pure protein (MP) meal with an emptying half-time of ~20 min, which was close to previous experimental results (10, 28). Gastric emptying was more delayed in the presence of additional dietary sucrose than with additional fat, with a time lag of 80 min in the emptying half-time after SMP vs. MP. This result seems particularly relevant, because a previous study involving two meals with the same protein and sucrose content as MP and SMP had reported a similar delay in the gastric emptying profile (30). Consistent with previous findings in the literature, summarized in Table 3, the model predicted a predominant splanchnic uptake of dietary N during the early postprandial phase, which modulated the delivery of dietary AA to peripheral tissues (3, 23, 27, 29, 35, 50). This is in agreement with the idea that the acute anabolic effect of orally ingested AA occurs primarily in the splanchnic area (13, 17, 38, 44), whereas muscle proteins are of little importance to the rapid replenishment of tissue proteins after ingestion (33). According to several studies, the first-pass splanchnic extraction (i.e., retention plus deamination) of AA after the administration of a complete AA mixture accounts for between 30 and 70% of ingested AA, depending both on the AA considered and the duration of the experiment (45, 50, 51). Consistent with these results, we report the splanchnic extraction of ~46% of dietary input 8 h after the MP meal. This value rose to ~56% after the SMP meal, in line with previous studies that reported a splanchnic utilization of 58% for Phe in humans continuously fed a complete mixed meal (7) and 53% (averaged value for Leu, Lys, Phe, and Thr) after the constant intragastric administration of a complete mixed meal in piglets (38). Moreover, in agreement with the findings in piglets (36, 37) and in dogs (50, 51), the model predicted incorporation into splanchnic protein, which varied as a function of the meal between 20 and 30% of ingested N at 6 h. The amount of dietary N reaching peripheral tissues was thus predicted to be reduced with the addition of dietary sucrose, and to a lesser extent with that of fat, as a consequence of both delayed absorption kinetics and an increase in temporary splanchnic retention and anabolism. Thus predicted peripheral uptake reached 37% of dietary N 4 h after MP ingestion but was significantly lower at 21% at the same time point after SMP. Consistent with this latter value, only 18% of available branched-chain AA had previously been estimated to be taken up by muscle during the first 4 h after ingestion of a single mixed meal (22). The predicted relative contribution of peripheral proteins to the total amount of proteins synthesized 8 h after a meal reached ~65% after MP and decreased to ~42% after SMP. This is consistent with previous findings that showed that protein synthesis in muscle made only a minority contribution (30-50%) to the whole body anabolic response after a mixed meal (31).

                              
View this table:
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  		Table 3.   Comparison of findings in the literature and model predictions

Dietary AA and insulin are considered to play important roles in promoting postprandial protein anabolism, but the isolated and/or concomitant contribution of hormonal and substrate factors to the protein anabolism associated with the fed state still requires clarification (44). An interesting outcome of these model predictions was the determination of dietary N replenishment kinetics of free AA pools in the tissues. These pools can be considered as buffer areas capable of an immediate response to acute variations in N intake, whereas protein synthesis systems have limited capacities to deal with an AA excess (9, 21). As a direct consequence, a rapid increase in the free AA pool leads to the saturation of synthesis capacity and exposes transiently stored AA to oxidation (34). Consistent with these findings, our model correctly predicted that the amount of dietary N incorporated into SP after 7 h would be negatively correlated with the height of the SA peak. Fat and sucrose are thus associated with a temporary increase in splanchnic accretion during the first postprandial hours, as a consequence of delayed dietary N gastric emptying and the resulting flattened SA appearance profile. The idea of a central and regulatory role of SA was further supported by the results of the sensitivity analysis, as the rates of disappearance from SA (k9,4, the transfer rate to body urea, k5,4, the rate of delivery to the periphery, and k7,4, the transfer rate to SP) exerted the most influence on the whole body retention and incorporation of dietary N into SP and PP. Sensitivity analysis further indicated that, if sucrose was present in the meal, the gastric emptying rate (k2,1) and splanchnic protein synthesis rate (k7,4) exerted an increased influence on the metabolic fate of dietary N. The slowing down of gastric emptying, which led to a delayed and flattened appearance of dietary N into SA, and the enhanced incorporation of dietary N from SA into SP may both, therefore, be involved in the dietary N sparing effect of dietary sucrose. By analogy with dietary CHO, Boirie et al. (8) had already developed the concept of "slow" and "fast" proteins according to the rate at which dietary proteins are digested and absorbed from the gut, and they concluded that the resulting pattern of aminoacidemia (amplitude and duration) affects postprandial protein synthesis, breakdown, and deposition. It has also been reported in food-deprived chicks that liver protein synthesis was more stimulated in animals fed protein plus sucrose, and to a lesser extent protein plus fat, than protein alone (48). In contrast, in the peripheral zone, the incorporation of dietary N into protein is positively correlated with the free AA level. Consistent with our model predictions, it has already been reported that AA concentrations are the principal determinant of AA uptake across human forearm tissue during a protein meal (1). The key role played by the kinetics of dietary AA appearance in the splanchnic bed and peripheral area regarding modulation of their utilization for anabolism emphasizes the importance of studying N metabolism in the fed state using a non-steady-state approach.

Moreover, the presence of dietary sucrose induced acute hyperinsulinemia that was not observed after MP or FMP (25). Insulin has been reported to increase whole body protein synthesis in the concomitant presence of AA (12), but studies concerning regional AA metabolism have generally failed to demonstrate a stimulating effect of insulin on muscle tissue protein synthesis, a paradigm for the largest protein pool in the body (16, 17). Likewise, some studies in mice have failed to demonstrate a muscular anabolic effect of the ingestion of starch plus casein, despite the anabolic effect of this meal in the liver and gastrointestinal tract (33). Furthermore, the well-known peripheral hypoaminoacidemic effect of systemic hyperinsulinemia can be explained by the rapid primary action of this hormone in the splanchnic region (31, 40). Taken together, these and other data suggest that splanchnic tissue may be involved mainly in the increase in protein synthesis associated with insulin secretion (17), because any acute hormonal effect would have an earlier impact on fast- rather than on slow-turning over proteins (39). Thus the addition of CHO to a pure protein meal has been shown to enhance protein synthesis in the gut, and this increase was found to be related to the postprandial insulin response (19). Similarly, albumin synthesis has been reported to be under the regulation of insulin (16, 17, 39, 44). In this respect, the hyperinsulinemia observed after SMP was predicted to be associated with a stronger splanchnic anabolic response compared with both MP and FMP and a weaker peripheral response compared with MP. However, despite the decreased dietary N availability in peripheral tissues after SMP ingestion, the fraction of the peripheral free AA rate of appearance that is incorporated into protein, i.e., peripheral protein synthesis efficiency (PSE), was stimulated by hyperinsulinemia, as previously reported elsewhere (5). Peripheral PSE thus increased from ~25% after MP and FMP to 31% after SMP ingestion. These values are in the same range (~30%) as those previously found for muscle PSE after the ingestion of an AA mixture (43, 45). However, the higher PSE after SMP did not compensate for concomitant lower substrate availability, thus leading to a lower incorporation of dietary N into PP compared with MP. We therefore conclude that dietary AA alone stimulate muscle protein anabolism after the ingestion of a pure protein meal, solely by increasing the availability of substrate for protein synthesis, as previously reported (41). Insulin has an additional effect by stimulating anabolism but to a lesser extent in muscle than in the splanchnic area. In fact, the regional differential effect of insulinemia and aminoacidemia depends concomitantly on the size and fractional synthetic rate (FSR) of the protein pool involved. Because of the small size and high FSR of the splanchnic protein pool, modulation of its synthesis efficiency is the principal determinant of dietary N incorporation. In contrast, the small FSR but considerable pool size of peripheral tissues results in an ability to incorporate substrates, which is mainly dependent on their availability.

In conclusion, our model proved to be accurate in discriminating between different nutritional conditions and can be used as a predictive tool to highlight the acute postprandial mechanisms occurring in tissues and regulating the dynamic transfer of dietary N between organs. The replenishment dynamics of free AA pools and the synergistic effect of hormone secretions appear to play a primordial role in dietary N utilization by tissue proteins. Indeed, the slowing of gastric emptying and the temporary increase in splanchnic retention and anabolism observed after the SMP meal (which is more similar to the probable physiological case of mixed-meal ingestion) are likely to feature the processes involved in N homeostasis in the context of discontinuous intake of nutrients (31). These processes would allow the sparing of dietary N from deamination through the temporary "storage" of ingested AA in the labile splanchnic protein pool (17, 34, 36, 37, 46), while simultaneously buffering the peripheral tissues from excessive changes to free AA concentrations (1, 2), thus maintaining long-term homeostasis by spreading the release of meal-derived AA into the body over a longer period of time (18, 34, 35). We demonstrate that the reduced deamination of dietary protein observed experimentally during the postprandial nonsteady state in the presence of CHO was due to a higher dietary N incorporation into the splanchnic protein, whereas release to the peripheral area was markedly reduced. The anabolic action of insulin was particularly efficient in the splanchnic tissues, which are exposed to the highest concentrations of exogenous AA and are capable of responding with substantial protein synthesis because of their high protein turnover. In contrast with our previous inability to observe any fat effect on whole body dietary N retention from experimental data, in this case, we were able to detect a transient improving effect of fat on the incorporation of dietary N into splanchnic protein during the first postprandial hours. This was due to the delays in gastric emptying and dietary AA absorption, but the absence of insulin secretion led to a rapid release of dietary AA and their subsequent deamination. Finally, our model is little invasive and could usefully be confronted with several conditions to optimize food composition as a function of physiological and nutritional status (exercise, aging, hormonal impairment).


    ACKNOWLEDGEMENTS

We acknowledge the contribution of the modeling work group at the Institut National Agronomique Paris-Grignon for stimulating discussions during the course of this work.


    FOOTNOTES

This work was supported by Arilait Recherches (Paris, France).

Address for reprint requests and other correspondence: H. Fouillet, UMR de Physiologie de la Nutrition et du Comportement Alimentaire, Institut National Agronomique Paris-Grignon, 16 rue Claude Bernard, F-75231 Paris Cédex 05, France (fouillet{at}inapg.inra.fr).

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received 27 November 2000; accepted in final form 20 March 2001.


    REFERENCES
TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
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