Skip to main content

Modelling of protein turnover provides insight for metabolic demands on those specific amino acids utilised at disproportionately faster rates than other amino acids

Abstract

The nitrogen balance is regulated by factors such as diet, physical activity, age, pathogenic challenges, and climatic conditions. A paradigm was developed from published recommended rates of protein intake (g/kg/day) with corresponding rates of endogenous protein turnover and excretion, to extrapolate amino acid balances under various conditions. The average proportions of amino acids in the ingested proteins representing a well-balanced diet were used to assess intake and an average human composition profile from five major high-turnover proteins in the body to assess endogenous protein turnover. The amino acid excretion profiles for urine and sweat were constructed for males and females from published data. The model calculated the nitrogen balances for a range of amino acids to determine the amino acid requirements to support daily exertion. Histidine, serine, glycine, and ornithine were in negative balances in males and females and this potential deficit was greater in the higher body-mass ranges. Conversely, leucine, isoleucine, and valine were conserved during nitrogen flux and resulted in positive balances. The model was run under a scenario of high demand for the synthesis of IgG during a response to an infectious challenge which indicated that these were increased requirements for tyrosine, threonine, and valine. It was concluded that these amino acids represent points of limitation to anabolic metabolism by restriction of their supply at critical times of demand. This would especially occur under conditions of fitness training, maintaining intensive exercise regimes, facilitating responses to pathogenic challenge, or recovery from injury.

Introduction

The study of nitrogen balance has been extensively researched, revealing complex relationships between various pools of metabolites that act to maintain metabolic support for homeostasis and exercise activities (el-Khoury et al. 1994; Fielding and Parkington 2002; Millward 2004; Millward et al. 1996; Poortmans et al. 2012). Assessment of the nitrogen balance is difficult, as it needs to encompass protein turnover in tissues, organs and muscles as well as requirements for energy metabolism and the utilisation of amino acids in numerous biochemical pathways and regulatory systems. The rates of utilisation depend on factors such as genetics as well as diet, physical activity, pathogenic challenges, and climate. Notwithstanding these variations, consensus evaluations of nitrogen turnover have been determined, whereby 0.6 g/kg/day of protein would be sufficient to achieve a zero nitrogen balance. It has thus been recommended that 0.75–0.8 g/kg/day would be a minimum recommended daily intake for adults, but would be higher in babies and children undergoing critical growth phases (Tessari 2006). These values increase on the basis of rates of physical exercise activity, whereby adults undertaking muscle strength training would require 1.6–1.7 g/kg/day and those undertaking endurance training would require 1.2–1.4 g/kg/day (Dunstan et al. 2016; Fielding and Parkington 2002; Poortmans et al. 2012). The assessment of protein loss is more difficult to assess, because the waste nitrogen from energy metabolism is excreted as urea, ammonia, and creatinine. Amino acids and these waste products can also be lost directly via urine, faeces, and sweat, with the latter including contributions from natural moisturising factors leached from the skin via sweating, sebum, and desquamation (Dunstan et al. 2016).

Management of nitrogen balance could have a direct influence on fatigue, both in the healthy and unwell populations. Fatigue is experienced frequently in the healthy public from daily exertion which can vary greatly throughout the week for individuals with demanding work profiles, care commitments, fitness training, sports events and excursions. This type of fatigue is referred to as “peripheral” fatigue and results from impairment and micro-damage of muscle tissue, but can also occur as a result of low-level immune responses to acute infections (Prinsen et al. 2015). Simplistically, fatigue can be easily defined as “difficulty in initiating or sustaining voluntary activities” (Chaudhuri and Behan 2004). The logical approach to a scenario of increased exercise loading has been to increase protein intake to counter the higher rates of protein turnover. This generally has efficacy, but raises some interesting research questions when one considers that certain amino acids are utilised at disproportionally faster rates than others. The composition of dietary protein does not necessarily reflect the differential usage rates and thus taking in sufficient protein to meet the demands of a few, highly utilised amino acids, may leave others in surplus. The body does not effectively store amino acids, and therefore, there is potential for them to be used in oxidation for energy metabolism or converted to fatty acids.

Six key amino acids have been shown to be lost in sweat at concentrations much higher (4–20 fold) than those found in the plasma (Dunstan et al. 2016). These amino acids were identified as histidine, serine, glycine, ornithine, lysine, and aspartic acid. The concentrations of these amino acids were higher in sweat from females compared with males, suggesting that females may be more susceptible to fatigue from altered nitrogen homeostasis (Dunstan et al. 2017). It was also shown that the average losses of histidine, glycine, serine, and lysine comprised nearly 60% of amino acids excreted through urine (Dunstan et al. 2017). The combined losses of these key amino acids from urination and sweating were modelled under various scenarios ranging from sedentary- to medium-level exertion. It was demonstrated that the losses of these amino acids become very extensive, as exertion levels rise (Dunstan et al. 2017).

Serine, glycine, and aspartic acid can all be produced in the body and are thus deemed non-essential. However, under periods of elevated exertion and activity or during periods of pathogenic challenge, the body may not be able to meet the demand for these amino acids by the way of endogenous supply and ingested proteins (de Koning et al. 2003; Jackson 1991; Meléndez-Hevia et al. 2009; Rezaei et al. 2013; Wang et al. 2013). These amino acids are required in non-nutritive metabolic pathways which make them very difficult to quantify despite their considerable avenues of utilisation. Examples of the metabolic functions of amino acids have been summarised for glycine, serine, histidine, lysine, ornithine, and aspartic acid in Table 1. The plasma maintains a reservoir of amino acids which services the supply of these nutrients to muscles, tissues, and organs in the body. The composition of amino acids is maintained under homeostasis via hormonal regulation of anabolic (human growth hormone and insulin-like growth factor) and catabolic (cortisol and cytokines) processes, all of which are influenced by protein ingestion and bodily activity.

Table 1 Summary of the proteinogenic and metabolic utilisation profiles for those amino acids identified as being utilised at disproportionately faster rates than other amino acids in humans

The goal of this investigation was to model the dietary intake of amino acids via a range of protein sources in regard to published rates of protein turnover and excretion. On the premise that certain key amino acids are utilised and excreted at higher rates than others, the data were then adjusted to include average rates of excretion of selected amino acids which have been reported in the literature. This simple approach can provide insight as to how deficits in certain amino acids can build over time with constant daily exertion. The model was then used to demonstrate potential localised demands (a) in muscles during a 60 min exercise session and (2) in bone marrow for IgG production during an infectious challenge.

Methods

The general interactions and flow of protein nitrogen have been well summarised by Tessari (2006). To assess the total daily nitrogen losses, it was proposed that this will be 56 mg/kg/day based on general average excretion rates of 36 mg/kg/day from urine, 12 mg/kg/day from faeces, and 8 mg/kg/day from a combination of saliva, desquamations, sweat, sebum, hair, and nails (Tessari 2006). This represents the obligatory nitrogen loss (ONL) which would represent 3.92 g N for a 70 kg person, and if one assumed an equivalence factor of 6.25 g protein per g of nitrogen, then this would represent 24.5 g protein per day.

It was determined that 0.6 g protein/kg/day is the level required to deliver a “0” nitrogen balance without growth and increased muscle mass (FAO 1985; Poortmans et al. 2012; Waterlow 1984; Waterlow and Jackson 1981). It was thus proposed that 0.75–0.8 g protein/kg/day would be a minimum recommended daily intake for adults (Tessari 2006) and these values would increase to 1.2–1.4 g protein/kg/day for endurance athletes and 1.6–1.7 g protein/kg/day for those undertaking muscle strength training (Fielding and Parkington 2002; Poortmans et al. 2012). The standard rate used for this modelling procedure was set at 1.2 g protein/kg/day (Tessari 2006). To develop the protein utilisation aspects of the model, a number of parameters were fixed based on literature reference values: protein turnover rate was 5.7 g/kg/day (Poortmans et al. 2012; Waterlow 1984; Waterlow and Jackson 1981); 15% protein intake oxidised for metabolism; 75% of protein intake used for protein synthesis; 27% of protein turnover oxidised for metabolism; 67% of protein turnover used for protein synthesis; 6–10% of amino acids from the proteins would be utilised in various metabolic pathways; obligatory N excretion losses as protein equivalents 350 mg/kg/day (i.e., 56 × 6.25) (Tessari 2006).

The next stage of development for the model was to extrapolate from the assessment of protein flux to amino acid transitions which is difficult when considering the highly variable amino acid compositions of different proteins. A simplistic approach for modelling was developed to estimate the nitrogen balances of the group of 6 amino acids shown to be lost at disproportionately faster rates: serine, glycine, histidine, lysine and aspartic acid as well as the non-proteinogenic ornithine, for comparison with the non-essential glutamine/glutamic acid (Glx), alanine and proline, as well as the essential leucine, isoleucine, valine, threonine, methionine, tyrosine, and phenylalanine. A representative human protein composition of these amino acids was estimated by averaging the percentage abundances of amino acids from five highly abundant human proteins: collagen (Chung and Miller 1974), albumin (Spahr and Edsall 1964), haemoglobin (Stein 1958; Stein et al. 1957), actin (Carsten 1963; Raszkowski et al. 1977), and myosin (Raszkowski et al. 1977), as shown in Table 2. A representative ingested protein composition of these amino acids was similarly estimated by averaging the percentage abundances of amino acids from meat and plant sources, assuming a well-balanced diet (Table 2). The meat source itself was averaged from beef (Samicho et al. 2013), pork (Okrouhlá et al. 2006), chicken (Rossi et al. 2009), and fish (Diniz et al. 2013), whereas the plant composition was averaged from peas (Pownall et al. 2010), rice (Carvalho et al. 2013), beans (Carvalho et al. 2013), and wheat (Chen and Bushuk 1970) (Supplementary data, Table A1). This provided the means to assign quantitative values for amino acid utilisation using the average meat/plant percentages to extrapolate the intake of amino acids via ingested proteins and the human average percentages to estimate the contributions from endogenous protein turnover.

Table 2 Average percentage relative abundance compositions of selected amino acids in human protein composition (Table A1) and dietary sources (Table A1)

The development of the excretion component of the model was the most difficult to conceptualise. Evaluations of nitrogen balance by measures of total nitrogen flux have established generally accepted partitions for nitrogen flow (Poortmans et al. 2012; Tessari 2006; Waterlow 1984). Extrapolating them to protein quantities has its uses for evaluating protein requirements, but drilling down to amino acid fluxes is problematic. The first option is to assume that amino acids would be lost at the same proportions, as they are ingested in proteins. This is extremely unlikely for several reasons, since: certain amino acids are used in multiple biochemical pathways in addition to protein synthesis; endogenous production of non-essential amino acids will skew the intake proportions; and certain amino acids are lost at disproportionately higher rates in urine and sweat than other amino acids (Dunstan et al. 2016, 2017). To counter this dilemma, the model was designed to generate two sets of estimates regarding input and output balances for each of the amino acids. The first estimate assumed that the excretion profile of amino acids mirrored the average protein composition of ingested proteins and the second estimate utilised excretion profiles that were adjusted to reflect concentrations measured in urine and sweat (Dunstan et al. 2016, 2017). Separate models were established for males and females, because significantly, different excretion characteristics were noted between the sexes (Dunstan et al. 2017). The design of the model allowed comparisons to be made between the sexes while demonstrating relationships between increasing body mass and the rates of protein intake and utilisation. The parameters used and their corresponding rationale are summarised in Table 3. The urine profiles previously reported in a healthy population group of males and females: n = 30 were also used to test the model (Jones et al. 2005).

Table 3 Summary of the parameters used in the modelling of amino acid fluxes based on protein intake, turnover, metabolism, and excretion

The model was then used to estimate protein utilisation rates for an 80 kg male with a protein intake rate at 0.6 g/kg/day to generate a theoretical 0 nitrogen balance. It was argued that 90% of this intake would be utilised for oxidation and synthesis of new proteins [15% and 75%, respectively, (Tessari 2006)] and that this would constitute the rate of “minimal protein utilisation” (MPU) required from the diet per day for maintenance. This rate could be considered to represent a minimal estimate of the extra demand on endogenous protein turnover required during periods of exercise when ingestion is not possible. The nitrogen balance of amino acids was thus estimated in the context of amino acid utilisation during exercise by setting the protein intake rate to 0, and adding the rate of MPU to the endogenous protein turnover rate in muscle proteins. In this way, the model could be tuned to identify those amino acids inducing the greatest demand on muscle protein turnover during exercise.

Results and discussion

A simplistic model was developed utilising published rates of protein intake, oxidation, protein synthesis, and excretion, to investigate the nitrogen balance in terms of the throughput of individual amino acids. The first appraisal involved using the model to evaluate the fluxes for a 70 kg male and a 70 kg female with a protein intake set at 1.2 g/kg/day and a protein synthesis rate of 5.7 g/kg/day, while the remaining fixed variables were set, as shown in Table 3. The resulting calculations of protein intake, turnover, and utilisation have been presented for the 70 kg person, as shown in Table 4.

Table 4 Daily utilisation of protein resources for a 70 kg individual has been calculated by assuming a protein intake of 1.2 g protein/kg/day and fixed rates of utilisation by oxidation, protein synthesis, and excretory losses

These values were extrapolated from units of protein into amino acids using average intake compositions from plant and meat proteins and turnover/excretion compositions from human proteins. The average percentage composition of amino acids in the plant/meat proteins was used to estimate the daily specific gram intake of the selected amino acids from (A) 84 g of dietary protein and (B) 399 g of protein turnover, as shown in Table 5. The total daily usage of each amino acid was then calculated to predict losses from (C) protein synthesis, (D) oxidation metabolism and (E) excretion. These values are entered as negative, because they represent utilisation of resources and thus summing the input and output values from (A) to (E) generated the nitrogen balance (F). There are no separate estimates at this stage between males and females, because fluxes were determined on a g/kg/day basis.

Table 5 Predicted levels of amino acids for a 70 kg male and a 70 kg female with a protein intake set at 1.2 g/kg/day and a protein turnover rate of 5.7 g/kg/day which was generated by the model from protein intake and protein turnover as well as the predicted fluxes into energy metabolism, protein synthesis, and excretion via urine, faeces, and sweat, as shown in Table 3

The values of nitrogen balance calculated for each of the amino acids in (F) were based on the assumption that the amino acids were utilised and excreted in the same proportions that they were ingested or provided from endogenous protein turnover. In this context, the nitrogen balance values were all positive and collectively (+ 8.3 g) represented 1.7% of the daily utilisation of proteins (483 g). However, certain amino acids are used in multiple biochemical pathways and are excreted at disproportionately faster rates than other amino acids, as shown in Table 1. The skewed rates of utilisation for metabolism are very difficult to estimate, and thus, this parameter could not be effectively adjusted. However, the model could be altered to include adjustments to represent more realistic rates of excretion via urine and sweat (Dunstan et al. 2016, 2017). The adjusted excretion rates for males (G) and females (H) resulted in enhanced losses of histidine, serine, glycine, and ornithine shown by more negative nitrogen balance assessments (Table 5). As a consequence, the net balances of proline, aspartic acid, phenylalanine, leucine, isoleucine, and valine all increased substantially [compared with (F)].

An external source of urine data was also tested for a mixed group of 11 healthy males and 19 healthy females (Jones et al. 2005), yielding similar results with negative adjusted nitrogen balances observed for histidine (− 1.4), serine (− 0.8), glycine (− 4.4), and ornithine (− 0.4) with all others in positive balance (supplementary Table A4). The skewed losses of histidine, serine, glycine, and ornithine could thus be viewed as potential sacrificial losses to conserve the remainder of the amino acids.

The adjusted nitrogen balances for the amino acids were compared between the sexes in Fig. 1 which showed that the males have a generally higher output of histidine, whereas the females had higher outputs of glycine and serine. The model is not perfect, because it has not included adjustments for skewed losses of amino acids from utilisation in metabolic pathways and losses via faeces. However, it does show that the skewed nature of excretion of certain amino acids at faster rates than others has impact on demand for those amino acids. Deficits in histidine can lead to anaemia and has been shown to be critical for the formation of haemoglobin and red blood cells (Clemens et al. 1984; Cooperman and Lopez 2002; Kopple and Swendseid 1975). Histidine is also required for the formation of the dipeptide carnosine (β-alanyl-l-histidine) which is highly concentrated in the muscles and brain (Bauchart et al. 2007; Reddy et al. 2005; Tamaki et al. 1984). The ingestion of protein is not the only source of histidine. When consuming meat, one is also taking in substantial quantities of carnosine which is not necessarily included in the evaluation of “protein”. Most of the ingested carnosine (70–80%) is broken down to histidine and β-alanine in the digestive tract prior to absorption (Bauchart et al. 2007; Tamaki et al. 1984). It was concluded that consumption of meat, especially for athletes, was vital to meet protein turnover demands to supply sufficient histidine. It also raises the question as to whether replacement of meat with cheaper whey proteins is sufficient to meet the demands of exercise or recovery from ill-health and pathogenic challenge.

Fig. 1
figure 1

Comparison of the nitrogen balances for each of the amino acids assessed in the model for males and females determined at 70 kg with a protein intake of 1.2 g/kg/day and a protein turnover rate of 5.7 g/kg/day. The first series (assuming input = output) shows the positive nitrogen balances calculated for all the amino acids on the basis that they would be excreted in the same proportions in which they would be generated as a resource from ingested proteins and from endogenous protein turnover. The series for males and females show the nitrogen balances calculated for all the amino acids when the model used realistic excretion rates for each amino acid which had been previously measured in males and females (Dunstan et al. 2016, 2017)

Serine, glycine, and histidine are the major components lost in urine and sweat. Serine is the direct metabolic precursor to glycine synthesis, and together, these amino acids contribute to numerous metabolic roles in the body, as summarised in Table 1. The human body has the capacity to synthesise serine and glycine on demand, but under certain conditions, it may not be able to keep up with demand (Darling et al. 1999; Eagle 1959; Jackson 1991; Maxwell et al. 1956; Meléndez-Hevia et al. 2009; Rezaei et al. 2013; Stover et al. 1997; Wang et al. 2013; Wu 2010a, b).

The model was then applied to looking at the influence of body masses on males (70–100 kg) and females (50–80 kg) in Fig. 2. Effectively, it demonstrates that the heavier the person (male or female), the greater the negative balances are for histidine, serine, glycine, and ornithine and the greater the apparent accumulations of the remaining amino acids, particularly leucine, aspartic acid, and proline. Thus, the demands on intake of histidine are more substantial in the higher weight ranges and there is a requirement for the enhanced provision of glycine, serine, and ornithine from endogenous metabolism. The net result for the essential amino acids would appear to be that there is some conservation of the essential amino acids in the heavier weight ranges. However, it should be noted that amino acids cannot be “stored”—they are either incorporated into proteins, utilised in oxidative or other metabolic pathways, converted to fats, or excreted. It is evident from the modelling in Fig. 2 that there would be a higher risk of having insufficient histidine, glycine, and serine in the heavier weight ranges. These components are, therefore, more likely to become limiting factors to certain aspects of metabolism and anabolism. If these factors were limiting for protein synthesis, then the accumulated essential amino acids may not be utilised as required in protein synthesis, and subsequently, they would be oxidised, converted to fat, or excreted. This could provide a novel insight as to why people in the higher weight range would find it harder to lose weight, even if they were eating balanced diets with appropriate protein and carbohydrate content with low fat.

Fig. 2
figure 2

Comparison of the nitrogen balances for each of the amino acids assessed in the model for males determined at 70, 80, 90, and 100 kg and for females at 50, 60, 70, and 80 kg with a protein intake of 1.2 g/kg/day and a protein turnover rate of 5.7 g/kg/day. The top graphs show the positive nitrogen balances calculated for all the amino acids on the basis that they would be excreted in the same proportions in which they would be generated from ingested proteins and from endogenous protein turnover. The lower graphs represent the nitrogen balances calculated for all the amino acids when the model used realistic excretion rates for each amino acid which had been previously measured in males and females (Dunstan et al. 2016, 2017)

To consider this further, the influence on increasing protein intake was assessed in the model for an 80 kg male in Fig. 3, where increasing protein intake has some minimal beneficial influence on serine and glycine but virtually no impact on histidine. Conversely, increasing the protein intake led to increasing the positive balance of the other amino acids, but, if histidine, serine and glycine were in short supply, this could potentially limit synthesis of proteins and the surplus essential amino acid components would be oxidised, converted to fat stores or excreted.

Fig. 3
figure 3

Comparison of the nitrogen balances for each of the amino acids assessed in the model for 80 kg males determined at a protein intake of 0.8, 1.2, and 1.6 g/kg/day and a protein turnover rate of 5.7 g/kg/day. The top graph shows the positive nitrogen balances calculated for all the amino acids on the basis that they would be excreted in the same proportions in which they would be generated from ingested proteins and from endogenous protein turnover. The lower graph represents the nitrogen balances calculated for all the amino acids when the model used realistic excretion rates for each amino acid which had been previously measured in males and females (Dunstan et al. 2016, 2017)

Increasing the protein synthesis rates might be expected to occur as exercise demand increases with increasing intensity of training. As expected, the higher rates of protein synthesis and turnover shown in Fig. 4 led to more histidine, serine, and glycine being recycled via endogenous protein turnover, and thus, the nitrogen balance for these three components improved (Fig. 4). However, increased protein turnover also leads to an increased availability of the remaining amino acids. If any of the amino acids lost at disproportionately faster rates via metabolism and excretion pathways became limiting for protein synthesis due to the negative nitrogen balance, then the essential amino acids will be lost to oxidation, converted to fat or excreted. Once processed and stored as fats, the essential amino acids cannot be reconstructed and are permanently lost as a critical resource.

Fig. 4
figure 4

Comparison of the nitrogen balances for each of the amino acids assessed in the model for 80 kg males determined at protein turnover rates of 3, 4, 5, 6, and 7 g/kg/day with a protein intake of 1.2 g/kg/day. The top graph shows the positive nitrogen balances calculated for all the amino acids on the basis that they would be excreted in the same proportions in which they would be generated from ingested proteins and from endogenous protein turnover. The lower graph represents the nitrogen balances calculated for all the amino acids when the model used realistic excretion rates for each amino acid which had been previously measured in males and females (Dunstan et al. 2016, 2017)

Investigations of nitrogen balance have been largely focussed on a daily requirement schedule. When undertaking an extended period of exercise which prohibits protein intake, the body is subjected to a phase of intensified demand to provide endogenous resources to support the activity. The model was run to ascertain the immediate amino acid demands on endogenous protein turnover during exercise without protein ingestion. The results in Fig. 5 show that there were negative nitrogen balances for most of the amino acids, where Glx showed the greatest impact. These outcomes would represent the shortfall from operating without ingestion of protein as well as the compensation for high losses in sweat of specific components. During the post-exercise recovery phase, muscle protein turnover will continue for hours after exertion to support the recuperation and repair processes (Martin-Rosset 2008). Digestion is limited for hours after exercise, and thus, exogenous supply of protein amino acids is not readily forthcoming (Brouns et al. 1987; Burton et al. 2004; Butterfield 1987; Martin-Rosset 2008; van Wijck et al. 2013; Williams et al. 1996). Even if digestion were fully operational, it would take hours before the proteins would be fully broken down for utilisation of the amino acids by the body. However, the absorption of free amino acids is not affected by moderate to severe exercise (Cammack et al. 1982). These modelling evaluations thus provided a premise for developing a supplementation strategy to replenish those amino acids in negative balance (histidine, serine, glycine, and ornithine). This approach would better sustain a positive nitrogen balance, and facilitate anabolic metabolism for recovery and repair processes. The essential amino acids released from endogenous protein turnover would not then be surplus to demand and lost as “wastage”, because the limiting factors for anabolism have been replaced. Direct replenishment of these amino acids may also be feasible in certain endurance sports and may have substantial long-term benefits in maintaining muscle integrity and reducing damage.

Fig. 5
figure 5

Negative nitrogen balances of amino acids estimated by the model (mg/h) during prolonged exercise with no ingestion of protein and no excretion via urine or faeces. Under this scenario, there is an increased demand on muscle protein turnover to supply the amino acid resources to support exercise

In the scenario where an individual is responding to an infectious challenge, the production of IgG represents a primary immune response, where 66–95% is derived from the bone marrow and the remainder in the spleen. It has been estimated that this represents around 960 mg per day for a healthy 80 kg individual and this could double in those people with activated immune systems (Thornton et al. 1996). This rate of synthesis of IgG in the healthy individual represents around 0.3% of the whole body protein synthesis and adjustments in this context represent negligible impact on the whole body amino acid utilisation profile. However, since the bone marrow represents around 2.6 kg of the body mass (Fliedner et al. 2002) and is responsible for most of the IgG synthesis, there would be very high localised demand for specific amino acids in response to pathogenic challenge. This may have a net draining effect on the plasma supply of these amino acid resources. Appraisal of the amino acid composition of the IgG heavy chain indicated that the major components include serine (9.1%), valine (8.4%), threonine (7.4%), and tyrosine (6.1%) (Chaplin et al. 1965) which are present at 1.5–2 times their average composition calculated from the other five body proteins (see Table 2). On this basis, the model was run to evaluate the potential impact on amino acid demand within the bone marrow by slightly increasing the specific rates of utilisation of these amino acids for protein synthesis from endogenous resources, as shown in Table 2 (see also supplementary Table A1). The nitrogen balances for the amino acids under these conditions are summarised in Fig. 6 for comparison with the balances under normal healthy conditions.

Fig. 6
figure 6

Comparison of the nitrogen balances for each of the amino acids assessed in a healthy 80 kg male compared with an equivalent male mounting an IgG response to pathogenic challenge. The amino acid utilisation rates were adjusted to represent the specific increases in demand for the major components of the IgG heavy chain, as shown in Table 2

It was apparent that the host defence response would generate higher levels of demand for serine, tyrosine, threonine, and valine, resulting in their negative nitrogen balances. Serine can potentially be generated endogenously, but under a critical requirement for a rapid response, the body may not be able to keep up with demand. Tyrosine can be synthesised from phenylalanine, but phenylalanine is an essential amino acid, and both may become limiting during this IgG response. Valine is an essential branch chain amino acid and must come from exogenous supply. The body instigates a catabolic response to pathogenic challenge to assist in provision of the necessary substrates from the turnover of muscle proteins required for supporting the immune defence. This is instigated because a rapid and efficient response is required to ensure that the infection is curtailed before becoming too well established. The extent of protein synthesis may well have been underestimated for supporting the response to pathogenic challenge, and this current modelling demonstrates that certain amino acids may become locally limiting under periods of heavy demand for production of large quantities of specific proteins for immune function or repair and recovery from injury.

It was concluded that it is important to focus on meeting the amino acid requirements of people under various regimes of activities, rather than generally just considering crude protein requirements. The negative balances observed in this model identified histidine, glycine, serine, and ornithine as potentially limiting factors for anabolic metabolism, especially under conditions of fitness training and maintaining intensive exercise regimes. If an individual is suffering an infectious challenge, then this model would suggest that tyrosine, threonine and valine should also be supplemented. The grams per day in negative balance (Table 5) provide a guide for the proportions and quantities of amino acids for specific supplementation. This model approach provides a basis for explaining how a daily provision of just 5 g of amino acids, representing 6% of the daily protein intake, could provide benefit if taken immediately after or during exercise, or during pathogenic challenge. People in higher weight ranges would have greater demands on the supply of these amino acids to sustain a positive nitrogen balance.

References

  • Bauchart C, Savary-Auzeloux I, Patureau Mirand P, Thomas E, Morzel M, Remond D (2007) Carnosine concentration of ingested meat affects carnosine net release into the portal vein of minipigs. J Nutr 137:589–593

    Article  CAS  PubMed  Google Scholar 

  • Briggs S, Freedland RA (1976) Effect of ornithine and lactate on urea synthesis in isolated hepatocytes. Biochem J 160:205–209

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Brouns F, Saris WHM, Rehrer NJ (1987) Abdominal complaints and gastrointestinal function during long-lasting exercise. Int J Sports Exerc Med 8:175–189

    Article  CAS  Google Scholar 

  • Bucci L, Hickson JF, Pivarnik JM, Wolinsky I, McMahon JC, Turner SD (1990) Ornithine ingestion and growth hormone release in bodybuilders. Nutr Res 10:239–245

    Article  CAS  Google Scholar 

  • Burton DA, Stokes K, Hall GM (2004) Physiological effects of exercise. BJA Educ 4(6):185–188

    Google Scholar 

  • Butterfield GE (1987) Whole-body protein utilisation in humans. Med Sci Sports Exerc 19:S157–S165

    Article  CAS  PubMed  Google Scholar 

  • Cammack J, Read NW, Cann PA, Greenwood B, Holgate AM (1982) Effect of prolonged exercise on the passage of a solid meal through the stomach and small intestine. Gut 23:957–961

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Carsten ME (1963) Actin, its amino acid composition and its reaction with iodoacetate. Biochemistry 2:32–34

    Article  CAS  PubMed  Google Scholar 

  • Carvalho AV, Bassinello PZ, de Oliveira A, Ferreira TF, Carvalho RN, Nakamoto S (2013) Characterization of pre-gelatinized rice and bean flour. Food Sci Technol 33:245–250

    Article  Google Scholar 

  • Chaplin H, Cohen S, Press EM (1965) Preparation and properties of the peptide chains of normal human 19S gamma-globulin (IgM). Biochem J 95:256–261

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Chaudhuri A, Behan PO (2004) Fatigue in neurological disorders. Lancet 363:978–988

    Article  PubMed  Google Scholar 

  • Chen CH, Bushuk W (1970) Nature of proteins in Triticale and its parental species: 1. Solubility characteristics and amino acid composition of endosperm proteins. Can J Plant Sci 50:9–14

    Article  CAS  Google Scholar 

  • Chen PE, Geballe MT, Stansfeld PJ, Johnston AR, Yuan H, Jacob AL, Snyder JP, Traynelis SF, Wyllie DJ (2005) Structural features of the glutamate binding site in recombinant NR1/NR2A N-methyl-d-aspartate receptors determined by site-directed mutagenesis and molecular modeling. Mol Pharmacol 67:1470–1484

    Article  CAS  PubMed  Google Scholar 

  • Chung E, Miller EJ (1974) Collagen polymorphism: characterization of molecules with the chain composition (alpha 1 (3)03 in human tissues. Science 183:1200–1201

    Article  CAS  PubMed  Google Scholar 

  • Civitelli R, Villareal DT, Agnusdei D, Nardi P, Avioli LV, Gennari C (1992) Dietary l-lysine and calcium metabolism in humans. Nutrition 8:400–405

    CAS  PubMed  Google Scholar 

  • Clemens RA, Kopple JD, Swendseid ME (1984) Metabolic effects of histidine-deficient diets fed to growing rats by gastric tube. J Nutr 114:2138–2146

    Article  CAS  PubMed  Google Scholar 

  • Cooperman JM, Lopez R (2002) The role of histidine in the anemia of folate deficiency. Exp Biol Med 227:998–1000

    Article  CAS  Google Scholar 

  • Dai Z, Wu Z, Yang Y, Wang J, Satterfield MC, Meininger CJ, Bazer FW, Wu G (2013) Nitric oxide and energy metabolism in mammals. BioFactors (Oxf Engl) 39:383–391

    Article  CAS  Google Scholar 

  • Darling PB, Dunn M, Sarwar G, Brookes S, Ball RO, Pencharz PB (1999) Threonine kinetics in preterm infants fed their mothers’ milk or formula with various ratios of whey to casein. Am J Clin Nutr 69:105–114

    Article  CAS  PubMed  Google Scholar 

  • Davidson MB (1987) Effect of growth hormone on carbohydrate and lipid metabolism. Endocr Rev 8:115–131

    Article  CAS  PubMed  Google Scholar 

  • de Koning TJ, Snell K, Duran M, Berger R, Poll-The B-T, Surtees R (2003) L-serine in disease and development. Biochem J 371:653–661

    Article  PubMed  PubMed Central  Google Scholar 

  • Diniz GS, Barbarino E, Oiano-Neto J, Pacheco S, Lourenço SO (2013) Gross chemical profile and calculation of nitrogen-to-protein conversion factors for nine species of fishes from coastal waters of Brazil. Latin Am J Aquat Res 41(2):254–264

    Google Scholar 

  • Dunstan RH, Sparkes DL, Dascombe BJ, Macdonald MM, Evans CA, Stevens CJ, Crompton MJ, Gottfries J, Franks J, Murphy G, Wood R, Roberts TK (2016) Sweat facilitated amino acid losses in male athletes during exercise at 32-34 degrees C. PLoS One 11:e0167844

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Dunstan RH, Sparkes DL, Dascombe BJ, Stevens CJ, Murphy GR, Macdonald MM, Gottfries J, Gottfries CG, Roberts TK (2017) Sex differences in amino acids lost via sweating could lead to differential susceptibilities to disturbances in nitrogen balance and collagen turnover. Amino Acids 49:1337–1345

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Eagle H (1959) Amino acid metabolism in mammalian cell cultures. Science 130:432–437

    Article  CAS  PubMed  Google Scholar 

  • el-Khoury AE, Fukagawa NK, Sanchez M, Tsay RH, Gleason RE, Chapman TE, Young VR (1994) Validation of the tracer-balance concept with reference to leucine: 24-h intravenous tracer studies with L-[1-13C]leucine and [15 N-15 N]urea. Am J Clin Nutr 59:1000–1011

    Article  CAS  PubMed  Google Scholar 

  • Evain-Brion D, Donnadieu M, Roger M, Job JC (1982) Simultaneous study of somatotrophic and corticotrophic pituitary secretions during ornithine infusion test. Clin Endocrinol 17:119–122

    Article  CAS  Google Scholar 

  • Fao J (1985) Energy and protein requirements. Report of a joint FAO/WHO/UNU Expert Consultation. World Health Org Tech Rep Ser 724:1–206

    Google Scholar 

  • Felig P (1975) Amino acid metabolism in man. Annu Rev Biochem 44:933–955

    Article  CAS  PubMed  Google Scholar 

  • Felig P, Owen OE, Wahren J, Cahill GF Jr (1969) Amino acid metabolism during prolonged starvation. J Clin Invest 48:584–594

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Fielding RA, Parkington J (2002) What are the dietary protein requirements of physically active individuals? New evidence on the effects of exercise on protein utilization during post-exercise recovery. Nutr Clin Care Off Publ Tufts Univ 5:191–196

    Article  Google Scholar 

  • Fliedner TM, Graessle D, Paulsen C, Reimers K (2002) Structure and function of bone marrow hemopoiesis: mechanisms of response to ionizing radiation exposure. Cancer Biotherap Radiopharm 17:405–426

    Article  CAS  Google Scholar 

  • Hafkenscheid JC, Hectors MP (1975) An enzymic method for the determination of the glycine/taurine ratio of conjugated bile acids in bile. Clin Chim Acta Int J Clin Chem 65:67–74

    Article  CAS  Google Scholar 

  • Hall JC (1998) Glycine. JPEN 22:393–398

    Article  CAS  Google Scholar 

  • Harmeyer J (2002) The physiological role of l-carnitine. Lohmann Inf 27:15–21

    Google Scholar 

  • Hobart LJ, Seibel I, Yeargans GS, Seidler NW (2004) Anti-crosslinking properties of carnosine: significance of histidine. Life Sci 75:1379–1389

    Article  CAS  PubMed  Google Scholar 

  • Hoppel C (2003) The role of carnitine in normal and altered fatty acid metabolism. Am J Kidney Dis 41:S4–S12

    Article  CAS  PubMed  Google Scholar 

  • Jackson AA (1991) The glycine story. Eur J Clin Nutr 45:59–65

    CAS  PubMed  Google Scholar 

  • Johnson JL, Duran M (2001) Molybdenum cofactor deficiency and isolated sulfite oxidase deficiency. In: Scriver CR, Beaudet AL, Valle D, Sly WS (eds) The metabolic and molecular bases of inherited disease. McGraw-Hill Inc, New York, pp 3163–3177

    Google Scholar 

  • Jones MG, Cooper E, Amjad S, Goodwin CS, Barron JL, Chalmers RA (2005) Urinary and plasma organic acids and amino acids in chronic fatigue syndrome. Clin Chim Acta Int J Clin Chem 361:150–158

    Article  CAS  Google Scholar 

  • Konishi Y, Koosaka Y, Maruyama R, Imanishi K, Kasahara K, Matsuda A, Akiduki S, Hishida Y, Kurata Y, Shibamoto T, Satomi J, Tanida M (2015) l-Ornithine intake affects sympathetic nerve outflows and reduces body weight and food intake in rats. Brain Res Bull 111:48–52

    Article  CAS  Google Scholar 

  • Kopple JD, Swendseid ME (1975) Evidence that histidine is an essential amino acid in normal and chronically uremic man. J Clin Invest 55:881–891

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Martin-Rosset W (2008) Protein requirements and allowances of the exercising horse. In: Saastamoinen MT, Martin-Rosset W (eds) Nutrition of the exercising horse. Wageningen Academic Publishers, The Netherlands, pp 183–204

    Google Scholar 

  • Maxwell M, McCoy TA, Neuman RE (1956) The amino acid requirements of the Walker carcinosarcoma 256 in vitro. Can Res 16:979–984

    CAS  Google Scholar 

  • Meléndez-Hevia E, de Paz-Lugo P, Cornish-Bowden A, Cárdenas ML (2009) A weak link in metabolism: the metabolic capacity for glycine biosynthesis does not satisfy the need for collagen synthesis. J Biosci 34:853–872

    Article  CAS  PubMed  Google Scholar 

  • Millward DJ (2004) Macronutrient intakes as determinants of dietary protein and amino acid adequacy. J Nutr 134:1588s–1596s

    Article  CAS  PubMed  Google Scholar 

  • Millward DJ, Fereday A, Gibson NR, Pacy PJ (1996) Post-prandial protein metabolism. Bailliere’s Clin Endocrinol Metab 10:533–549

    Article  CAS  Google Scholar 

  • Nieto-Alamilla G, Marquez-Gomez R, Garcia-Galvez AM, Morales-Figueroa GE, Arias-Montano JA (2016) The histamine H3 receptor: structure, pharmacology, and function. Mol Pharmacol 90:649–673

    Article  CAS  PubMed  Google Scholar 

  • Okrouhlá M, Stupka R, Čítek J, Šprysl M, Kluzáková E, Trnka M, Štolc L (2006) Amino acid composition of pig meat in relation to live weight and sex. Czech J Anim Sci 51:529–534

    Article  Google Scholar 

  • Pokrovskiy MV, Korokin MV, Tsepeleva SA, Pokrovskaya TG, Gureev VV, Konovalova EA, Gudyrev OS, Kochkarov VI, Korokina LV, Dudina EN, Babko AV, Terehova EG (2011) Arginase inhibitor in the pharmacological correction of endothelial dysfunction. Int J Hyperten 2011:515047

    Article  CAS  Google Scholar 

  • Poortmans JR, Carpentier A, Pereira-Lancha LO, Lancha A Jr (2012) Protein turnover, amino acid requirements and recommendations for athletes and active populations. Br J Med Biol Res 45:875–890

    Article  CAS  Google Scholar 

  • Pownall TL, Udenigwe CC, Aluko RE (2010) Amino acid composition and antioxidant properties of pea seed (Pisum sativum L.) enzymatic protein hydrolysate fractions. J Agric Food Chem 58:4712–4718

    Article  CAS  PubMed  Google Scholar 

  • Prinsen H, van Dijk JP, Zwarts MJ, Leer JW, Bleijenberg G, van Laarhoven HW (2015) The role of central and peripheral muscle fatigue in postcancer fatigue: a randomized controlled trial. J Pain Symptom Manag 49:173–182

    Article  Google Scholar 

  • Raghavan M, Smith CK, Schutt CE (1989) Analytical determination of methylated histidine in proteins: actin methylation. Anal Biochem 178:194–197

    Article  CAS  PubMed  Google Scholar 

  • Rajendra S, Lynch JW, Schofield PR (1997) The glycine receptor. Pharmacol Therap 73:121–146

    Article  CAS  Google Scholar 

  • Raszkowski RR, Welty JD, Peterson MB (1977) The amino acid composition of actin and myosin and Ca2+ -activated myosin adenosine triphosphatase in chronic canine congestive heart failure. Circ Res 40:191–198

    Article  CAS  PubMed  Google Scholar 

  • Rawlings AV, Harding CR (2004) Moisturization and skin barrier function. Dermatol Ther 17(Suppl 1):43–48

    Article  Google Scholar 

  • Rawlings AV, Scott IR, Harding CR, Bowser PA (1994) Stratum corneum moisturization at the molecular level. J Invest Dermatol 103:731–741

    Article  CAS  PubMed  Google Scholar 

  • Reddy VP, Garrett MR, Perry G, Smith MA (2005) Carnosine: a versatile antioxidant and antiglycating agent. Sci Aging Knowl Environ SAGE KE 2005:pe12

    Google Scholar 

  • Rezaei R, Wang W, Wu Z, Dai Z, Wang J, Wu G (2013) Biochemical and physiological bases for utilization of dietary amino acids by young Pigs. J Anim Sci Biotechnol 4:7

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Rodwell VW (2000) Conversion of amino acids to specialized products. In: Murray RK, Granner DK, Mayes PA, Rodwell PW (eds) Harper’s biochemistry. Appleton & Lange, New York

    Google Scholar 

  • Rossi DM, Flôres SH, Venzke JG, Ayub MAZ (2009) Biological evaluation of mechanically deboned chicken meat protein hydrolysate. Revista de Nutrição. 22:879–885

    Article  CAS  Google Scholar 

  • Samicho Z, Ab Mutalib SR, Abdullah N (2013) Amino acid composition of droughtmaster beef at various beef cuts. Agric Sci 4:61–64

    CAS  Google Scholar 

  • Scott IR, Harding CR, Barrett JG (1982) Histidine-rich protein of the keratohyalin granules. Source of the free amino acids, urocanic acid and pyrrolidone carboxylic acid in the stratum corneum. Biochem Biophys Acta 719:110–117

    Article  CAS  PubMed  Google Scholar 

  • Snell K, Natsumeda Y, Weber G (1987) The modulation of serine metabolism in hepatoma 3924A during different phases of cellular proliferation in culture. Biochem J 245:609–612

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Spahr PF, Edsall JT (1964) Amino acid composition of human and bovine serum mercaptalbumins. J Biol Chem 239:850–854

    CAS  PubMed  Google Scholar 

  • Stein WH (1958) Observations of the amino acid composition of human hemoglobins. In: National Academy of Sciences (US) and National Research Council (US) Division of Medical Sciences. Conference on Hemoglobin: 2–3 May 1957. National Academies Press (US), Washington (DC)

  • Stein WH, Kunkel HG, Cole RD, Spackman DH, Moore S (1957) Observation on the amino acid composition of human hemoglobins. Biochim Biophys Acta 24:640–642

    Article  CAS  PubMed  Google Scholar 

  • Stover PJ, Chen LH, Suh JR, Stover DM, Keyomarsi K, Shane B (1997) Molecular cloning, characterization, and regulation of the human mitochondrial serine hydroxymethyltransferase gene. J Biol Chem 272:1842–1848

    Article  CAS  PubMed  Google Scholar 

  • Sugino T, Shirai T, Kajimoto Y, Kajimoto O (2008) L-ornithine supplementation attenuates physical fatigue in healthy volunteers by modulating lipid and amino acid metabolism. Nutr Res (NY) 28:738–743

    Article  CAS  Google Scholar 

  • Tamaki N, Funatsuka A, Fujimoto S, Hama T (1984) The utilization of carnosine in rats fed on a histidine-free diet and its effect on the levels of tissue histidine and carnosine. J Nutr Sci Vitaminol 30:541–551

    Article  CAS  PubMed  Google Scholar 

  • Tessari P (2006) Nitrogen balance and protein requirements: definition and measurements. In: Mantovani G (ed) Cachexia and wasting: a modern approach. Springer, New York, pp 73–80

    Chapter  Google Scholar 

  • Thornton CA, Welle S, Griggs RC, Abraham GN (1996) Human IgG production in vivo: determination of synthetic rate by nonradioactive tracer incorporation. J Immunol 157:950–955

    CAS  PubMed  Google Scholar 

  • Topo E, Soricelli A, D’Aniello A, Ronsini S, D’Aniello G (2009) The role and molecular mechanism of d-aspartic acid in the release and synthesis of LH and testosterone in humans and rats. Reprod Biol Endocrinol 7:120

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • van Wijck K, Pennings B, van Bijnen AA, Senden JMG, Buurman WA, Dejong CHC, van Loon LJC, Lenaerts K (2013) Dietary protein digestion and absorption are impaired during acute postexercise recovery in young men. Am J Physiol Regul Integr Comp Physiol 304:R356–R361

    Article  CAS  Google Scholar 

  • Wade AM, Tucker HN (1998) Antioxidant characteristics of l-histidine. J Nutr Biochem 9:308–315

    Article  CAS  Google Scholar 

  • Wang W, Wu Z, Dai Z, Yang Y, Wang J, Wu G (2013) Glycine metabolism in animals and humans: implications for nutrition and health. Amino Acids 45:463–477

    Article  CAS  PubMed  Google Scholar 

  • Waterlow JC (1984) Protein turnover with special reference to man. Q J Exp Physiol Camb Engl 69:409–438

    Article  CAS  Google Scholar 

  • Waterlow JC, Jackson AA (1981) Nutrition and protein turnover in man. Br Med Bull 37:5–10

    Article  CAS  PubMed  Google Scholar 

  • Williams BD, Robert RW, Bracy DP, Wasserman DH (1996) Gut proteolysis contributes essential amino acids during exercise. Am J Physiol Endocrinol Metab 270:E85–E90

    Article  CAS  Google Scholar 

  • Wu G (2009) Amino acids: metabolism, functions, and nutrition. Amino Acids 37:1–17

    Article  CAS  PubMed  Google Scholar 

  • Wu G (2010a) Functional amino acids in growth, reproduction, and health. Adv Nutr Bethesda MD 1:31–37

    Article  CAS  Google Scholar 

  • Wu G (2010b) Recent advances in swine amino acid nutrition. J Anim Sci Biotechnol 1:118–130

    Google Scholar 

  • Wu G, Fang YZ, Yang S, Lupton JR, Turner ND (2004) Glutathione metabolism and its implications for health. J Nutr 134:489–492

    Article  CAS  PubMed  Google Scholar 

  • Yamauchi M, Sricholpech M (2012) Lysine post-translational modifications of collagen. Essays Biochem 52:113–133

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zhong Z, Wheeler MD, Li X, Froh M, Schemmer P, Yin M, Bunzendaul H, Bradford B, Lemasters JJ (2003) L-Glycine: a novel antiinflammatory, immunomodulatory, and cytoprotective agent. Curr Opin Clin Nutr Metab Care 6:229–240

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This work was supported by the Gideon Lang research Foundation.

Funding

The work was supported by the Gideon Lang Research Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author information

Affiliations

Authors

Corresponding author

Correspondence to R. H. Dunstan.

Ethics declarations

Conflict of interest

The authors declare they have no conflict of interest.

Ethics statement

No actual experiments were performed on humans or animals for this study. All data for modelling were derived from published resources and acknowledged appropriately.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Handling Editor: K. Barnouin.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 58 kb)

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Dunstan, R.H., Macdonald, M.M., Murphy, G.R. et al. Modelling of protein turnover provides insight for metabolic demands on those specific amino acids utilised at disproportionately faster rates than other amino acids. Amino Acids 51, 945–959 (2019). https://doi.org/10.1007/s00726-019-02734-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00726-019-02734-1

Keywords

  • Amino acids
  • Protein turnover
  • Nitrogen balance
  • Metabolic homeostasis
  • Metabolic modelling