Threonine – Tryptophan : new understanding into the roles two essential amino acids play in metabolic health – dietary restriction

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Studies by Monash Biomedicine Discovery Institute (BDI), have provided a new understanding into the roles two essential amino acids play in metabolic health, which may help scientists in the fight against obesity.

Led by Dr. Adam Rose , the recent finding, published in Nature Communications, shows that by reducing the amount of two amino acids – threonine and tryptophan – in young healthy mice, they were able to burn more calories than they consumed, without calorie reduction, keeping them lean and healthy and without the side-effect of lower muscle mass.

A low-threonine diet even protected mice that were morbidly obese and prone to developing type 2 diabetes.

While a moderate reduction in dietary protein and therefore essential amino acids can enhance vitality, diets devoid of this component can make people sick very quickly and are not recommended.

However, this study has shown that a reconsideration of the functions of these two amino acids in nutrition warrants further exploration.

“Once we understand which particular dietary components are needed for the health-promoting effects of these diets we can design strategies to mimic them, simulating the effects without having the negative side effects,” Dr. Rose said.

A highlight of the study was an experiment where Dr. Rose and his team genetically manipulated the mice to be able to synthesize the essential amino acid threonine, which blocked the health promoting effects of the low threonine diet and saw the mice gain weight, proving that these two amino acids can hold the key to a new diet approach.

Dr. Matthew Piper, a key co-author adds, “We are finding an increasing number of situations in which essential amino acids are powerful modulators of lifelong health and lifespan. Our findings on their specific effects gives us exciting insights into how we might harness their benefits to drive better health.”

Co-author Professor Stephen Simpson of the University of Sydney’s Charles Perkins Centre said, “We are beginning to understand how critical the balance of dietary amino acids is to the control of appetite, health and aging.”


Restriction of dietary protein or of specific amino acids has been proposed as a potential treatment for metabolic syndrome [1,2]. Chronic protein restriction has long been associated with an array of beneficial metabolic responses, such as enhanced insulin sensitivity, reduced body weight, increased energy expenditure, and longevity [3,4,5,6,7,8].

The metabolic hormone FGF21 is important for the mediation of beneficial metabolic responses to protein restriction [9,10,11,12,13,14], but the extent of its contribution is still unknown [15].

Although key amino acids responsible for the maintenance of metabolic health remain unidentified, neutral amino acids are apparently critical for this function [16,17]. Restriction of branched-chain amino acids (BCAAs; leucine, isoleucine, valine), individually or in combination, is thought to improve metabolic health due to their effects on signaling via insulin, insulin-like growth factor 1 (IGF1), and mammalian target of rapamycin (mTOR) [1,18].

Reduction of dietary BCAAs reduces fat mass [19] and improves muscular insulin sensitivity in rodents [2]. Methionine or tryptophan restriction has been strongly associated with longevity [20,21], and methionine restriction alone has been shown to reduce body weight and fat mass and to improve glucose metabolism [19,21,22].

This phenotype has been attributed, at least partially, to FGF21 upregulation [23], which in turn increases energy expenditure by promoting browning of the white adipose tissue (WAT) [12,24].

Although methionine and leucine restriction drive some common mechanisms related to protein restriction that underlie improved metabolism, the metabolic effects of the former are more potent than those of the latter [25].

Recently, threonine and tryptophan have emerged as key mediators of protein restriction [3]. The link between FGF21 and dietary protein restriction was first made by Laegar et al. [9,10], renewing interest in its potential for treating metabolic disorders, such as diabetes and fatty liver disease [12,26].

While the benefits of protein restriction are well-documented, its usefulness as a dietary intervention is largely restricted to carefully controlled animal experiments. With the possible exception of the vegan diet [27], selectively reducing the intake of individual amino acids to a beneficial level is difficult in human nutrition.

However, many physiological outcomes of protein restriction are replicated in SLC6A19-knockout (SLC6A19ko) mice, for example, increased FGF21 levels, reduced mTORC1 signaling in liver, intestine, and adipose and muscle tissues, and insulin-independent glucose removal [28,29]. SLC6A19 is the major transporter of neutral amino acids at the apical side of small intestine epithelia and renal proximal tubular epithelia, functioning as the major mediator that delivers neutral amino acids to the systemic circulation [30,31].

Consistent with the metabolic effects of protein restriction, SLC6A19ko mice have reduced body weight, improved glucose tolerance, reduced plasma and liver fatty acids, and browning of subcutaneous white adipose tissue when compared to wild-type (wt) mice [28].

The potential use of SLC6A19 as a target to improve metabolic disease is further exemplified by the ability of SLC6A19ko to normalize the elevated levels of phenylalanine in a mouse model of phenylketonuria [32]. Lack of human SLC6A19 results in Hartnup disorder [31,33], a largely asymptomatic protein-malabsorption syndrome characterized by high levels of neutral amino acids in the urine.

This phenotype is fully replicated in SLC6A19ko mice, showing elevated levels of neutral amino acids in urine and faeces due to lack of renal and intestinal transporters, respectively [34]. Beneficial effects of protein restriction, such as upregulation of FGF21 and improved glucose tolerance, as observed in the SLC6A19ko model, are yet to be confirmed in Hartnup patients.

We propose that pharmacological blockage of SLC6A19 [35,36] can achieve replication of beneficial effects of protein restriction without the need to implement strict dietary habits that are practically difficult to maintain.

Inhibition of SLC6A19 may have further benefits, as it causes amino acids to move further distal in the intestine, where it triggers the release of incretins, namely, glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic peptide (GIP) [28]. The presence of amino acids in the distal intestine can be readily detected by the appearance of bacterial amino acid fermentation products [34].

We therefore investigated the role of SLC6A19 under different protein diets using an SLC6A19ko mouse model as a surrogate for its complete pharmacological inhibition. Several studies have previously used untargeted metabolomics to predict dietary outcomes by studying different biological fluids, such as urine or plasma [37,38]. Here, we aimed to investigate the nexus between dietary protein composition and intestinal protein absorption.

Discussion
Restriction of dietary protein is emerging as a nutritional concept that improves metabolic health in mice; however, with the possible exception of a vegan diet [27], it cannot be easily applied to dietary recommendations in humans.

We previously showed that ablation of SLC6A19 generated a metabolic phenotype similar to that achieved by dietary protein restriction [28,32]. BCAAs, namely, methionine and threonine, were investigated as candidate amino acids, representing the main drivers of improved metabolic health [7,43,44].

Notably, these amino acids are all substrates of SLC6A19 [30]. In this study, we aimed to investigate the nexus between protein malabsorption and dietary protein content. We previously identified groups of metabolites that can serve as biomarkers of protein restriction and malabsorption, mostly amino acids and amino acid-derived products of bacterial fermentation [34].

Experimentally, these biomarkers are best determined 1 h after feeding, which in mice can be synchronized by a short fasting period (6 h), followed by offering chow. In our hands, this is a reliable method to induce feeding before sample collection.

Under these conditions, the peak height of essential amino acids and that of bacterial amino acid-derived metabolites largely reflect their postprandial absorption on top of low, basal fasting metabolite levels.

This is consistent with amino acid absorption time courses in human control subjects and individuals with Hartnup disorder [45]. Two aspects are discussed here: Firstly, the difference between wt mice and SLC6A19ko mice, and secondly, general trends associated with diets of different protein contents.

Genotype Effects: Due to its location, SLC6A19 plays a pivotal role in modulating the transfer of neutral amino acids from the lumen of the intestine into the blood and further to organs [46,47].

Ablation of SLC6A19 reduces the absorption of all neutral amino acids, but threonine and tryptophan appear to be affected more than other amino acids, while remaining low in the absence of SLC6A19 on the tested diets with different protein contents. Whether these two amino acids underlie the physiological outcomes in SLC6A19ko mice remains to be proven [28].

The absorption of other neutral amino acids, such as BCAAs, phenylalanine, and methionine, was slightly reduced on an SP diet, but this outcome was prominent when dietary protein content was increased to 52%. Fasting amino acid levels were not affected by the genotype. We previously showed that amino acid levels were maintained by reducing amino acid metabolism, as evidenced by lower levels of urea [28], thereby compensating for reduced absorption and increased excretion of amino acids [34].

In addition to neutral amino acid uptake mediated by SLC6A19, neutral amino acids are also absorbed as dipeptides or tripeptides via the peptide transporter PEPT1 (SLC15A1) from the intestine [33,48].

Involvement of SLC15A1 in intestinal amino acid absorption only becomes evident in the presence of high protein loads, while no significant differences in plasma amino acid levels are observed with diets of low or normal protein content [49,50]. A few amino acids, such as valine, isoleucine, proline, and threonine, showed reduced plasma levels in the SLC15A1ko mice compared to wt mice after administration of a protein-enriched bolus [50].

Our study demonstrated that a lack of SLC6A19 affected the absorption of threonine and tryptophan more than that of other amino acids. This was surprising, as neither amino acid was the preferred substrate of this transporter [35], which may point to redundancy for BCAAs and other large neutral amino acids.

The apical amino cationic amino acid transporter b0,+AT could mediate the transport of BCAA, but only in exchange with cationic amino acids [51]. However, the existence of an additional neutral amino acid transporter in the apical membrane of the small intestinal epithelia was not proven [52].

There were no changes to the expression of basolateral neutral amino acid transporters, such as LAT2 or TAT1, which could affect tryptophan or threonine absorption (unpublished data). In the large intestine, expression of amino acid transporters ATB0,+ and ASCT2 is prominent [52,53,54], and some amino acids may move distally enough in SLC6A19ko mice [34,55] to be taken up by these transporters.

Threonine is a poor substrate of ATB0,+, but a good substrate of ASCT2, while tryptophan is a good substrate of ATB0,+, but not accepted by ASCT2 [52]. Thus, it appears unlikely that absorption in the distal intestine compensates for lack of B0AT1. PEPT1 also does not strongly discriminate between amino acid composition of the dipeptides or tripeptides [56].

Threonine and tryptophan have recently attracted interest as the limiting amino acids underlying hyperphagia induced by low-protein diets [3]. Despite low levels of circulating threonine and tryptophan levels in SLC6A19ko mice, we did not observe an increase in food intake, whereas Zapata et al. (2019) [57] and Solon-Biet et al. (2019) [3] reported that an increase in food intake could be corrected by threonine and tryptophan supplementation. Threonine and tryptophan have also been highlighted as key players behind the beneficial effects of protein restriction, at least in part due to FGF21 upregulation [57].

Previously, methionine restriction was linked to the upregulation of FGF21 [23,25,58], whereas contradictory results were obtained upon leucine restriction [25,59]. The restriction of neutral amino acids absorption in SLC6A19ko mice is sufficient to induce upregulation of FGF21 comparable to protein-restricted mice [10,28].

Although SLC6A19 effects are more prominent in mice on high-protein diets, the overall amino acid absorption is similar to that of wt mice on low-protein diets. This explains why Hartnup disorder is benign on a protein-sufficient diet.

Such observations further suggest that pharmacological inhibition of SLC6A19 is likely to generate the metabolic outcomes associated with dietary protein restriction. Elevated levels of circulating BCAAs have been associated with obesity and insulin resistance [60,61,62], although the causal relationship is still unclear [44,63]. Moreover, elevated amino acid levels could reflect high protein intake [3,8].

Effects of Dietary Protein Content: Previously, we identified bacterial metabolites, namely, p-cresol glucuronide and indole-3-propionic acid, originating from tyrosine and tryptophan fermentation, respectively, as SLC6A19ko biomarkers in the intestine [34].

Some bacterial metabolites can be used also as indicators of protein content, particularly postprandially. Phenyl-acetate, indole-3-lactic acid, and 2-aminoadipic acid positively correlated with the protein content. Other bacterial amino acid-derived metabolites, such as indole-3-propionic acid and indole-3-actetic acid, increased with LP and SP diets, but returned back to LP diet levels when given an HP diet. This may reflect changes in the microbiome occurring during the 14-day diet adaptation.

We also observed a direct correlation between dietary protein content and the abundance of essential amino acids in wt mice postprandially. Previous studies in rats also reported similar correlations of plasma essential amino acids in the postprandial state [17,64], showing a reduction with a 5% casein diet and an increase with diets containing 60% casein, with the exception of threonine [64].

In fasting mice, in contrast, significant increases in amino acids were only observed when they were fed a high-protein diet. This is also in agreement with previous studies, where fasting amino acid levels remained unchanged when rats were fed with a 6% or 24% protein diet, with the exceptions of serine or glycine [65].

Plasma levels of essential amino acids, especially BCAAs, were previously shown to be significantly reduced with low-protein diets [1,4,64] and elevated when high-protein diets were consumed [3,66].

In summary, amino acids are evidently potent bioactive metabolites whose levels are tightly controlled. However, plasma levels of essential amino acids can predict dietary protein intake in the postprandial state. Low or high protein intake has been shown to affect metabolic health by a variety of mechanisms.

Our results indicate that absorption of essential amino acids is reduced significantly in the absence of SLC6A19, especially following a high-protein diet. We conclude that pharmacological inhibition of SLC6A19 is one of the very few strategies that could apply the concept of dietary protein restriction to human nutrition.

References

  1. Fontana L., Cummings N.E., Arriola Apelo S.I., Neuman J.C., Kasza I., Schmidt B.A., Cava E., Spelta F., Tosti V., Syed F.A., et al. Decreased Consumption of Branched-Chain Amino Acids Improves Metabolic Health. Cell Rep. 2016;16:520–530. doi: 10.1016/j.celrep.2016.05.092.
  2. White P.J., Lapworth A.L., An J., Wang L., McGarrah R.W., Stevens R.D., Ilkayeva O., George T., Muehlbauer M.J., Bain J.R., et al. Branched-chain amino acid restriction in Zucker-fatty rats improves muscle insulin sensitivity by enhancing efficiency of fatty acid oxidation and acyl-glycine export. Mol. Metab. 2016;5:538–551. doi: 10.1016/j.molmet.2016.04.006.
  3. Solon-Biet S.M., Cogger V.C., Pulpitel T., Wahl D., Clark X., Bagley E.E., Gregoriou G.C., Senior A.M., Wang Q.-P., Brandon A.E., et al. Branched-chain amino acids impact health and lifespan indirectly via amino acid balance and appetite control. Nat. Metab. 2019;1:532–545. doi: 10.1038/s42255-019-0059-2.
  4. Solon-Biet S.M., Mitchell S.J., Coogan S.C., Cogger V.C., Gokarn R., McMahon A.C., Raubenheimer D., de Cabo R., Simpson S.J., Le Couteur D.G. Dietary Protein to Carbohydrate Ratio and Caloric Restriction: Comparing Metabolic Outcomes in Mice. Cell Rep. 2015;11:1529–1534. doi: 10.1016/j.celrep.2015.05.007.
  5. Wahl D., Solon-Biet S.M., Wang Q.P., Wali J.A., Pulpitel T., Clark X., Raubenheimer D., Senior A.M., Sinclair D.A., Cooney G.J., et al. Comparing the Effects of Low-Protein and High-Carbohydrate Diets and Caloric Restriction on Brain Aging in Mice. Cell Rep. 2018;25:2234–2243. doi: 10.1016/j.celrep.2018.10.070.
  6. Fontana L., Partridge L. Promoting health and longevity through diet: From model organisms to humans. Cell. 2015;161:106–118. doi: 10.1016/j.cell.2015.02.020.
  7. Senior A.M., Solon-Biet S.M., Cogger V.C., Le Couteur D.G., Nakagawa S., Raubenheimer D., Simpson S.J. Dietary macronutrient content, age-specific mortality and lifespan. Proc. Biol. Sci. 2019;286:20190393. doi: 10.1098/rspb.2019.0393.
  8. Solon-Biet S.M., McMahon A.C., Ballard J.W., Ruohonen K., Wu L.E., Cogger V.C., Warren A., Huang X., Pichaud N., Melvin R.G., et al. The ratio of macronutrients, not caloric intake, dictates cardiometabolic health, aging, and longevity in ad libitum-fed mice. Cell Metab. 2014;19:418–430. doi: 10.1016/j.cmet.2014.02.009.
  9. Laeger T., Albarado D.C., Burke S.J., Trosclair L., Hedgepeth J.W., Berthoud H.R., Gettys T.W., Collier J.J., Munzberg H., Morrison C.D. Metabolic Responses to Dietary Protein Restriction Require an Increase in FGF21 that Is Delayed by the Absence of GCN2. Cell Rep. 2016;16:707–716. doi: 10.1016/j.celrep.2016.06.044.
  10. Laeger T., Henagan T.M., Albarado D.C., Redman L.M., Bray G.A., Noland R.C., Munzberg H., Hutson S.M., Gettys T.W., Schwartz M.W., et al. FGF21 is an endocrine signal of protein restriction. J. Clin. Investig. 2014;124:3913–3922. doi: 10.1172/JCI74915.
  11. Li H., Wu G., Fang Q., Zhang M., Hui X., Sheng B., Wu L., Bao Y., Li P., Xu A., et al. Fibroblast growth factor 21 increases insulin sensitivity through specific expansion of subcutaneous fat. Nat. Commun. 2018;9:272. doi: 10.1038/s41467-017-02677-9.
  12. Maida A., Zota A., Vegiopoulos A., Appak-Baskoy S., Augustin H.G., Heikenwalder M., Herzig S., Rose A.J. Dietary protein dilution limits dyslipidemia in obesity through FGF21-driven fatty acid clearance. J. Nutr. Biochem. 2018;57:189–196. doi: 10.1016/j.jnutbio.2018.03.027.
  13. Schlein C., Talukdar S., Heine M., Fischer A.W., Krott L.M., Nilsson S.K., Brenner M.B., Heeren J., Scheja L. FGF21 Lowers Plasma Triglycerides by Accelerating Lipoprotein Catabolism in White and Brown Adipose Tissues. Cell Metab. 2016;23:441–453. doi: 10.1016/j.cmet.2016.01.006.
  14. Maida A., Zota A., Sjoberg K.A., Schumacher J., Sijmonsma T.P., Pfenninger A., Christensen M.M., Gantert T., Fuhrmeister J., Rothermel U., et al. A liver stress-endocrine nexus promotes metabolic integrity during dietary protein dilution. J. Clin. Investig. 2016;126:3263–3278. doi: 10.1172/JCI85946.
  15. Hill C.M., Berthoud H.R., Munzberg H., Morrison C.D. Homeostatic sensing of dietary protein restriction: A case for FGF21. Front. Neuroendocrinol. 2018;51:125–131. doi: 10.1016/j.yfrne.2018.06.002.
  16. Green C.L., Lamming D.W. Regulation of metabolic health by essential dietary amino acids. Mech. Ageing Dev. 2019;177:186–200. doi: 10.1016/j.mad.2018.07.004.
  17. Maida A., Chan J.S.K., Sjoberg K.A., Zota A., Schmoll D., Kiens B., Herzig S., Rose A.J. Repletion of branched chain amino acids reverses mTORC1 signaling but not improved metabolism during dietary protein dilution. Mol. Metab. 2017;6:873–881. doi: 10.1016/j.molmet.2017.06.009.
  18. Soultoukis G.A., Partridge L. Dietary Protein, Metabolism, and Aging. Annu. Rev. Biochem. 2016;85:5–34. doi: 10.1146/annurev-biochem-060815-014422.
  19. Cummings N.E., Williams E.M., Kasza I., Konon E.N., Schaid M.D., Schmidt B.A., Poudel C., Sherman D.S., Yu D., Arriola Apelo S.I., et al. Restoration of metabolic health by decreased consumption of branched-chain amino acids. J. Physiol. 2018;596:623–645. doi: 10.1113/JP275075.
  20. He C., Tsuchiyama S.K., Nguyen Q.T., Plyusnina E.N., Terrill S.R., Sahibzada S., Patel B., Faulkner A.R., Shaposhnikov M.V., Tian R., et al. Enhanced longevity by ibuprofen, conserved in multiple species, occurs in yeast through inhibition of tryptophan import. PLoS Genet. 2014;10:e1004860. doi: 10.1371/journal.pgen.1004860.
  21. Miller R.A., Buehner G., Chang Y., Harper J.M., Sigler R., Smith-Wheelock M. Methionine-deficient diet extends mouse lifespan, slows immune and lens aging, alters glucose, T4, IGF-I and insulin levels, and increases hepatocyte MIF levels and stress resistance. Aging Cell. 2005;4:119–125. doi: 10.1111/j.1474-9726.2005.00152.x.
  22. Brown-Borg H.M., Buffenstein R. Cutting back on the essentials: Can manipulating intake of specific amino acids modulate health and lifespan? Ageing Res. Rev. 2017;39:87–95. doi: 10.1016/j.arr.2016.08.007.
  23. Lees E.K., Krol E., Grant L., Shearer K., Wyse C., Moncur E., Bykowska A.S., Mody N., Gettys T.W., Delibegovic M. Methionine restriction restores a younger metabolic phenotype in adult mice with alterations in fibroblast growth factor 21. Aging Cell. 2014;13:817–827. doi: 10.1111/acel.12238.
  24. Douris N., Stevanovic D.M., Fisher F.M., Cisu T.I., Chee M.J., Nguyen N.L., Zarebidaki E., Adams A.C., Kharitonenkov A., Flier J.S., et al. Central Fibroblast Growth Factor 21 Browns White Fat via Sympathetic Action in Male Mice. Endocrinology. 2015;156:2470–2481. doi: 10.1210/en.2014-2001.
  25. Lees E.K., Banks R., Cook C., Hill S., Morrice N., Grant L., Mody N., Delibegovic M. Direct comparison of methionine restriction with leucine restriction on the metabolic health of C57BL/6J mice. Sci. Rep. 2017;7:9977. doi: 10.1038/s41598-017-10381-3.
  26. Kharitonenkov A., Adams A.C. Inventing new medicines: The FGF21 story. Mol. Metab. 2014;3:221–229. doi: 10.1016/j.molmet.2013.12.003.
  27. McCarty M.F., Barroso-Aranda J., Contreras F. The low-methionine content of vegan diets may make methionine restriction feasible as a life extension strategy. Med. Hypotheses. 2009;72:125–128. doi: 10.1016/j.mehy.2008.07.044.
  28. Jiang Y., Rose A.J., Sijmonsma T.P., Bröer A., Pfenninger A., Herzig S., Schmoll D., Bröer S. Mice lacking neutral amino acid transporter B(0)AT1 (Slc6a19) have elevated levels of FGF21 and GLP-1 and improved glycaemic control. Mol. Metab. 2015;4:406–417. doi: 10.1016/j.molmet.2015.02.003.
  29. Bröer A., Juelich T., Vanslambrouck J.M., Tietze N., Solomon P.S., Holst J., Bailey C.G., Rasko J.E., Bröer S. Impaired nutrient signaling and body weight control in a Na+ neutral amino acid cotransporter (Slc6a19)-deficient mouse. J. Biol. Chem. 2011;286:26638–26651. doi: 10.1074/jbc.M111.241323.
  30. Bröer A., Klingel K., Kowalczuk S., Rasko J.E., Cavanaugh J., Bröer S. Molecular cloning of mouse amino acid transport system B0, a neutral amino acid transporter related to Hartnup disorder. J. Biol. Chem. 2004;279:24467–24476. doi: 10.1074/jbc.M400904200.
  31. Bröer S. The role of the neutral amino acid transporter B0AT1 (SLC6A19) in Hartnup disorder and protein nutrition. IUBMB Life. 2009;61:591–599. doi: 10.1002/iub.210.
  32. Belanger A.M., Przybylska M., Gefteas E., Furgerson M., Geller S., Kloss A., Cheng S.H., Zhu Y., Yew N.S. Inhibiting neutral amino acid transport for the treatment of phenylketonuria. JCI Insight. 2018;3:121762. doi: 10.1172/jci.insight.121762.
  33. Bröer S., Cavanaugh J.A., Rasko J.E. Neutral amino acid transport in epithelial cells and its malfunction in Hartnup disorder. Biochem. Soc. Trans. 2005;33:233–236. doi: 10.1042/BST0330233.
  34. Javed K., Cheng Q., Carroll A.J., Truong T.T., Bröer S. Development of Biomarkers for Inhibition of SLC6A19 (B(0)AT1)-A Potential Target to Treat Metabolic Disorders. Int. J. Mol. Sci. 2018;19:3597. doi: 10.3390/ijms19113597.
  35. Cheng Q., Shah N., Bröer A., Fairweather S., Jiang Y., Schmoll D., Corry B., Bröer S. Identification of novel inhibitors of the amino acid transporter B(0) AT1 (SLC6A19), a potential target to induce protein restriction and to treat type 2 diabetes. Br. J. Pharmacol. 2017;174:468–482. doi: 10.1111/bph.13711.
  36. Danthi S.J., Liang B., Smicker O., Coupland B., Gregory J., Gefteas E., Tietz D., Klodnitsky H., Randall K., Belanger A., et al. Identification and Characterization of Inhibitors of a Neutral Amino Acid Transporter, SLC6A19, Using Two Functional Cell-Based Assays. SLAS Discov. 2018;24:111–120. doi: 10.1177/2472555218794627.
  37. O’Sullivan A., Gibney M.J., Brennan L. Dietary intake patterns are reflected in metabolomic profiles: Potential role in dietary assessment studies. Am. J. Clin. Nutr. 2011;93:314–321. doi: 10.3945/ajcn.110.000950.
  38. Andersen M.B., Rinnan A., Manach C., Poulsen S.K., Pujos-Guillot E., Larsen T.M., Astrup A., Dragsted L.O. Untargeted metabolomics as a screening tool for estimating compliance to a dietary pattern. J. Proteome Res. 2014;13:1405–1418. doi: 10.1021/pr400964s.
  39. Tsugawa H., Cajka T., Kind T., Ma Y., Higgins B., Ikeda K., Kanazawa M., VanderGheynst J., Fiehn O., Arita M. MS-DIAL: Data-independent MS/MS deconvolution for comprehensive metabolome analysis. Nat. Methods. 2015;12:523–526. doi: 10.1038/nmeth.3393.
  40. Kopka J., Schauer N., Krueger S., Birkemeyer C., Usadel B., Bergmuller E., Dormann P., Weckwerth W., Gibon Y., Stitt M., et al. [email protected]: The Golm Metabolome Database. Bioinformatics. 2005;21:1635–1638. doi: 10.1093/bioinformatics/bti236. [PubMed] [CrossRef] [Google Scholar]
  41. Chong J., Soufan O., Li C., Caraus I., Li S., Bourque G., Wishart D.S., Xia J. MetaboAnalyst 4.0: Towards more transparent and integrative metabolomics analysis. Nucleic Acids Res. 2018;46:W486–W494. doi: 10.1093/nar/gky310. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  42. Colquhoun D. An investigation of the false discovery rate and the misinterpretation of p-values. R. Soc. Open Sci. 2014;1:140216. doi: 10.1098/rsos.140216. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  43. Latimer M.N., Freij K.W., Cleveland B.M., Biga P.R. Physiological and Molecular Mechanisms of Methionine Restriction. Front. Endocrinol. (Lausanne) 2018;9:217. doi: 10.3389/fendo.2018.00217. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  44. Lynch C.J., Adams S.H. Branched-chain amino acids in metabolic signalling and insulin resistance. Nat. Rev. Endocrinol. 2014;10:723–736. doi: 10.1038/nrendo.2014.171. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  45. Navab F., Asatoor A.M. Studies on intestinal absorption of amino acids and a dipeptide in a case of Hartnup disease. Gut. 1970;11:373–379. doi: 10.1136/gut.11.5.373. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  46. Bröer S. Amino acid transport across mammalian intestinal and renal epithelia. Physiol. Rev. 2008;88:249–286. doi: 10.1152/physrev.00018.2006. [PubMed] [CrossRef] [Google Scholar]
  47. Bröer S. Amino Acid Transporters as Disease Modifiers and Drug Targets. SLAS Discov. 2018;23:303–320. doi: 10.1177/2472555218755629. [PubMed] [CrossRef] [Google Scholar]
  48. Bröer S., Bröer A. Amino acid homeostasis and signalling in mammalian cells and organisms. Biochem. J. 2017;474:1935–1963. doi: 10.1042/BCJ20160822. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  49. Nassl A.M., Rubio-Aliaga I., Sailer M., Daniel H. The intestinal peptide transporter PEPT1 is involved in food intake regulation in mice fed a high-protein diet. PLoS ONE. 2011;6:e26407. doi: 10.1371/journal.pone.0026407. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  50. Nassl A.M., Rubio-Aliaga I., Fenselau H., Marth M.K., Kottra G., Daniel H. Amino acid absorption and homeostasis in mice lacking the intestinal peptide transporter PEPT1. Am. J. Physiol. Gastrointest. Liver Physiol. 2011;301:G128–G137. doi: 10.1152/ajpgi.00017.2011. [PubMed] [CrossRef] [Google Scholar]
  51. Busch A.E., Herzer T., Waldegger S., Schmidt F., Palacin M., Biber J., Markovich D., Murer H., Lang F. Opposite directed currents induced by the transport of dibasic and neutral amino acids in Xenopus oocytes expressing the protein rBAT. J. Biol. Chem. 1994;269:25581–25586. [PubMed] [Google Scholar]
  52. Broer S., Fairweather S.J. Amino Acid Transport Across the Mammalian Intestine. Compr. Physiol. 2018;9:343–373. doi: 10.1002/cphy.c170041. [PubMed] [CrossRef] [Google Scholar]
  53. Sloan J.L., Mager S. Cloning and functional expression of a human Na(+) and Cl(-)-dependent neutral and cationic amino acid transporter B(0+) J. Biol. Chem. 1999;274:23740–23745. doi: 10.1074/jbc.274.34.23740. [PubMed] [CrossRef] [Google Scholar]
  54. Gupta N., Miyauchi S., Martindale R.G., Herdman A.V., Podolsky R., Miyake K., Mager S., Prasad P.D., Ganapathy M.E., Ganapathy V. Upregulation of the amino acid transporter ATB0,+(SLC6A14) in colorectal cancer and metastasis in humans. Biochim. Biophys. Acta. 2005;1741:215–223. doi: 10.1016/j.bbadis.2005.04.002. [PubMed] [CrossRef] [Google Scholar]
  55. Singer D., Camargo S.M., Ramadan T., Schafer M., Mariotta L., Herzog B., Huggel K., Wolfer D., Werner S., Penninger J.M., et al. Defective intestinal amino acid absorption in Ace2 null mice. Am. J. Physiol. Gastrointest. Liver Physiol. 2012;303:G686–G695. doi: 10.1152/ajpgi.00140.2012. [PubMed] [CrossRef] [Google Scholar]
  56. Daniel H. Molecular and integrative physiology of intestinal peptide transport. Annu. Rev. Physiol. 2004;66:361–384. doi: 10.1146/annurev.physiol.66.032102.144149. [PubMed] [CrossRef] [Google Scholar]
  57. Zapata R.C., Singh A., Pezeshki A., Chelikani P.K. Tryptophan restriction partially recapitulates the age-dependent effects of total amino acid restriction on energy balance in diet-induced obese rats. J. Nutr. Biochem. 2019;65:115–127. doi: 10.1016/j.jnutbio.2018.12.006. [PubMed] [CrossRef] [Google Scholar]
  58. Wanders D., Forney L.A., Stone K.P., Burk D.H., Pierse A., Gettys T.W. FGF21 Mediates the Thermogenic and Insulin-Sensitizing Effects of Dietary Methionine Restriction but Not Its Effects on Hepatic Lipid Metabolism. Diabetes. 2017;66:858–867. doi: 10.2337/db16-1212. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  59. Wanders D., Stone K.P., Dille K., Simon J., Pierse A., Gettys T.W. Metabolic responses to dietary leucine restriction involve remodeling of adipose tissue and enhanced hepatic insulin signaling. Biofactors. 2015;41:391–402. doi: 10.1002/biof.1240. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  60. Newgard C.B., An J., Bain J.R., Muehlbauer M.J., Stevens R.D., Lien L.F., Haqq A.M., Shah S.H., Arlotto M., Slentz C.A., et al. A branched-chain amino acid-related metabolic signature that differentiates obese and lean humans and contributes to insulin resistance. Cell Metab. 2009;9:311–326. doi: 10.1016/j.cmet.2009.02.002. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  61. Giesbertz P., Daniel H. Branched-chain amino acids as biomarkers in diabetes. Curr. Opin. Clin. Nutr. Metab. Care. 2016;19:48–54. doi: 10.1097/MCO.0000000000000235. [PubMed] [CrossRef] [Google Scholar]
  62. Wurtz P., Soininen P., Kangas A.J., Ronnemaa T., Lehtimaki T., Kahonen M., Viikari J.S., Raitakari O.T., Ala-Korpela M. Branched-chain and aromatic amino acids are predictors of insulin resistance in young adults. Diabetes Care. 2013;36:648–655. doi: 10.2337/dc12-0895. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  63. Yoon M.S. The Emerging Role of Branched-Chain Amino Acids in Insulin Resistance and Metabolism. Nutrients. 2016;8:405. doi: 10.3390/nu8070405. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  64. Fafournoux P., Remesy C., Demigne C. Fluxes and membrane transport of amino acids in rat liver under different protein diets. Am. J. Physiol. 1990;259:E614–E625. doi: 10.1152/ajpendo.1990.259.5.E614. [PubMed] [CrossRef] [Google Scholar]
  65. Kalhan S.C., Uppal S.O., Moorman J.L., Bennett C., Gruca L.L., Parimi P.S., Dasarathy S., Serre D., Hanson R.W. Metabolic and genomic response to dietary isocaloric protein restriction in the rat. J. Biol. Chem. 2011;286:5266–5277. doi: 10.1074/jbc.M110.185991. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  66. Milsom J.P., Morgan M.Y., Sherlock S. Factors affecting plasma amino acid concentrations in control subjects. Metabolism. 1979;28:313–319. doi: 10.1016/0026-0495(79)90101-X. [PubMed] [CrossRef] [Google Scholar]


More information: Yann W. Yap et al, Restriction of essential amino acids dictates the systemic metabolic response to dietary protein dilution, Nature Communications (2020). DOI: 10.1038/s41467-020-16568-z

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