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© 2005 The American Society for Nutritional Sciences J. Nutr. 135:1571S-1575S, June 2005

4th Amino Acid Assessment Workshop

Transcriptomics and Metabolomics of Dietary Leucine Excess1

Kaori Matsuzaki, Hisanori Kato, Ryosei Sakai*, Sakino Toue*, Michiko Amao* and Takeshi Kimura2

Department of Applied Biological Chemistry Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, Japan, and * Ajinomoto Co., Inc., Institute of Life Sciences, Kawasaki, Japan

2To whom correspondence should be addressed. E-mail: takeshi_kimura{at}ajinomoto.com.


   ABSTRACT
TOP
 ABSTRACT
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 LITERATURE CITED
 
Changes were investigated in plasma metabolites and physiological and toxicological variables in rats fed for 2 wk on a basal diet or diets with 1.5, 5, 10, 15, and 30% added leucine. In the same experiment, the changes in gene expression in livers of rats fed the basal diet or diets with 5% and 15% added leucine were investigated using DNA microarrays. Cluster analysis of multivariate correlations of metabolites and physiological and toxicological variables indicated that the variables associated with excess nitrogen clustered together with leucine and {alpha}-ketoisocaproate. The gene expression data, although preliminary, indicated that there was little change in the expression of enzymes of the catabolic pathways for leucine but that there were changes in enzymes associated with nitrogen metabolism and other pathways downstream of leucine catabolism. The data seem consistent with excess leucine exerting its effects through the overloading of nitrogen metabolism and that urea or {alpha}-ketoisocaproate could be an early marker for the upper limit of adequate intake.

KEY WORDS: • gas chromatography–mass spectrometry • DNA microarray • dietary reference intake • tolerable upper level • acceptable daily intake

Early studies on amino acid excess focused primarily on the effects of excess amino acids given to animals in diets with low protein levels (1,2). Studies in which leucine was given to animals in diets with adequate protein levels indicate that large doses of leucine are well tolerated (3,4). There have been numerous reports on the role of leucine as a signaling molecule modulating protein catabolism (5), but the significance of these effects with respect to toxicity or adverse effects has not been studied.

In the previous workshops (6,7), we outlined 2 approaches that may be useful in determining the upper adequacy range of amino acids. One was the use of cluster analysis of multivariate correlations (CAMC)3 to identify metabolites of cystine that correlated with toxicity. The other was the use of 13C tracers to find "metabolic limits" by looking for inflection points for the generation of carbon dioxide derived from leucine. In attempting to find ways to find the upper adequacy range of leucine, we have applied CAMC to the analysis of leucine metabolites and have tried to understand the underlying mechanisms of responses to excessive doses by using DNA microarray analysis of mRNA from livers of animals treated with excess leucine.


   MATERIALS AND METHODS
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 ABSTRACT
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 LITERATURE CITED
 
Rats

The study received prior approval from Ajinomoto’s Institutional Animal Care and Use Committee. Male Fischer rats (F-344, 5 wk old), purchased from Charles River, were maintained in a controlled condition of 12 h light (0700 h to 1900 h), 12 h dark, at 23 ± 1°C, and at 55 ± 10% humidity. The rats were housed individually in stainless-steel cages and had free access to tap water and a purified diet based on the AIN-93G composition (8), with some modification, in which both dextrinized cornstarch and sucrose were replaced by cornstarch (modified AIN-93G) for 1 wk. Then, the rats were given basal modified AIN-93G or the experimental diets containing graded dosages of crystallized L-leucine [1.5, 5, 10, 15, 30% (w:w), corresponding to 5, 15, 26, 34, 51% of total N intake, respectively; n = 6] in compensation for the cornstarch. Metabolic cages were set to collect urine samples on day 13 of the experimental diets. The diet was removed the next morning (0800 h), and then a 24-h urine sample collected from each rat was stored at –80°C before analysis. In the afternoon (1330 h to 1500 h), the rats were anesthetized, blood was collected from the inferior vena cava, and the left lobe of the liver was removed. Plasma was separated from an aliquot of the blood using EDTA (NONCLOT-D, Daiichi Pure Chemicals) as the anti-coagulant, and serum was separated from the remainder after resting for 1 to 2 h. Each liver specimen was frozen quickly using a metal clamp cooled in liquid nitrogen and stored at –80°C.

Serum biochemistry

Serum biochemical variables [aspartate aminotransferase (ASAT), alanine aminotransferase (ALAT), creatine phosphokinase, lactate dehydrogenase, alkaline phosphatase (ALP) activities, total birilubin (T-BIL), phospholipid pyridoxal (PL), total cholesterol, triglyceride, glucose, total protein, blood urea nitrogen (BUN), creatine (CRE), Ca, Na, K, Cl, and inorganic phosphate (IP)] were measured using a biochemistry automatic analyzer TBA-120FR (Toshiba).

Amino acid analysis

Amino acid concentrations in the plasma and urine samples were measured by an automatic amino acid analyzer (L-8800, Hitachi), as reported previously (6,7). Briefly, the samples were mixed with 2 volumes of 5% (w:w) trichloroacetic acid and centrifuged to remove protein as a precipitate. Amino acids separated by cation exchange chromatography were detected spectrophotometrically after postcolumn reaction with ninhydrin reagent.

Preparation for GC-MS analysis

Plasma samples were mixed with 5 volumes of ethanol to remove protein as a precipitate and were dried under vacuum. The samples dissolved in water were mixed with 1 volume of 20 g/L O-phenylendiamine (Kanto Chemical) and incubated at 90°C for 1 h to generate quinoxialinol derivatives of ketoacids. Organic acids including ketoacid derivatives were separated as ethyl acetate extracts (fraction A). The water phases of the ethyl acetate extraction were applied to a 1-mL bed volume of cation-exchange column (Dowex 50Wx8, H+ form; Bio-Rad). Cation-binding metabolites were eluted with 3 mol/L ammonia solution (fraction B). Both fraction A and B were dried under vacuum, dissolved in 100 µL of trimethylsilylation reagent mixture [100:1:100 (v:v:v) of bis(trimethylsilyl)trifluoroacetamide, trimethylchlorosilane and pyridine; Sigma-Aldrich] and placed at room temperature for >3 h before GC-MS analysis.

GC-MS analysis

A Hewlett-Packard GC-MS system consisting of a Model 6890N GC equipped with HP-5MS column (30 m x 0.25 mm i.d., Hewlett Packard) and a model 5973N MS was used for the analysis. The GC temperature was increased from 60°C to 280°C at a rate of 5°C/min. Positive ions generated by electron impact ionization were monitored by SCAN mode (m/z = 50–800) for metabolic profiling. For more precise measurement of plasma {alpha}-ketoisocaproic acid ({alpha}-KIC), {alpha}-ketoisovaleric acid ({alpha}-KIV), and {alpha}-keto-ß-methyl-n-valeric acid ({alpha}-KMV), selected ions (m/z = 232, 260, and 232 for {alpha}-KIC, {alpha}-KIV, and {alpha}-KMV, respectively) were monitored. {alpha}-Ketocaproic acid (m/z = 232) was added to the original plasma beforehand as an internal standard.

Statistical analysis

Data were expressed as means ± SD. Statistical differences among the groups were determined by Tukey’s test after ANOVA for multiple comparisons using JMP 5.1.2 (SAS Institute). CAMC for physiological and toxicological variables and plasma metabolites also was performed using JMP 5.1.2.

DNA microarray analysis

All experiments and analyses were performed according to the protocol for GeneChip analysis. Total RNA was prepared from the livers of the control group, 5% leucine group, and 15% leucine group using Trizol reagent. Equal amounts of RNA from 6 rats of each group were mixed and used for purification of poly (A)+ mRNA [poly (A)+ purification kit, Pomega]. The mRNAs were reverse-transcribed with T7-(dT)24 primer and copied into double-strand cDNAs (SuperScript Choice System, Invitrogen). Then, biotin-labeled cRNAs were synthesized (RNA transcript labeling kit, Enzo Life Sciences) and fragmented by heating at 94°C for 35 min. At each step, the quality and the quantity of samples were assessed by measuring the optical density or by agarose gel electrophoresis. Fragmented cRNAs were hybridized to the Affymetrix GeneChip Test3 Array to verify the quality of the cRNAs. After this, cRNAs were hybridized to the Affymetrix GeneChip Rat Genome 230 2.0 array. After hybridization and subsequent washing and staining using the Affymetrix Fluidics station 400, fluorescence was measured by GeneChip Operating Software 1.0.


   RESULTS
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 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 LITERATURE CITED
 
General physiological and toxicological variables

The results of excessive leucine ingestion on general physiological and toxicological variables that showed significant differences from the control group variables are summarized in Table 1. There were dose-dependent increases in plasma ammonia and serum BUN, as well as urine volume and serum ALAT. Serum glucose and PL at intermediate doses were significantly higher than in controls but not at the highest dose. There were dose-dependent decreases in body-weight gain, muscle weight, and serum CRE, whereas food intake, serum ALP, Ca, and IP were lower than controls only for the group with the highest dose. There were no significant changes of the other measured variables.


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  		TABLE 1 Effects of dietary additional leucine on general variables1

 
CAMCs

When CAMC was performed on all available data, as shown in Figure 1A, it was found that, of the variables that showed significant increases, ALAT, ammonia, BUN, and urine volume were part of the same cluster (ALAT cluster), whereas glucose and PL were part of another cluster (glucose cluster). Of the decreased variables, food intake, body-weight gain, muscle weight, Ca, and ALP were part of the same cluster, whereas CRE and IP were parts of different clusters, respectively. On closer examination of the clusters, it was found that {alpha}-KIC and leucine were the only leucine metabolites in the ALAT cluster (Fig. 1B). It is of interest to note that the same substance measured by different methods appears at slightly different positions within the cluster, indicating the effects of measurement errors and that caution should be exercised in interpreting the microstructure of the clusters. In the glucose cluster, numerous fatty acids and lipids as well as PL, lactic acid, kidney weight, and T-BIL were present (Fig. 1C).



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  		FIGURE 1 CAMCs on general toxicological parameters and plasma metabolites. A: Correlations of all parameters are shown in tree diagram. Among the parameters described are general toxicological parameters with significant changes by excessive leucine intake. B: ALAT cluster in Figure 1A. C: Glucose cluster in Figure 1A. 1Serum biochemical parameters. 2Plasma metabolites measured by an amino acid analyzer. 3Plasma ketoacid of BCAA measured by selected ion monitoring in GC-MS. 4Metabolites in cation binding fraction of plasma samples. 5Metabolites in ethyl acetate extracts of plasma samples. 4,5Metabolite peaks were detected by SCAN mode analysis in GC-MS. Each metabolite was conjectured from the mass spectra using mass spectrum databases [NIST 98 (National Institute of Standard Technology) and Wiley Registry (John Wiley & Sons)].

 
Microarray analysis

The overall results of microarray analysis are shown in Table 2. The genes that were upregulated or downregulated by 2-fold or more compared with the control are classified into groups by their known biochemical functions. The number of upregulated genes in the case of the 5% leucine diet was 108 and that of downregulated ones was 5. The 15% leucine diet resulted in upregulation of 41 genes and downregulation of 18 genes. Data are reported for changes in gene expression in pathways associated with the observed significant changes in physiological and toxicological variables. A list of genes associated with amino acid, carbohydrate, and lipid–sterol metabolism whose expression differed by more than 2-fold compared with the control is given in Table 3. Only the direction of change is given, because we believe that verification of the DNA microarray results by more quantitative methods is needed to list numerical values. There were 8 genes associated with amino acid metabolism that were upregulated by more than 2-fold at one or both leucine levels compared with the control. Of these genes, 5 were involved in nitrogen metabolism. These were serine dehydratase (SDH), tyrosine aminotransferase (TAT), ASAT, ALAT, and ornithine aminotransferase (OAT). SDH and ASAT were increased for both leucine levels, and OAT and ALAT were increased only at 15% leucine. No change in expression of genes associated with leucine catabolism in either the 5% or the 15% groups was more than 2-fold compared with the control group.


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  		TABLE 2 Effects of dietary additional leucine on hepatic gene expression

 

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  		TABLE 3 Effects of dietary additional leucine on hepatic gene expression involved in metabolism of dietary nutrients

 
For genes associated with glucose metabolism, the expression of glycerol 3-phosphate dehydrogenase (GPD) increased by more than 2-fold compared with the control in the livers of rats given 5% leucine. Other genes associated with carbohydrate metabolism were also upregulated. For genes associated with lipid metabolism, isopentenyl-diphosphate delta isomerase and squalene epoxidase were upregulated by over 2-fold with both leucine levels compared with the control. There were 11 genes that were upregulated by over 2-fold with either one of the leucine levels, and 3 genes that were downregulated by over 2-fold at the 15% leucine dose. Of genes not shown in Table 3, there were 10 genes related to receptors and signal transduction that were upregulated by over 2-fold only in the 5% leucine group.


   DISCUSSION
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 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
LITERATURE CITED
 
The physiological and toxicological variables that showed significant increases (Table 1) fell into 2 groupings, those that showed dose-dependent increases, namely ALAT, ammonia, BUN, and urine volume, and those that showed increases but not at the highest dose, namely glucose and PL. The results of CAMC (Fig. 1) also indicated that these 2 groups were distinct. Ammonia, BUN, and urine volume are likely related to the excess nitrogen intake, whereas ALAT could have increased as a result of the nitrogen load or because of specific organ toxicity of leucine or one of its metabolites. ALAT is known to be present at high concentrations in the liver and kidney (9). Because of the fact that other variables of liver damage were not seen to increase with increased leucine dose, it is suggested that the increase in ALAT may be a result of some form of damage to the kidneys.

The CAMC of metabolites, together with physiological and toxicological variables, was intended to identify metabolites that may be associated with toxicity. In a previous analysis of data from rats fed diets with excess cystine, numerous unidentified peaks were found in the same cluster as toxicological variables (7). In contrast, with leucine excess, the only metabolite of leucine catabolism found to be associated with a parameter of toxicity (ALAT) was {alpha}-KIC (Fig. 1B). As shown in Figure 2, an amino group is deposited in the body during the generation of {alpha}-KIC, and so it could be a marker of nitrogen deposition. The fact that no other metabolites were found in the same cluster as ALAT would be consistent with the excess nitrogen load being the cause of its increase instead of the generation of a "toxic metabolite" from leucine catabolism. The possibility cannot be ruled out that the effects are because of the direct effects of leucine itself or of {alpha}-KIC, or that a "toxic metabolite" generated in a tissue is short lived and does not appear in blood.



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  		FIGURE 2 Upregulation of the genes involved in nitrogen metabolism in the liver by leucine load. The genes involved in nitrogen metabolism are picked up from Table 3 (framed enzymes: more than 2-fold increase in the rats fed 5% or 10% leucine diet compared with control). Upregulation of SDH in the liver is consistent with the increase in plasma concentrations of ammonia, urea, and glutamine in the rats fed excessive leucine. Enhanced expression of numbers of aminotransferases (TAT, ALAT, OAT, ASAT) indicates a possible increase in glutamate-related transamination reactions in the liver. The mechanisms underlying the above alterations of the gene expression would not be simple, because expression of branched-chain aminotransferase in the liver is reportedly very low (12).

 
The DNA microarray data indicated that there were no large changes in the expression of genes associated with leucine catabolism in the liver in spite of the large amount of leucine ingested. However, a number of aminotransferases were upregulated in the livers of rats given excess leucine, indicating a response to increased nitrogen metabolism (Fig. 2). SDH, an enzyme known to be expressed in response to increases in protein levels, was also upregulated, suggesting that leucine may play an important role in animals responding to various protein levels (10,11). Changes in the expression of genes associated with lipid–sterol metabolism may have been caused by an increase in acetyl Co-A, the end product of the metabolism of the carbon chain of leucine (Fig. 3). The excess supply of acetyl Co-A may have lead to a reduction in glycolysis or an increase in gluconeogenesis leading to the significant increase in glucose, and, because PL is made from glucose through the enzyme GPD, it would be consistent that glucose and PL were found in the same cluster. Although there were increases in the expression of a number of genes associated with receptors and signal transduction (Table 1), it was not clear whether these changes were associated with controlling the changes in expression of the genes associated with metabolism (Table 2) that were observed. It appears that, in this study, most of the dose-dependent increases in the physiological and toxicological variables with leucine excess can be explained in terms of the excess of the final metabolites of leucine catabolism, nitrogen, and acetyl Co-A. The variables associated with nitrogen metabolism showed an increase at lower leucine doses than the other types of variables (Table 1), so it may be useful to focus on markers of nitrogen metabolism as early markers for the excess intake of leucine. As BUN showed a significant increase at the lowest leucine dose among the other variables, it could be a direct early marker for toxicity resulting from nitrogen excess. However, BUN is a general end product for all nitrogen intakes and it may be more useful to use {alpha}-KIC as a marker for nitrogen deposition from leucine as a marker for leucine excess. It should be noted that in a study where leucine was administered for 13 wk, a longer period than in this study, the increases in BUN were not observed at levels up to 5% leucine in the diet (3). However, the animals in the 13-wk study underwent an overnight fast per the usual protocol for a toxicological study, equivalent to a full day without food because of the nocturnal eating habits of rats, before blood collection, whereas in our study the fasting period was 5.5–8 h. In light of these observations, it would seem that urinary nitrogen or urinary {alpha}-KIC over 24 h or some other suitable time period may be a more robust marker.



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  		FIGURE 3 Alteration of the gene expression involved in glucose metabolism in the rats fed excessive leucine. The genes involved in glucose metabolism are picked up from Table 3 and mapped in the metabolic pathway (framed enzymes: more than 2-fold increase in the rats fed 5% or 10% leucine diet compared with the control). Both acceleration of leucine catabolism and serine dehydratase activity could lead to inhibition of pyruvate kinase (pyruvate synthesis from phosphoenol pyruvate), which is one of the rate-limiting enzymes for glycolysis. Upregulation of GPD, inhibition of pyruvate kinase, and accelerated synthesis of acetyl CoA and acetoacetyl CoA because of enhanced leucine catabolism are all possible factors to promote phospholipid synthesis.

 


   FOOTNOTES
 
1 Published in a supplement to The Journal of Nutrition. Presented at the conference "The Fourth Workshop on the Assessment of Adequate Intake of Dietary Amino Acids" held October 28–29, 2004, Kobe, Japan. The conference was sponsored by the International Council on Amino Acid Science. The Workshop Organizing Committee included Dennis M. Bier, Luc Cynober, David H. Baker, Yuzo Hayashi, Motoni Kadowaki, and Andrew G. Renwick. Guest editors for the supplement publication were David H. Baker, Dennis M. Bier, Luc Cynober, John D. Fernstrom, Yuzo Hayashi, Motoni Kadowaki, and Dwight E. Matthews. Back

3 Abbreviations used: {alpha}-KIC, {alpha}-ketoisocaproic acid; {alpha}-KIV, {alpha}-ketoisovaleric acid; {alpha}-KMV, {alpha}-keto-ß-methyl-n-valeric acid; ALAT, alanine aminotransferase; ALP, alkaline phosphatase; ASAT, aspartate aminotransferase; BUN, blood urea nitrogen; CAMC, cluster analysis of multivariate correlations; CRE creatine; GPD, glycerol 3-phosphate dehydrogenase; IP, inorganic phosphate; OAT, ornithine aminotransferase; PL, phospholipid pyridoxal; SDH, serine dehydratase; TAT, tyrosine aminotransferase; T-BIL, total birilubin. Back


   LITERATURE CITED
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 LITERATURE CITED
 

1. Harper, A. E., Benevenga, N. J. & Wohlhueter, R. M. (1970) Effects of ingestion of disproportionate amounts of amino acids. Physiol. Rev. 50:428-558.[Free Full Text]

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4. Mawatari, K., Katsumata, T., Uematsu, M., Katsumata, T., Yoshida, J., Smriga, M. & Kimura, T. (2004) Prolonged oral treatment with an essential amino acid L-leucine does not affect female reproductive function and embryo-fetal development in rats. Food Chem. Toxicol. 42:1505-1511.[Medline]

5. Kimball, S. R. & Jefferson, L. S. (2004) Amino acids as regulators of gene expression. Nutr. Metab. 1:3-12.

6. Noguchi, Y., Sakai, R. & Kimura, T. (2003) Metabolomics and its potential for assessment of adequacy and safety of amino acid intake. J. Nutr. 133(suppl. 1):2097S-2100S.[Abstract/Free Full Text]

7. Sakai, R., Miura, M., Amao, M., Kodama, R., Toue, S., Noguchi, Y. & Kimura, T. (2004) Potential approaches to the assessment of amino acid adequacy in rats: a progress report. J. Nutr. 134(suppl.):1651S-1655S.[Abstract/Free Full Text]

8. National Research Council (1995) Nutrient requirements of the laboratory rat. Nutrient Requirements of Laboratory Animals 4th rev. ed. 1995:11-79 National Academy Press Washington, DC.

9. Kamoda, N., Minatogawa, Y., Nakamura, M., Nakanishi, J., Okuno, E. & Kido, R. (1980) The organ distribution of human alanine-2-oxoglutarate amino transferase and alanine-glyoxylate aminotransferase. Biochem. Med. 23:25-34.[Medline]

10. Anderson, H. L., Benevenga, N. J. & Harper, A. E. (1968) Associations among food and protein intake, serine dehydratase, and plasma amino acids. Am. J. Physiol. 214:1008-1013.[Free Full Text]

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12. Suryawan, A., Hawes, J. W., Harris, R. A., Shimomura, Y., Jenkins, A. E. & Hutson, S. M. (1998) A molecular model of human branched-chain amino acid metabolism. Am. J. Clin. Nutr. 68:72-81.[Abstract]




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