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To assess the use of plasma free amino acids (PFAAs) as biomarkers for metabolic disorders, it is essential to identify genetic factors that influence PFAA concentrations. PFAA concentrations were absolutely quantified by liquid chromatography–mass spectrometry using plasma samples from 1338 Japanese individuals, and genome-wide quantitative trait locus (QTL) analysis was performed for the concentrations of 21 PFAAs. We next conducted a conditional QTL analysis using the concentration of each PFAA adjusted by the other 20 PFAAs as covariates to elucidate genetic determinants that influence PFAA concentrations. We identified eight genes that showed a significant association with PFAA concentrations, of which two, SLC7A2 and PKD1L2, were identified. SLC7A2 was associated with the plasma levels of arginine and ornithine, and PKD1L2 with the level of glycine. The significant associations of these two genes were revealed in the conditional QTL analysis, but a significant association between serine and the CPS1 gene disappeared when glycine was used as a covariate. We demonstrated that conditional QTL analysis is useful for determining the metabolic pathways predominantly used for PFAA metabolism. Our findings will help elucidate the physiological roles of genetic components that control the metabolism of amino acids.

Previous studies demonstrated independent contributions of plasma free amino acids (PFAAs) and high uric acid (UA) concentrations to increased risks of lifestyle-related diseases (LSRDs), but the important associations between these factors and LSRDs remain unknown. We quantified PFAAs and UA amongst Japanese subjects without LSRDs (no-LSRD, n = 2805), and with diabetes mellitus (DM, n = 415), dyslipidemia (n = 3207), hypertension (n = 2736) and metabolic syndrome (MetS, n = 717). The concentrations of most amino acids differed significantly between the subjects with and without hyperuricemia (HU) and also between the no-LSRD and LSRD groups (p

Our aim is to construct a practical dynamic-simulation system that can model the metabolic and regulatory processes involved in the production of primary metabolites, such as amino acids. We have simulated the production of glutamate by transient batch-cultivation using a model of Escherichia coli central metabolism. Kinetic data were used to produce both the metabolic parts of the model, including the phosphotransferase system, glycolysis, the pentose-phosphate pathway, the tricarboxylic acid cycle, the glyoxylate shunt, and the anaplerotic pathways, and the regulatory parts of the model, including regulation by transcription factors, cyclic AMP receptor protein (CRP), making large colonies protein (Mlc), catabolite repressor/activator (Cra), pyruvate dehydrogenase complex repressor (PdhR), and acetate operon repressor (IclR). RNA polymerase and ribosome concentrations were expressed as a function of the specific growth rate, μ, corresponding to the changes in the growth rate during batch cultivation. Parameter fitting was performed using both extracellular concentration measurements and in vivo enzyme activities determined by 13C flux analysis. By manual adjustment of the parameters, we simulated the batch fermentation of glucose or fructose by a wild-type strain (MG1655) and a glutamate-producing strain (MG1655 ΔsucA). The differences caused by the carbon source, and by wild-type and glutamate-producing strains, were clearly shown by the simulation. A sensitivity analysis revealed the factors that could be altered to improve the production process. Furthermore, an in silico deletion experiments could suggested the existence of uncharacterized regulation. We concluded that our simulation model could function as a new tool for the rational improvement and design of metabolic and regulatory networks.

Metabolic flux analysis using 13C-labeled substrates is a well-developed method for investigating cellular behavior in steady-state culture condition. To extend its application, in particular to typical industrial conditions, such as batch and fed-batch cultivations, a novel method of 13C metabolic flux analysis is proposed. An isotopomer balancing model was developed to elucidate flux distributions in the central metabolism and all amino acids synthetic pathways. A lysine-producing strain of Escherichia coli was cultivated by fed-batch mode in a growth medium containing yeast extract. Mass distribution data was derived from both intracellular free amino acids and proteinogenic amino acids measured by LC-MS/MS, and a correction parameter for the protein turnover effect on the mass distributions of intracellular amino acids was introduced. Metabolic flux distributions were determined in both exponential and stationary phases. Using this new approach, a culture phase-dependent metabolic shift was detected in the fed-batch culture. The approach presented here has great potential for investigating cellular behavior in industrial processes, independent of cultivation modes, metabolic phase and growth medium.

Background Studies on the association of plasma-free amino acids with gout are very limited and produced conflicting results. Therefore, we sought to explore and characterize the plasma-free amino acid (PFAA) profile in patients with gout and evaluate its association with the latter. Methods Data from a total of 819 subjects (including 34 patients with gout) undergoing an annual health examination program in Shimane, Japan were considered for this study. Venous blood samples were collected from the subjects and concentrations of 19 plasma amino acids were determined by high-performance liquid chromatography–electrospray ionization–mass spectrometry. Student’s t-test was applied for comparison of variables between patient and control groups. The relationships between the presence or absence of gout and individual amino acids were investigated by logistic regression analysis controlling for the effects of potential demographic confounders. Results Among 19 amino acids, the levels of 10 amino acids (alanine, glycine, isoleucine, leucine, methionine, phenylalanine, proline, serine, tryptophan, valine) differed significantly (P