A Methionine Chemical Shift Based Order Parameter Characterizing Global Protein Dynamics.

Coupling of side chain dynamics over long distances is an important component of allostery. Methionine side chains show the largest intrinsic flexibility among methyl-containing residues but the actual degree of conformational averaging depends on the proximity and mobility of neighboring residues. The 13 C NMR chemical shifts of the methyl groups of methionine residues located at long distances in the same protein show a similar scaling with respect to the values predicted from the static X-ray structure by quantum methods. This results in a good linear correlation between calculated and observed chemical shifts. The slope is protein dependent and ranges from zero for the highly flexible calmodulin to 0.7 for the much more rigid calcineurin catalytic domain. The linear correlation is indicative of a similar level of side-chain conformational averaging over long distances, and the slope of the correlation line can be interpreted as an order parameter of the global side-chain flexibility.

THE METABOLOMICS SIGNATURE ASSOCIATED WITH RESPONSIVENESS TO STEROID THERAPY IN FOCAL SEGMENTAL GLOMERULOSCLEROSIS: A PILOT STUDY.

BACKGROUND: Focal segmental glomerulosclerosis (FSGS) is considered one of the most severe glomerular diseases and around 80% of cases are resistant to steroid treatment. Since a large proportion of steroid-resistant (SR) FSGS patients progress to end-stage renal disease, other therapeutic strategies may benefit this population. However, identification of non-invasive biomarkers to predict this high-risk population is needed. OBJECTIVE: We aimed to identify the biomarker candidates to distinguish SR from steroid-sensitive (SS) patients using metabolomics approach and to identify the possible molecular mechanism of resistance. METHODS: Urine was collected from biopsy-proven FSGS patients eligible for monotherapy with prednisolone. Patients were followed for 6-8 weeks and categorized as SS or SR. Metabolite profile of urine samples was analyzed by one-dimensional 1H-nuclear magnetic resonance (1H-NMR). Predictive biomarker candidates and their diagnostic importance impaired molecular pathways in SR patients, and the common target molecules between biomarker candidates and drug were predicted. RESULTS: Homovanillic acid, 4-methylcatechol, and tyrosine were suggested as the significant predictive biomarker candidates, while L-3,4-dihydroxyphenylalanine, norepinephrine, and gentisic acid had high accuracy as well. Tyrosine metabolism was the most important pathway that is perturbed in SR patients. Common targets of the action of biomarker candidates and prednisolone were molecules that contributed in apoptosis. CONCLUSION: Urine metabolites including homovanillic acid, 4-methylcatechol, and tyrosine may serve as potential non-invasive predictive biomarkers for evaluating the responsiveness of FSGS patients.

A Noninvasive Urine Metabolome Panel as Potential Biomarkers for Diagnosis of T Cell-Mediated Renal Transplant Rejection.

Acute T cell-mediated rejection (TCMR) is a major complication after renal transplantation. TCMR diagnosis is very challenging and currently depends on invasive renal biopsy and nonspecific markers such as serum creatinine. A noninvasive metabolomics panel could allow early diagnosis and improved accuracy and specificity. We report, in this study, on urine metabolome changes in renal transplant recipients diagnosed with TCMR, with a view to future metabolomics-based diagnostics in transplant medicine. We performed urine metabolomic analyses in three study groups: (1) 7 kidney transplant recipients with acute TCMR, (2) 15 kidney transplant recipients without rejection but with impaired kidney function, and (3) 6 kidney transplant recipients with stable renal function, using 1H-nuclear magnetic resonance. Multivariate modeling of metabolites suggested a diagnostic panel where the diagnostic accuracy of each metabolite was calculated by receiver operating characteristic curve analysis. The impaired metabolic pathways associated with TCMR were identified by pathway analysis. In all, a panel of nine differential metabolites encompassing nicotinamide adenine dinucleotide, 1-methylnicotinamide, cholesterol sulfate, gamma-aminobutyric acid (GABA), nicotinic acid, nicotinamide adenine dinucleotide phosphate, proline, spermidine, and alpha-hydroxyhippuric acid were identified as novel potential metabolite biomarkers of TCMR. Proline, spermidine, and GABA had the highest area under the curve (>0.7) and were overrepresented in the TCMR group. Nicotinate and nicotinamide metabolism was the most important pathway in TCMR. These findings call for clinical validation in larger study samples and suggest that urinary metabolomics warrants future consideration as a noninvasive research tool for TCMR diagnostic innovation.

The metabolome profiling of obese and non-obese individuals: Metabolically healthy obese and unhealthy non-obese paradox.

OBJECTIVES: The molecular basis of "metabolically healthy obese" and "metabolically unhealthy non-obese" phenotypes is not fully understood. Our objective was to identify metabolite patterns differing in obese (metabolically healthy vs unhealthy (MHO vs MUHO)) and non-obese (metabolically healthy vs unhealthy (MHNO vs MUHNO)) individuals. MATERIALS AND METHODS: This case-control study was performed on 86 subjects stratified into four groups using anthropometric and clinical measurements: MHO (21), MUHO (21), MHNO (22), and MUHNO (22). Serum metabolites were profiled using nuclear magnetic resonance (NMR). Multivariate analysis was applied to uncover discriminant metabolites, and enrichment analysis was performed to identify underlying pathways. RESULTS: Significantly higher levels of glutamine, asparagine, alanine, L-glutathione reduced, 2-aminobutyrate, taurine, betaine, and choline, and lower level of D-sphingosine were observed in MHO group compared with MUHO. In comparison of MHNO and MUHNO groups, significantly lower levels of alanine, glycine, glutamine, histidine, L-glutathione reduced, and betaine, and higher levels of isoleucine, L-proline, cholic acid, and carnitine appeared in MUHNO individuals. Moreover, significantly affected pathways included amino acid metabolism, urea cycle and ammonia recycling in MUHO subjects and glutathione metabolism, amino acid metabolism, and ammonia recycling in MUHNO members. CONCLUSION: Literature review helped us to hint that altered levels of most metabolites might associate to insulin sensitivity and insulin resistance in MHO and MUHNO individuals, respectively. Besides, abnormal amino acid metabolism and ammonia recycling involved in unhealthy phenotypes (MUHO, MUHNO) might be associated with insulin resistance.

Urine and serum NMR-based metabolomics in pre-procedural prediction of contrast-induced nephropathy.

Contrast induced nephropathy (CIN) has been reported to be the third foremost cause of acute renal failure. Metabolomics is a robust technique that has been used to identify potential biomarkers for the prediction of renal damage. We aim to analyze the serum and urine metabolites changes, before and after using contrast for coronary angiography, to determine if metabolomics can predict early development of CIN. 66 patients undergoing elective coronary angiography were eligible for enrollment. Urine and serum samples were collected prior to administration of CM and 72 h post procedure and analyzed by nuclear magnetic resonance. The significant differential metabolites between patients who develop CIN and patients who have stable renal function after angiography were identified using U test and receiver operating characteristic analysis was performed for each metabolite candidate. Potential susceptible pathways to cytotoxic effect of CM were investigated by pathway analysis. A predictive panel composed of six urinary metabolites had the best area under the curve. Glutamic acid, uridine diphosphate, glutamine and tyrosine were the most important serum predictive biomarkers. Several pathways related to amino acid and nicotinamide metabolism were suggested as impaired pathways in CIN prone patients. Changes exist in urine and serum metabolomics patterns in patients who do and do not develop CIN after coronary angiography hence metabolites may be potential predictive identifiers of CIN.

Metabolic profiling of seminal plasma from teratozoospermia patients.

Teratozoospermia is one of conditions that can cause male infertility. The mechanism of teratozoospermia remains unclear. The knowledge of the metabolites in human seminal plasma (HSP) is meaningful for the pathological study of teratozoospermia. Analysis of changed metabolites in HSP can help understand the cellular mechanism, find the novel biomarkers and subsequently design a diagnosis test. In this study, the analysis of samples performed by proton nuclear magnetic resonance spectroscopy (1H NMR spectroscopy) to identify the various metabolites, with the aim of finding metabolic profiles and biomarkers related to male infertility. Eighteen de-regulated metabolites were identified in fertile men compared to teratozoospermia patients. These changes illustrate the deficiencies in absorption or metabolism of these metabolites in teratozoospermia. Furthermore, metabolic profiling showed that it is not possible to classify teratozoospermia based on teratozoospermia index (TZI). To the best of our knowledge, this is the first metabolic profiling analysis of HSP described the metabolic features of teratozoospermia in a holistic view.

Metabolomics approach reveals urine biomarkers and pathways associated with the pathogenesis of lupus nephritis.

OBJECTIVES: lupus nephritis (LN) is a severe form of systemic lupus erythematosus (SLE) with renal complications. Current diagnosis is based on invasive renal biopsy and serum antibodies and complement levels that are not specific enough. The current study aims to identify new biomarker candidates for non-invasive diagnosis of LN and explore the pathogenic mechanisms that contribute to renal injury. MATERIALS AND METHODS: A metabolomics approach using 1H-nuclear magnetic resonance (1H-NMR), was developed for comparison of urine metabolic profile of 14 LN patients, 10 SLE patients, and 11 healthy controls (HCs). Differential biomarker candidates were identified by using multivariate modeling, and their diagnostic accuracy was evaluated by receiver operating characteristic analysis (ROC). RESULTS: Three metabolites were common in differentiating all three groups including beta-alanine, 2,2-dimethylsucssinic acid, and 3,4-Dihydroxyphenylacetaldehyde and suggested as a diagnostic panel for LN with AUC of 0.89, sensitivity of 81 %, and specificity of 100 %. Complementary analyses on pathways indicated that nicotinate and nicotinamide metabolism is the most important perturbed pathway in LN. CONCLUSION: Metabolomics is a useful tool for identification of biomarkers with the ability to diagnose LN patients and predict perturbed pathways responsible for renal injury.

Metabolomics analysis of the saliva in patients with chronic hepatitis B using nuclear magnetic resonance: a pilot study.

OBJECTIVES: Hepatitis B virus infection causes chronic disease such as cirrhosis and hepatocellular carcinoma. The metabolomics investigations have been demonstrated to be related to pathophysiologic mechanisms in many disorders such as hepatitis B infection. The aim of this study was to investigate the saliva metabolic profile of patients with chronic hepatitis B infection and to identify underlying mechanisms as well as potential biomarkers associated with the disease. MATERIALS AND METHODS: Saliva from 16 healthy subjects and 20 patients with chronic hepatitis B virus were analyzed by nuclear magnetic resonance (NMR). Then, multivariate statistical analysis was performed to identify discriminative metabolites between two groups. RESULTS: A set of metabolites were detected, including propionic acid, putrescine, acetic acid, succinic acid, tyrosine, lactic acid, butyric acid, pyruvic acid, 4-pyridoxic acid and 4-hydroxybenzoic acid, which in combination with one another could accurately distinguish patients from healthy controls. Our results clearly demonstrated altered metabolites are involved in nine metabolic pathways. CONCLUSION: Metabolomics has the potential to be considered as a novel clinical tool for hepatitis B diagnosis while contributing to a comprehensive understanding of disease mechanisms.

A pilot study of the effect of phospholipid curcumin on serum metabolomic profile in patients with non-alcoholic fatty liver disease: a randomized, double-blind, placebo-controlled trial.

BACKGROUND/OBJECTIVES: Curcumin, a natural polyphenol compound in the spice turmeric, has been found to have potent anti-oxidative and anti-inflammatory activity. Curcumin may treat non-alcoholic fatty liver disease (NAFLD) through its beneficial effects on biomarkers of oxidative stress (OS) and inflammation, which are considered as two feature of this disease. However, the effects of curcumin on NAFLD have been remained poorly understood. This investigation evaluated the effects of administrating curcumin on metabolic status in NAFLD patients. SUBJECTS/METHODS: Fifty-eight NAFLD patients participated in a randomized, double-blind, placebo-controlled parallel design of study. The subjects were allocated randomly into two groups, which either received 250 mg phospholipid curcumin or placebo, one capsule per day for a period of 8 weeks. Fasting blood samples were taken from each subject at the start and end of the study period. Subsequently, metabolomics analysis was performed for serum samples using NMR. RESULTS: Compared with the placebo, supplementing phospholipid curcumin resulted in significant decreases in serum including 3- methyl-2-oxovaleric acid, 3-hydroxyisobutyrate, kynurenine, succinate, citrate, α-ketoglutarate, methylamine, trimethylamine, hippurate, indoxyl sulfate, chenodeoxycholic acid, taurocholic acid, and lithocholic acid. This profile of metabolic biomarkers could distinguish effectively NAFLD subjects who were treated with curcumin and placebo groups, achieving value of 0.99 for an area under receiver operating characteristic curve (AUC). CONCLUSIONS: Characterizing the serum metabolic profile of the patients with NAFLD at the end of the intervention using NMR-based metabolomics method indicated that the targets of curcumin treatment included some amino acids, TCA cycle, bile acids, and gut microbiota.

Cis-trans proline isomers in the catalytic domain of calcineurin.

Calcineurin is an essential calcium-activated serine/threonine phosphatase. The six NMR-observable methionine methyl groups in the catalytic domain of human calcineurin Aα (CNA) were assigned and used as reporters of the presence of potential cis-trans isomers in solution. Proline 84 is found in the cis conformation in most calcineurin X-ray structures, and proline 309, which is part of a highly conserved motif in phosphoprotein phosphatases, was modeled with a cis peptide bond in one of the two molecules present in the asymmetric unit of CNA. We mutated each of the two prolines to alanine to force the trans conformation. Solution NMR shows that the P84A CNA mutant exists in two forms, compatible with cis-trans isomers, while the P309A mutant is predominantly in the trans conformation. DATABASE: PDB depositions mentioned PDB 5C1V and 2JOG.

The metabolomics signature associated with responsiveness to steroid therapy in focal segmental glomerulosclerosis: a pilot study

Abstract Background Focal segmental glomerulosclerosis (FSGS) is considered one of the most severe glomerular diseases and around 80% of cases are resistant to steroid treatment. Since a large proportion of steroid-resistant (SR) FSGS patients progress to end-stage renal disease, other therapeutic strategies may benefit this population. However, identification of non-invasive biomarkers to predict this high-risk population is needed. Objective We aimed to identify the biomarker candidates to distinguish SR from steroid-sensitive (SS) patients using metabolomics approach and to identify the possible molecular mechanism of resistance. Methods Urine was collected from biopsy-proven FSGS patients eligible for monotherapy with prednisolone. Patients were followed for 6-8 weeks and categorized as SS or SR. Metabolite profile of urine samples was analyzed by one-dimensional 1H-nuclear magnetic resonance (1H-NMR). Predictive biomarker candidates and their diagnostic importance impaired molecular pathways in SR patients, and the common target molecules between biomarker candidates and drug were predicted. Results Homovanillic acid, 4-methylcatechol, and tyrosine were suggested as the significant predictive biomarker candidates, while L-3,4-dihydroxyphenylalanine, norepinephrine, and gentisic acid had high accuracy as well. Tyrosine metabolism was the most important pathway that is perturbed in SR patients. Common targets of the action of biomarker candidates and prednisolone were molecules that contributed in apoptosis. Conclusion Urine metabolites including homovanillic acid, 4-methylcatechol, and tyrosine may serve as potential non-invasive predictive biomarkers for evaluating the responsiveness of FSGS patients.