Gender-Specific Metabolomic Profiling of Obesity in Leptin-Deficient ob/ob Mice by 1H NMR Spectroscopy

Despite the numerous metabolic studies on obesity, gender bias in obesity has rarely been investigated. Here, we report the metabolomic analysis of obesity by using leptin-deficient ob/ob mice based on the gender. Metabolomic analyses of urine and serum from ob/ob mice compared with those from C57BL/6J lean mice, based on the ¹H NMR spectroscopy in combination with multivariate statistical analysis, revealed clear metabolic differences between obese and lean mice. We also identified 48 urine and 22 serum metabolites that were statistically significantly altered in obese mice compared to lean controls. These metabolites are involved in amino acid metabolism (leucine, alanine, ariginine, lysine, and methionine), tricarbocylic acid cycle and glucose metabolism (pyruvate, citrate, glycolate, acetoacetate, and acetone), lipid metabolism (cholesterol and carnitine), creatine metabolism (creatine and creatinine), and gut-microbiome-derived metabolism (choline, TMAO, hippurate, p-cresol, isobutyrate, 2-hydroxyisobutyrate, methylamine, and trigonelline). Notably, our metabolomic studies showed distinct gender variations. The obese male mice metabolism was specifically associated with insulin signaling, whereas the obese female mice metabolism was associated with lipid metabolism. Taken together, our study identifies the biomarker signature for obesity in ob/ob mice and provides biochemical insights into the metabolic alteration in obesity based on gender.     

A metabolic discrimination model for nasopharyngeal carcinoma and its potential role in the therapeutic evaluation of radiotherapy

Nasopharyngeal carcinoma (NPC) is one of the most common malignancies in Southeast Asia and radiotherapy or radiotherapy, in combination with chemotherapy is the primary treatment strategy. In this study, we adopted a metabolomic method to investigate the metabolic disorders in NPC and evaluate the effect of radiotherapy on metabolic profile alterations in NPC patients. To generate the NPC metabolic profiles, 402 serum samples were collected from 100 newly-diagnosed NPC patients and 100 healthy volunteers. Based on gas chromatography–mass spectrometry (GC–MS) metabolomics coupled with partial least squares-discriminant analysis, a NPC discrimination model was constructed with a sensitivity of 88 % (88/100) and a specificity of 92 % (92/100). Seven metabolites, including glucose, linoleic acid, stearic acid, arachidonic acid, proline, β-hydroxy butyrate and glycerol 1-hexadecanoate, were identified as contributing mostly to the discrimination of NPC serum from healthy controls. To validate if the model can be applied for therapeutic evaluation, 202 serum samples were collected from 20 patients receiving standard radiotherapy for up to a 3-year follow-up period. The metabolic footprints of 20 NPC patients treated with standard radiotherapy are visually presented. Based on the footprint trends of the sera samples in irradiation-treated NPC patients who were gradually closer to healthy controls or not, patients were divided into positive and negative groups, respectively. The coincident rate of the trends of metabolic footprints to the actual clinical prognosis trend was approximately 80 %. This study demonstrates that a GC–MS-based metabolic profiling approach as a novel strategy may be capable to delineating the potential of metabolite alterations in discrimination and therapeutic evaluation of NPC patients.     

Comparative Circadian Metabolomics Reveal Differential Effects of Nutritional Challenge in the Serum and Liver

Diagnosis and therapeutic interventions in pathological conditions rely upon clinical monitoring of key metabolites in the serum. Recent studies show that a wide range of metabolic pathways are controlled by circadian rhythms whose oscillation is affected by nutritional challenges, underscoring the importance of assessing a temporal window for clinical testing and thereby questioning the accuracy of the reading of critical pathological markers in circulation. We have been interested in studying the communication between peripheral tissues under metabolic homeostasis perturbation. Here we present a comparative circadian metabolomic analysis on serum and liver in mice under high fat diet. Our data reveal that the nutritional challenge induces a loss of serum metabolite rhythmicity compared with liver, indicating a circadian misalignment between the tissues analyzed. Importantly, our results show that the levels of serum metabolites do not reflect the circadian liver metabolic signature or the effect of nutritional challenge. This notion reveals the possibility that misleading reads of metabolites in circulation may result in misdiagnosis and improper treatments. Our findings also demonstrate a tissue-specific and time-dependent disruption of metabolic homeostasis in response to altered nutrition.     

Metabolic analysis of infants with bronchopulmonary dysplasia under early nutrition therapy: An observational cohort study

To assess the amino acid and fatty acid metabolite patterns between infants with and without bronchopulmonary dysplasia in different nutritional stages after birth and identify metabolic indicators of bronchopulmonary dysplasia. This was an observational cohort of preterm infants born at a gestational age ≤32 + 6 weeks and with a body weight ≤2000 g. Amino acid and carnitine profiles were measured in dried blood spots (DBSs) during the early nutrition transitional phase using tandem mass spectrometry. Bronchopulmonary dysplasia was defined as oxygen dependence at 36 weeks of postmenstrual age or 28 days after birth. Metabolomic analysis was employed to define metabolites with significant differences, map significant metabolites into pathways, and identify metabolic indicators of bronchopulmonary dysplasia. We evaluated 45 neonates with and 40 without bronchopulmonary dysplasia. Four amino acids and three carnitines showed differences between the groups. Three carnitines (C0, C2, and C6:1) were high in the bronchopulmonary dysplasia group mostly; conversely, all four amino acids (threonine, arginine, methionine, and glutamine (Gln)) were low in the bronchopulmonary dysplasia group. Pathway analysis of these metabolites revealed two pathways with significant changes (p < 0.05). ROC analysis showed Gln/C6:1 at total parenteral nutrition phase had both 80% sensitivity and specificity for predicting the development of bronchopulmonary dysplasia, with an area under the curve of 0.81 (95% confidence interval 0.71–0.89). Amino acid and fatty acid metabolite profiles changed in infants with bronchopulmonary dysplasia after birth during the nutrition transitional period, suggesting that metabolic dysregulation may participate in the development of bronchopulmonary dysplasia. Our findings demonstrate that metabolic indicators are promising for forecasting the occurrence of bronchopulmonary dysplasia among preterm neonates.     

Cancer cachexia’s metabolic signature in a murine model confirms a distinct entity

Despite recent consensus definitions, lack of specific biomarkers remains a hurdle towards a more accurate and efficient diagnosis of cancer cachexia, distinguishing cachexia as a separate entity from other wasting syndromes. In a previous pilot study, we have shown that cancer-cachectic mice have a unique metabolic fingerprint with distinct glucose and lipid alterations compared to healthy controls. Further metabolomics studies were carried out to investigate differences in metabolic profiles of cancer-cachectic mice to tumor-bearing non-cachectic mice, calorie-restricted mice, and surgically treated cancer-cachectic mice. CD2F1 mice were divided into: (1) Cachexia Group received cachexia-inducing C26 undifferentiated colon carcinoma cells; (2) Tumor-Burden Group received, non-cachectic, P388 lymphoma cells; (3) Caloric-Restriction Group, remaining cancer-free, but subjected to caloric-restriction; (4) Surgery Group, similar to Cachexia Group, but tumors resected mid-experiment; and (5) Control Group aged intact. Baseline, mid-experiment and final serum samples were collected for ¹H NMR spectroscopic analysis. After data reduction, unsupervised principal component analysis and orthogonal projections to latent structures analyses demonstrate that the unique metabolic fingerprint is independent of tumor-burden and distinct from profiles of caloric-restriction and aging. Hyperlipidemia, hyperglycemia, and reduced branched-chain amino acids distinguish cachexia from other groups. Furthermore, the profile of surgically treated mice differs from that of cachectic mice, reverting to a profile more congruent with healthy controls indicating cachexia is amenable to correction where surgical cure is possible. That metabolomic analysis of murine serum is able to differentiate cachexia from tumor-burden and caloric-restriction warrants similar translational investigations in patients to explore cancer cachexia’s unique biomarkers.     

Integrative Metabolic Signatures for Hepatic Radiation Injury

Background

Radiation-induced liver disease (RILD) is a dose-limiting factor in curative radiation therapy (RT) for liver cancers, making early detection of radiation-associated liver injury absolutely essential for medical intervention. A metabolomic approach was used to determine metabolic signatures that could serve as biomarkers for early detection of RILD in mice.

Methods

Anesthetized C57BL/6 mice received 0, 10 or 50 Gy Whole Liver Irradiation (WLI) and were contrasted to mice, which received 10 Gy whole body irradiation (WBI). Liver and plasma samples were collected at 24 hours after irradiation. The samples were processed using Gas Chromatography/Mass Spectrometry and Liquid Chromatography/Mass Spectrometry.

Results

Twenty four hours after WLI, 407 metabolites were detected in liver samples while 347 metabolites were detected in plasma. Plasma metabolites associated with 50 Gy WLI included several amino acids, purine and pyrimidine metabolites, microbial metabolites, and most prominently bradykinin and 3-indoxyl-sulfate. Liver metabolites associated with 50 Gy WLI included pentose phosphate, purine, and pyrimidine metabolites in liver. Plasma biomarkers in common between WLI and WBI were enriched in microbial metabolites such as 3 indoxyl sulfate, indole-3-lactic acid, phenyllactic acid, pipecolic acid, hippuric acid, and markers of DNA damage such as 2-deoxyuridine. Metabolites associated with tryptophan and indoles may reflect radiation-induced gut microbiome effects. Predominant liver biomarkers in common between WBI and WLI were amino acids, sugars, TCA metabolites (fumarate), fatty acids (lineolate, n-hexadecanoic acid) and DNA damage markers (uridine).

Conclusions

We identified a set of metabolomic markers that may prove useful as plasma biomarkers of RILD and WBI. Pathway analysis also suggested that the unique metabolic changes observed after liver irradiation was an integrative response of the intestine, liver and kidney.     

Cross‐sectional serum metabolomic study of multiple forms of muscular dystrophy

Muscular dystrophies are characterized by a progressive loss of muscle tissue and/or muscle function. While metabolic alterations have been described in patients’‐derived muscle biopsies, non‐invasive readouts able to describe these alterations are needed in order to objectively monitor muscle condition and response to treatment targeting metabolic abnormalities. We used a metabolomic approach to study metabolites concentration in serum of patients affected by multiple forms of muscular dystrophy such as Duchenne and Becker muscular dystrophies, limb‐girdle muscular dystrophies type 2A and 2B, myotonic dystrophy type 1 and facioscapulohumeral muscular dystrophy. We show that 15 metabolites involved in energy production, amino acid metabolism, testosterone metabolism and response to treatment with glucocorticoids were differentially expressed between healthy controls and Duchenne patients. Five metabolites were also able to discriminate other forms of muscular dystrophy. In particular, creatinine and the creatine/creatinine ratio were significantly associated with Duchenne patients performance as assessed by the 6‐minute walk test and north star ambulatory assessment. The obtained results provide evidence that metabolomics analysis of serum samples can provide useful information regarding muscle condition and response to treatment, such as to glucocorticoids treatment.     

Metabolic characterization of hepatitis B virus-related liver cirrhosis using NMR-based serum metabolomics

Introduction

Liver cirrhosis (LC) is an advanced liver disease that can develop into hepatocellular carcinoma. Hepatitis B virus (HBV) infection is one of the main causes of LC. Therefore, there is an urgent need for developing a new method to monitor the progression of HBV-related LC (HBV-LC).

Objectives

In this study, we attempted to examine serum metabolic changes in healthy individuals as well as patients with HBV and HBV-LC. Furthermore, potential metabolite biomarkers were identified to evaluate patients progressed from health to HBV-LC.

Methods

Metabolic profiles in the serum of healthy individuals as well as patients with HBV and HBV-LC were detected using an NMR-based metabolomic approach. Univariate and multivariate analyses were conducted to analyze serum metabolic changes during HBV-LC progression. Moreover, potential metabolite biomarkers were explored by receiver operating characteristic curve analysis.

Results

Serum metabolic changes were closely associated with the progression of HBV-LC, mainly involving energy metabolism, protein metabolism, lipid metabolism and microbial metabolism. Serum histidine was identified as a potential biomarker for HBV patients. Acetate, formate, pyruvate and glutamine in the serum were identified as a potential biomarker panel for patients progressed from HBV to HBV-LC. In addition, phenylalanine, unsaturated lipid, n-acetylglycoprotein and acetone in the serum could be considered as a potential common biomarkers panel for these patients.

Conclusion

NMR-based serum metabolomic approach could be a promising tool to monitor the progression of liver disease. Different metabolites may reflect different stages of liver disease.

     

1H-NMR-based metabolomics for cancer targeting and metabolic engineering –A review

Nuclear magnetic resonance (NMR) spectroscopy acts as the best tool that can be used in tissue engineering scaffolds to investigate unknown metabolites. Moreover, metabolomics is a systems approach for examining in vivo and in vitro metabolic profiles, which promises to provide data on cancer metabolic alterations. However, metabolomic profiling allows for the activity of small molecules and metabolic alterations to be measured. Furthermore, metabolic profiling also provides high-spectral resolution, which can then be linked to potential metabolic relationships. An altered metabolism is a hallmark of cancer that can control many malignant properties to drive tumorigenesis. Metabolite targeting and metabolic engineering contribute to carcinogenesis by proliferation, and metabolic differentiation. The resulting the metabolic differences are examined with traditional chemometric methods such as principal component analysis (PCA), and partial least squares-discriminate analysis (PLS-DA). In this review, we examine NMR-based activity metabolomic platforms that can be used to analyze various fluxomics and for multivariant statistical analysis in cancer. We also aim to provide the reader with a basic understanding of NMR spectroscopy, cancer metabolomics, target profiling, chemometrics, and multifunctional tools for metabolomics discrimination, with a focus on metabolic phenotypic diversity for cancer therapeutics.     

Plasma metabolomics reveals a potential panel of biomarkers for early diagnosis in acute coronary syndrome

Discovery of new biomarkers is critical for early diagnosis of acute coronary syndrome (ACS). Recent advances in metabolomic technologies have drastically enhanced the possibility of improving the knowledge of its physiopathology through the identification of the altered metabolic pathways. In this study, analyses of peripheral plasma from non-ST segment elevation ACS patients and healthy controls by gas chromatography–mass spectrometry (GC–MC) permitted the identification of 15 metabolites with statistical differences (p < 0.05) between experimental groups. Additionally, validation by GC–MC and liquid chromatography–MC permitted us to identify a potential panel of biomarkers formed by 5-OH-tryptophan, 2-OH-butyric acid and 3-OH-butyric acid. This panel of biomarkers reflects the oxidative stress and the hypoxic state that suffers the myocardial cells and consequently constitutes a metabolomic signature of the atherogenesis process that could be used for early diagnosis of ACS.     

Serum Metabolomic Patterns in Patients with Autoimmune Thyroid Disease

Objective: Autoimmune thyroid disease, including Graves disease (GD) and Hashimoto thyroiditis (HT), is one of the most common endocrine diseases. GD and HT are the main etiologies for hyperthyroidism and hypothyroidism, respectively. This study aimed to provide a metabolomic analysis of GD patients with hyperthyroidism and HT patients with hypothyroidism.Methods: This study investigated serum metabolomics in 43 GD patients with hyperthyroidism, 45 HT patients with hypothyroidism, and 52 age- and sex-matched healthy controls. The metabolomic data were analyzed by performing multivariate statistical analysis.Results: The 186 metabolites including amino acids, bile acids, free fatty acids, and lipids were identified in all participants. Multivariate models indicated systematic differences in the hyperthyroidism, hypothyroidism, and control groups. Compared to healthy controls, the 22 metabolites in the hyperthyroidism group and the 17 metabolites in the hypothyroidism group were significantly changed. Pathway analysis showed that hyperthyroidism had a significant impact on arginine and proline metabolism and aminoacyl-transfer ribonucleic acid biosynthesis, while hypothyroidism had a significant impact on alanine, aspartate, and glutamate metabolism.Conclusion: The serum metabolomic pattern changes in patients with autoimmune thyroid dysfunction.Abbreviations: BMI = body mass index; CA = cholic acid; CDCA = chenodeoxycholic acid; DCA = deoxycholic acid; FBG = fasting plasma glucose; FINS = fasting plasma insulin; FT3 = free triiodothyronine; FT4 = free thyroxine; GD = Graves disease; GDCA = glycodeoxycholic acid; HDL-C = high-density lipoprotein cholesterol; HOMA-IR = homeostasis model assessment of insulin resistance; HT = Hashimoto thyroiditis; LDL-C = low-density lipoprotein cholesterol; PC = phosphatidylcholine; PCA = principal component analysis; PLS-DA = partial least squares discriminant analysis; SM = sphingomyelin; TBA = total bile acid; TC = total cholesterol; TG = triglyceride; TSH = thyrotropin; VIP = variable influences on projection     

Using proteomic approach to identify tumor-associated proteins as biomarkers in human esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers in China. The lower survival rate of ESCC is attributed to late diagnosis and poor therapeutic efficacy; therefore, the identification of tumor-associated proteins as biomarkers for early diagnosis, and the discovery of novel targets for therapeutic intervention, seems very important for increasing the survival rate of ESCC. To identify tumor-associated proteins as biomarkers in ESCC, we have analyzed ESCC tissues and adjacent normal tissues by two-dimensional electrophoresis (2DE) and matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) analysis. The results showed that a total of 104 protein spots with different expression levels were found on 2DE, and 47 proteins were eventually identified by MALDI-TOF MS. Among these identified proteins, 33 proteins including keratin 17 (KRT17), biliverdin reductase B (BLVRB), proteasome activator subunit 1 (PSME1), manganese superoxide dismutase (MnSOD), high-mobility group box-1(HMGB1), heat shock protein 70 (HSP70), peroxiredoxin (PRDX1), keratin 13 (KRT13), and so on were overexpressed, and 14 proteins including cystatin B (CSTB), tropomyosin 2 (TPM2), annexin 1 (ANX1), transgelin (TAGLN), keratin 19 (KRT19), stratifin (SFN), and so on were down-expressed in ESCC. Biological functions of these proteins are associated with cell proliferation, cell motility, protein folding, oxidative stress, and signal transduction. In the subsequent study using immunoassay on ESCC serum samples and tissue-array slides, two representative proteins, HSP70 and HMGB1, were selected as examples for the purpose of validation. The results showed that both HSP70 and HMGB1 can induce autoantibody response in ESCC sera and have higher expression in ESCC tissues. Especially, the frequency of antibodies to HSP70 in ESCC sera was significantly higher than that in normal human sera. The preliminary results suggest that some of these identified proteins might contribute to esophageal cell differentiation and carcinogenesis, certain proteins could be used as tumor-associated antigen (TAA) biomarkers in cancer diagnosis, and further studies on these identified proteins should provide more evidence of how these proteins are involved in carcinogenesis of ESCC.     

Biomarkers of inflammation, immunosuppression and stress with active disease are revealed by metabolomic profiling of tuberculosis patients

Although tuberculosis (TB) causes more deaths than any other pathogen, most infected individuals harbor the pathogen without signs of disease. We explored the metabolome of >400 small molecules in serum of uninfected individuals, latently infected healthy individuals and patients with active TB. We identified changes in amino acid, lipid and nucleotide metabolism pathways, providing evidence for anti-inflammatory metabolomic changes in TB. Metabolic profiles indicate increased activity of indoleamine 2,3 dioxygenase 1 (IDO1), decreased phospholipase activity, increased abundance of adenosine metabolism products, as well as indicators of fibrotic lesions in active disease as compared to latent infection. Consistent with our predictions, we experimentally demonstrate TB-induced IDO1 activity. Furthermore, we demonstrate a link between metabolic profiles and cytokine signaling. Finally, we show that 20 metabolites are sufficient for robust discrimination of TB patients from healthy individuals. Our results provide specific insights into the biology of TB and pave the way for the rational development of metabolic biomarkers for TB.     

Altered metabolome and microbiome features provide clues in understanding irritable bowel syndrome and depression comorbidity

Irritable bowel syndrome (IBS) is one of the functional gastrointestinal disorders characterized by chronic and/or recurrent symptoms of abdominal pain and irregular defecation. Changed gut microbiota has been proposed to mediate IBS; however, contradictory results exist, and IBS-specific microbiota, metabolites, and their interactions remain poorly understood. To address this issue, we performed metabolomic and metagenomic profiling of stool and serum samples based on discovery (n = 330) and validation (n = 101) cohorts. Fecal metagenomic data showed moderate dysbiosis compared with other diseases, in contrast, serum metabolites showed significant differences with greater power to distinguish IBS patients from healthy controls. Specifically, 726 differentially abundant serum metabolites were identified, including a cluster of fatty acyl-CoAs enriched in IBS. We further identified 522 robust associations between differentially abundant gut bacteria and fecal metabolites, of which three species including Odoribacter splanchnicus, Escherichia coli, and Ruminococcus gnavus were strongly associated with the low abundance of dihydropteroic acid. Moreover, dysregulated tryptophan/serotonin metabolism was found to be correlated with the severity of IBS depression in both fecal and serum metabolomes, characterized by a shift in tryptophan metabolism towards kynurenine production. Collectively, our study revealed serum/fecal metabolome alterations and their relationship with gut microbiome, highlighted the massive alterations of serum metabolites, which empower to recognize IBS patients, suggested potential roles of metabolic dysregulation in IBS pathogenesis, and offered new clues to understand IBS depression comorbidity. Our study provided a valuable resource for future studies, and would facilitate potential clinical applications of IBS featured microbiota and/or metabolites.Subject terms: Clinical microbiology, Colitis, Metagenomics     

Dietary leucine--an environmental modifier of insulin resistance acting on multiple levels of metabolism

Environmental factors, such as the macronutrient composition of the diet, can have a profound impact on risk of diabetes and metabolic syndrome. In the present study we demonstrate how a single, simple dietary factor--leucine--can modify insulin resistance by acting on multiple tissues and at multiple levels of metabolism. Mice were placed on a normal or high fat diet (HFD). Dietary leucine was doubled by addition to the drinking water. mRNA, protein and complete metabolomic profiles were assessed in the major insulin sensitive tissues and serum, and correlated with changes in glucose homeostasis and insulin signaling. After 8 weeks on HFD, mice developed obesity, fatty liver, inflammatory changes in adipose tissue and insulin resistance at the level of IRS-1 phosphorylation, as well as alterations in metabolomic profile of amino acid metabolites, TCA cycle intermediates, glucose and cholesterol metabolites, and fatty acids in liver, muscle, fat and serum. Doubling dietary leucine reversed many of the metabolite abnormalities and caused a marked improvement in glucose tolerance and insulin signaling without altering food intake or weight gain. Increased dietary leucine was also associated with a decrease in hepatic steatosis and a decrease in inflammation in adipose tissue. These changes occurred despite an increase in insulin-stimulated phosphorylation of p70S6 kinase indicating enhanced activation of mTOR, a phenomenon normally associated with insulin resistance. These data indicate that modest changes in a single environmental/nutrient factor can modify multiple metabolic and signaling pathways and modify HFD induced metabolic syndrome by acting at a systemic level on multiple tissues. These data also suggest that increasing dietary leucine may provide an adjunct in the management of obesity-related insulin resistance.     

Effects of myocardial ischemia/reperfusion injury on plasma metabolomic profile during aging

BackgroundHeart disease is a frequent cause of hospitalization and mortality for elderly patients. A common feature of both heart disease and aging itself is the involvement of metabolic organ alterations ultimately leading to changes in circulating metabolite levels. However, the specific contribution of aging and ischemic injury to the metabolic dysregulation occurring in older adults with ischemic heart disease is still unknown.AimTo evaluate the effects of aging and ischemia/reperfusion (I/R) injury on plasma metabolomic profiling in mice.MethodsYoung and aged mice were subjected to a minimally invasive model of I/R injury or sham operation. Complete evaluation of cardiac function and untargeted plasma metabolomics analysis were performed.ResultsWe confirmed that aged mice from the sham group had impaired cardiac function and augmented left ventricular (LV) dimensions compared to young sham‐operated mice. Further, we found that ischemic injury did not drastically reduce LV systolic/diastolic function and dyssynchrony in aged compared to young mice. Using an untargeted metabolomics approach focused on aqueous metabolites, we found that ischemic injury does not affect the plasma metabolomic profile either in young or old mice. Our data also demonstrate that age significantly affects circulating metabolite levels (predominantly amino acids, phospholipids and organic acids) and perturbs several pathways involved in amino acid, glucid and nucleic acid metabolism as well as pyridoxal‐5′‐phosphate salvage pathway in both sham and ischemic mice.ConclusionsOur approach increases our understanding of age‐associated plasma metabolomic signatures in mice with and without heart disease excluding confounding factors related to metabolic comorbidities.     

Metabolomics of the human aqueous humor

Introduction

The optical elements of the eye—cornea, lens, and vitreous humor—are avascular tissues, and their nutrition and waste removal are provided by aqueous humor (AH). The AH production occurs through the active secretion and the passive diffusion/ultrafiltration of blood plasma. The comparison of the metabolomic profiles of AH and plasma is important for understanding of the mechanisms of biochemical processes and metabolite transport taking place in vivo in ocular tissues.

Objectives

The work is aimed at the determination of concentrations of a wide range of most abundant metabolites in the human AH, the comparison of the metabolomic profiles of AH and serum, and the analysis of the post-mortem metabolomic changes in these two biological fluids.

Methods

The quantitative metabolomic profiling was carried out with the use of two independent methods—high-frequency ¹H NMR spectroscopy and HPLC with high-resolution ESI-MS detection.

Results

The concentrations of 71 most abundant metabolites in blood serum and AH from living patients and human cadavers have been measured. It has been found that the level of ascorbate in AH is by two orders of magnitude higher than that in serum; the levels of other metabolites are either similar to that in serum, or differ from that by a factor of 2–5. The post-mortem metabolomic composition of both serum and AH undergoes rapid and strong changes.

Conclusion

The differences between the metabolomic profiles of AH and serum for majority of metabolites can be attributed to the metabolic activity of the ocular tissues leading to the lack or excess of some metabolites, while the high concentration of ascorbate in AH demonstrates the activity of ascorbate-specific pumps at the blood-aqueous border. The post-mortem metabolomic changes are caused by the disruption of the major biochemical cycles and cell lysis. These changes should be taken into account in the analysis of disease-induced changes in post-mortem samples of the ocular tissues.

     

Biomarkers of Inflammation,Immunosuppression and Stress Are Revealed by Metabolomic Profiling of Tuberculosis Patients

Although tuberculosis (TB) causes more deaths than any other pathogen, most infected individuals harbor the pathogen without signs of disease. We explored the metabolome of >400 small molecules in serum of uninfected individuals, latently infected healthy individuals and patients with active TB. We identified changes in amino acid, lipid and nucleotide metabolism pathways, providing evidence for anti-inflammatory metabolomic changes in TB. Metabolic profiles indicate increased activity of indoleamine 2,3 dioxygenase 1 (IDO1), decreased phospholipase activity, increased abundance of adenosine metabolism products, as well as indicators of fibrotic lesions in active disease as compared to latent infection. Consistent with our predictions, we experimentally demonstrate TB-induced IDO1 activity. Furthermore, we demonstrate a link between metabolic profiles and cytokine signaling. Finally, we show that 20 metabolites are sufficient for robust discrimination of TB patients from healthy individuals. Our results provide specific insights into the biology of TB and pave the way for the rational development of metabolic biomarkers for TB.     

A metabolic signature predicts biological age in mice

Our understanding of the mechanisms by which aging is produced is still very limited. Here, we have determined the sera metabolite profile of 117 wild‐type mice of different genetic backgrounds ranging from 8 to 129 weeks of age. This has allowed us to define a robust metabolomic signature and a derived metabolomic score that reliably/accurately predicts the age of wild‐type mice. In the case of telomerase‐deficient mice, which have a shortened lifespan, their metabolomic score predicts older ages than expected. Conversely, in the case of mice that overexpress telomerase, their metabolic score corresponded to younger ages than expected. Importantly, telomerase reactivation late in life by using a TERT‐based gene therapy recently described by us significantly reverted the metabolic profile of old mice to that of younger mice, further confirming an anti‐aging role for telomerase. Thus, the metabolomic signature associated with natural mouse aging accurately predicts aging produced by telomere shortening, suggesting that natural mouse aging is in part produced by presence of short telomeres. These results indicate that the metabolomic signature is associated with the biological age rather than with the chronological age. This constitutes one of the first aging‐associated metabolomic signatures in a mammalian organism.