Randomised, double-blind, placebo-controlled trial with azithromycin selects for anti-inflammatory microbial metabolites in the emphysematous lung.

INTRODUCTION: Azithromycin (AZM) reduces pulmonary inflammation and exacerbations in patients with COPD having emphysema. The antimicrobial effects of AZM on the lower airway microbiome are not known and may contribute to its beneficial effects. Here we tested whether AZM treatment affects the lung microbiome and bacterial metabolites that might contribute to changes in levels of inflammatory cytokines in the airways. METHODS: 20 smokers (current or ex-smokers) with emphysema were randomised to receive AZM 250 mg or placebo daily for 8 weeks. Bronchoalveolar lavage (BAL) was performed at baseline and after treatment. Measurements performed in acellular BAL fluid included 16S rRNA gene sequences and quantity; 39 cytokines, chemokines and growth factors and 119 identified metabolites. The response to lipopolysaccharide (LPS) by alveolar macrophages after ex-vivo treatment with AZM or bacterial metabolites was assessed. RESULTS: Compared with placebo, AZM did not alter bacterial burden but reduced α-diversity, decreasing 11 low abundance taxa, none of which are classical pulmonary pathogens. Compared with placebo, AZM treatment led to reduced in-vivo levels of chemokine (C-X-C) ligand 1 (CXCL1), tumour necrosis factor (TNF)-α, interleukin (IL)-13 and IL-12p40 in BAL, but increased bacterial metabolites including glycolic acid, indol-3-acetate and linoleic acid. Glycolic acid and indol-3-acetate, but not AZM, blunted ex-vivo LPS-induced alveolar macrophage generation of CXCL1, TNF-α, IL-13 and IL-12p40. CONCLUSION: AZM treatment altered both lung microbiota and metabolome, affecting anti-inflammatory bacterial metabolites that may contribute to its therapeutic effects. TRIAL REGISTRATION NUMBER: NCT02557958.

Enrichment of the lung microbiome with oral taxa is associated with lung inflammation of a Th17 phenotype.

Microaspiration is a common phenomenon in healthy subjects, but its frequency is increased in chronic inflammatory airway diseases, and its role in inflammatory and immune phenotypes is unclear. We have previously demonstrated that acellular bronchoalveolar lavage samples from half of the healthy people examined are enriched with oral taxa (here called pneumotypeSPT) and this finding is associated with increased numbers of lymphocytes and neutrophils in bronchoalveolar lavage. Here, we have characterized the inflammatory phenotype using a multi-omic approach. By evaluating both upper airway and acellular bronchoalveolar lavage samples from 49 subjects from three cohorts without known pulmonary disease, we observed that pneumotypeSPT was associated with a distinct metabolic profile, enhanced expression of inflammatory cytokines, a pro-inflammatory phenotype characterized by elevated Th-17 lymphocytes and, conversely, a blunted alveolar macrophage TLR4 response. The cellular immune responses observed in the lower airways of humans with pneumotypeSPT indicate a role for the aspiration-derived microbiota in regulating the basal inflammatory status at the pulmonary mucosal surface.

Serum phosphatidylethanolamine levels distinguish benign from malignant solitary pulmonary nodules and represent a potential diagnostic biomarker for lung cancer.

BACKGROUND: Recent computed tomography (CT) screening trials showed that it is effective for early detection of lung cancer, but were plagued by high false positive rates. Additional blood biomarker tests designed to complement CT screening and reduce false positive rates are highly desirable. OBJECTIVE: Identify blood-based metabolite biomarkers for diagnosing lung cancer. MEHTODS: Serum samples from subjects participating in a CT screening trial were analyzed using untargeted GC-TOFMS and HILIC-qTOFMS-based metabolomics. Samples were acquired prior to diagnosis (pre-diagnostic, n= 17), at-diagnosis (n= 25) and post-diagnosis (n= 19) of lung cancer and from subjects with benign nodules (n= 29). RESULTS: Univariate analysis identified 40, 102 and 30 features which were significantly different between subjects with malignant (pre-, at- and post-diagnosis) solitary pulmonary nodules (SPNs) and benign SPNs, respectively. Ten metabolites were consistently different between subjects presenting malignant (pre- and at-diagnosis) or benign SPNs. Three of these 10 metabolites were phosphatidylethanolamines (PE) suggesting alterations in lipid metabolism. Accuracies of 77%, 83% and 78% in the pre-diagnosis group and 69%, 71% and 67% in the at-diagnosis group were determined for PE(34:2), PE(36:2) and PE(38:4), respectively. CONCLUSIONS: This study demonstrates evidence of early metabolic alterations that can possibly distinguish malignant from benign SPNs. Further studies in larger pools of samples are warranted.

Diacetylspermine Is a Novel Prediagnostic Serum Biomarker for Non-Small-Cell Lung Cancer and Has Additive Performance With Pro-Surfactant Protein B.

PURPOSE: We have investigated the potential of metabolomics to discover blood-based biomarkers relevant to lung cancer screening and early detection. An untargeted metabolomics approach was applied to identify biomarker candidates using prediagnostic sera from the Beta-Carotene and Retinol Efficacy Trial (CARET) study. PATIENTS AND METHODS: A liquid chromatography/mass spectrometry hydrophilic interaction method designed to profile a wide range of metabolites was applied to prediagnostic serum samples from CARET participants (current or former heavy smokers), consisting of 100 patients who subsequently developed non-small-cell lung cancer (NSCLC) and 199 matched controls. A separate aliquot was used to quantify levels of pro-surfactant protein B (pro-SFTPB), a previously established protein biomarker for NSCLC. On the basis of the results from the discovery set, blinded validation of a metabolite, identified as N(1),N(12)-diacetylspermine (DAS), and pro-SFTPB was performed using an independent set of CARET prediagnostic sera from 108 patients with NSCLC and 216 matched controls. RESULTS: Serum DAS was elevated by 1.9-fold, demonstrating significant specificity and sensitivity in the discovery set for samples collected up to 6 months before diagnosis of NSCLC. In addition, DAS significantly complemented performance of pro-SFTPB in both the discovery and validations sets, with a combined area under the curve in the validation set of 0.808 (P < .001 v pro-SFTPB). CONCLUSION: DAS is a novel serum metabolite with significant performance in prediagnostic NSCLC and has additive performance with pro-SFTPB.

Systemic Metabolomic Changes in Blood Samples of Lung Cancer Patients Identified by Gas Chromatography Time-of-Flight Mass Spectrometry.

Lung cancer is a leading cause of cancer deaths worldwide. Metabolic alterations in tumor cells coupled with systemic indicators of the host response to tumor development have the potential to yield blood profiles with clinical utility for diagnosis and monitoring of treatment. We report results from two separate studies using gas chromatography time-of-flight mass spectrometry (GC-TOF MS) to profile metabolites in human blood samples that significantly differ from non-small cell lung cancer (NSCLC) adenocarcinoma and other lung cancer cases. Metabolomic analysis of blood samples from the two studies yielded a total of 437 metabolites, of which 148 were identified as known compounds and 289 identified as unknown compounds. Differential analysis identified 15 known metabolites in one study and 18 in a second study that were statistically different (p-values <0.05). Levels of maltose, palmitic acid, glycerol, ethanolamine, glutamic acid, and lactic acid were increased in cancer samples while amino acids tryptophan, lysine and histidine decreased. Many of the metabolites were found to be significantly different in both studies, suggesting that metabolomics appears to be robust enough to find systemic changes from lung cancer, thus showing the potential of this type of analysis for lung cancer detection.

Metabolomic markers of altered nucleotide metabolism in early stage adenocarcinoma.

Adenocarcinoma, a type of non-small cell lung cancer, is the most frequently diagnosed lung cancer and the leading cause of lung cancer mortality in the United States. It is well documented that biochemical changes occur early in the transition from normal to cancer cells, but the extent to which these alterations affect tumorigenesis in adenocarcinoma remains largely unknown. Herein, we describe the application of mass spectrometry and multivariate statistical analysis in one of the largest biomarker research studies to date aimed at distinguishing metabolic differences between malignant and nonmalignant lung tissue. Gas chromatography time-of-flight mass spectrometry was used to measure 462 metabolites in 39 malignant and nonmalignant lung tissue pairs from current or former smokers with early stage (stage IA-IB) adenocarcinoma. Statistical mixed effects models, orthogonal partial least squares discriminant analysis and network integration, were used to identify key cancer-associated metabolic perturbations in adenocarcinoma compared with nonmalignant tissue. Cancer-associated biochemical alterations were characterized by (i) decreased glucose levels, consistent with the Warburg effect, (ii) changes in cellular redox status highlighted by elevations in cysteine and antioxidants, alpha- and gamma-tocopherol, (iii) elevations in nucleotide metabolites 5,6-dihydrouracil and xanthine suggestive of increased dihydropyrimidine dehydrogenase and xanthine oxidoreductase activity, (iv) increased 5'-deoxy-5'-methylthioadenosine levels indicative of reduced purine salvage and increased de novo purine synthesis, and (v) coordinated elevations in glutamate and UDP-N-acetylglucosamine suggesting increased protein glycosylation. The present study revealed distinct metabolic perturbations associated with early stage lung adenocarcinoma, which may provide candidate molecular targets for personalizing therapeutic interventions and treatment efficacy monitoring.

Is diabetes mellitus-linked amino acid signature associated with ß-blocker-induced impaired fasting glucose?

BACKGROUND: The 5-amino acid (AA) signature, including isoleucine, leucine, valine, tyrosine, and phenylalanine, has been associated with incident diabetes mellitus and insulin resistance. We investigated whether this same AA signature, single-nucleotide polymorphisms in genes in their catabolic pathway, was associated with development of impaired fasting glucose (IFG) after atenolol treatment. METHODS AND RESULTS: Among 234 European American participants enrolled in the Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR) study and treated with atenolol for 9 weeks, we prospectively followed a nested cohort that had both metabolomics profiling and genotype data available for the development of IFG. We assessed the association between baseline circulating levels of isoleucine, leucine, valine, tyrosine, and phenylalanine, as well as single-nucleotide polymorphisms in branched-chain amino-acid transaminase 1 (BCAT1) and phenylalanine hydroxylase (PAH) with development of IFG. All baseline AA levels were strongly associated with IFG development. Each increment in standard deviation of the 5 AAs was associated with the following odds ratio and 95% confidence interval for IFG based on a fully adjusted model: isoleucine 2.29 (1.31-4.01), leucine 1.80 (1.10-2.96), valine 1.77 (1.07-2.92), tyrosine 2.13 (1.20-3.78), and phenylalanine 2.04 (1.16-3.59). The composite P value was 2×10(-5). Those with PAH (rs2245360) AA genotype had the highest incidence of IFG (P for trend=0.0003). CONCLUSIONS: Our data provide important insight into the metabolic and genetic mechanisms underlying atenolol-associated adverse metabolic effects. Clinical Trial Registration- http://www.clinicaltrials.gov; Unique Identifier: NCT00246519.

Pharmacometabolomic signature of ataxia SCA1 mouse model and lithium effects.

We have shown that lithium treatment improves motor coordination in a spinocerebellar ataxia type 1 (SCA1) disease mouse model (Sca1(154Q/+)). To learn more about disease pathogenesis and molecular contributions to the neuroprotective effects of lithium, we investigated metabolomic profiles of cerebellar tissue and plasma from SCA1-model treated and untreated mice. Metabolomic analyses of wild-type and Sca1(154Q/+) mice, with and without lithium treatment, were performed using gas chromatography time-of-flight mass spectrometry and BinBase mass spectral annotations. We detected 416 metabolites, of which 130 were identified. We observed specific metabolic perturbations in Sca1(154Q/+) mice and major effects of lithium on metabolism, centrally and peripherally. Compared to wild-type, Sca1(154Q/+) cerebella metabolic profile revealed changes in glucose, lipids, and metabolites of the tricarboxylic acid cycle and purines. Fewer metabolic differences were noted in Sca1(154Q/+) mouse plasma versus wild-type. In both genotypes, the major lithium responses in cerebellum involved energy metabolism, purines, unsaturated free fatty acids, and aromatic and sulphur-containing amino acids. The largest metabolic difference with lithium was a 10-fold increase in ascorbate levels in wild-type cerebella (p<0.002), with lower threonate levels, a major ascorbate catabolite. In contrast, Sca1(154Q/+) mice that received lithium showed no elevated cerebellar ascorbate levels. Our data emphasize that lithium regulates a variety of metabolic pathways, including purine, oxidative stress and energy production pathways. The purine metabolite level, reduced in the Sca1(154Q/+) mice and restored upon lithium treatment, might relate to lithium neuroprotective properties.

Pharmacometabolomics reveals racial differences in response to atenolol treatment.

Antihypertensive drugs are among the most commonly prescribed drugs for chronic disease worldwide. The response to antihypertensive drugs varies substantially between individuals and important factors such as race that contribute to this heterogeneity are poorly understood. In this study we use metabolomics, a global biochemical approach to investigate biochemical changes induced by the beta-adrenergic receptor blocker atenolol in Caucasians and African Americans. Plasma from individuals treated with atenolol was collected at baseline (untreated) and after a 9 week treatment period and analyzed using a GC-TOF metabolomics platform. The metabolomic signature of atenolol exposure included saturated (palmitic), monounsaturated (oleic, palmitoleic) and polyunsaturated (arachidonic, linoleic) free fatty acids, which decreased in Caucasians after treatment but were not different in African Americans (p<0.0005, q<0.03). Similarly, the ketone body 3-hydroxybutyrate was significantly decreased in Caucasians by 33% (p<0.0001, q<0.0001) but was unchanged in African Americans. The contribution of genetic variation in genes that encode lipases to the racial differences in atenolol-induced changes in fatty acids was examined. SNP rs9652472 in LIPC was found to be associated with the change in oleic acid in Caucasians (p<0.0005) but not African Americans, whereas the PLA2G4C SNP rs7250148 associated with oleic acid change in African Americans (p<0.0001) but not Caucasians. Together, these data indicate that atenolol-induced changes in the metabolome are dependent on race and genotype. This study represents a first step of a pharmacometabolomic approach to phenotype patients with hypertension and gain mechanistic insights into racial variability in changes that occur with atenolol treatment, which may influence response to the drug.

Metabolomics reveals amino acids contribute to variation in response to simvastatin treatment.

UNLABELLED: Statins are widely prescribed for reducing LDL-cholesterol (C) and risk for cardiovascular disease (CVD), but there is considerable variation in therapeutic response. We used a gas chromatography-time-of-flight mass-spectrometry-based metabolomics platform to evaluate global effects of simvastatin on intermediary metabolism. Analyses were conducted in 148 participants in the Cholesterol and Pharmacogenetics study who were profiled pre and six weeks post treatment with 40 mg/day simvastatin: 100 randomly selected from the full range of the LDL-C response distribution and 24 each from the top and bottom 10% of this distribution ("good" and "poor" responders, respectively). The metabolic signature of drug exposure in the full range of responders included essential amino acids, lauric acid (p<0.0055, q<0.055), and alpha-tocopherol (p<0.0003, q<0.017). Using the HumanCyc database and pathway enrichment analysis, we observed that the metabolites of drug exposure were enriched for the pathway class amino acid degradation (p<0.0032). Metabolites whose change correlated with LDL-C lowering response to simvastatin in the full range responders included cystine, urea cycle intermediates, and the dibasic amino acids ornithine, citrulline and lysine. These dibasic amino acids share plasma membrane transporters with arginine, the rate-limiting substrate for nitric oxide synthase (NOS), a critical mediator of cardiovascular health. Baseline metabolic profiles of the good and poor responders were analyzed by orthogonal partial least square discriminant analysis so as to determine the metabolites that best separated the two response groups and could be predictive of LDL-C response. Among these were xanthine, 2-hydroxyvaleric acid, succinic acid, stearic acid, and fructose. Together, the findings from this study indicate that clusters of metabolites involved in multiple pathways not directly connected with cholesterol metabolism may play a role in modulating the response to simvastatin treatment. TRIAL REGISTRATION: ClinicalTrials.gov NCT00451828.

Identification of naturally occurring fatty acids of the myelin sheath that resolve neuroinflammation.

Lipids constitute 70% of the myelin sheath, and autoantibodies against lipids may contribute to the demyelination that characterizes multiple sclerosis (MS). We used lipid antigen microarrays and lipid mass spectrometry to identify bona fide lipid targets of the autoimmune response in MS brain, and an animal model of MS to explore the role of the identified lipids in autoimmune demyelination. We found that autoantibodies in MS target a phosphate group in phosphatidylserine and oxidized phosphatidylcholine derivatives. Administration of these lipids ameliorated experimental autoimmune encephalomyelitis by suppressing activation and inducing apoptosis of autoreactive T cells, effects mediated by the lipids' saturated fatty acid side chains. Thus, phospholipids represent a natural anti-inflammatory class of compounds that have potential as therapeutics for MS.

Untargeted metabolomics identifies enterobiome metabolites and putative uremic toxins as substrates of organic anion transporter 1 (Oat1).

Untargeted metabolomics on the plasma and urine from wild-type and organic anion transporter-1 (Oat1/Slc22a6) knockout mice identified a number of physiologically important metabolites, including several not previously linked to Oat1-mediated transport. Several, such as indoxyl sulfate, derive from Phase II metabolism of enteric gut precursors and accumulate in chronic kidney disease (CKD). Other compounds included vitamins (pantothenic acid, 4-pyridoxic acid), urate, and metabolites in the tryptophan and nucleoside pathways. Three metabolites, indoxyl sulfate, kynurenine, and xanthurenic acid, were elevated in the plasma and interacted strongly and directly with Oat1 in vitro with IC50 of 18, 12, and 50 µM, respectively. A pharmacophore model based on several identified Oat1 substrates was used to screen the NCI database and candidate compounds interacting with Oat1 were validated in an in vitro assay. Together, the data suggest a complex, previously unidentified remote communication between the gut microbiome, Phase II metabolism in the liver, and elimination via Oats of the kidney, as well as indicating the importance of Oat1 in the handling of endogenous toxins associated with renal failure and uremia. The possibility that some of the compounds identified may be part of a larger remote sensing and signaling pathway is also discussed.

Variability analysis of human plasma and cerebral spinal fluid reveals statistical significance of changes in mass spectrometry-based metabolomics data.

Analytical and biological variability are issues of central importance to human metabolomics studies. Here both types of variation are examined in human plasma and cerebrospinal fluid (CSF) using a global liquid chromatography/mass spectrometry (LC/MS) metabolomics strategy. The platform shows small analytical variation with a median coefficient of variation (CV) of 15-16% for both plasma and CSF sample matrixes when the integrated area of each peak in the mass spectra is considered. Analysis of biological variation shows that human CSF has a median CV of 35% and plasma has a median CV of 46%. To understand the difference in CV between the biofluids, we compared plasma and CSF independently obtained from different healthy humans. Additionally, we analyzed another group of patients from whom we compared matched CSF and plasma (plasma and CSF obtained from the same human subject). A similar number of features was observed in both biofluids, although the majority of features appeared with greater intensity in plasma. More than a dozen metabolites shared between the human CSF and plasma metabolomes were identified based on accurate mass measurements, retention times, and MS/MS spectra. The fold change in these metabolites was consistent with the median biological CV determined for all peaks. The measured median biological CV together with analysis of intragroup variation of healthy individuals suggests that fold changes above 2 in metabolomics studies investigating plasma or CSF are statistically relevant with respect to the inherent variability of a healthy control group. These data demonstrate the reproducibility of the global metabolomics platform using LC/MS and reveal the robustness of the approach for biomarker discovery.

Response and recovery in the plasma metabolome tracks the acute LCMV-induced immune response.

Lymphocytic choriomeningitis virus (LCMV) infection of mice is noncytopathic, producing well-characterized changes reflecting the host immune response. Untargeted metabolomics using mass spectrometry identified endogenous small molecule changes in blood from mice inoculated with LCMV, sampled at days 1, 3, 7, and 14 post infection. These time points correspond to well characterized events during acute LCMV infection and the immune response. Diverse pathways were altered, including TCA cycle intermediates, gamma-glutamyl dipeptides, lysophosphatidyl cholines, and fatty acids. The kynurenine pathway was activated, surprising because it is stimulated by IFN-gamma, which LCMV suppresses, thus, suggesting alternative activators. In contrast, biopterin/neopterin, another IFN-gamma stimulated pathway, was not activated. Many metabolites followed "response and recovery" kinetics, decreasing after infection to a minimum at days 3-7, and returning to normal by day 14. The TCA pathway followed this pattern, including citrate, cis-aconitate and alpha-ketoglutarate, intriguing because succinate has been shown to mediate cellular immunity. This response and recovery dynamic tracks the immune response, including the rise and fall of natural killer cell populations, serum TNF receptor concentration, and viral clearance. Metabolomics can provide target pathways for molecular diagnostics or therapeutics of viral infection and immunity.

Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites.

Although it has long been recognized that the enteric community of bacteria that inhabit the human distal intestinal track broadly impacts human health, the biochemical details that underlie these effects remain largely undefined. Here, we report a broad MS-based metabolomics study that demonstrates a surprisingly large effect of the gut "microbiome" on mammalian blood metabolites. Plasma extracts from germ-free mice were compared with samples from conventional (conv) animals by using various MS-based methods. Hundreds of features were detected in only 1 sample set, with the majority of these being unique to the conv animals, whereas approximately 10% of all features observed in both sample sets showed significant changes in their relative signal intensity. Amino acid metabolites were particularly affected. For example, the bacterial-mediated production of bioactive indole-containing metabolites derived from tryptophan such as indoxyl sulfate and the antioxidant indole-3-propionic acid (IPA) was impacted. Production of IPA was shown to be completely dependent on the presence of gut microflora and could be established by colonization with the bacterium Clostridium sporogenes. Multiple organic acids containing phenyl groups were also greatly increased in the presence of gut microbes. A broad, drug-like phase II metabolic response of the host to metabolites generated by the microbiome was observed, suggesting that the gut microflora has a direct impact on the drug metabolism capacity of the host. Together, these results suggest a significant interplay between bacterial and mammalian metabolism.

Novel multiprotein complexes identified in the hyperthermophilic archaeon Pyrococcus furiosus by non-denaturing fractionation of the native proteome.

Virtually all cellular processes are carried out by dynamic molecular assemblies or multiprotein complexes, the compositions of which are largely undefined. They cannot be predicted solely from bioinformatics analyses nor are there well defined techniques currently available to unequivocally identify protein complexes (PCs). To address this issue, we attempted to directly determine the identity of PCs from native microbial biomass using Pyrococcus furiosus, a hyperthermophilic archaeon that grows optimally at 100 degrees C, as the model organism. Novel PCs were identified by large scale fractionation of the native proteome using non-denaturing, sequential column chromatography under anaerobic, reducing conditions. A total of 967 distinct P. furiosus proteins were identified by mass spectrometry (nano LC-ESI-MS/MS), representing approximately 80% of the cytoplasmic proteins. Based on the co-fractionation of proteins that are encoded by adjacent genes on the chromosome, 106 potential heteromeric PCs containing 243 proteins were identified, only 20 of which were known or expected. In addition to those of unknown function, novel and uncharacterized PCs were identified that are proposed to be involved in the metabolism of amino acids (10), carbohydrates (four), lipids (two), vitamins and metals (three), and DNA and RNA (nine). A further 30 potential PCs were classified as tentative, and the remaining potential PCs (13) were classified as weakly interacting. Some major advantages of native biomass fractionation for PC identification are that it provides a road map for the (partial) purification of native forms of novel and uncharacterized PCs, and the results can be utilized for the recombinant production of low abundance PCs to provide enough material for detailed structural and biochemical analyses.

Metabolomic analysis of the cerebrospinal fluid reveals changes in phospholipase expression in the CNS of SIV-infected macaques.

HIV infiltrates the CNS soon after an individual has become infected with the virus, and can cause dementia and encephalitis in late-stage disease. Here, a global metabolomics approach was used to find and identify metabolites differentially regulated in the cerebrospinal fluid (CSF) of rhesus macaques with SIV-induced CNS disease, as we hypothesized that this might provide biomarkers of virus-induced CNS damage. The screening platform used a non-targeted, mass-based metabolomics approach beginning with capillary reverse phase chromatography and electrospray ionization with accurate mass determination, followed by novel, nonlinear data alignment and online database screening to identify metabolites. CSF was compared before and after viral infection. Significant changes in the metabolome specific to SIV-induced encephalitis were observed. Metabolites that were increased during infection-induced encephalitis included carnitine, acyl-carnitines, fatty acids, and phospholipid molecules. The elevation in free fatty acids and lysophospholipids correlated with increased expression of specific phospholipases in the brains of animals with encephalitis. One of these, a phospholipase A2 isoenzyme, is capable of releasing a number of the fatty acids identified. It was expressed in different areas of the brain in conjunction with glial activation, rather than linked to regions of SIV infection and inflammation, indicating widespread alterations in infected brains. The identification of specific metabolites as well as mechanisms of their increase illustrates the potential of mass-based metabolomics to address problems in CNS biochemistry and neurovirology, as well as neurodegenerative diseases.

Organic anion transporter 3 contributes to the regulation of blood pressure.

Renal organic anion transporters (OAT) are known to mediate the excretion of many drugs, but their function in normal physiology is not well understood. In this study, mice lacking organic anion transporter 3 (Oat3) had a 10 to 15% lower BP than wild-type mice, raising the possibility that Oat3 transports an endogenous regulator of BP. The aldosterone response to a low-salt diet was blunted in Oat3-null mice, but baseline aldosterone concentration was higher in these mice, suggesting that aldosterone dysregulation does not fully explain the lower BP in the basal state; therefore, both targeted and global metabolomic analyses of plasma and urine were performed, and several potential endogenous substrates of Oat3 were found to accumulate in the plasma of Oat3-null mice. One of these substrates, thymidine, was transported by Oat3 expressed in vitro. In vivo, thymidine, as well as two of the most potent Oat3 inhibitors that were characterized, reduced BP by 10 to 15%; therefore, Oat3 seems to regulate BP, and Oat3 inhibitors might be therapeutically useful antihypertensive agents. Moreover, polymorphisms in human OAT3 might contribute to the genetic variation in susceptibility to hypertension.

Multiple organic anion transporters contribute to net renal excretion of uric acid.

Excretion of uric acid, a compound of considerable medical importance, is largely determined by the balance between renal secretion and reabsorption. The latter process has been suggested to be principally mediated by urate transporter 1 (URAT1; slc22a12), but the role of various putative urate transporters has been much debated. We have characterized urate handling in mice null for RST, the murine ortholog of URAT1, as well as in those null for the related organic anion transporters Oat1 and Oat3. Expression of mRNA of other putative urate transporters (UAT, MRP2, MRP4, Oatv1) was unaffected in the knockouts, as were general indexes of renal function (glomerular filtration rate, fractional excretion of fluid and electrolytes). While mass spectrometric analyses of urine and plasma revealed significantly diminished renal reabsorption of urate in RST-null mice, the bulk of reabsorption, surprisingly, was preserved. Oat1- and Oat3-null mice manifested decreased secretion rather than reabsorption, indicating that these related transporters transport urate in the "opposite" direction to RST. Moreover, metabolomic analyses revealed significant alteration in the concentration of several molecules in the plasma and urine of RST knockouts, some of which may represent additional substrates of RST. The results suggest that RST, Oat1, and Oat3 each contribute to urate handling, but, at least in mice, the bulk of reabsorption is mediated by a transporter(s) that remains to be identified. We discuss the data in the context of recent human genetic studies that suggest that the magnitude of the contribution of URAT1 to urate reabsorption might vary with ethnic background.

Metabolomics identifies perturbations in human disorders of propionate metabolism.

BACKGROUND: We applied untargeted mass spectrometry-based metabolomics to the diseases methylmalonic acidemia (MMA) and propionic acidemia (PA). METHODS: We used a screening platform that used untargeted, mass-based metabolomics of methanol-extracted plasma to find significantly different molecular features in human plasma samples from MMA and PA patients and from healthy individuals. Capillary reverse phase liquid chromatography (4 microL/min) was interfaced to a TOF mass spectrometer, and data were processed using nonlinear alignment software (XCMS) and an online database (METLIN) to find and identify metabolites differentially regulated in disease. RESULTS: Of the approximately 3500 features measured, propionyl carnitine was easily identified as the best biomarker of disease (P value 1.3 x 10(-18)), demonstrating the proof-of-concept use of untargeted metabolomics in clinical chemistry discovery. Five additional acylcarnitine metabolites showed significant differentiation between plasma from patients and healthy individuals, and gamma-butyrobetaine was highly increased in a subset of patients. Two acylcarnitine metabolites and numerous unidentified species differentiate MMA and PA. Many metabolites that do not appear in any public database, and that remain unidentified, varied significantly between normal, MMA, and PA, underscoring the complex downstream metabolic effects resulting from the defect in a single enzyme. CONCLUSIONS: This proof-of-concept study demonstrates that metabolomics can expand the range of metabolites associated with human disease and shows that this method may be useful for disease diagnosis and patient clinical evaluation.