Organization of GC/MS and LC/MS metabolomics data into chemical libraries

Machine Vision Methods, Natural Language Processing, and Machine Learning Algorithms for Automated Dispersion Plot Analysis and Chemical Identification from Complex Mixtures

Gas-phase trace chemical detection techniques such as ion mobility spectrometry (IMS) and differential mobility spectrometry (DMS) can be used in many settings, such as evaluating the health condition of patients or detecting explosives at airports. These devices separate chemical compounds in a mixture and provide information to identify specific chemical species of interest. Further, these types of devices operate well in both controlled lab environments and in-field applications. Frequently, the commercial versions of these devices are highly tailored for niche applications (e.g., explosives detection) because of the difficulty involved in reconfiguring instrumentation hardware and data analysis software algorithms. In order for researchers to quickly adapt these tools for new purposes and broader panels of chemical targets, it is critical to develop new algorithms and methods for generating libraries of these sensor responses. Microelectromechanical system (MEMS) technology has been used to fabricate DMS devices that miniaturize the platforms for easier deployment; however, concurrent advances in advanced data analytics are lagging. DMS generates complex three-dimensional dispersion plots for both positive and negative ions in a mixture. Although simple spectra of single chemicals are straightforward to interpret (both visually and via algorithms), it is exceedingly challenging to interpret dispersion plots from complex mixtures with many chemical constituents. This study uses image processing and computer vision steps to automatically identify features from DMS dispersion plots. We used the bag-of-words approach adapted from natural language processing and information retrieval to cluster and organize these features. Finally, a support vector machine (SVM) learning algorithm was trained using these features in order to detect and classify specific compounds in these represented conceptualized data outputs. Using this approach, we successfully maintain a high level of correct chemical identification, even when a gas mixture increases in complexity with interfering chemicals present.

Metabolic adaptation of short-living growth hormone transgenic mice to methionine restriction and supplementation

Extension of mammalian health and life span has been achieved using various dietary interventions. We previously reported that restricting dietary methionine (MET) content extends life span only when growth hormone signaling is intact (no life span increase in GH deficiency or GH resistance). To understand the metabolic responses of altered dietary MET in the context of accelerated aging (high GH), the current study evaluated MET and related pathways in short-living GH transgenic (GH Tg) and wild-type mice following 8 weeks of restricted (0.16%), low (0.43%), or enriched (1.3%) MET consumption. Liver MET metabolic enzymes were suppressed in GH Tg compared to diet-matched wild-type mice. MET metabolite levels were differentially affected by GH status and diet. SAM:SAH ratios were markedly higher in GH Tg mice. Glutathione levels were lower in both genotypes consuming 0.16% MET but reduced in GH Tg mice when compared to wild type. Tissue thioredoxin and glutaredoxin were impacted by diet and GH status. The responsiveness to the different MET diets is reflected across many metabolic pathways indicating the importance of GH signaling in the ability to discriminate dietary amino acid levels and alter metabolism and life span.

Breast cancer risk in relation to plasma metabolites among Hispanic and African American women

PURPOSE

The metabolic etiology of breast cancer has been explored in the past several years using metabolomics. However, most of these studies only included non-Hispanic White individuals.

METHODS

To fill this gap, we performed a two-step (discovery and validation) metabolomics profiling in plasma samples from 358 breast cancer patients and 138 healthy controls. All study subjects were either Hispanics or non-Hispanic African Americans.

RESULTS

A panel of 14 identified metabolites significantly differed between breast cancer cases and healthy controls in both the discovery and validation sets. Most of these identified metabolites were lipids. In the pathway analysis, citrate cycle (TCA cycle), arginine and proline metabolism, and linoleic acid metabolism pathways were observed, and they significantly differed between breast cancer cases and healthy controls in both sets. From those 14 metabolites, we selected 9 non-correlated metabolites to generate a metabolic risk score. Increased metabolites risk score was associated with a 1.87- and 1.63-fold increased risk of breast cancer in the discovery and validation sets, respectively (Odds ratio (OR) 1.87, 95% Confidence interval (CI) 1.50, 2.32; OR 1.63, 95% CI 1.36, 1.95).

CONCLUSIONS

In summary, our study identified metabolic profiles and pathways that significantly differed between breast cancer cases and healthy controls in Hispanic or non-Hispanic African American women. The results from our study might provide new insights on the metabolic etiology of breast cancer.

Deleterious mutations in ALDH1L2 suggest a novel cause for neuro-ichthyotic syndrome

Neuro-ichthyotic syndromes are a group of rare genetic diseases mainly associated with perturbations in lipid metabolism, intracellular vesicle trafficking, or glycoprotein synthesis. Here, we report a patient with a neuro-ichthyotic syndrome associated with deleterious mutations in the ALDH1L2 (aldehyde dehydrogenase 1 family member L2) gene encoding for mitochondrial 10-formyltetrahydrofolate dehydrogenase. Using fibroblast culture established from the ALDH1L2-deficient patient, we demonstrated that the enzyme loss impaired mitochondrial function affecting both mitochondrial morphology and the pool of metabolites relevant to β-oxidation of fatty acids. Cells lacking the enzyme had distorted mitochondria, accumulated acylcarnitine derivatives and Krebs cycle intermediates, and had lower ATP and increased ADP/AMP indicative of a low energy index. Re-expression of functional ALDH1L2 enzyme in deficient cells restored the mitochondrial morphology and the metabolic profile of fibroblasts from healthy individuals. Our study underscores the role of ALDH1L2 in the maintenance of mitochondrial integrity and energy balance of the cell, and suggests the loss of the enzyme as the cause of neuro-cutaneous disease.

Pharmacometabolomic Pathway Response of Effective Anticancer Agents on Different Diets in Rats with Induced Mammary Tumors

Metabolomics is an effective approach to characterize the metabotype which can reflect the influence of genetics, physiological status, and environmental factors such as drug intakes, diet. Diet may change the chemopreventive efficacy of given agents due to the altered physiological status of the subject. Here, metabolomics response to a chemopreventive agent targretin or tamoxifen, in rats with methylnitrosourea-induced tumors on a standard diet (4% fat, CD) or a high fat diet (21% fat, HFD) was evaluated, and found that (1) the metabolome was substantially affected by diet and/or drug treatment; (2) multiple metabolites were identified as potential pharmacodynamic biomarkers related to targretin or tamoxifen regardless of diet and time; and (3) the primary bile acid pathway was significantly affected by targretin treatment in rats on both diets, and the lysolipid pathway was significantly affected by tamoxifen treatment in rats on the high fat diet.

Time of Exercise Specifies the Impact on Muscle Metabolic Pathways and Systemic Energy Homeostasis

While the timing of food intake is important, it is unclear whether the effects of exercise on energy metabolism are restricted to unique time windows. As circadian regulation is key to controlling metabolism, understanding the impact of exercise performed at different times of the day is relevant for physiology and homeostasis. Using high-throughput transcriptomic and metabolomic approaches, we identify distinct responses of metabolic oscillations that characterize exercise in either the early rest phase or the early active phase in mice. Notably, glycolytic activation is specific to exercise at the active phase. At the molecular level, HIF1α, a central regulator of glycolysis during hypoxia, is selectively activated in a time-dependent manner upon exercise, resulting in carbohydrate exhaustion, usage of alternative energy sources, and adaptation of systemic energy expenditure. Our findings demonstrate that the time of day is a critical factor to amplify the beneficial impact of exercise on both metabolic pathways within skeletal muscle and systemic energy homeostasis.

Caloric Restriction Alters Postprandial Responses of Essential Brain Metabolites in Young Adult Mice

Caloric restriction (CR) has been shown to extend longevity and protect brain function in aging. However, the effects of CR in young adult mice remain largely unexplored. In addition to the fundamental, long-term changes, recent studies demonstrate that CR has a significant impact on transient, postprandial metabolic flexibility and turnover compared to control groups. The goal of this study was to identify the brain metabolic changes at a transient (2 h) and steady (6 h) postprandial state in young mice (5–6 months of age) fed with CR or ad libitum (AL; free eating). Using metabolomics profiling, we show that CR mice had significantly higher levels of neurotransmitters (e.g., glutamate, N-acetylglutamate), neuronal integrity markers (e.g., NAA and NAAG), essential fatty acids (e.g., DHA and DPA), and biochemicals associated carnitine metabolism (related to reduced oxidative stress and inflammation) in the cerebral cortex and hippocampus at 2-h. These biochemicals remained at high levels at the 6-h postprandial time-point. The AL mice did not show the similar increases in essential fatty acid and carnitine metabolism until the 6-h time-point, and failed to show increases in neurotransmitters and neuronal integrity markers at any time-point. On the other hand, metabolites related to glucose utilization—glycolysis and pentose phosphate pathway (PPP)—were low in the CR mice throughout the 6-h period and significantly increased at the 6-h time-point in the AL mice. Our findings suggest that CR induces distinct postprandial responses in metabolites that are essential to maintain brain functions. CR mice produced higher levels of essential brain metabolites in a shorter period after a meal and sustained the levels for an extended period, while maintaining a lower level of glucose utilization. These early brain metabolism changes in the CR mice might play a critical role for neuroprotection in aging. Understanding the interplay between dietary intervention and postprandial metabolic responses from an early age may have profound implications for impeding brain aging and reducing risk for neurodegenerative disorders.

Metabolomics signature associated with circulating serum selenoprotein P levels

PURPOSE

Selenoprotein P (SELENOP) has been previously related to various metabolic traits with partially conflicting results. The identification of SELENOP-associated metabolites, using an untargeted metabolomics approach, may provide novel biological insights relevant to disentangle the role of SELENOP in human health.

METHODS

In this cross-sectional study, 572 serum metabolites were identified by comparing the obtained LC-MS/MS spectra with spectra stored in Metabolon's spectra library. Serum SELENOP levels were measured in 832 men and women using an ELISA kit.

RESULTS

Circulating SELENOP levels were associated with 24 out of 572 metabolites after accounting for the number of independent dimensions in the metabolomics data, including inverse associations with alanine, glutamate, leucine, isoleucine and valine, an unknown compound X-12063, urate and the peptides gamma-glutamyl-leucine, and N-acetylcarnosine. Positive associations were observed between SELENOP and several lipid compounds. Of the identified metabolites, each standard deviation increase in the branched-chain amino acids (isoleucine, leucine, valine), alanine and gamma-glutamyl-leucine was related to higher odds of having T2DM [OR (95% CI): 1.96 (1.41-2.73); 1.62 (1.15-2.28); 1.94 (1.45-2.60), 1.57 (1.17-2.11), and 1.52 (1.13-2.05), respectively].

CONCLUSIONS

Higher serum SELENOP levels were associated with an overall healthy metabolomics profile, which may provide further insights into potential mechanisms of SELENOP-associated metabolic disorders.

De novo missense variant in the GTPase effector domain (GED) of DNM1L leads to static encephalopathy and seizures

DNM1L encodes a GTPase of the dynamin superfamily, which plays a crucial role in mitochondrial and peroxisomal fission. Pathogenic variants affecting the middle domain and the GTPase domain of DNM1L have been implicated in encephalopathy because of defective mitochondrial and peroxisomal fission 1 (EMPF1, MIM #614388). Patients show variable phenotypes ranging from severe hypotonia leading to death in the neonatal period to developmental delay/regression, with or without seizures. Familial pathogenic variants in the GTPase domain have also been associated with isolated optic atrophy. We present a 27-yr-old woman with static encephalopathy, a history of seizures, and nystagmus, in whom a novel de novo heterozygous variant was detected in the GTPase effector domain (GED) of DNM1L (c.2072A>G, p.Tyr691Cys). Functional studies in Drosophila demonstrate large, abnormally distributed peroxisomes and mitochondria, an effect very similar to that of middle domain missense alleles observed in pediatric subjects with EMPF1. To our knowledge, not only is this the first report of a disease-causing variant in the GED domain in humans, but this is also the oldest living individual reported with EMPF1. Longitudinal data of this kind helps to expand our knowledge of the natural history of a growing list of DNM1L-related disorders.

Association of breast and gut microbiota dysbiosis and the risk of breast cancer: a case-control clinical study

BACKGROUND

Breast cancer ranks first in women, and is the second cause of death in this gender. In addition to genetics, the environment contributes to the development of the disease, although the factors involved are not well known. Among the latter is the influence of microorganisms and, therefore, attention is recently being paid to the mammary microbiota. We hypothesize that the risk of breast cancer could be associated with the composition and functionality of the mammary/gut microbiota, and that exposure to environmental contaminants (endocrine disruptors, EDCs) might contribute to alter these microbiota.

METHODS

We describe a case-control clinical study that will be performed in women between 25 and 70 years of age. Cases will be women diagnosed and surgically intervened of breast cancer (stages I and II). Women with antecedents of cancer or advanced tumor stage (metastasis), or who have received antibiotic treatment within a period of 3 months prior to recruitment, or any neoadjuvant therapy, will be excluded. Controls will be women surgically intervened of breast augmentation or reduction. Women with oncological, gynecological or endocrine history, and those who have received antibiotic treatment within a period of 3 months prior to recruitment will also be excluded. Blood, urine, breast tissue and stool samples will be collected. Data regarding anthropometric, sociodemographic, reproductive history, tumor features and dietary habits will be gathered. Metabolomic studies will be carried out in stool and breast tissue samples. Metagenomic studies will also be performed in stool and breast tissue samples to ascertain the viral, fungal, bacterial and archaea populations of the microbiota. Quantitation of estrogens, estrogen metabolites and EDCs in samples of serum, urine and breast tissue will also be performed.

DISCUSSION

This is the first time that the contribution of bacteria, archaea, viruses and fungi together with their alteration by environmental contaminants to the risk of breast cancer will be evaluated in the same study. Results obtained could contribute to elucidate risk factors, improve the prognosis, as well as to propose novel intervention studies in this disease.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03885648 , 03/25/2019. Retrospectively registered.

2-Pyrrolidinone and Succinimide as Clinical Screening Biomarkers for GABA-Transaminase Deficiency: Anti-seizure Medications Impact Accurate Diagnosis

Broad-scale untargeted biochemical phenotyping is a technology that supplements widely accepted assays, such as organic acid, amino acid, and acylcarnitine analyses typically utilized for the diagnosis of inborn errors of metabolism. In this study, we investigate the analyte changes associated with 4-aminobutyrate aminotransferase (ABAT, GABA transaminase) deficiency and treatments that affect GABA metabolism. GABA-transaminase deficiency is a rare neurodevelopmental and neurometabolic disorder caused by mutations in ABAT and resulting in accumulation of GABA in the cerebrospinal fluid (CSF). For that reason, measurement of GABA in CSF is currently the primary approach to diagnosis. GABA-transaminase deficiency results in severe developmental delay with intellectual disability, seizures, and movement disorder, and is often associated with death in childhood. Using an untargeted metabolomics platform, we analyzed EDTA plasma, urine, and CSF specimens from four individuals with GABA-transaminase deficiency to identify biomarkers by comparing the biochemical profile of individual patient samples to a pediatric-centric population cohort. Metabolomic analyses of over 1,000 clinical plasma samples revealed a rich source of biochemical information. Three out of four patients showed significantly elevated levels of the molecule 2-pyrrolidinone (Z-score ≥2) in plasma, and whole exome sequencing revealed variants of uncertain significance in ABAT. Additionally, these same patients also had elevated levels of succinimide in plasma, urine, and CSF and/or homocarnosine in urine and CSF. In the analysis of clinical EDTA plasma samples, the levels of succinimide and 2-pyrrolidinone showed a high level of correlation (R = 0.73), indicating impairment in GABA metabolism and further supporting the association with GABA-transaminase deficiency and the pathogenicity of the ABAT variants. Further analysis of metabolomic data across our patient population revealed the association of elevated levels of 2-pyrrolidinone with administration of vigabatrin, a commonly used anti-seizure medication and a known inhibitor of GABA-transaminase. These data indicate that anti-seizure medications may alter the biochemical and metabolomic data, potentially impacting the interpretation and diagnosis for the patient. Further, these data demonstrate the power of combining broad scale genotyping and phenotyping technologies to diagnose inherited neurometabolic disorders and support the use of metabolic phenotyping of plasma to screen for GABA-transaminase deficiency.

Plasma serotonin levels are associated with antidepressant response to SSRIs

BACKGROUND

Less than half of patients with major depressive disorder (MDD) respond to their first antidepressant trial. Our understanding of the underlying mechanisms of selective serotonin reuptake inhibitors (SSRIs) remains poor, and there is no reliable method of predicting treatment response.

METHODS

Thirty-seven MDD subjects and 41 healthy controls, somatically healthy and medication-free for at least six weeks, were recruited, and plasma serotonin (5-HT) levels were assessed at baseline. Twenty-six of the MDD subjects were then treated in an open-label manner with clinically appropriate doses of sertraline for 8 weeks, after which plasma 5-HT levels were again assessed. Response to treatment was defined as an improvement of 50% or more on the Hamilton Depression Rating Scale.

RESULTS

Non-responders to sertraline treatment had significantly lower pre-treatment 5-HT levels compared to both healthy controls and responders (F = 4.4, p = 0.004 and p = 0.036, respectively). There was a significant decrease in 5-HT levels over treatment in all MDD subjects (t = 6.2, p = 0.000003). The decrease was significantly more prominent in responders compared to non-responders (t = 2.1, p = 0.047). There was no significant difference in post-treatment 5-HT levels between responders and non-responders.

LIMITATIONS

The study had a modest sample size. 5-HT levels in plasma may not reflect 5-HT levels in the brain.

CONCLUSIONS

The results indicate that SSRI response may be facilitated by adequate baseline plasma 5-HT content and that successful SSRI treatment is associated with greater decreases in circulating 5-HT. Plasma 5-HT content may be a predictor of SSRI treatment outcome. Potential underlying mechanisms are discussed.

Alcohol-induced changes in the gut microbiome and metabolome of rhesus macaques

RATIONALE

Increasing evidence has demonstrated that changes in the gut microbiome, including those associated with dietary influences, are associated with alterations in many physiological processes. Alcohol consumption is common across human cultures and is likely to have a major effect on the gut microbiome, but there remains a paucity of information on its effects in primates.

OBJECTIVES

The effects of chronic alcohol consumption on the primate gut microbiome and metabolome were studied in rhesus macaques that were freely drinking alcohol. The objectives of the study were to determine what changes occurred in the gut microbiome following long-term exposure to alcohol and if these changes were reversible following a period of abstinence.

METHODS

Animals consuming alcohol were compared to age-matched controls without access to alcohol and were studied before and after a period of abstinence. Fecal samples from rhesus macaques were used for 16S rRNA sequencing to profile the gut microbiome and for metabolomic profiling using mass spectrometry.

RESULTS

Alcohol consumption resulted in a loss of alpha-diversity in rhesus macaques, though this was partially ameliorated by a period of abstinence. Higher levels of Firmicutes were observed in alcohol-drinking animals at the expense of a number of other microbial taxa, again normalizing in part with a period of abstinence. Metabolomic changes were primarily associated with differences in glycolysis when animals were consuming alcohol and differences in fatty acids when alcohol-drinking animals became abstinent.

CONCLUSIONS

The consumption of alcohol has specific effects on the microbiome and metabolome of rhesus macaques independent of secondary influences. Many of these changes are reversed by a relatively short period of abstinence.

Metabolite Changes in Maternal and Fetal Plasma Following Spontaneous Labour at Term in Humans Using Untargeted Metabolomics Analysis: A Pilot Study

The mechanism of human labour remains poorly understood, limiting our ability to manage complications of parturition such as preterm labour and induction of labour. In this study we have investigated the effect of labour on plasma metabolites immediately following delivery, comparing cord and maternal plasma taken from women who laboured spontaneously and delivered vaginally with women who were delivered via elective caesarean section and did not labour. Samples were analysed using ultra high-performance liquid chromatography-tandem mass spectrometry. Welch’s two-sample t-test was used to identify any significant differences. Of 826 metabolites measured, 26.9% (222/826) were significantly altered in maternal plasma and 21.1% (174/826) in cord plasma. Labour involves changes in many maternal organs and poses acute metabolic demands in the uterus and in the fetus and these are reflected in our results. While a proportion of these differences are likely to be secondary to the physiological demands of labour itself, these results present a comprehensive picture of the metabolome in the maternal and fetal circulations at the time of delivery and can be used to guide future studies. We discuss potential causal pathways for labour including endocannabinoids, ceramides, sphingolipids and steroids. Further work is necessary to confirm the specific pathways involved in the spontaneous onset of labour.

Comparison of the microbiome, metabolome, and lipidome of obese and non-obese horses

Metabolic diseases such as obesity and type 2 diabetes in humans have been linked to alterations in the gastrointestinal microbiota and metabolome. Knowledge of these associations has improved our understanding of the pathophysiology of these diseases and guided development of diagnostic biomarkers and therapeutic interventions. The cellular and molecular pathophysiology of equine metabolic syndrome (EMS) and obesity in horses, however, remain ill-defined. Thus, the objectives of this study were to characterize the fecal microbiome, fecal metabolome, and circulating lipidome in obese and non-obese horses. The fecal microbiota, fecal metabolome, and serum lipidome were evaluated in obese (case) horses (n = 20) and non-obese (control) horses (n = 20) matched by farm of origin (n = 7). Significant differences in metabolites of the mitochondrial tricarboxylic acid cycle and circulating free fatty acids were identified in the obese horses compared to the non-obese horses. These results indicate that the host and bacterial metabolism should be considered important in obese horses. Further studies to determine whether these associations are causal and the mechanistic basis of the association are warranted because they might reveal diagnostic biomarkers and therapeutic interventions to mitigate obesity, EMS, and sequelae including laminitis.

Mechanistic identification of biofluid metabolite changes as markers of acetaminophen-induced liver toxicity in rats

Acetaminophen (APAP) is the most commonly used analgesic and antipyretic drug in the world. Yet, it poses a major risk of liver injury when taken in excess of the therapeutic dose. Current clinical markers do not detect the early onset of liver injury associated with excess APAP-information that is vital to reverse injury progression through available therapeutic interventions. Hence, several studies have used transcriptomics, proteomics, and metabolomics technologies, both independently and in combination, in an attempt to discover potential early markers of liver injury. However, the casual relationship between these observations and their relation to the APAP mechanism of liver toxicity are not clearly understood. Here, we used Sprague-Dawley rats orally gavaged with a single dose of 2 g/kg of APAP to collect tissue samples from the liver and kidney for transcriptomic analysis and plasma and urine samples for metabolomic analysis. We developed and used a multi-tissue, metabolism-based modeling approach to integrate these data, characterize the effect of excess APAP levels on liver metabolism, and identify a panel of plasma and urine metabolites that are associated with APAP-induced liver toxicity. Our analyses, which indicated that pathways involved in nucleotide-, lipid-, and amino acid-related metabolism in the liver were most strongly affected within 10 h following APAP treatment, identified a list of potential metabolites in these pathways that could serve as plausible markers of APAP-induced liver injury. Our approach identifies toxicant-induced changes in endogenous metabolism, is applicable to other toxicants based on transcriptomic data, and provides a mechanistic framework for interpreting metabolite alterations.

Metabolic and proteomic signatures of hypoglycaemia in type 2 diabetes

AIMS

To determine the biochemical changes that underlie hypoglycaemia in a healthy control group and in people with type 2 diabetes (T2D).

MATERIALS AND METHODS

We report a hypoglycaemic clamp study in seven healthy controls and 10 people with T2D. Blood was withdrawn at four time points: at baseline after an overnight fast; after clamping to euglycaemia at 5 mmol/L; after clamping to hypoglycaemia at 2.8 mmol/L; and 24 hours later, after overnight fast. Deep molecular phenotyping using non-targeted metabolomics and the SomaLogic aptamer-based proteomics platform was performed on collected samples.

RESULTS

A total of 955 metabolites and 1125 proteins were identified, with significant alterations in >90 molecules. A number of metabolites significantly increased during hypoglycaemia, but only cortisol, adenosine-3',5'-cyclic monophosphate (cyclic AMP), and pregnenolone sulphate, were independent of insulin. By contrast, identified protein changes were triggered by hypoglycaemia rather than insulin. The T2D group had significantly higher levels of fatty acids including 10-nonadecenoate, linolenate and dihomo-linoleate during hypoglycaemia compared with the control group. Molecules contributing to cardiovascular complications such as fatty-acid-binding protein-3 and pregnenolone sulphate were altered in the participants with T2D during hypoglycaemia. Almost all molecules returned to baseline at 24 hours.

CONCLUSIONS

The present study provides a comprehensive description of molecular events that are triggered by insulin-induced hypoglycaemia. We identified deregulated pathways in T2D that may play a role in the pathophysiology of hypoglycaemia-induced cardiovascular complications.

Diet-Related Metabolic Perturbations of Gut Microbial Shikimate Pathway-Tryptamine-tRNA Aminoacylation-Protein Synthesis in Human Health and Disease

Human gut bacterial Na(+)-transporting NADH:ubiquinone reductase (NQR) sequence is associated with Alzheimer disease (AD). Here, Alzheimer disease-associated sequence (ADAS) is further characterized in cultured spore-forming Clostridium sp. Tryptophan and NQR substrate ubiquinone have common precursor chorismate in microbial shikimate pathway. Tryptophan-derived tryptamine presents in human diet and gut microbiome. Tryptamine inhibits tryptophanyl-tRNA synthetase (TrpRS) with consequent neurodegeneration in cell and animal models. Tryptophanyl-tRNA synthetase inhibition causes protein biosynthesis impairment similar to that revealed in AD. Tryptamine-induced TrpRS gene-dose reduction is associated with TrpRS protein deficiency and cell death. In animals, tryptamine treatment results in toxicity, weight gain, and prediabetes-related hypoglycemia. Sequence analysis of gut microbiome database reveals 89% to 100% ADAS nucleotide identity in American Indian (Cheyenne and Arapaho [C&A]) Oklahomans, of which ~93% being overweight or obese and 50% self-reporting type 2 diabetes (T2D). Alzheimer disease-associated sequence occurs in 10.8% of C&A vs 1.3% of healthy American population. This observation is of considerable interest because T2D links to AD and obesity. Alzheimer disease-associated sequence prevails in gut microbiome of colorectal cancer, which linked to AD. Metabolomics revealed that tryptamine, chorismate precursor quinate, and chorismate product 4-hydroxybenzoate (ubiquinone precursor) are significantly higher, while tryptophan-containing dipeptides are lower due to tRNA aminoacylation deficiency in C&A compared with non-native Oklahoman who showed no ADAS. Thus, gut microbial tryptamine overproduction correlates with ADAS occurrence. Antibiotic and diet additives induce ADAS and tryptamine. Mitogenic/cytotoxic tryptamine cause microbial and human cell death, gut dysbiosis, and consequent disruption of host-microbe homeostasis. Present analysis of 1246 participants from 17 human gut metagenomics studies revealed ADAS in cell death diseases.

Immunometabolic Signatures Predict Risk of Progression to Active Tuberculosis and Disease Outcome

There remains a pressing need for biomarkers that can predict who will progress to active tuberculosis (TB) after exposure to Mycobacterium tuberculosis (MTB) bacterium. By analyzing cohorts of household contacts of TB index cases (HHCs) and a stringent non-human primate (NHP) challenge model, we evaluated whether integration of blood transcriptional profiling with serum metabolomic profiling can provide new understanding of disease processes and enable improved prediction of TB progression. Compared to either alone, the combined application of pre-existing transcriptome- and metabolome-based signatures more accurately predicted TB progression in the HHC cohorts and more accurately predicted disease severity in the NHPs. Pathway and data-driven correlation analyses of the integrated transcriptional and metabolomic datasets further identified novel immunometabolomic signatures significantly associated with TB progression in HHCs and NHPs, implicating cortisol, tryptophan, glutathione, and tRNA acylation networks. These results demonstrate the power of multi-omics analysis to provide new insights into complex disease processes.

Metabolomic analysis of male combat veterans with post traumatic stress disorder

Posttraumatic stress disorder (PTSD) is associated with impaired major domains of psychology and behavior. Individuals with PTSD also have increased co-morbidity with several serious medical conditions, including autoimmune diseases, cardiovascular disease, and diabetes, raising the possibility that systemic pathology associated with PTSD might be identified by metabolomic analysis of blood. We sought to identify metabolites that are altered in male combat veterans with PTSD. In this case-control study, we compared metabolomic profiles from age-matched male combat trauma-exposed veterans from the Iraq and Afghanistan conflicts with PTSD (n = 52) and without PTSD (n = 51) (‘Discovery group’). An additional group of 31 PTSD-positive and 31 PTSD-negative male combat-exposed veterans was used for validation of these findings (‘Test group’). Plasma metabolite profiles were measured in all subjects using ultrahigh performance liquid chromatography/tandem mass spectrometry and gas chromatography/mass spectrometry. We identified key differences between PTSD subjects and controls in pathways related to glycolysis and fatty acid uptake and metabolism in the initial ‘Discovery group’, consistent with mitochondrial alterations or dysfunction, which were also confirmed in the ‘Test group’. Other pathways related to urea cycle and amino acid metabolism were different between PTSD subjects and controls in the ‘Discovery’ but not in the smaller ‘Test’ group. These metabolic differences were not explained by comorbid major depression, body mass index, blood glucose, hemoglobin A1c, smoking, or use of analgesics, antidepressants, statins, or anti-inflammatories. These data show replicable, wide-ranging changes in the metabolic profile of combat-exposed males with PTSD, with a suggestion of mitochondrial alterations or dysfunction, that may contribute to the behavioral and somatic phenotypes associated with this disease.

Dystrophinopathy-associated dysfunction of Krebs cycle metabolism

Duchenne muscular dystrophy is a deadly muscle-wasting disorder caused by loss of dystrophin protein. Studies suggest that metabolic alterations are important to disease pathogenesis. Because muscle accounts for ~40% of body mass, we hypothesized that dystrophy-mediated metabolic changes would be measurable in biofluids and that a metabolomic analysis of urine would provide insight into the metabolic status of dystrophic muscle. Using the mdx mouse model, we performed a large-scale metabolomic screen at 1 and 3 months. While 10% of metabolites were altered at age 1 month, 40% were changed at 3 months. Principal component analysis distinguished wild-type from mdx animals, with the greatest separation at 3 months. A critical distinguishing pathway was Krebs cycle metabolite depletion in mdx urine. Five of seven detected Krebs cycle metabolites were depleted in mdx urine, with succinate being the most robustly affected metabolite. Using selected reaction monitoring mass spectrometry, we demonstrated that muscle-specific dystrophin expression corrects mdx succinate depletion. When subjected to downhill treadmill running, wild-type and mdx mice expressing recombinant dystrophin in skeletal muscle displayed significant increases in urinary succinate levels. However, mdx succinate levels were unchanged, suggesting urinary succinate depletion may reflect an inability to upregulate the Krebs cycle following exercise. Finally, we show that supplementing the Krebs cycle in an ex vivo fatigue/recovery assay significantly impacts mdx muscle performance but has no effect on wild-type muscle. Our results suggest that global metabolic impairment is associated with mdx disease progression and that Krebs cycle deficiencies are a downstream consequence of dystrophin loss.

Metabolic pathways modulate the neuronal toxicity associated with fragile X-associated tremor/ataxia syndrome

Fragile X-associated tremor/ataxia syndrome (FXTAS) is an adult-onset neurodegenerative disorder that affects premutation carriers (55-200 CGG repeats) of the fragile X mental retardation 1 (FMR1) gene. Much remains unknown regarding the metabolic alterations associated with FXTAS, especially in the brain, and the most affected region, the cerebellum. Investigating the metabolic changes in FXTAS will aid in the identification of biomarkers as well as in understanding the pathogenesis of disease. To identify the metabolic alterations associated with FXTAS, we took advantage of our FXTAS mouse model that expresses 90 CGG repeats in cerebellar Purkinje neurons and exhibits the key phenotypic features of FXTAS. We performed untargeted global metabolic profiling of age-matched control and FXTAS mice cerebella at 16-20 weeks and 55 weeks. Out of 506 metabolites measured in cerebellum, we identified 186 metabolites that demonstrate significant perturbations due to the (CGG)90 repeat (P<0.05) and found that these differences increase dramatically with age. To identify key metabolic changes in FXTAS pathogenesis, we performed a genetic screen using a Drosophila model of FXTAS. Out of 28 genes that we tested in the fly, 8 genes showed significant enhanced neuronal toxicity associated with CGG repeats, such as Schlank (ceramide synthase), Sk2 (sphingosine kinase) and Ras (IMP dehydrogenase). By combining metabolic profiling with a Drosophila genetic screen to identify genetic modifiers of FXTAS, we demonstrate an effective method for functional validation of high-throughput metabolic data and show that sphingolipid and purine metabolism are significantly perturbed in FXTAS pathogenesis.

Metabolitic profiling of amino acids in paraquat-induced acute kidney injury

BACKGROUND

The herbicide paraquat (1, 1'-dimethyl-4, 4'-bipyridylium dichloride; PQ) is a poison well-known to cause delayed mortality due to acute kidney injuries (AKI). This study examines the changes in serum amino acids (AAs) metabolite profiles as surrogate markers of renal cell metabolism and function after paraquat poisoning.

METHODS

To identify the metabolic profiling of free serum AAs and its metabolites, serum from 40 paraquat-poisoned patients with or without AKI is collected. LC-MS/GC-MS is performed to analyze AA molecules. A Cox proportional hazard model was used to assess for incidence of AKI. Receiver operating characteristic (ROC) curve is applied to evaluate AKI occurrence and prognosis.

RESULTS

A total of 102 serum AAs and its metabolites were identified. Compared with non-AKI patients, 37 varied significantly in AKI patients. The univariate Cox proportional hazard model analysis revealed that the estimated PQ amount, plasma PQ concentration, urine PQ concentration, APACHE, SOFA scores and 16 amino acids correlated with the incidence of AKI. Further analyses revealed that 3-methylglutarylcarnitine, 1-methylimidazoleacetate, and urea showed higher cumulative hazard ratios for the occurrence of AKI during follow-up (P < 0.05). The area under the curve (AUC) of 3-methylglutarylcarnitine, 1-methylimidazoleacetate and urea were 0.917, 0.857, 0.872, respectively.

CONCLUSION

3-methylglutarylcarnitine, 1-methylimidazoleacetate and urea were associated with AKI in patients with paraquat intoxication.

Genome-wide association study in frontal fibrosing alopecia identifies four susceptibility loci including HLA-B*07:02

Frontal fibrosing alopecia (FFA) is a recently described inflammatory and scarring type of hair loss affecting almost exclusively women. Despite a dramatic recent increase in incidence the aetiopathogenesis of FFA remains unknown. We undertake genome-wide association studies in females from a UK cohort, comprising 844 cases and 3,760 controls, a Spanish cohort of 172 cases and 385 controls, and perform statistical meta-analysis. We observe genome-wide significant association with FFA at four genomic loci: 2p22.2, 6p21.1, 8q24.22 and 15q2.1. Within the 6p21.1 locus, fine-mapping indicates that the association is driven by the HLA-B*07:02 allele. At 2p22.1, we implicate a putative causal missense variant in CYP1B1, encoding the homonymous xenobiotic- and hormone-processing enzyme. Transcriptomic analysis of affected scalp tissue highlights overrepresentation of transcripts encoding components of innate and adaptive immune response pathways. These findings provide insight into disease pathogenesis and characterise FFA as a genetically predisposed immuno-inflammatory disorder driven by HLA-B*07:02.

Frontal fibrosing alopecia (FFA) features lichenoid cutaneous inflammation and scarring hair loss. Here, Tziotzios et al. identify four genetic loci associated with FFA by GWAS followed by Bayesian fine-mapping, co-localisation and HLA imputation which highlights HLA-B*07:02 as a risk factor.

Network Modeling of Liver Metabolism to Predict Plasma Metabolite Changes During Short-Term Fasting in the Laboratory Rat

The liver—a central metabolic organ that integrates whole-body metabolism to maintain glucose and fatty-acid regulation, and detoxify ammonia—is susceptible to injuries induced by drugs and toxic substances. Although plasma metabolite profiles are increasingly investigated for their potential to detect liver injury earlier than current clinical markers, their utility may be compromised because such profiles are affected by the nutritional state and the physiological state of the animal, and by contributions from extrahepatic sources. To tease apart the contributions of liver and non-liver sources to alterations in plasma metabolite profiles, here we sought to computationally isolate the plasma metabolite changes originating in the liver during short-term fasting. We used a constraint-based metabolic modeling approach to integrate central carbon fluxes measured in our study, and physiological flux boundary conditions gathered from the literature, into a genome-scale model of rat liver metabolism. We then measured plasma metabolite profiles in rats fasted for 5–7 or 10–13 h to test our model predictions. Our computational model accounted for two-thirds of the observed directions of change (an increase or decrease) in plasma metabolites, indicating their origin in the liver. Specifically, our work suggests that changes in plasma lipid metabolites, which are reliably predicted by our liver metabolism model, are key features of short-term fasting. Our approach provides a mechanistic model for identifying plasma metabolite changes originating in the liver.

Metabolomics-based identification of metabolic alterations in PARK2

Objective

Parkin is the causative gene for autosomal recessive familial Parkinson's disease (PD), although it remains unclear how parkin dysfunction is involved with the general condition. Recently, serum and/or plasma metabolomics revealed alterations in metabolic pathways that might reflect pathomechanisms of idiopathic PD (iPD). Thus, we hypothesized that serum metabolomics of patients with homozygous or compound heterozygous parkin mutations (namely, PARK2) might reflect metabolic alterations due to parkin dysfunction.

Methods

We enrolled 15 PARK2 patients (52 ± 17.6 years) confirmed with homozygous (seven cases) and compound heterozygous (eight cases) parkin mutations, along with 19 healthy age‐matched controls (51 ± 11.5 years). We analyzed 830 metabolites from participants’ serum using well‐established metabolomics technologies, including ultra‐high performance liquid chromatography/tandem mass spectroscopy.

Results

Based on metabolic profiles, hierarchical matrix analysis can divide samples between control and PARK2 subjects. Profiles from PARK2 patients showed significantly higher levels of fatty acid (FA) metabolites and oxidized lipids, and significantly lower levels of antioxidant, caffeine, and benzoate‐related metabolites.

Interpretation

Metabolomics can identify specific metabolic alterations in PARK2 patients compared with controls. Alterations in FA metabolites suggest a relationship between parkin function and lipid metabolism. The elevation of oxidized lipids in combination with decreasing antioxidants may reflect general hyperoxidative stress. Decreasing benzoate‐related metabolites might be due to the alteration in gut microbiota. Consequently, caffeine and its metabolites may be decreased due to malabsorption. These findings are similar to metabolic alterations in iPD. Thus, serum/plasma metabolomics may reflect the association between parkin dysfunction and parkinsonism.

The metabolite repair enzyme Nit1 is a dual-targeted amidase that disposes of damaged glutathione in Arabidopsis

The tripeptide glutathione (GSH) is implicated in various crucial physiological processes including redox buffering and protection against heavy metal toxicity. GSH is abundant in plants, with reported intracellular concentrations typically in the 1-10 mM range. Various aminotransferases can inadvertently transaminate the amino group of the γ-glutamyl moiety of GSH to produce deaminated glutathione (dGSH), a metabolite damage product. It was recently reported that an amidase known as Nit1 participates in dGSH breakdown in mammals and yeast. Plants have a hitherto uncharacterized homolog of the Nit1 amidase. We show that recombinant Arabidopsis Nit1 (At4g08790) has high and specific amidase activity towards dGSH. Ablating the Arabidopsis Nit1 gene causes a massive accumulation of dGSH and other marked changes to the metabolome. All plant Nit1 sequences examined had predicted plastidial targeting peptides with a potential second start codon whose use would eliminate the targeting peptide. In vitro transcription/translation assays show that both potential translation start codons in Arabidopsis Nit1 were used and confocal microscopy of Nit1-GFP fusions in plant cells confirmed both cytoplasmic and plastidial localization. Furthermore, we show that Arabidopsis enzymes present in leaf extracts convert GSH to dGSH at a rate of 2.8 pmol min^-1 mg^-1 in the presence of glyoxalate as an amino acceptor. Our data demonstrate that plants have a dGSH repair system that is directed to at least two cellular compartments via the use of alternative translation start sites.

Metabolite Profiles of Raw Peanut Seeds Reveal Differences between Market-Types

Peanuts (Arachis hypogaea L.) are prized for their flavor and popular worldwide as food or as food ingredients. The raw peanut seed contains the precursor compounds to roasted peanut flavor and has the potential to be manipulated through traditional breeding methods. However, little is known about the metabolome of the raw seeds. Comprehensive metabolite profiles of both raw runner and Virginia-type peanuts were determined. Using a system incorporating several methodologies including (RP)/UPLC-MS/MS and HILIC/UPLC-MS/MS, along with quantitation of fatty acids, free amino acids, and tocopherols, 365 metabolites were identified and of these, 52 were significantly different between market types (P < 0.05). Higher levels of gamma-glutamylalanine, oxylipins, purine metabolites, and alpha-ketoglutarate derived members of the glutamate family of amino acids defined the Virginia-type, while runner-type peanuts were differentiated by their ethylmalonate and eicosenoate content. This study presents a comprehensive analysis of the raw peanut seed, providing knowledge of the range of small molecules present in peanuts. The new information presented here will enable future research for peanut quality improvement. PRACTICAL APPLICATION: Peanuts are widely used as snack foods and as food ingredients. Knowledge of the secondary metabolite compounds in raw peanuts is needed to determine their importance in peanut flavor and nutritional quality. This report used a nontargeted analytical approach for the identification of these types of compounds in peanuts for the first time. These data were supplemented with quantitative analysis of free amino acids and tocopherols and discussed as potential flavor precursors and health promoting compounds.

Metabolomics Approaches for the Diagnosis and Understanding of Kidney Diseases

Diseases of the kidney are difficult to diagnose and treat. This review summarises the definition, cause, epidemiology and treatment of some of these diseases including chronic kidney disease, diabetic nephropathy, acute kidney injury, kidney cancer, kidney transplantation and polycystic kidney diseases. Numerous studies have adopted a metabolomics approach to uncover new small molecule biomarkers of kidney diseases to improve specificity and sensitivity of diagnosis and to uncover biochemical mechanisms that may elucidate the cause and progression of these diseases. This work includes a description of mass spectrometry-based metabolomics approaches, including some of the currently available tools, and emphasises findings from metabolomics studies of kidney diseases. We have included a varied selection of studies (disease, model, sample number, analytical platform) and focused on metabolites which were commonly reported as discriminating features between kidney disease and a control. These metabolites are likely to be robust indicators of kidney disease processes, and therefore potential biomarkers, warranting further investigation.

Deep molecular phenotypes link complex disorders and physiological insult to CpG methylation

Epigenetic regulation of cellular function provides a mechanism for rapid organismal adaptation to changes in health, lifestyle and environment. Associations of cytosine-guanine di-nucleotide (CpG) methylation with clinical endpoints that overlap with metabolic phenotypes suggest a regulatory role for these CpG sites in the body's response to disease or environmental stress. We previously identified 20 CpG sites in an epigenome-wide association study (EWAS) with metabolomics that were also associated in recent EWASs with diabetes-, obesity-, and smoking-related endpoints. To elucidate the molecular pathways that connect these potentially regulatory CpG sites to the associated disease or lifestyle factors, we conducted a multi-omics association study including 2474 mass-spectrometry-based metabolites in plasma, urine and saliva, 225 NMR-based lipid and metabolite measures in blood, 1124 blood-circulating proteins using aptamer technology, 113 plasma protein N-glycans and 60 IgG-glyans, using 359 samples from the multi-ethnic Qatar Metabolomics Study on Diabetes (QMDiab). We report 138 multi-omics associations at these CpG sites, including diabetes biomarkers at the diabetes-associated TXNIP locus, and smoking-specific metabolites and proteins at multiple smoking-associated loci, including AHRR. Mendelian randomization suggests a causal effect of metabolite levels on methylation of obesity-associated CpG sites, i.e. of glycerophospholipid PC(O-36: 5), glycine and a very low-density lipoprotein (VLDL-A) on the methylation of the obesity-associated CpG loci DHCR24, MYO5C and CPT1A, respectively. Taken together, our study suggests that multi-omics-associated CpG methylation can provide functional read-outs for the underlying regulatory response mechanisms to disease or environmental insults.

Randomized controlled trial of low (5%) versus ultralow (2%) oxygen for extended culture using bipronucleate and tripronucleate human preimplantation embryos

OBJECTIVE

To determine whether [1] exposure of embryos to 5% oxygen (O₂) from day 1 (D1) to D3, and then to 2% O₂ from D3 to D5, improves total blastocyst yield, as compared with continuous exposure to 5% O₂; and [2] extended culture in 2% O₂ alters key metabolic processes and O₂-regulated gene expression in human preimplantation embryos.

DESIGN

Randomized controlled trial.

SETTING

Academic medical center.

PATIENT(S)

Bipronucleate and tripronucleate embryos donated for research.

INTERVENTION(S)

On D1, sibling zygotes were randomized to culture in 5% O₂ from D1 to D5 (n = 102; "5% group") or 5% O₂ from D1 to D3, then 2% O₂ from D3 to D5 (n = 101, "2% group").

MAIN OUTCOME MEASURE(S)

Developmental stage and grade; D5 total cell counts; mass spectrometry of spent media; quantitative polymerase chain reaction of 21 genes in inner cell mass and trophectoderm.

RESULT(S)

Among cleaved embryos (n = 176, 87%), those in the 2% group were less likely to arrest at the cleavage stage on D5 (34 of 87, 39.1%) compared with the 5% group (52 of 89, 58.4%) (adjusted odds ratio 0.38, 95% confidence interval 0.18-0.80). Those in the 2% group were more likely to blastulate (35 of 87, 40.2%) than those in the 5% group (20 of 89, 22.5%) (adjusted odds ratio 2.55, 95% confidence interval 1.27-5.12). Culture in 2% O₂ was associated with significantly fewer cells in early and advanced blastocysts, alteration in relative abundances of anabolic amino acids and metabolites involved in redox homeostasis, and differential expression of MUC1 in trophectoderm.

CONCLUSION(S)

These findings provide foundational evidence for future investigation of 2% O₂ as the preferred O₂ tension for extended culture of human embryos.

Serum bile acid patterns are associated with the presence of NAFLD in twins, and dose-dependent changes with increase in fibrosis stage in patients with biopsy-proven NAFLD

BACKGROUND

The fasting-state serum bile acid profile in nonalcoholic fatty liver disease (NAFLD) has been reported to differ when nonalcoholic steatohepatitis is compared to nonalcoholic fatty liver. However, there are few data comparing changes in NAFLD vs non-NAFLD, or whether the bile acid profile differs according to the degree of fibrosis.

AIM

To examine the serum bile acid profile across the entire spectrum of NAFLD.

METHODS

We performed a cross-sectional analysis of two complementary cohorts: a Twin and Family cohort of 156 participants, and a biopsy-proven-NAFLD cohort of 156 participants with fasting bile acid profiling using liquid chromatography/mass spectrometry.

RESULTS

In the Twin and Family cohort (mean age 46.3 years and body mass index (BMI) 26.6 kg/m² ), 36 (23%) participants had NAFLD (magnetic resonance imaging proton density fat fraction ≥ 5%). Higher chenodeoxycholyl conjugates (9.0% vs 6.5%, P = 0.019) and lower glycohyocholate (1.2% vs 3.6%, P < 0.001) were observed in NAFLD compared to non-NAFLD-controls. In the biopsy-proven-NAFLD cohort (mean age 49.8 years, BMI 32.0 kg/m² ), no differences in total bile acid were seen between nonalcoholic fatty liver vs nonalcoholic steatohepatitis. The total unconjugated bile acid significantly decreased across nonalcoholic steatohepatitis categories (P = 0.044). The distribution of stage of fibrosis was F0: 42.3%, F1: 32.7%, F2: 10.3%, F3: 8.3% and F4: 6.4%. The total serum bile acid increased with increase in fibrosis stage (P < 0.001). The primary conjugated bile acid proportion increased (P < 0.001) whereas unconjugated bile acid (P = 0.006), unconjugated cholyl (P < 0.001) and chenodeoxycholyl conjugates (P < 0.002) significantly decreased with increase in liver fibrosis stage.

CONCLUSIONS

Fasting-state serum bile acid profile alterations are seen across the entire spectrum of NAFLD. The total serum bile acids did not differ significantly between NAFLD vs non-NAFLD and nonalcoholic fatty liver vs nonalcoholic steatohepatitis, but were significantly perturbed progressively as liver fibrosis increases.

Effects of omega-3 polyunsaturated fatty-acid supplementation on neuropathic pain symptoms and sphingosine levels in Mexican-Americans with type 2 diabetes

PURPOSE

To determine whether dietary supplementation with omega-3 polyunsaturated fatty acids (PUFAs) reduces neuropathic pain symptoms in Mexican-Americans with type 2 diabetes.

METHODS

Forty volunteers with type 2 diabetes enrolled in the "En Balance-PLUS" program, which provided weekly nutrition-diabetes education and daily supplementation with 1,000 mg docosahexaenoic acid (DHA)-200 mg eicosapentaenoic acid over 3 months. The study assessed self-reported neuropathic pain symptoms pre/postintervention using the short-form McGill Pain Questionnaire (SF-MPQ), monitored clinical laboratory values at baseline and 3 months, and performed baseline and 3-month metabolomic analysis of plasma samples.

RESULTS

A total of 26 participants self-reported neuropathic pain symptoms at baseline. After 3 months of omega-3 PUFA supplementation, participants reported significant improvement in SF-MPQ scores (sensory, affective, and visual analogue scale; P<0.001, P=0.012, and P<0.001, respectively). Untargeted metabolomic analysis revealed that participants in the moderate-high SF-MPQ group had the highest relative plasma sphingosine levels at baseline compared to the low SF-MPQ group (P=0.0127) and the nonpain group (P=0.0444). Omega-3 PUFA supplementation increased plasma DHA and reduced plasma sphingosine levels in participants reporting neuropathic pain symptoms (P<0.001 and P<0.001, respectively). Increased plasma DHA levels significantly correlated with improved SF-MPQ sensory scores (r=0.425, P=0.030). Improved SF-MPQ scores, however, did not correlate with clinical/laboratory parameters.

CONCLUSION

The data suggest that omega-3 PUFAs dietary supplementation may reduce neuropathic pain symptoms in individuals with type 2 diabetes and correlates with sphingosine levels in the plasma.

The Supragingival Biofilm in Early Childhood Caries: Clinical and Laboratory Protocols and Bioinformatics Pipelines Supporting Metagenomics, Metatranscriptomics, and Metabolomics Studies of the Oral Microbiome

Early childhood caries (ECC) is a biofilm-mediated disease. Social, environmental, and behavioral determinants as well as innate susceptibility are major influences on its incidence; however, from a pathogenetic standpoint, the disease is defined and driven by oral dysbiosis. In other words, the disease occurs when the natural equilibrium between the host and its oral microbiome shifts toward states that promote demineralization at the biofilm-tooth surface interface. Thus, a comprehensive understanding of dental caries as a disease requires the characterization of both the composition and the function or metabolic activity of the supragingival biofilm according to well-defined clinical statuses. However, taxonomic and functional information of the supragingival biofilm is rarely available in clinical cohorts, and its collection presents unique challenges among very young children. This paper presents a protocol and pipelines available for the conduct of supragingival biofilm microbiome studies among children in the primary dentition, that has been designed in the context of a large-scale population-based genetic epidemiologic study of ECC. The protocol is being developed for the collection of two supragingival biofilm samples from the maxillary primary dentition, enabling downstream taxonomic (e.g., metagenomics) and functional (e.g., transcriptomics and metabolomics) analyses. The protocol is being implemented in the assembly of a pediatric precision medicine cohort comprising over 6000 participants to date, contributing social, environmental, behavioral, clinical, and biological data informing ECC and other oral health outcomes.

Random Forest Analysis of Untargeted Metabolomics Data Suggests Increased Use of Omega Fatty Acid Oxidation Pathway in Drosophila Melanogaster Larvae Fed a Medium Chain Fatty Acid Rich High-Fat Diet

Obesity is a complex disease, shaped by both genetic and environmental factors such as diet. In this study, we use untargeted metabolomics and Drosophila melanogaster to model how diet and genotype shape the metabolome of obese phenotypes. We used 16 distinct outbred genotypes of Drosophila larvae raised on normal (ND) and high-fat (HFD) diets, to produce three distinct phenotypic classes; genotypes that stored more triglycerides on a ND relative to the HFD, genotypes that stored more triglycerides on a HFD relative to ND, and genotypes that showed no change in triglyceride storage on either of the two diets. Using untargeted metabolomics we characterized 350 metabolites: 270 with definitive chemical IDs and 80 that were chemically unidentified. Using random forests, we determined metabolites that were important in discriminating between the HFD and ND larvae as well as between the triglyceride phenotypic classes. We found that flies fed on a HFD showed evidence of an increased use of omega fatty acid oxidation pathway, an alternative to the more commonly used beta fatty acid oxidation pathway. Additionally, we observed no correlation between the triglyceride storage phenotype and free fatty acid levels (laurate, caprate, caprylate, caproate), indicating that the distinct metabolic profile of fatty acids in high-fat diet fed Drosophila larvae does not propagate into triglyceride storage differences. However, dipeptides did show moderate differences between the phenotypic classes. We fit Gaussian graphical models (GGMs) of the metabolic profiles for HFD and ND flies to characterize changes in metabolic network structure between the two diets, finding the HFD to have a greater number of edges indicating that metabolome varies more across samples on a HFD. Taken together, these results show that, in the context of obesity, metabolomic profiles under distinct dietary conditions may not be reliable predictors of phenotypic outcomes in a genetically diverse population.

Untargeted metabolomics identifies unique though benign biochemical changes in patients with pathogenic variants in UROC1

Urocanic aciduria is caused by a deficiency in the enzyme urocanase (E.C. 4.2.1.49) encoded by the gene UROC1. In the past, deficiency of urocanase has been associated with intellectual disability in a few case studies with some suggestion that the enzyme deficiency was the causative etiology. Here, we describe two phenotypically normal siblings with compound heterozygous pathogenic variants in UROC1 and characteristic biochemical evidence of urocanase deficiency collected utilizing untargeted metabolomic analysis. These findings suggest that urocanic aciduria may represent an otherwise benign biochemical phenotype and that those individuals with concurrent developmental delay should continue to be evaluated for other underlying causes for their symptoms.

Metabolomics of mammalian brain reveals regional differences

Background

The mammalian brain is organized into regions with specific biological functions and properties. These regions have distinct transcriptomes, but little is known whether they may also differ in their metabolome. The metabolome, a collection of small molecules or metabolites, is at the intersection of the genetic background of a given cell or tissue and the environmental influences that affect it. Thus, the metabolome directly reflects information about the physiologic state of a biological system under a particular condition. The objective of this study was to investigate whether various brain regions have diverse metabolome profiles, similarly to their genetic diversity. The answer to this question would suggest that not only the genome but also the metabolome may contribute to the functional diversity of brain regions.

Methods

We investigated the metabolome of four regions of the mouse brain that have very distinct functions: frontal cortex, hippocampus, cerebellum, and olfactory bulb. We utilized gas- and liquid- chromatography mass spectrometry platforms and identified 215 metabolites.

Results

Principal component analysis, an unsupervised multivariate analysis, clustered each brain region based on its metabolome content, thus providing the unique metabolic profile of each region. A pathway-centric analysis indicated that olfactory bulb and cerebellum had most distinct metabolic profiles, while the cortical parenchyma and hippocampus were more similar in their metabolome content. Among the notable differences were distinct oxidative-anti-oxidative status and region-specific lipid profiles. Finally, a global metabolic connectivity analysis using the weighted correlation network analysis identified five hub metabolites that organized a unique metabolic network architecture within each examined brain region. These data indicate the diversity of global metabolome corresponding to specialized regional brain function and provide a new perspective on the underlying properties of brain regions.

Conclusion

In summary, we observed many differences in the metabolome among the various brain regions investigated. All four brain regions in our study had a unique metabolic signature, but the metabolites came from all categories and were not pathway-centric.

Electronic supplementary material

The online version of this article (10.1186/s12918-018-0644-0) contains supplementary material, which is available to authorized users.

Differences among Unique Nanoparticle Protein Corona Constructs: A Case Study Using Data Analytics and Multi-Variant Visualization to Describe Physicochemical Characteristics

Gold nanoparticles (AuNPs) used in pharmaceutical treatments have been shown to effectively deliver a payload, such as an active pharmaceutical ingredient or image contrast agent, to targeted tissues in need of therapy or diagnostics while minimizing exposure, availability, and accumulation to surrounding biological compartments. Data sets collected in this field of study include some toxico- and pharmacodynamic properties (e.g., distribution and metabolism) but many studies lack information about adsorption of biological molecules or absorption into cells. When nanoparticles are suspended in blood serum, a protein corona cloud forms around its surface. The extent of the applications and implications of this formed cloud are unknown. Some researchers have speculated that the successful use of nanoparticles in pharmaceutical treatments relies on a comprehensive understanding of the protein corona composition. The work presented in this paper uses a suite of data analytics and multi-variant visualization techniques to elucidate particle-to-protein interactions at the molecular level. Through mass spectrometry analyses, corona proteins were identified through large and complex datasets. With such high-output analyses, complex datasets pose a challenge when visualizing and communicating nanoparticle-protein interactions. Thus, the creation of a streamlined visualization method is necessary. A series of user-friendly data informatics techniques were used to demonstrate the data flow of protein corona characteristics. Multi-variant heat maps, pie charts, tables, and three-dimensional regression analyses were used to improve results interpretation, facilitate an iterative data transfer process, and emphasize features of the nanoparticle-protein corona system that might be controllable. Data informatics successfully highlights the differences between protein corona compositions and how they relate to nanoparticle surface charge.

Comparative Metabolomic Sampling of Upper and Lower Airways by Four Different Methods to Identify Biochemicals That May Support Bacterial Growth

Bacteria need nutrients from the host environment to survive, yet we know little about which biochemicals are present in the airways (the metabolome), which of these biochemicals are essential for bacterial growth and how they change with airway disease. The aims of this pilot study were to develop and compare methodologies for sampling the upper and lower airway metabolomes and to identify biochemicals present in the airways that could potentially support bacterial growth. Eight healthy human volunteers were sampled by four methods: two standard approaches - nasal lavage and induced sputum, and two using a novel platform, synthetic adsorptive matrix (SAM) strips—nasosorption and bronchosorption. Collected samples were analyzed by Ultrahigh Performance Liquid Chromatography-Tandem Mass Spectroscopy (UPLC-MS/MS). Five hundred and eighty-one biochemicals were recovered from the airways belonging to a range of metabolomic super-pathways. We observed significant differences between the sampling approaches. Significantly more biochemicals were recovered when SAM strips were used, compared to standard sampling techniques. A range of biochemicals that could support bacterial growth were detected in the different samples. This work demonstrates for the first time that SAM strips are a highly effective method for sampling the airway metabolome. This work will assist further studies to understand how changes in the airway metabolome affect bacterial infection in patients with underlying airway disease.

Characterization and functional biology of the soybean aleurone layer

BACKGROUND

Soybean is a globally important oil seed crop. Both the high protein and oil content of soybean seeds make this crop a lucrative commodity. As in higher eukaryotic species with available genomes, the functional annotation of most of soybean's genes still remains to be investigated. A major hurdle in the functional genomics of soybean is a rapid method to test gene constructs before embarking on stable transformation experiments.

RESULTS

In this paper we describe the morphology and composition of the persistent single-cell aleurone layer that derives from the endosperm of developing soybean seeds. Its composition compared to cotyledonary tissue indicates the aleurone layer plays a role in both abiotic and biotic stress. The potential utility as the aleurone layer as a transient expression system in soybean was shown. As a near transparent single-cell layer it can be used as a transient expression system to study transgene expression and inter- and intra-cellular targeting as it is amenable to microscopic techniques.

CONCLUSION

The transparent single cell aleurone layer was shown to be compositionally comparable to cotyledonary tissue in soybean with an enrichment in oxidative response proteins and shown to be a potential transient expression platform.

Metabolite changes in blood predict the onset of tuberculosis

New biomarkers of tuberculosis (TB) risk and disease are critical for the urgently needed control of the ongoing TB pandemic. In a prospective multisite study across Subsaharan Africa, we analyzed metabolic profiles in serum and plasma from HIV-negative, TB-exposed individuals who either progressed to TB 3–24 months post-exposure (progressors) or remained healthy (controls). We generated a trans-African metabolic biosignature for TB, which identifies future progressors both on blinded test samples and in external data sets and shows a performance of 69% sensitivity at 75% specificity in samples within 5 months of diagnosis. These prognostic metabolic signatures are consistent with development of subclinical disease prior to manifestation of active TB. Metabolic changes associated with pre-symptomatic disease are observed as early as 12 months prior to TB diagnosis, thus enabling timely interventions to prevent disease progression and transmission.

The tuberculosis pandemic requires new methods for diagnosing and containing infections prior to active disease. Here, the authors performed a multi-site observational study within sub-Saharan Africa and present serum and plasma metabolic signatures that can predict the onset of active TB with a high degree of sensitivity and specificity.

Maize multi-omics reveal roles for autophagic recycling in proteome remodelling and lipid turnover

The turnover of cytoplasmic material by autophagic encapsulation and delivery to vacuoles is essential for recycling cellular constituents, especially under nutrient-limiting conditions. To determine how cells/tissues rely on autophagy, we applied in-depth multi-omic analyses to study maize (Zea mays) autophagy mutants grown under nitrogen-replete and -starvation conditions. Broad alterations in the leaf metabolome were evident in plants missing the core autophagy component ATG12, even in the absence of stress, particularly affecting products of lipid turnover and secondary metabolites, which were underpinned by substantial changes in the transcriptome and/or proteome. Cross-comparison of messenger RNA and protein abundances allowed for the identification of organelles, protein complexes and individual proteins targeted for selective autophagic clearance, and revealed several processes controlled by this catabolism. Collectively, we describe a facile multi-omic strategy to survey autophagic substrates, and show that autophagy has a remarkable influence in sculpting eukaryotic proteomes and membranes both before and during nutrient stress.

Comparison of Effects of Diet on Mammary Cancer: Efficacy of Various Preventive Agents and Metabolomic Changes of Different Diets and Agents

To determine the effects of diet, rats were placed on a standard diet (4% fat) or on a modified Western (high-fat diet, HFD) diet (21% fat) at 43 days of age (DOA) and administered methylnitrosourea (MNU) at 50 DOA. Rats were administered effective (tamoxifen, vorozole, and Targretin) or ineffective (metformin and Lipitor) chemopreventive agents either by daily gavage or in the diet beginning at 57 DOA and continuing until sacrifice (190 DOA). Latency period of the tumors was determined by palpation, and multiplicity and cancer weights per rat were determined at final sacrifice. Rats on the HFD versus standard diet had: (i) a 6% increase in final body weights; (ii) significant decreases in tumor latency; and (iii) significant increases in final tumor multiplicity and average tumor weight. Tamoxifen, vorozole, and Targretin were highly effective preventive agents, whereas Lipitor and metformin were ineffective in rats on either diet. Serum was collected at 78 DOA and at sacrifice (190 DOA), and metabolomics were determined to identify the metabolite changes due to diets and effective agents. Rats given the HFD had increased levels of saturated free fatty acids (including myristate) and decreased levels of 2-aminooctanoate. Furthermore, rats on the HFD diet had increased levels of 2-aminobutyrate and decreases in glycine markers previously identified as indicators of prediabetes. Targretin increased long-chain glycophospholipids (e.g., oleyl-linoleoyl-glycerophosphocholine) and decreased primary bile acids (e.g., taurocholate). Tamoxifen increased palmitoyl-linoleoyl-glycophosphocholine and decreased stearoyl-arachidonyl glycophosphocholine. Finally, increased levels of methylated nucleotides (5-methylcytidine) and decreased levels of urea cycle metabolites (N-acetylcitrulline) were associated with the presence of mammary cancers.

Dissection of metabolic reprogramming in polycystic kidney disease reveals coordinated rewiring of bioenergetic pathways

Autosomal Dominant Polycystic Kidney Disease (ADPKD) is a genetic disorder caused by loss-of-function mutations in PKD1 or PKD2. Increased glycolysis is a prominent feature of the disease, but how it impacts on other metabolic pathways is unknown. Here, we present an analysis of mouse Pkd1 mutant cells and kidneys to investigate the metabolic reprogramming of this pathology. We show that loss of Pkd1 leads to profound metabolic changes that affect glycolysis, mitochondrial metabolism, and fatty acid synthesis (FAS). We find that Pkd1-mutant cells preferentially use glutamine to fuel the TCA cycle and to sustain FAS. Interfering with either glutamine uptake or FAS retards cell growth and survival. We also find that glutamine is diverted to asparagine via asparagine synthetase (ASNS). Transcriptional profiling of PKD1-mutant human kidneys confirmed these alterations. We find that silencing of Asns is lethal in Pkd1-mutant cells when combined with glucose deprivation, suggesting therapeutic approaches for ADPKD.

Christine Podrini et al. present a comprehensive analysis of Pkd1 mutant mouse cells and kidneys, providing new insight into autosomal dominant polycystic kidney disease (ADPKD). They find that Pkd1 loss leads to profound metabolic changes, including asparagine synthase-driven glutamine anaplerosis.

Metabolomics in the clinic: A review of the shared and unique features of untargeted metabolomics for clinical research and clinical testing

Metabolomics is the untargeted measurement of the metabolome, which is composed of the complement of small molecules detected in a biological sample. As such, metabolomic analysis produces a global biochemical phenotype. It is a technology that has been utilized in the research setting for over a decade. The metabolome is directly linked to and is influenced by genetics, epigenetics, environmental factors, and the microbiome-all of which affect health. Metabolomics can be applied to human clinical diagnostics and to other fields such as veterinary medicine, nutrition, exercise, physiology, agriculture/plant biochemistry, and toxicology. Applications of metabolomics in clinical testing are emerging, but several aspects of its use as a clinical test differ from applications focused on research or biomarker discovery and need to be considered for metabolomics clinical test data to have optimum impact, be meaningful, and be used responsibly. In this review, we deconstruct aspects and challenges of metabolomics for clinical testing by illustrating the significance of test design, accurate and precise data acquisition, quality control, data processing, n-of-1 comparison to a reference population, and biochemical pathway analysis. We describe how metabolomics technology is integral to defining individual biochemical phenotypes, elaborates on human health and disease, and fits within the precision medicine landscape. Finally, we conclude by outlining some future steps needed to bring metabolomics into the clinical space and to be recognized by the broader medical and regulatory fields.

Identification of Enolase as the Target of 2-Aminothiazoles in Mycobacterium tuberculosis

Tuberculosis is a massive global burden and Mycobacterium tuberculosis is increasingly resistant to first- and second-line drugs. There is an acute need for new anti-mycobacterial drugs with novel targets. We previously evaluated a series of 2-aminothiazoles with activity against Mycobacterium tuberculosis. In this study, we identify the glycolytic enzyme enolase as the target of these molecules using pull down studies. We demonstrate that modulation of the level of enolase expression affects sensitivity to 2-aminothiazoles; increased expression leads to resistance while decreased protein levels increase sensitivity. Exposure to 2-aminothiazoles results in increased levels of metabolites preceding the action of enolase in the glycolytic pathway and decreased ATP levels. We demonstrate that 2-aminothiazoles inhibit the activity of the human α-enolase, which could also account for the cytotoxicity of some of those molecules. If selectivity for the bacterial enzyme over the human enzyme could be achieved, enolase would represent an attractive target for M. tuberculosis drug discovery and development efforts.

A metabolomic map of Zellweger spectrum disorders reveals novel disease biomarkers

PURPOSE

Peroxisome biogenesis disorders-Zellweger spectrum disorders (PBD-ZSD) are metabolic diseases with multisystem manifestations. Individuals with PBD-ZSD exhibit impaired peroxisomal biochemical functions and have abnormal levels of peroxisomal metabolites, but the broader metabolic impact of peroxisomal dysfunction and the utility of metabolomic methods is unknown.

METHODS

We studied 19 individuals with clinically and molecularly characterized PBD-ZSD. We performed both quantitative peroxisomal biochemical diagnostic studies in parallel with untargeted small molecule metabolomic profiling in plasma samples with detection of >650 named compounds.

RESULTS

The cohort represented intermediate to mild PBD-ZSD subjects with peroxisomal biochemical alterations on targeted analysis. Untargeted metabolomic profiling of these samples revealed elevations in pipecolic acid and long-chain lysophosphatidylcholines, as well as an unanticipated reduction in multiple sphingomyelin species. These sphingomyelin reductions observed were consistent across the PBD-ZSD samples and were rare in a population of >1,000 clinical samples. Interestingly, the pattern or "PBD-ZSD metabolome" was more pronounced in younger subjects suggesting studies earlier in life reveal larger biochemical changes.

CONCLUSION

Untargeted metabolomics is effective in detecting mild to intermediate cases of PBD-ZSD. Surprisingly, dramatic reductions in plasma sphingomyelin are a consistent feature of the PBD-ZSD metabolome. The use of metabolomics in PBD-ZSD can provide insight into novel biomarkers of disease.

Link between gut-microbiome derived metabolite and shared gene-effects with hepatic steatosis and fibrosis in NAFLD

Previous studies have shown that gut-microbiome is associated with nonalcoholic fatty liver disease (NAFLD). We aimed to examine if serum metabolites, especially those derived from the gut-microbiome, have a shared gene-effect with hepatic steatosis and fibrosis. This is a cross-sectional analysis of a prospective discovery cohort including 156 well-characterized twins and families with untargeted metabolome profiling assessment. Hepatic steatosis was assessed using magnetic-resonance-imaging proton-density-fat-fraction (MRI-PDFF) and fibrosis using MR-elastography (MRE). A twin additive genetics and unique environment effects (AE) model was used to estimate the shared gene-effect between metabolites and hepatic steatosis and fibrosis. The findings were validated in an independent prospective validation cohort of 156 participants with biopsy-proven NAFLD including shotgun metagenomics sequencing assessment in a subgroup of the cohort. In the discovery cohort, 56 metabolites including 6 microbial metabolites had a significant shared gene-effect with both hepatic steatosis and fibrosis after adjustment for age, sex and ethnicity. In the validation cohort, 6 metabolites were associated with advanced fibrosis. Among them, only one microbial metabolite, 3-(4-hydroxyphenyl)lactate, remained consistent and statistically significantly associated with liver fibrosis in the discovery and validation cohort (fold-change of higher-MRE versus lower-MRE: 1.78, P < 0.001 and of advanced versus no advanced fibrosis: 1.26, P = 0.037, respectively). The share genetic determination of 3-(4-hydroxyphenyl)lactate with hepatic steatosis was RG :0.57,95%CI:0.27-0.80, P < 0.001 and with fibrosis was RG :0.54,95%CI:0.036-1, P = 0.036. Pathway reconstruction linked 3-(4-hydroxyphenyl)lactate to several human gut-microbiome species. In the validation cohort, 3-(4-hydroxyphenyl)lactate was significantly correlated with the abundance of several gut-microbiome species, belonging only to Firmicutes, Bacteroidetes and Proteobacteria phyla, previously reported as associated with advanced fibrosis. Conclusion: This proof of concept study provides evidence of a link between the gut-microbiome and 3-(4-hydroxyphenyl)lactate that shares gene-effect with hepatic steatosis and fibrosis. (Hepatology 2018).