Showing papers on "Metabolite published in 2019"

Macronutrient metabolism by the human gut microbiome: major fermentation by-products and their impact on host health

Abstract: The human gut microbiome is a critical component of digestion, breaking down complex carbohydrates, proteins, and to a lesser extent fats that reach the lower gastrointestinal tract. This process results in a multitude of microbial metabolites that can act both locally and systemically (after being absorbed into the bloodstream). The impact of these biochemicals on human health is complex, as both potentially beneficial and potentially toxic metabolites can be yielded from such microbial pathways, and in some cases, these effects are dependent upon the metabolite concentration or organ locality. The aim of this review is to summarize our current knowledge of how macronutrient metabolism by the gut microbiome influences human health. Metabolites to be discussed include short-chain fatty acids and alcohols (mainly yielded from monosaccharides); ammonia, branched-chain fatty acids, amines, sulfur compounds, phenols, and indoles (derived from amino acids); glycerol and choline derivatives (obtained from the breakdown of lipids); and tertiary cycling of carbon dioxide and hydrogen. Key microbial taxa and related disease states will be referred to in each case, and knowledge gaps that could contribute to our understanding of overall human wellness will be identified.

Metabolic reaction network-based recursive metabolite annotation for untargeted metabolomics.

Abstract: Large-scale metabolite annotation is a challenge in liquid chromatogram-mass spectrometry (LC-MS)-based untargeted metabolomics. Here, we develop a metabolic reaction network (MRN)-based recursive algorithm (MetDNA) that expands metabolite annotations without the need for a comprehensive standard spectral library. MetDNA is based on the rationale that seed metabolites and their reaction-paired neighbors tend to share structural similarities resulting in similar MS2 spectra. MetDNA characterizes initial seed metabolites using a small library of MS2 spectra, and utilizes their experimental MS2 spectra as surrogate spectra to annotate their reaction-paired neighbor metabolites, which subsequently serve as the basis for recursive analysis. Using different LC-MS platforms, data acquisition methods, and biological samples, we showcase the utility and versatility of MetDNA and demonstrate that about 2000 metabolites can cumulatively be annotated from one experiment. Our results demonstrate that MetDNA substantially expands metabolite annotation, enabling quantitative assessment of metabolic pathways and facilitating integrative multi-omics analysis. Untargeted metabolomics detects large numbers of metabolites but their annotation remains challenging. Here, the authors develop a metabolic reaction network-based recursive algorithm that expands metabolite annotation by taking advantage of the mass spectral similarity of reaction-paired neighbor metabolites.

A cheminformatics approach to characterize metabolomes in stable-isotope-labeled organisms

Abstract: We report a computational approach (implemented in MS-DIAL 3.0; http://prime.psc.riken.jp/ ) for metabolite structure characterization using fully 13C-labeled and non-labeled plants and LC–MS/MS. Our approach facilitates carbon number determination and metabolite classification for unknown molecules. Applying our method to 31 tissues from 12 plant species, we assigned 1,092 structures and 344 formulae to 3,604 carbon-determined metabolite ions, 69 of which were found to represent structures currently not listed in metabolome databases. A computational approach facilitates molecular formula, metabolite class, and structure assignment for plant metabolites on the basis of LC–MS analysis of fully 13C-labeled and unlabeled plants.

Structure Annotation of All Mass Spectra in Untargeted Metabolomics

Abstract: Urine metabolites are used in many clinical and biomedical studies but usually only for a few classic compounds. Metabolomics detects vastly more metabolic signals that may be used to precisely define the health status of individuals. However, many compounds remain unidentified, hampering biochemical conclusions. Here, we annotate all metabolites detected by two untargeted metabolomic assays, hydrophilic interaction chromatography (HILIC)-Q Exactive HF mass spectrometry and charged surface hybrid (CSH)-Q Exactive HF mass spectrometry. Over 9,000 unique metabolite signals were detected, of which 42% triggered MS/MS fragmentations in data-dependent mode. On the highest Metabolomics Standards Initiative (MSI) confidence level 1, we identified 175 compounds using authentic standards with precursor mass, retention time, and MS/MS matching. An additional 578 compounds were annotated by precursor accurate mass and MS/MS matching alone, MSI level 2, including a novel library specifically geared at acylcarnitines (CarniBlast). The rest of the metabolome is usually left unannotated. To fill this gap, we used the in silico fragmentation tool CSI:FingerID and the new NIST hybrid search to annotate all further compounds (MSI level 3). Testing the top-ranked metabolites in CSI:Finger ID annotations yielded 40% accuracy when applied to the MSI level 1 identified compounds. We classified all MSI level 3 annotations by the NIST hybrid search using the ClassyFire ontology into 21 superclasses that were further distinguished into 184 chemical classes. ClassyFire annotations showed that the previously unannotated urine metabolome consists of 28% derivatives of organic acids, 16% heterocyclics, and 16% lipids as major classes.

A tryptophan metabolite of the skin microbiota attenuates inflammation in patients with atopic dermatitis through the aryl hydrocarbon receptor

Abstract: Background Previous studies have revealed significant alterations in the skin microbiota of patients with atopic dermatitis (AD) not only in diversity and composition but also in function, and the tryptophan (Trp) metabolic pathway is attenuated in the skin microbiota of patients with AD. Objective We sought to assess Trp metabolites on the skin surfaces of patients with AD and to explore the function of the microbial Trp metabolites in skin inflammation in patients with AD. Methods A gel-patch method was developed to collect metabolites on the skin surface, which were then assessed by using liquid chromatography–tandem mass spectrometry. A mouse model of calcipotriol (MC903)–induced AD-like dermatitis was used to evaluate the effects of microbial metabolites on AD, and aryl hydrocarbon receptor (AhR)–null mice and keratinocyte cultures were used to investigate the mechanism. Results Major microbial metabolites of Trp were detected on the skin surfaces of healthy subjects, and the level of indole-3-aldehyde (IAId), an indole derivative of Trp catabolism, was significantly lower in lesional and nonlesional skin of patients with AD than that of healthy subjects. IAId significantly attenuated skin inflammation in mice with MC903-induced AD-like dermatitis, and this effect was blocked by an AhR antagonist and abolished in AhR-null mice. Furthermore, IAId was found to inhibit the MC903-induced expression of thymic stromal lymphopoietin in keratinocytes in vivo and in vitro, which was mediated by binding of AhR to the thymic stromal lymphopoietin promoter. Conclusion IAId, a skin microbiota–derived Trp metabolite, negatively regulated skin inflammation in patients with AD, revealing that skin microbiota play a significant functional role in the pathogenesis of AD.

Gamma-aminobutyric acid-producing lactobacilli positively affect metabolism and depressive-like behaviour in a mouse model of metabolic syndrome

Abstract: Metabolic and neuroactive metabolite production represents one of the mechanisms through which the gut microbiota can impact health. One such metabolite, gamma-aminobutyric acid (GABA), can modulate glucose homeostasis and alter behavioural patterns in the host. We previously demonstrated that oral administration of GABA-producing Lactobacillus brevis DPC6108 has the potential to increase levels of circulating insulin in healthy rats. Therefore, the objective of this study was to assess the efficacy of endogenous microbial GABA production in improving metabolic and behavioural outcomes in a mouse model of metabolic dysfunction. Diet-induced obese and metabolically dysfunctional mice received one of two GABA-producing strains, L. brevis DPC6108 or L. brevis DSM32386, daily for 12 weeks. After 8 and 10 weeks of intervention, the behavioural and metabolic profiles of the mice were respectively assessed. Intervention with both L. brevis strains attenuated several abnormalities associated with metabolic dysfunction, causing a reduction in the accumulation of mesenteric adipose tissue, increased insulin secretion following glucose challenge, improved plasma cholesterol clearance and reduced despair-like behaviour and basal corticosterone production during the forced swim test. Taken together, this exploratory dataset indicates that intervention with GABA-producing lactobacilli has the potential to improve metabolic and depressive- like behavioural abnormalities associated with metabolic syndrome in mice.

Machine-Learning-Driven Surface-Enhanced Raman Scattering Optophysiology Reveals Multiplexed Metabolite Gradients Near Cells

Abstract: The extracellular environment is a complex medium in which cells secrete and consume metabolites. Molecular gradients are thereby created near cells, triggering various biological and physiological responses. However, investigating these molecular gradients remains challenging because the current tools are ill-suited and provide poor temporal and special resolution while also being destructive. Herein, we report the development and application of a machine learning approach in combination with a surface-enhanced Raman spectroscopy (SERS) nanoprobe to measure simultaneously the gradients of at least eight metabolites in vitro near different cell lines. We found significant increase in the secretion or consumption of lactate, glucose, ATP, glutamine, and urea within 20 μm from the cells surface compared to the bulk. We also observed that cancerous cells (HeLa) compared to fibroblasts (REF52) have a greater glycolytic rate, as is expected for this phenotype. Endothelial (HUVEC) and HeLa cells exhibited signi...

A call to arms: Mustering secondary metabolites for success and survival of an opportunistic pathogen.

Abstract: Aspergillus fumigatus is a ubiquitous saprophytic mold able to grow on a diversity of material ranging from decayed organic matter in the environment to space station cupolas [1]. Yet this fungus is equally adept as a serious opportunistic pathogen, causing pulmonary aspergillosis and the more deadly invasive aspergillosis (IA). There are an estimated 3,000,000 cases of pulmonary aspergillosis annually and more than 200,000 cases of IA each year reaching a mortality rate of up to 90% in the most susceptible populations [2]. Difficulties in treating IA include delayed detection and increasing resistance to antifungal treatment. Like many opportunistic fungi, there is no one gene that makes A. fumigatus such a threatening pathogen. One unique feature of this pathogen is its arsenal of small molecules that impact disease development. Secondary metabolites are characterized as bioactive molecules of low molecular weight that are not required for growth of the organism but instead aid survival in harsh environments, resisting desiccation and UV stress and improving competition with other microbes. For A. fumigatus, these benefits extend to aiding growth not only in the environment but in the human body as well. Some secondary metabolites combat the host immune system by affecting immune cell function or by shielding the fungus against host attack, whereas others allow the fungus to acquire essential, scarce cofactors. The following synopsis of secondary metabolites produced by the opportunistic human pathogen A. fumigatus highlights how microbial metabolites, although undoubtedly evolved as environmental protectants, can impact infectious disease development (Fig 1). Although we delineate the roles of each metabolite by category for ease of discussion (e.g., “on the offensive,” “scavenging the battlefield,” “arms race”), the reader should note that each metabolite may have several biological roles for the fungus, in part illustrated in Fig 1. Open in a separate window Fig 1 Roles of Aspergillus fumigatus secondary metabolites. A list of the secondary metabolites produced by A. fumigatus, flanked by their proposed roles in the environment (right) and the host (left). Metabolites with a “?” indicate that the compound has not been examined in a niche. Bracketed numerals (e.g., [22]) indicate the reference associated with the role of the metabolite. Nidulanin A is a proposed metabolite produced by A. fumigatus, whereas all other metabolites are characterized end-product metabolites from a biosynthetic gene cluster. ROS, reactive oxygen species; TNF-α, tumor necrosis factor alpha.

Intact metabolite spectrum mining by deep learning in proton magnetic resonance spectroscopy of the brain.

Abstract: Purpose To develop a robust method for brain metabolite quantification in proton magnetic resonance spectroscopy (1 H-MRS) using a convolutional neural network (CNN) that maps in vivo brain spectra that are typically degraded by low SNR, line broadening, and spectral baseline into noise-free, line-narrowed, baseline-removed intact metabolite spectra. Methods A CNN was trained (n = 40 000) and tested (n = 5000) on simulated brain spectra with wide ranges of SNR (6.90-20.74) and linewidth (10-20 Hz). The CNN was further tested on in vivo spectra (n = 40) from five healthy volunteers with substantially different SNR, and the results were compared with those from the LCModel analysis. A Student t test was performed for the comparison. Results Using the proposed method the mean-absolute-percent-errors (MAPEs) in the estimated metabolite concentrations were 12.49% ± 4.35% for aspartate, creatine (Cr), γ-aminobutyric acid (GABA), glucose, glutamine, glutamate, glutathione (GSH), myo-Inositol (mI), N-acetylaspartate, phosphocreatine (PCr), phosphorylethanolamine, and taurine over the whole simulated spectra in the test set. The metabolite concentrations estimated from in vivo spectra were close to the reported ranges for the proposed method and the LCModel analysis except mI, GSH, and especially Cr/PCr for the LCModel analysis, and phosphorylcholine to glycerophosphorylcholine ratio (PC/GPC) for both methods. The metabolite concentrations estimated across the in vivo spectra with different SNR were less variable with the proposed method (~10% or less) than with the LCModel analysis. Conclusion The robust performance of the proposed method against low SNR may allow a subminute 1 H-MRS of human brain, which is an important technical development for clinical studies.

Remote sensing and signaling in kidney proximal tubules stimulates gut microbiome-derived organic anion secretion

Abstract: Membrane transporters and receptors are responsible for balancing nutrient and metabolite levels to aid body homeostasis. Here, we report that proximal tubule cells in kidneys sense elevated endogenous, gut microbiome-derived, metabolite levels through EGF receptors and downstream signaling to induce their secretion by up-regulating the organic anion transporter-1 (OAT1). Remote metabolite sensing and signaling was observed in kidneys from healthy volunteers and rats in vivo, leading to induced OAT1 expression and increased removal of indoxyl sulfate, a prototypical microbiome-derived metabolite and uremic toxin. Using 2D and 3D human proximal tubule cell models, we show that indoxyl sulfate induces OAT1 via AhR and EGFR signaling, controlled by miR-223. Concomitantly produced reactive oxygen species (ROS) control OAT1 activity and are balanced by the glutathione pathway, as confirmed by cellular metabolomic profiling. Collectively, we demonstrate remote metabolite sensing and signaling as an effective OAT1 regulation mechanism to maintain plasma metabolite levels by controlling their secretion.

Non-targeted metabolomics in sport and exercise science

Abstract: Metabolomics incorporates the study of metabolites that are produced and released through physiological processes at both the systemic and cellular levels. Biological compounds at the metabolite le...

Pharmacokinetics, Tissue Distribution, Metabolism, and Excretion of Naringin in Aged Rats.

Abstract: Aging is an inevitable biological process characterized by the loss of functional capacity and associated with changes in all phases of pharmacokinetic processes. Naringin, a dietary flavanone glycoside, has been proved to be beneficial for the treatment of multiple age-associated chronic diseases. To date, the pharmacokinetic processes of naringin in aged individuals are still unknown. Thus, a rapid resolution liquid chromatography tandem triple quadrupole mass spectrometry (RRLC-QQQ-MS/MS) method was established for the determination of naringin and its metabolite naringenin in rat plasma, urine, feces, and tissue homogenate. The pharmacokinetic parameters were calculated and a higher exposure of naringin and naringenin were observed in aged rats. Naringin and naringenin were mostly distributed in gastrointestinal tract, liver, kidney, lung, and trachea. Furthermore, a total of 39 flavonoid metabolites (mainly glucuronides and sulfates) and 46 microbial-derived phenolic catabolites were screened with ultra-fast liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry (UFLC-Q-TOF-MS/MS). Naringenin, hippuric acid, and 3-(4'-hydroxyphenyl)propionic acid were predominated metabolites. This study systemically investigated the pharmacokinetics, tissue distribution, metabolism, and excretion of naringin in aged rats, revealing age- and gender-related changes in the in vivo behavior of naringin. These results would be helpful for the interpretation of pharmacokinetics and pharmacodynamics of naringin in aged population.

Metabolite profiling and identification of enzymes responsible for the metabolism of mitragynine, the major alkaloid of Mitragyna speciosa (kratom)

Abstract: 1. Mitragynine is the major indole-based alkaloid of Mitragyna speciosa (kratom). Decoctions (teas) of the plant leaves have been used traditionally for cough, diarrhoea, pain, hypertension and for the treatment of opioid addiction. In the West, kratom has become increasingly utilized for mood elevation, pain treatment and as a means of self-treating opioid addiction. 2. Metabolic pathways of mitragynine were identified in human liver microsomes (HLM) and S9 fractions. A total of thirteen metabolites were identified, four oxidative metabolites and a metabolite formed by demethylation at the 9-methoxy group were the major metabolites of mitragynine. 3. The cytochrome P450 enzymes involved in the metabolism of mitragynine were identified using selective chemical inhibitors of HLM and recombinant cytochrome P450. The metabolism of mitragynine was predominantly carried out through the CYP3A4 with minor contributions by CYP2D6 and CYP2C9. The formation of five oxidative metabolites (Met2, Met4, Met6, Met8 and Met11) was catalyzed by the CYP3A4. 4. In summary, mitragynine was extensively metabolized in HLM primarily to O-demethylated and mono-oxidative metabolites. The CYP3A4 enzyme plays a predominant role in the metabolic clearance of mitragynine and also in the formation of 7-hydroxymitragynine (Met2), a known active minor alkaloid identified in the leaf material.

Metabolite profiling and genome-wide association studies reveal response mechanisms of phosphorus deficiency in maize seedling.

Abstract: Inorganic phosphorus (Pi) is an essential element in numerous metabolic reactions and signaling pathways, but the molecular details of these pathways remain largely unknown. In this study, metabolite profiles of maize (Zea mays L.) leaves and roots were compared between six low-Pi-sensitive lines and six low-Pi-tolerant lines under Pi-sufficient and Pi-deficient conditions to identify pathways and genes associated with the low-Pi stress response. Results showed that under Pi deprivation the concentrations of nucleic acids, organic acids and sugars were increased, but that the concentrations of phosphorylated metabolites, certain amino acids, lipid metabolites and nitrogenous compounds were decreased. The levels of secondary metabolites involved in plant immune reactions, including benzoxazinoids and flavonoids, were significantly different in plants grown under Pi-deficient conditions. Among them, the 11 most stable metabolites showed significant differences under low- and normal-Pi conditions based on the coefficient of variation (CV). Isoleucine and alanine were the most stable metabolites for the identification of Pi-sensitive and Pi-resistant maize inbred lines. With the significant correlation between morphological traits and metabolites, five low-Pi-responding consensus genes associated with morphological traits and simultaneously involved in metabolic pathways were mined by combining metabolites profiles and genome-wide association study (GWAS). The consensus genes induced by Pi deficiency in maize seedlings were also validated by reverse-transcription quantitative polymerase chain reaction (RT-qPCR). Moreover, these genes were further validated in a recombinant inbred line (RIL) population, in which the glucose-6-phosphate-1-epimerase encoding gene mediated yield and correlated traits to phosphorus availability. Together, our results provide a framework for understanding the metabolic processes underlying Pi-deficient responses and give multiple insights into improving the efficiency of Pi use in maize.

Thermopriming reprograms metabolic homeostasis to confer heat tolerance.

Abstract: Heat stress threatens agriculture worldwide. Plants acquire heat stress tolerance through priming, which establishes stress memory during mild or severe transient heat stress. Such induced thermotolerance restructures metabolic networks and helps maintain metabolic homeostasis under heat stress. Here, we used an electrospray ionization mass spectrometry-based platform to explore the composition and dynamics of the metabolome of Arabidopsis thaliana under heat stress and identify metabolites involved in thermopriming. Primed plants performed better than non-primed plants under severe heat stress due to altered energy pathways and increased production of branched-chain amino acids, raffinose family oligosaccharides (RFOs), lipolysis products, and tocopherols. These metabolites serve as osmolytes, antioxidants and growth precursors to help plants recover from heat stress, while lipid metabolites help protect membranes against heat stress. The carbohydrate (e.g., sucrose and RFOs) and lipid superpathway metabolites showed the most significant increases. Under heat stress, there appears to be crosstalk between carbohydrate metabolism (i.e., the thermomemory metabolites stachyose, galactinol, and raffinose) and tyrosine metabolism towards the production of the thermomemory metabolite salidroside, a phenylethanoid glycoside. Crosstalk occurs between two glycerophospholipid pathways (the biosynthetic pathways of the thermomemory metabolite S-adenosyl-L-homocysteine and the terpenoid backbone) and the δ-tocopherol (chloroplast lipid) pathway, which favors the production of glycine betaine and other essential tocopherols, respectively, compounds which are essential for abiotic stress tolerance in plants. Therefore, metabolomic analysis can provide comprehensive insights into the metabolites involved in stress responses, which could facilitate plant breeding to maximize crop yields under adverse conditions.

The Saliva Metabolome in Association to Oral Health Status.

Abstract: Periodontitis is one of the most prevalent oral diseases worldwide and is caused by multifactorial interactions between host and oral bacteria. Altered cellular metabolism of host and microbes releases a number of intermediary end products known as metabolites. There is an increasing interest in identifying metabolites from oral fluids such as saliva to widen the understanding of the complex pathogenesis of periodontitis. It is believed that some metabolites might serve as indicators toward early detection and screening of periodontitis and perhaps even for monitoring its prognosis in the future. Because contemporary periodontal screening methods are deficient, there is an urgent need for novel approaches in periodontal screening procedures. To this end, we associated oral parameters (clinical attachment level, periodontal probing depth, supragingival plaque, supragingival calculus, number of missing teeth, and removable denture) with a large set of salivary metabolites ( n = 284) obtained by mass spectrometry among a subsample ( n = 909) of nondiabetic participants from the Study of Health in Pomerania (SHIP-Trend-0). Linear regression analyses were performed in age-stratified groups and adjusted for potential confounders. A multifaceted image of associated metabolites ( n = 107) was revealed with considerable differences according to age groups. In the young (20 to 39 y) and middle-aged (40 to 59 y) groups, metabolites were predominantly associated with periodontal variables, whereas among the older subjects (≥60 y), tooth loss was strongly associated with metabolite levels. Metabolites associated with periodontal variables were clearly linked to tissue destruction, host defense mechanisms, and bacterial metabolism. Across all age groups, the bacterial metabolite phenylacetate was significantly associated with periodontal variables. Our results revealed alterations of the salivary metabolome in association with age and oral health status. Among our comprehensive panel of metabolites, periodontitis was significantly associated with the bacterial metabolite phenylacetate, a promising substance for further biomarker research.

Uncovering sperm metabolome to discover biomarkers for bull fertility

Abstract: Subfertility decreases the efficiency of the cattle industry because artificial insemination employs spermatozoa from a single bull to inseminate thousands of cows. Variation in bull fertility has been demonstrated even among those animals exhibiting normal sperm numbers, motility, and morphology. Despite advances in research, molecular and cellular mechanisms underlying the causes of low fertility in some bulls have not been fully elucidated. In this study, we investigated the metabolic profile of bull spermatozoa using non-targeted metabolomics. Statistical analysis and bioinformatic tools were employed to evaluate the metabolic profiles high and low fertility groups. Metabolic pathways associated with the sperm metabolome were also reported. A total of 22 distinct metabolites were detected in spermatozoa from bulls with high fertility (HF) or low fertility (LF) phenotype. The major metabolite classes of bovine sperm were organic acids/derivatives and fatty acids/conjugates. We demonstrated that the abundance ratios of five sperm metabolites were statistically different between HF and LF groups including gamma-aminobutyric acid (GABA), carbamate, benzoic acid, lactic acid, and palmitic acid. Metabolites with different abundances in HF and LF bulls had also VIP scores of greater than 1.5 and AUC- ROC curves of more than 80%. In addition, four metabolic pathways associated with differential metabolites namely alanine, aspartate and glutamate metabolism, β-alanine metabolism, glycolysis or gluconeogenesis, and pyruvate metabolism were also explored. This is the first study aimed at ascertaining the metabolome of spermatozoa from bulls with different fertility phenotype using gas chromatography-mass spectrometry. We identified five metabolites in the two groups of sires and such molecules can be used, in the future, as key indicators of bull fertility.

An untargeted fecal and urine metabolomics analysis of the interplay between the gut microbiome, diet and human metabolism in Indian and Chinese adults.

Abstract: Gut microbiome plays a vital role in human health. Human fecal and urine metabolome could provide a functional readout of gut microbial metabolism as well as its interaction with host and diet. However, this relationship still needs to be fully characterized. We established an untargeted GC-MS metabolomics method which enabled the detection of 122 and 86 metabolites including amino acids, phenolics, indoles, carbohydrates, sugars and metabolites of microbial origin from fecal and urine samples respectively. 41 compounds were confirmed using external standards. Next, we compared the fecal and urine metabolome of 16 healthy Indian and Chinese adults, ages 22–35 years, using a combined GC-MS and LC-MS approach. We showed dietary habit or ethnicity wise grouping of urine and fecal metabolite profiles of Indian and Chinese adults. Our analysis revealed 53 differentiating metabolites including higher abundance of amino acids and phenolics in Chinese and higher abundance of fatty acids, glycocholic acid, metabolites related to tryptophan metabolism in Indian adults. Correlation analysis showed a strong association of metabolites with gut bacterial profiles of the same subjects in the genus and species level. Thus, our results suggest that gut bacterial compositional changes could be eventually monitored and probed using a metabolomics approach.

The Colorful Diversity of Thyroid Hormone Metabolites

Abstract: Since the discovery of L-thyroxine, the main secretory product of the thyroid gland, and its major metabolite T3, which exerts the majority of thyroid hormone action via ligand-dependent modulation of the function of T3 receptors in nuclei, mitochondria, and other subcellular compartments, various other T4-derived endogenous metabolites have been identified in blood and tissues of humans, animals, and early protochordates. This review addresses major historical milestones and experimental findings resulting in the discovery of the key enzymes of thyroid hormone metabolism, the three selenoprotein deiodinases, as well as the decarboxylases and amine oxidases involved in formation and degradation of recently identified endogenous thyroid hormone metabolites, i.e. 3-iodothyronamine and 3-thyroacetic acid. The concerted action of deiodinases 2 and 3 in regulation of local T3 availability is discussed. Special attention is given to the role of the thyromimetic “hot” metabolite 3,5-T2 and the “cool” 3-iodothyronamine, especially after administration of pharmacological doses of these endogenous thyroid hormone metabolites in various animal experimental models. In addition, available information on the biological roles of the two major acetic acid derivatives of thyroid hormones, i.e. Tetrac and Triac, as well as sulfated metabolites of thyroid hormones is reviewed. This review addresses the consequences of the existence of this broad spectrum of endogenous thyroid hormone metabolites, the “thyronome,” beyond the classical thyroid hormone profile comprising T4, T3, and rT3 for appropriate analytical coverage and clinical diagnostics using mass spectrometry versus immunoassays for determination of total and free concentrations of thyroid hormone metabolites in blood and tissues.