Fate of thianthrene in biological systems.

1. Thianthrene is a sulfur-containing tricyclic molecule distributed widely within the macrostructure of hydrocarbon fossil fuels. Identified nearly 150 years ago, its chemistry has been widely explored leading to insights into reaction mechanisms and radical ion formation. 2. It has been claimed to have therapeutic application in the treatment of dermal infections and to interfere with enzyme and nucleic acid function, but appears to have little toxicity. 3. Following its oral administration to the rat, the majority remained within the gastrointestinal tract. After three days, about 88% was detected in the combined excreta with the remainder still within the animal. It is readily taken up into fish from the surrounding aqueous environment and has been placed within the "bioaccumulative category" to be regarded with concern. 4. Mammalian metabolism appeared to be restricted to ring carbon oxidation and subsequent glucuronic acid conjugation. Small amounts of sulfoxide and disulfoxide were also formed. No ring degradation was evident. Microorganisms similarly undertook aromatic ring hydroxylation but were able also to rupture the ring system by attacking the carbon-sulfur linkages and thereby degrading the molecule.

Topological analysis of metabolic networks integrating co-segregating transcriptomes and metabolomes in type 2 diabetic rat congenic series.

BACKGROUND: The genetic regulation of metabolic phenotypes (i.e., metabotypes) in type 2 diabetes mellitus occurs through complex organ-specific cellular mechanisms and networks contributing to impaired insulin secretion and insulin resistance. Genome-wide gene expression profiling systems can dissect the genetic contributions to metabolome and transcriptome regulations. The integrative analysis of multiple gene expression traits and metabolic phenotypes (i.e., metabotypes) together with their underlying genetic regulation remains a challenge. Here, we introduce a systems genetics approach based on the topological analysis of a combined molecular network made of genes and metabolites identified through expression and metabotype quantitative trait locus mapping (i.e., eQTL and mQTL) to prioritise biological characterisation of candidate genes and traits. METHODS: We used systematic metabotyping by 1H NMR spectroscopy and genome-wide gene expression in white adipose tissue to map molecular phenotypes to genomic blocks associated with obesity and insulin secretion in a series of rat congenic strains derived from spontaneously diabetic Goto-Kakizaki (GK) and normoglycemic Brown-Norway (BN) rats. We implemented a network biology strategy approach to visualize the shortest paths between metabolites and genes significantly associated with each genomic block. RESULTS: Despite strong genomic similarities (95-99 %) among congenics, each strain exhibited specific patterns of gene expression and metabotypes, reflecting the metabolic consequences of series of linked genetic polymorphisms in the congenic intervals. We subsequently used the congenic panel to map quantitative trait loci underlying specific mQTLs and genome-wide eQTLs. Variation in key metabolites like glucose, succinate, lactate, or 3-hydroxybutyrate and second messenger precursors like inositol was associated with several independent genomic intervals, indicating functional redundancy in these regions. To navigate through the complexity of these association networks we mapped candidate genes and metabolites onto metabolic pathways and implemented a shortest path strategy to highlight potential mechanistic links between metabolites and transcripts at colocalized mQTLs and eQTLs. Minimizing the shortest path length drove prioritization of biological validations by gene silencing. CONCLUSIONS: These results underline the importance of network-based integration of multilevel systems genetics datasets to improve understanding of the genetic architecture of metabotype and transcriptomic regulation and to characterize novel functional roles for genes determining tissue-specific metabolism.

S-carboxymethyl-L-cysteine.

S-carboxymethyl-L-cysteine, the side-chain carboxymethyl derivative of the sulfur-containing amino acid, cysteine, has been known and available for almost 80 years. During this time, it has been put to a variety of uses, but it is within the field of respiratory medicine that, presently, it has found a clinical niche. Early studies indicated that this compound underwent a rather simplistic, predictable pattern of metabolism, whereas later investigations alluded to more subtle interactions with the pathways of intermediary metabolism, as may be expected for an amino acid derivative. In addition, suggestions of polymorphic influences and circadian rhythms within metabolic profiles have emerged. These latter factors may underlie the conflicting reports regarding the therapeutic efficacy of this compound: that it appears to work well in some patients, but has no measurable effects in others. The relevant literature pertaining to the fate of this compound within living systems has been reviewed and a comprehensive précis advanced. Hopefully, this article will serve as a vade mecum for those interested in S-carboxymethyl-L-cysteine and as a catalyst for future research.

Untargeted metabolome quantitative trait locus mapping associates variation in urine glycerate to mutant glycerate kinase.

With successes of genome-wide association studies, molecular phenotyping systems are developed to identify genetically determined disease-associated biomarkers. Genetic studies of the human metabolome are emerging but exclusively apply targeted approaches, which restricts the analysis to a limited number of well-known metabolites. We have developed novel technical and statistical methods for systematic and automated quantification of untargeted NMR spectral data designed to perform robust and accurate quantitative trait locus (QTL) mapping of known and previously unreported molecular compounds of the metabolome. For each spectral peak, six summary statistics were calculated and independently tested for evidence of genetic linkage in a cohort of F2 (129S6xBALB/c) mice. The most significant evidence of linkages were obtained with NMR signals characterizing the glycerate (LOD10-42) at the mutant glycerate kinase locus, which demonstrate the power of metabolomics in quantitative genetics to identify the biological function of genetic variants. These results provide new insights into the resolution of the complex nature of metabolic regulations and novel analytical techniques that maximize the full utilization of metabolomic spectra in human genetics to discover mappable disease-associated biomarkers.

Racemates revisited: heterochiral assemblies and the example of DL-thalidomide.

The existence of racemic compounds, comprised of pairs of opposite enantiomers as discrete molecular entities, has been accepted for over a century. However, their ability to remain as associated dimers when in solution is uncertain, if not generally doubted. In this article, data has been assembled to provide evidence for the presence of intact dimeric heterochiral assemblies in solution and presents DL-thalidomide as a probable example of this phenomenon.

Metabolic profiling reveals a contribution of gut microbiota to fatty liver phenotype in insulin-resistant mice.

Here, we study the intricate relationship between gut microbiota and host cometabolic phenotypes associated with dietary-induced impaired glucose homeostasis and nonalcoholic fatty liver disease (NAFLD) in a mouse strain (129S6) known to be susceptible to these disease traits, using plasma and urine metabotyping, achieved by (1)H NMR spectroscopy. Multivariate statistical modeling of the spectra shows that the genetic predisposition of the 129S6 mouse to impaired glucose homeostasis and NAFLD is associated with disruptions of choline metabolism, i.e., low circulating levels of plasma phosphatidylcholine and high urinary excretion of methylamines (dimethylamine, trimethylamine, and trimethylamine-N-oxide), coprocessed by symbiotic gut microbiota and mammalian enzyme systems. Conversion of choline into methylamines by microbiota in strain 129S6 on a high-fat diet reduces the bioavailability of choline and mimics the effect of choline-deficient diets, causing NAFLD. These data also indicate that gut microbiota may play an active role in the development of insulin resistance.