PubMed

Metabolic profiling as a tool for prioritizing antimicrobial compounds. J Ind Microbiol Biotechnol. 2015 Sep 3; Authors: Wu C, Choi YH, van Wezel GP Abstract Metabolomics is an analytical technique that allows scientists to globally profile low molecular weight metabolites between samples in a medium- or high-throughput environment. Different biological samples are statistically analyzed and correlated to a bioactivity of interest, highlighting differentially produced compounds as potential biomarkers. Here, we review NMR- and MS-based metabolomics as technologies to facilitate the identification of novel antimicrobial natural products from microbial sources. Approaches to elicit the production of poorly expressed (cryptic) molecules are thereby a key to allow statistical analysis of samples to identify bioactive markers, while connection of compounds to their biosynthetic gene cluster is a determining step in elucidating the biosynthetic pathway and allows downstream process optimization and upscaling. The review focuses on approaches built around NMR-based metabolomics, which enables efficient dereplication and guided fractionation of (antimicrobial) compounds. PMID: 26335567 [PubMed - as supplied by publisher]

Scientific workflow optimization for improved peptide and protein identification. BMC Bioinformatics. 2015;16(1):284 Authors: Holl S, Mohammed Y, Zimmermann O, Palmblad M Abstract BACKGROUND: Peptide-spectrum matching is a common step in most data processing workflows for mass spectrometry-based proteomics. Many algorithms and software packages, both free and commercial, have been developed to address this task. However, these algorithms typically require the user to select instrument- and sample-dependent parameters, such as mass measurement error tolerances and number of missed enzymatic cleavages. In order to select the best algorithm and parameter set for a particular dataset, in-depth knowledge about the data as well as the algorithms themselves is needed. Most researchers therefore tend to use default parameters, which are not necessarily optimal. RESULTS: We have applied a new optimization framework for the Taverna scientific workflow management system ( http://ms-utils.org/Taverna_Optimization.pdf ) to find the best combination of parameters for a given scientific workflow to perform peptide-spectrum matching. The optimizations themselves are non-trivial, as demonstrated by several phenomena that can be observed when allowing for larger mass measurement errors in sequence database searches. On-the-fly parameter optimization embedded in scientific workflow management systems enables experts and non-experts alike to extract the maximum amount of information from the data. The same workflows could be used for exploring the parameter space and compare algorithms, not only for peptide-spectrum matching, but also for other tasks, such as retention time prediction. CONCLUSION: Using the optimization framework, we were able to learn about how the data was acquired as well as the explored algorithms. We observed a phenomenon identifying many ammonia-loss b-ion spectra as peptides with N-terminal pyroglutamate and a large precursor mass measurement error. These insights could only be gained with the extension of the common range for the mass measurement error tolerance parameters explored by the optimization framework. PMID: 26335531 [PubMed - as supplied by publisher]

Laboratory Medicine Meets Precision Medicine: the Paradigm of Metabolomics in Perinatology. Proposals from the 4th International Conference on Neonatal and Pediatric Laboratory Medicine. Clin Chim Acta. 2015 Aug 31; Authors: Mussap M, Ferrari M, Fanos V PMID: 26335287 [PubMed - as supplied by publisher]

A correction method for systematic error in (1)H-NMR time-course data validated through stochastic cell culture simulation. BMC Syst Biol. 2015;9(1):51 Authors: Sokolenko S, Aucoin MG Abstract BACKGROUND: The growing ubiquity of metabolomic techniques has facilitated high frequency time-course data collection for an increasing number of applications. While the concentration trends of individual metabolites can be modeled with common curve fitting techniques, a more accurate representation of the data needs to consider effects that act on more than one metabolite in a given sample. To this end, we present a simple algorithm that uses nonparametric smoothing carried out on all observed metabolites at once to identify and correct systematic error from dilution effects. In addition, we develop a simulation of metabolite concentration time-course trends to supplement available data and explore algorithm performance. Although we focus on nuclear magnetic resonance (NMR) analysis in the context of cell culture, a number of possible extensions are discussed. RESULTS: Realistic metabolic data was successfully simulated using a 4-step process. Starting with a set of metabolite concentration time-courses from a metabolomic experiment, each time-course was classified as either increasing, decreasing, concave, or approximately constant. Trend shapes were simulated from generic functions corresponding to each classification. The resulting shapes were then scaled to simulated compound concentrations. Finally, the scaled trends were perturbed using a combination of random and systematic errors. To detect systematic errors, a nonparametric fit was applied to each trend and percent deviations calculated at every timepoint. Systematic errors could be identified at time-points where the median percent deviation exceeded a threshold value, determined by the choice of smoothing model and the number of observed trends. Regardless of model, increasing the number of observations over a time-course resulted in more accurate error estimates, although the improvement was not particularly large between 10 and 20 samples per trend. The presented algorithm was able to identify systematic errors as small as 2.5 % under a wide range of conditions. CONCLUSION: Both the simulation framework and error correction method represent examples of time-course analysis that can be applied to further developments in (1)H-NMR methodology and the more general application of quantitative metabolomics. PMID: 26335002 [PubMed - as supplied by publisher]

Intracellular Survival of Leishmania major Depends on Uptake and Degradation of Extracellular Matrix Glycosaminoglycans by Macrophages. PLoS Pathog. 2015 Sep;11(9):e1005136 Authors: Naderer T, Heng J, Saunders EC, Kloehn J, Rupasinghe TW, Brown TJ, McConville MJ Abstract Leishmania parasites replicate within the phagolysosome compartment of mammalian macrophages. Although Leishmania depend on sugars as a major carbon source during infections, the nutrient composition of the phagolysosome remains poorly described. To determine the origin of the sugar carbon source in macrophage phagolysosomes, we have generated a N-acetylglucosamine acetyltransferase (GNAT) deficient Leishmania major mutant (∆gnat) that is auxotrophic for the amino sugar, N-acetylglucosamine (GlcNAc). This mutant was unable to grow or survive in ex vivo infected macrophages even when macrophages were cultivated in presence of exogenous GlcNAc. In contrast, the L. major ∆gnat mutant induced normal skin lesions in mice, suggesting that these parasites have access to GlcNAc in tissue macrophages. Intracellular growth of the mutant in ex vivo infected macrophages was restored by supplementation of the macrophage medium with hyaluronan, a GlcNAc-rich extracellular matrix glycosaminoglycan. Hyaluronan is present and constitutively turned-over in Leishmania-induced skin lesions and is efficiently internalized into Leishmania containing phagolysosomes. These findings suggest that the constitutive internalization and degradation of host glycosaminoglycans by macrophages provides Leishmania with essential carbon sources, creating a uniquely favorable niche for these parasites. PMID: 26334531 [PubMed - as supplied by publisher]

The elementome of calcium-based urinary stones and its role in urolithiasis. Nat Rev Urol. 2015 Sep 1; Authors: Ramaswamy K, Killilea DW, Kapahi P, Kahn AJ, Chi T, Stoller ML Abstract Urolithiasis affects around 10% of the US population with an increasing rate of prevalence, recurrence and penetrance. The causes for the formation of most urinary calculi remain poorly understood, but obtaining the chemical composition of these stones might help identify key aspects of this process and new targets for treatment. The majority of urinary stones are composed of calcium that is complexed in a crystalline matrix with organic and inorganic components. Surprisingly, mitigation of urolithiasis risk by altering calcium homeostasis has not been very effective. Thus, studies to identify other therapeutic stone-specific targets, using proteomics, metabolomics and microscopy techniques, have been conducted, revealing a high level of complexity. The data suggest that numerous metals other than calcium and many nonmetals are present within calculi at measurable levels and several have distinct distribution patterns. Manipulation of the levels of some of these elemental components of calcium-based stones has resulted in clinically beneficial changes in stone chemistry and rate of stone formation. The elementome-the full spectrum of elemental content-of calcium-based urinary calculi is emerging as a new concept in stone research that continues to provide important insights for improved understanding and prevention of urinary stone disease. PMID: 26334088 [PubMed - as supplied by publisher]

Related Articles Metabolomics Biomarkers for Breast Cancer. Pathobiology. 2015 Sep;82(3-4):153-65 Authors: Günther UL Abstract Metabolomics represents a more recent addition to the range of omics tools, which are increasingly used in clinical applications. By measuring the composition of small molecules in tissues, blood or urine, it provides a sensitive molecular readout often associated with disease and its states, especially in cancer. Changes in metabolism related to cancer are increasingly well understood and are seen as a major hallmark of cancer. This review covers metabolomics used in human breast cancers, with a focus on its application in clinical diagnostics. There are clear indications that metabolomics could be a useful addition to currently established clinical diagnostic tools for breast cancer, including the possibility to detect cancer and to predict treatment responses and survival rates from blood and tissue samples. PMID: 26330356 [PubMed - in process]

Related Articles Translational metabolomics in cancer research. Biomark Med. 2015 Sep 1; Authors: Snyder NW, Mesaros C, Blair IA Abstract Over the last decade there has been a bottleneck in the introduction of new validated cancer metabolic biomarkers into clinical practice. Unfortunately, there are no biomarkers with adequate sensitivity for the early detection of cancer, and there remain a reliance on cancer antigens for monitoring treatment. The need for new diagnostics has led to the exploration of untargeted metabolomics for discovery of early biomarkers of specific cancers and targeted metabolomics to elucidate mechanistic aspects of tumor progression. The successful translation of such strategies to the treatment of cancer would allow earlier intervention to improve survival. We have reviewed the methodology that is being used to achieve these goals together with recent advances in implementing translational metabolomics in cancer. PMID: 26329905 [PubMed - as supplied by publisher]

Related Articles Metabolic profiling and enzyme analyses indicate a potential role of antioxidant systems in complementing glyphosate resistance in an Amaranthus palmeri biotype. J Agric Food Chem. 2015 Sep 2; Authors: Maroli AS, Nandula V, Dayan FE, Duke S, Gerard P, Tharayil N Abstract Metabolomics and biochemical assays were employed to identify physiological perturbations induced by glyphosate in a susceptible (S) and resistant (R) biotype of Amaranthus palmeri. At 8 h after treatment (HAT), shikimic acid accumulated in both R- and S-biotypes in response to glyphosate application, which was accompanied by an increase in organic acids and aromatic amino acids in the R-biotype and an increase in sugars and branched-chain amino acids in the S-biotype. However, by 80 HAT the metabolite pool of glyphosate-treated R-biotype was similar to that of the water-treated control S and R-biotype, indicating physiological recovery. Furthermore, glyphosate-treated R-biotype had lower reactive oxygen species (ROS) damage, higher ROS scavenging activity, and higher levels of secondary compounds of the shikimate pathway. Thus metabolomics, in conjunction with biochemical assays, indicate that glyphosate induced metabolic perturbations are not limited to shikimate pathway, and the oxidant quenching efficiency could potentially complement the glyphosate resistance in this R-biotype. PMID: 26329798 [PubMed - as supplied by publisher]

Related Articles Investigation on the antidepressant effect of sea buckthorn seed oil through the GC-MS-based metabolomics approach coupled with multivariate analysis. Food Funct. 2015 Sep 2; Authors: Tian JS, Liu CC, Xiang H, Zheng XF, Peng GJ, Zhang X, Du GH, Qin XM Abstract Depression is one of the prevalent and serious mental disorders and the number of depressed patients has been on the rise globally during the recent decades. Sea buckthorn seed oil from traditional Chinese medicine (TCM) is edible and has been widely used for treatment of different diseases for a long time. However, there are few published reports on the antidepressant effect of sea buckthorn seed oil. With the objective of finding potential biomarkers of the therapeutic response of sea buckthorn seed oil in chronic unpredictable mild stress (CUMS) rats, urine metabolomics based on gas chromatography-mass spectrometry (GC-MS) coupled with multivariate analysis was applied. In this study, we discovered a higher level of pimelic acid as well as palmitic acid and a lower level of suberic acid, citrate, phthalic acid, cinnamic acid and Sumiki's acid in urine of rats exposed to CUMS procedures after sea buckthorn seed oil was administered. These changes of metabolites are involved in energy metabolism, fatty acid metabolism and other metabolic pathways as well as in the synthesis of neurotransmitters and it is helpful to facilitate the efficacy evaluation and mechanism elucidating the effect of sea buckthorn seed oil for depression management. PMID: 26328874 [PubMed - as supplied by publisher]

Related Articles DnsID in MyCompoundID for Rapid Identification of Dansylated Amine- and Phenol-Containing Metabolites in LC-MS-Based Metabolomics. Anal Chem. 2015 Sep 1; Authors: Huan T, Wu Y, Tang C, Lin G, Li L Abstract High-performance chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) is an enabling technology based on rational design of labeling reagents to target a class of metabolites sharing the same functional group (e.g., all the amine-containing metabolites or the amine submetabolome) to provide concomitant improvements in metabolite separation, detection and quantification. However, identification of labeled metabolites remains to be an analytical challenge. In this work, we describe a library of labeled standards and a search method for metabolite identification in CIL LC-MS. The current library consists of 273 unique metabolites, mainly amines and phenols, that are individually labeled by dansylation (Dns). Some of them produced more than one Dns-derivative (isomers or multiple labeled products), resulting in a total of 315 dansyl compounds in the library. These metabolites cover 42 metabolic pathways, allowing the possibility of probing their changes in metabolomics studies. Each labeled metabolite contains three searchable parameters: molecular ion mass, MS/MS spectrum and retention time (RT). To overcome RT variations caused by experimental conditions used, we have developed a calibration method to normalize RTs of labeled metabolites using a mixture of RT calibrants. A search program, DnsID, has been developed in www.MyCompoundID.org for automated identification of dansyl labeled metabolites in a sample based on matching one or more of the three parameters with those of the library standards. Using human urine as an example, we illustrate the workflow and analytical performance of this method for metabolite identification. This freely accessible resource is expandable by adding more amine and phenol standards in the future. In addition, the same strategy should be applicable for developing other labeled standards libraries to cover different classes of metabolites for comprehensive metabolomics using CIL LC-MS. PMID: 26327437 [PubMed - as supplied by publisher]

Related Articles Comparative investigations on the biological effects of As (III) and As (V) in clam Ruditapes philippinarum using multiple biomarkers. Fish Shellfish Immunol. 2015 Aug 29; Authors: Ji C, Xu H, Wang Q, Zhao J, Wu H Abstract Inorganic arsenic is a known pollutant with two chemical forms, arsenite (As (III)) and arsenate (As (V)), in marine environment. Clam Ruditapes philippinarum is an important fishery species along the Bohai coast. In this study, the biological effects induced by the two arsenic chemical forms (arsenite and arsenate) were compared using multiple biochemical indices in the digestive glands of clam R. philippinarum. The production of reactive oxygen species, antioxidant enzyme activities and metabolic responses exhibited that both As (III) and As (V) induced immune, oxidative and osmotic stresses in clam digestive glands. The differential metabolic biomarkers, histidine and taurine, indicated the differential responsive mechanisms in osmotic regulation in clam digestive glands. In addition, both arsenic treatments enhanced the anaerobiosis metabolism in clam digestive glands. Overall, this work illustrated that arsenite and arsenate induced similar biological effects in clams, which might be accounted for the biological transformation of arsenate to arsenite in clams. PMID: 26327115 [PubMed - as supplied by publisher]

Related Articles Reviews 2015. Electrophoresis. 2015 Jan;36(1):1 Authors: El Rassi Z PMID: 25556751 [PubMed - indexed for MEDLINE]

Related Articles Dehalococcoides mccartyi strain DCMB5 Respires a broad spectrum of chlorinated aromatic compounds. Appl Environ Microbiol. 2015 Jan;81(2):587-96 Authors: Pöritz M, Schiffmann CL, Hause G, Heinemann U, Seifert J, Jehmlich N, von Bergen M, Nijenhuis I, Lechner U Abstract Polyhalogenated aromatic compounds are harmful environmental contaminants and tend to persist in anoxic soils and sediments. Dehalococcoides mccartyi strain DCMB5, a strain originating from dioxin-polluted river sediment, was examined for its capacity to dehalogenate diverse chloroaromatic compounds. Strain DCMB5 used hexachlorobenzenes, pentachlorobenzenes, all three tetrachlorobenzenes, and 1,2,3-trichlorobenzene as well as 1,2,3,4-tetra- and 1,2,4-trichlorodibenzo-p-dioxin as electron acceptors for organohalide respiration. In addition, 1,2,3-trichlorodibenzo-p-dioxin and 1,3-, 1,2-, and 1,4-dichlorodibenzo-p-dioxin were dechlorinated, the latter to the nonchlorinated congener with a remarkably short lag phase of 1 to 4 days following transfer. Strain DCMB5 also dechlorinated pentachlorophenol and almost all tetra- and trichlorophenols. Tetrachloroethene was dechlorinated to trichloroethene and served as an electron acceptor for growth. To relate selected dechlorination activities to the expression of specific reductive dehalogenase genes, the proteomes of 1,2,3-trichlorobenzene-, pentachlorobenzene-, and tetrachloroethene-dechlorinating cultures were analyzed. Dcmb_86, an ortholog of the chlorobenzene reductive dehalogenase CbrA, was the most abundant reductive dehalogenase during growth with each electron acceptor, suggesting its pivotal role in organohalide respiration of strain DCMB5. Dcmb_1041 was specifically induced, however, by both chlorobenzenes, whereas 3 putative reductive dehalogenases, Dcmb_1434, Dcmb_1339, and Dcmb_1383, were detected only in tetrachloroethene-grown cells. The proteomes also harbored a type IV pilus protein and the components for its assembly, disassembly, and secretion. In addition, transmission electron microscopy of DCMB5 revealed an irregular mode of cell division as well as the presence of pili, indicating that pilus formation is a feature of D. mccartyi during organohalide respiration. PMID: 25381236 [PubMed - indexed for MEDLINE]

Related Articles Discovery of a novel amino acid racemase through exploration of natural variation in Arabidopsis thaliana. Proc Natl Acad Sci U S A. 2015 Aug 31; Authors: Strauch RC, Svedin E, Dilkes B, Chapple C, Li X Abstract Plants produce diverse low-molecular-weight compounds via specialized metabolism. Discovery of the pathways underlying production of these metabolites is an important challenge for harnessing the huge chemical diversity and catalytic potential in the plant kingdom for human uses, but this effort is often encumbered by the necessity to initially identify compounds of interest or purify a catalyst involved in their synthesis. As an alternative approach, we have performed untargeted metabolite profiling and genome-wide association analysis on 440 natural accessions of Arabidopsis thaliana. This approach allowed us to establish genetic linkages between metabolites and genes. Investigation of one of the metabolite-gene associations led to the identification of N-malonyl-d-allo-isoleucine, and the discovery of a novel amino acid racemase involved in its biosynthesis. This finding provides, to our knowledge, the first functional characterization of a eukaryotic member of a large and widely conserved phenazine biosynthesis protein PhzF-like protein family. Unlike most of known eukaryotic amino acid racemases, the newly discovered enzyme does not require pyridoxal 5'-phosphate for its activity. This study thus identifies a new d-amino acid racemase gene family and advances our knowledge of plant d-amino acid metabolism that is currently largely unexplored. It also demonstrates that exploitation of natural metabolic variation by integrating metabolomics with genome-wide association is a powerful approach for functional genomics study of specialized metabolism. PMID: 26324904 [PubMed - as supplied by publisher]

Related Articles [Chemical comparison of different Farfarae Flos by NMR-based metabolomic approaches]. Yao Xue Xue Bao. 2015 May;50(5):599-604 Authors: Zhang ZZ, Zhi HJ, Qin XM, Li ZY Abstract 1H NMR-based metabolomic approach combined with multivariate statistical analysis was used to evaluate the quality of 21 Farfarae Flos (FF) samples from different growth regions. Principal component analysis showed that wild and cultivated FF could be separated clearly, suggesting a big chemical difference existed between them. Supervised PLS-DA analysis indicated that the wild samples showed higher levels of secondary metabolites, such as bauer-7-ene-3β, 16α-diol, chlorogenic acid, rutin, 7-(3'-ethylcrotonoyloxy)-1α-(2'-methyl-butyryloxy)-3, 14-dehydro-Z-notonipetranone (EMDNT), tussilagone, β-sitosterol and sitosterone. This is consistent with traditional experience that the quality of wild samples are better than that of cultivated ones. The content of pyrrolizidine alkaloids senkirkine also differed greatly among samples from different habitats. The Pearson correlation analysis showed that senkirkine is positively correlated with 4, 5-O-dicaffeoylquinic acid, 3,5-O-dicaffeoylquinic acid, 3,4-O-dicaffeoylquinic acid, rutin, kampferol analogues, to a statistically significant extent. The correlation between the toxic compounds and the bioactive components in FF should be further studied. PMID: 26234144 [PubMed - indexed for MEDLINE]

Related Articles [Metabolomic approach to evaluating the effect of the mixed decoction of kelp and licorice on system metabolism of SD rats]. Yao Xue Xue Bao. 2015 Mar;50(3):312-8 Authors: Sun RB, Yu XY, Mao Y, Ge C, Yang Na, A JY, Tang YP, Duan JA, Ma ZT, Wu XT, Zhu XX, Wang GJ Abstract The aim of the study is to evaluate the effects of the single and mixed decoction of Thallus laminariae (kelp) and Glycyrrhiza glabra (licorice) on the metabolism and their difference. The mixed decoction of kelp and licorice and the single decoction were made and intragastrically administered to the SD rats. The effect on system metabolism, the toxicity of liver and kidney were assessed by GC-MS profiling of the endogenous molecules in serum, routine biochemical assays and histographic inspection of tissues from SD rats, separately. The mixed decoction of kelp and licorice induced more obvious pathological abnormalities in SD rats than a single decoction of kelp, while the extracts of licorice did not show any pathological change. Neither the mixed, nor the single decoction showed abnormal histopathology. After intragastric administration of extracts for 5 days, the mixed decoction induced a decrease of ALT (no significant change in the groups of single decoction) and an increase of BUN (so did the single decoction of kelp). Metabolomic profile of the molecules in serum revealed that the metabolic patterns were all obviously affected for the three groups, i.e., the mixed and single decoction of kelp and licorice. The rats given with the single decoction of kelp showed a similar pattern to that of the mixed decoction, indicating that the kelp primarily contributed the perturbation of metabolism for the mixed decoction. All three groups induced a decrease of branched chain amino acids, TCA cycle intermediates and glycolysis intermediates (e.g., pyruvic acid and lactic acid) and an increase of 3-hydroxybutyric acid. Kelp decoction showed stronger potential in reducing TCA cycle intermediates and glycolysis intermediates than the other two groups, while the levels of branched chain amino acids were the lowest after licorice extracts were given. These results suggested that the effect of the mixed decoction on metabolism was closely associated with both kelp and licorice. The continuous administration of single decoction of kelp and the mixed decoction of licorice and kelp resulted in pathological abnormalities in kidney of SD rats. The mixed decoction of kelp and licorice distinctly perturbed sera molecules and hence system metabolism, which showed associated with those of kelp and licorice. Although the metabolic effect was associated with both kelp and licorice, the results suggested kelp contributed to it primarily. PMID: 26118110 [PubMed - indexed for MEDLINE]

Related Articles [metabonomics research on coronary heart disease patients of phlegm turbidity syndrome and qi deficiency syndrome]. Zhongguo Zhong Xi Yi Jie He Za Zhi. 2015 Feb;35(2):193-7 Authors: Cheng P, Chen ZQ, Wang DS Abstract OBJECTIVE: To study the correlation between Chinese medical types of coronary heart disease (CHD) [i.e., phlegm turbidity syndrome (PTS) and qi deficiency syndrome (QDS)] and their metabolites. METHODS: Recruited were 65 CHD patients including 37 cases of PTS and 28 cases of QDS. Serum endogenous metabolites in the two syndrome types were determined by gas chromatograph-mass spectrometer-computer (GC/MS), and their differences between their metabolic profiles analyzed. RESULTS: More than 100 chromatographic peaks were totally scanned. Chromatograms obtained was matched with mass spectrum bank, and finally we got the category contribution value of 46 kinds of substances. Results of MCTree analysis showed patients of PTS and patients of QDS could be effectively distinguished. Compounds contributing to identify the two syndromes were sequenced as serine, valine, 2 hydroxy propionic acid. Comparison of metabolites showed contents of serine and 2 hydroxy propionic acid were higher in patients of PTS than in patients of QDS (P<0.05). CONCLUSION: The differences in the metabonomics of CHD TCM syndrome types could provide material bases for TCM syndrome differentiation of CHD, indicating that metabonomics technologies might become a new research method for TCM syndrome typing. PMID: 25881465 [PubMed - indexed for MEDLINE]

Related Articles Thiobenzothiazole-modified Hydrocortisones Display Anti-inflammatory Activity with Reduced Impact on Islet β-Cell Function. J Biol Chem. 2015 May 22;290(21):13401-16 Authors: Burke SJ, May AL, Noland RC, Lu D, Brissova M, Powers AC, Sherrill EM, Karlstad MD, Campagna SR, Stephens JM, Collier JJ Abstract Glucocorticoids signal through the glucocorticoid receptor (GR) and are administered clinically for a variety of situations, including inflammatory disorders, specific cancers, rheumatoid arthritis, and organ/tissue transplantation. However, glucocorticoid therapy is also associated with additional complications, including steroid-induced diabetes. We hypothesized that modification of the steroid backbone is one strategy to enhance the therapeutic potential of GR activation. Toward this goal, two commercially unavailable, thiobenzothiazole-containing derivatives of hydrocortisone (termed MS4 and MS6) were examined using 832/13 rat insulinoma cells as well as rodent and human islets. We found that MS4 had transrepression properties but lacked transactivation ability, whereas MS6 retained both transactivation and transrepression activities. In addition, MS4 and MS6 both displayed anti-inflammatory activity. Furthermore, MS4 displayed reduced impact on islet β-cell function in both rodent and human islets. Similar to dexamethasone, MS6 promoted adipocyte development in vitro, whereas MS4 did not. Moreover, neither MS4 nor MS6 activated the Pck1 (Pepck) gene in primary rat hepatocytes. We conclude that modification of the functional groups attached to the D-ring of the hydrocortisone steroid molecule produces compounds with altered structure-function GR agonist activity with decreased impact on insulin secretion and reduced adipogenic potential but with preservation of anti-inflammatory activity. PMID: 25851902 [PubMed - indexed for MEDLINE]

Related Articles [A novel metabolomic data scaling method based on K-L divergence]. Guang Pu Xue Yu Guang Pu Fen Xi. 2014 Oct;34(10):2868-72 Authors: Deng LL, Cheng KK, Shen GP, Zhou L, Liu XZ, Dong JY, Chen Z Abstract A new scaling method in the current study based on Kullback-Leibler (K-L) divergence is proposed for NMR metabolomic data. The proposed method (called K-L scaling) is a supervised scaling method as group information is incorporated in the scaling procedure. Notably, K-L divergence measures the difference between two different datasets by their probability distributions, it can be used for the analysis of data that either follows Gaussian or non-Gaussian distributions. In K-L scaling, all variables were first standardized to unit variance, then their variance was adjusted using Kullback-Leibler divergence to highlight the significant variables. K-L scaling can tell effectively the difference in spectral data points between two experimental groups, and then enhances the weights of biological-relevant variables, and at the same time reduces the weight of noise and uninformative variables. The developed method was applied to a H-NMR metabolomic dataset acquired from human urine. Analysis results of the dataset showed that this new scaling method is efficient in suppressing the contribution of noise in the resulting multivariate model In addition, it can increase the weights of important variables, and improve the interpretability and predictability of subsequent principal component regression (PCR) and partial least squares discriminant analysis (PLS-DA). Furthermore, the scaling method facilitated the identification of metabolic signatures. The current result suggested that the developed K-L scaling method may become a useful alternative for the preprocessing of NMR-based metabolomic data. PMID: 25739240 [PubMed - indexed for MEDLINE]