Invariance and plasticity in the Drosophila melanogaster metabolomic network in response to temperature

BACKGROUND: Metabolomic responses to extreme thermal stress have recently been investigated in Drosophila melanogaster. However, a network level understanding of metabolomic responses to longer and less drastic temperature changes, which more closely reflect variation in natural ambient temperatures experienced during development and adulthood, is currently lacking. Here we use high-resolution, non-targeted metabolomics to dissect metabolomic changes in D. melanogaster elicited by moderately cool (18°C) or warm (27°C) developmental and adult temperature exposures. RESULTS: We find that temperature at which larvae are reared has a dramatic effect on metabolomic network structure measured in adults. Using network analysis, we are able to identify modules that are highly differentially expressed in response to changing developmental temperature, as well as modules whose correlation structure is strongly preserved across temperature. CONCLUSIONS: Our results suggest that the effect of temperature on the metabolome provides an easily studied and powerful model for understanding the forces that influence invariance and plasticity in biological networks. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-014-0139-6) contains supplementary material, which is available to authorized users

Metabolic Characterization of the Common Marmoset (Callithrix jacchus)

High-resolution metabolomics has created opportunity to integrate nutrition and metabolism into genetic studies to improve understanding of the diverse radiation of primate species. At present, however, there is very little information to help guide experimental design for study of wild populations. In a previous non-targeted metabolomics study of common marmosets (Callithrix jacchus), Rhesus macaques, humans, and four non-primate mammalian species, we found that essential amino acids (AA) and other central metabolites had interspecies variation similar to intraspecies variation while non-essential AA, environmental chemicals and catabolic waste products had greater interspecies variation. The present study was designed to test whether 55 plasma metabolites, including both nutritionally essential and non-essential metabolites and catabolic products, differ in concentration in common marmosets and humans. Significant differences were present for more than half of the metabolites analyzed and included AA, vitamins and central lipid metabolites, as well as for catabolic products of AA, nucleotides, energy metabolism and heme. Three environmental chemicals were present at low nanomolar concentrations but did not differ between species. Sex and age differences in marmosets were present for AA and nucleotide metabolism and warrant additional study. Overall, the results suggest that quantitative, targeted metabolomics can provide a useful complement to non-targeted metabolomics for studies of diet and environment interactions in primate evolution.National Institutes of Health (U.S.) (grant AG038746

The Effects of Graded Levels of Calorie Restriction : XIII. Global Metabolomics Screen Reveals Graded Changes in Circulating Amino Acids, Vitamins, and Bile Acids in the Plasma of C57BL/6 Mice

Work toward having all the data from this series of papers online is currently ongoing. All significant metabolites in relation to CR manipulation are listed in Supplementary Material S1. Data on the nonsignificant metabolites are freely available for anyone who requests it from the corresponding author at [email protected] The study was supported by the UK Biotechnology and Biological Sciences Research Council BBSRC (BB/G009953/1 and BB/J020028/1 to J.R.S.) and a studentship of C.L.G. from the BBSRC EastBio Doctoral Training Partnership. C.L.G. received support from the laboratory of D.P.; D.P. was supported in part by NIH grant AGO49494.Peer reviewedPublisher PD

Efficacy of APX2039 in a Rabbit Model of Cryptococcal Meningitis

Cryptococcal Meningitis (CM) is uniformly fatal if not treated, and treatment options are limited. We previously reported on the activity of APX2096, the prodrug of the novel Gwt1 inhibitor APX2039, in a mouse model of CM. Here, we investigated the efficacy of APX2039 in mouse and rabbit models of CM. In the mouse model, the controls had a mean lung fungal burden of 5.95 log10 CFU/g, whereas those in the fluconazole-, amphotericin B-, and APX2039-treated mice were 3.56, 4.59, and 1.50 log10 CFU/g, respectively. In the brain, the control mean fungal burden was 7.97 log10 CFU/g, while the burdens were 4.64, 7.16, and 1.44 log10 CFU/g for treatment with fluconazole, amphotericin B, and APX2039, respectively. In the rabbit model of CM, the oral administration of APX2039 at 50 mg/kg of body weight twice a day (BID) resulted in a rapid decrease in the cerebrospinal fluid (CSF) fungal burden, and the burden was below the limit of detection by day 10 postinfection. The effective fungicidal activity (EFA) was -0.66 log10 CFU/mL/day, decreasing from an average of 4.75 log10 CFU/mL to 0 CFU/mL, over 8 days of therapy, comparing favorably with good clinical outcomes in humans associated with reductions of the CSF fungal burden of -0.4 log10 CFU/mL/day, and, remarkably, 2-fold the EFA of amphotericin B deoxycholate in this model (-0.33 log10 CFU/mL/day). A total drug exposure of the area under the concentration-time curve from 0 to 24 h (AUC0-24) of 25 to 50 mg · h/L of APX2039 resulted in near-maximal antifungal activity. These data support the further preclinical and clinical evaluation of APX2039 as a new oral fungicidal monotherapy for the treatment of CM. IMPORTANCE Cryptococcal meningitis (CM) is a fungal disease with significant global morbidity and mortality. The gepix Gwt1 inhibitors are a new class of antifungal drugs. Here, we demonstrated the efficacy of APX2039, the second member of the gepix class, in rabbit and mouse models of cryptococcal meningitis. We also analyzed the drug levels in the blood and cerebrospinal fluid in the highly predictive rabbit model and built a mathematical model to describe the behavior of the drug with respect to the elimination of the fungal pathogen. We demonstrated that the oral administration of APX2039 resulted in a rapid decrease in the CSF fungal burden, with an effective fungicidal activity of -0.66 log10 CFU/mL/day, comparing favorably with good clinical outcomes in humans associated with reductions of -0.4 log10 CFU/mL/day. The drug APX2039 had good penetration of the central nervous system and is an excellent candidate for future clinical testing in humans for the treatment of CM

APX001 and Other Gwt1 inhibitor Prodrugs are Effective in Experimental Coccidioides immitis Pneumonia

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xMSanalyzer: automated pipeline for improved feature detection and downstream analysis of large-scale, non-targeted metabolomics data

<p>Abstract</p> <p>Background</p> <p>Detection of low abundance metabolites is important for de novo mapping of metabolic pathways related to diet, microbiome or environmental exposures. Multiple algorithms are available to extract <it>m/z</it> features from liquid chromatography-mass spectral data in a conservative manner, which tends to preclude detection of low abundance chemicals and chemicals found in small subsets of samples. The present study provides software to enhance such algorithms for feature detection, quality assessment, and annotation.</p> <p>Results</p> <p>xMSanalyzer is a set of utilities for automated processing of metabolomics data. The utilites can be classified into four main modules to: 1) improve feature detection for replicate analyses by systematic re-extraction with multiple parameter settings and data merger to optimize the balance between sensitivity and reliability, 2) evaluate sample quality and feature consistency, 3) detect feature overlap between datasets, and 4) characterize high-resolution <it>m/z</it> matches to small molecule metabolites and biological pathways using multiple chemical databases. The package was tested with plasma samples and shown to more than double the number of features extracted while improving quantitative reliability of detection. MS/MS analysis of a random subset of peaks that were exclusively detected using xMSanalyzer confirmed that the optimization scheme improves detection of real metabolites.</p> <p>Conclusions</p> <p>xMSanalyzer is a package of utilities for data extraction, quality control assessment, detection of overlapping and unique metabolites in multiple datasets, and batch annotation of metabolites. The program was designed to integrate with existing packages such as apLCMS and XCMS, but the framework can also be used to enhance data extraction for other LC/MS data software.</p