Species-Specific Variations in the Metabolomic Profiles of Acropora hyacinthus and Acropora millepora Mask Acute Temperature Stress Effects in Adult Coral Colonies

Coral reefs are suffering unprecedented declines in health state on a global scale. Some have suggested that human assisted evolution or assisted gene flow may now be necessary to effectively restore reefs and pre-condition them for future climate change. An understanding of the key metabolic processes in corals, including under stressed conditions, would greatly facilitate the effective application of such interventions. To date, however, there has been little research on corals at this level, particularly regarding studies of the metabolome of Scleractinian corals. Here, the metabolomic profiles [measured using 1H nuclear magnetic resonance spectroscopy (1H NMR) and ultra-high-performance liquid chromatography-mass spectrometry (LC-MS)] of two dominant reef building corals, Acropora hyacinthus and A. millepora, from two distinct geographical locations (Australia and Singapore) were characterized. We assessed how an acute temperature stress (an increase of 3.25°C ± 0.28 from ambient control levels over 8 days), shifted the corals’ baseline metabolomic profiles. Regardless of the profiling method utilized, metabolomic signatures of coral colonies were significantly distinct between coral species, a result supporting previous work. However, this strong species-specific metabolomic signature appeared to mask any changes resulting from the acute heat stress. On closer examination, we were able to discriminate between control and temperature stressed groups using a partial least squares discriminant analysis classification model (PLSDA). However, in all cases “late” components needed to be selected (i.e., 7 and 8 instead of 1 and 2), suggesting any treatment effect was small, relative to other sources of variation. This highlights the importance of pre-characterizing the coral colony metabolomes, and of factoring that knowledge into any experimental design that seeks to understand the apparently subtle metabolic effects of acute heat stress on adult corals. Further research is therefore needed to decouple these apparent individual and species-level metabolomic responses to climate change in corals.NER

Metabolic status of CSF distinguishes rats with tauopathy from controls

Abstract Background Tauopathies represent heterogeneous groups of neurodegenerative diseases that are characterised by abnormal deposition of the microtubule-associated protein tau. Alzheimer’s disease is the most prevalent tauopathy, affecting more than 35 million people worldwide. In this study we investigated changes in metabolic pathways associated with tau-induced neurodegeneration. Methods Cerebrospinal fluid (CSF), plasma and brain tissue were collected from a transgenic rat model for tauopathies and from age-matched control animals. The samples were analysed by targeted and untargeted metabolomic methods using high-performance liquid chromatography coupled to mass spectrometry. Unsupervised and supervised statistical analysis revealed biochemical changes associated with the tauopathy process. Results Energy deprivation and potentially neural apoptosis were reflected in increased purine nucleotide catabolism and decreased levels of citric acid cycle intermediates and glucose. However, in CSF, increased levels of citrate and aconitate that can be attributed to glial activation were observed. Other significant changes were found in arginine and phosphatidylcholine metabolism. Conclusions Despite an enormous effort invested in development of biomarkers for tauopathies during the last 20 years, there is no clinically used biomarker or assay on the market. One of the most promising strategies is to create a panel of markers (e.g., small molecules, proteins) that will be continuously monitored and correlated with patients’ clinical outcome. In this study, we identified several metabolic changes that are affected during the tauopathy process and may be considered as potential markers of tauopathies in humans

SLIDE—Novel Approach to Apocrine Sweat Sampling for Lipid Profiling in Healthy Individuals

We designed a concept of 3D-printed attachment with porous glass filter disks—SLIDE (Sweat sampLIng DevicE) for easy sampling of apocrine sweat. By applying advanced mass spectrometry coupled with the liquid chromatography technique, the complex lipid profiles were measured to evaluate the reproducibility and robustness of this novel approach. Moreover, our in-depth statistical evaluation of the data provided an insight into the potential use of apocrine sweat as a novel and diagnostically relevant biofluid for clinical analyses. Data transformation using probabilistic quotient normalization (PQN) significantly improved the analytical characteristics and overcame the ‘sample dilution issue’ of the sampling. The lipidomic content of apocrine sweat from healthy subjects was described in terms of identification and quantitation. A total of 240 lipids across 15 classes were identified. The lipid concentrations varied from 10−10 to 10−4 mol/L. The most numerous class of lipids were ceramides (n = 61), while the free fatty acids were the most abundant ones (average concentrations of 10−5 mol/L). The main advantages of apocrine sweat microsampling include: (a) the non-invasiveness of the procedure and (b) the unique feature of apocrine sweat, reflecting metabolome and lipidome of the intracellular space and plasmatic membranes. The SLIDE application as a sampling technique of apocrine sweat brings a promising alternative, including various possibilities in modern clinical practice

Metabolomic, Lipidomic and Proteomic Characterisation of Lipopolysaccharide-induced Inflammation Mouse Model

Neuroinflammation is an important feature in the pathogenesis and progression of central nervous system (CNS) diseases including Alzheimer's disease (AD). One of the widely used animal models of peripherally induced neuroinflammation and neurodegeneration is a lipopolysaccharide (LPS)-induced inflammation mouse model. An acute LPS administration has been widely used for investigation of inflammation-associated disease and testing inflammation-targeting drug candidates. In the present metabolomic, lipidomic and proteomic study, we investigated short-term effects of systemic inflammation induced by LPS administration on the mouse plasma and brain cortical and hippocampal metabolome, lipidome as well as expression of the brain cortical proteins which were shown to be involved in inflammation-associated CNS diseases. From a global perspective, the hippocampus was more vulnerable to the effects of LPS-induced systemic inflammation than the cortex. In addition, the study revealed several brain region-specific changes in metabolic pathways and lipids, such as statistically significant increase in several cortical and hippocampal phosphatidylcholines/phosphatidylethanolamines, and significantly decreased levels of brain cortical betaine after LPS treatment in mice. Moreover, LPS treatment in mice caused significantly increased protein expression of GluN1 receptor in the brain cortex. The revealed perturbations in the LPS-induced inflammation mouse model may give insight into the mechanisms underlying inflammation-associated CNS diseases. In addition, the finding of the study provide important information about the appropriate use of the model during target validation and drug candidate testing.Open access articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Additional file 1: Table S1. of Metabolic status of CSF distinguishes rats with tauopathy from controls

Abbreviations of metabolites used in targeted metabolomic analysis. Tables S2, S3. Results of analysis of CSF from confirmatory study: targeted analysis (Table S2) and untargeted (Table S3). Table S4. Twenty most discriminating features from untargeted analysis of brain tissue samples. Figure S1. Expression levels of insoluble tau proteins in brainstem of transgenic animals used for study. Figures S2, S3, S4, S5, S6, S7. OPLS-DA score scatterplots and S-plots built for targeted and untargeted metabolomics: CSF targeted (Fig. S2) and untargeted (Fig. S5) metabolomics, plasma targeted (Fig. S3) and untargeted (Fig. S6) metabolomics, brain tissue targeted (Fig. S4) and untargeted (Fig. S7) metabolomics. Figures S8, S9. OPLS-DA score scatterplots and S-plots built for targeted and untargeted metabolomics of CSF in confirmation study: targeted (Fig. S8) and untargeted (Fig. S9) metabolomics. Figure S10. Box plots of most discriminating features of brain tissue samples in untargeted metabolomic analysis. (DOCX 4660 kb

Metabolomics Simultaneously Derives Benchmark Dose Estimates and Discovers Metabolic Biotransformations in a Rat Bioassay

Benchmark dose (BMD) modeling estimates the dose of a chemical that causes a perturbation from baseline. Transcriptional BMDs have been shown to be relatively consistent with apical end point BMDs, opening the door to using molecular BMDs to derive human health-based guidance values for chemical exposure. Metabolomics measures the responses of small-molecule endogenous metabolites to chemical exposure, complementing transcriptomics by characterizing downstream molecular phenotypes that are more closely associated with apical end points. The aim of this study was to apply BMD modeling to in vivo metabolomics data, to compare metabolic BMDs to both transcriptional and apical end point BMDs. This builds upon our previous application of transcriptomics and BMD modeling to a 5-day rat study of triphenyl phosphate (TPhP), applying metabolomics to the same archived tissues. Specifically, liver from rats exposed to five doses of TPhP was investigated using liquid chromatography-mass spectrometry and 1H nuclear magnetic resonance spectroscopy-based metabolomics. Following the application of BMDExpress2 software, 2903 endogenous metabolic features yielded viable dose-response models, confirming a perturbation to the liver metabolome. Metabolic BMD estimates were similarly sensitive to transcriptional BMDs, and more sensitive than both clinical chemistry and apical end point BMDs. Pathway analysis of the multiomics data sets revealed a major effect of TPhP exposure on cholesterol (and downstream) pathways, consistent with clinical chemistry measurements. Additionally, the transcriptomics data indicated that TPhP activated xenobiotic metabolism pathways, which was confirmed by using the underexploited capability of metabolomics to detect xenobiotic-related compounds. Eleven biotransformation products of TPhP were discovered, and their levels were highly correlated with multiple xenobiotic metabolism genes. This work provides a case study showing how metabolomics and transcriptomics can estimate mechanistically anchored points-of-departure. Furthermore, the study demonstrates how metabolomics can also discover biotransformation products, which could be of value within a regulatory setting, for example, as an enhancement of OECD Test Guideline 417 (toxicokinetics).</p

Metabolomics Simultaneously Derives Benchmark Dose Estimates and Discovers Metabolic Biotransformations in a Rat Bioassay

Benchmark dose (BMD) modeling estimates the dose of a chemical that causes a perturbation from baseline. Transcriptional BMDs have been shown to be relatively consistent with apical end point BMDs, opening the door to using molecular BMDs to derive human health-based guidance values for chemical exposure. Metabolomics measures the responses of small-molecule endogenous metabolites to chemical exposure, complementing transcriptomics by characterizing downstream molecular phenotypes that are more closely associated with apical end points. The aim of this study was to apply BMD modeling to in vivo metabolomics data, to compare metabolic BMDs to both transcriptional and apical end point BMDs. This builds upon our previous application of transcriptomics and BMD modeling to a 5-day rat study of triphenyl phosphate (TPhP), applying metabolomics to the same archived tissues. Specifically, liver from rats exposed to five doses of TPhP was investigated using liquid chromatography-mass spectrometry and 1H nuclear magnetic resonance spectroscopy-based metabolomics. Following the application of BMDExpress2 software, 2903 endogenous metabolic features yielded viable dose-response models, confirming a perturbation to the liver metabolome. Metabolic BMD estimates were similarly sensitive to transcriptional BMDs, and more sensitive than both clinical chemistry and apical end point BMDs. Pathway analysis of the multiomics data sets revealed a major effect of TPhP exposure on cholesterol (and downstream) pathways, consistent with clinical chemistry measurements. Additionally, the transcriptomics data indicated that TPhP activated xenobiotic metabolism pathways, which was confirmed by using the underexploited capability of metabolomics to detect xenobiotic-related compounds. Eleven biotransformation products of TPhP were discovered, and their levels were highly correlated with multiple xenobiotic metabolism genes. This work provides a case study showing how metabolomics and transcriptomics can estimate mechanistically anchored points-of-departure. Furthermore, the study demonstrates how metabolomics can also discover biotransformation products, which could be of value within a regulatory setting, for example, as an enhancement of OECD Test Guideline 417 (toxicokinetics).</p