Multiomics implicate gut microbiota in altered lipid and energy metabolism in Parkinson's disease

We aimed to investigate the link between serum metabolites, gut bacterial community composition, and clinical variables in Parkinson's disease (PD) and healthy control subjects (HC). A total of 124 subjects were part of the study (63 PD patients and 61 HC subjects). 139 metabolite features were found to be predictive between the PD and Control groups. No associations were found between metabolite features and within-PD clinical variables. The results suggest alterations in serum metabolite profiles in PD, and the results of correlation analysis between metabolite features and microbiota suggest that several bacterial taxa are associated with altered lipid and energy metabolism in PD.Peer reviewe

A systematic analysis of TCA Escherichia coli mutants reveals suitable genetic backgrounds for enhanced hydrogen and ethanol production using glycerol as main carbon source

Biodiesel has emerged as an environmentally friendly alternative to fossil fuels; however, the low price of glycerol feed-stocks generated from the biodiesel industry has become a burden to this industry. A feasible alternative is the microbial biotransformation of waste glycerol to hydrogen and ethanol. Escherichia coli, a microorganism commonly used for metabolic engineering, is able to biotransform glycerol into these products. Nevertheless, the wild type strain yields can be improved by rewiring the carbon flux to the desired products by genetic engineering. Due to the importance of the central carbon metabolism in hydrogen and ethanol synthesis, E. coli single null mutant strains for enzymes of the TCA cycle and other related reactions were studied in this work. These strains were grown anaerobically in a glycerol-based medium and the concentrations of ethanol, glycerol, succinate and hydrogen were analysed by HPLC and GC. It was found that the reductive branch is the more relevant pathway for the aim of this work, with malate playing a central role. It was also found that the putative C4-transporter dcuD mutant improved the target product yields. These results will contribute to reveal novel metabolic engineering strategies for improving hydrogen and ethanol production by E. coli

Electronic cigarette exposure triggers neutrophil inflammatory responses

Background The use of electronic cigarettes (e-cigs) is increasing and there is widespread perception that e-cigs are safe. E-cigs contain harmful chemicals; more research is needed to evaluate the safety of e-cig use. Our aim was to investigate the effects of e-cigs on the inflammatory response of human neutrophils. Methods Neutrophils were exposed to e-cig vapour extract (ECVE) and the expression of CD11b and CD66b was measured by flow cytometry and MMP-9 and CXCL8 by ELISA. We also measured the activity of neutrophil elastase (NE) and MMP-9, along with the activation of inflammatory signalling pathways. Finally we analysed the biochemical composition of ECVE by ultra-high performance liquid chromatography mass spectrometry. Results ECVE caused an increase in the expression of CD11b and CD66b, and increased the release of MMP-9 and CXCL8. Furthermore, there was an increase in NE and MMP-9 activity and an increase in p38 MAPK activation. We also identified several harmful chemicals in ECVE, including known carcinogens. Conclusions ECVE causes a pro-inflammatory response from human neutrophils. This raises concerns over the safety of e-cig use

Validating differential volatilome profiles in Parkinson’s disease

Contains fulltext : 231972.pdf (Publisher’s version ) (Open Access

Development of Zwitterionic Hydrophilic Liquid Chromatography (ZICⓇHILIC-MS) metabolomics method for Shotgun analysis of human urine

Urine is a product of the body’s metabolism and the majority of the metabolic products exiting via the renal system are rendered polar in order to be water soluble. Resolution of urinary metabolites for metabolomic studies requires the development of HPLC separation techniques that match this feature of biological chemistry. ZIC –HILIC is an ideal candidate to take forward resolution of such metabolites where reverse phase is unable to give adequate separation. Metabolomic data has to be processed by Shotgun multivariate analysis to sift through thousands of analytes and their variables such as ion intensity. In the development of ZIC-HILIC separation with mass spectrometric (IT-ToF) detection, methodological variability have to be minimized so that any Shotgun data analysis does not reveal potential biomarker analytes that are artifacts or are adversely affected of the separation and detection technique. Here, we report the development of a ZIC-HILIC mass spectrometry method that is suitable for SIMCA P+ data analysis of urine. Variables such as resolution, run reproducibility and sample storage temperature were evaluated in tandem with SIMCA P+ data analysis and quality control pre-processing. The developed method couples quality control runs that pre-process and exclude analytes that are insufficiently robust for further candidate biomarker studies. This meant labile analytes that could not be reproduced in 70% of QC runs (which are pools of all samples run that day) were excluded. However, urine samples stored at 4°C for more than 9 months will contain metabolites that will alter and produce small molecule marker artifacts when compared to samples stored at -20°C. In conclusion, the developed method is a robust method of ZIC-HILIC mass spectrometry shotgun analysis suitable for urinary metabolome discovery of robust biomarkers