The ubiD/ubiX or the homologous fdc/pad genes have been implicated in the non-oxidative reversible decarboxylation of aromatic substrates, and play a pivotal role in bacterial ubiquinone biosynthesis1–3 or microbial biodegradation of aromatic compounds4–6 respectively. Despite biochemical studies on individual gene products, the composition and co-factor requirement of the enzyme responsible for in vivo decarboxylase activity remained unclear7–9. We show Fdc is solely responsible for (de)carboxylase activity, and that it requires a new type of cofactor: a prenylated flavin synthesised by the associated UbiX/Pad10. Atomic resolution crystal structures reveal two distinct isomers of the oxidized cofactor can be observed: an isoalloxazine N5-iminium adduct and a N5 secondary ketimine species with drastically altered ring structure, both having azomethine ylide character. Substrate binding positions the dipolarophile enoic acid group directly above the azomethine ylide group. The structure of a covalent inhibitor-cofactor adduct suggests 1,3-dipolar cycloaddition chemistry supports reversible decarboxylation in these enzymes. While 1,3-dipolar cycloaddition is commonly used in organic chemistry11–12, we propose this presents the first example of an enzymatic 1,3-dipolar cycloaddition reaction. Our model for Fdc/UbiD catalysis offers new routes in alkene hydrocarbon production or aryl (de)carboxylation.

Ubiquinone, or coenzyme Q, is a ubiquitous lipid-soluble redox cofactor that is an essential component of electron transfer chains1. Eleven genes have been implicated in bacterial ubiquinone biosynthesis, including ubiX and ubiD, which are responsible for decarboxylation of the 3-octaprenyl-4-hydroxybenzoate precursor2. Despite structural and biochemical characterization of UbiX as an FMN-binding protein, no decarboxylase activity has been detected3–4. We report here that UbiX produces a novel flavin-derived cofactor required for the decarboxylase activity of UbiD5. UbiX acts as a flavin prenyltransferase, linking a dimethylallyl moiety to the flavin N5 and C6 atoms. This adds a fourth non-aromatic ring to the flavin isoalloxazine group. In contrast to other prenyltransferases6–7, UbiX is metal-independent and requires dimethylallyl-monophosphate as substrate. Kinetic crystallography reveals that the prenyl transferase mechanism of UbiX resembles that of the terpene synthases8. The active site environment is dominated by π-systems, which assist phosphate-C1’ bond breakage following FMN reduction, leading to formation of the N5-C1’ bond. UbiX then acts as a chaperone for adduct reorientation, via transient carbocation species, leading ultimately to formation of the dimethylallyl C3’-C6 bond. The study establishes the mechanism for formation of a new flavin-derived cofactor, extending both flavin and terpenoid biochemical repertoire.

Current clinical practices focus on a small number of biochemical directly related to the pathophysiology with patients and thus only describe a very limited metabolome of a patient and fail to consider the interations of these small molecules. This lack of extended information may prevent clinicians from making the best possible therapeutic interventions in sufficient time to improve patient care. Various post-genomics ‘(’omic)’ approaches have been used for therapeutic interventions previously. Metabolomics now a well-established’omics approach, has been widely adopted as a novel approach for biomarker discovery and in tandem with genomics (especially SNPs and GWAS) has the potential for providing systemic understanding of the underlying causes of pathology. In this review, we discuss the relevance of metabolomics approaches in clinical sciences and its potential for biomarker discovery which may help guide clinical interventions. Although a powerful and potentially high throughput approach for biomarker discovery at the molecular level, true translation of metabolomics into clinics is an extremely slow process. Quicker adaptation of biomarkers discovered using metabolomics can be possible with novel portable and wearable technologies aided by clever data mining, as well as deep learning and artificial intelligence; we shall also discuss this with an eye to the future of precision medicine where metabolomics can be delivered to the masses.

BackgroundThe 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.MethodsNeutrophils 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.ResultsECVE 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.ConclusionsECVE causes a pro-inflammatory response from human neutrophils. This raises concerns over the safety of e-cig use.Electronic supplementary materialThe online version of this article (doi:10.1186/s12931-016-0368-x) contains supplementary material, which is available to authorized users.

Parkinson’s disease (PD) is a progressive, neurodegenerative disease that presents with significant motor symptoms, for which there is no diagnostic chemical test. We have serendipitously identified a hyperosmic individual, a “Super Smeller” who can detect PD by odor alone, and our early pilot studies have indicated that the odor was present in the sebum from the skin of PD subjects. Here, we have employed an unbiased approach to investigate the volatile metabolites of sebum samples obtained noninvasively from the upper back of 64 participants in total (21 controls and 43 PD subjects). Our results, validated by an independent cohort ( n =31), identified a distinct volatiles-associated signature of PD, including altered levels of perillic aldehyde and eicosane, the smell of which was then described as being highly similar to the scent of PD by our “Super Smeller”.

Parkinson’s disease (PD) is a progressive neurodegenerative disorder, which is characterised by degeneration of distinct neuronal populations, including dopaminergic neurons of the substantia nigra. Here, we use a metabolomics profiling approach to identify changes to lipids in PD observed in sebum, a non-invasively available biofluid. We used liquid chromatography-mass spectrometry (LC-MS) to analyse 274 samples from participants (80 drug naïve PD, 138 medicated PD and 56 well matched control subjects) and detected metabolites that could predict PD phenotype. Pathway enrichment analysis shows alterations in lipid metabolism related to the carnitine shuttle, sphingolipid metabolism, arachidonic acid metabolism and fatty acid biosynthesis. This study shows sebum can be used to identify potential biomarkers for PD.

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Global ageing poses a substantial economic burden on health and social care costs. Enabling a greater proportion of older people to stay healthy for longer is key to the future sustainability of health, social and economic policy. Frailty and associated decrease in resilience plays a central role in poor health in later life. In this study, we present a population level assessment of the metabolic phenotype associated with frailty. Analysis of serum from 1191 older individuals (aged between 56 and 84 years old) and subsequent longitudinal validation (on 786 subjects) was carried out using liquid and gas chromatography-mass spectrometry metabolomics and stratified across a frailty index designed to quantitatively summarize vulnerability. Through multivariate regression and network modelling and mROC modeling we identified 12 significant metabolites (including three tocotrienols and six carnitines) that differentiate frail and non-frail phenotypes. Our study provides evidence that the dysregulation of carnitine shuttle and vitamin E pathways play a role in the risk of frailty.