UbiX is a flavin prenyltransferase required for bacterial ubiquinone biosynthesis.

Ubiquinone (also known as coenzyme Q) is a ubiquitous lipid-soluble redox cofactor that is an essential component of electron transfer chains. Eleven genes have been implicated in bacterial ubiquinone biosynthesis, including ubiX and ubiD, which are responsible for decarboxylation of the 3-octaprenyl-4-hydroxybenzoate precursor. Despite structural and biochemical characterization of UbiX as a flavin mononucleotide (FMN)-binding protein, no decarboxylase activity has been detected. Here we report that UbiX produces a novel flavin-derived cofactor required for the decarboxylase activity of UbiD. 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 prenyltransferases, UbiX is metal-independent and requires dimethylallyl-monophosphate as substrate. Kinetic crystallography reveals that the prenyltransferase mechanism of UbiX resembles that of the terpene synthases. 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. Our findings establish the mechanism for formation of a new flavin-derived cofactor, extending both flavin and terpenoid biochemical repertoires.

New cofactor supports α,ß-unsaturated acid decarboxylation via 1,3-dipolar cycloaddition.

The bacterial ubiD and ubiX or the homologous fungal fdc1 and pad1 genes have been implicated in the non-oxidative reversible decarboxylation of aromatic substrates, and play a pivotal role in bacterial ubiquinone (also known as coenzyme Q) biosynthesis or microbial biodegradation of aromatic compounds, respectively. Despite biochemical studies on individual gene products, the composition and cofactor requirement of the enzyme responsible for in vivo decarboxylase activity remained unclear. Here we show that Fdc1 is solely responsible for the reversible decarboxylase activity, and that it requires a new type of cofactor: a prenylated flavin synthesized by the associated UbiX/Pad1. Atomic resolution crystal structures reveal that two distinct isomers of the oxidized cofactor can be observed, an isoalloxazine N5-iminium adduct and a N5 secondary ketimine species with markedly 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 that 1,3-dipolar cycloaddition chemistry supports reversible decarboxylation in these enzymes. Although 1,3-dipolar cycloaddition is commonly used in organic chemistry, we propose that this presents the first example, to our knowledge, of an enzymatic 1,3-dipolar cycloaddition reaction. Our model for Fdc1/UbiD catalysis offers new routes in alkene hydrocarbon production or aryl (de)carboxylation.

Two Glycerol-3-Phosphate Dehydrogenases from Chlamydomonas Have Distinct Roles in Lipid Metabolism.

The metabolism of glycerol-3-phosphate (G3P) is important for environmental stress responses by eukaryotic microalgae. G3P is an essential precursor for glycerolipid synthesis and the accumulation of triacylglycerol (TAG) in response to nutrient starvation. G3P dehydrogenase (GPDH) mediates G3P synthesis, but the roles of specific GPDH isoforms are currently poorly understood. Of the five GPDH enzymes in the model alga Chlamydomonas reinhardtii, GPD2 and GPD3 were shown to be induced by nutrient starvation and/or salt stress. Heterologous expression of GPD2, a putative chloroplastic GPDH, and GPD3, a putative cytosolic GPDH, in a yeast gpd1Δ mutant demonstrated the functionality of both enzymes. C. reinhardtii knockdown mutants for GPD2 and GPD3 showed no difference in growth but displayed significant reduction in TAG concentration compared with the wild type in response to phosphorus or nitrogen starvation. Overexpression of GPD2 and GPD3 in C. reinhardtii gave distinct phenotypes. GPD2 overexpression lines showed only subtle metabolic phenotypes and no significant alteration in growth. In contrast, GPD3 overexpression lines displayed significantly inhibited growth and chlorophyll concentration, reduced glycerol concentration, and changes to lipid composition compared with the wild type, including increased abundance of phosphatidic acids but reduced abundance of diglycerides, triglycerides, and phosphatidylglycerol lipids. This may indicate a block in the downstream glycerolipid metabolism pathway in GPD3 overexpression lines. Thus, lipid engineering by GPDH modification may depend on the activities of other downstream enzyme steps. These results also suggest that GPD2 and GPD3 GPDH isoforms are important for nutrient starvation-induced TAG accumulation but have distinct metabolic functions.

Mitochondrial aconitase is a key regulator of energy production for growth and protein expression in Chinese hamster ovary cells.

INTRODUCTION: Mammalian cells like Chinese hamster ovary (CHO) cells are routinely used for production of recombinant therapeutic proteins. Cells require a continuous supply of energy and nutrients to sustain high cell densities whilst expressing high titres of recombinant proteins. Cultured mammalian cells are primarily dependent on glucose and glutamine metabolism for energy production. OBJECTIVES: The TCA cycle is the main source of energy production and its continuous flow is essential for cell survival. Modulated regulation of TCA cycle can affect ATP production and influence CHO cell productivity. METHODS: To determine the key metabolic reactions of the cycle associated with cell growth in CHO cells, we transiently silenced each gene of the TCA cycle using RNAi. RESULTS: Silencing of at least four TCA cycle genes was detrimental to CHO cell growth. With an exception of mitochondrial aconitase (or Aco2), all other genes were associated with ATP production reactions of the TCA cycle and their resulting substrates can be supplied by other anaplerotic and cataplerotic reactions. This study is the first of its kind to have established key role of aconitase gene in CHO cells. We further investigated the temporal effects of aconitase silencing on energy production, CHO cell metabolism, oxidative stress and recombinant protein production. CONCLUSION: Transient silencing of mitochondrial aconitase inhibited cell growth, reduced ATP production, increased production of reactive oxygen species and reduced cell specific productivity of a recombinant CHO cell line by at least twofold.

Quantitative Online Liquid Chromatography-Surface-Enhanced Raman Scattering (LC-SERS) of Methotrexate and its Major Metabolites.

The application of Raman spectroscopy as a detection method coupled with liquid chromatography (LC) has recently attracted considerable interest, although this has currently been limited to isocratic elution. The combination of LC with rapidly advancing Raman techniques, such as surface-enhanced Raman scattering (SERS), allows for rapid separation, identification and quantification, leading to quantitative discrimination of closely eluting analytes. This study has demonstrated the utility of SERS in conjunction with reversed-phase liquid chromatography (RP-LC), for the detection and quantification of the therapeutically relevant drug molecule methotrexate (MTX) and its metabolites 7-hydroxy methotrexate (7-OH MTX) and 2,4-diamino-N(10)-methylpteroic acid (DAMPA) in pure solutions and mixtures, including spikes into human urine from a healthy individual and patients under medication. While the RP-LC analysis developed employed gradient elution, where the chemical constituents of the mobile phase were modified stepwise during analysis, this did not overtly interfere with the SERS signals. In addition, the practicability and clinical utility of this approach has also been demonstrated using authentic patients' urine samples. Here, the identification of MTX, 7-OH MTX and DAMPA are based on their unique SERS spectra, providing limits of detection of 2.36, 1.84, and 3.26 µM respectively. Although these analytes are amenable to LC and LC-MS detection an additional major benefit of the SERS approach is its applicability toward the detection of analytes that do not show UV absorption or are not ionised for mass spectrometry (MS)-based detection. The results of this study clearly demonstrate the potential application of online LC-SERS analysis for real-time high-throughput detection of drugs and their related metabolites in human biofluids.

Fractional Factorial Design of MALDI-TOF-MS Sample Preparations for the Optimized Detection of Phospholipids and Acylglycerols.

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) has successfully been used for the analysis of high molecular weight compounds, such as proteins and nucleic acids. By contrast, analysis of low molecular weight compounds with this technique has been less successful due to interference from matrix peaks which have a similar mass to the target analyte(s). Recently, a variety of modified matrices and matrix additives have been used to overcome these limitations. An increased interest in lipid analysis arose from the feasibility of correlating these components with many diseases, e.g. atherosclerosis and metabolic dysfunctions. Lipids have a wide range of chemical properties making their analysis difficult with traditional methods. MALDI-TOF-MS shows excellent potential for sensitive and rapid analysis of lipids, and therefore this study focuses on computational-analytical optimization of the analysis of five lipids (4 phospholipids and 1 acylglycerol) in complex mixtures using MALDI-TOF-MS with fractional factorial design (FFD) and Pareto optimality. Five different experimental factors were investigated using FFD which reduced the number of experiments performed by identifying 720 key experiments from a total of 8064 possible analyses. Factors investigated included the following: matrices, matrix preparations, matrix additives, additive concentrations, and deposition methods. This led to a significant reduction in time and cost of sample analysis with near optimal conditions. We discovered that the key factors used to produce high quality spectra were the matrix and use of appropriate matrix additives.

Rapid, Accurate, and Quantitative Detection of Propranolol in Multiple Human Biofluids via Surface-Enhanced Raman Scattering.

There has been an increasing demand for rapid and sensitive techniques for the identification and quantification of pharmaceutical compounds in human biofluids during the past few decades, and surface-enhanced Raman scattering (SERS) is one of a number of physicochemical techniques with the potential to meet these demands. In this study we have developed a SERS-based analytical approach for the assessment of human biofluids in combination with chemometrics. This novel approach has enabled the detection and quantification of the ß-blocker propranolol spiked into human serum, plasma, and urine at physiologically relevant concentrations. A range of multivariate statistical analysis techniques, including principal component analysis (PCA), principal component-discriminant function analysis (PC-DFA) and partial least-squares regression (PLSR) were employed to investigate the relationship between the full SERS spectral data and the level of propranolol. The SERS spectra when combined with PCA and PC-DFA demonstrated clear differentiation of neat biofluids and biofluids spiked with varying concentrations of propranolol ranging from 0 to 120 µM, and clear trends in ordination scores space could be correlated with the level of propranolol. Since PCA and PC-DFA are categorical classifiers, PLSR modeling was subsequently used to provide accurate propranolol quantification within all biofluids with high prediction accuracy (expressed as root-mean-square error of predictions) of 0.58, 9.68, and 1.69 for serum, plasma, and urine respectively, and these models also had excellent linearity for the training and test sets between 0 and 120 µM. The limit of detection as calculated from the area under the naphthalene ring vibration from propranolol was 133.1 ng/mL (0.45 µM), 156.8 ng/mL (0.53 µM), and 168.6 ng/mL (0.57 µM) for serum, plasma, and urine, respectively. This result shows a consistent signal irrespective of biofluid, and all are well within the expected physiological level of this drug during therapy. The results of this study demonstrate the potential of SERS application as a diagnostic screening method, following further validation and optimization to improve detection of pharmaceutical compounds and quantification in human biofluids, which may open up new exciting opportunities for future use in various biomedical and forensic applications.

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.

Chicken, beams, and Campylobacter: rapid differentiation of foodborne bacteria via vibrational spectroscopy and MALDI-mass spectrometry.

Campylobacter species are one of the main causes of food poisoning worldwide. Despite the availability of established culturing and molecular techniques, due to the fastidious nature of these microorganisms, simultaneous detection and species differentiation still remains challenging. This study focused on the differentiation of eleven Campylobacter strains from six species, using Fourier transform infrared (FT-IR) and Raman spectroscopies, together with matrix-assisted laser desorption ionisation-time of flight-mass spectrometry (MALDI-TOF-MS), as physicochemical approaches for generating biochemical fingerprints. Cluster analysis of data from each of the three analytical approaches provided clear differentiation of each Campylobacter species, which was generally in agreement with a phylogenetic tree based on 16S rRNA gene sequences. Notably, although C. fetus subspecies fetus and venerealis are phylogenetically very closely related, using FT-IR and MALDI-TOF-MS data these subspecies were readily differentiated based on differences in the lipid (2920 and 2851 cm(-1)) and fingerprint regions (1500-500 cm(-1)) of the FT-IR spectra, and the 500-2000 m/z region of the MALDI-TOF-MS data. A finding that was further investigated with targeted lipidomics using liquid chromatography-mass spectrometry (LC-MS). Our results demonstrate that such metabolomics approaches combined with molecular biology techniques may provide critical information and knowledge related to the risk factors, virulence, and understanding of the distribution and transmission routes associated with different strains of foodborne Campylobacter spp.

Meat, the metabolites: an integrated metabolite profiling and lipidomics approach for the detection of the adulteration of beef with pork.

Adulteration of high quality food products with sub-standard and cheaper grades is a world-wide problem taxing the global economy. Currently, many traditional tests suffer from poor specificity, highly complex outputs and a lack of high-throughput processing. Metabolomics has been successfully used as an accurate discriminatory technique in a number of applications including microbiology, cancer research and environmental studies and certain types of food fraud. In this study, we have developed metabolomics as a technique to assess the adulteration of meat as an improvement on current methods. Different grades of beef mince and pork mince, purchased from a national retail outlet were combined in a number of percentage ratios and analysed using GC-MS and UHPLC-MS. These techniques were chosen because GC-MS enables investigations of metabolites involved in primary metabolism whilst UHPLC-MS using reversed phase chromatography provides information on lipophilic species. With the application of chemometrics and statistical analyses, a panel of differential metabolites were found for identification of each of the two meat types. Additionally, correlation was observed between metabolite content and percentage of fat declared on meat products' labelling.

Classification of Bacillus and Brevibacillus species using rapid analysis of lipids by mass spectrometry.

Bacillus are aerobic spore-forming bacteria that are known to lead to specific diseases, such as anthrax and food poisoning. This study focuses on the characterization of these bacteria by the detection of lipids extracted from 33 well-characterized strains from the Bacillus and Brevibacillus genera, with the aim to discriminate between the different species. For the purpose of analysing the lipids extracted from these bacterial samples, two rapid physicochemical techniques were used: matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF-MS) and liquid chromatography in conjunction with mass spectrometry (LC-MS). The findings of this investigation confirmed that MALDI-TOF-MS could be used to identify different bacterial lipids and, in combination with appropriate chemometrics, allowed for the discrimination between these different bacterial species, which was supported by LC-MS. The average correct classification rates for the seven species of bacteria were 62.23 and 77.03 % based on MALDI-TOF-MS and LC-MS data, respectively. The Procrustes distance for the two datasets was 0.0699, indicating that the results from the two techniques were very similar. In addition, we also compared these bacterial lipid MALDI-TOF-MS profiles to protein profiles also collected by MALDI-TOF-MS on the same bacteria (Procrustes distance, 0.1006). The level of discrimination between lipids and proteins was equivalent, and this further indicated the potential of MALDI-TOF-MS analysis as a rapid, robust and reliable method for the classification of bacteria based on different bacterial chemical components. Graphical abstract MALDI-MS has been successfully developed for the characterization of bacteria at the subspecies level using lipids and benchmarked against HPLC.

Metabolomics investigation of recombinant mTNFα production in Streptomyces lividans.

BACKGROUND: Whilst undergoing differentiation, Streptomyces produce a large quantity of hydrolytic enzymes and secondary metabolites, and it is this very ability that has focussed increasing interest on the use of these bacteria as hosts for the production of various heterologous proteins. However, within this genus, the exploration and understanding of the metabolic burden associated with such bio-products has only just begun. In this study our overall aim was to apply metabolomics approaches as tools to get a glimpse of the metabolic alterations within S. lividans TK24 when this industrially relevant microbe is producing recombinant murine tumour necrosis factor alpha (mTNFα), in comparison to wild type and empty (non-recombinant protein containing) plasmid-carrying strains as controls. RESULTS: Whilst growth profiles of all strains demonstrated comparable trends, principal component-discriminant function analysis of Fourier transform infrared (FT-IR) spectral data, showed clear separation of wild type from empty plasmid and mTNFα-producing strains, throughout the time course of incubation. Analysis of intra- and extra-cellular metabolic profiles using gas chromatography-mass spectrometry (GC-MS) displayed similar trends to the FT-IR data. Although the strain carrying the empty plasmid demonstrated metabolic changes due to the maintenance of the plasmid, the metabolic behaviour of the recombinant mTNFα-producing strain appeared to be the most significantly affected. GC-MS results also demonstrated a significant overflow of several organic acids (pyruvate, 2-ketoglutarate and propanoate) and sugars (xylitol, mannose and fructose) in the mTNFα-producing strain. CONCLUSION: The results obtained in this study have clearly demonstrated the metabolic impacts of producing mTNFα in S. lividans TK24, while displaying profound metabolic effects of harbouring the empty PIJ486 plasmid. In addition, the level of mTNFα produced in this study, further highlights the key role of media composition towards the efficiency of a bioprocess and metabolic behaviour of the host cells, which directly influences the yield of the recombinant product.

Shotgun metabolomic profiles in maternal urine identify potential mass spectral markers of abnormal fetal biochemistry - dihydrouracil and progesterone in the metabolism of Down syndrome.

In Down syndrome (DS) in particular, the precise cellular mechanisms linking genotype to phenotype is not straightforward despite a clear mapping of the genetic cause. Metabolomic profiling might be more revealing in understanding molecular-cellular mechanisms of inborn errors of metabolism/syndromes than genomics alone and also result in new prenatal screening approaches. The urinary metabolome of 122 maternal urine from women with and without an aneuploid pregnancy (predominantly Down syndrome) were compared by both zwitterionic hydrophilic interaction chromatography (ZIC-HILIC) and reversed-phase liquid chromatography (RPLC) coupled to hybrid ion trap time of flight mass spectral analysis. ZIC-HILIC mass spectrometry resolved 10-fold more unique molecular ions than RPLC mass spectrometry, of which molecules corresponding to ions of m/z 114.07 and m/z 314.20 showed maternal urinary level changes that significantly coincided with the presence of a DS fetus. The ion of m/z 314.20 was identified as progesterone and m/z 114.07 as dihydrouracil. A metabolomics profiling-based maternal urinary screening test modelled from this separation data would detect approximately 87 and 60.87% (using HILIC-MS and RPLC-MS, respectively) of all DS pregnancies between 9 and 23 weeks of gestation with no false positives.

HILIC-MS-based shotgun metabolomic profiling of maternal urine at 9-23 weeks of gestation - establishing the baseline changes in the maternal metabolome.

In this data-rich age it is no longer necessary to methodically isolate, characterize and measure specific molecules. What is important is to identify which of the hundreds or thousands of resolved and measured 'unknown' molecules are potentially associated with the pathophysiology of interest. We have taken LC-MS data from pregnancy urine and applied SIMCA P+ data analysis software in shotgun metabolomics to search the large amount of data for significant metabolite changes that occur in the transition from the first to early second trimester of pregnancy. Seventy-two individual urine samples were examined spanning 9-23 weeks of gestation. Three-hundred and eighty-three ions were identified and variations were mapped between profiles of different gestational age and the significance quantified. In urine collected during pregnancy, the transition from first to early second trimester revealed a relatively steady pattern of metabolites except for four that showed a dramatic fall in abundance as pregnancy progressed from the first to second trimester. The pattern of changes in urinary metabolites identified by Zwitterionic Hydrophilic Liquid Interaction Chromatography (ZIC-HILIC) coupled to mass spectrometry was evaluated and we established a baseline of changes from which a search for metabolomic markers associated with clinical pathologies of pregnancy can be made as a part of wider ultraomics study.

Do not just do it, do it right: urinary metabolomics--establishing clinically relevant baselines.

Metabolomics is currently being adopted as a tool to understand numerous clinical pathologies. It is essential to choose the best combination of techniques in order to optimize the information gained from the biological sample examined. For example, separation by reverse-phase liquid chromatography may be suitable for biological fluids in which lipids, proteins and small organic compounds coexist in a relatively nonpolar environment, such as serum. However, urine is a highly polar environment and metabolites are often specifically altered to render them polar suitable for normal phase/hydrophilic interaction liquid chromatography. Similarly, detectors such as high-resolution mass spectrometry (MS) may negate the need for a pre-separation but specific detection and quantification of less abundant analytes in targeted metabolomics may require concentration of the ions by methods such an ion trap MS. In addition, the inherent variability of metabolomic profiles need to be established in appropriately large sample sets of normal controls. This review aims to explore various techniques that have been tried and tested over the past decade. Consideration is given to various key drawbacks and positive alternatives published by active research groups and an optimum combination that should be used for urinary metabolomics is suggested to generate a reliable dataset for baseline studies.

How storage post sampling influences the stability of sebum when used for mass spectrometry metabolomics analysis?

Sebum is a biofluid excreted by sebaceous glands in the skin. In recent years sebum has been shown to contain endogenous metabolites diagnostic of disease, with remarkable results for Parkinson's Disease. Given that sebum sampling is facile and non-invasive, its potential for use in clinical biochemistry diagnostic assays should be explored including the parameters for standard operating procedures around collection, transport, and storage. To this aim we have here investigated the reproducibility of mass spectrometry data from sebum in relation to both storage temperature and length of storage. Sebum samples were collected from volunteers and stored for up to four weeks at a range of temperatures: ambient (circa 17 °C), -20 °C and -80 °C. Established extraction protocols were employed and samples were analysed by two chromatographic mass spectrometry techniques and data investigated using PCA, PLS-DA and ANOVA. We cannot discriminate samples as a function of storage temperature or time stored in unsupervised analysis using data acquired via TD-GC-MS and LC-IM-MS, although the sampling of volatiles was susceptible to batch effects. This study indicates that the requirements for storage and transport of sebum samples that may be used in clinical assays are less stringent than for liquid samples and indicate that sebum is suitable for remote and at home sampling prior to analysis.

Chewing the fat: How lipidomics is changing our understanding of human health and disease in 2022.

Lipids are biological molecules that play vital roles in all living organisms. They perform many cellular functions, such as 1) forming cellular and subcellular membranes, 2) storing and using energy, and 3) serving as chemical messengers during intra- and inter-cellular signal transduction. The large-scale study of the pathways and networks of cellular lipids in biological systems is called "lipidomics" and is one of the fastest-growing omics technologies of the last two decades. With state-of-the-art mass spectrometry instrumentation and sophisticated data handling, clinical studies show how human lipid composition changes in health and disease, thereby making it a valuable medium to collect for clinical applications, such as disease diagnostics, therapeutic decision-making, and drug development. This review gives a comprehensive overview of current workflows used in clinical research, from sample collection and preparation to data and clinical interpretations. This is followed by an appraisal of applications in 2022 and a perspective on the exciting future of clinical lipidomics.

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.

Paper Spray Ionization Ion Mobility Mass Spectrometry of Sebum Classifies Biomarker Classes for the Diagnosis of Parkinson's Disease.

Parkinson's disease (PD) is the second most common neurodegenerative disorder, and identification of robust biomarkers to complement clinical diagnosis will accelerate treatment options. Here, we demonstrate the use of direct infusion of sebum from skin swabs using paper spray ionization coupled with ion mobility mass spectrometry (PS-IM-MS) to determine the regulation of molecular classes of lipids in sebum that are diagnostic of PD. A PS-IM-MS method for sebum samples that takes 3 min per swab was developed and optimized. The method was applied to skin swabs collected from 150 people and elucidates ∼4200 features from each subject, which were independently analyzed. The data included high molecular weight lipids (>600 Da) that differ significantly in the sebum of people with PD. Putative metabolite annotations of several lipid classes, predominantly triglycerides and larger acyl glycerides, were obtained using accurate mass, tandem mass spectrometry, and collision cross section measurements.

Metabolomics of sebum reveals lipid dysregulation in Parkinson's disease.

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.