The use of metabolomics to monitor simultaneous changes in metabolic variables following supramaximal low volume high intensity exercise

High Intensity Exercise (HIE) stimulates greater physiological remodeling when compared to workload matched low-moderate intensity exercise. This study utilized an untargeted metabolomics approach to examine the metabolic perturbations that occur following two workload matched supramaximal low volume HIE trials. In a randomized order, 7 untrained males completed two exercise protocols separated by one week; 1) HIE150%: 30 x 20s cycling at 150% VO2peak, 40s passive rest; 2) HIE300%: 30 x 10s cycling at 300% VO2peak, 50 s passive rest. Total exercise duration was 30 minutes for both trials. Blood samples were taken at rest, during and immediately following exercise and at 60 minutes post exercise. Gas chromatography-mass spectrometry (GC-MS) analysis of plasma identified 43 known metabolites of which 3 demonstrated significant fold changes (HIE300% compared to the HIE150% value) during exercise, 14 post exercise and 23 at the end of the recovery period. Significant changes in plasma metabolites relating to lipid metabolism [fatty acids: dodecanoate (p=0.042), hexadecanoate (p=0.001), octadecanoate (p=0.001)], total cholesterol (p=0.001), and glycolysis [lactate (p=0.018)] were observed following exercise and during the recovery period. The HIE300% protocol elicited greater metabolic changes relating to lipid metabolism and glycolysis when compared to HIE150% protocol. These changes were more pronounced throughout the recovery period rather than during the exercise bout itself. Data from the current study demonstrate the use of metabolomics to monitor intensity-dependent changes in multiple metabolic pathways following exercise. The small sample size indicates a need for further studies in a larger sample cohort to validate these findings.

LC- HRMS based metabolomics in food safety and doping control – DeTECH21

Issues surrounding the misuse of prohibited and licensed substances in animals destined for food production and performance sport competition continue to be an enormous challenge to regulatory authorities charged with enforcing their control. Efficient analytical strategies are implemented to screen and confirm the presence of a wide range of exogenous substances in various biological matrices. However, such methods rely on the direct measurement of drugs and/or their metabolites in a targeted mode, allowing the detection of restricted number of compounds. As a consequence, emerging practices, in particular the use of natural hormones, designer drugs and low-dose cocktails, remain difficult to handle from a control point of view. A new SME-led FP7 funded project, DeTECH21, aims to overcome current limitations by applying an untargeted metabolomics approach based on liquid chromatography coupled to high resolution mass spectrometry and bioinformatic data analysis to identify bovine and equine animals which have been exposed to exogenous substances and assist in the identification of administered compounds. Markerbased strategies, dealing with the comprehensive analysis of metabolites present in a biological sample (urine/plasma/tissue), offer a reliable solution in the areas of food safety and animal sport doping control by effective, high-throughput and sensitive detection of exogenously administered agents. Therefore, the development of the first commercially available forensic test service based on metabolomics profiling will meet 21st century demands in animal forensics.

Metabolomics as a tool to explore the staphylococcal biofilm

Orthopaedic infections can be polymicrobial existing as a microbiome. Infections often incorporate staphylococcal species, including Staphylococcus aureus. Such infections can lead to life threatening illness and implant failure. Furthermore, biofilm formation on the implant surface can occur, increasing pathogenicity, exacerbating antibiotic resistance and altering antimicrobial mechanism of action. Bacteria change dramatically during the transition to a biofilm growth state: phenotypically; transcriptionally; and metabolically, highlighting the need for research into molecular mechanisms involved in biofilm formation. Metabolomics can provide a tool to analyse metabolic changes which are directly related to the expressed phenotype. Here, we aimed to provide greater understanding of orthopaedic infection caused by S. aureus and biofilm formation on the implant surface. Through metagenome analysis by employing: implant material extraction; DNA extraction; microbial enrichment; and whole genome sequencing, we present a microbiome study of the infected prosthesis to resolve the causative species of orthopaedic hip infection. Results highlight the presence of S. aureus as a primary cause of orthopaedic infection along with Enterococcus faecium and the presence of secondary pathogen Clostridium difficile. Although results were hindered by the presence of host contaminating DNA even after microbial enrichment, conclusions could be made over the potential increased pathogenicity caused by the presence of a secondary pathogen and highlight method and sample preparation considerations when undertaking such a study. Following this finding, studies were focused on an orthopaedic clinical isolate of S. aureus and a metabolome extraction method for staphylococcal biofilms was developed using cell lysis through bead beating and solvent metabolome extraction. The method was found to be reproducible when coupled with liquid chromatography-mass spectrometry (LC-MS) and bioinformatics, allowing for the detection of significant changes in metabolism between planktonic and biofilm cultures to be identified and drug mechanism of actions (MOA) to be studied. Metabolomics results highlight significant changes in a number of metabolic pathways including arginine biosynthesis and purine metabolism between the two cell populations, evidence of S. aureus responding to their changing environment, including oxygen availability and a decrease in pH. Focused investigations on purine metabolism looking for biofilm modulation effects were carried out. Modulation of the S. aureus biofilm phenotype was observed through the addition of exogenous metabolites. Inosine increased biofilm biomass while formycin B, an inosine analogue, showed a dispersal effect and a potential synergistic effect in biofilm dispersal when coupled with gentamycin. Changes in metabolism between planktonic cells and biofilms highlight the requirement for antimicrobial testing to be carried out against planktonic cells and biofilms. Untargeted metabolomics was used to study the MOA of triclosan in S. aureus. The triclosan target and MOA in bacteria has already been characterised, however, questions remain over its effects in bacteria. Although the use of triclosan has come under increasing speculation, its full effects are still largely unknown. Results show that triclosan can induce a cascade of detrimental events in the cell metabolism including significant changes in amino acid metabolism, affecting planktonic cells and biofilms. Results and conclusions provide greater understanding of orthopaedic infections and specifically focus on the S. aureus biofilm, confirming S. aureus as a primary cause of orthopaedic infection and using metabolomic analysis to look at the changing state of metabolism between the different growth states. Metabolomics is a valuable tool for biofilm and drug MOA studies, helping understand orthopaedic infection and implant failure, providing crucial insight into the biochemistry of bacteria for the potential for inferences to be gained, such as the MOA of antimicrobials and the identification of novel metabolic drug targets.

Development of an integrated metabolomic profiling approach for infectious diseases research

Metabolomic profiling offers direct insights into the chemical environment and metabolic pathway activities at sites of human disease. During infection, this environment may receive important contributions from both host and pathogen. Here we apply an untargeted metabolomics approach to identify compounds associated with an E. coli urinary tract infection population. Correlative and structural data from minimally processed samples were obtained using an optimized LC-MS platform capable of resolving ~2300 molecular features. Principal component analysis readily distinguished patient groups and multiple supervised chemometric analyses resolved robust metabolomic shifts between groups. These analyses revealed nine compounds whose provisional structures suggest candidate infection-associated endocrine, catabolic, and lipid pathways. Several of these metabolite signatures may derive from microbial processing of host metabolites. Overall, this study highlights the ability of metabolomic approaches to directly identify compounds encountered by, and produced from, bacterial pathogens within human hosts.

Genome-wide association study of metabolic traits reveals novel gene-metabolite-disease links.

Metabolic traits are molecular phenotypes that can drive clinical phenotypes and may predict disease progression. Here, we report results from a metabolome- and genome-wide association study on (1)H-NMR urine metabolic profiles. The study was conducted within an untargeted approach, employing a novel method for compound identification. From our discovery cohort of 835 Caucasian individuals who participated in the CoLaus study, we identified 139 suggestively significant (P<5×10(-8)) and independent associations between single nucleotide polymorphisms (SNP) and metabolome features. Fifty-six of these associations replicated in the TasteSensomics cohort, comprising 601 individuals from São Paulo of vastly diverse ethnic background. They correspond to eleven gene-metabolite associations, six of which had been previously identified in the urine metabolome and three in the serum metabolome. Our key novel findings are the associations of two SNPs with NMR spectral signatures pointing to fucose (rs492602, P = 6.9×10(-44)) and lysine (rs8101881, P = 1.2×10(-33)), respectively. Fine-mapping of the first locus pinpointed the FUT2 gene, which encodes a fucosyltransferase enzyme and has previously been associated with Crohn's disease. This implicates fucose as a potential prognostic disease marker, for which there is already published evidence from a mouse model. The second SNP lies within the SLC7A9 gene, rare mutations of which have been linked to severe kidney damage. The replication of previous associations and our new discoveries demonstrate the potential of untargeted metabolomics GWAS to robustly identify molecular disease markers.

Urinary metabolomic profiling to identify biomarkers of a flavonoid-rich and flavonoid-poor fruits and vegetables diet: the FLAVURS trial in adults: the FLAVURS trial

The present study aims to investigate the dose dependent effects of consuming diets enriched in flavonoid-rich and flavonoid-poor fruits and vegetables on the urine metabolome of adults who had a C1.5 fold increased risk of cardiovascular diseases. A single-blind, dose-dependent, parallel randomized controlled dietary intervention was conducted where volunteers (n = 126) were randomly assigned to one of three diets: high flavonoid diet, low flavonoid diet or habitual diet as a control for 18 weeks. High resolution LC– MS untargeted metabolomics with minimal sample cleanup was performed using an Orbitrap mass spectrometer. Putative biomarkers which characterize diets with high and low flavonoid content were selected by state-of-the-art data analysis strategies and identified by HR-MS and HR-MS/MS assays. Discrimination between diets was observed by application of two linear mixedmodels: one including a diet-time interaction effect and the second containing only a time effect. Valerolactones, phenolic acids and their derivatives were among sixteen biomarkers related to the high flavonoid dietary exposure. Four biomarkers related to the low flavonoid diet belonged to the family of phenolic acids. For the first time abscisic acid glucuronide was reported as a biomarker after a dietary intake, however its origins have to be examined by future hypothesis driven experiments using a more targeted approach. This metabolomic analysis has identified a number of dose dependent urinary biomarkers (i.e. proline betaine or iberin-N-acetyl cysteine), which can be used in future observation and intervention studies to assess flavonoids and nonflavonoid phenolic intakes and compliance to fruit and vegetable intervention.

Investigating metabolomic biomarkers of hypoxic ischaemic encephalopathy

Background An early objective biomarker to predict the severity of hypoxic-ischaemic encephalopathy (HIE) and identify infants suitable for intervention remains elusive. This thesis aims to progress metabolomic markers of HIE through a pipeline of biomarker discovery and validation by employing a novel untargeted mass spectrometry metabolomic method. Methodology Term infants with perinatal asphyxia were recruited, all having umbilical cord blood (UCB) drawn and biobanked within three hours of birth. HIE was defined by Sarnat score at 24hours and continuous multichannel-EEG. Infant neurodevelopment was assessed at 36-42 months using the Bayley Scales of Infant and Toddler Development Ed. III (BSID-III). Untargeted metabolomic analysis of UCB was performed using direct injection FT-ICR mass spectrometry (DI FT-ICR MS). Putative metabolite annotations and lipid classes were assigned and pathway analysis was performed. Results Untargeted metabolomic analysis: Thirty enrolled infants were diagnosed with HIE, including 17 mild, 8 moderate, and 5 severe cases. Pathway analysis revealed that ΔHIE was associated with a 50% and 75% perturbation of tryptophan and pyrimidine metabolism respectively, alongside alterations in amino acid pathways. Significant metabolite alterations were detected from six putatively identified lipid classes including fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, sterol lipids and prenol lipids. Outcome prediction: Metabolite model scores significantly correlated with outcome R=0.429 (model A) and R=0.549 (model B) respectively. Model B demonstrates the potential to predict both severe outcome (AUROC of 0.915) and intact survival (AUROC of 0.800). The effect of haemolysis: On average 5% of polar and 1.5% of non-polar features were altered between paired haemolysed and clean samples. However unsupervised multivariate analysis concluded that the preanalytical variability introduced by haemolysis was negligible compared with the inherent biological inter-individual variability. Conclusion This research has employed untargeted metabolomics to identify potential early cord blood biomarkers of HIE and has performed the technical validation of previously proposed markers.

First metabolomic approach of the epiphytic bacteria-marine diatom Haslea ostrearia relationships

The marine diatom Haslea ostrearia [1] produces a water-soluble blue-pigment named marennine [2] of economic interest. But the lack of knowledge of the ecological conditions, under which this microalga develops in its natural ecosystem, more especially bacteria H. ostrearia interactions, prevents any optimization of its culture in well-controlled conditions. The structure of the bacterial community was analyzed by PCR-TTGE before and after the isolation of H. ostrearia cells recovered from 4 localities, to distinguish the relative part of the biotope and the biocenose and eventually to describe the temporal dynamic of the structure of the bacterial community at two time-scales. The differences in genetic fingerprints, more especially high between two H. ostrearia isolates (HO-R and HO-BM) showed also the highest differences in the bacterial structure [3] as the result of specific metabolomics profiles. The non-targeted metabolomic investigation showed that these profiles were more distinct in case of bacteria-alga associations than for the H. ostrearia monoculture Here we present a Q-TOF LC/MS metabolomic fingerprinting approach [3]: - to investigate differential metabolites of axenic versus non axenic H. ostrearia cultures. - to focus on the specific metabolites of a bacterial surrounding associated with the activation or inhibition of the microalga growing. The Agilent suite of data processing software makes feature finding, statistical analysis, and identification easier. This enables rapid transformation of complex raw data into biologically relevant metabolite information.

Preliminary metabolomic approach on the bacterial structure community of Haslea ostrearia

The marine diatom Haslea ostrearia [1] produces a water-soluble blue-pigment named marennine [2] of economic interest. But the lack of knowledge of the ecological conditions, under which this microalga develops in its natural ecosystem, more especially bacteria H. ostrearia interactions, prevents any optimization of its culture in well-controlled conditions. The structure of the bacterial community was analyzed by PCR-TTGE before and after the isolation of H. ostrearia cells recovered from 4 localities, to distinguish the relative part of the biotope and the biocenose and eventually to describe the temporal dynamic of the structure of the bacterial community at two time-scales. The differences in genetic fingerprints, more especially high between two H. ostrearia isolates (HO-R and HO-BM) showed also the highest differences in the bacterial structure [3] as the result of specific metabolomics profiles. The non-targeted metabolomic investigation showed that these profiles were more distinct in case of bacteria-alga associations than for the H. ostrearia monoculture Here we present a Q-TOF LC/MS metabolomic fingerprinting approach [3]: - to investigate differential metabolites of axenic versus non axenic H. ostrearia cultures. - to focus on the specific metabolites of a bacterial surrounding associated with the activation or inhibition of the microalga growing. The Agilent suite of data processing software makes feature finding, statistical analysis, and identification easier. This enables rapid transformation of complex raw data into biologically relevant metabolite information.

Antiplatelet therapy and clinical outcomes in cardiovascular diseases

Cardiovascular diseases (CVD) is a leading cause of death in the world. Despite effective treatment regimens for ischaemic heart disease (IHD) and ischaemic stroke, mortality and recurrence rates remain high. Antiplatelet therapy is on effective treatment and reduces the risk of recurrent heart attack and stroke. Nevertheless, there are patients who stopped or interrupted their antiplatelet therapy for certain reasons or some patients may be resistant or poor responders to antiplatelet therapy. Furthermore, there is evidence of rebound effect in platelet activity after antiplatelet cessation and this may associate with increased risk of cardiovascular event. This thesis is divided into five main chapters (chapters 3 to 7) which attempt to provide data to help resolve the uncertainty. Chapter 1 highlights the background of cardiovascular diseases and the global burden of cardiovascular and cerebrovascular diseases. The metabolism of platelets, antiplatelet therapy and current antiplatelet therapy guidelines are described, followed by discussion of the risk of cardiovascular event and changes in antiplatelet therapy. Chapter 2 describes the data source from Virtual International Stroke Trial Archive (VISTA) and National Health Service Greater Glasgow and Clyde (NHSGGC) Safe Haven, followed by definition of outcome measures. In chapter 3, Virtual International Stroke Trial Archive (VISTA) data was examined to test whether continue with the same antiplatelet therapy or changing to a new antiplatelet regimen reduces the risk of subsequent events in patients who experience a stroke whilst taking antiplatelet therapy. The findings indicate that subjects who switch to a new antiplatelet regimen after stroke did not have a lower early recurrence rate than subjects who continued with the same antiplatelet therapy. Observations on bleeding complications were similar in both groups. However, changing antiplatelet regimen after stroke was associated with more favourable functional outcome across a full scale modified Rankin Scale (mRS) at 90 days. In chapter 4, association between early or later initiation of antiplatelet with a recurrent ischaemic stroke and bleeding complications was assessed using VISTA data. The findings indicate that there was no association between a recurrent ischaemic stroke and timing of initiation of antiplatelet drug after stroke. However, early initiation was associated with increased risk of bleeding. In terms of functional outcomes, this study demonstrated that the mid-time and late initiation of antiplatelet therapy after acute stroke are associated with better functional outcomes compared with early initiation. In chapter 5, a nested case-control study was performed to explore the rate of antiplatelet cessation and interruption in a sample of patients with recent ischaemic stroke and to assess the risk of cardiovascular events associated with cessation and interruption of antiplatelet. It was found that there was no increased risk of cardiovascular event among patients who had early cessation or interrupted/stopped antiplatelet therapy within 90 days following acute ischaemic stroke. In chapter 6, the incidence and predictors of cardiovascular events after DAPT cessation were evaluated. The incidence of cardiovascular event while taking DAPT and following discontinuation of DAPT was 15.7% and 16.7% respectively. This study found that increasing age was associated with an increased risk of cardiovascular event, whereas, revascularization-treated patients and longer duration of DAPT, were each associated with a decreased risk. The duration of DAPT six months and less was associated a significantly higher risk for cardiovascular event. In chapter 7, an untargeted metabolomics analysis was performed while on DAPT (aspirin plus ticagrelor) and once they stopped ticagrelor to identify metabolite changes associated with cardiovascular events after stopping DAPT. Ten ACS patients were recruited in this study and data were analysed for seven patients. Three hundred eleven putative metabolites were identified. This study found 16 putative metabolites significantly altered following ticagrelor cessation. Of these, seven metabolites were from lipid pathway and down-regulated some up to 3-fold. On the other hand, adenosine, from nucleotide metabolism was upregulated up to 2.6-fold. It concluded that there are changes in numerous pathways following DAPT discontinuation and whether these changes differ in patients who have cardiovascular event after stopping DAPT warrant further investigation. In chapter 8, a summary of the findings of this thesis are presented as well as the future directions of research in this area.

Treatment of lean and diet-induced obesity (DIO) mice with a novel stable obestatin analogue alters plasma metabolite levels as detected by untargeted LC–MS metabolomics

Introduction: Obestatin is a controversial gastrointestinal peptide purported to have metabolic actions.

Objectives: This study investigated whether treatment with a stable obestatin analogue (PEG-OB(Cys10, Cys13)) changed plasma metabolite levels firstly in lean and subsequently in diet-induced obesity (DIO) C57BL6/J mice.

Methods: Untargeted LC-HRMS metabolomics experiments were carried out in ESI + mode with plasma extracts from both groups of animals. Data were normalised, multivariate and univariate statistical analysis performed and metabolites of interest putatively identified.

Results: In lean mice, 39 metabolites were significantly changed by obestatin treatment and the majority of these were increased, including various C16 and C18 moieties of phosphatidylcholine, phosphatidylethanolamine, phosphatidylserine and monoacylglycerol, along with vitamin A, vitamin D3, tyrosine, acetylcarnitine and 2α-(hydroxymethyl)-5α-androstane-3β,17β-diol. Decreased concentrations of glycolithocholic acid, 3-dehydroteasterone and various phospholipids were observed. In DIO mice, 25 metabolites were significantly affected and strikingly, the magnitudes of changes here were generally much greater in DIO mice than in lean mice, and in contrast, the majority of metabolite changes were decreases. Four metabolites affected in both groups included glycolithocholic acid, and three different long-chain (C18) phospholipid molecules (phosphatidylethanolamine, platelet activating factor (PAF), and monoacylglycerol). Metabolites exclusively affected in DIO mice included various phosphatidylcholines, lysophosphatidylcholines and fatty acyls, as well as creatine and oxidised glutathione.

Conclusion: This investigation demonstrates that obestatin treatment affects phospholipid turnover and influences lipid homeostasis, whilst providing convincing evidence that obestatin may be acting to ameliorate diet-induced impairments in lipid metabolism, and it may influence steroid, bile acid, PAF and glutathione metabolism.

Effect of insulin resistance on monounsaturated fatty acid levels : a multi-cohort non-targeted metabolomics and mendelian randomization study

Insulin resistance (IR) and impaired insulin secretion contribute to type 2 diabetes and cardiovascular disease. Both are associated with changes in the circulating metabolome, but causal directions have been difficult to disentangle. We combined untargeted plasma metabolomics by liquid chromatography/mass spectrometry in three non-diabetic cohorts with Mendelian Randomization (MR) analysis to obtain new insights into early metabolic alterations in IR and impaired insulin secretion. In up to 910 elderly men we found associations of 52 metabolites with hyperinsulinemic-euglycemic clamp-measured IR and/or β-cell responsiveness (disposition index) during an oral glucose tolerance test. These implicated bile acid, glycerophospholipid and caffeine metabolism for IR and fatty acid biosynthesis for impaired insulin secretion. In MR analysis in two separate cohorts (n = 2,613) followed by replication in three independent studies profiled on different metabolomics platforms (n = 7,824 / 8,961 / 8,330), we discovered and replicated causal effects of IR on lower levels of palmitoleic acid and oleic acid. A trend for a causal effect of IR on higher levels of tyrosine reached significance only in meta-analysis. In one of the largest studies combining "gold standard" measures for insulin responsiveness with non-targeted metabolomics, we found distinct metabolic profiles related to IR or impaired insulin secretion. We speculate that the causal effects on monounsaturated fatty acid levels could explain parts of the raised cardiovascular disease risk in IR that is independent of diabetes development.

New insight on obesity and adipose-derived stem cells by comprehensive metabolomics

Obesity affects the functional capability of adipose-derived stem cells (ASCs) and their effective use in regenerative medicine through mechanisms still poorly understood. Here we employed a multiplatform (LC/MS, CE/MS, GC/MS) metabolomics untargeted approach to investigate the metabolic alteration underlying the inequalities observed in obese-derived ASCs. The metabolic fingerprint (metabolites within the cells) and footprint (metabolites secreted in the culture medium) from humans or mice, obese and non-obese derived ASCs, were characterized by providing valuable information. Metabolites associated to glycolysis, TCA, pentose phosphate pathway and polyol pathway were increased in the footprint of obese-derived human ASCs indicating alterations in the carbohydrate metabolism; whereas from the murine model, deep differences in lipid and amino acid catabolism were highlighted. Therefore, new insights on the ASCs metabolome were provided that enhance our understanding of the processes underlying the ASCs stemness capacity and its relationship with obesity, in different cell models.

Mass spectrometry-based metabolomics towards understanding of gene functions with a diversity of biological contexts

Currently, mass spectrometry-based metabolomics studies extend beyond conventional chemical categorization and metabolic phenotype analysis to understanding gene function in various biological contexts (e.g., mammalian, plant, and microbial). These novel utilities have led to many innovative discoveries in the following areas: disease pathogenesis, therapeutic pathway or target identification, the biochemistry of animal and plant physiological and pathological activities in response to diverse stimuli, and molecular signatures of host-pathogen interactions during microbial infection. In this review, we critically evaluate the representative applications of mass spectrometry-based metabolomics to better understand gene function in diverse biological contexts, with special emphasis on working principles, study protocols, and possible future development of this technique. Collectively, this review raises awareness within the biomedical community of the scientific value and applicability of mass spectrometry-based metabolomics strategies to better understand gene function, thus advancing this application's utility in a broad range of biological fields