Quantitative LC-MS study of compounds found predictive of COVID-19 severity and outcome.

INTRODUCTION: Since the beginning of the SARS-CoV-2 pandemic in December 2019 multiple metabolomics studies have proposed predictive biomarkers of infection severity and outcome. Whilst some trends have emerged, the findings remain intangible and uninformative when it comes to new patients. OBJECTIVES: In this study, we accurately quantitate a subset of compounds in patient serum that were found predictive of severity and outcome. METHODS: A targeted LC-MS method was used in 46 control and 95 acute COVID-19 patient samples to quantitate the selected metabolites. These compounds included tryptophan and its degradation products kynurenine and kynurenic acid (reflective of immune response), butyrylcarnitine and its isomer (reflective of energy metabolism) and finally 3',4'-didehydro-3'-deoxycytidine, a deoxycytidine analogue, (reflective of host viral defence response). We subsequently examine changes in those markers by disease severity and outcome relative to those of control patients' levels. RESULTS & CONCLUSION: Finally, we demonstrate the added value of the kynurenic acid/tryptophan ratio for severity and outcome prediction and highlight the viral detection potential of ddhC.

Determining the role of novel metabolic pathways in driving intracranial pressure reduction after weight loss.

Idiopathic intracranial hypertension, a disease classically occurring in women with obesity, is characterized by raised intracranial pressure. Weight loss leads to the reduction in intracranial pressure. Additionally, pharmacological glucagon-like peptide-1 agonism reduces cerebrospinal fluid secretion and intracranial pressure. The potential mechanisms by which weight loss reduces intracranial pressure are unknown and were the focus of this study. Meal stimulation tests (fasted plasma sample, then samples at 15, 30, 60, 90 and 120 min following a standardized meal) were conducted pre- and post-bariatric surgery [early (2 weeks) and late (12 months)] in patients with active idiopathic intracranial hypertension. Dynamic changes in gut neuropeptides (glucagon-like peptide-1, gastric inhibitory polypeptide and ghrelin) and metabolites (untargeted ultra-high performance liquid chromatography-mass spectrometry) were evaluated. We determined the relationship between gut neuropeptides, metabolites and intracranial pressure. Eighteen idiopathic intracranial hypertension patients were included [Roux-en-Y gastric bypass (RYGB) n = 7, gastric banding n = 6 or sleeve gastrectomy n = 5]. At 2 weeks post-bariatric surgery, despite similar weight loss, RYGB had a 2-fold (50%) greater reduction in intracranial pressure compared to sleeve. Increased meal-stimulated glucagon-like peptide-1 secretion was observed after RYGB (+600%) compared to sleeve (+319%). There was no change in gastric inhibitory polypeptide and ghrelin. Dynamic changes in meal-stimulated metabolites after bariatric surgery consistently identified changes in lipid metabolites, predominantly ceramides, glycerophospholipids and lysoglycerophospholipids, which correlated with intracranial pressure. A greater number of differential lipid metabolites were observed in the RYGB cohort at 2 weeks, and these also correlated with intracranial pressure. In idiopathic intracranial hypertension, we identified novel changes in lipid metabolites and meal-stimulated glucagon-like peptide-1 levels following bariatric surgery which were associated with changes in intracranial pressure. RYGB was most effective at reducing intracranial pressure despite analogous weight loss to gastric sleeve at 2 weeks post-surgery and was associated with more pronounced changes in these metabolite pathways. We suggest that these novel perturbations in lipid metabolism and glucagon-like peptide-1 secretion are mechanistically important in driving a reduction in intracranial pressure following weight loss in patients with idiopathic intracranial hypertension. Therapeutic targeting of these pathways, for example with glucagon-like peptide-1 agonist infusion, could represent a therapeutic strategy.

Unlocking the secrets of the microbiome: exploring the dynamic microbial interplay with humans through metabolomics and their manipulation for synthetic biology applications.

Metabolomics is a powerful research discovery tool with the potential to measure hundreds to low thousands of metabolites. In this review, we discuss the application of GC-MS and LC-MS in discovery-based metabolomics research, we define metabolomics workflows and we highlight considerations that need to be addressed in order to generate robust and reproducible data. We stress that metabolomics is now routinely applied across the biological sciences to study microbiomes from relatively simple microbial systems to their complex interactions within consortia in the host and the environment and highlight this in a range of biological species and mammalian systems including humans. However, challenges do still exist that need to be overcome to maximise the potential for metabolomics to help us understanding biological systems. To demonstrate the potential of the approach we discuss the application of metabolomics in two broad research areas: (1) synthetic biology to increase the production of high-value fine chemicals and reduction in secondary by-products and (2) gut microbial interaction with the human host. While burgeoning in importance, the latter is still in its infancy and will benefit from the development of tools to detangle host-gut-microbial interactions and their impact on human health and diseases.

Providing metabolomics education and training: pedagogy and considerations.

BACKGROUND: Metabolomics is a highly multidisciplinary and non-standardised research field. Metabolomics researchers must possess and apply extensive cross-disciplinary content knowledge, subjective experience-based judgement, and the associated diverse skill sets. Accordingly, appropriate educational and training initiatives are important in developing this knowledge and skills base in the metabolomics community. For these initiatives to be successful, they must consider both pedagogical best practice and metabolomics-specific contextual challenges. AIM OF REVIEW: The aim of this review is to provide consolidated pedagogical guidance for educators and trainers in metabolomics educational and training programmes. KEY SCIENTIFIC CONCEPTS OF REVIEW: In this review, we discuss the principles of pedagogical best practice as they relate to metabolomics. We then discuss the challenges and considerations in developing and delivering education and training in metabolomics. Finally, we present examples from our own teaching practice to illustrate how pedagogical best practice can be integrated into metabolomics education and training programmes.

Suitability of Dried Blood Spots for Accelerating Veterinary Biobank Collections and Identifying Metabolomics Biomarkers With Minimal Resources.

Biomarker discovery using biobank samples collected from veterinary clinics would deliver insights into the diverse population of pets and accelerate diagnostic development. The acquisition, preparation, processing, and storage of biofluid samples in sufficient volumes and at a quality suitable for later analysis with most suitable discovery methods remain challenging. Metabolomics analysis is a valuable approach to detect health/disease phenotypes. Pre-processing changes during preparation of plasma/serum samples may induce variability that may be overcome using dried blood spots (DBSs). We report a proof of principle study by metabolite fingerprinting applying UHPLC-MS of plasma and DBSs acquired from healthy adult dogs and cats (age range 1-9 years), representing each of 4 dog breeds (Labrador retriever, Beagle, Petit Basset Griffon Vendeen, and Norfolk terrier) and the British domestic shorthair cat (n = 10 per group). Blood samples (20 and 40 µL) for DBSs were loaded onto filter paper, air-dried at room temperature (3 h), and sealed and stored (4°C for ~72 h) prior to storage at -80°C. Plasma from the same blood draw (250 µL) was prepared and stored at -80°C within 1 h of sampling. Metabolite fingerprinting of the DBSs and plasma produced similar numbers of metabolite features that had similar abilities to discriminate between biological classes and correctly assign blinded samples. These provide evidence that DBSs, sampled in a manner amenable to application in in-clinic/in-field processing, are a suitable sample for biomarker discovery using UHPLC-MS metabolomics. Further, given appropriate owner consent, the volumes tested (20-40 µL) make the acquisition of remnant blood from blood samples drawn for other reasons available for biobanking and other research activities. Together, this makes possible large-scale biobanking of veterinary samples, gaining sufficient material sooner and enabling quicker identification of biomarkers of interest.

Metabolomics Reveal Potential Natural Substrates of AcrB in Escherichia coli and Salmonella enterica Serovar Typhimurium.

In the fight against antibiotic resistance, drugs that target resistance mechanisms in bacteria can be used to restore the therapeutic effectiveness of antibiotics. The multidrug resistance efflux complex AcrAB-TolC is the most clinically relevant efflux pump in Enterobacterales and is a target for drug discovery. Inhibition of the pump protein AcrB allows the intracellular accumulation of a wide variety of antibiotics, effectively restoring their therapeutic potency. To facilitate the development of AcrB efflux inhibitors, it is desirable to discover the native substrates of the pump, as these could be chemically modified to become inhibitors. We analyzed the native substrate profile of AcrB in Escherichia coli MG1655 and Salmonella enterica serovar Typhimurium SL1344 using an untargeted metabolomics approach. We analyzed the endo- and exometabolome of the wild-type strain and their respective AcrB loss-of-function mutants (AcrB D408A) to determine the metabolites that are native substrates of AcrB. Although there is 95% homology between the AcrB proteins of S. Typhimurium and E. coli, we observed mostly different metabolic responses in the exometabolomes of the S. Typhimurium and E. coli AcrB D408A mutants relative to those in the wild type, potentially indicating a differential metabolic adaptation to the same mutation in these two species. Additionally, we uncovered metabolite classes that could be involved in virulence of S. Typhimurium and a potential natural substrate of AcrB common to both species.IMPORTANCE Multidrug-resistant Gram-negative bacteria pose a global threat to human health. The AcrB efflux pump confers inherent and evolved drug resistance to Enterobacterales, including Escherichia coli and Salmonella enterica serovar Typhimurium. We provide insights into the physiological role of AcrB: (i) we observe that loss of AcrB function in two highly related species, E. coli and S. Typhimurium, has different biological effects despite AcrB conferring drug resistance to the same groups of antibiotics in both species, and (ii) we identify potential natural substrates of AcrB, some of which are in metabolite classes implicated in the virulence of S. Typhimurium. Molecules that inhibit multidrug efflux potentiate the activity of old, licensed, and new antibiotics. The additional significance of our research is in providing data about the identity of potential natural substrates of AcrB in both species. Data on these will facilitate the discovery of, and/or could be chemically modified to become, new efflux inhibitors.

International Ring Trial of a High Resolution Targeted Metabolomics and Lipidomics Platform for Serum and Plasma Analysis.

A challenge facing metabolomics in the analysis of large human cohorts is the cross-laboratory comparability of quantitative metabolomics measurements. In this study, 14 laboratories analyzed various blood specimens using a common experimental protocol provided with the Biocrates AbsoluteIDQ p400HR kit, to quantify up to 408 metabolites. The specimens included human plasma and serum from male and female donors, mouse and rat plasma, as well as NIST SRM 1950 reference plasma. The metabolite classes covered range from polar (e.g., amino acids and biogenic amines) to nonpolar (e.g., diacyl- and triacyl-glycerols), and they span 11 common metabolite classes. The manuscript describes a strict system suitability testing (SST) criteria used to evaluate each laboratory's readiness to perform the assay, and provides the SST Skyline documents for public dissemination. The study found approximately 250 metabolites were routinely quantified in the sample types tested, using Orbitrap instruments. Interlaboratory variance for the NIST SRM-1950 has a median of 10% for amino acids, 24% for biogenic amines, 38% for acylcarnitines, 25% for glycerolipids, 23% for glycerophospholipids, 16% for cholesteryl esters, 15% for sphingolipids, and 9% for hexoses. Comparing to consensus values for NIST SRM-1950, nearly 80% of comparable analytes demonstrated bias of <50% from the reference value. The findings of this study result in recommendations of best practices for system suitability, quality control, and calibration. We demonstrate that with appropriate controls, high-resolution metabolomics can provide accurate results with good precision across laboratories, and the p400HR therefore is a reliable approach for generating consistent and comparable metabolomics data.

Multiple metabolic pathways are predictive of ricin intoxication in a rat model.

INTRODUCTION: Exposure to ricin can be lethal and treatments that are under development have short windows of opportunity for administration after exposure. It is therefore essential to achieve early detection of ricin exposure to provide the best prognosis for exposed individuals. Ricin toxin can be detected in clinical samples via several antibody-based techniques, but the efficacy of these can be limited due to the rapid processing and cellular uptake of toxin in the body and subsequent low blood ricin concentrations. Other diagnostic tools that perform, in an orthogonal manner, are therefore desirable. OBJECTIVES: To determine time-dependent metabolic changes in Sprague-Dawley rats following intravenous exposure to ricin. METHODS: Sprague-Dawley rats were intravenously exposed to ricin and multiple blood samples were collected from each animal for up to 48 h following exposure in two independent studies. Plasma samples were analysed applying HILIC and C18 reversed phase UHPLC-MS assays followed by univariate and multivariate analysis. RESULTS: In Sprague-Dawley rats we have demonstrated that metabolic changes measured in blood can distinguish between rats exposed intravenously to ricin and controls prior to the onset of behavioral signs of intoxication after 24 h. A total of 37 metabolites were significantly altered following exposure to ricin when compared to controls. The arginine/proline, bile acid and triacylglyceride metabolic pathways were highlighted as being important with two triacylglycerides at 8 h post exposure giving an AUROC score of 0.94. At 16 h and 24 h the AUROC score increased to 0.98 and 1.0 with the number of metabolites in the panel increasing to 5 and 7, respectively. CONCLUSIONS: These data demonstrate that metabolites may be a useful tool to diagnose and detect ricin exposure, thus increasing the effectiveness of supportive therapy and future ricin-specific medical treatments.

Exploring the mode of action of dithranol therapy for psoriasis: a metabolomic analysis using HaCaT cells.

Psoriasis is a common, immune-mediated inflammatory skin disease characterized by red, heavily scaled plaques. The disease affects over one million people in the UK and causes significant physical, psychological and societal impact. There is limited understanding regarding the exact pathogenesis of the disease although it is believed to be a consequence of genetic predisposition and environmental triggers. Treatments vary from topical therapies, such as dithranol, for disease of limited extent (<5% body surface area) to the new immune-targeted biologic therapies for severe psoriasis. Dithranol (also known as anthralin) is a topical therapy for psoriasis believed to work by inhibiting keratinocyte proliferation. To date there have been no metabolomic-based investigations into psoriasis. The HaCaT cell line is a model system for the epidermal keratinocyte proliferation characteristic of psoriasis and was thus chosen for study. Dithranol was applied at therapeutically relevant doses to HaCaT cells. Following the optimisation of enzyme inactivation and metabolite extraction, gas chromatography-mass spectrometry was employed for metabolomics as this addresses central metabolism. Cells were challenged with 0-0.5 µg mL(-1) in 0.1 µg mL(-1) steps and this quantitative perturbation generated data that were highly amenable to correlation analysis. Thus, we used a combination of traditional principal components analysis, hierarchical cluster analysis, along with correlation networks. All methods highlighted distinct metabolite groups, which had different metabolite trajectories with respect to drug concentration and the interpretation of these data established that cellular metabolism had been altered significantly and provided further clarification of the proposed mechanism of action of the drug.

Molecular phenotyping of a UK population: defining the human serum metabolome.

Phenotyping of 1,200 'healthy' adults from the UK has been performed through the investigation of diverse classes of hydrophilic and lipophilic metabolites present in serum by applying a series of chromatography-mass spectrometry platforms. These data were made robust to instrumental drift by numerical correction; this was prerequisite to allow detection of subtle metabolic differences. The variation in observed metabolite relative concentrations between the 1,200 subjects ranged from less than 5 % to more than 200 %. Variations in metabolites could be related to differences in gender, age, BMI, blood pressure, and smoking. Investigations suggest that a sample size of 600 subjects is both necessary and sufficient for robust analysis of these data. Overall, this is a large scale and non-targeted chromatographic MS-based metabolomics study, using samples from over 1,000 individuals, to provide a comprehensive measurement of their serum metabolomes. This work provides an important baseline or reference dataset for understanding the 'normal' relative concentrations and variation in the human serum metabolome. These may be related to our increasing knowledge of the human metabolic network map. Information on the Husermet study is available at http://www.husermet.org/. Importantly, all of the data are made freely available at MetaboLights (http://www.ebi.ac.uk/metabolights/).

A model of yeast glycolysis based on a consistent kinetic characterisation of all its enzymes.

We present an experimental and computational pipeline for the generation of kinetic models of metabolism, and demonstrate its application to glycolysis in Saccharomyces cerevisiae. Starting from an approximate mathematical model, we employ a "cycle of knowledge" strategy, identifying the steps with most control over flux. Kinetic parameters of the individual isoenzymes within these steps are measured experimentally under a standardised set of conditions. Experimental strategies are applied to establish a set of in vivo concentrations for isoenzymes and metabolites. The data are integrated into a mathematical model that is used to predict a new set of metabolite concentrations and reevaluate the control properties of the system. This bottom-up modelling study reveals that control over the metabolic network most directly involved in yeast glycolysis is more widely distributed than previously thought.

Improving metabolic flux predictions using absolute gene expression data.

BACKGROUND: Constraint-based analysis of genome-scale metabolic models typically relies upon maximisation of a cellular objective function such as the rate or efficiency of biomass production. Whilst this assumption may be valid in the case of microorganisms growing under certain conditions, it is likely invalid in general, and especially for multicellular organisms, where cellular objectives differ greatly both between and within cell types. Moreover, for the purposes of biotechnological applications, it is normally the flux to a specific metabolite or product that is of interest rather than the rate of production of biomass per se. RESULTS: An alternative objective function is presented, that is based upon maximising the correlation between experimentally measured absolute gene expression data and predicted internal reaction fluxes. Using quantitative transcriptomics data acquired from Saccharomyces cerevisiae cultures under two growth conditions, the method outperforms traditional approaches for predicting experimentally measured exometabolic flux that are reliant upon maximisation of the rate of biomass production. CONCLUSION: Due to its improved prediction of experimentally measured metabolic fluxes, and of its lack of a requirement for knowledge of the biomass composition of the organism under the conditions of interest, the approach is likely to be of rather general utility. The method has been shown to predict fluxes reliably in single cellular systems. Subsequent work will investigate the method's ability to generate condition- and tissue-specific flux predictions in multicellular organisms.

Raman spectroscopy: lighting up the future of microbial identification.

Over the last decade Raman spectroscopy has become established as a physicochemical technique for the rapid identification of microbes. This powerful analytical method generates a spectroscopic fingerprint from the microbial sample, which provides quantitative and qualitative information that can be used to characterize, discriminate and identify microorganisms, in both bacteria slurry and at the single-cell level. Recent developments in Raman spectroscopy have dramatically increased in recent years due to the enhancement of the signal by techniques including tip-enhanced Raman spectroscopy and coherent anti-Stokes Raman spectroscopy and due to the availability of user-friendly instrumentation and software. The result of this has been reduced cost and rapid collection time, and it has allowed the nonspecialist access to this physical sciences approach for biological applications. In this article, we will briefly explain the technique of Raman spectroscopy and discuss enhancement techniques, including the recent application of tip-enhanced Raman spectroscopy to microbiology, as well as the move towards rapid microbial identification with Raman spectroscopy. Furthermore, recent studies have combined Raman spectroscopy with microfluidic devices, giving greater control of sample conditions, which will no doubt have an important impact in the future development of Raman spectroscopy for microbial identification.

Absolute quantification of the glycolytic pathway in yeast: deployment of a complete QconCAT approach.

The availability of label-free data derived from yeast cells (based on the summed intensity of the three strongest, isoform-specific peptides) permitted a preliminary assessment of protein abundances for glycolytic proteins. Following this analysis, we demonstrate successful application of the QconCAT technology, which uses recombinant DNA techniques to generate artificial concatamers of large numbers of internal standard peptides, to the quantification of enzymes of the glycolysis pathway in the yeast Saccharomyces cerevisiae. A QconCAT of 88 kDa (59 tryptic peptides) corresponding to 27 isoenzymes was designed and built to encode two or three analyte peptides per protein, and after stable isotope labeling of the standard in vivo, protein levels were determined by LC-MS, using ultra high performance liquid chromatography-coupled mass spectrometry. We were able to determine absolute protein concentrations between 14,000 and 10 million molecules/cell. Issues such as efficiency of extraction and completeness of proteolysis are addressed, as well as generic factors such as optimal quantotypic peptide selection and expression. In addition, the same proteins were quantified by intensity-based label-free analysis, and both sets of data were compared with other quantification methods.

The use of continuous culture in systems biology investigations.

When acquiring data for systems biology studies, it is essential to perform the experiments in controlled and reproducible conditions. Advances in the fields of proteomics and metabolomics allow the quantitative analysis of the components of the biological cell. It is essential to include a method in the experimental pipeline to culture the biological system in controlled and reproducible conditions to facilitate the acquisition of high-quality data. The employment of continuous culture methods for the growth of microorganisms is an ideal tool to achieve these objectives. This chapter will review the continuous culture approaches which may be applied in such studies, outline the experimental options which should be considered, and describe the approach applied in the production of steady-state cultures of Saccharomyces cerevisiae.

Sample preparation related to the intracellular metabolome of yeast methods for quenching, extraction, and metabolite quantitation.

The determination of intracellular metabolite concentrations in Saccharomyces cerevisiae cell systems requires appropriate experimental methods to (a) collect cells and rapidly inhibit metabolism (quenching), (b) fracture cell walls and extract metabolites from within the cellular envelope(s), and (c) detect and quantify metabolites. A range of methods are applied for each of these processes, and no single method is appropriate for all metabolites. For example, the physicochemical diversity of metabolites, including solubility in water or organic solvents, is large. No single extraction solvent is appropriate for all metabolites reported in S. cerevisiae, and multiple solvent systems for extraction employing water, methanol, and chloroform at different pH are recommended for targeted extraction of metabolites. In this chapter, methods for the targeted study of organic acids present in the tricarboxylic acid cycle will be described. These include (a) the quenching of metabolism in batch cell cultures, (b) a single extraction method which provides the extraction of a wide diversity of metabolites, and (c) an analytical method applying gas chromatography-mass spectrometry for targeted analysis of six organic acids present in the tricarboxylic acid cycle metabolic pathway.

Fit-for-purpose quenching and extraction protocols for metabolic profiling of yeast using chromatography-mass spectrometry platforms.

Metabolomics involves the investigation of the intracellular (endometabolome) and extracellular (exometabolome) pools of metabolites in biological systems. Methods to sample the exometabolome and to quench metabolism and extract intracellular metabolites for the model eukaryote Saccharomyces cerevisiae are presented here. These methods have been developed and validated to provide a fit-for-purpose protocol for global analyses of the S. cerevisiae metabolome. The protocol allows the extraction of a wide variety of metabolite classes and provides reproducible results to allow relative and semi-quantitative comparisons between samples of different origin. For exometabolome studies, fast sampling and separation of cells by syringe filtration is recommended. For endometabolome studies, fast quenching of intracellular metabolism is performed using a 60:40 (v/v) methanol:aqueous ammonium hydrogen carbonate solution at -48 °C. Extraction of intracellular metabolites is performed using multiple freeze/thaw cycles in a 60:40 (v/v) methanol:water solution at temperatures lower than 0 °C.

TARDIS-based microbial metabolomics: time and relative differences in systems.

Metabolomics can play a particularly important role in elucidating novel anabolic and catabolic pathways in bacteria and fungi, and in understanding the dynamics of metabolism. In these approaches, an isotopically labelled substrate, with an artificially high abundance of isotopic label, is fed to the microorganism under study. The products become isotopically labelled, and can be measured using a combination of mass spectrometry and nuclear magnetic resonance spectroscopy. This mass isotopomer analysis is referred to as time and relative differences in systems (TARDIS)-based analysis, as it measures and quantifies the temporal sequential emergence of these labelled products. In this review, we cover this topic from an experimental point of view in relation to the study of metabolism, and summarise how the application of radioactive and stable isotopes is being used in pathway elucidation and metabolic flux determination (fluxomics).

Metabolomic approaches reveal that cell wall modifications play a major role in ethylene-mediated resistance against Botrytis cinerea.

In Arabidopsis, resistance to the necrotrophic fungus Botrytis cinerea is conferred by ethylene via poorly understood mechanisms. Metabolomic approaches compared the responses of the wild-type, the ethylene-insensitive mutant etr1-1, which showed increased susceptibility, and the constitutively active ethylene mutants ctr1-1 and eto2 both exhibited decreased susceptibility to B. cinerea. Fourier transform-infrared (FT-IR) spectroscopy demonstrated reproducible biochemical differences between treatments and genotypes. To identify discriminatory mass-to-charge ratios (m/z) associated with resistance, discriminant function analysis was employed on spectra derived from direct injection electrospray ionisation-mass spectrometry on the derived principal components of these data. Ethylene-modulated m/z were mapped onto Arabidopsis biochemical pathways and many were associated with hydroxycinnamate and monolignol biosynthesis, both linked to cell wall modification. A high-resolution linear triple quadrupole-Orbitrap hybrid system confirmed the identity of key metabolites in these pathways. The contribution of these pathways to defence against B. cinerea was validated through the use of multiple Arabidopsis mutants. The FT-IR microspectroscopy indicated that spatial accumulation of hydroxycinnamates and monolignols at the cell wall to confine disease was linked ot ethylene. These data demonstrate the power of metabolomic approaches in elucidating novel biological phenomena, especially when coupled to validation steps exploiting relevant mutant genotypes.