Expanding flavone and flavonol production capabilities in Escherichia coli

Flavones and flavonols are important classes of flavonoids with nutraceutical and pharmacological value, and their production by fermentation with recombinant microorganisms promises to be a scalable and economically favorable alternative to extraction from plant sources. Flavones and flavonols have been produced recombinantly in a number of microorganisms, with Saccharomyces cerevisiae typically being a preferred production host for these compounds due to higher yields and titers of precursor compounds, as well as generally improved ability to functionally express cytochrome P450 enzymes without requiring modification to improve their solubility. Recently, a rapid prototyping platform has been developed for high-value compounds in E. coli, and a number of gatekeeper (2S)-flavanones, from which flavones and flavonols can be derived, have been produced to high titers in E. coli using this platform. In this study, we extended these metabolic pathways using the previously reported platform to produce apigenin, chrysin, luteolin and kaempferol from the gatekeeper flavonoids naringenin, pinocembrin and eriodictyol by the expression of either type-I flavone synthases (FNS-I) or type-II flavone synthases (FNS-II) for flavone biosynthesis, and by the expression of flavanone 3-dioxygenases (F3H) and flavonol synthases (FLS) for the production of the flavonol kaempferol. In our best-performing strains, titers of apigenin and kaempferol reached 128 mg L-1 and 151 mg L-1 in 96-DeepWell plates in cultures supplemented with an additional 3 mM tyrosine, though titers for chrysin (6.8 mg L-1) from phenylalanine, and luteolin (5.0 mg L-1) from caffeic acid were considerably lower. In strains with upregulated tyrosine production, apigenin and kaempferol titers reached 80.2 mg L-1 and 42.4 mg L-1 respectively, without the further supplementation of tyrosine beyond the amount present in the rich medium. Notably, the highest apigenin, chrysin and luteolin titers were achieved with FNS-II enzymes, suggesting that cytochrome P450s can show competitive performance compared with non-cytochrome P450 enzymes in prokaryotes for the production of flavones.

Mapping the Initial Stages of a Protective Pathway that Enhances Catalytic Turnover by a Lytic Polysaccharide Monooxygenase

Oxygenase and peroxygenase enzymes generate intermediates at their active sites which bring about the controlled functionalization of inert C-H bonds in substrates, such as in the enzymatic conversion of methane to methanol. To be viable catalysts, however, these enzymes must also prevent oxidative damage to essential active site residues, which can occur during both coupled and uncoupled turnover. Herein, we use a combination of stopped-flow spectroscopy, targeted mutagenesis, TD-DFT calculations, high-energy resolution fluorescence detection X-ray absorption spectroscopy, and electron paramagnetic resonance spectroscopy to study two transient intermediates that together form a protective pathway built into the active sites of copper-dependent lytic polysaccharide monooxygenases (LPMOs). First, a transient high-valent species is generated at the copper histidine brace active site following treatment of the LPMO with either hydrogen peroxide or peroxyacids in the absence of substrate. This intermediate, which we propose to be a CuII-(histidyl radical), then reacts with a nearby tyrosine residue in an intersystem-crossing reaction to give a ferromagnetically coupled (S = 1) CuII-tyrosyl radical pair, thereby restoring the histidine brace active site to its resting state and allowing it to re-enter the catalytic cycle through reduction. This process gives the enzyme the capacity to minimize damage to the active site histidine residues "on the fly" to increase the total turnover number prior to enzyme deactivation, highlighting how oxidative enzymes are evolved to protect themselves from deleterious side reactions during uncoupled turnover.

Metabolomics of Escherichia coli for Disclosing Novel Metabolic Engineering Strategies for Enhancing Hydrogen and Ethanol Production

The biological production of hydrogen is an appealing approach to mitigating the environmental problems caused by the diminishing supply of fossil fuels and the need for greener energy. Escherichia coli is one of the best-characterized microorganisms capable of consuming glycerol-a waste product of the biodiesel industry-and producing H₂ and ethanol. However, the natural capacity of E. coli to generate these compounds is insufficient for commercial or industrial purposes. Metabolic engineering allows for the rewiring of the carbon source towards H₂ production, although the strategies for achieving this aim are difficult to foresee. In this work, we use metabolomics platforms through GC-MS and FT-IR techniques to detect metabolic bottlenecks in the engineered ΔldhΔgndΔfrdBC::kan (M4) and ΔldhΔgndΔfrdBCΔtdcE::kan (M5) E. coli strains, previously reported as improved H₂ and ethanol producers. In the M5 strain, increased intracellular citrate and malate were detected by GC-MS. These metabolites can be redirected towards acetyl-CoA and formate by the overexpression of the citrate lyase (CIT) enzyme and by co-overexpressing the anaplerotic human phosphoenol pyruvate carboxykinase (hPEPCK) or malic (MaeA) enzymes using inducible promoter vectors. These strategies enhanced specific H₂ production by up to 1.25- and 1.49-fold, respectively, compared to the reference strains. Other parameters, such as ethanol and H₂ yields, were also enhanced. However, these vectors may provoke metabolic burden in anaerobic conditions. Therefore, alternative strategies for a tighter control of protein expression should be addressed in order to avoid undesirable effects in the metabolic network.

Metabolomics for the design of new metabolic engineering strategies for improving aerobic succinic acid production in Escherichia coli

INTRODUCTION

Glycerol is a byproduct from the biodiesel industry that can be biotransformed by Escherichia coli to high added-value products such as succinate under aerobic conditions. The main genetic engineering strategies to achieve this aim involve the mutation of succinate dehydrogenase (sdhA) gene and also those responsible for acetate synthesis including acetate kinase, phosphate acetyl transferase and pyruvate oxidase encoded by ackA, pta and pox genes respectively in the ΔsdhAΔack-ptaΔpox (M4) mutant. Other genetic manipulations to rewire the metabolism toward succinate consist on the activation of the glyoxylate shunt or blockage the pentose phosphate pathway (PPP) by deletion of isocitrate lyase repressor (iclR) or gluconate dehydrogenase (gnd) genes on M4-ΔiclR and M4-Δgnd mutants respectively.

OBJECTIVE

To deeply understand the effect of the blocking of the pentose phosphate pathway (PPP) or the activation of the glyoxylate shunt, metabolite profiles were analyzed on M4-Δgnd, M4-ΔiclR and M4 mutants.

METHODS

Metabolomics was performed by FT-IR and GC-MS for metabolite fingerprinting and HPLC for quantification of succinate and glycerol.

RESULTS

Most of the 65 identified metabolites showed lower relative levels in the M4-ΔiclR and M4-Δgnd mutants than those of the M4. However, fructose 1,6-biphosphate, trehalose, isovaleric acid and mannitol relative concentrations were increased in M4-ΔiclR and M4-Δgnd mutants. To further improve succinate production, the synthesis of mannitol was suppressed by deletion of mannitol dehydrogenase (mtlD) on M4-ΔgndΔmtlD mutant that increase ~ 20% respect to M4-Δgnd.

CONCLUSION

Metabolomics can serve as a holistic tool to identify bottlenecks in metabolic pathways by a non-rational design. Genetic manipulation to release these restrictions could increase the production of succinate.

Comparing root exudate collection techniques: An improved hybrid method

1. Plant-microbe interactions are critical for ecosystem functioning and drive rhizosphere processes. Root exudates are an important soil carbon (C) input, as well as a mechanism for communication between plants and rhizosphere microbes, but are notoriously difficult to extract and characterise. Common methods produce either substantial noise from the soil or do not mimic natural systems. Optimising methods for root exudate collection in soil is crucial for advancing our understanding of root-microbe interactions under changing environmental conditions. 2. Hybrid root exudate collection methods, where plants are grown in soil and transferred to hydroponics for exudate collection after root washing, might offer an ecologically relevant alternative to existing approaches. However, this method causes potential root damage as well as osmosis and subsequent leaking of cell contents. Here, we assessed different 'root recovery' periods after root washing and before hybrid root exudate collection, by comparing root exudate quantity and quality with both damaged root extracts and with leachates collected from the intact root-soil system. This was done across three common grassland species representing three functional groups. 3. We found that root exudate profiles of the shortest recovery period (0 days) were similar to damaged root extracts and were very high in C. With an increasing period of root recovery, profiles were more similar to leachates collected from the intact root-soil system, and C concentrations decreased. While both hybrid and leachate collection methods separated species by their root exudate profiles, the hybrid method was less variable in terms of the amount of C measured and provided a more diverse and abundant metabolome with better identification of metabolites. 4. Our results show that a recovery period after root washing of at least 3 days is critical to prevent root damage bias in hybrid collection methods, and that our hybrid method yields exudates that discriminate between species. Our data also suggest that exudates collected with this hybrid method are ecologically valid, which is vital for gaining a mechanistic understanding of their role in ecosystem functioning.

Validating Differential Volatilome Profiles in Parkinson's Disease

Parkinson's disease (PD) is a progressive neurodegenerative disorder that does not currently have a robust clinical diagnostic test. Nonmotor symptoms such as skin disorders have long since been associated with the disease, and more recently a characteristic odor emanating from the skin of people with Parkinson's has been identified. Here, dynamic head space (DHS) thermal desorption (TD) gas chromatography-mass spectrometry (GC-MS) is implemented to directly measure the volatile components of sebum on swabs sampled from people with Parkinson's-both drug naïve and those on PD medications (n = 100) and control subjects (n = 29). Supervised multivariate analyses of data showed 84.4% correct classification of PD cases using all detected volatile compounds. Variable importance in projection (VIP) scores were generated from these data, which revealed eight features with VIP > 1 and p < 0.05 which all presented a downregulation within the control cohorts. Purified standards based on previously annotated analytes of interest eicosane and octadecanal did not match to patient sample data, although multiple metabolite features are annotated with these compounds all with high spectral matches indicating the presence of a series of similar structured species. DHS-TD-GC-MS analysis of a range of lipid standards has revealed the presence of common hydrocarbon species rather than differentiated intact compounds which are hypothesized to be breakdown products of lipids. This replication study validates that a differential volatile profile between control and PD cohorts can be measured using an analytical method that measures volatile compounds directly from skin swabs.

Engineering Escherichia coli towards de novo production of gatekeeper (2S)-flavanones: naringenin, pinocembrin, eriodictyol and homoeriodictyol

Natural plant-based flavonoids have drawn significant attention as dietary supplements due to their potential health benefits, including anti-cancer, anti-oxidant and anti-asthmatic activities. Naringenin, pinocembrin, eriodictyol and homoeriodictyol are classified as (2S)-flavanones, an important sub-group of naturally occurring flavonoids, with wide-reaching applications in human health and nutrition. These four compounds occupy a central position as branch point intermediates towards a broad spectrum of naturally occurring flavonoids. Here, we report the development of Escherichia coli production chassis for each of these key gatekeeper flavonoids. Selection of key enzymes, genetic construct design and the optimization of process conditions resulted in the highest reported titers for naringenin (484 mg/l), improved production of pinocembrin (198 mg/l) and eriodictyol (55 mg/l from caffeic acid), and provided the first example of in vivo production of homoeriodictyol directly from glycerol (17 mg/l). This work provides a springboard for future production of diverse downstream natural and non-natural flavonoid targets.

Rapid prototyping of microbial production strains for the biomanufacture of potential materials monomers

Bio-based production of industrial chemicals using synthetic biology can provide alternative green routes from renewable resources, allowing for cleaner production processes. To efficiently produce chemicals on-demand through microbial strain engineering, biomanufacturing foundries have developed automated pipelines that are largely compound agnostic in their time to delivery. Here we benchmark the capabilities of a biomanufacturing pipeline to enable rapid prototyping of microbial cell factories for the production of chemically diverse industrially relevant material building blocks. Over 85 days the pipeline was able to produce 17 potential material monomers and key intermediates by combining 160 genetic parts into 115 unique biosynthetic pathways. To explore the scale-up potential of our prototype production strains, we optimized the enantioselective production of mandelic acid and hydroxymandelic acid, achieving gram-scale production in fed-batch fermenters. The high success rate in the rapid design and prototyping of microbially-produced material building blocks reveals the potential role of biofoundries in leading the transition to sustainable materials production.

Highly multiplexed, fast and accurate nanopore sequencing for verification of synthetic DNA constructs and sequence libraries

Synthetic biology utilizes the Design-Build-Test-Learn pipeline for the engineering of biological systems. Typically, this requires the construction of specifically designed, large and complex DNA assemblies. The availability of cheap DNA synthesis and automation enables high-throughput assembly approaches, which generates a heavy demand for DNA sequencing to verify correctly assembled constructs. Next-generation sequencing is ideally positioned to perform this task, however with expensive hardware costs and bespoke data analysis requirements few laboratories utilize this technology in-house. Here a workflow for highly multiplexed sequencing is presented, capable of fast and accurate sequence verification of DNA assemblies using nanopore technology. A novel sample barcoding system using polymerase chain reaction is introduced, and sequencing data are analyzed through a bespoke analysis algorithm. Crucially, this algorithm overcomes the problem of high-error rate nanopore data (which typically prevents identification of single nucleotide variants) through statistical analysis of strand bias, permitting accurate sequence analysis with single-base resolution. As an example, 576 constructs (6 × 96 well plates) were processed in a single workflow in 72 h (from Escherichia coli colonies to analyzed data). Given our procedure's low hardware costs and highly multiplexed capability, this provides cost-effective access to powerful DNA sequencing for any laboratory, with applications beyond synthetic biology including directed evolution, single nucleotide polymorphism analysis and gene synthesis.

Integrated Probabilistic Annotation: A Bayesian-Based Annotation Method for Metabolomic Profiles Integrating Biochemical Connections, Isotope Patterns, and Adduct Relationships

In a typical untargeted metabolomics experiment, the huge amount of complex data generated by mass spectrometry necessitates automated tools for the extraction of useful biological information. Each metabolite generates numerous mass spectrometry features. The association of these experimental features to the underlying metabolites still represents one of the major bottlenecks in metabolomics data processing. While certain identification (e.g., by comparison to authentic standards) is always desirable, it is usually achievable only for a limited number of compounds, and scientists often deal with a significant amount of putatively annotated metabolites. The confidence in a specific annotation is usually assessed by considering different sources of information (e.g., isotope patterns, adduct formation, chromatographic retention times, and fragmentation patterns). IPA (integrated probabilistic annotation) offers a rigorous and reproducible method to automatically annotate metabolite profiles and evaluate the resulting confidence of the putative annotations. It is able to provide a rigorous measure of our confidence in any putative annotation and is also able to update and refine our beliefs (i.e., background prior knowledge) by incorporating different sources of information in the annotation process, such as isotope patterns, adduct formation and biochemical relations. The IPA package is freely available on GitHub ( https://github.com/francescodc87/IPA ), together with the related extensive documentation.

Mobilising ion mobility mass spectrometry for metabolomics

Chromatography-based mass spectrometry approaches (xC-MS) are commonly used in untargeted metabolomics, providing retention time, m/z values and metabolite-specific fragments, all of which are used to identify and validate an unknown analyte. Ion mobility-mass spectrometry (IM-MS) is emerging as an enhancement to classic xC-MS strategies, by offering additional ion separation as well as collision cross section (CCS) determination. In order to apply such an approach to a metabolomics workflow, verified data from metabolite standards is necessary. In this work we present experimental DTCCSN2 values for a range of metabolites in positive and negative ionisation modes using drift tube-ion mobility-mass spectrometry (DT-IM-MS) with nitrogen as the buffer gas. The value of DTCCSN2 measurements for application in metabolite identification relies on a robust technique that acquires measurements of high reproducibility. We report that the CCS values found for 86% of metabolites measured in replicate have a relative standard deviation lower than 0.2%. Examples of metabolites with near identical mass are demonstrated to be separated by ion mobility with over 4% difference in DTCCSN2 values. We conclude that the integration of ion mobility into current LC-MS workflows can aid in small molecule identification for both targeted and untargeted metabolite screening.

Machine Learning of Designed Translational Control Allows Predictive Pathway Optimization in Escherichia coli

The field of synthetic biology aims to make the design of biological systems predictable, shrinking the huge design space to practical numbers for testing. When designing microbial cell factories, most optimization efforts have focused on enzyme and strain selection/engineering, pathway regulation, and process development. In silico tools for the predictive design of bacterial ribosome binding sites (RBSs) and RBS libraries now allow translational tuning of biochemical pathways; however, methods for predicting optimal RBS combinations in multigene pathways are desirable. Here we present the implementation of machine learning algorithms to model the RBS sequence-phenotype relationship from representative subsets of large combinatorial RBS libraries allowing the accurate prediction of optimal high-producers. Applied to a recombinant monoterpenoid production pathway in Escherichia coli, our approach was able to boost production titers by over 60% when screening under 3% of a library. To facilitate library screening, a multiwell plate fermentation procedure was developed, allowing increased screening throughput with sufficient resolution to discriminate between high and low producers. High producers from one library did not translate during scale-up, but the reduced screening requirements allowed rapid rescreening at the larger scale. This methodology is potentially compatible with any biochemical pathway and provides a powerful tool toward predictive design of bacterial production chassis.

High throughput screening of complex biological samples with mass spectrometry – from bulk measurements to single cell analysis

We review the state of the art in HTS using mass spectrometry with minimal sample preparation from complex biological matrices. We focus on industrial and biotechnological applications.

Structural and catalytic properties of the peroxygenase P450 enzyme CYP152K6 from Bacillus methanolicus

The CYP152 family of cytochrome P450 enzymes (P450s or CYPs) are bacterial peroxygenases that use hydrogen peroxide to drive hydroxylation and decarboxylation of fatty acid substrates. We have expressed and purified a novel CYP152 family member - CYP152K6 from the methylotroph Bacillus methanolicus MGA3. CYP152K6 was characterized using spectroscopic, analytical and structural methods. CYP152K6, like its peroxygenase counterpart P450SPα (CYP152B1) from Sphingomonas paucimobilis, does not undergo significant fatty acid-induced perturbation to the heme spectrum, with the exception of a minor Soret shift observed on binding dodecanoic acid. However, CYP152K6 purified from an E. coli expression system was crystallized and its structure was determined to 1.3 Å with tetradecanoic acid bound. No lipids were present in conditions used for crystallogenesis, and thus CYP152K6 must form a complex by incorporating the fatty acid from E. coli cells. Turnover studies with dodecanoic acid revealed several products, with 2-hydroxydodecanoic acid as the major product and much smaller quantities of 3-hydroxydodecanoic acid. Secondary turnover products were undec-1-en-1-ol, 2-hydroxydodec-2-enoic acid and 2,3-dihydroxydodecanoic acid. This is the first report of a 2,3-hydroxylated fatty acid product made by a peroxygenase P450, with the dihydroxylated product formed by CYP152K6-catalyzed 3-hydroxylation of 2-hydroxydodecanoic acid, but not by 2-hydroxylation of 3-hydroxydodecanoic acid.

Abstract 4109: Multi-modality imaging to interrogate lipidome changes during melanoma progression in zebrafish

Lipids play diverse roles in the body, including cell structure, cell signalling, and energy production; all of which are altered in cancer. Lipid metabolism is therefore a potential therapeutic target, and here has been investigated using a transgenic zebrafish model. This study combines transcriptome and lipidomic analyses for the first time, with in-vivo positron emission tomography (PET) and ex-vivo desorption electrospray ionisation-mass spectrometry (DESI-MS), to investigate lipid metabolism changes in melanoma. Most lipids are made of fatty acids, and the methods by which tumours acquire fatty acids can be altered compared to normal tissue. Here, the PET tracer [18F]-FTHA (a fatty acid analogue) has been used to demonstrate free fatty acid uptake in melanoma tumours in-vivo. Additionally, the excellent spatial resolution of mass spectrometry imaging has been utilised by imaging the FTHA ex-vivo by DESI-MS, allowing more precise spatial correlation with the histology, and revealing the heterogeneous nature of this fatty acid uptake. These imaging data complement the findings of the transcriptome analyses which show upregulation of genes associated with fatty acid uptake. Integrating transcriptome and lipidome data analyses revealed dysregulation of glycerophospholipid pathways, and was supported by DESI-MS data, which revealed heterogeneous changes in lipid metabolism.

Citation Format: Fiona Henderson, Hannah Johnston, Emrys Jones, Duncan Foster, Raghavendar T. Nagaraju, Michael Green, Michael Fairclough, Irene Barinaga-Rementeria Ramirez, Shuning He, B.Ewa Snaar-Jagalska, Katherine A. Hollywood, Warwick Dunn, Herman P. Spaink, Paul Lorigan, Emmanuelle Claude, Kaye Williams, Adam Hurlstone, Adam McMahon. Multi-modality imaging to interrogate lipidome changes during melanoma progression in zebrafish [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4109.

Engineering the "Missing Link" in Biosynthetic (-)-Menthol Production: Bacterial Isopulegone Isomerase

The realization of a synthetic biology approach to microbial (1R,2S,5R)-(−)-menthol (1) production relies on the identification of a gene encoding an isopulegone isomerase (IPGI), the only enzyme in the Mentha piperita biosynthetic pathway as yet unidentified. We demonstrate that Δ5-3-ketosteroid isomerase (KSI) from Pseudomonas putida can act as an IPGI, producing (R)-(+)-pulegone ((R)-2) from (+)-cis-isopulegone (3). Using a robotics-driven semirational design strategy, we identified a key KSI variant encoding four active site mutations, which confer a 4.3-fold increase in activity over the wild-type enzyme. This was assisted by the generation of crystal structures of four KSI variants, combined with molecular modeling of 3 binding to identify key active site residue targets. The KSI variant was demonstrated to function efficiently within cascade biocatalytic reactions with downstream Mentha enzymes pulegone reductase and (−)-menthone:(−)-menthol reductase to generate 1 from 3. This study introduces the use of a recombinant IPGI, engineered to function efficiently within a biosynthetic pathway for the production of 1 in microorganisms.

Adipose tissue and metabolic and inflammatory responses to stroke are altered in obese mice

Obesity is an independent risk factor for stroke, although several clinical studies have reported that obesity improves stroke outcome. Obesity is hypothesised to aid recovery by protecting against post-stroke catabolism. We therefore assessed whether obese mice had an altered metabolic and inflammatory response to stroke. Obese ob/ob mice underwent a 20-min middle cerebral artery occlusion and 24-h reperfusion. Lipid metabolism and expression of inflammatory cytokines were assessed in the plasma, liver and adipose tissue. The obese-specific metabolic response to stroke was assessed in plasma using non-targeted ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) metabolomics coupled with univariate and multivariate analysis. Obesity had no effect on the extent of weight loss 24 h after stroke but affected the metabolic and inflammatory responses to stroke, predominantly affecting lipid metabolism. Specifically, obese mice had increases in plasma free fatty acids and expression of adipose lipolytic enzymes. Metabolomics identified several classes of metabolites affected by stroke in obese mice, including fatty acids and membrane lipids (glycerophospholipids, lysophospholipids and sphingolipids). Obesity also featured increases in inflammatory cytokines in the plasma and adipose tissue. Overall, these results demonstrate that obesity affected the acute metabolic and inflammatory response to stroke and suggest a potential role for adipose tissue in this effect. These findings could have implications for longer-term recovery and also further highlight the importance of considering comorbidities in preclinical stroke research, especially when identifying biomarkers for stroke. However, further work is required to assess whether these changes translate into long-term effects on recovery.

Summary: Obesity, a co-morbidity for stroke, affected the acute metabolic and inflammatory response to stroke, highlighting the importance of considering comorbidities in preclinical stroke research, especially when identifying biomarkers.

Real-Time Monitoring of Enzyme-Catalysed Reactions using Deep UV Resonance Raman Spectroscopy

For enzyme-catalysed biotransformations, continuous in situ detection methods minimise the need for sample manipulation, ultimately leading to more accurate real-time kinetic determinations of substrate(s) and product(s). We have established for the first time an on-line, real-time quantitative approach to monitor simultaneously multiple biotransformations based on UV resonance Raman (UVRR) spectroscopy. To exemplify the generality and versatility of this approach, multiple substrates and enzyme systems were used involving nitrile hydratase (NHase) and xanthine oxidase (XO), both of which are of industrial and biological significance, and incorporate multistep enzymatic conversions. Multivariate data analysis of the UVRR spectra, involving multivariate curve resolution-alternating least squares (MCR-ALS), was employed to effect absolute quantification of substrate(s) and product(s); repeated benchmarking of UVRR combined with MCR-ALS by HPLC confirmed excellent reproducibility.

Metabolomics for the masses: The future of metabolomics in a personalized world

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

Elevation of brain glucose and polyol-pathway intermediates with accompanying brain-copper deficiency in patients with Alzheimer's disease: metabolic basis for dementia

Impairment of brain-glucose uptake and brain-copper regulation occurs in Alzheimer's disease (AD). Here we sought to further elucidate the processes that cause neurodegeneration in AD by measuring levels of metabolites and metals in brain regions that undergo different degrees of damage. We employed mass spectrometry (MS) to measure metabolites and metals in seven post-mortem brain regions of nine AD patients and nine controls, and plasma-glucose and plasma-copper levels in an ante-mortem case-control study. Glucose, sorbitol and fructose were markedly elevated in all AD brain regions, whereas copper was correspondingly deficient throughout (all P < 0.0001). In the ante-mortem case-control study, by contrast, plasma-glucose and plasma-copper levels did not differ between patients and controls. There were pervasive defects in regulation of glucose and copper in AD brain but no evidence for corresponding systemic abnormalities in plasma. Elevation of brain glucose and deficient brain copper potentially contribute to the pathogenesis of neurodegeneration in AD.

Graded perturbations of metabolism in multiple regions of human brain in Alzheimer's disease: Snapshot of a pervasive metabolic disorder

Alzheimer's disease (AD) is an age-related neurodegenerative disorder that displays pathological characteristics including senile plaques and neurofibrillary tangles. Metabolic defects are also present in AD-brain: for example, signs of deficient cerebral glucose uptake may occur decades before onset of cognitive dysfunction and tissue damage. There have been few systematic studies of the metabolite content of AD human brain, possibly due to scarcity of high-quality brain tissue and/or lack of reliable experimental methodologies. Here we sought to: 1) elucidate the molecular basis of metabolic defects in human AD-brain; and 2) identify endogenous metabolites that might guide new approaches for therapeutic intervention, diagnosis or monitoring of AD. Brains were obtained from nine cases with confirmed clinical/neuropathological AD and nine controls matched for age, sex and post-mortem delay. Metabolite levels were measured in post-mortem tissue from seven regions: three that undergo severe neuronal damage (hippocampus, entorhinal cortex and middle-temporal gyrus); three less severely affected (cingulate gyrus, sensory cortex and motor cortex); and one (cerebellum) that is relatively spared. We report a total of 55 metabolites that were altered in at least one AD-brain region, with different regions showing alterations in between 16 and 33 metabolites. Overall, we detected prominent global alterations in metabolites from several pathways involved in glucose clearance/utilization, the urea cycle, and amino-acid metabolism. The finding that potentially toxigenic molecular perturbations are widespread throughout all brain regions including the cerebellum is consistent with a global brain disease process rather than a localized effect of AD on regional brain metabolism.

Characterisation of the metabolome of ocular tissues and post-mortem changes in the rat retina

Time-dependent post-mortem biochemical changes have been demonstrated in donor cornea and vitreous, but there have been no published studies to date that objectively measure post-mortem changes in the retinal metabolome over time. The aim of the study was firstly, to investigate post-mortem, time-dependent changes in the rat retinal metabolome and secondly, to compare the metabolite composition of healthy rat ocular tissues. To study post-mortem changes in the rat retinal metabolome, globes were enucleated and stored at 4 °C and sampled at 0, 2, 4, 8, 24 and 48 h post-mortem. To study the metabolite composition of rat ocular tissues, eyes were dissected immediately after culling to isolate the cornea, lens, vitreous and retina, prior to storing at -80 °C. Tissue extracts were subjected to Gas Chromatograph Mass Spectrometry (GC-MS) and Ultra High Performance Liquid Chromatography Mass Spectrometry (UHPLC-MS). Generally, the metabolic composition of the retina was stable for 8 h post-mortem when eyes were stored at 4 °C, but showed increasing changes thereafter. However, some more rapid changes were observed such as increases in TCA cycle metabolites after 2 h post-mortem, whereas some metabolites such as fatty acids only showed decreases in concentration from 24 h. A total of 42 metabolites were identified across the ocular tissues by GC-MS (MSI level 1) and 2782 metabolites were annotated by UHPLC-MS (MSI level 2) according to MSI reporting standards. Many of the metabolites detected were common to all of the tissues but some metabolites showed partitioning between different ocular structures with 655, 297, 93 and 13 metabolites being uniquely detected in the retina, lens, cornea and vitreous respectively. Only a small percentage (1.6%) of metabolites found in the vitreous were only detected in the retina and not other tissues. In conclusion, mass spectrometry-based techniques have been used for the first time to compare the metabolic composition of different ocular tissues. The metabolite composition of the retina stored at 4 °C post-mortem is mostly stable for at least 8 h.

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.

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.

Introduction to metabolomics and its applications in ophthalmology

Metabolomics is the study of endogenous and exogenous metabolites in biological systems, which aims to provide comparative semi-quantitative information about all metabolites in the system. Metabolomics is an emerging and potentially powerful tool in ophthalmology research. It is therefore important for health professionals and researchers involved in the speciality to understand the basic principles of metabolomics experiments. This article provides an overview of the experimental workflow and examples of its use in ophthalmology research from the study of disease metabolism and pathogenesis to identification of biomarkers.

Metabolic Dysfunction Is Restricted to the Sciatic Nerve in Experimental Diabetic Neuropathy

High glucose levels in the peripheral nervous system (PNS) have been implicated in the pathogenesis of diabetic neuropathy (DN). However, our understanding of the molecular mechanisms that cause the marked distal pathology is incomplete. We performed a comprehensive, system-wide analysis of the PNS of a rodent model of DN. We integrated proteomics and metabolomics from the sciatic nerve (SN), the lumbar 4/5 dorsal root ganglia (DRG), and the trigeminal ganglia (TG) of streptozotocin-diabetic and healthy control rats. Even though all tissues showed a dramatic increase in glucose and polyol pathway intermediates in diabetes, a striking upregulation of mitochondrial oxidative phosphorylation and perturbation of lipid metabolism was found in the distal SN that was not present in the corresponding cell bodies of the DRG or the cranial TG. This finding suggests that the most severe molecular consequences of diabetes in the nervous system present in the SN, the region most affected by neuropathy. Such spatial metabolic dysfunction suggests a failure of energy homeostasis and/or oxidative stress, specifically in the distal axon/Schwann cell-rich SN. These data provide a detailed molecular description of the distinct compartmental effects of diabetes on the PNS that could underlie the distal-proximal distribution of pathology.

Making colourful sense of Raman images of single cells

We demonstrate how changes in the application of colour shading can dramatically alter Raman images of single human keratinocytes cells.