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.

Volatile Aroma Compound Production Is Affected by Growth Rate in S. cerevisiae.

The initial growth rate of a yeast strain is a key parameter in the production of fermented beverages. Fast growth is linked with higher fermentative capacity and results in less slow and stuck fermentations unable to reach the expected final gravity. As concentrations of metabolites are in a constant state of flux, quantitative data on how growth rate affects the production of aromatic compounds becomes an important factor for brewers. Chemostats allow to set and keep a specific dilution rate throughout the fermentation and are ideal system to study the effect of growth on aroma production. In this study, we ran chemostats alongside batch and fed-batch cultures, compared volatile profiles detected at different growth rates, and identified those affected by the different feeding profiles. Specifically, we quantified six abundant aroma compounds produced in anaerobic glucose-limited continuous cultivations of S. cerevisiae at different dilution rates. We found that volatile production was affected by the growth rate in four out of six compounds assayed, with higher alcohols and esters following opposite trends. Batch and fed-batch fermentations were devised to study the extent by which the final concentration of volatile compounds is influenced by glucose availability. Compared with the batch system, fed-batch fermentations, where the yeast growth was artificially limited by a slow constant release of nutrients in the media, resulted in a significant increase in concentration of higher alcohols, mirroring the results obtained in continuous fermentations. This study paves the way to further process development optimization for the production of fermented beverages. IMPORTANCE The production of fermentation beverages will need to quickly adapt to changes in both the climate and customer demands, requiring the development of new strains and processes. Breakthroughs in the field are hindered by the limited knowledge on the interplay between physiology and aroma compound production in yeast. No quantitative data on how growth rate affects aroma profile is available in the literature to guide optimization of the complex flavors in fermented beverages. In this study, we exploited the chemostat system, alongside with batch and fed-batch cultures, to compare volatile profiles at different growth rates. We identified the aromatic compounds affected by the different feeding profiles and nutrient limitations. Moreover, we uncovered the correlation between yeast growth, esters, and higher alcohols production. This study showcases the potential of the application of feeding profiles for the manipulation of aroma in the craft beverage industry.

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.

Prototyping of microbial chassis for the biomanufacturing of high-value chemical targets.

Metabolic engineering technologies have been employed with increasing success over the last three decades for the engineering and optimization of industrial host strains to competitively produce high-value chemical targets. To this end, continued reductions in the time taken from concept, to development, to scale-up are essential. Design-Build-Test-Learn pipelines that are able to rapidly deliver diverse chemical targets through iterative optimization of microbial production strains have been established. Biofoundries are employing in silico tools for the design of genetic parts, alongside combinatorial design of experiments approaches to optimize selection from within the potential design space of biological circuits based on multi-criteria objectives. These genetic constructs can then be built and tested through automated laboratory workflows, with performance data analysed in the learn phase to inform further design. Successful examples of rapid prototyping processes for microbially produced compounds reveal the potential role of biofoundries in leading the sustainable production of next-generation bio-based chemicals.

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.

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.

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.

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

High throughput screening (HTS) of molecular analytes is in high demand from and implemented in many areas of chemistry, medicine and industrial biotechnology including the discovery of biomarkers and the development of new chemical entities. Despite its prevalence, technical challenges remain in many of the new application areas of HTS which require rapid results from complex mixtures, for example in: screening biotransformations; targeted metabolomics; and in locating drugs and/or metabolites in biological matrices. Common to all of these are lengthy and costly sample preparation stages, involving recovery from cell cultures, extractions followed by low throughput LC-MS/MS methods or specific fluorescence measurements. In the latter the target molecules need to be inherently fluorescent or to include a fluorescent label or tag which can adversely influence a cellular system. Direct infusion mass spectrometry coupled with robotic sample infusion is a viable contender for information rich HTS with sub-second analysis times, and recent developments in ambient ionisation have heralded a new era where screening can be performed on crude cell lysates or even from live cells. Besides commercially available technologies such as RapidFire, Acoustic Mist Ionisation, and the TriVersa ChipMate there are promising new developments from academic groups. Novel applications using desorption electrospray ionisation, microfluidics, rapid LC-separation and 'one cell' direct infusion methods offer much potential for increasing throughput from 'messy' complex samples and for significantly reducing the amount of material that needs to be analysed. Here we review recent advances in HTS coupled with MS with an emphasis on methods that reduce or remove all sample preparation and will facilitate single cell screening approaches.

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.

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.

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

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

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.

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

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

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.

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.

Making colourful sense of Raman images of single cells.

In order to understand biological systems it is important to gain pertinent information on the spatial localisation of chemicals within cells. With the relatively recent advent of high-resolution chemical imaging this is being realised and one rapidly developing area of research is the Raman mapping of single cells, an approach whose success has vast potential for numerous areas of biomedical research. However, there is a danger of undermining the potential routine use of Raman mapping due to a lack of consistency and transparency in the way false-shaded Raman images are constructed. In this study we demonstrate, through the use of simulated data and real Raman maps of single human keratinocyte (HaCaT) cells, how changes in the application of colour shading can dramatically alter the final Raman images. In order to avoid ambiguity and potential subjectivity in image interpretation we suggest that data distribution plots are used to aid shading approaches and that extreme care is taken to use the most appropriate false-shading for the biomedical question under investigation.

Bioproduction of methylated phenylpropenes and isoeugenol in Escherichia coli.

Phenylpropenes are a class of natural products that are synthesised by a vast range of plant species and hold considerable promise in the flavour and fragrance industries. Many in vitro studies have been carried out to elucidate and characterise the enzymes responsible for the production of these volatile compounds. However, there is a scarcity of studies demonstrating the in vivo production of phenylpropenes in microbial cell factories. In this study, we engineered Escherichia coli to produce methylchavicol, methyleugenol and isoeugenol from their respective phenylacrylic acid precursors. We achieved this by extending and modifying a previously optimised heterologous pathway for the biosynthesis of chavicol and eugenol. We explored the potential of six S-adenosyl l-methionine (SAM)-dependent O-methyltransferases to produce methylchavicol and methyleugenol from chavicol and eugenol, respectively. Additionally, we examined two isoeugenol synthases for the production of isoeugenol from coniferyl acetate. The best-performing strains in this study were able to achieve titres of 13 mg L-1 methylchavicol, 59 mg L-1 methyleugenol and 361 mg L-1 isoeugenol after feeding with their appropriate phenylacrylic acid substrates. We were able to further increase the methyleugenol titre to 117 mg L-1 by supplementation with methionine to facilitate SAM recycling. Moreover, we report the biosynthesis of methylchavicol and methyleugenol from l-tyrosine through pathways involving six and eight enzymatic steps, respectively.

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.

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.