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Advances in genome engineering and associated technologies have reinvigorated natural products research. Here we highlight the latest developments in the field across the discover-design-build-test-learn cycle of bioengineering, from recent progress in computational tools for AI-supported genome mining, enzyme and pathway engineering, and compound identification to novel host systems and new techniques for improving production levels, and place these trends in the context of responsible research and innovation, emphasizing the importance of anticipatory analysis at the early stages of process development.
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Eicosanoids are a family of bioactive lipids, including derivatives of the ubiquitous fatty acid arachidonic acid (AA). The intimate involvement of eicosanoids in inflammation motivates the development of predictive in silico models for a systems-level exploration of disease mechanisms, drug development and replacement of animal models. Using an ensemble modelling strategy, we developed a computational model of the AA cascade. This approach allows the visualisation of plausible and thermodynamically feasible predictions, overcoming the limitations of fixed-parameter modelling. A quality scoring method was developed to quantify the accuracy of ensemble predictions relative to experimental data, measuring the overall uncertainty of the process. Monte Carlo ensemble modelling was used to quantify the prediction confidence levels. Model applicability was demonstrated using mass spectrometry mediator lipidomics to measure eicosanoids produced by HaCaT epidermal keratinocytes and 46BR.1N dermal fibroblasts, treated with stimuli (calcium ionophore A23187), (ultraviolet radiation, adenosine triphosphate) and a cyclooxygenase inhibitor (indomethacin). Experimentation and predictions were in good qualitative agreement, demonstrating the ability of the model to be adapted to cell types exhibiting differences in AA release and enzyme concentration profiles. The quantitative agreement between experimental and predicted outputs could be improved by expanding network topology to include additional reactions. Overall, our approach generated an adaptable, tuneable ensemble model of the AA cascade that can be tailored to represent different cell types and demonstrated that the integration of in silico and in vitro methods can facilitate a greater understanding of complex biological networks such as the AA cascade.
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Ácido Araquidônico , Simulação por Computador , Queratinócitos , Ácido Araquidônico/metabolismo , Humanos , Queratinócitos/metabolismo , Lipidômica/métodos , Método de Monte Carlo , Eicosanoides/metabolismo , Modelos Biológicos , Fibroblastos/metabolismo , Linhagem Celular , Calcimicina/farmacologiaRESUMO
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.
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Selenzyme is a retrobiosynthesis tool that suggests candidate enzymes for user query reactions. Enzyme suggestions are based on identical reactions, as well as similar reactions, since enzymes are often capable of promiscuous substrate binding. Selenzyme is a user-friendly, widely used web-tool for ranking enzymes based on reaction similarity and additional features, including the phylogenetic distance between the source species of the enzyme and the intended host. While Selenzyme has proved invaluable in assisting with enzyme selection for known reactions, as well as many novel or orphan reactions, weaknesses have been exposed in its ability to rank functionally related enzymes. Within this update, we introduce a new reaction similarity scoring algorithm, which is used in conjunction with the previous similarity calculation, to improve the accuracy of enzyme suggestions based on non-identical similar reactions, across a range of EC reaction classes. This allows enzymes to be suggested for reactions not found within the database, even if the reaction is unbalanced. A database update was also carried out, to ensure that reaction and enzyme knowledge remains current. This update can be accessed at http://selenzymeRF.synbiochem.co.uk/.
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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.
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OBJECTIVE: Hesperetin is an important O-methylated flavonoid produced by citrus fruits and of potential pharmaceutical relevance. The microbial biosynthesis of hesperetin could be a viable alternative to plant extraction, as plant extracts often yield complex mixtures of different flavonoids making it challenging to isolate pure compounds. In this study, hesperetin was produced from caffeic acid in the microbial host Escherichia coli. We combined a previously optimised pathway for the biosynthesis of the intermediate flavanone eriodictyol with a combinatorial library of plasmids expressing three candidate flavonoid O-methyltransferases. Moreover, we endeavoured to improve the position specificity of CCoAOMT7, a flavonoid O-methyltransferase from Arabidopsis thaliana that has been demonstrated to O-methylate eriodictyol in both the para- and meta-position, thus leading to a mixture of hesperetin and homoeriodictyol. RESULTS: The best performing flavonoid O-methyltransferase in our screen was found to be CCoAOMT7, which could produce up to 14.6 mg/L hesperetin and 3.8 mg/L homoeriodictyol from 3 mM caffeic acid in E. coli 5-alpha. Using a platform for enzyme engineering that scans the mutational space of selected key positions, predicting their structures using homology modelling and inferring their potential catalytic improvement using docking simulations, we were able to identify a CCoAOMT7 mutant with a two-fold higher position specificity for hesperetin. The mutant's catalytic activity, however, was considerably diminished. Our findings suggest that hesperetin can be created from central carbon metabolism in E. coli following the introduction of a caffeic acid biosynthesis pathway.
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Escherichia coli , Flavanonas , Flavanonas/metabolismo , Flavonoides/metabolismo , Metiltransferases/genéticaRESUMO
BACKGROUND: (Hydroxy)cinnamyl alcohols and allylphenols, including coniferyl alcohol and eugenol, are naturally occurring aromatic compounds widely utilised in pharmaceuticals, flavours, and fragrances. Traditionally, the heterologous biosynthesis of (hydroxy)cinnamyl alcohols from (hydroxy)cinnamic acids involved CoA-dependent activation of the substrate. However, a recently explored alternative pathway involving carboxylic acid reductase (CAR) has proven efficient in generating the (hydroxy)cinnamyl aldehyde intermediate without the need for CoA activation. In this study, we investigated the application of the CAR pathway for whole-cell bioconversion of a range of (hydroxy)cinnamic acids into their corresponding (hydroxy)cinnamyl alcohols. Furthermore, we sought to extend the pathway to enable the production of a variety of allylphenols and allylbenzene. RESULTS: By screening the activity of several heterologously expressed enzymes in crude cell lysates, we identified the combination of Segniliparus rugosus CAR (SrCAR) and Medicago sativa cinnamyl alcohol dehydrogenase (MsCAD2) as the most efficient enzymatic cascade for the two-step reduction of ferulic acid to coniferyl alcohol. To optimise the whole-cell bioconversion in Escherichia coli, we implemented a combinatorial approach to balance the gene expression levels of SrCAR and MsCAD2. This optimisation resulted in a coniferyl alcohol yield of almost 100%. Furthermore, we extended the pathway by incorporating coniferyl alcohol acyltransferase and eugenol synthase, which allowed for the production of eugenol with a titre of up to 1.61 mM (264 mg/L) from 3 mM ferulic acid. This improvement in titre surpasses previous achievements in the field employing a CoA-dependent coniferyl alcohol biosynthesis pathway. Our study not only demonstrated the successful utilisation of the CAR pathway for the biosynthesis of diverse (hydroxy)cinnamyl alcohols, such as p-coumaryl alcohol, caffeyl alcohol, cinnamyl alcohol, and sinapyl alcohol, from their corresponding (hydroxy)cinnamic acid precursors but also extended the pathway to produce allylphenols, including chavicol, hydroxychavicol, and methoxyeugenol. Notably, the microbial production of methoxyeugenol from sinapic acid represents a novel achievement. CONCLUSION: The combination of SrCAR and MsCAD2 enzymes offers an efficient enzymatic cascade for the production of a wide array of (hydroxy)cinnamyl alcohols and, ultimately, allylphenols from their respective (hydroxy)cinnamic acids. This expands the range of value-added molecules that can be generated using microbial cell factories and creates new possibilities for applications in industries such as pharmaceuticals, flavours, and fragrances. These findings underscore the versatility of the CAR pathway, emphasising its potential in various biotechnological applications.
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Eugenol , Eugenol/metabolismo , Preparações FarmacêuticasRESUMO
SUMMARY: The Integrated Probabilistic Annotation (IPA) is an automated annotation method for LC-MS-based untargeted metabolomics experiments that provides statistically rigorous estimates of the probabilities associated with each annotation. Here, we introduce ipaPy2, a substantially improved and completely refactored Python implementation of the IPA method. The revised method is now able to integrate tandem MS fragmentation data, which increases the accuracy of the identifications. Moreover, ipaPy2 provides a much more user-friendly interface, and isotope peaks are no longer treated as individual features but integrated into isotope fingerprints, greatly speeding up the calculations. The method has also been fully integrated with the mzMatch pipeline, so that the results of the annotation can be explored through the newly developed PeakMLViewerPy tool available at https://github.com/UoMMIB/PeakMLViewerPy. AVAILABILITY AND IMPLEMENTATION: The source code, extensive documentation, and tutorials are freely available on GitHub at https://github.com/francescodc87/ipaPy2.
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Metabolômica , Espectrometria de Massas em Tandem , Cromatografia Líquida/métodos , Teorema de Bayes , Metabolômica/métodos , SoftwareRESUMO
Transcription factors responsive to small molecules are essential elements in synthetic biology designs. They are often used as genetically encoded biosensors with applications ranging from the detection of environmental contaminants and biomarkers to microbial strain engineering. Despite our efforts to expand the space of compounds that can be detected using biosensors, the identification and characterization of transcription factors and their corresponding inducer molecules remain labor- and time-intensive tasks. Here, we introduce TFBMiner, a new data mining and analysis pipeline that enables the automated and rapid identification of putative metabolite-responsive transcription factor-based biosensors (TFBs). This user-friendly command line tool harnesses a heuristic rule-based model of gene organization to identify both gene clusters involved in the catabolism of user-defined molecules and their associated transcriptional regulators. Ultimately, biosensors are scored based on how well they fit the model, providing wet-lab scientists with a ranked list of candidates that can be experimentally tested. We validated the pipeline using a set of molecules for which TFBs have been reported previously, including sensors responding to sugars, amino acids, and aromatic compounds, among others. We further demonstrated the utility of TFBMiner by identifying a biosensor for S-mandelic acid, an aromatic compound for which a responsive transcription factor had not been found previously. Using a combinatorial library of mandelate-producing microbial strains, the newly identified biosensor was able to distinguish between low- and high-producing strain candidates. This work will aid in the unraveling of metabolite-responsive microbial gene regulatory networks and expand the synthetic biology toolbox to allow for the construction of more sophisticated self-regulating biosynthetic pathways.
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Técnicas Biossensoriais , Fatores de Transcrição , Fatores de Transcrição/genética , Fatores de Transcrição/metabolismo , Regulação da Expressão Gênica , Redes Reguladoras de Genes/genética , Biblioteca GênicaRESUMO
Breast cancer is one of the most common cancers threatening women worldwide. A limited number of available treatment options, frequent recurrence, and drug resistance exacerbate the prognosis of breast cancer patients. Thus, there is an urgent need for methods to investigate novel treatment options, while taking into account the vast molecular heterogeneity of breast cancer. Recent advances in molecular profiling technologies, including genomics, epigenomics, transcriptomics, proteomics and metabolomics data, enable approaching breast cancer biology at multiple levels of omics interaction networks. Systems biology approaches, including computational inference of 'big data' and mechanistic modelling of specific pathways, are emerging to identify potential novel combinations of breast cancer subtype signatures and more diverse targeted therapies.
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Streptomyces is one of the most relevant genera in biotechnology, and its rich secondary metabolism is responsible for the biosynthesis of a plethora of bioactive compounds, including several clinically relevant drugs. The use of Streptomyces species for the manufacture of natural products has been established for more than half a century; however, the tremendous advances observed in recent years in genetic engineering and molecular biology have revolutionised the optimisation of Streptomyces as cell factories and drastically expanded the biotechnological potential of these bacteria. Here, we illustrate the most exciting advances reported in the past few years, with a particular focus on the approaches significantly improving the biotechnological capacity of Streptomyces to produce clinical drugs and other valuable secondary metabolites.
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Streptomyces , Biotecnologia , Engenharia Genética , Metabolismo Secundário/genética , Streptomyces/genética , Streptomyces/metabolismoRESUMO
Covering: Focus on 2015 to 2020Plant and soil microbiomes consist of diverse communities of organisms from across kingdoms and can profoundly affect plant growth and health. Natural product-based intercellular signals govern important interactions between microbiome members that ultimately regulate their beneficial or harmful impacts on the plant. Exploiting these evolved signalling circuits to engineer microbiomes towards beneficial interactions with crops is an attractive goal. There are few reports thus far of engineering the intercellular signalling of microbiomes, but this article argues that it represents a tremendous opportunity for advancing the field of microbiome engineering. This could be achieved through the selection of synergistic consortia in combination with genetic engineering of signal pathways to realise an optimised microbiome.
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Microbiota , Solo , Bactérias/genética , Produtos Agrícolas , Raízes de Plantas , Microbiologia do SoloRESUMO
Planobispora rosea is the natural producer of the potent thiopeptide antibiotic GE2270A. Here, we present the results of a metabolomics and transcriptomics analysis of P. rosea during production of GE2270A. The data generated provides useful insights into the biology of this genetically intractable bacterium. We characterize the details of the shutdown of protein biosynthesis and the respiratory chain associated with the end of the exponential growth phase. We also provide the first description of the phosphate regulon in P. rosea. Based on the transcriptomics data, we show that both phosphate and iron are limiting P. rosea growth in our experimental conditions. Additionally, we identified and validated a new biosynthetic gene cluster associated with the production of the siderophores benarthin and dibenarthin in P. rosea. Together, the metabolomics and transcriptomics data are used to inform and refine the very first genome-scale metabolic model for P. rosea, which will be a valuable framework for the interpretation of future studies of the biology of this interesting but poorly characterized species. IMPORTANCE Planobispora rosea is a genetically intractable bacterium used for the production of GE2270A on an industrial scale. GE2270A is a potent thiopeptide antibiotic currently used as a precursor for the synthesis of two compounds under clinical studies for the treatment of Clostridium difficile infection and acne. Here, we present the very first systematic multi-omics investigation of this important bacterium, which provides a much-needed detailed picture of the dynamics of metabolism of P. rosea while producing GE2270A.
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The ability to engineer biological systems, whether to introduce novel functionality or improved performance, is a cornerstone of biotechnology and synthetic biology. Typically, this requires the generation of genetic diversity to explore variations in phenotype, a process that can be performed at many levels, from single molecule targets (i.e., in directed evolution of enzymes) to whole organisms (e.g., in chassis engineering). Recent advances in DNA synthesis technology and automation have enhanced our ability to create variant libraries with greater control and throughput. This review highlights the latest developments in approaches to create such a hierarchy of diversity from the enzyme level to entire pathways in vitro, with a focus on the creation of combinatorial libraries that are required to navigate a target's vast design space successfully to uncover significant improvements in function.
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Evolução Molecular Direcionada , Biologia Sintética , Biotecnologia , Variação Genética/genética , FenótipoRESUMO
Their biochemical versatility and biotechnological importance make actinomycete bacteria attractive targets for ambitious genetic engineering using the toolkit of synthetic biology. But their complex biology also poses unique challenges. This mini review discusses some of the recent advances in synthetic biology approaches from an actinomycete perspective and presents examples of their application to the rational improvement of industrially relevant strains.
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Actinobacteria/genética , Biologia Sintética/métodos , Actinobacteria/metabolismo , Microbiologia Industrial/métodos , Microbiologia Industrial/tendências , Engenharia Metabólica , Biologia Sintética/tendênciasRESUMO
The previously reported Streptomyces coelicolor M1146 is commonly used as a host strain for engineering of secondary metabolite production. In this study, absolute quantification of intracellular and extracellular metabolites of M1146 was performed in mid-log phase and stationary phase to observe major metabolites and the changes that occurred during growth. Decreased levels of central carbon metabolites (glycolysis, TCA cycle, and pentose phosphate pathway) and increased levels of amino acids were observed in stationary phase compared to mid-log phase. Furthermore, comparative metabolome analyses of M1146 upon expression of the actinorhodin biosynthetic gene cluster (M1146+ACT), a point mutation on the rpoB gene encoding RNA polymerase beta-subunit (M1152), and both expression of actinorhodin biosynthetic gene cluster and a rpoB point mutation (M1152+ACT) were performed. M1146+ACT showed higher levels of important cofactors, such as ATP, NADPH, and FMN while M1152 led to higher levels of intracellular S-adenosyl-methionine, acyl-CoAs, and extracellular nucleosides compared to M1146. M1152+ACT exhibited the highest levels of actinorhodin with elevated bases, nucleosides, and nucleotides, such as intracellular PRPP (phosphoribosyl phosphate), ATP, along with extracellular inosine, uridine, and guanine compared to the other three strains, which were considered to be combined effects of actinorhodin gene cluster expression and a rpoB point mutation. Metabolites analysis by means of absolute quantification demonstrated changes in precursors of secondary metabolites before and after phosphate depletion in M1146. Comparative metabolome analysis provided further insights into the effects of actinorhodin gene cluster expression along with a rpoB point mutation on the metabolome of S. coelicolor.
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RNA Polimerases Dirigidas por DNA/genética , Metaboloma , Família Multigênica/genética , Mutação Puntual , Streptomyces coelicolor/genética , Streptomyces coelicolor/metabolismo , Antraquinonas/metabolismoRESUMO
Spider silk is renowned for its impressive mechanical properties. It is one of the strongest known biomaterials, possessing mechanical properties that outmatch both steel and Kevlar. However, the farming of spiders for their silk is unfeasible. Consequently, production of recombinant spider silk proteins (spidroins) in more amenable hosts is an exciting field of research. For large-scale production to be viable, a heterologous silk production system that is both highly efficient and cost effective is essential. Genes encoding recombinant spidroin have been expressed in bacterial, yeast, insect, and mammalian cells, in addition to many other platforms. This review discusses the recent advances in exploiting an increasingly diverse range of host platforms in the heterologous production of recombinant spidroins.
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Fibroínas , Proteínas Recombinantes , Seda , Animais , Bactérias/genética , Biotecnologia/tendências , Fibroínas/genética , Insetos/genética , Mamíferos/genética , Proteínas Recombinantes/genética , Seda/genética , Leveduras/genéticaRESUMO
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.
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Cyclic adenosine monophosphate (cAMP) has been known to play an important role in regulating morphological development and antibiotic production in Streptomyces coelicolor. However, the functional connection between cAMP levels and antibiotic production and the mechanism by which cAMP regulates antibiotic production remain unclear. In this study, metabolomics- and transcriptomics-based multi-omics analysis was applied to S. coelicolor strains that either produce the secondary metabolite actinorhodin (Act) or lack most secondary metabolite biosynthesis pathways including Act. Comparative multi-omics analysis of the two strains revealed that intracellular and extracellular cAMP abundance was strongly correlated with actinorhodin production. Notably, supplementation of cAMP improved cell growth and antibiotic production. Further multi-omics analysis of cAMP-supplemented S. coelicolor cultures showed an increase of guanine and the expression level of purine metabolism genes. Based on this phenomenon, supplementation with 7-methylguanine, a competitive inhibitor of reactions utilizing guanine, with or without additional cAMP supplementation, was performed. This experiment revealed that the reactions inhibited by 7-methylguanine are mediating the positive effect on growth and antibiotic production, which may occur downstream of cAMP supplementation.