Identification, characterisation and application of inducible gene expression systems in Cupriavidus necator H16 and other bacteria

The production of key building block chemicals from renewable resources or waste forms a rapidly growing segment of the bioeconomy. The conversion of waste gases, such as carbon dioxide or carbon monoxide, into value-added compounds using metabolically engineered microorganisms has significant potential to maintain economic independence while reducing greenhouse gas emissions. Modification of cellular metabolism for the biosynthesis of a target molecule often requires an adjustment of gene expression, either of an endogenous or a heterologous metabolic pathway. Transcription factors are DNA-binding proteins that control gene expression at the transcriptional level in response to physical parameters, ions, or small effector molecules. They have become indispensable tools for the advancement of synthetic biology and metabolic engineering. In this work, significant progress was made in the discovery and characterisation of transcription factor-based inducible gene expression systems for metabolic engineering of the chemolithoautotroph Cupriavidus necator H16 and other bacteria. Firstly, a quantitative evaluation of a range of well characterised heterolougous inducible systems in C. necator was undertaken. Four of them, the positively regulated L-arabinose- and L-rhamnose-inducible systems and the negatively regulated acrylate- and cumate-inducible systems, were subsequently employed for the biosynthesis of the industrially relevant building block chemical isoprene. In addition to being used for controlling expression of structural genes, transcription factor-based inducible systems have gained increasing interest for their application as genetically encoded biosensors. Their ability to transduce the intracellular concentration of a target molecule into an output signal detectable in a high throughput format has the potential to revolutionise the field of microbial cell factory development. Currently, the number of compounds of biological interest by far exceeds the number of available biosensors. Here, this limitation was addressed by developing a universal genome-wide approach to identify novel transcription factor-based inducible gene expression systems. Once developed, the methodical pipeline was evaluated in the metabolically versatile C. necator. In total, 15 novel or little characterised inducible systems were identified and their broad host-range applicability was exemplified in three industrially relevant prokaryotes. Novel interactions between existing sensors and compounds of biological relevance were discovered by employing the largest reported library of transcription factor-based inducible systems in an automated high throughput screen. The same strategy, which was pursued in order to mine native inducible systems from the genome of C. necator, was used to source inducible systems responding to the industrially relevant platform chemicals 3-hydroxypropionic acid (3-HP) and itaconic acid. The HpdR/PhpdH-3-HP-inducible system from Pseudomonas putida KT2440 and the ItcR/Pccl-itaconic acid-inducible system from Yersinia pseudotuberculosis were thoroughly characterised for their regulator- and ligand dependent orthogonality, induction kinetics and dynamics. This thesis highlights their potential to be applied as biosensors for high-throughput microbial strain development to facilitate improved 3-HP and itaconate biosynthesis

A genome-wide approach for identification and characterisation of metabolite-inducible systems

© 2020, The Author(s). Inducible gene expression systems are vital tools for the advancement of synthetic biology. Their application as genetically encoded biosensors has the potential to contribute to diagnostics and to revolutionise the field of microbial cell factory development. Currently, the number of compounds of biological interest by far exceeds the number of available biosensors. Here, we address this limitation by developing a generic genome-wide approach to identify transcription factor-based inducible gene expression systems. We construct and validate 15 functional biosensors, provide a characterisation workflow to facilitate forward engineering efforts, exemplify their broad-host-range applicability, and demonstrate their utility in enzyme screening. Previously uncharacterised interactions between sensors and compounds of biological relevance are identified by employing the largest reported library of metabolite-responsive biosensors in an automated high-throughput screen. With the rapidly growing genomic data these innovative capabilities offer a platform to vastly increase the number of biologically detectable molecules

Engineering β-oxidation in <i>Yarrowia lipolytica</i> for methyl ketone production

Medium- and long-chain methyl ketones are fatty acid-derived compounds that can be used as biofuel blending agents, flavors and fragrances. However, their large-scale production from sustainable feedstocks is currently limited due to the lack of robust microbial biocatalysts. The oleaginous yeast Yarrowia lipolytica is a promising biorefinery platform strain for the production of methyl ketones from renewable lignocellulosic biomass due to its natively high flux towards fatty acid biosynthesis. In this study, we report the metabolic engineering of Y. lipolytica to produce long- and very long-chain methyl ketones. Truncation of peroxisomal β-oxidation by chromosomal deletion of pot1 resulted in the biosynthesis of saturated, mono-, and diunsaturated methyl ketones in the C13-C23 range. Additional overexpression and peroxisomal targeting of a heterologous bacterial methyl ketone biosynthesis pathway yielded an initial titer of 151.5 mg/L of saturated methyl ketones. Dissolved oxygen concentrations in the cultures were found to substantially impact cell morphology and methyl ketone biosynthesis. Bioreactor cultivation under optimized conditions resulted in a titer of 314.8 mg/L of total methyl ketones, representing more than a 6000-fold increase over the parental strain. This work highlights the potential of Y. lipolytica to serve as chassis organism for the biosynthesis of acyl-thioester derived long- and very long-chain methyl ketones.</p

Identification, characterisation and application of inducible gene expression systems in Cupriavidus necator H16 and other bacteria

The production of key building block chemicals from renewable resources or waste forms a rapidly growing segment of the bioeconomy. The conversion of waste gases, such as carbon dioxide or carbon monoxide, into value-added compounds using metabolically engineered microorganisms has significant potential to maintain economic independence while reducing greenhouse gas emissions. Modification of cellular metabolism for the biosynthesis of a target molecule often requires an adjustment of gene expression, either of an endogenous or a heterologous metabolic pathway. Transcription factors are DNA-binding proteins that control gene expression at the transcriptional level in response to physical parameters, ions, or small effector molecules. They have become indispensable tools for the advancement of synthetic biology and metabolic engineering. In this work, significant progress was made in the discovery and characterisation of transcription factor-based inducible gene expression systems for metabolic engineering of the chemolithoautotroph Cupriavidus necator H16 and other bacteria. Firstly, a quantitative evaluation of a range of well characterised heterolougous inducible systems in C. necator was undertaken. Four of them, the positively regulated L-arabinose- and L-rhamnose-inducible systems and the negatively regulated acrylate- and cumate-inducible systems, were subsequently employed for the biosynthesis of the industrially relevant building block chemical isoprene. In addition to being used for controlling expression of structural genes, transcription factor-based inducible systems have gained increasing interest for their application as genetically encoded biosensors. Their ability to transduce the intracellular concentration of a target molecule into an output signal detectable in a high throughput format has the potential to revolutionise the field of microbial cell factory development. Currently, the number of compounds of biological interest by far exceeds the number of available biosensors. Here, this limitation was addressed by developing a universal genome-wide approach to identify novel transcription factor-based inducible gene expression systems. Once developed, the methodical pipeline was evaluated in the metabolically versatile C. necator. In total, 15 novel or little characterised inducible systems were identified and their broad host-range applicability was exemplified in three industrially relevant prokaryotes. Novel interactions between existing sensors and compounds of biological relevance were discovered by employing the largest reported library of transcription factor-based inducible systems in an automated high throughput screen. The same strategy, which was pursued in order to mine native inducible systems from the genome of C. necator, was used to source inducible systems responding to the industrially relevant platform chemicals 3-hydroxypropionic acid (3-HP) and itaconic acid. The HpdR/PhpdH-3-HP-inducible system from Pseudomonas putida KT2440 and the ItcR/Pccl-itaconic acid-inducible system from Yersinia pseudotuberculosis were thoroughly characterised for their regulator- and ligand dependent orthogonality, induction kinetics and dynamics. This thesis highlights their potential to be applied as biosensors for high-throughput microbial strain development to facilitate improved 3-HP and itaconate biosynthesis

SelenzymeRF: updated enzyme suggestion software for unbalanced biochemical reactions

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/

TFBMiner: A User-Friendly Command Line Tool for the Rapid Mining of Transcription Factor-Based Biosensors

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

TFBMiner: A User-Friendly Command Line Tool for the Rapid Mining of Transcription Factor-Based Biosensors

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

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