Taming CRISPRi: Dynamic range tuning through guide RNA diversion.

CRISPRi is a powerful technique to repress gene expression in a targeted and highly efficient manner. However, this potency is a double-edged sword in inducible systems, as even leaky expression of guide RNA results in a repression phenotype, complicating applications such as dynamic metabolic engineering. We evaluated three methods to enhance the controllability of CRISPRi by modulating the level of free and DNA-bound guide RNA complexes. Overall repression can be attenuated through rationally designed mismatches in the reversibility determining region of the guide RNA sequence; decoy target sites can selectively modulate repression at low levels of induction; and the implementation of feedback control not only enhances the linearity of induction, but broadens the dynamic range of the output as well. Furthermore, feedback control significantly enhances the recovery rate after induction is removed. Used in combination, these techniques enable the fine-tuning of CRISPRi to meet restrictions imposed by the target and match the input signal required for induction.

Dynamic feedback regulation for efficient membrane protein production using a small RNA-based genetic circuit in Escherichia coli.

BACKGROUND: Membrane proteins (MPs) are an important class of molecules with a wide array of cellular functions and are part of many metabolic pathways. Despite their great potential-as therapeutic drug targets or in microbial cell factory optimization-many challenges remain for efficient and functional expression in a host such as Escherichia coli. RESULTS: A dynamically regulated small RNA-based circuit was developed to counter membrane stress caused by overexpression of different MPs. The best performing small RNAs were able to enhance the maximum specific growth rate with 123%. On culture level, the total MP production was increased two-to three-fold compared to a system without dynamic control. This strategy not only improved cell growth and production of the studied MPs, it also suggested the potential use for countering metabolic burden in general. CONCLUSIONS: A dynamically regulated feedback circuit was developed that can sense metabolic stress caused by, in casu, the overexpression of an MP and responds to it by balancing the metabolic state of the cell and more specifically by downregulating the expression of the MP of interest. This negative feedback mechanism was established by implementing and optimizing simple-to-use genetic control elements based on post-transcriptional regulation: small non-coding RNAs. In addition to membrane-related stress when the MP accumulated in the cytoplasm as aggregates, the sRNA-based feedback control system was still effective for improving cell growth but resulted in a decreased total protein production. This result suggests promiscuity of the MP sensor for more than solely membrane stress.

ProD: A Tool for Predictive Design of Tailored Promoters in Escherichia coli.

A major goal in synthetic biology is the engineering of synthetic gene circuits with a predictable, controlled and designed outcome. This creates a need for building blocks that can modulate gene expression without interference with the native cell system. A tool allowing forward engineering of promoters with predictable transcription initiation frequency is still lacking. Promoter libraries specific for σ70 to ensure the orthogonality of gene expression were built in Escherichia coli and labeled using fluorescence-activated cell sorting to obtain high-throughput DNA sequencing data to train a convolutional neural network. We were able to confirm in vivo that the model is able to predict the promoter transcription initiation frequency (TIF) of new promoter sequences. Here, we provide an online tool for promoter design (ProD) in E. coli, which can be used to tailor output sequences of desired promoter TIF or predict the TIF of a custom sequence.

Biosensor-driven, model-based optimization of the orthogonally expressed naringenin biosynthesis pathway.

BACKGROUND: The rapidly expanding synthetic biology toolbox allows engineers to develop smarter strategies to tackle the optimization of complex biosynthetic pathways. In such a strategy, multi-gene pathways are subdivided in several modules which are each dynamically controlled to fine-tune their expression in response to a changing cellular environment. To fine-tune separate modules without interference between modules or from the host regulatory machinery, a sigma factor (σ) toolbox was developed in previous work for tunable orthogonal gene expression. Here, this toolbox is implemented in E. coli to orthogonally express and fine-tune a pathway for the heterologous biosynthesis of the industrially relevant plant metabolite, naringenin. To optimize the production of this pathway, a practical workflow is still imperative to balance all steps of the pathway. This is tackled here by the biosensor-driven screening, subsequent genotyping of combinatorially engineered libraries and finally the training of three different computer models to predict the optimal pathway configuration. RESULTS: The efficiency and knowledge gained through this workflow is demonstrated here by improving the naringenin production titer by 32% with respect to a random pathway library screen. Our best strain was cultured in a batch bioreactor experiment and was able to produce 286 mg/L naringenin from glycerol in approximately 26 h. This is the highest reported naringenin production titer in E. coli without the supplementation of pathway precursors to the medium or any precursor pathway engineering. In addition, valuable pathway configuration preferences were identified in the statistical learning process, such as specific enzyme variant preferences and significant correlations between promoter strength at specific steps in the pathway and titer. CONCLUSIONS: An efficient strategy, powered by orthogonal expression, was applied to successfully optimize a biosynthetic pathway for microbial production of flavonoids in E. coli up to high, competitive levels. Within this strategy, statistical learning techniques were combined with combinatorial pathway optimization techniques and an in vivo high-throughput screening method to efficiently determine the optimal operon configuration of the pathway. This "pathway architecture designer" workflow can be applied for the fast and efficient development of new microbial cell factories for different types of molecules of interest while also providing additional insights into the underlying pathway characteristics.

Predictive design of sigma factor-specific promoters.

To engineer synthetic gene circuits, molecular building blocks are developed which can modulate gene expression without interference, mutually or with the host's cell machinery. As the complexity of gene circuits increases, automated design tools and tailored building blocks to ensure perfect tuning of all components in the network are required. Despite the efforts to develop prediction tools that allow forward engineering of promoter transcription initiation frequency (TIF), such a tool is still lacking. Here, we use promoter libraries of E. coli sigma factor 70 (σ70)- and B. subtilis σB-, σF- and σW-dependent promoters to construct prediction models, capable of both predicting promoter TIF and orthogonality of the σ-specific promoters. This is achieved by training a convolutional neural network with high-throughput DNA sequencing data from fluorescence-activated cell sorted promoter libraries. This model functions as the base of the online promoter design tool (ProD), providing tailored promoters for tailored genetic systems.

Mapping and refactoring pathway control through metabolic and protein engineering: The hexosamine biosynthesis pathway.

Microorganisms possess a plethora of regulatory mechanisms to tightly control the flux through their metabolic network, allowing optimal behaviour in response to environmental conditions. However, these mechanisms typically counteract metabolic engineering efforts to rewire the metabolism with a view to overproduction. Hence, overcoming flux control is key in the development of microbial cell factories, illustrated in this contribution using the strictly controlled hexosamine biosynthesis pathway. The hexosamine biosynthesis pathway has recently garnered attention as gateway for the industrial biotechnological production of numerous mono-, oligo- and polysaccharidic compounds, composed of, i.a., glucosamine, N-acetylglucosamine, and neuraminic acid and with a vast application potential in the health, comsetics, and agricultural sector. First, the various alternative pathways in eukaryotes and prokaryotes are discussed. Second, the main regulatory mechanisms on transcriptional, translational and post-translational control, and the strategies to circumvent these pathway bottlenecks are highlighted. These efforts can serve as an inspiration to tackle regulatory control when optimizing any microbial cell factory.

Chimeric LysR-Type Transcriptional Biosensors for Customizing Ligand Specificity Profiles toward Flavonoids.

Transcriptional biosensors enable key applications in both metabolic engineering and synthetic biology. Due to nature's immense variety of metabolites, these applications require biosensors with a ligand specificity profile customized to the researcher's needs. In this work, chimeric biosensors were created by introducing parts of a donor regulatory circuit from Sinorhizobium meliloti, delivering the desired luteolin-specific response, into a nonspecific biosensor chassis from Herbaspirillum seropedicae. Two strategies were evaluated for the development of chimeric LysR-type biosensors with customized ligand specificity profiles toward three closely related flavonoids, naringenin, apigenin, and luteolin. In the first strategy, chimeric promoter regions were constructed at the biosensor effector module, while in the second strategy, chimeric transcription factors were created at the biosensor detector module. Via both strategies, the biosensor repertoire was expanded with luteolin-specific chimeric biosensors demonstrating a variety of response curves and ligand specificity profiles. Starting from the nonspecific biosensor chassis, a shift from 27.5% to 95.3% luteolin specificity was achieved with the created chimeric biosensors. Both strategies provide a compelling, faster, and more accessible route for the customization of biosensor ligand specificity, compared to de novo design and construction of each biosensor circuit for every desired ligand specificity.

Exploring of the feature space of de novo developed post-transcriptional riboregulators.

Metabolic engineering increasingly depends upon RNA technology to customly rewire the metabolism to maximize production. To this end, pure riboregulators allow dynamic gene repression without the need of a potentially burdensome coexpressed protein like typical Hfq binding small RNAs and clustered regularly interspaced short palindromic repeats technology. Despite this clear advantage, no clear general design principles are available to de novo develop repressing riboregulators, limiting the availability and the reliable development of these type of riboregulators. Here, to overcome this lack of knowledge on the functionality of repressing riboregulators, translation inhibiting RNAs are developed from scratch. These de novo developed riboregulators explore features related to thermodynamical and structural factors previously attributed to translation initiation modulation. In total, 12 structural and thermodynamic features were defined of which six features were retained after removing correlations from an in silico generated riboregulator library. From this translation inhibiting RNA library, 18 riboregulators were selected using a experimental design and subsequently constructed and co-expressed with two target untranslated regions to link the translation inhibiting RNA features to functionality. The pure riboregulators in the design of experiments showed repression down to 6% of the original protein expression levels, which could only be partially explained by a ordinary least squares regression model. To allow reliable forward engineering, a partial least squares regression model was constructed and validated to link the properties of translation inhibiting RNA riboregulators to gene repression. In this model both structural and thermodynamic features were important for efficient gene repression by pure riboregulators. This approach enables a more reliable de novo forward engineering of effective pure riboregulators, which further expands the RNA toolbox for gene expression modulation.

Modularization and Response Curve Engineering of a Naringenin-Responsive Transcriptional Biosensor.

To monitor the intra- and extracellular environment of micro-organisms and to adapt their metabolic processes accordingly, scientists are reprogramming nature's myriad of transcriptional regulatory systems into transcriptional biosensors, which are able to detect small molecules and, in response, express specific output signals of choice. However, the naturally occurring response curve, the key characteristic of biosensor circuits, is typically not in line with the requirements for real-life biosensor applications. In this contribution, a natural LysR-type naringenin-responsive biosensor circuit is developed and characterized with Escherichia coli as host organism. Subsequently, this biosensor is dissected into a clearly defined detector and effector module without loss of functionality, and the influence of the expression levels of both modules on the biosensor response characteristics is investigated. Two collections of ten unique synthetic biosensors each are generated. Each collection demonstrates a unique diversity of response curve characteristics spanning a 128-fold change in dynamic and 2.5-fold change in operational ranges and 3-fold change in levels of Noise, fit for a wide range of applications, such as adaptive laboratory evolution, dynamic pathway control and high-throughput screening methods. The established biosensor engineering concepts, and the developed biosensor collections themselves, are of use for the future development and customization of biosensors in general, for the multitude of biosensor applications and as a compelling alternative for the commonly used LacI-, TetR- and AraC-based inducible circuits.

Development of N-acetylneuraminic acid responsive biosensors based on the transcriptional regulator NanR.

Transcriptional biosensors have various applications in metabolic engineering, including dynamic pathway control and high-throughput screening of combinatorial strain libraries. Previously, various biosensors have been created from naturally occurring transcription factors (TFs), largely relying on native sequences without the possibility to modularly optimize their response curve. The lack of design and engineering techniques thus greatly hinders the development of custom biosensors. In view of the intended application this is detrimental. In contrast, a bottom-up approach to design tailor-made biosensors was pursued here. Novel biosensors were created that respond to N-acetylneuraminic acid (Neu5Ac), an important sugar moiety with various biological functions, by employing native and engineered promoters that interact with the TF NanR. This bottom-up approach, whereby various tuned modules, e.g., the ribosome binding site (RBS) controlling NanR translation can be combined, enabled the reliable engineering of various response curve characteristics. The latter was validated by testing these biosensors in combination with various Neu5Ac-producing pathways, which allowed to produce up to 1.4 ± 0.4 g/L extracellular Neu5Ac. In this way, the repertoire of biosensors was expanded with seven novel functional Neu5Ac-responsive biosensors.

A sigma factor toolbox for orthogonal gene expression in Escherichia coli.

Synthetic genetic sensors and circuits enable programmable control over timing and conditions of gene expression and, as a result, are increasingly incorporated into the control of complex and multi-gene pathways. Size and complexity of genetic circuits are growing, but stay limited by a shortage of regulatory parts that can be used without interference. Therefore, orthogonal expression and regulation systems are needed to minimize undesired crosstalk and allow for dynamic control of separate modules. This work presents a set of orthogonal expression systems for use in Escherichia coli based on heterologous sigma factors from Bacillus subtilis that recognize specific promoter sequences. Up to four of the analyzed sigma factors can be combined to function orthogonally between each other and toward the host. Additionally, the toolbox is expanded by creating promoter libraries for three sigma factors without loss of their orthogonal nature. As this set covers a wide range of transcription initiation frequencies, it enables tuning of multiple outputs of the circuit in response to different sensory signals in an orthogonal manner. This sigma factor toolbox constitutes an interesting expansion of the synthetic biology toolbox and may contribute to the assembly of more complex synthetic genetic systems in the future.

Standardization in synthetic biology: an engineering discipline coming of age.

BACKGROUND: Leaping DNA read-and-write technologies, and extensive automation and miniaturization are radically transforming the field of biological experimentation by providing the tools that enable the cost-effective high-throughput required to address the enormous complexity of biological systems. However, standardization of the synthetic biology workflow has not kept abreast with dwindling technical and resource constraints, leading, for example, to the collection of multi-level and multi-omics large data sets that end up disconnected or remain under- or even unexploited. PURPOSE: In this contribution, we critically evaluate the various efforts, and the (limited) success thereof, in order to introduce standards for defining, designing, assembling, characterizing, and sharing synthetic biology parts. The causes for this success or the lack thereof, as well as possible solutions to overcome these, are discussed. CONCLUSION: Akin to other engineering disciplines, extensive standardization will undoubtedly speed-up and reduce the cost of bioprocess development. In this respect, further implementation of synthetic biology standards will be crucial for the field in order to redeem its promise, i.e. to enable predictable forward engineering.

Recursive DNA Assembly Using Protected Oligonucleotide Duplex Assisted Cloning (PODAC).

A problem rarely tackled by current DNA assembly methods is the issue of cloning additional parts into an already assembled construct. Costly PCR workflows are often hindered by repeated sequences, and restriction based strategies impose design constraints for each enzyme used. Here we present Protected Oligonucleotide Duplex Assisted Cloning (PODAC), a novel technique that makes use of an oligonucleotide duplex for iterative Golden Gate cloning using only one restriction enzyme. Methylated bases confer protection from digestion during the assembly reaction and are removed during replication in vivo, unveiling a new cloning site in the process. We used this method to efficiently and accurately assemble a biosynthetic pathway and demonstrated its robustness toward sequence repeats by constructing artificial CRISPR arrays. As PODAC is readily amenable to standardization, it would make a useful addition to the synthetic biology toolkit.

Direct Combinatorial Pathway Optimization.

Combinatorial engineering approaches are becoming increasingly popular, yet they are hindered by the lack of specialized techniques for both efficient introduction of sequence variability and assembly of numerous DNA parts, required for the construction of lengthy multigene pathways. In this contribution, we introduce a new combinatorial multigene pathway assembly scheme based on Single Strand Assembly (SSA) methods and Golden Gate Assembly, exploiting the strengths of both assembly techniques. With a minimum of intermediary steps and an accompanying set of well-characterized and ready-to-use genetic parts, the developed workflow allows effective introduction of various libraries and efficient assembly of multigene pathways. It was put to the test by optimizing the lycopene pathway as proof-of-principle. The here constructed libraries yield ample variation in lycopene production. In addition, good-performing transformants with a significantly higher lycopene production were obtained as compared to previously published reference strains. The best selected producer yielded 3-fold improvement in lycopene titers up to 448 mg lycopene/g CDW. The proposed workflow in combination with the accompanying sets of ready-to-use expression and carrier plasmids, will allow the combinatorial assembly of increasingly lengthy product pathways with minimal effort.

Tailor-made transcriptional biosensors for optimizing microbial cell factories.

Monitoring cellular behavior and eventually properly adapting cellular processes is key to handle the enormous complexity of today's metabolic engineering questions. Hence, transcriptional biosensors bear the potential to augment and accelerate current metabolic engineering strategies, catalyzing vital advances in industrial biotechnology. The development of such transcriptional biosensors typically starts with exploring nature's richness. Hence, in a first part, the transcriptional biosensor architecture and the various modi operandi are briefly discussed, as well as experimental and computational methods and relevant ontologies to search for natural transcription factors and their corresponding binding sites. In the second part of this review, various engineering approaches are reviewed to tune the main characteristics of these (natural) transcriptional biosensors, i.e., the response curve and ligand specificity, in view of specific industrial biotechnology applications, which is illustrated using success stories of transcriptional biosensor engineering.

Comparative fluxome and metabolome analysis for overproduction of succinate in Escherichia coli.

An aerobic succinate-producing Escherichia coli mutant was compared to its wild-type by quantitatively analyzing both the metabolome and fluxome, during glucose-limited steady-state and succinate excess dynamic conditions, in order to identify targets for further strain engineering towards more efficient succinate production. The mutant had four functional mutations under the conditions investigated: increased expression of a succinate exporter (DcuC), deletion of a succinate importer (Dct), deletion of succinate dehydrogenase (SUCDH) and expression of a PEP carboxylase (PPC) with increased capacity due to a point mutation. The steady-state and dynamic patterns of the intracellular metabolite levels and fluxes in response to changes were used to locate the quantitative differences in the physiology/metabolism of the mutant strain. Unexpectedly the mutant had a higher energy efficiency, indicated by a much lower rate of oxygen consumption, under glucose-limited conditions, caused by the deletion of the transcription factors IclR and ArcA. Furthermore the mutant had a much lower uptake capacity for succinate (26-fold) and oxygen (17-fold under succinate excess) compared to the wild-type strain. The mutant strain produced 7.9 mmol.CmolX(-1).h(-1) succinate during chemostat cultivation, showing that the choice of the applied genetic modifications was a successful strategy. Furthermore, the applied genetic modifications resulted in multiple large changes in metabolite levels (FBP, pyruvate, 6PG, NAD(+) /NADH ratio, α-ketogluarate) corresponding to large changes in fluxes. Compared to the wild-type a considerable flux shift occurred from the tricarboxylic acid (TCA) cycle to the oxidative part of the pentose phosphate pathway, including an inversion of the pyruvate kinase flux. The mutant responded very differently to excess of succinate, with a remarkable possible reversal of the TCA cycle. The mutant and the wild-type both showed homeostatic behaviour with respect to the energy charge. In contrast, large changes in redox ratios (NAD(+) /NADH) occurred in the wild-type, while the mutant showed even larger changes. This large redox change can be associated to the reversal of flux directions. The observed large flexibility in the central metabolism following genetic (deletions) and environmental (substrate excess) perturbations of the mutant, indicates that introducing a more efficient succinate exporter could result in an even higher succinate production rate.

Putting RNA to work: Translating RNA fundamentals into biotechnological engineering practice.

Synthetic biology, in close concert with systems biology, is revolutionizing the field of metabolic engineering by providing novel tools and technologies to rationally, in a standardized way, reroute metabolism with a view to optimally converting renewable resources into a broad range of bio-products, bio-materials and bio-energy. Increasingly, these novel synthetic biology tools are exploiting the extensive programmable nature of RNA, vis-à-vis DNA- and protein-based devices, to rationally design standardized, composable, and orthogonal parts, which can be scaled and tuned promptly and at will. This review gives an extensive overview of the recently developed parts and tools for i) modulating gene expression ii) building genetic circuits iii) detecting molecules, iv) reporting cellular processes and v) building RNA nanostructures. These parts and tools are becoming necessary armamentarium for contemporary metabolic engineering. Furthermore, the design criteria, technological challenges, and recent metabolic engineering success stories of the use of RNA devices are highlighted. Finally, the future trends in transforming metabolism through RNA engineering are critically evaluated and summarized.

Metabolic engineering of Escherichia coli into a versatile glycosylation platform: production of bio-active quercetin glycosides.

BACKGROUND: Flavonoids are bio-active specialized plant metabolites which mainly occur as different glycosides. Due to the increasing market demand, various biotechnological approaches have been developed which use Escherichia coli as a microbial catalyst for the stereospecific glycosylation of flavonoids. Despite these efforts, most processes still display low production rates and titers, which render them unsuitable for large-scale applications. RESULTS: In this contribution, we expanded a previously developed in vivo glucosylation platform in E. coli W, into an efficient system for selective galactosylation and rhamnosylation. The rational of the novel metabolic engineering strategy constitutes of the introduction of an alternative sucrose metabolism in the form of a sucrose phosphorylase, which cleaves sucrose into fructose and glucose 1-phosphate as precursor for UDP-glucose. To preserve these intermediates for glycosylation purposes, metabolization reactions were knocked-out. Due to the pivotal role of UDP-glucose, overexpression of the interconverting enzymes galE and MUM4 ensured the formation of both UDP-galactose and UDP-rhamnose, respectively. By additionally supplying exogenously fed quercetin and overexpressing a flavonol galactosyltransferase (F3GT) or a rhamnosyltransferase (RhaGT), 0.94 g/L hyperoside (quercetin 3-O-galactoside) and 1.12 g/L quercitrin (quercetin 3-O-rhamnoside) could be produced, respectively. In addition, both strains showed activity towards other promising dietary flavonols like kaempferol, fisetin, morin and myricetin. CONCLUSIONS: Two E. coli W mutants were engineered that could effectively produce the bio-active flavonol glycosides hyperoside and quercitrin starting from the cheap substrates sucrose and quercetin. This novel fermentation-based glycosylation strategy will allow the economically viable production of various glycosides.

Development of an in vivo glucosylation platform by coupling production to growth: Production of phenolic glucosides by a glycosyltransferase of Vitis vinifera.

Glycosylation of small molecules can significantly alter their properties such as solubility, stability, and/or bioactivity, making glycosides attractive and highly demanded compounds. Consequently, many biotechnological glycosylation approaches have been developed, with enzymatic synthesis and whole-cell biocatalysis as the most prominent techniques. However, most processes still suffer from low yields, production rates and inefficient UDP-sugar formation. To this end, a novel metabolic engineering strategy is presented for the in vivo glucosylation of small molecules in Escherichia coli W. This strategy focuses on the introduction of an alternative sucrose metabolism using sucrose phosphorylase for the direct and efficient generation of glucose 1-phosphate as precursor for UDP-glucose formation and fructose, which serves as a carbon source for growth. By targeted gene deletions, a split metabolism is created whereby glucose 1-phosphate is rerouted from the glycolysis to product formation (i.e., glucosylation). Further, the production pathway was enhanced by increasing and preserving the intracellular UDP-glucose pool. Expression of a versatile glucosyltransferase from Vitis vinifera (VvGT2) enabled the strain to efficiently produce 14 glucose esters of various hydroxycinnamates and hydroxybenzoates with conversion yields up to 100%. To our knowledge, this fast growing (and simultaneously producing) E. coli mutant is the first versatile host described for the glucosylation of phenolic acids in a fermentative way using only sucrose as a cheap and sustainable carbon source.

Biotechnological advances in UDP-sugar based glycosylation of small molecules.

Glycosylation of small molecules like specialized (secondary) metabolites has a profound impact on their solubility, stability or bioactivity, making glycosides attractive compounds as food additives, therapeutics or nutraceuticals. The subsequently growing market demand has fuelled the development of various biotechnological processes, which can be divided in the in vitro (using enzymes) or in vivo (using whole cells) production of glycosides. In this context, uridine glycosyltransferases (UGTs) have emerged as promising catalysts for the regio- and stereoselective glycosylation of various small molecules, hereby using uridine diphosphate (UDP) sugars as activated glycosyldonors. This review gives an extensive overview of the recently developed in vivo production processes using UGTs and discusses the major routes towards UDP-sugar formation. Furthermore, the use of interconverting enzymes and glycorandomization is highlighted for the production of unusual or new-to-nature glycosides. Finally, the technological challenges and future trends in UDP-sugar based glycosylation are critically evaluated and summarized.