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All living organisms have evolved and fine-tuned specialized mechanisms to precisely monitor a vast array of different types of molecules. These natural mechanisms can be sourced by researchers to build Biological Sensors (BioS) by combining them with an easily measurable output, such as fluorescence. Because they are genetically encoded, BioS are cheap, fast, sustainable, portable, self-generating and highly sensitive and specific. Therefore, BioS hold the potential to become key enabling tools that stimulate innovation and scientific exploration in various disciplines. However, the main bottleneck in unlocking the full potential of BioS is the fact that there is no standardized, efficient and tunable platform available for the high-throughput construction and characterization of biosensors. Therefore, a modular, Golden Gate-based construction platform, called MoBioS, is introduced in this article. It allows for the fast and easy creation of transcription factor-based biosensor plasmids. As a proof of concept, its potential is demonstrated by creating eight different, functional and standardized biosensors that detect eight diverse molecules of industrial interest. In addition, the platform contains novel built-in features to facilitate fast and efficient biosensor engineering and response curve tuning.

Synthetic biology can play a major role in the development of sustainable industrial biotechnology processes. However, the development of economically viable production processes is currently hampered by the limited availability of host organisms that can be engineered for a specific production process. To date, standard hosts such as Escherichia coli and Saccharomyces cerevisiae are often used as starting points for process development since parts and tools allowing their engineering are readily available. However, their suboptimal metabolic background or impaired performance at industrial scale for a desired production process, can result in increased costs associated with process development and/or disappointing production titres. Building a universal and portable gene expression system allowing genetic engineering of hosts across the bacterial domain would unlock the bacterial domain for industrial biotechnology applications in a highly standardized manner and, doing so, render industrial biotechnology processes more competitive compared to the current polluting chemical processes. This review gives an overview of a selection of bacterial hosts highly interesting for industrial biotechnology based on both their metabolic and process optimization properties. Moreover, the requirements and progress made so far to enable universal, standardized, and portable gene expression across the bacterial domain is discussed.

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 σ

Catechins have proven to have several health benefits, yet a huge interindividual variability occurs. The meta-bolic potency of the colonic microbiota towards catechin is a key determinant of this variability. Microbiota from two donors - previously characterized as a fast and a slow converter- were incubated with (+)-catechin in vitro. The robustness of in vitro metabolic profiles was verified by well-fitted human trials. The colon region-dependent and donor-dependent patterns were reflected in both metabolic features and colonic microbiota composition. Upstream and downstream metabolites were mainly detected in the proximal and distal colons, respectively, and were considered important explanatory variables for microbiota clustering in the corresponding colon regions. Higher abundances of two catechin-metabolizing bacteria, Eggerthella and Flavonifractor were found in the distal colon compared to the proximal colon and in slow converter than fast converter. Additionally, these two bacteria were enriched in treatment samples compared to sham treatment samples.

Synthetic biology requires well-characterized biological parts that can be combined into functional modules. One type of biological parts are transcriptional regulators and their cognate operator elements, which enable to either generate an input-specific response or are used as actuator modules. A range of regulators has already been characterized and used for orthogonal gene expression engineering, however, previous efforts have mostly focused on bacterial regulators. This work aims to design and explore the use of an archaeal TetR family regulator, FadRSa from Sulfolobus acidocaldarius, in a bacterial system, namely Escherichia coli. This is a challenging objective given the fundamental difference between the bacterial and archaeal transcription machinery and the lack of a native TetR-like FadR regulatory system in E. coli. The synthetic σ70-dependent bacterial promoter proD was used as a starting point to design hybrid bacterial/archaeal promoter/operator regions, in combination with the mKate2 fluorescent reporter enabling a readout. Four variations of proD containing FadRSa binding sites were constructed and characterized. While expressional activity of the modified promoter proD was found to be severely diminished for two of the constructs, constructs in which the binding site was introduced adjacent to the -35 promoter element still displayed sufficient basal transcriptional activity and showed up to 7-fold repression upon expression of FadRSa. Addition of acyl-CoA has been shown to disrupt FadRSa binding to the DNA in vitro. However, extracellular concentrations of up to 2 mM dodecanoate, subsequently converted to acyl-CoA by the cell, did not have a significant effect on repression in the bacterial system. This work demonstrates that archaeal transcription regulators can be used to generate actuator elements for use in E. coli, although the lack of ligand response underscores the challenge of maintaining biological function when transferring parts to a phylogenetically divergent host.

Glycolipids are target molecules in biotechnology and biomedicine as biosurfactants, biomaterials and bioactive molecules. An engineered E. coli strain for the production of glycoglycerolipids (GGL) used the MG517 glycolipid synthase from M. genitalium for glucosyl transfer from UDPGlc to diacylglycerol acceptor (Mora-Buye et al., 2012). The intracellular diacylglycerol pool proved to be the limiting factor for GGL production. Here we designed different metabolic engineering strategies to enhance the availability of precursor substrates for the glycolipid synthase by modulating fatty acids, acyl donor and phosphatidic acid biosynthesis. Knockouts of tesA, fadE and fabR genes involved in fatty acids degradation, overexpression of the transcriptional regulator FadR, the acyltransferases PlsB and C, and the pyrophosphatase Cdh for phosphatidic acid biosynthesis, as well as the phosphatase PgpB for conversion to diacylglycerol were explored with the aim of improving GGL titers. Among the different engineered strains, the ΔtesA strain co-expressing MG517 and a fusion PlsCxPgpB protein was the best producer, with a 350% increase of GGL titer compared to the parental strain expressing MG517 alone. Attempts to boost UDPGlc availability by overexpressing the uridyltransferase GalU or knocking out the UDP-sugar diphosphatase encoding gene ushA did not further improve GGL titers. Most of the strains produced GGL containing a variable number of glucosyl units from mono-to tetra-saccharides. Interestingly, the strains co-expressing Cdh showed a shift in the GGL profile towards the diglucosylated lipid (up to 80% of total GGLs) whereas the strains with a fadR knockout presented a higher amount of unsaturated acyl chains. In all cases, GGL production altered the lipidic composition of the E. coli membrane, observing that GGL replace phosphatidylethanolamine to maintain the overall membrane charge balance.

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. ispartof: BIOTECHNOLOGY AND BIOENGINEERING vol:115 issue:7 pages:1855-1865 ispartof: location:United States status: published

Fine-tuning biosynthetic pathways is crucial for the development of economic feasible microbial cell factories. Therefore, the use of computational models able to predictably design regulatory sequences for pathway engineering proves to be a valuable tool, especially for modifying genes at the translational level. In this study we developed a computational approach for the de novo design of 5'-untranslated regions (5'UTRs) in Saccharomyces cerevisiae with a predictive outcome on translation initiation rate. On the basis of existing data, a partial least-squares (PLS) regression model was trained and showed good performance on predicting protein abundances of an independent test set. This model was further used for the construction of a "yUTR calculator" that can design 5'UTR sequences with a diverse range of desired translation efficiencies. The predictive power of our yUTR calculator was confirmed in vivo by different representative case studies. As such, these results show the great potential of data driven approaches for reliable pathway engineering in S. cerevisiae.

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.

Machine learning is becoming an integral part of the Design-Build-Test-Learn cycle in biotechnology. Machine learning models learn from collected datasets such as omics data and predict a defined outcome, which has led to both production improvements and predictive tools in the field. Robust prediction of the behavior of microbial cell factories and production processes not only greatly increases our understanding of the function of such systems, but also provides significant savings of development time. However, many pitfalls when modeling biological data – bad fit, noisy data, model instability, low data quantity and imbalances in the data – cause models to suffer in their performance. Here we provide an accessible, in-depth analysis on the problems created by these pitfalls, as well as means of their detection and mediation, with a focus on supervised learning. Assessing the state of the art, we show that, currently, in-depth analyses of model performance are often absent and must be improved. This review provides a toolbox for the analysis of model robustness and performance, and simultaneously proposes a standard for the community to facilitate future work. It is further accompanied by an interactive online tutorial on the discussed issues.

As flavonoids have beneficial health effects on humans, they are gaining increasing interest from pharmaceutical and health industries. However, current production methods, such as plant extraction and chemical synthesis, are inadequate to meet the demand. Therefore, microbial production might offer a promising alternative. During recent years, microbial strains able to produce flavonoids to a certain extent have been developed. However production titers are limited to the mg l−1 range, hampering the industrial exploitation of these strains. The latter will not be achieved by simply introducing the heterologous pathway in the production host and optimizing the fermentation process, but will depend on the interaction of different aspects of metabolic engineering and process engineering to overcome the current limitations. Next to engineering the production strain to optimize the availability of precursors, the pathway itself also requires intensive engineering. Currently utilized strategies result in a wide variety of different production strains, requiring high-throughput screening methods to identify optimal performing strains. As more and more organisms are being characterized, each with their own specific properties which might be beneficial for the heterologous production of flavonoids, the choice of the production host is another important aspect. Finally, the use of co-cultures might offer an alternative in which different parts of the process are performed by different organisms. This review aims to provide an overview of the research that has been done on these separate aspects. The work presented here could be used as a framework for further research.

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.

Taxadiene-5α-Hydroxylase (CYP725A4) is a membrane-bound plant cytochrome P450 that catalyzes the oxidation of taxadiene to taxadiene-5α-ol. This oxidation is a key step in the production of the valuable cancer therapeutic and natural plant product, taxol. In this work, we report the bacterial expression and purification of six different constructs of CYP725A4. All six of these constructs are N-terminally modified and three of them are fused to cytochrome P450 reductase to form a chimera construct. The construct with the highest yield of CYP725A4 protein was then selected for substrate binding and kinetic analysis. Taxadiene binding followed type-1 substrate patterns with an observed KD of 2.1 μM ± 0.4 μM. CYP725A4 was further incorporated into nanoscale lipid bilayers (nanodiscs) and taxadiene metabolism was measured. Taxadiene metabolism followed Michaelis-Menten kinetics with an observed Vmax of 30 ± 8 pmol/min/nmolCYP725A4 and a KM of 123 ± 52 μM. Additionally, molecular operating environment (MOE) modeling was performed in order to gain insight into the interactions of taxadiene with CYP725A4 active site. Taken together, we demonstrate the successful expression and purification of the functional membrane-bound plant CYP, CYP725A4, in E. coli.

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.

Biotechnological production routes for fine and bulk chemicals are progressively explored and developed. Yet this development is hampered by the many constraints determining the metabolic sweet spot, such as optimal expression levels, metabolic stress, feedback regulation, etc.In this regard, we introduce a novel, highly reliable, and rapid single-strand assembly (SSA) methods for combinatorial pathway engineering. In this contribution, SSA is elucidated which enables one to modulate the expression via promoter and/or RBS randomization. Moreover, a new combinatorial multigene pathway assembly scheme based on single-strand assembly (SSA) methods and Golden Gate Assembly is introduced, exploiting the strengths of both assembly techniques.

Biotechnological production routes for fine and bulk chemicals are progressively explored and developed. Yet this development is hampered by the many constraints determining the metabolic sweet spot, such as optimal expression levels, metabolic stress, feedback regulation, etc.In this regard, we introduce a novel, highly reliable, and rapid single-strand assembly (SSA) methods for combinatorial pathway engineering. In this contribution, SSA is elucidated which enables one to modulate the expression via promoter and/or RBS randomization. Moreover, a new combinatorial multigene pathway assembly scheme based on single-strand assembly (SSA) methods and Golden Gate Assembly is introduced, exploiting the strengths of both assembly techniques.

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.

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.

Recent advances in metabolic engineering have demonstrated the potential to exploit biological chemistry for the synthesis of complex molecules. Much of the progress to date has leveraged increasingly precise genetic tools to control the transcription and translation of enzymes for superior biosynthetic pathway performance. However, applying these approaches and principles to the synthesis of more complex natural products will require a new set of tools for enabling various classes of metabolic chemistries (i.e., cyclization, oxygenation, glycosylation, and halogenation) in vivo. Of these diverse chemistries, oxygenation is one of the most challenging and pivotal for the synthesis of complex natural products. Here, using Taxol as a model system, we use nature's favored oxygenase, the cytochrome P450, to perform high-level oxygenation chemistry in Escherichia coli. An unexpected coupling of P450 expression and the expression of upstream pathway enzymes was discovered and identified as a key obstacle for functional oxidative chemistry. By optimizing P450 expression, reductase partner interactions, and N-terminal modifications, we achieved the highest reported titer of oxygenated taxanes (∼570 ± 45 mg/L) in E. coli. Altogether, this study establishes E. coli as a tractable host for P450 chemistry, highlights the potential magnitude of protein interdependency in the context of synthetic biology and metabolic engineering, and points to a promising future for the microbial synthesis of complex chemical entities.

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.

Ethylene glycol (EG) is an important commodity chemical with broad industrial applications. It is presently produced from petroleum or natural gas feedstocks in processes requiring consumption of significant quantities of non-renewable resources. Here, we report a novel pathway for biosynthesis of EG from the renewable sugar glucose in metabolically engineered Escherichia coli. Serine-to-EG conversion was first achieved through a pathway comprising serine decarboxylase, ethanolamine oxidase, and glycolaldehyde reductase. Serine provision in E. coli was then enhanced by overexpression of the serine-biosynthesis pathway. The integration of these two parts into the complete EG-biosynthesis pathway in E. coli allowed for production of 4.1 g/L EG at a cumulative yield of 0.14 g-EG/g-glucose, establishing a foundation for a promising biotechnology. Biotechnol. Bioeng. 2016;113: 376–383. © 2015 Wiley Periodicals, Inc.

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.

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.

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., Author summary To allow reliable forward engineering of microbial cell factories, various metabolic engineering efforts rely on RNA-based technology. As such, programmable riboregulators allow dynamic control over gene expression. However, no clear design principles exist for de novo developed repressing riboregulators, which limits their applicability. Here, various engineering principles are identified and computationally explored. Subsequently, various design criteria are used in an experimental design, which were explored in an in vivo study. This resulted in a regression model that enables a more reliable computational design of repression small RNAs.

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.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.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.

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.

The rapid and efficient assembly of multi-step metabolic pathways for generating microbial strains with desirable phenotypes is a critical procedure for metabolic engineering, and remains a significant challenge in synthetic biology. Although several DNA assembly methods have been developed and applied for metabolic pathway engineering, many of them are limited by their suitability for combinatorial pathway assembly. The introduction of transcriptional (promoters), translational (ribosome binding site (RBS)) and enzyme (mutant genes) variability to modulate pathway expression levels is essential for generating balanced metabolic pathways and maximizing the productivity of a strain. We report a novel, highly reliable and rapid single strand assembly (SSA) method for pathway engineering. The method was successfully optimized and applied to create constructs containing promoter, RBS and/or mutant enzyme libraries. To demonstrate its efficiency and reliability, the method was applied to fine-tune multi-gene pathways. Two promoter libraries were simultaneously introduced in front of two target genes, enabling orthogonal expression as demonstrated by principal component analysis. This shows that SSA will increase our ability to tune multi-gene pathways at all control levels for the biotechnological production of complex metabolites, achievable through the combinatorial modulation of transcription, translation and enzyme activity.

The increasing public awareness of adverse health impacts from excessive sugar consumption has created increasing interest in plant-derived, natural low-calorie or zero-calorie sweeteners. Two plant species which contain natural sweeteners, Stevia rebaudiana and Siraitia grosvenorii, have been extensively profiled to identify molecules with high intensity sweetening properties. However, sweetening ability does not necessarily make a product viable for commercial applications. Some criteria for product success are proposed to identify which targets are likely to be accepted by consumers. Limitations of plant-based production are discussed, and a case is put forward for the necessity of biotechnological production methods such as plant cell culture or microbial fermentation to meet needs for commercial-scale production of natural sweeteners.

The GNB/LNB (galacto- N -biose/lacto- N -biose) pathway plays a crucial role in bifidobacteria during growth on human milk or mucin from epithelial cells. It is thought to be the major route for galactose utilization in Bifidobacterium longum as it is an energy-saving variant of the Leloir pathway. Both pathways are present in B. bifidum , and galactose 1-phosphate (gal1P) is considered to play a key role. Due to its toxic nature, gal1P is further converted into its activated UDP-sugar through the action of poorly characterized uridylyltransferases. In this study, three uridylyltransferases ( galT1 , galT2 , and ugpA ) from Bifidobacterium bifidum were cloned in an Escherichia coli mutant and screened for activity on the key intermediate gal1P. GalT1 and GalT2 showed UDP-glucose-hexose-1-phosphate uridylyltransferase activity (EC 2.7.7.12), whereas UgpA showed promiscuous UTP-hexose-1-phosphate uridylyltransferase activity (EC 2.7.7.10). The activity of UgpA toward glucose 1-phosphate was about 33-fold higher than that toward gal1P. GalT1, as part of the bifidobacterial Leloir pathway, was about 357-fold more active than GalT2, the functional analog in the GNB/LNB pathway. These results suggest that GalT1 plays a more significant role than previously thought and predominates when B. bifidum grows on lactose and human milk oligosaccharides. GalT2 activity is required only during growth on substrates with a GNB core such as mucin glycans.

In natural 1,3-propanediol (PDO) producing microorganisms such as Klebsiella pneumoniae, Citrobacter freundii and Clostridium sp., the genes coding for PDO producing enzymes are grouped in a dha cluster. This article describes the dha cluster of a novel candidate for PDO production, Citrobacter werkmanii DSM17579 and compares the cluster to the currently known PDO clusters of Enterobacteriaceae and Clostridiaceae. Moreover, we attribute a putative function to two previously unannotated ORFs, OrfW and OrfY, both in C. freundii and in C. werkmanii: both proteins might form a complex and support the glycerol dehydratase by converting cob(I)alamin to the glycerol dehydratase cofactor coenzyme B12. Unraveling this biosynthesis cluster revealed high homology between the deduced amino acid sequence of the open reading frames of C. werkmanii DSM17579 and those of C. freundii DSM30040 and K. pneumoniae MGH78578, i.e., 96 and 87.5 % identity, respectively. On the other hand, major differences between the clusters have also been discovered. For example, only one dihydroxyacetone kinase (DHAK) is present in the dha cluster of C. werkmanii DSM17579, while two DHAK enzymes are present in the cluster of K. pneumoniae MGH78578 and Clostridium butyricum VPI1718.

The interactions between the intracellular metabolome, fluxome and growth rate of Escherichia coli after sudden glycolytic/gluconeogenic substrate shifts are studied based on pulses of different substrates to an aerobic glucose-limited steady-state (dilution rate=0.1h(-1)). After each added glycolytic (glucose) and gluconeogenic (pyruvate and succinate) substrate pulse, no by-products were secreted and a pseudo steady state in flux and metabolites was achieved in about 30-40s. In the pulse experiments a large oxygen uptake capacity of the cells was observed. The in vivo dynamic responses showed massive reorganization and flexibility (1/100-14-fold change) of extra/intracellular metabolic fluxes, matching with large changes in the concentrations of intracellular metabolites, including reversal of reaction rate for pseudo/near equilibrium reactions. The coupling of metabolome and fluxome could be described by Q-linear kinetics. Remarkably, the three different substrate pulses resulted in a very similar increase in growth rate (0.13-0.3h(-1)). Data analysis showed that there must exist as yet unknown mechanisms which couple the protein synthesis rate to changes in central metabolites.

Natural product metabolic engineering potentially offers sustainable and affordable access to numerous valuable molecules. However, challenges in characterizing and assembling complex biosynthetic pathways have prevented more rapid progress in this field. The anticancer agent Taxol represents an excellent case study. Assembly of a biosynthetic pathway for Taxol has long been stalled at its first functionalization, putatively an oxygenation performed by the cytochrome P450 CYP725A4, due to confounding characterizations. Here, through combined in vivo (Escherichia coli), in vitro (lipid nanodisc), and metabolite stability assays, we verify the presence and likely cause of this enzyme's inherent promiscuity. Thereby, we remove the possibility that promiscuity simply existed as an artifact of previous metabolic engineering approaches. Further, spontaneous rearrangement and the stabilizing effect of a hydrophobic overlay suggest a potential role for nonenzymatic chemistry in Taxol's biosynthesis. Taken together, this work confirms taxadiene-5α-ol as a primary enzymatic product of CYP725A4 and provides direction for future Taxol metabolic and protein engineering efforts.

Impressive advances in the field of synthetic biology go hand in hand with the discovery, design, and use of novel DNA and RNA elements. Efficient synthesis of large oligonucleotides and double-stranded DNA parts, chip-based synthesis of DNA libraries, and a detailed understanding of fundamental biological mechanisms and increased capacities in bioinformatics enable new findings and applications.

WOS: 000368884500001, PubMed ID: 26822953, Background: Imbalance in cofactors causing the accumulation of intermediates in biosynthesis pathways is a frequently occurring problem in metabolic engineering when optimizing a production pathway in a microorganism. In our previous study, a single knock-out Citrobacter werkmanii Delta dhaD was constructed for improved 1,3-propanediol (PDO) production. Instead of an enhanced PDO concentration on this strain, the gene knock-out led to the accumulation of the toxic intermediate 3-hydroxypropionaldehyde (3-HPA). The hypothesis was emerged that the accumulation of this toxic intermediate, 3-HPA, is due to a cofactor imbalance, i.e. to the limited supply of reducing equivalents (NADH). Here, this bottleneck is alleviated by rationally engineering cell metabolism to balance the cofactor supply. Results: By eliminating non-essential NADH consuming enzymes (such as lactate dehydrogenase coded by ldhA, and ethanol dehydrogenase coded by adhE) or by increasing NADH producing enzymes, the accumulation of 3-HPA is minimized. Combining the above modifications in C. werkmanii Delta dhaD resulted in the strain C. werkmanii Delta dhaD Delta ldhA.adhE, Promotion of Innovation through Science and Technology in Flanders (IWT-Vlaanderen)Institute for the Promotion of Innovation by Science and Technology in Flanders (IWT) [B/14045/07]; Multidisciplinary Research Partnership Ghent Bio-Economy, The authors wish to thank the Institute for the Promotion of Innovation through Science and Technology in Flanders (IWT-Vlaanderen) for financial support in the framework of the PhD grant (B/14045/07) of Maervoet V. The research was also supported by the Multidisciplinary Research Partnership Ghent Bio-Economy. The authors wish to thank dr. Ajikumar Parayil for valuable comments on and edits to the manuscript which was improved by his helpful suggestions.

Transcription is a complex and dynamic process representing the first step in gene expression that can be readily controlled through current tools in molecular biology. Elucidating and subsequently controlling transcriptional processes in various prokaryotic and eukaryotic organisms have been a key element in translational research, yielding a variety of new opportunities for scientists and engineers. This chapter aims to give an overview of how the fields of molecular and synthetic biology have contributed both historically and presently to the state of the art in transcriptional engineering. The described tools and techniques, as well as the emerging genetic circuit engineering discipline, open the door to new advances in the fields of medical and industrial biotechnology.

Industrial biotechnology promises to revolutionize conventional chemical manufacturing in the years ahead, largely owing to the excellent progress in our ability to re-engineer cellular metabolism. However, most successes of metabolic engineering have been confined to over-producing natively synthesized metabolites in E. coli and S. cerevisiae. A major reason for this development has been the descent of metabolic engineering, particularly secondary metabolic engineering, to a collection of demonstrations rather than a systematic practice with generalizable tools. Synthetic biology, a more recent development, faces similar criticisms. Herein, we attempt to lay down a framework around which bioreaction engineering can systematize itself just like chemical reaction engineering. Central to this undertaking is a new approach to engineering secondary metabolism known as ‘multivariate modular metabolic engineering’ (MMME), whose novelty lies in its assessment and elimination of regulatory and pathway bottlenecks by re-defining the metabolic network as a collection of distinct modules. After introducing the core principles of MMME, we shall then present a number of recent developments in secondary metabolic engineering that could potentially serve as its facilitators. It is hoped that the ever-declining costs of de novo gene synthesis; the improved use of bioinformatic tools to mine, sort and analyze biological data; and the increasing sensitivity and sophistication of investigational tools will make the maturation of microbial metabolic engineering an autocatalytic process. Encouraged by these advances, research groups across the world would take up the challenge of secondary metabolite production in simple hosts with renewed vigor, thereby adding to the range of products synthesized using metabolic engineering., National Institutes of Health (U.S.) (1-R01-GM085323-01A1), Special Research Funds BOF (BOF08/PDO/014), Research Foundation Flanders (FWO-Vlaandern V.4.174.10.N.01)