SynBioFromLeukipposInstitute

Aromatic building blocks are amongst the most important bulk feedstocks in the chemical industry. As these compounds are commonly derived from petrochemistry, obtaining them is becoming more and more a matter of costs and sustainability. Biochemistry gives rise to a wealth of compounds that can potentially replace current petroleum-based chemicals or be used for novel materials. The aromatic compounds para-aminobenzoic acid (pABA) and para-hydroxybenzoic acid (pHBA) and the aromatics derived compound cis,cis-muconic acid (ccMA) can be precursors for, but are not limited to, terephthalic or/and adipic acid. These are essential feedstocks for the production of PET and nylon. The three compounds can be derived from the shikimate pathway, an anabolic pathway leading to the biosynthesis of aromatic amino acids, present in certain prokaryotes and eukaryotes, including fungi. By combination of metabolic modelling with genetic engineering, a microbial production system based on the yeast Saccharomyces cerevisiae can be designed, which effectively channels flux into the target compounds.

In order to develop a competitive bio-based process, yields, titers and rates need to be maximized. While productivity or rates in a process can be altered using genetic engineering, carbon yield, and pathway feasibility are stoichiometrically and thermodynamically predetermined. Both limitations need to be considered when designing a microbial production system.

For formation of adipic acid and precursors many bio-based routes exists. More rational than just picking one for in vivo studies rather all available biochemical pathways were examined in silico using metabolic modelling. To compare theoretical yields and reaction thermodynamics an interface that allowed network-embedded thermodynamic analysis of elementary flux modes was developed. This allowed distinguishing between thermodynamically feasible and infeasible flux distributions. Feasible maximum theoretical product carbon yields were substantially different in E. coli and S. cerevisiae metabolic models and ranged from 32% to 92%. Further, many pathways appeared to be restricted by a thermodynamic equilibrium lying on the substrate side, some even infeasible.

The only routes that deliver significant product yields and were thermodynamically favoured were shikimate pathway based. Being currently of strong scientific interest, recent implementations of these pathways in E. coli and S. cerevisiae were evaluated and strain construction strategies optimized, using the concept of constrained minimal cut-sets. Especially in S. cerevisiae a single non-obvious knock-out target allowed coupling of growth to product formation; in particular, the deletion of the pyruvate kinase reaction resulted in a minimum yield constraint of 28%.

Though unique to shikimate pathway, this strategy is transferrable to other products which are derived from chorismate and also involve the formation of pyruvate as a by-product. This applies to pHBA. With further optimizations, the strategy was applied in vivo for the production of this compound in S. cerevisiae. As the pyruvate kinase knock-out entails a growth defect on glucose, a synthetic circuit was used, which allowed conditional knock-down and activation of the determined genetic modifications and by this dynamic control of the phenotype. Thus, production could be separated from growth and it could be proven that the in silico determined genetic intervention strategy holds valid in vivo, resulting in a 1.1 mM final product titer.

Further, production of pABA from shikimate pathway in S. cerevisiae was investigated and optimized: Several alleles from different yeast strains of the genes (ABZ1 and ABZ2) for pABA formation from chorismate were screened, using a strain genetically engineered to channel flux to chorismate. ABZ1 of AWRI1631 and ABZ2 of QA23 delivered the highest pABA production. To further increase production, the impact of carbon-source on product yield was investigated in silico using metabolic modelling. It was found that combined glycerol-ethanol was a superior carbon-source than glucose, glycerol or ethanol alone, especially when employed in molar ratios between 1:2 and 2:1. This could be confirmed in vivo with carbon yields reaching up to 2.64%. A fed-batch process on glycerol-ethanol delivered total aromatics titers as high as 1.73 mM.

It could be shown that feasibility and viability of adipic acid production greatly depends on the pathway and the organism chosen for engineering. Weaknesses of existing strain construction strategies for ccMA production could be identified and a radical optimization strategy was determined.

Inferences from metabolic modelling were proven experimentally for pHBA and pABA production. The obtained concentrations and yields are the highest in S. cerevisiae to date and among the highest in a microbial production system, underlining th

In recent years, new methods for computational RNA design have been developed and applied to various problems in synthetic biology and nanotechnology. Lately, there is considerable interest in incorporating essential biological information when solving the inverse RNA folding problem. Correspondingly, RNAfbinv aims at including biologically meaningful constraints and is the only program to-date that performs a fragment-based design of RNA sequences. In doing so it allows the design of sequences that do not necessarily exactly fold into the target, as long as the overall coarse-grained tree graph shape is preserved. Augmented by the weighted sampling algorithm of incaRNAtion, our web server called incaRNAfbinv implements the method devised in RNAfbinv and offers an interactive environment for the inverse folding of RNA using a fragment-based design approach. It takes as input: a target RNA secondary structure; optional sequence and motif constraints; optional target minimum free energy, neutrality and GC content. In addition to the design of synthetic regulatory sequences, it can be used as a pre-processing step for the detection of novel natural occurring RNAs. The two complementary methodologies RNAfbinv and incaRNAtion are merged together and fully implemented in our web server incaRNAfbinv, available at http://www.cs.bgu.ac.il/incaRNAfbinv.

One key aspect of synthetic biology is the development and characterization of modular biological building blocks that can be assembled to construct integrated cell-based circuits performing computational functions. Likewise, the idea of extracting biological modules from the cellular context has led to the development of in vitro operating systems. This principle has attracted substantial interest to extend the repertoire of functional materials by connecting them with modules derived from synthetic biology. In this respect, synthetic biological switches and sensors, as well as biological targeting or structure modules, have been employed to upgrade functions of polymers and solid inorganic material. The resulting systems hold great promise for a variety of applications in diagnosis, tissue engineering and drug delivery. This review reflects on the most recent developments and critically discusses challenges concerning in vivo functionality and tolerance that must be addressed to allow the future translation of such synthetic biology-upgraded materials from the bench to the bedside.

In the fields of clinical diagnostics and point-of-care diagnosis as well as food and environmental monitoring there is a high demand for reliable high-throughput, rapid and highly sensitive assays for a simultaneous detection of several analytes in complex and low-volume samples. Sensor platforms based on solution-processable electrolyte-gated carbon nanotube field-effect transistors (CNT-FETs) are a simple and cost-effective alternative for conventional assays. In this work we demonstrate a selective as well as direct detection of the products of an enzyme-substrate interaction, here the for metabolic processes important urea-urease system, with sensors based on spray-coated CNT-FETs. The selective and direct detection is achieved by immobilizing the enzyme urease via certain surface functionalization techniques on the sensor surface and further modifying the active interfaces with polymeric ion-selective membranes as well as pH-sensitive layers. Thereby, we can avoid the generally applied approach for a field-effect based detection of enzyme reactions via detecting changes in the pH value due to an on-going enzymatic reaction and directly detect selectively the products of the enzymatic conversion. Thus, we can realize a buffering-capacity independent monitoring of changes in the substrate concentration.

A label-free fiber optic biosensor based on a long period grating (LPG) and a basic optical interrogation scheme using off the shelf components is used for the detection of in-situ DNA hybridization. A new methodology is proposed for the determination of the spectral position of the LPG mode resonance. The experimental limit of detection obtained for the DNA was 62±2 nM and the limit of quantification was 209±7 nM. The sample specificity was experimentally demonstrated using DNA targets with different base mismatches relatively to the probe and was found that the system has a single base mismatch selectivity.

A dopamine biosensor has been developed using nickel oxide nanoparticles (NPs) and tyrosinase enzyme conjugate. Nickel oxide (NiO) NPs were synthesized by sol–gel method using anionic surfactant, sodium dodecyl sulphate (SDS), as template to control the size of synthesized nanoparticles. The structural and morphological studies of the prepared NPs were carried out using X-ray diffraction (XRD), transmission electron microscopy (TEM) and dynamic light scattering (DLS) techniques. Afterwards, tyrosinase enzyme molecules were adsorbed on NiO NPs surface and enzyme coated NPs were deposited on indium tin oxide (ITO) coated flexible polyethylene terephthalate (PET) substrate by solution casting method. The formation of enzyme–NPs conjugate was investigated by atomic force microscopy (AFM) and Fourier transform infrared spectroscopy (FTIR) techniques and used in selective detection and estimation of neurochemical dopamine by electrochemical method. The fabricated Tyrosinase/NiO/ITO electrode exhibits high sensitivity of 60.2 nA/µM in linear detection range (2–100 μM) with a detection limit of 1.038 μM. The proposed sensor had a response time of 45 s, long shelf life (45 days) with good reproducibility and selectivity in presence of interfering substances and was validated with real samples. The tyrosinase enzyme functionalized NiO platform has good bio-sensing efficacy and can be used in detection of other catecholamines and phenolic neurochemicals.

We have developed synthetic gene networks that enable engineered cells to selectively program surface chemistry. E. coli were engineered to upregulate biotin synthase, and therefore biotin synthesis, upon biochemical induction. Additionally, two different functionalized surfaces were developed that utilized binding between biotin and streptavidin to regulate enzyme assembly on programmable surfaces. When combined, the interactions between engineered cells and surfaces demonstrated that synthetic biology can be used to engineer cells that selectively control and modify molecular assembly by exploiting surface chemistry. Our system is highly modular and has the potential to influence fields ranging from tissue engineering to drug development and delivery.

Advances in synthetic genomics are now well underway in yeasts due to the low cost of synthetic DNA. These new capabilities also bring greater need for quantitating the presence, loss and rearrangement of loci within synthetic yeast genomes. Methods for achieving this will ideally; i) be robust to industrial settings, ii) adhere to a global standard and iii) be sufficiently rapid to enable at-line monitoring during cell growth. The methylotrophic yeast Pichia pastoris (P. pastoris) is increasingly used for industrial production of biotherapeutic proteins so we sought to answer the following questions for this particular yeast species. Is time-consuming DNA purification necessary to obtain accurate end-point polymerase chain reaction (e-pPCR) and quantitative PCR (qPCR) data? Can the novel linear regression of efficiency qPCR method (LRE qPCR), which has properties desirable in a synthetic biology standard, match the accuracy of conventional qPCR? Does cell cultivation scale influence PCR performance? To answer these questions we performed e-pPCR and qPCR in the presence and absence of cellular material disrupted by a mild 30s sonication procedure. The e-pPCR limit of detection (LOD) for a genomic target locus was 50 pg (4.91x103 copies) of purified genomic DNA (gDNA) but the presence of cellular material reduced this sensitivity sixfold to 300 pg gDNA (2.95x104 copies). LRE qPCR matched the accuracy of a conventional standard curve qPCR method. The presence of material from bioreactor cultivation of up to OD600 = 80 did not significantly compromise the accuracy of LRE qPCR. We conclude that a simple and rapid cell disruption step is sufficient to render P. pastoris samples of up to OD600 = 80 amenable to analysis using LRE qPCR which we propose as a synthetic biology standard.

Networking biofabricated systems through molecular communication

Covering: 2000 to 2016Progress in synthetic biology is enabled by powerful bioinformatics tools allowing the integration of the design, build and test stages of the biological engineering cycle. In this review we illustrate how this integration can be achieved, with a particular focus on natural products discovery and production. Bioinformatics tools for the DESIGN and BUILD stages include tools for the selection, synthesis, assembly and optimization of parts (enzymes and regulatory elements), devices (pathways) and systems (chassis). TEST tools include those for screening, identification and quantification of metabolites for rapid prototyping. The main advantages and limitations of these tools as well as their interoperability capabilities are highlighted.

The first example of droplet digital PCR logic gates (“YES”, “OR” and “AND”) for Hg (II) and Ag (I) ion detection has been constructed based on two amplification events triggered by a metal-ion-mediated base mispairing (T-Hg(II)-T and C-Ag(I)-C). In this work, Hg(II) and Ag(I) were used as the input, and the “true” hierarchical colors or “false” green were the output. Through accurate molecular recognition and high sensitivity amplification, positive droplets were generated by droplet digital PCR and viewed as the basis of hierarchical digital signals. Based on this principle, YES gate for Hg(II) (or Ag(I)) detection, OR gate for Hg(II) or Ag(I) detection and AND gate for Hg(II) and Ag(I) detection were developed, and their sensitively and selectivity were reported. The results indicate that the ddPCR logic system developed based on the different indicators for Hg(II) and Ag(I) ions provides a useful strategy for developing advanced detection methods, which are promising for multiplex metal ion analysis and intelligent DNA calculator design applications.

This paper describes a novel, simple, and disposable immunosensor based on indium-tin oxide (ITO) sheets modified with gold nanoparticles to sensitively analyze heat shock protein 70 (HSP70), a potential biomarker that could be evaluated in diagnosis of some carcinomas. Disposable ITO coated Polyethylene terephthalate (PET) electrodes were used and modified with gold nanoparticles in order to construct the biosensors. Optimization and characterization steps were analyzed by electrochemical techniques such as electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). Surface morphology of the biosensor was also identified by electrochemical methods, scanning electron microscopy (SEM), and atomic force microscopy (AFM). To interpret binding characterization of HSP70 to anti-HSP70 single frequency impedance method was successfully operated. Moreover, the proposed HSP70 immunosensor acquired good stability, repeatability, and reproducibility. Ultimately, proposed biosensor was introduced to real human serum samples to determine HSP70 sensitively and accurately.

An advanced optical biosensor was developed based on the enzymatic reaction with halogenated aliphatic hydrocarbons that is accompanied by the fluorescence change of pH indicator. The device is applicable for the detection of halogenated contaminants in water samples with pH ranging from 4 to 10 and temperature ranging from 5 to 60 °C. Main advantages of the developed biosensor are small size (60×30×190 mm3) and portability, which together with short measurement time of 1 min belong to crucial attributes of analytical technique useful for routine environmental monitoring. The biosensor was successfully applied for the detection of several important halogenated pollutants under laboratory conditions, e.g., 1,2-dichloroethane, 1,2,3-trichloropropane and γ-hexachlorocyclohexane, with the limits of detection of 2.7, 1.4 and 12.1 mg L−1, respectively. The continuous monitoring was demonstrated by repetitive injection of halogenated compound into measurement solution. Consequently, field trials under environmental settings were performed. The presence of 1,2-dichloroethane (10 mg L−1) was proved unambiguously on one of three potentially contaminated sites in Czech Republic, and the same contaminant was monitored on contaminated locality in Serbia. Equipped by Global Positioning System, the biosensor was used for creation of a precise map of contamination. Concentrations determined by biosensor and by gas chromatograph coupled with mass spectrometer exhibited the correlation coefficient of 0.92, providing a good confidence for the routine use of the biosensor system in both field screening and monitoring.