117 research outputs found

    Synthetic biology—putting engineering into biology

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    Synthetic biology is interpreted as the engineering-driven building of increasingly complex biological entities for novel applications. Encouraged by progress in the design of artificial gene networks, de novo DNA synthesis and protein engineering, we review the case for this emerging discipline. Key aspects of an engineering approach are purpose-orientation, deep insight into the underlying scientific principles, a hierarchy of abstraction including suitable interfaces between and within the levels of the hierarchy, standardization and the separation of design and fabrication. Synthetic biology investigates possibilities to implement these requirements into the process of engineering biological systems. This is illustrated on the DNA level by the implementation of engineering-inspired artificial operations such as toggle switching, oscillating or production of spatial patterns. On the protein level, the functionally self-contained domain structure of a number of proteins suggests possibilities for essentially Lego-like recombination which can be exploited for reprogramming DNA binding domain specificities or signaling pathways. Alternatively, computational design emerges to rationally reprogram enzyme function. Finally, the increasing facility of de novo DNA synthesis—synthetic biology’s system fabrication process—supplies the possibility to implement novel designs for ever more complex systems. Some of these elements have merged to realize the first tangible synthetic biology applications in the area of manufacturing of pharmaceutical compounds.

    Synthetic biology—putting engineering into biology

    Get PDF
    Synthetic biology is interpreted as the engineering-driven building of increasingly complex biological entities for novel applications. Encouraged by progress in the design of artificial gene networks, de novo DNA synthesis and protein engineering, we review the case for this emerging discipline. Key aspects of an engineering approach are purpose-orientation, deep insight into the underlying scientific principles, a hierarchy of abstraction including suitable interfaces between and within the levels of the hierarchy, standardization and the separation of design and fabrication. Synthetic biology investigates possibilities to implement these requirements into the process of engineering biological systems. This is illustrated on the DNA level by the implementation of engineering-inspired artificial operations such as toggle switching, oscillating or production of spatial patterns. On the protein level, the functionally self-contained domain structure of a number of proteins suggests possibilities for essentially Lego-like recombination which can be exploited for reprogramming DNA binding domain specificities or signaling pathways. Alternatively, computational design emerges to rationally reprogram enzyme function. Finally, the increasing facility of de novo DNA synthesis—synthetic biology's system fabrication process—supplies the possibility to implement novel designs for ever more complex systems. Some of these elements have merged to realize the first tangible synthetic biology applications in the area of manufacturing of pharmaceutical compounds. Contact: [email protected]

    In Silico Genome-Scale Reconstruction and Validation of the Staphylococcus aureus Metabolic Network

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    A genome-scale metabolic model of the Gram-positive, facultative anaerobic opportunistic pathogen Staphylococcus aureus N315 was constructed based on current genomic data, literature, and physiological information. The model comprises 774 metabolic processes representing approximately 23% of all protein-coding regions. The model was extensively validated against experimental observations and it correctly predicted main physiological properties of the wild-type strain, such as aerobic and anaerobic respiration and fermentation. Due to the frequent involvement of S. aureus in hospital-acquired bacterial infections combined with its increasing antibiotic resistance, we also investigated the clinically relevant phenotype of small colony variants and found that the model predictions agreed with recent findings of proteome analyses. This indicates that the model is useful in assisting future experiments to elucidate the interrelationship of bacterial metabolism and resistance. To help directing future studies for novel chemotherapeutic targets, we conducted a large-scale in silico gene deletion study that identified 158 essential intracellular reactions. A more detailed analysis showed that the biosynthesis of glycans and lipids is rather rigid with respect to circumventing gene deletions, which should make these areas particularly interesting for antibiotic development. The combination of this stoichiometric model with transcriptomic and proteomic data should allow a new quality in the analysis of clinically relevant organisms and a more rationalized system-level search for novel drug targets.

    In situ Product Recovery Integrated with Biotransformations

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    Biocatalysis constitutes an effective tool for the production of fine chemicals. In order to widen the spectrum of applicable reaction types to reactions that are constrained by inhibitions, product toxicity, or degradation, an unfavorable position of the thermodynamic equilibrium, or by kinetic control, in situ product removal (ISPR) is an attractive process option to overcome those limitations. To fully exploit the benefits of the ISPR approach, selective removal of the product to an auxiliary phase with high capacity is usually required. Obviously, such an operation becomes increasingly difficult with decreasing differences in the physical properties of substrate(s) and product(s) as it is arguably frequently the case with biotransformations. In this paper we analyze the possibilities to apply ISPR to biotransformations and identify the most promising developments supported by simple model considerations to fully exploit the potential of ISPR

    Development of a fermentation process based on a defined medium for the production of pregallidermin, a nontoxic precursor of the lantibiotic gallidermin

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    In this work, a defined medium was developed and optimized for the mutant strain Staphylococcusgallinarum ΔP, which produces pregallidermin (PGDM), a nontoxic precursor of the lantibiotic gallidermin (GDM). The availability of a defined medium is a prerequisite for a rational process development and the investigation of medium effects on final product concentration, yield, and volumetric productivity. We identified four vitamins and three metal ions as essential for growth and PGDM production with S. gallinarum ΔP. The strain was capable of growing without any added amino acids, but the addition of proline had a strong growth-stimulatory effect. The concentrations of all essential compounds were balanced in a continuous culture using a medium-shift technique. Based on this balanced medium, a fed-batch process was developed in which S. gallinarum ΔP was grown up to a biomass concentration of 67gl−1 and produced 1.95gl−1 PGDM, equivalent to 0.57mM. In the fermentation broth, we identified other GDM precursors in addition to those with a 12 or 14-amino-acid-long leader peptide that had been observed previously. Including those precursors with shorter leader sequences, the final concentration would correspond to 0.69mM. In molar terms, this represents a roughly fourfold or fivefold increase, respectively, over established, complex medium-based gallidermin production processes (Kempf et al. 2000). With the same medium and feed protocol, the maximum concentration of mature GDM produced by wild-type S. gallinarum TĂŒ 3928 was only 0.08m

    A reduction in growth rate of Pseudomonas putida KT2442 counteracts productivity advances in medium-chain-length polyhydroxyalkanoate production from gluconate

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    <p>Abstract</p> <p>Background</p> <p>The substitution of plastics based on fossil raw material by biodegradable plastics produced from renewable resources is of crucial importance in a context of oil scarcity and overflowing plastic landfills. One of the most promising organisms for the manufacturing of medium-chain-length polyhydroxyalkanoates (mcl-PHA) is <it>Pseudomonas putida </it>KT2440 which can accumulate large amounts of polymer from cheap substrates such as glucose. Current research focuses on enhancing the strain production capacity and synthesizing polymers with novel material properties. Many of the corresponding protocols for strain engineering rely on the rifampicin-resistant variant, <it>P. putida </it>KT2442. However, it remains unclear whether these two strains can be treated as equivalent in terms of mcl-PHA production, as the underlying antibiotic resistance mechanism involves a modification in the RNA polymerase and thus has ample potential for interfering with global transcription.</p> <p>Results</p> <p>To assess PHA production in <it>P. putida </it>KT2440 and KT2442, we characterized the growth and PHA accumulation on three categories of substrate: PHA-related (octanoate), PHA-unrelated (gluconate) and poor PHA substrate (citrate). The strains showed clear differences of growth rate on gluconate and citrate (reduction for KT2442 > 3-fold and > 1.5-fold, respectively) but not on octanoate. In addition, <it>P</it>. <it>putida </it>KT2442 PHA-free biomass significantly decreased after nitrogen depletion on gluconate. In an attempt to narrow down the range of possible reasons for this different behavior, the uptake of gluconate and extracellular release of the oxidized product 2-ketogluconate were measured. The results suggested that the reason has to be an inefficient transport or metabolization of 2-ketogluconate while an alteration of gluconate uptake and conversion to 2-ketogluconate could be excluded.</p> <p>Conclusions</p> <p>The study illustrates that the recruitment of a pleiotropic mutation, whose effects might reach deep into physiological regulation, effectively makes <it>P. putida </it>KT2440 and KT2442 two different strains in terms of mcl-PHA production. The differences include the onset of mcl-PHA production (nitrogen limitation) and the resulting strain performance (growth rate). It remains difficult to predict a priori<it/>where such major changes might occur, as illustrated by the comparable behavior on octanoate. Consequently, experimental data on mcl-PHA production acquired for <it>P. putida </it>KT2442 cannot always be extrapolated to KT2440 and vice versa, which potentially reduces the body of available knowledge for each of these two model strains for mcl-PHA production substantially.</p

    Multienzymnetzwerke fĂŒr die Feinchemie

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    Zusammenfassung: Die Produktion von Feinchemikalien beruht auf Prozessen mit mehreren Reaktionsschritten. Wir arbeiten an Konzepten fĂŒr die Rekrutierung, Isolierung und Optimierung von in vitro-Enzymkaskaden aus Zellextrakten fĂŒr die Synthese von komplexen Zucker

    Pressure to kill or pressure to boost: a review on the various effects and applications of hydrostatic pressure in bacterial biotechnology

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    Much knowledge has been gained for the last 30years about the effects of pressure on bacteria, and various pressure-based technologies have been designed. The development of modern molecular biology techniques (e.g., DNA microarrays) as well as the technological advances realized in the manufacturing of robust sampling and high-pressure devices has allowed these advances. Not only the direct effects on cell components (membranes, proteins, and nucleic acids) have been unraveled, but also the cellular response to pressure has been investigated by means of transcriptome and proteome analyses. Initially, research was performed by marine biologists who studied the microorganisms living in the deep sea at pressures of 1,000bar. In parallel, food technologists developed pressure-based methods for inactivating microorganisms without altering the food properties as much as with temperature treatment. The preservation of specific product properties is also the rationale for pressure-based methods for the disinfection of biomaterials and for vaccine production. Therefore, attention was first focused on the "killing” potential of high pressure. On the other hand, there has been a growing interest in using elevated pressures (up to ~10bar) for enhancing the productivity of bioprocesses. In this case, no killing effect was sought, but pressure was applied to "boost” the process by enhancing the oxygen transfer to the cell culture. This paper gives an overview on the effects of pressures in the range of 1bar to 10kbar on bacteria and presents the major and most recent achievements realized in the development of pressure-based biotechnological application

    Chemical and enzymatic routes to dihydroxyacetone phosphate

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    Stereoselective carbon-carbon bond formation with aldolases has become an indispensable tool in preparative synthetic chemistry. In particular, the dihydroxyacetone phosphate (DHAP)-dependent aldolases are attractive because four different types are available that allow access to a complete set of diastereomers of vicinal diols from achiral aldehyde acceptors and the DHAP donor substrate. While the substrate specificity for the acceptor is rather relaxed, these enzymes show only very limited tolerance for substituting the donor. Therefore, access to DHAP is instrumental for the preparative exploitation of these enzymes, and several routes for its synthesis have become available. DHAP is unstable, so chemical synthetic routes have concentrated on producing a storable precursor that can easily be converted to DHAP immediately before its use. Enzymatic routes have concentrated on integrating the DHAP formation with upstream or downstream catalytic steps, leading to multi-enzyme arrangements with up to seven enzymes operating simultaneously. While the various chemical routes suffer from either low yields, complicated work-up, or toxic reagents or catalysts, the enzymatic routes suffer from complex product mixtures and the need to assemble multiple enzymes into one reaction scheme. Both types of routes will require further improvement to serve as a basis for a scalable route to DHA

    Systematic assignment of thermodynamic constraints in metabolic network models

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    BACKGROUND: The availability of genome sequences for many organisms enabled the reconstruction of several genome-scale metabolic network models. Currently, significant efforts are put into the automated reconstruction of such models. For this, several computational tools have been developed that particularly assist in identifying and compiling the organism-specific lists of metabolic reactions. In contrast, the last step of the model reconstruction process, which is the definition of the thermodynamic constraints in terms of reaction directionalities, still needs to be done manually. No computational method exists that allows for an automated and systematic assignment of reaction directions in genome-scale models. RESULTS: We present an algorithm that – based on thermodynamics, network topology and heuristic rules – automatically assigns reaction directions in metabolic models such that the reaction network is thermodynamically feasible with respect to the production of energy equivalents. It first exploits all available experimentally derived Gibbs energies of formation to identify irreversible reactions. As these thermodynamic data are not available for all metabolites, in a next step, further reaction directions are assigned on the basis of network topology considerations and thermodynamics-based heuristic rules. Briefly, the algorithm identifies reaction subsets from the metabolic network that are able to convert low-energy co-substrates into their high-energy counterparts and thus net produce energy. Our algorithm aims at disabling such thermodynamically infeasible cyclic operation of reaction subnetworks by assigning reaction directions based on a set of thermodynamics-derived heuristic rules. We demonstrate our algorithm on a genome-scale metabolic model of E. coli. The introduced systematic direction assignment yielded 130 irreversible reactions (out of 920 total reactions), which corresponds to about 70% of all irreversible reactions that are required to disable thermodynamically infeasible energy production. CONCLUSION: Although not being fully comprehensive, our algorithm for systematic reaction direction assignment could define a significant number of irreversible reactions automatically with low computational effort. We envision that the presented algorithm is a valuable part of a computational framework that assists the automated reconstruction of genome-scale metabolic models
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