Systems and Synthetic Biology最新文献

Pichia pastoris is an efficient expression system for production of recombinant proteins. To understand its physiology for building novel applications it is important to understand and reconstruct its metabolic network. The metabolic reconstruction approach connects genotype with phenotype. Here, we have attempted to reconstruct carbohydrate metabolism pathways responsible for high biomass density and N-glycosylation pathways involved in the post translational modification of proteins of P. pastoris CBS7435. Both these metabolic pathways play a crucial role in heterologous protein production. We report novel, missing and unannotated enzymes involved in the target metabolic pathways. A strong possibility of cellulose and xylose metabolic processes in P. pastoris CBS7435 suggests its use in the area of biofuels. The reconstructed metabolic networks can be used for increased yields and improved product quality, for designing appropriate growth medium, for production of recombinant therapeutics and for making biofuels.

Synthetic biology is often presented as a promissory field that ambitions to produce novelty by design. The ultimate promise is the production of living systems that will perform new and desired functions in predictable ways. Nevertheless, realizing promises of novelty has not proven to be a straightforward endeavour. This paper provides an overview of, and explores the existing debates on, the possibility of designing living systems de novo as they appear in interdisciplinary talks between engineering and biological views within the field of synthetic biology. To broaden such interdisciplinary debates, we include the views from the social sciences and the humanities and we point to some fundamental sources of disagreement within the field. Different views co-exist, sometimes as controversial tensions, but sometimes also pointing to integration in the form of intermediate positions. As the field is emerging, multiple choices are possible. They will inform alternative trajectories in synthetic biology and will certainly shape its future. What direction is best is to be decided in reflexive and socially robust ways.

Biotechnological and life science innovations do not only lead to immense progress in diverse fields of natural science and technical research and thereby drive economic development, they also fundamentally affect the relationship between nature, technology and society. Taken this seriously, the ethical and societal assessment of emerging biotechnologies as for example synthetic biology is challenged not only to constrain on questions of biosafety and biosecurity but also to face the societal questions within the different fields as an interface problem of science and society. In order to map this vague and stirring field, we propose the concept of bio-objects to explore the reciprocal interaction at the interface of science and society serious as well to have the opportunity to detect possible junctions of societal discontent and unease before their appearance.

The ATP4A encodes α subunit of H(+), K(+)-ATPase that contains catalytic sites of the enzyme forming pores through cell membrane which allows the ion transport. H(+), K(+)-ATPase is a membrane bound P-type ATPase enzyme which is found on the surface of parietal cells and uses the energy derived from each cycle of ATP hydrolysis that can help in exchanging ions (H(+), K(+) and Cl(-)) across the cell membrane secreting acid into the gastric lumen. The 3-D model of α-subunit of H(+), K(+)-ATPase was generated by homology modeling. It was evaluated and validated on the basis of free energies and amino acid residues. The inhibitor binding amino acid active pockets were identified in the 3-D model by molecular docking. The two drugs Omeprazole and Rabeprazole were found more potent interactions with generated model of α-subunit of H(+), K(+)-ATPase on the basis of their affinity between drug-protein interactions. We have generated ATP4A gene regulatory networks for interactions with other proteins which involved in regulation that can help in fine-tuning of proton pump and ion channels. These findings provide a new dimension for discovery and development of proton pump inhibitors and gene regulation of the ATPase. It can be helpful in better understanding of human physiology and also using synthetic biology strategy for reprogramming of parietal cells for control of gastric ulcers.

Quorum sensing (QS) is a process which allows a population of bacteria to coordinately regulate gene expression of their entire community. Bacillus subtilis is a soil organism which uses QS to alternate between competence for DNA uptake and sporulation. We propose a model to describe the components involved in QS and to analyze reaction species involved in the regulation of QS machinery. We targeted only those QS phenotypes for which the genetic organization and molecular characterization of the components are fully elucidated. We have analyzed simulations for concentration of different species involved in competence as well as sporulation pathways at diverse time period using quantitative methods. It was observed that there is possibility of achieving different measurement from reactions taken place between species by applying irreversible Michaelis-Menten kinetic law. We obtain variation in measurement on changing parameters such as concentrations ranging from 0.3 to 50 μM in stepwise manner by setting end time in the range of 0.1-100 ms. Additionally we observe covariance between different reaction species involved in QS by fluctuating their quantities in real-time simulations. Our model mimics correctly the phenotype for competence and virulence. We concluded that time factor play major role to determine rate kinetics of diverse reaction species as compared to their concentrations and support the hypothesis of getting genetic stability while colonies are in synchronization.

A homoserine auxotroph strain of Corynebacterium glutamicum accumulates storage compound trehalose with lysine when limited by growth. Industrially lysine is produced from C. glutamicum through aspartate biosynthetic pathway, where enzymatic activity of aspartate kinase is allosterically controlled by the concerted feedback inhibition of threonine plus lysine. Ample threonine in the medium supports growth and inhibits lysine production (phenotype-I) and its complete absence leads to inhibition of growth in addition to accumulating lysine and trehalose (phenotype-II). In this work, we demonstrate that as threonine concentration becomes limiting, metabolic state of the cell shifts from maximizing growth (phenotype-I) to maximizing trehalose phenotype (phenotype-II) in a highly sensitive manner (with a Hill coefficient of 4). Trehalose formation was linked to lysine production through stoichiometry of the network. The study demonstrated that the net flux of the population was a linear combination of the two optimal phenotypic states, requiring only two experimental measurements to evaluate the flux distribution. The property of linear combination of two extreme phenotypes was robust for various medium conditions including varying batch time, initial glucose concentrations and medium osmolality.

Multicopper oxidase (MCO) is an enzyme which involves in reducing the oxygen in a four electron reduction to water with concomitant one electron oxidation of reducing the substrate. We have generated the 3-D structure of MCO by homology modeling and validated on the basis of free energy while 90.4 % amino acid residues present in allowed regions of Ramachandran plot. The screening of potential hazardous aromatic compounds for MCO was performed using molecular docking. We obtained Sulfonaphthal, Thymolphthalein, Bromocresol green and Phloretin derivatives of phenol and aromatic hydrocarbon were efficient substrates for MCO. The phylogeny of MCO reveals that other bacteria restrain the homologous gene of MCO may play an important role in biodegradation of aromatic compounds. We have demonstrated the gene regulatory network of MCO with other cellular proteins which play a key role in gene regulation. These findings provide a new insight for oxidization of phenolic and aromatic compounds using biodegradation process for controlling environmental pollution.

Building on the linear matrix inequality (LMI) formulation developed recently by Zavlanos et al. (Automatica: Special Issue Syst Biol 47(6):1113-1122, 2011), we present a theoretical framework and algorithms to derive a class of ordinary differential equation (ODE) models of gene regulatory networks using literature curated data and microarray data. The solution proposed by Zavlanos et al. (Automatica: Special Issue Syst Biol 47(6):1113-1122, 2011) requires that the microarray data be obtained as the outcome of a series of controlled experiments in which the network is perturbed by over-expressing one gene at a time. We note that this constraint may be relaxed for some applications and, in addition, demonstrate how the conservatism in these algorithms may be reduced by using the Perron-Frobenius diagonal dominance conditions as the stability constraints. Due to the LMI formulation, it follows that the bounded real lemma may easily be used to make use of additional information. We present case studies that illustrate how these algorithms can be used on datasets to derive ODE models of the underlying regulatory networks.

Synthetic Biology is a singular, revolutionary scenario with a vast range of practical applications but, is SB research really based on engineering principles? Is it contributing to the artificial synthesis of life or using approaches "sophisticated" enough to fall outside the scope of biotechnology or metabolic engineering? We have reviewed the state of the art on synthetic biology and we conclude that most research projects actually describe an extension of metabolic engineering. We draw this conclusion because the complexity of living organisms, their tight dependence on evolution and our limited knowledge of the interactions between the molecules they are made of, actually make life difficult to engineer. We therefore propose the term synthetic biology should be used more sparingly.

The goal of this work is to optimize production of bio-ethanol by fermentation through regulating yeast growth energy (YGE), and provide the mechanism of ethanol production from food-waste leachate (FWL) using yeast (S. cerevisiae) as inoculums to be predictable and controllable. The wide range of reduced sugar concentration (RSC) which is commonly administered from low (35 g per liter) to very high (100 g per liter) is responsible for costs increasing besides risks of FWL contamination and death of yeast cells. A mathematical model is presented to describe yeast growth energy (YGE) due to RSC doses along with predicting the amounts of ethanol yield by each dose to identify the optimum one. Simulations of the presented model showed that YGE, energy intake (EI), and their produced ethanol energy (PEE) are always balanced during fermentation process according to the law of conservation of energy. For a better fermentation rate in a continuous process and a large-scale production; YGE should be less than half of EI and more than its quarter (i.e. [Formula: see text]) which keeps the residual energy less than YGE to avoid risks of osmotic stresses or aging of cells allowing the survival of all yeast cells as long as possible to maximize ethanol production and decrease productivity costs.