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Cupriavidus necator H16 gains increasing attention in microbial research and biotechnological application due to its diverse metabolic features. Here we present a tightly controlled gene expression system for C. necator including the pBBR1-vector that contains hybrid promoters originating from C. necator native tolC-promoter in combination with a synthetic tetO-operator. The expression of the reporter gene from these plasmids relies on the addition of the exogenous inducer doxycycline (dc). The novel expression system offers a combination of advantageous features as; (i) high and dose-dependent recombinant protein production, (ii) tight control with a high dynamic range (On/Off ratio), which makes it applicable for harmful pathways or for toxic protein production, (iii) comparable cheap inducer (doxycycline, dc), (iv) effective at low inducer concentration, that makes it useful for large scale application, (v) rapid, diffusion controlled induction, and (vi) the inducer does not interfere within the cell metabolism. As applications of the expression system in C. necator H16, the growth ability on glycerol was enhanced by constitutively expressing the E. coli glpk gene-encoding for glycerol kinase. Likewise, we used the system to overcome the expression toxicity of mevalonate pathway in C. necator H16. With this system, the mevalonate-genes were successfully introduced in the host and the recombinant strains could produce about 200 mg/l mevalonate.
We present new numerical results for shape optimization problems of interior Neumann eigenvalues. This field is not well understood from a theoretical standpoint. The existence of shape maximizers is not proven beyond the first two eigenvalues, so we study the problem numerically. We describe a method to compute the eigenvalues for a given shape that combines the boundary element method with an algorithm for nonlinear eigenvalues. As numerical optimization requires many such evaluations, we put a focus on the efficiency of the method and the implemented routine. The method is well suited for parallelization. Using the resulting fast routines and a specialized parametrization of the shapes, we found improved maxima for several eigenvalues.
Three-dimensional (3D) full-field measurements provide a comprehensive and accurate validation of finite element (FE) models. For the validation, the result of the model and measurements are compared based on two respective point-sets and this requires the point-sets to be registered in one coordinate system. Point-set registration is a non-convex optimization problem that has widely been solved by the ordinary iterative closest point algorithm. However, this approach necessitates a good initialization without which it easily returns a local optimum, i.e. an erroneous registration. The globally optimal iterative closest point (Go-ICP) algorithm has overcome this drawback and forms the basis for the presented open-source tool that can be used for the validation of FE models using 3D full-field measurements. The capability of the tool is demonstrated using an application example from the field of biomechanics. Methodological problems that arise in real-world data and the respective implemented solution approaches are discussed.