Engineering of a robust Escherichia coli chassis and exploitation for large-scale production processes.

In large-scale bioprocesses microbes are exposed to heterogeneous substrate availability reducing the overall process performance. A series of deletion strains was constructed from E. coli MG1655 aiming for a robust phenotype in heterogeneous fermentations with transient starvation. Deletion targets were hand-picked based on a list of genes derived from previous large-scale simulation runs. Each gene deletion was conducted on the premise of strict neutrality towards growth parameters in glucose minimal medium. The final strain of the series, named E. coli RM214, was cultivated continuously in an STR-PFR (stirred tank reactor - plug flow reactor) scale-down reactor. The scale-down reactor system simulated repeated passages through a glucose starvation zone. When exposed to nutrient gradients, E. coli RM214 had a significantly lower maintenance coefficient than E. coli MG1655 (Δms = 0.038 gGlucose/gCDW/h, p < 0.05). In an exemplary protein production scenario E. coli RM214 remained significantly more productive than E. coli MG1655 reaching 44% higher eGFP yield after 28 h of STR-PFR cultivation. This study developed E. coli RM214 as a robust chassis strain and demonstrated the feasibility of engineering microbial hosts for large-scale applications.

The sRNA NsiR4 is involved in nitrogen assimilation control in cyanobacteria by targeting glutamine synthetase inactivating factor IF7.

Glutamine synthetase (GS), a key enzyme in biological nitrogen assimilation, is regulated in multiple ways in response to varying nitrogen sources and levels. Here we show a small regulatory RNA, NsiR4 (nitrogen stress-induced RNA 4), which plays an important role in the regulation of GS in cyanobacteria. NsiR4 expression in the unicellular Synechocystis sp. PCC 6803 and in the filamentous, nitrogen-fixing Anabaena sp. PCC 7120 is stimulated through nitrogen limitation via NtcA, the global transcriptional regulator of genes involved in nitrogen metabolism. NsiR4 is widely conserved throughout the cyanobacterial phylum, suggesting a conserved function. In silico target prediction, transcriptome profiling on pulse overexpression, and site-directed mutagenesis experiments using a heterologous reporter system showed that NsiR4 interacts with the 5'UTR of gifA mRNA, which encodes glutamine synthetase inactivating factor (IF)7. In Synechocystis, we observed an inverse relationship between the levels of NsiR4 and the accumulation of IF7 in vivo. This NsiR4-dependent modulation of gifA (IF7) mRNA accumulation influenced the glutamine pool and thus [Formula: see text] assimilation via GS. As a second target, we identified ssr1528, a hitherto uncharacterized nitrogen-regulated gene. Competition experiments between WT and an ΔnsiR4 KO mutant showed that the lack of NsiR4 led to decreased acclimation capabilities of Synechocystis toward oscillating nitrogen levels. These results suggest a role for NsiR4 in the regulation of nitrogen metabolism in cyanobacteria, especially for the adaptation to rapid changes in available nitrogen sources and concentrations. NsiR4 is, to our knowledge, the first identified bacterial sRNA regulating the primary assimilation of a macronutrient.

Convolutional neural network and level-set spectral element method for ultrasonic imaging of delamination cavities in an anisotropic composite structure.

We present a computational approach that incorporates a convolutional neural network (CNN) for detecting internal delamination in a layered 2D plane-strain anisotropic composite structure of transient elastodynamic fields. The two-dimensional spectral element method (SEM) is utilized to simulate the propagation of elastic waves in an orthotropic solid sandwiched by isotropic solids and their interaction with the internal delamination cavity. This work generates training data consisting of input-layer features (i.e., measured wave signals) and output-layer features (i.e., element types, such as void or regular, of all elements in a domain). To accelerate training data generation, we utilize explicit time integration (e.g., the Runge-Kutta scheme) coupled with an SEM wave solver. Applying the level-set method additionally avoids having to perform an expensive re-meshing process for every possible configuration of the delamination cavities during the data-generation phase. The CNN is trained to classify each element as a non-void or void element from the measured wave signals. Clusters of identified void elements reconstruct targeted cavities. Once our neural network is trained using synthetic data, we analyze how effectively the CNN performs on synthetic measurement data. To this end, we use blind test data from a third-party simulator that explicitly models the traction-free boundary of cavities for anisotropic materials without the application of the level-set method. Our numerical examples show that our approach can effectively detect the internal cavities in an anisotropic structure made of aluminum and carbon fiber-reinforced epoxy using the measured elastic waves without any prior information about the cavities' locations, shapes, and numbers. The presented method can be extended into a more realistic 3D setting and utilized for the nondestructive test of various anisotropic composite structures.

Inverse modeling and experimental validation for reconstructing wave sources on a 2D solid from surficial measurement.

This paper discusses a source inversion method for the reconstruction of moving or stationary wave sources on the top surface of a two-dimensional (2D) linear elastic solid. This adjoint-gradient-based source inversion method uses vibrational measurements from sensors at the top surface of the solid, which can be heterogeneous and damped, to reconstruct temporal and spatial distributions of the wave sources. The finite element method (FEM) is used to obtain wave solutions with the high-resolution discretization of source functions in space and time leading the number of inversion parameters to range in the millions. Numerical experiments, in which the iterative inversion procedure begins with an initial guess of zero loading at all points in space and time, show that the presented approach is effective at reconstructing horizontal and vertical components of force (i.e., normal and shear tractions) for multiple simultaneous moving dynamic distributed loads without any prior knowledge about the loads except that all loading is applied along the top surface of the solid. Provided that moving loads on roadways are applied to the top surface, it is shown that updating the guessed loading at just surface nodes, rather than at all nodes in space, greatly improves the inversion results. The inversion is shown to be as effective at reconstructing loads on the top surface of a solid when the solid is horizontally layered with multiple materials as when the solid it is homogeneous. Reducing the distance between sensors improves the accuracy of the inversion while reducing the width of distributed loads leads to less accurate results. The authors also validate the presented inversion method by using experimental data obtained from lab-scale tests at a high frequency (100 kHz) for a stationary load on a homogeneous solid.

Lamb wave-based mapping of plate structures via frontier exploration.

Substantial improvements in material processing and manufacturing techniques in recent years necessitate the introduction of effective and efficient nondestructive testing (NDT) methods that can seamlessly integrate into day-to-day aircraft and aerospace operations. Lamb wave-based methods have been identified as one of the most promising candidates for the inspection of large-scale structures. At the same time, there is presently a high level of research in the field of autonomous mobile robotics, especially in simultaneous localization and mapping (SLAM). Thus, this paper investigates a means to automate Lamb wave-based NDT by positioning sensors along a planar structure through mobile service robots. To this end, a generalized method for the mapping of plate structures using scattered Lamb waves by means of frontier exploration is presented such that an autonomous SLAM-capable NDT system can become realizable. The performance of this novel Lamb wave-based frontier exploration is first evaluated in simulation. It is shown that it generally outperforms a random frontier exploration and may even perform near-optimal in the case of an isotropic, square panel. These findings are then validated in laboratory experiments, confirming the general feasibility of utilizing Lamb waves for SLAM. Furthermore, the versatility of the developed methodology is successfully demonstrated on a more complexly shaped stiffened panel.

Semi-analytical modeling of anchor loss in plate-mounted resonators.

A semi-analytical technique for estimating the energy loss in a resonator mounted to an infinite plate substrate is proposed in this paper. In a plate, only Lamb waves have to be considered, leading to a simplified characterization of the energy carried away from a vibrating source on the plate surface. Instead of employing absorbing elements at the boundaries of the plate-resonator finite element model, it is shown how the semi-analytical approach of stitching together analytical Lamb wave expressions to the finite element model can be utilized. The approach is demonstrated for single and double cantilever configurations on a plate. The results have excellent agreement with those of conventional transient finite element simulations.

RNA interactomics: recent advances and remaining challenges.

Tight regulation of cellular processes is key to the development of complex organisms but also vital for simpler ones. During evolution, different regulatory systems have emerged, among them RNA-based regulation that is carried out mainly by intramolecular and intermolecular RNA-RNA interactions. However, methods for the transcriptome-wide detection of these interactions were long unavailable. Recently, three publications described high-throughput methods to directly detect RNA duplexes in living cells. This promises to enable in-depth studies of RNA-based regulation and will narrow the gaps in our understanding of RNA structure and function. In this review, we highlight the benefits of these methods and their commonalities and differences and, in particular, point to methodological shortcomings that hamper their wider application. We conclude by presenting ideas for how to overcome these problems and commenting on the prospects we see in this area of research.

Dispersion of Lamb waves in a honeycomb composite sandwich panel.

Composite materials are increasingly being used in advanced aircraft and aerospace structures. Despite their many advantages, composites are often susceptible to hidden damages that may occur during manufacturing and/or service of the structure. Therefore, safe operation of composite structures requires careful monitoring of the initiation and growth of such defects. Ultrasonic methods using guided waves offer a reliable and cost effective method for defects monitoring in advanced structures due to their long propagation range and their sensitivity to defects in their propagation path. In this paper, some of the useful properties of guided Lamb type waves are investigated, using analytical, numerical and experimental methods, in an effort to provide the knowledge base required for the development of viable structural health monitoring systems for composite structures. The laboratory experiments involve a pitch-catch method in which a pair of movable transducers is placed on the outside surface of the structure for generating and recording the wave signals. The specific cases considered include an aluminum plate, a woven composite laminate and an aluminum honeycomb sandwich panel. The agreement between experimental, numerical and theoretical results are shown to be excellent in certain frequency ranges, providing a guidance for the design of effective inspection systems.