Novel gnd_v2 Fusion Tag and Engineered TEV Protease Enable Efficient Production of Brazzein.

Protein solubility and purification challenges often hinder the large-scale production of valuable proteins like brazzein, a potent sweet protein with significant health benefits and commercial potential. This study introduces two novel tools to overcome protine expression and purification bottlenecks: a gnd_v2 fusion tag and an engineered Tobacco Etch Virus (TEV) protease. The gnd_v2 tag, derived from 6-phosphogluconate dehydrogenase, was engineered to improve the soluble expression of brazzein. This tag increased brazzein's solubility by four times compared to the wildtype gnd tag, marking a significant advancement in efficient brazzein production. To address the challenge of cleaving the fusion tag, we engineered a TEV protease variant with high efficiency, particularly at the glutamine residue at brazzein's P1' site - a known difficulty for wild-type TEV proteases. We achieved streamlined production of pure, functional brazzein by integrating this tailored protease cleavage with an ultrafiltration-based purification protocol. Notably, the purified brazzein demonstrated a sweetness potency approximately 2500 times that of sucrose, highlighting its potential as a high-intensity natural sweetener. While this study focused on brazzein, the gnd_v2 tag shows promise for enhancing the solubility of other challenging proteins. More broadly, this work presents a versatile toolset for the scalable production of diverse functional proteins, with significant implications for industrial applications in food and pharmaceutical domains.

MicroFPGA: An affordable FPGA platform for microscope control.

Modern microscopy relies increasingly on microscope automation to improve throughput, ensure reproducibility or observe rare events. Automation requires computer control of the important elements of the microscope. Furthermore, optical elements that are usually fixed or manually movable can be placed on electronically-controllable elements. In most cases, a central electronics board is necessary to generate the control signals they require and to communicate with the computer. For such tasks, Arduino microcontrollers are widely used due to their low cost and programming entry barrier. However, they are limiting in their performance for applications that require high-speed or multiple parallel processes. Field programmable gate arrays (FPGA) are the perfect technology for high-speed microscope control, as they are capable of processing signals in parallel and with high temporal precision. While plummeting prices made the technology available to consumers, a major hurdle remaining is the complex languages used to configure them. In this work, we used an affordable FPGA, delivered with an open-source and friendly-to-use programming language, to create a versatile microscope control platform called MicroFPGA. It is capable of synchronously triggering cameras and multiple lasers following complex patterns, as well as generating various signals used to control microscope elements such as filter wheels, servomotor stages, flip-mirrors, laser power or acousto-optic modulators. MicroFPGA is open-source and we provide online Micro-Manager, Java, Python and LabVIEW libraries, together with blueprints and tutorials.

Anisotropy in the Tensile Properties of a Selective Laser Melted Ti-5Al-5Mo-5V-1Cr-1Fe Alloy during Aging Treatment.

In this work, the anisotropic microstructure and mechanical properties of selective laser melted (SLMed) Ti-5Al-5Mo-5V-1Cr-1Fe (Ti-55511) alloy before and after aging treatment are investigated. Owing to the unique thermal gradient, the prior columnar ß grains with {001} texture component grow in the building direction, and the mechanical properties of the as-fabricated Ti-55511 alloy exhibit slight anisotropy. Aging treatment creates uniform precipitation of the α phase at the boundaries as well as the interior of ß grains. Due to the microstructure of the aged samples with a weak texture, the mechanical properties exhibit almost isotropic characteristics with an ultimate tensile strength of 1133 to 1166 MPa, yield strength of 1093 to 1123 MPa, and elongation from 13 to 16%, which meet the aerospace allowable specification very well. By XRD and EBSD analyses, the total dislocation density of the aged samples (~134.8 × 1013 m-2) is significantly lower than that of the as-fabricated samples (~259.4 × 1013 m-2); however, the aged samples exhibit a higher geometrically necessary dislocation (GND) density (~28.5 × 1013 m-2) compared with the as-fabricated samples GND density (~2.9 × 1013 m-2). Thus, a new approach to strengthening theory for estimating the anisotropic mechanical properties of AM alloys is proposed.

Revealing geometrically necessary dislocation density from electron backscatter patterns via multi-modal deep learning.

The characterization of geometrically necessary dislocation (GND) is central to understanding the plastic deformation in materials. Currently, fast and accurate determination of GND density via Electron Backscatter Diffraction (EBSD) remains a challenge. Here, a multi-modal deep learning approach is proposed to predict GND density in terms of electron backscatter patterns (EBSPs) and dislocation configurations. The proposed multi-modal architecture consists of two separated convolutional neural network (CNN) processing streams. One CNN stream aims at extracting pattern shifts from EBSPs, and the other CNN stream focuses on learning suitable representations of dislocation configurations. We also introduce a specific data augmentation strategy termed neighboring pairs generating strategy for the GND prediction task. Taking the GND density from dictionary indexing-based analysis as the target property, high accuracy is achieved on several aluminum samples. Also, our networks are robust to various forms of noise, and the prediction speed is as fast as modern EBSD scanning rates, enabling real-time GND density analysis possible.

Insights into tribofilm formation on Ti-6V-4Al in a bioactive environment: Correlation between surface modification and micro-mechanical properties.

Ti-6Al-4V has been used as a surgical implant material for a long time because of its combination of strength, corrosion resistance and biocompatibility. However, there remains much that is not understood about how the surface reacts with the environment under tribocorrosion conditions. In particular, the conditions under which tribofilms form and their role on friction and wear are not clear. To evaluate the complicated nature of the dynamic surface microstructural changes on the wear track, high resolution transmission electron microscopy (TEM), scanning transmission electron microscope (STEM) and electron energy loss spectroscopy (EELS) have been used to characterise the structure and chemical composition of the tribofilm. Detailed analysis of the formation and structure of the tribofilm and the metal surface deformation behaviour were studied as a function of applied potential and the role of proteins in the lubricant. For the first time, graphitic and onion-like carbon structures from wear debris were found in the testing solution. The presence of carbon nanostructures in the tribocorrosion process and the formation of the tribofilm leads to an improved tribocorrosion behaviour of the system, in particular a reduction in wear and friction. A detailed, quantitative, analysis of surface deformation was undertaken, in particular, the geometrically necessary dislocation (GND) density was quantified using precession electron diffraction (PET). A clear correlation between applied potential, tribofilm formation and the surface strain was established. STATEMENT OF SIGNIFICANCE: The formation of tribofilm and microstructure modification of the Ti-6Al-4V surface during tribocorrosion in a physiological environment is not fully understood. In particular, the correlation between microstructural changes and electrochemical conditions is not clear. This study presents a detailed investigation of the structure and chemical composition of tribofilms at the nanoscale during tribocorrosion tests in simulated body fluid and gives a detailed and quantitative description of the evolved surface structure. A clear correlation between applied potential, tribofilm formation and the surface strain was established. Moreover, particular attention is paid to the wear debris particles captured from the lubricating solution, including nanocarbon onion structures. The implications for tribocorrosion of the alloy in its performance as an implant are discussed.

A single-gene approach for the subspecies classification of Mycobacteroides abscessus.

The subspecies classification of Mycobacteroides abscessus complex into M. abscessus, M. massiliense and M. bolletii requires the amplification and sequencing of multiple genes. The objective of this study was to evaluate the possibility of subspecies classification using a single PCR target. An in silico study was performed to classify 1613 strains deposited in a public database using 9 genes (partial gene sequences of hsp65, rpoB, sodA, argH, cya, glpK, gnd, and murC, and the full gene sequence of MAB_3542c). We found the housekeeping gene gnd to be able to classify the M. abscessus subspecies with high accuracy (99.94%). A single-gene PCR approach based on gnd would be a suitable replacement for the more expensive, labor-intensive and time-consuming multi-gene PCR analysis currently in use for the subspecies identification of M. abscessus.

Effective production of succinic acid from coconut water (Cocos nucifera) by metabolically engineered Escherichia coli with overexpression of Bacillus subtilis pyruvate carboxylase.

Succinic acid is an important acid which is used in medicine and pharmaceutical companies. Metabolically engineered Escherichia coli strain was used for the effective production of succinic acid using Cocos nucifera water, which contained 5.00 ± 0.02 g/L glucose, 6.10 ± 0.01 g /L fructose and 6.70 ± 0.02 g /L sucrose. Fermentation of C. nucifera water with E. coli M6PM produced a final concentration of 11.78 ± 0.02 g/L succinic acid and yield of 1.23 ± 0.01 mol/mol, 0.66 ± 0.01 g/g total sugars after 72 h dual-phase fermentation in M9 medium while modeled sugar was 0.38 ± 0.02 mol/mol total sugars. It resulted in 72% of the maximum theoretical yield of succinic acid. Here we show that novel substrate of C. nucifera water resulted in effective production of succinic acid. These investigations unveil the importance of C. nucifera water as a substrate for the production of biochemicals.

A Class of Rate-Independent Lower-Order Gradient Plasticity Theories: Implementation and Application to Disc Torsion Problem.

As the characteristic scale of products and production processes decreases, the plasticity phenomena observed start to deviate from those evidenced at the macroscale. The current research aims at investigating this gap using a lower-order gradient enhanced approach both using phenomenological continuum level as well as crystal plasticity models. In the phenomenological approach, a physically based hardening model relates the flow stress to the density of dislocations where it is assumed that the sources of immobile dislocations are both statistically stored (SSDs) as well as geometrically necessary dislocations (GNDs). In the crystal plasticity model, the evolution of the critical resolved shear stress is also defined based on the total number of dislocations. The GNDs are similarly incorporated in the hardening based on projecting the plastic strain gradients through the Burgers tensor on slip systems. A rate-independent formulation is considered that eliminates any artificial inhomogeneous hardening behavior due to numerical stabilization. The behavior of both models is compared in simulations focusing on the effect of structurally imposed gradients versus the inherent gradients arising in crystal plasticity simulations.

Growth Adaptation of gnd and sdhCB Escherichia coli Deletion Strains Diverges From a Similar Initial Perturbation of the Transcriptome.

Adaptive laboratory evolution (ALE) has emerged as a new approach with which to pursue fundamental biological inquiries and, in particular, new insights into the systemic function of a gene product. Two E. coli knockout strains were constructed: one that blocked the Pentose Phosphate Pathway (gnd KO) and one that decoupled the TCA cycle from electron transport (sdhCDAB KO). Despite major perturbations in central metabolism, minimal growth rate changes were found in the two knockout strains. More surprisingly, many similarities were found in their initial transcriptomic states that could be traced to similarly perturbed metabolites despite the differences in the network location of the gene perturbations and concomitant re-routing of pathway fluxes around these perturbations. However, following ALE, distinct metabolomic and transcriptomic states were realized. These included divergent flux and gene expression profiles in the gnd and sdhCDAB KOs to overcome imbalances in NADPH production and nitrogen/sulfur assimilation, respectively, that were not obvious limitations of growth in the unevolved knockouts. Therefore, this work demonstrates that ALE provides a productive approach to reveal novel insights of gene function at a systems level that cannot be found by observing the fresh knockout alone.

DNA barcoding and species delimitation of Chaitophorinae (Hemiptera, Aphididae).

Chaitophorinae aphids are widespread across Eurasia and North America, and include some important agricultural and horticultural pests. So, accurate rapid species identification is very important. Here, we used three mitochondrial genes and one endosymbiont gene to calculate and analyze the genetic distances within different datasets. For species delimitation, two distance-based methods were employed, threshold with NJ (neighbor-joining) and ABGD (Automatic Barcode Gap Discovery), and two tree-based approaches, GMYC (General Mixed Yule Coalescent) and PTP (Poisson Tree Process). The genetic interspecific divergence was clearly larger than the intraspecific divergence for four molecular markers. COI and COII genes were found to be more suitable for Chaitophorinae DNA barcoding. For species delimitation, at least one distance-based method combined with one tree-based method would be preferable. Based on the data for Chaitophorus saliniger and Laingia psammae, DNA barcoding may also reveal geographical variation.

Interrogation of single nucleotide polymorphisms in gnd provides a novel method for molecular serogrouping of clinically important Shiga toxin producing Escherichia coli (STEC) targeted by regulation in the United States, including the "big six" non-O157 STEC and STEC O157.

Escherichia coli O157:H7 has frequently been associated with foodborne infections and is considered an adulterant in raw non-intact beef in the U.S. Shiga toxin-producing E. coli (STEC) belonging to serogroups O26, O45, O103, O111, O121, and O145 (known as the "big six" non-O157) were estimated to cause >70% of foodborne infections attributed to non-O157 serogroups in the U.S., as a result, these six serogroups have also been targeted by regulation in the U.S. The purpose of this study was to develop a rapid and high-throughput molecular method to group STEC isolates into seven clinically important serogroups (i.e., O157 and the "big six" non-O157 serogroups) targeted by regulation in the U.S. by interrogating single nucleotide polymorphisms (SNPs) in gnd. A collection of 195 STEC isolates, including isolates belonging to O157:H7 (n=18), O26 (n=21), O45 (n=19), O103 (n=24), O111 (n=24), O121 (n=23), O145 (n=21), and ten other STEC serogroups (n=45), was assembled and characterized by full gnd sequencing to identify informative SNPs for molecular serogrouping. A multiplex SNP typing assay was developed to interrogate twelve informative gnd SNPs by single base pair extension chemistry and used to characterize the STEC isolate collection assembled here. SNP types were assigned to each isolate by the assay and polymorphisms were confirmed with gnd sequence data. O-serogroup-specific SNP types were identified for each of the seven clinically important STEC serogroups, which allowed the differentiation of these seven STEC serogroups from other non-O157 STEC serogroups. Although serogroups of the "big six" non-O157 STEC and O157:H7 contained multiple SNP types per O-serogroup, there were no overlapping SNP types between serogroups. Our results demonstrate that molecular serogrouping of STEC isolates by interrogation of informative SNPs in gnd represents an alternative to traditional serogrouping by agglutination for rapid and high-throughput identification of clinically important STEC serogroups targeted by regulation for surveillance and epidemiological investigations.

Model-guided metabolic gene knockout of gnd for enhanced succinate production in Escherichia coli from glucose and glycerol substrates.

The metabolic role of 6-phosphogluconate dehydrogenase (gnd) under anaerobic conditions with respect to succinate production in Escherichia coli remained largely unspecified. Herein we report what are to our knowledge the first metabolic gene knockout of gnd to have increased succinic acid production using both glucose and glycerol substrates in E. coli. Guided by a genome scale metabolic model, we engineered the E. coli host metabolism to enhance anaerobic production of succinic acid by deleting the gnd gene, considering its location in the boundary of oxidative and non-oxidative pentose phosphate pathway. This strategy induced either the activation of malic enzyme, causing up-regulation of phosphoenolpyruvate carboxylase (ppc) and down regulation of phosphoenolpyruvate carboxykinase (ppck) and/or prevents the decarboxylation of 6 phosphogluconate to increase the pool of glyceraldehyde-3-phosphate (GAP) that is required for the formation of phosphoenolpyruvate (PEP). This approach produced a mutant strain BMS2 with succinic acid production titers of 0.35 g l(-1) and 1.40 g l(-1) from glucose and glycerol substrates respectively. This work further clearly elucidates and informs other studies that the gnd gene, is a novel deletion target for increasing succinate production in E. coli under anaerobic condition using glucose and glycerol carbon sources. The knowledge gained in this study would help in E. coli and other microbial strains development for increasing succinate production and/or other industrial chemicals.

Quantifying NAD(P)H production in the upper Entner-Doudoroff pathway from Pseudomonas putida KT2440.

Despite the lack of biochemical information, all available in silico metabolic models of Pseudomonas putida KT2440 consider NADP as the only cofactor accepted by the glucose-6-phosphate dehydrogenases. Because the Entner-Doudoroff pathway is the main glycolytic route in this bacterium, determining how much NADH and NADPH are produced in the reaction catalyzed by these enzymes is very important for the correct interpretation of metabolic flux distributions. To determine the actual cofactor preference of the glucose-6-phosphate dehydrogenase encoded by the zwf-1 gene (PputG6PDH-1), the major isoform during growth on glucose, we purified this protein and studied its kinetic properties. Based on simple kinetic principles, we estimated the in vivo relative production of NADH and NADPH during the oxidation of glucose-6-phosphate (G6P). Contrary to the general assumption, our calculations showed that the reaction catalyzed by PputG6PDH-1 yields around 1/3 mol of NADPH and 2/3 mol of NADH per mol of oxidized G6P. Additionally, we obtained data suggesting that the reaction catalyzed by the 6-phosphogluconate dehydrogenase is active during growth on glucose, and it also produces NADH. These results indicate that the stoichiometric matrix of in silico models of P. putida KT2440 must be corrected and highlight the importance of considering the physiological concentrations of the involved metabolites to estimate the actual proportion of NADH and NADPH produced by a dehydrogenase.

Escherichia coli 6-phosphogluconate dehydrogenase aids in tellurite resistance by reducing the toxicant in a NADPH-dependent manner.

Exposure to the tellurium oxyanion tellurite (TeO3(2-)) results in the establishment of an oxidative stress status in most microorganisms. Usually, bacteria growing in the presence of the toxicant turn black because of the reduction of tellurite (Te(4+)) to the less-toxic elemental tellurium (Te(0)). In vitro, at least part of tellurite reduction occurs enzymatically in a nicotinamide dinucleotide-dependent reaction. In this work, we show that TeO3(2-) reduction by crude extracts of Escherichia coli overexpressing the zwf gene (encoding glucose-6-phosphate dehydrogenase) takes place preferentially in the presence of NADPH instead of NADH. The enzyme responsible for toxicant reduction was identified as 6-phosphogluconate dehydrogenase (Gnd). The gnd gene showed a subtle induction at short times after toxicant exposure while strains lacking gnd were more susceptible to the toxicant. These results suggest that both NADPH-generating enzymes from the pentose phosphate shunt may be involved in tellurite detoxification and resistance in E. coli.