A quantitative image analysis pipeline for the characterization of filamentous fungal morphologies as a tool to uncover targets for morphology engineering: a case study using aplD in Aspergillus niger

Background Fungal fermentation is used to produce a diverse repertoire of enzymes, chemicals, and drugs for various industries. During submerged cultivation, filamentous fungi form a range of macromorphologies, including dispersed mycelia, clumped aggregates, or pellets, which have critical implications for rheological aspects during fermentation, gas/nutrient transfer, and, thus, product titres. An important component of strain engineering efforts is the ability to quantitatively assess fungal growth phenotypes, which will drive novel leads for morphologically optimized production strains. Results In this study, we developed an automated image analysis pipeline to quantify the morphology of pelleted and dispersed growth (MPD) which rapidly and reproducibly measures dispersed and pelleted macromorphologies from any submerged fungal culture. It (i) enables capture and analysis of several hundred images per user/day, (ii) is designed to quantitatively assess heterogeneous cultures consisting of dispersed and pelleted forms, (iii) gives a quantitative measurement of culture heterogeneity, (iv) automatically generates key Euclidian parameters for individual fungal structures including particle diameter, aspect ratio, area, and solidity, which are also assembled into a previously described dimensionless morphology number MN, (v) has an in-built quality control check which enables end-users to easily confirm the accuracy of the automated calls, and (vi) is easily adaptable to user-specified magnifications and macromorphological definitions. To concomitantly provide proof of principle for the utility of this image analysis pipeline, and provide new leads for morphologically optimized fungal strains, we generated a morphological mutant in the cell factory Aspergillus niger based on CRISPR-Cas technology. First, we interrogated a previously published co-expression networks for A. niger to identify a putative gamma-adaptin encoding gene (aplD) that was predicted to play a role in endosome cargo trafficking. Gene editing was used to generate a conditional aplD expression mutant under control of the titratable Tet-on system. Reduced aplD expression caused a hyperbranched growth phenotype and diverse defects in pellet formation with a putative increase in protein secretion. This possible protein hypersecretion phenotype could be correlated with increased dispersed mycelia, and both decreased pellet diameter and MN. Conclusion The MPD image analysis pipeline is a simple, rapid, and flexible approach to quantify diverse fungal morphologies. As an exemplar, we have demonstrated that the putative endosomal transport gene aplD plays a crucial role in A. niger filamentous growth and pellet formation during submerged culture. This suggests that endocytic components are underexplored targets for engineering fungal cell factories.DFG, 414044773, Open Access Publizieren 2019 - 2020 / Technische Universität Berli

Functional exploration of co-expression networks identifies a nexus for modulating protein and citric acid titres in Aspergillus niger submerged culture

Background: Filamentous fungal cell factories are used to produce numerous proteins, enzymes, and organic acids. Protein secretion and filamentous growth are tightly coupled at the hyphal tip. Additionally, both these processes require ATP and amino acid precursors derived from the citric acid cycle. Despite this interconnection of organic acid production and protein secretion/filamentous growth, few studies in fungi have identified genes which may concomitantly impact all three processes. Results: We applied a novel screen of a global co-expression network in the cell factory Aspergillus niger to identify candidate genes which may concomitantly impact macromorphology, and protein/organic acid fermentation. This identified genes predicted to encode the Golgi localized ArfA GTPase activating protein (GAP, AgeB), and ArfA guanine nucleotide exchange factors (GEFs SecG and GeaB) to be co-expressed with citric acid cycle genes. Consequently, we used CRISPR-based genome editing to place the titratable Tet-on expression system upstream of ageB, secG, and geaB in A. niger. Functional analysis revealed that ageB and geaB are essential whereas secG was dispensable for early filamentous growth. Next, gene expression was titrated during submerged cultivations under conditions for either protein or organic acid production. ArfA regulators played varied and culture-dependent roles on pellet formation. Notably, ageB or geaB expression levels had major impacts on protein secretion, whereas secG was dispensable. In contrast, reduced expression of each predicted ArfA regulator resulted in an absence of citric acid in growth media. Finally, titrated expression of either GEFs resulted in an increase in oxaloacetic acid concentrations in supernatants. Conclusion: Our data suggest that the Golgi may play an underappreciated role in modulating organic acid titres during industrial applications, and that this is SecG, GeaB and AgeB dependent in A. niger. These data may lead to novel avenues for strain optimization in filamentous fungi for improved protein and organic acid titres.TU Berlin, Open-Access-Mittel - 201

A simple and efficient procedure for Knoevenagel reaction promoted by imidazolium-based ionic liquids

Various room temperature ionic liquids (RTILs), notably, 1-methoxyethyl-3-methylimidazolium trifluoroacetate [MeOEtMIM]+[CF3COO]ˉ , have been used to promote the Knoevenagel condensation to afford substituted olefins. All reactions proceeded effectively in the absence of any other catalysts or co-solvents with good to excellent yields. This method is simple and applicable to reactions involving a wide range of aldehydes and ketones with methylene compounds. The ionic liquid can be recycled without noticeable reduction of its catalytic activity. A plausible reaction mechanism is proposed

Numerical Simulation of 2D Supersonic Magnetohydrodynamic Channel and Study on Hall Effect

AbstractIn this research effort, numerical simulation of two-dimensional magnetohydrodynamic (MHD) channel is performed and Hall effect is studied. The computational model consists of the Navier-Stokes (N-S) equations coupled with electrical-magnetic source terms, Maxwell equations and the generalized Ohm's law. Boundary conditions for the electrical potential equation considering Hall effect are derived. To start with, the MHD channel with single-pair electrodes is studied and flow of the electric current is in accordance with physical principle. Then the MHD channel with five-pair electrodes is numerically simulated. The results show that the electrical current concentrates on the downstream of the anode and the upstream of the cathode due to Hall effect, and the flow field becomes asymmetrical. At the current value of the magnetic interaction parameter, the electrical-magnetic force affects the flow remarkably, decreasing the outlet Mach number and increasing the outlet pressure; what's more, the flow structure in the channel becomes extremely complex. Performances of MHD channels with continual electrodes and segmented electrodes are compared. The results show that performance of the MHD channel with segmented electrodes is better than that with continual electrodes with the increase of Hall parameter

Characterization of Maternal and Fetal CYP3A-Mediated Progesterone Metabolism

INTRODUCTION: Progesterone is critical for maintaining pregnancy and onset of labor. We evaluated CYP450-mediated progesterone meta-bolism, specifically the contribution of CYP3A isoforms. MATERIALS AND METHODS: In vitro progesterone metabolism was characterized in human liver microsomes (HLMs) with and without selective cytochrome P450 inhibitors and in recombinant CYP3A4, CYP3A5, and CYP3A7. 6β-hydroxyprogesterone (6β-OHP) and 16α-hydroxyprogesterone (16α-OHP) metabolites were quantified by HPLC/UV and fit to the Michaelis-Menten equation to determine Km and Vmax. The effect of CYP3A5 expression on progesterone clearance was determined by in vitro in vivo extrapolation. RESULTS: Ketoconazole inhibited formation of both 6β-OHP and 16α-OHP more than 95%. 6β-OHP and 16α-OHP were both produced by CYP3A4 (2.3 and 1.3 µL/min/pmol, respectively) to a greater extent than by CYP3A5 (0.09 and 0.003 µL/min/pmol) and CYP3A7 (0.004 and 0.003 µL/min/pmol). CONCLUSIONS: Maternal clearance of progesterone by hepatic CYP450's is driven primarily by CYP3A4, with limited contributions from CYP3A5 and CYP3A7

Synthesis and Antibacterial Property of An Encapsulated Sulfonamide Nanoparticle in a Multidisciplinary Approach

Multigram quantity of a novel Sulfa Drug complex -poly(amido)amine-sulfonamide or PAMAM-Sulfa- was synthesized, from commercially available materials. It was characterized with spectroscopic methods such as nuclear magnetic resonance (NMR). The Kirby-Bauer test was used to test it against gram positive and/or gram negative bacteria using different concentrations of an ethanol solution of the PAMAM-Sulfa complex. The goal of this experiment was to synthesize and study the effect of water soluble encapsulated sulfonamides on common bacteria by undergraduate students engaging in research involving more than one STEM discipline. Students synthesized a dendrimer-sulfonamide complex before evaluating its antibiotic properties. In doing so, students employed research methods that are common to chemistry, biology and nanoscience while also learning about mechanism of infectious diseases, drugs and drug resistance. This project allowed students to combine aspects of scientific research that are usually done separately, and an opportunity to observe the seamlessness of multidisciplinary science

Unique caudal plumage of Jeholornis and complex tail evolution in early birds

The Early Cretaceous bird Jeholornis was previously only known to have a distally restricted ornamental frond of tail feathers. We describe a previously unrecognized fan-shaped tract of feathers situated dorsal to the proximal caudal vertebrae. The position and morphology of these feathers is reminiscent of the specialized upper tail coverts observed in males of some sexually dimorphic neornithines. As in the neornithine tail, the unique “two-tail” plumage in Jeholornis probably evolved as the result of complex interactions between natural and sexual selective pressures and served both aerodynamic and ornamental functions. We suggest that the proximal fan would have helped to streamline the body and reduce drag whereas the distal frond was primarily ornamental. Jeholornis reveals that tail evolution was complex and not a simple progression from frond to fan.Fil: O'Connor, Jingmai. Chinese Academy Of Sciences. Institute of Vertebrate Paleontology and Paleoanthropology; República de ChinaFil: Wang, Xiaoli. Linyi University; ChinaFil: Sullivan, Corwin. Chinese Academy Of Sciences. Institute of Vertebrate Paleontology and Paleoanthropology; República de ChinaFil: Zheng, Xiaoting. Linyi University; China. Shandong Tianyu Museum of Nature; ChinaFil: Tubaro, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales; ArgentinaFil: Zhang, Xiaomei. Shandong Tianyu Museum of Nature; ChinaFil: Zhou, Zhonghe. Chinese Academy Of Sciences. Institute of Vertebrate Paleontology and Paleoanthropology; República de Chin

Masked Language Model Based Textual Adversarial Example Detection

Adversarial attacks are a serious threat to the reliable deployment of machine learning models in safety-critical applications. They can misguide current models to predict incorrectly by slightly modifying the inputs. Recently, substantial work has shown that adversarial examples tend to deviate from the underlying data manifold of normal examples, whereas pre-trained masked language models can fit the manifold of normal NLP data. To explore how to use the masked language model in adversarial detection, we propose a novel textual adversarial example detection method, namely Masked Language Model-based Detection (MLMD), which can produce clearly distinguishable signals between normal examples and adversarial examples by exploring the changes in manifolds induced by the masked language model. MLMD features a plug and play usage (i.e., no need to retrain the victim model) for adversarial defense and it is agnostic to classification tasks, victim model's architectures, and to-be-defended attack methods. We evaluate MLMD on various benchmark textual datasets, widely studied machine learning models, and state-of-the-art (SOTA) adversarial attacks (in total $3*4*4 = 48$ settings). Experimental results show that MLMD can achieve strong performance, with detection accuracy up to 0.984, 0.967, and 0.901 on AG-NEWS, IMDB, and SST-2 datasets, respectively. Additionally, MLMD is superior, or at least comparable to, the SOTA detection defenses in detection accuracy and F1 score. Among many defenses based on the off-manifold assumption of adversarial examples, this work offers a new angle for capturing the manifold change. The code for this work is openly accessible at \url{https://github.com/mlmddetection/MLMDdetection}.Comment: 13 pages,3 figure