Enhancing the production of L-proline in recombinant Escherichia coli BL21 by metabolic engineering.

L-proline is widely used in the fields of food, medicine and agriculture, and is also an important raw material for the synthesis of trans-4-hydroxy-L-proline. In this study, enhancing the production of L-proline by metabolic engineering was investigated. Three genes, proB, proA and proC, were introduced into Escherichia coli BL21 by molecular biology technology to increase the metabolic flow of L-proline from glucose. The genes putP and proP related to the proline transfer were knocked out by CRISPR/Cas9 gene editing technology to weaken the feedback inhibition of proB to increase the production of L-proline. The fermentation curves of the engineered strain at different glucose concentrations were determined, and a glucose concentration of 10 g/L was chosen to expand the batch culture to 1 L shake flask. Ultimately, through these efforts, the titer of L-proline reached 832.19 mg/L in intermittent glucose addition fermentation in a 1 L shake flask.

Vacuolar H+-ATPase determines daughter cell fates through asymmetric segregation of the nucleosome remodeling and deacetylase complex.

Asymmetric cell divisions (ACDs) generate two daughter cells with identical genetic information but distinct cell fates through epigenetic mechanisms. However, the process of partitioning different epigenetic information into daughter cells remains unclear. Here, we demonstrate that the nucleosome remodeling and deacetylase (NuRD) complex is asymmetrically segregated into the surviving daughter cell rather than the apoptotic one during ACDs in Caenorhabditis elegans. The absence of NuRD triggers apoptosis via the EGL-1-CED-9-CED-4-CED-3 pathway, while an ectopic gain of NuRD enables apoptotic daughter cells to survive. We identify the vacuolar H+-adenosine triphosphatase (V-ATPase) complex as a crucial regulator of NuRD's asymmetric segregation. V-ATPase interacts with NuRD and is asymmetrically segregated into the surviving daughter cell. Inhibition of V-ATPase disrupts cytosolic pH asymmetry and NuRD asymmetry. We suggest that asymmetric segregation of V-ATPase may cause distinct acidification levels in the two daughter cells, enabling asymmetric epigenetic inheritance that specifies their respective life-versus-death fates.

Evaluation of surfactant-aided polycyclic aromatic hydrocarbon biodegradation by molecular docking and molecular dynamic simulation in the marine environment.

Marine oil spills directly cause polycyclic aromatic hydrocarbons (PAHs) pollution and affect marine organisms due to their toxic property. Chemical and bio-based dispersants composed of surfactants and solvents are considered effective oil spill-treating agents. Dispersants enhance oil biodegradation in the marine environment by rapidly increasing their solubility in the water column. However, the effect of dispersants, especially surfactants, on PAHs degradation by enzymes produced by microorganisms has not been studied at the molecular level. The role of the cytochrome P450 (CYP) enzyme in converting contaminants into reactive metabolites during the biodegradation process has been evidenced, but the activity in the presence of surfactants is still ambiguous. Thus, this study focused on the evaluation of the impact of chemical and bio-surfactants (i.e., Tween 80 (TWE) and Surfactin (SUC)) on the biodegradation of naphthalene (NAP), chrysene (CHR), and pyrene (PYR), the representative components of PAHs, with CYP enzyme from microalgae Parachlorella kessleri using molecular docking and molecular dynamics (MD) simulation. The molecular docking analysis revealed that PAHs bound to residues at the CYP active site through hydrophobic interactions for biodegradation. The MD simulation showed that the surfactant addition changed the enzyme conformation in the CYP-PAH complexes to provide more interactions between the enzyme and PAHs. This led to an increase in the enzyme's capability to degrade PAHs. Binding free energy (ΔG||Bind) calculations confirmed that surfactant treatment could enhance PAHs degradation by the enzyme. The SUC gave a better result on NAP and PYR biodegradation based on ΔG||Bind, while TWE facilitated the biodegradation of CHR. The research outputs could greatly facilitate evaluating the behaviors of oil spill-treating agents and oil spill response operations in the marine environment.

Site-directed mutagenesis of bifunctional riboflavin kinase/FMN adenylyltransferase via CRISPR/Cas9 to enhance riboflavin production.

Vitamin B2 is an essential water-soluble vitamin. For most prokaryotes, a bifunctional enzyme called FAD synthase catalyzes the successive conversion of riboflavin to FMN and FAD. In this study, the plasmid pNEW-AZ containing six key genes for the riboflavin synthesis was transformed into strain R2 with the deleted FMN riboswitch, yielding strain R5. The R5 strain could produce 540.23 ± 5.40 mg/L riboflavin, which was 10.61 % higher than the R4 strain containing plasmids pET-AE and pAC-Z harboring six key genes. To further enhance the production of riboflavin, homology matching and molecular docking were performed to identify key amino acid residues of FAD synthase. Nine point mutation sites were identified. By comparing riboflavin kinase activity, mutations of T203D and N210D, which respectively decreased by 29.90 % and 89.32 % compared to wild-type FAD synthase, were selected for CRISPR/Cas9 gene editing of the genome, generating engineered strains R203 and R210. pNEW-AZ was transformed into R203, generating R6. R6 produced 657.38 ± 47.48 mg/L riboflavin, a 21.69 % increase compared to R5. This study contributes to the high production of riboflavin in recombinant E. coli BL21.

Automated Generation and Analysis of Molecular Images Using Generative Artificial Intelligence Models.

The development of scanning probe microscopy (SPM) has enabled unprecedented scientific discoveries through high-resolution imaging. Simulations and theoretical analysis of SPM images are equally important as obtaining experimental images since their comparisons provide fruitful understandings of the structures and physical properties of the investigated systems. So far, SPM image simulations are conventionally based on quantum mechanical theories, which can take several days in tasks of large-scale systems. Here, we have developed a scanning tunneling microscopy (STM) molecular image simulation and analysis framework based on a generative adversarial model, CycleGAN. It allows efficient translations between STM data and molecular models. Our CycleGAN-based framework introduces an approach for high-fidelity STM image simulation, outperforming traditional quantum mechanical methods in efficiency and accuracy. We envision that the integration of generative networks and high-resolution molecular imaging opens avenues in materials discovery relying on SPM technologies.

Tire additives: Evaluation of joint toxicity, design of new derivatives and mechanism analysis of free radical oxidation.

N-(1,3-Dimethylbutyl)-N'-phenyl-p-phenylenediamine (6PPD) is one of the most widely used antioxidant agents in tire additives. Its ozonation by-product 6PPD-quinone has recently been recognized as inducing acute mortality in aquatic organisms such as coho salmon. In this study, we aimed to develop an in-silico method to design environmentally friendly 6PPD derivatives and evaluate the joint toxicity of 6PPD with other commonly used tire additives on coho salmon through full factorial design-molecular docking and molecular dynamic simulation. The toxicity mentioned in this study is represented by the binding energy of chemical(s) binding to the coho salmon growth hormone. The recommended formula for tire additives with relatively low toxicity was then proposed. To further reduce the toxicity of 6PPD, 129 6PPD derivatives were designed based on the N-H bond dissociation reaction, and three of these derivatives showed improved antioxidant activity and 6PPD-106 was finally screened as the optimum alternative with lower toxicity to coho salmon. Besides, the mechanism of free radical oxidation (i.e., antioxidation and ozonation metabolic pathway) for 6PPD-106 was also analyzed and found that after ozonation, the toxicity of 6PPD-106's by-products is much lower than that of 6PPD's by-products. This study provided a molecular modelling-based examination of 6PPD, which comprehensively advanced the understanding of 6PPD's environmental behaviors and provided more environmentally friendly 6PPD alternatives with desired functional property and lower ecological risks.

Biosynthesis of the phycocyanin ß-subunit in Escherichia coli BL21 and its antioxidant activity and application in the preservation of fresh-cut apples.

In this study, the biosynthesis of phycocyanin ß-subunit (CpcB) in Escherichia coli BL21 was investigated, and its antioxidant activity and application in anti-browning of fresh-cut apples was explored. Four genes (cpcB, cpeS, hox1 and pcyA) involved in the biosynthesis of CpcB were cloned and transformed into E. coli BL21 by constructing recombinant plasmid pETDuet-5. The positive transformant was screened by ampicillin resistance. The analysis of SDS-PAGE and zinc fluorescence spectrum showed that CpcB was successfully expressed in E. coli BL21 with a molecular weight of 21 kDa. The purified CpcB had a maximum absorption peak at 615 nm, and its maximum florescence emission wavelength was 640 nm. It exhibited a stronger ability to scavenge four free radicals than Vc. The color change in fresh-cut apples was obviously delayed by the CpcB treatment. These results suggest that CpcB may be used as a potential anti-browning agent for food preservation.

Unraveling the Mechanisms of On-Surface Photoinduced Reaction with Polarized Light Excitations.

On-surface reaction has been shown as a powerful strategy to achieve atomically precise nanostructures. Numerous reactions have been realized on surfaces with thermal annealing as the primary excitation. In contrast, far fewer reactions have been triggered by light on surfaces despite its advantages due to the nonthermal process. This is possibly ascribed to our limited understanding on the excitation mechanisms of on-surface photoinduced reactions. In this work, we have studied the photoinduced debrominated coupling by using a linearly polarized light. We successfully achieved the reaction with no annealing process and obtained oligomers as the primary reaction products, which is in contrast with the formation of polymers with traditional thermal treatments. By exploring the dependence of reaction yield on the angle of incidence, we demonstrate an experimental method that can provide fundamental insights. The comparison with the theoretical approximation suggests indirect hot carrier excitation as the leading excitation mechanism. Our results not only provide fundamental insight into the surface photochemical reactions but also set the basis for harnessing light to construct unconventional nanomaterials.

A Comprehensive Biochemical Characterization of Hybrid Grouper Larvae (Epinephelus fuscoguttatus♀ × Epinephelus lanceolatus♂) during Yolk-Sac Larval Development.

To investigate the shifts in the biochemical composition of hybrid grouper during the early larval stages, we collected samples at various developmental milestones, spanning from newly hatched larvae (stage I) to 4 days after hatching (stage V). Our findings revealed several notable trends: (1) The total length of hybrid grouper larvae exhibited a significant increase as the yolk-sac absorption progressed from stage I to V. Concurrently, there was a marked decrease in yolk volume and oil volume during the transition from stage I to III, followed by a gradual decline from stage III to V. (2) Dry weight and total lipid content displayed a rapid reduction throughout the larval development period, while the total protein content exhibited a declining trend. (3) The concentrations of triacylglycerols and wax esters/steryl esters decreased considerably, particularly at stage V. However, no differences were observed among the contents of ketones, hydrocarbons, and sterols. (4) As yolk-sac larvae developed from stage I to V, a significant reduction was observed in the levels of essential amino acids (EAAs), such as leucine, valine, isoleucine, phenylalanine, glycine, alanine, serine, proline, and tyrosine. This trend was also observed for non-EAAs and total amino acids, with fluctuations in the content of other amino acids. (5) There was a significant decrease in the levels of specific fatty acids, including C16:0, saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs), C18:0, 18:1n-9, and C20:4n-6. In contrast, the contents of C22:6n-3, polyunsaturated fatty acids (PUFAs), n-3 PUFA, n-6 PUFA, and the combination of docosahexaenoic acid (DHA) + eicosapentaenoic acid (EPA), as well as the DHA/EPA ratio, remained stable from stage I to III but declined thereafter. (6) During the early developmental stages, the utilization sequence of fatty acids followed a pattern of prioritizing SFAs, followed by MUFAs, n-6 PUFA, and n-3 PUFA. These findings provide further insights into the nutritional priorities of hybrid grouper larvae during their early development, with a particular emphasis on lipids and fatty acids as vital energy sources. Additionally, our results highlight variations in the efficiency of utilization among different types of fatty acids, while protein utilization remained relatively stable, characterized by the selective consumption of amino acid content.

Order-Disorder Transition of Two-Dimensional Molecular Networks through a Stoichiometric Design.

Materials with disordered structures may exhibit interesting properties. Metal-organic frameworks (MOFs) are a class of hybrid materials composed of metal nodes and coordinating organic linkers. Recently, there has been growing interest in MOFs with structural disorder and the investigations of amorphous structures on surfaces. Herein, we demonstrate a bottom-up method to construct disordered molecular networks on metal surfaces by selecting two organic molecule linkers with the same symmetry but different sizes for preparing two-component samples with different stoichiometric ratios. The amorphous networks are directly imaged by scanning tunneling microscopy under ultrahigh vacuum with a submolecular resolution, allowing us to quantify its degree of disorder and other structural properties. Furthermore, we resort to molecular dynamics simulations to understand the formation of the amorphous metal-organic networks. The results may advance our understanding of the mechanism of formation of monolayer molecular networks with structural disorders, facilitating the design and exploration of amorphous MOF materials with intriguing properties.

Fabrication high toughness poly(butylene adipate-co-terephthalate)/thermoplastic starch composites via melt compounding with ethylene-methyl acrylate-glycidyl methacrylate.

The preparation of biodegradable composites with high toughness and low cost is of great significance for their application and promotion in the packaging field. As a renewable and biodegradable material with abundant sources, the inclusion of starch in biodegradable composites can significantly reduce costs. However, the poor compatibility between starch and matrix severely limits its large-scale practical application. In this work, the poly(butylene adipate-co-terephthalate)/thermoplastic starch/ethylene-methyl acrylate-glycidyl methacrylate (PBAT/TPS/EGMA) blends with high toughness were prepared by melt compounding. The elongation at break increased significantly from 533 ± 125 % for the PBAT/TPS(60/40) blend to 1188 ± 28 % for the PBAT/TPS/EGMA(60/40/2) blend. According to the analysis of Fourier Transform Infrared Spectroscopy (FT-IR) and Scanning Electron Microscope (SEM), the toughness improvement brought about by the addition of EGMA can be attributed to the enhanced compatibility between PBAT and TPS and the refinement of TPS particle size. The knowledge obtained from this study provides a method to enhance the toughness of biodegradable polymer composites with high TPS loading, which will facilitate the practical application of starch in the packing field.

Global histone H2B degradation regulates insulin/IGF signaling-mediated nutrient stress.

Eukaryotic organisms adapt to environmental fluctuations by altering their epigenomic landscapes and transcriptional programs. Nucleosomal histones carry vital epigenetic information and regulate gene expression, yet the mechanisms underlying chromatin-bound histone exchange remain elusive. Here, we found that histone H2Bs are globally degraded in Caenorhabditis elegans during starvation. Our genetic screens identified mutations in ubiquitin and ubiquitin-related enzymes that block H2B degradation in starved animals, identifying lysine 31 as the crucial residue for chromatin-bound H2B ubiquitination and elimination. Retention of aberrant nucleosomal H2B increased the association of the FOXO transcription factor DAF-16 with chromatin, generating an ectopic gene expression profile detrimental to animal viability when insulin/IGF signaling was reduced in well-fed animals. Furthermore, we show that the ubiquitin-proteasome system regulates chromosomal histone turnover in human cells. During larval development, C. elegans epidermal cells undergo H2B turnover after fusing with the epithelial syncytium. Thus, histone degradation may be a widespread mechanism governing dynamic changes of the epigenome.

Predicting Molecular Self-Assembly on Metal Surfaces Using Graph Neural Networks Based on Experimental Data Sets.

The application of supramolecular chemistry on solid surfaces has received extensive attention in the past few decades. To date, combining experiments with quantum mechanical or molecular dynamic methods represents the key strategy to explore the molecular self-assembled structures, which is, however, often laborious. Recently, machine learning (ML) has become one of the most exciting tools in material research, allowing for both efficiency and accuracy in predicting molecular properties. In this work, we constructed a graph neural network to predict the self-assembly of functional polycyclic aromatic hydrocarbons (PAHs) on metal surfaces. Using scanning tunneling microscopy (STM), we characterized the self-assembled nanostructures of a homologous series of PAH molecules on different metal surfaces to construct an experimental data set for model training. Compared with traditional ML algorithms, our model exhibits better predictive performance. Finally, the generalization of the model is further verified by comparing the ML predictions and experimental results of different functionalized molecule. Our results demonstrate training experimental data sets to produce a predictive ML model of molecular self-assembly with generalization performance, which allows for the predictive design of nanostructures with functional molecules.

Applying a Deep-Learning-Based Keypoint Detection in Analyzing Surface Nanostructures.

Scanning tunneling microscopy (STM) imaging has been routinely applied in studying surface nanostructures owing to its capability of acquiring high-resolution molecule-level images of surface nanostructures. However, the image analysis still heavily relies on manual analysis, which is often laborious and lacks uniform criteria. Recently, machine learning has emerged as a powerful tool in material science research for the automatic analysis and processing of image data. In this paper, we propose a method for analyzing molecular STM images using computer vision techniques. We develop a lightweight deep learning framework based on the YOLO algorithm by labeling molecules with its keypoints. Our framework achieves high efficiency while maintaining accuracy, enabling the recognitions of molecules and further statistical analysis. In addition, the usefulness of this model is exemplified by exploring the length of polyphenylene chains fabricated from on-surface synthesis. We foresee that computer vision methods will be frequently used in analyzing image data in the field of surface chemistry.

Steering on-surface polymerization through coordination with a bidentate ligand.

A double-chain structure was fabricated on Au (111) with a bromine-functionalized phenanthroline precursor. We reveal the competition between the on-surface metal-ligand coordination and C-C coupling of the precursor by scanning tunneling microscopy (STM) imaging and density functional theory (DFT) calculations at the molecular level. Our work provides an additional strategy for controlling the on-surface polymerization, which is of great relevance to the construction of novel nanostructures.

RAB6A functions as a critical modulator of the stem-like subsets in cholangiocarcinoma.

RAB6A is a member of RAB GTPase family and plays an important role in the targeted transport of neurotrophic receptors and inflammatory cytokines. RAB6A-mediated secretory pathway is involved in many physiological and pathological processes. Defects in RAB6A-mediated secretory pathway may lead to the development of many diseases, including cancer. However, its role in cholangiocarcinoma (CCA) has not yet been revealed. We explored the regulatory role of RAB6A in the stem-like subsets of CCA. We showed that RAB6A knockdown (KD) impedes cancer stem cells (CSCs) properties and epithelial-mesenchymal transition in vitro and that suppression of RAB6A inhibits tumor growth in vivo. We screened target cargos of RAB6A in CCA cells and identified a extracellular matrix component as the target cargo. RAB6A binds directly to OPN, and RAB6A KD suppressed OPN secretion and inhibited the interaction between OPN and αV integrin receptor. Moreover, RAB6A KD inhibited the AKT signaling pathway, which is a downstream effector of the integrin receptor signaling. In addition, shRNA targeting OPN blocked endogenous expression of OPN and consequently weakened CSCs properties in RAB6A-formed spheres. Similarly, inhibitor of AKT signaling, MK2206 also impedes oncogenic function of RAB6A in the stem-like subsets of CCA cells. In conclusion, our findings showed that RAB6A sustains CSCs phenotype maintenance by modulating the secretion of OPN and consequentially activating the downstream AKT signaling pathway. Targeting the RAB6A/OPN axis may be an effective strategy for CCA therapy.

Triangle Counting Rule: An Approach to Forecast the Magnetic Properties of Benzenoid Polycyclic Hydrocarbons.

Open-shell benzenoid polycyclic hydrocarbons (BPHs) are promising materials for future quantum applications. However, the search for and realization of open-shell BPHs with desired properties is a challenging task due to the gigantic chemical space of BPHs, requiring new strategies for both theoretical understanding and experimental advancement. In this work, by building a structure database of BPHs through graphical enumeration, performing data-driven analysis, and combining tight-binding and mean-field Hubbard calculations, we discovered that the number of the internal vertices of the BPH graphs is closely correlated to their open-shell characters. We further established a simple rule, the triangle counting rule, to predict the magnetic ground states of BPHs. These findings not only provide a database of open-shell BPHs, but also extend the well-known Lieb's theorem and Ovchinnikov's rule and provide a straightforward method for designing open-shell carbon nanostructures. These insights may aid in the exploration of emerging quantum phases and the development of magnetic carbon materials for technology applications.

FBXO31 sensitizes cancer stem cells-like cells to cisplatin by promoting ferroptosis and facilitating proteasomal degradation of GPX4 in cholangiocarcinoma.

BACKGROUND & AIMS: Cholangiocarcinoma (CCA) is a malignant tumour originating from the biliary epithelium that easily infiltrates, metastasizes and recurs. The deficiency of FBXO31 facilitates the initiation and progression of several types of cancer. However, the involvement of FBXO31 in CCA progression has remained unclear. METHODS: qRT-PCR was used to detect the expression of FBXO31 in CCA. The biological functions of FBXO31 were confirmed in vivo and in vitro. Sphere formation and flow cytometry were used to identify the stem cell properties of CCA. RESULTS: FBXO31 is downregulated in CCA and that deficiency of FBXO31 is associated with the TNM stage of CCA. Functional studies showed FBXO31 inhibits cell growth, migration, invasion, cancer stem cell (CSC) properties and epithelial-mesenchymal transition (EMT) in vitro and impedes tumour growth in vivo. In addition, overexpression of FBXO31 increases the cisplatin (CDDP) sensitivity of CCA cells. RNA-sequencing analysis revealed that FBXO31 is involved in redox biology and metal ion metabolism in CCA cells during CDDP treatment. Further studies revealed that FBXO31 enhances ferroptosis induced by CDDP in CCA and CSC-like cells. FBXO31 enhances ubiquitination of glutathione peroxidase 4 (GPX4), which leads to proteasomal degradation of GPX4. Moreover, overexpression of GPX4 compromises the promoting effects of FBXO31 on CDDP-induced ferroptosis in CCA and CSC-like cells. CONCLUSIONS: Our studies indicate that FBXO31 functions as a tumour suppressor in CCA and sensitizes CSC-like cells to CDDP by promoting ferroptosis and facilitating the proteasomal degradation of GPX4.

A Deep-Learning Framework for the Automated Recognition of Molecules in Scanning-Probe-Microscopy Images.

Computer vision as a subcategory of deep learning tackles complex vision tasks by dealing with data of images. Molecular images with exceptionally high resolution have been achieved thanks to the development of techniques like scanning probe microscopy (SPM). However, extracting useful information from SPM image data requires careful analysis which heavily relies on human supervision. In this work, we develop a deep learning framework using an advanced computer vision algorithm, Mask R-CNN, to address the challenge of molecule detection, classification and instance segmentation in binary molecular nanostructures. We employ the framework to determine two triangular-shaped molecules of similar STM appearance. Our framework could accurately differentiate two molecules and label their positions. We foresee that the application of computer vision in SPM images will become an indispensable part in the field, accelerating data mining and the discovery of new materials.

On-surface synthesis of ethers through dehydrative coupling of hydroxymethyl substituents.

On-surface synthesis has been a subject of intensive research during the last decade. Various chemical reactions have been developed on surfaces to prepare compounds and carbon nanostructures, most of which are centered on the carbon-carbon bond formation. Despite the vast progress so far, the diversity of functional groups in organic chemistry has been far less explored in on-surface synthesis. Herein, we study the surface-assisted synthesis of ethers through the homocoupling of hydroxymethyl substituents on Ag(111). By using two hydroxymethyl substituent functionalized molecular precursors with different symmetries, we have achieved the formation of ether chains and rings. High-resolution scanning tunneling microscopy complemented with density functional theory calculations are used to support our findings and offer mechanistic insights into the reaction. This work expands the toolbox of on-surface reactions for the bottom-up fabrication of more sophisticated functional nanostructures.