Structural diversification of natural substrates modified by the O-methyltransferase AurJ from Fusarium Graminearum.

Aromatic polyketide and phenylpropanoid derivatives are a large class of natural products produced by bacteria, fungi, and plants. The O-methylation is a unique decoration that can increase structural diversity of aromatic compounds and improve their pharmacological properties, but the substrate specificity of O-methyltransferase hinders the discovery of more natural products with O-methylation through biosynthesis. Here, we reported that the O-methyltransferase AurJ from plant pathogenic fungus Fusarium graminearum could methylate a broad range of natural substrates of monocyclic, bicyclic, and tricyclic aromatic precursors, exhibiting excellent substrate tolerance. This finding will partly change our stereotype about the specificity of traditional methyltransferases, and urge us to mine more O-methyltransferases with good substrate tolerance and discover more methylated natural products for drug discovery and development through directed evolution and combinatorial biosynthesis.

Hierarchical Belief Propagation on Image Segmentation Pyramid.

The Markov random field (MRF) for stereo matching can be solved using belief propagation (BP). However, the solution space grows significantly with the introduction of high-resolution stereo images and 3D plane labels, making the traditional BP algorithms impractical in inference time and convergence. We present an accurate and efficient hierarchical BP framework using the representation of the image segmentation pyramid (ISP). The pixel-level MRF can be solved by a top-down inference on the ISP. We design a hierarchy of MRF networks using the graph of superpixels at each ISP level. From the highest/image to the lowest/pixel level, the MRF models can be efficiently inferred with constant global guidance using the optimal labels of the previous level. The large texture-less regions can be handled effectively by the MRF model on a high level. The advanced 3D continuous labels and a novel support-points regularization are integrated into our framework for stereo matching. We provide a data-level parallelism implementation which is orders of magnitude faster than the best graph cuts (GC) algorithm. The proposed framework, HBP-ISP, outperforms the best GC algorithm on the Middlebury stereo matching benchmark.

Application of CRISPR in Filamentous Fungi and Macrofungi: From Component Function to Development Potentiality.

Fungi, particularly filamentous fungi and macrofungi, have a very powerful ability to produce secondary metabolites and can serve as excellent chassis cells for the production of enzymes or natural products of great value in synthetic biology. Thus, it is imperative to establish simple, reliable, and efficient techniques for their genetic modification. However, the heterokaryosis of some fungi and the dominance of nonhomologous end-joining (NHEJ) repair mechanisms in vivo have been greatly affecting the efficiency of fungal gene editing. In recent years, the CRISPR/Cas9 system has been applied as a widely used gene editing technology in life science research and has also played an important role in the genetic modification of filamentous and macrofungi. The various functional components (cas9, sgRNA, promoter, and screening marker) of the CRISPR/Cas9 system and its development, as well as the difficulties and potential of the CRISPR/Cas9 system in filamentous fungus and macrofungi, are the main topics of this paper.

Mining and Characterization of Indolethylamine N-Methyltransferases in Amphibian Toad Bufo gargarizans.

Strong, psychedelic indolethylamines (IAAs) are typically present in trace amounts in the majority of species, but they build up significantly in the skin of amphibian toads, especially N-methylated 5-hydroxytryptamine (5-HT) analogues. However, there is no pertinent research on the investigation of indoleamine N-methyltransferase (INMT) in amphibians, nor is there any adequate information on the key amino acids that influence the activity of known INMTs from other species. Herein, we focused on Bufo toad INMT (BINMT) for the first time and preliminarily identified BINMT 1 from the transcriptomes of Bufo gargarizans active on tryptamine, 5-HT, and N-methyl-5-HT. We established the enzyme kinetic characteristics of BINMT 1 and identified the essential amino acids influencing its activity via molecular docking and site-directed mutagenesis. Subsequently, we carried out sequence alignment and phylogenetic tree analysis on 43 homologous proteins found in the genome of B. gargarizans with BINMT 1 as the probe and selected seven of them for protein expression and activity assays. It was found that only three proteins possessing the highest similarity to BINMT 1 had INMT activity. Our research unveils the binding residues of BINMT for 5-HT analogues for the first time and initiates the study of INMTs in amphibian toads, serving as a tentative reference for further study of BINMT and providing insight into the comprehension of BINMT's catalytic mechanism and its role in the biosynthesis of 5-HT analogues in Bufo toads. It also contributes to the expansion of the INMT library to help explore and explain interspecies evolution in the future.

Sparse-to-Local-Dense Matching for Geometry-Guided Correspondence Estimation.

Establishing reliable correspondences between two views is one of the most important components of various vision tasks. This paper proposes a novel sparse-to-local-dense (S2LD) matching method to conduct fully differentiable correspondence estimation with the prior from epipolar geometry. The sparse-to-local-dense matching asymmetrically establishes correspondences with consistent sub-pixel coordinates while reducing the computation of matching. The salient features are explicitly located, and the description is conditioned on both views with the global receptive field provided by the attention mechanism. The correspondences are progressively established in multiple levels to reduce the underlying re-projection error. We further propose a 3D noise-aware regularizer with differentiable triangulation. Additional guidance from 3D space is encoded by the regularizer in training to handle the supervision noise caused by the errors in camera poses and depth maps. The proposed method demonstrates outstanding matching accuracy and geometric estimation capability on multiple datasets and tasks.

Joint-Confidence-guided Multi-Task Learning for 3D Reconstruction and Understanding from Monocular Camera.

3D reconstruction and understanding from monocular camera is a key issue in computer vision. Recent learning-based approaches, especially multi-task learning, significantly achieve the performance of the related tasks. However a few works still have limitation in drawing loss-spatial-aware information. In this paper, we propose a novel Joint-confidence-guided network (JCNet) to simultaneously predict depth, semantic labels, surface normal, and joint confidence map for corresponding loss functions. In details, we design a Joint Confidence Fusion and Refinement (JCFR) module to achieve multi-task feature fusion in the unified independent space, which can also absorb the geometric-semantic structure feature in the joint confidence map. We use confidence-guided uncertainty generated by the joint confidence map to supervise the multi-task prediction across the spatial and channel dimensions. To alleviate the training attention imbalance among different loss functions or spatial regions, the Stochastic Trust Mechanism (STM) is designed to stochastically modify the elements of joint confidence map in the training phase. Finally, we design a calibrating operation to alternately optimize the joint confidence branch and the other parts of JCNet to avoid overfiting. The proposed methods achieve state-of-the-art performance in both geometric-semantic prediction and uncertainty estimation on NYU-Depth V2 and Cityscapes.

Hydroxylation with Unusual Stereoinversion Catalyzed by an FeII /2-OG Dependent Oxidase and 3,6-Diene-2,5-diketopiperazine Formation in the Biosynthesis of Brevianamide†K.

Natural products with the 3,6-diene-2,5-diketopiperazine core are widely distributed in nature; however, the biosynthetic mechanism of 3,6-diene-2,5-diketopiperazine in fungi remains to be further elucidated. Through heterologous expression and biochemical investigation of an FeII /2-oxoglutarate-dependent oxidase (AspE) and a heme-dependent P450 enzyme (AspF), we report that AspE, AspF and subsequent dehydration account for the formation of the 3,6-diene-2,5-diketopiperazine substructure of brevianamide K from Aspergillus sp. SK-28, a symbiotic fungus of mangrove plant Kandelia candel. More interestingly, in-depth investigation of the enzymatic mechanism showed that AspE promotes hydroxylation of brevianamide Q with unprecedented stereoinversion through hydrogen atom abstraction and water nucleophilic attack from the opposite face of the resultant iminium cation intermediate.

Production of the antifungal biopesticide physcion through the combination of microbial fermentation and chemical post-treatment.

Physcion is an anthraquinone compound observed dominantly in medicinal herbs. This anthraquinone possesses a variety of pharmaceutically important activities and has been developed to be a widely used antifungal biopesticide. Herein, we report on the effective preparation of 3R-torosachrysone (4), a tetrahydroanthracene precursor of physcion, in Aspergillus oryzae NSAR1 by heterologous expression of related genes mined from the phlegmacins-producing ascomycete Talaromyces sp. F08Z-0631. Conditions for converting 4 into physcion were studied and optimized, leading to the development of a concise approach for extracting high-purity physcion from the alkali-treated fermentation broth of the 4-producing A. oryzae strain.

DMMIC derivatization-assisted liquid chromatography-mass spectrometry method for metabolite profiling of the glutathione anabolic pathway in esophageal cancer tissues and cells.

In this work, a new pyrylium derivatization-assisted liquid chromatography-mass spectrometry (LC-MS) method was developed for metabolite profiling of the glutathione anabolic pathway (GAP) in cancer tissues and cells. The pyrylium salt of 6,7-dimethoxy-3-methyl isochromenylium tetrafluoroborate (DMMIC) was used to label the amino group of metabolites, and a reductant of dithiothreitol (DTT) was employed to stabilize the thiol group. By combining DMMIC derivatization with LC-MS, it was feasible to quantify the 13 main metabolites on the GAP in complex biological samples, which had good linearity (R2 = 0.9981-0.9999), precision (interday precision of 1.6%-19.0% and intraday precision of 1.4%-19.8%) and accuracy (83.4%-115.7%). Moreover, the recovery assessments in tissues (82.5%-107.3%) and in cells (98.1%-118.9%) with GSH-13C2, 15N, and Cys-15N demonstrated the reliability of the method in detecting tissues and cells. Following a methodological evaluation, the method was applied successfully to investigate difference in the GAP between the carcinoma and para-carcinoma tissues of esophageal squamous cell carcinoma (ESCC) and the effect of p-hydroxycinnamaldehyde (CMSP) on the GAP in KYSE-150 esophageal cancer cells. The results demonstrate that the developed method provides a promising new tool to elucidate the roles of GAP in physiological and pathological processes, which can contribute to research on drugs and diseases.

Hierarchical Superpixel Segmentation by Parallel CRTrees Labeling.

This paper proposes a hierarchical superpixel segmentation by representing an image as a hierarchy of 1-nearest neighbor (1-NN) graphs with pixels/superpixels denoting the graph vertices. The 1-NN graphs are built from the pixel/superpixel adjacent matrices to ensure connectivity. To determine the next-level superpixel hierarchy, inspired by FINCH clustering, the weakly connected components (WCCs) of the 1-NN graph are labeled as superpixels. We reveal that the WCCs of a 1-NN graph consist of a forest of cycle-root-trees (CRTrees). The forest-like structure inspires us to propose a two-stage parallel CRTrees labeling which first links the child vertices to the cycle-roots and then labels all the vertices by the cycle-roots. We also propose an inter-inner superpixel distance penalization and a Lab color lightness penalization base on the property that the distance of a CRTree decreases monotonically from the child to root vertices. Experiments show the parallel CRTrees labeling is several times faster than recent advanced sequential and parallel connected components labeling algorithms. The proposed hierarchical superpixel segmentation has comparable performance to the best performer ETPS (state-of-the-arts) on the BSDS500, NYUV2, and Fash datasets. At the same time, it can achieve 200FPS for 480P video streams.

Mechanistic investigations of hirsutene biosynthesis catalyzed by a chimeric sesquiterpene synthase from Steccherinum ochraceum.

The high efficiency and elegance of terpene synthases is fascinating in constructing the molecular skeleton of complicated terpenoids with multiple chiral centers. Although the rapid development of sequencing technology has led to the discovery of an increasing number of terpene synthases, the cyclization mechanisms of some terpene synthases remains elusive. Here, we report that a chimeric sesquiterpene synthase from Steccherinum ochraceum is responsible for the biosynthesis of (+)-hirsutene, a linear triquinane sesquiterpene. Structural validation, and isotope labeling experiments demonstrate that the biosynthesis of (+)-hirsutene employs an unusual cyclization mode, involving three different cyclization processes (C1-C11, C2-C9, C3-C6), one intramolecular 1,2-hydride shift (C9-C10) and three successive 1,2-alkyl shifts to construct the 5-5-5 fused ring skeleton of (+)-hirsutene.

Unsymmetrically Regioselective Homodimerization Depends on the Subcellular Colocalization of Laccase/Fasciclin Protein in the Biosynthesis of Phlegmacins.

Phlegmacins are homodimeric dihydroanthracenone natural products featuring two torosachrysone monomers unsymmetrically conjugated by 7,10'-coupling. Herein, we report the identification and characterization of the biosynthetic gene cluster of phlegmacins in ascomycete Talaromyces sp. F08Z-0631. On the basis of the heterologous reconstitution of the phlegmacin pathway in Aspergillus oryzae, we demonstrated an unprecedented laccase-involved unsymmetrically regioselective oxidative coupling reaction. The association of laccase PhlC and the fasciclin partner protein PhlB was verified to be indispensable for the coupling activity. Intriguingly, both proteins can be transferred and located independently at the mitochondrial membrane. Notably, only their subcellular colocalization led to the occurrence of oxidative dimerization. These observations add new insights into the poorly understood catalytic mechanisms of various laccases involved in the biosynthesis of secondary metabolites, particularly those functioning with variable partners.

Investigation of 2,2'-Bipyridine Biosynthesis Reveals a Common Two-Component System for Aldehydes Production by Carboxylate Reduction.

Here, we report a two-component enzymatic system that efficiently catalyzes the reduction of a carboxylate to an aldehyde in the biosynthesis of 2,2'-bipyridine antibiotics caerulomycins. The associated paradigm involves the activation of carboxylate by ATP-dependent adenylation protein CaeF, followed by its reduction catalyzed by CaeB2, a new class of NADPH-dependent aldehyde dehydrogenase (ALDH) that directly reduces AMP-conjugated carboxylate, which is distinct from the known aldehyde-producing enzymes that reduce ACP- or CoA-conjugated carboxylates.

Root Canal Segmentation in CBCT Images by 3D U-Net with Global and Local Combination Loss.

Accurate root canal segmentation provides an important assistance for root canal therapy. The existing research such as level set method have made effective progress in tooth and root canal segmentation. In the current situation, however, doctors are required to specify an initial area for the target root canal manually. In this paper, we propose a fully automatic and high precision root canal segmentation method based on deep learning and hybrid level set constraints. We set up the global image encoder and local region decoder for global localization and local segmentation, and then combine the contour information generated by level set. Through using CLAHE algorithm and a combination loss based on dice loss, we solve the class imbalance problem and improved recognition ability. More accurate and faster root canal segmentation is implemented under the framework of multi-task learning and evaluated by experiments on 78 Cone Beam CT images. The experimental results show that the proposed 3D U-Net had higher segmentation performance than state of the art algorithms. The average dice similarity coefficient (DSC) is 0.952.

Dissection of the Enzymatic Process for Forming a Central Imidazopiperidine Heterocycle in the Biosynthesis of a Series c Thiopeptide Antibiotic.

Thiopeptide antibiotics are a family of ribosomally synthesized and posttranslationally modified peptide natural products of significant interest in anti-infective agent development. These antibiotics are classified into five subfamilies according to differences in the central 6-membered heterocycle of the thiopeptide framework. The mechanism through which imidazopiperidine, the most heavily functionalized central domain characteristic of a series c thiopeptide, is formed remains unclear. Based on mining and characterization of the genes specifically involved in the biosynthesis of Sch40832, we here report an enzymatic process for transforming a series b thiopeptide into a series c product through a series a intermediate. This process starts with F420-dependent hydrogenation of the central dehydropiperidine unit to a saturated piperidine unit. With the activity of a cytochrome P450 monooxygenase, the piperidine-thiazole motif of the intermediate undergoes an unusual oxygenation-mediated rearrangement to provide an imidazopiperidine heterocycle subjected to further S-methylation and aldehyde reduction. This study represents the first biochemical reconstitution of the pathway forming a stable series c thiopeptide.

Triptolide: reflections on two decades of research and prospects for the future.

Covering: 2000 to 2020 Triptolide is a bioactive diterpene triepoxide isolated from Tripterygium wilfordii Hook F, a traditional Chinese medicinal plant whose extracts have been used as anti-inflammatory and immunosuppressive remedies for centuries. Although triptolide and its analogs exhibit potent bioactivities against various cancers, and inflammatory and autoimmune diseases, none of them has been approved to be used in the clinic. This review highlights advances in material sourcing, molecular mechanisms, clinical progress and new drug design strategies for triptolide over the past two decades, along with some prospects for the future course of development of triptolide.

Segment-Based Disparity Refinement With Occlusion Handling for Stereo Matching.

In this paper, we propose a disparity refinement method that directly refines the winner-take-all (WTA) disparity map by exploring its statistical significance. According to the primary steps of the segment-based stereo matching, the reference image is over-segmented into superpixels and a disparity plane is fitted for each superpixel by an improved random sample consensus (RANSAC). We design a two-layer optimization to refine the disparity plane. In the global optimization, mean disparities of superpixels are estimated by Markov random field (MRF) inference, and then, a 3D neighborhood system is derived from the mean disparities for occlusion handling. In the local optimization, a probability model exploiting Bayesian inference and Bayesian prediction is adopted and achieves second-order smoothness implicitly among 3D neighbors. The two-layer optimization is a pure disparity refinement method because no correlation information between stereo image pairs is demanded during the refinement. Experimental results on the Middlebury and KITTI datasets demonstrate that the proposed method can perform accurate stereo matching with a faster speed and handle the occlusion effectively. It can be indicated that the "matching cost computation + disparity refinement" framework is a possible solution to produce accurate disparity map at low computational cost.

Simulation of orthodontic force of archwire applied to full dentition using virtual bracket displacement method.

OBJECTIVE: Orthodontic force simulation of tooth provides important guidance for clinical orthodontic treatment. However, previous studies did not involve the simulation of orthodontic force of archwire applied to full dentition. This study aimed to develop a method to simulate orthodontic force of tooth produced by loading a continuous archwire to full dentition using finite element method. METHOD: A three-dimensional tooth-periodontal ligament-bone complex model of mandible was reconstructed from computed tomography images, and models of brackets and archwire were built. The simulation was completed through two steps. First, node displacements of archwire before and after loading were estimated through moving virtual brackets to drive archwire deformation. Second, the obtained node displacements were loaded to implement the loading of archwire, and orthodontic force was calculated. An orthodontic force tester (OFT) was used to measure orthodontic force in vitro for the validation. RESULTS: After the simulation convergence, archwire was successfully loaded to brackets, and orthodontic force of teeth was obtained. Compared with the measured orthodontic force using the OFT, the absolute difference of the simulation results ranged from 0.5 to 22.7 cN for force component and ranged from 2.2 to 80.0 cN•mm for moment component, respectively. The relative difference of the simulation results ranged from 2.5% to 11.0% for force component, and ranged from 0.6% to 14.7% for moment component, respectively. CONCLUSIONS: The developed orthodontic force simulation method based on virtual bracket displacement can be used to simulate orthodontic force provided by the archwire applied to full dentition.

Discovery of caerulomycin/collismycin-type 2,2'-bipyridine natural products in the genomic era.

2,2'-Bipyridine (2,2'-BP) is the unique molecular scaffold of the bioactive natural products represented by caerulomycins (CAEs) and collismycins (COLs). CAEs and COLs are highly similar in the chemical structures in which their 2,2'-BP cores typically contain a di- or tri-substituted ring A and an unmodified ring B. Here, we summarize the CAE and COL-type 2,2'-BP natural products known or hypothesized to date: (1) isolated using methods traditional for natural product characterization, (2) created by engineering the biosynthetic pathways of CAEs or COLs, and (3) predicted upon bioinformatics-guided genome mining. The identification of these CAE and COL-type 2,2'-BP natural products not only demonstrates the development of research techniques and methods in the field of natural product chemistry but also reflects the general interest in the discovery of CAE and COL-type 2,2'-BP natural products.

A Method for Tooth Model Reconstruction Based on Integration of Multimodal Images.

A complete digital tooth model is needed for computer-aided orthodontic treatment. However, current methods mainly use computed tomography (CT) images to reconstruct the tooth model which may require multiple CT scans during orthodontic progress, and the reconstructed model is also inaccurate in crown area. This study developed a tooth model reconstruction method based on integration of CT images and laser scan images to overcome these disadvantages. In the method, crown models and complete tooth models are first reconstructed, respectively, from laser scan images and CT images. Then, crown models from laser scan images and tooth models from CT images are registered. Finally, the crown from laser scan images and root from CT images were fused to obtain a new tooth model. Experimental results verified that the developed method is effective to generate the complete tooth model by integrating CT images and laser scan images. Using the proposed method, the reconstructed models provide more accurate crown than CT images, and it is feasible to obtain complete tooth models at any stage of orthodontic treatment by using one CT scan at the pretreatment stage and one laser scan at that stage to avoid multiple CT scans.