novoPathFinder: a webserver of designing novel-pathway with integrating GEM-model

To increase the number of value-added chemicals that can be produced by metabolic engineering and synthetic biology, constructing metabolic space with novel reactions/pathways is crucial. However, with the large number of reactions that existed in the metabolic space and complicated metabolisms within hosts, identifying novel pathways linking two molecules or heterologous pathways when engineering a host to produce a target molecule is an arduous task. Hence, we built a user-friendly web server, novoPathFinder, which has several features: (i) enumerate novel pathways between two specified molecules without considering hosts; (ii) construct heterologous pathways with known or putative reactions for producing target molecule within Escherichia coli or yeast without giving precursor; (iii) estimate novel pathways with considering several categories, including enzyme promiscuity, Synthetic Complex Score (SCScore) and LD50 of intermediates, overall stoichiometric conversions, pathway length, theoretical yields and thermodynamic feasibility. According to the results, novoPathFinder is more capable to recover experimentally validated pathways when comparing other rule-based web server tools. Besides, more efficient pathways with novel reactions could also be retrieved for further experimental exploration. novoPathFinder is available at http://design.rxnfinder.org/novopathfinder/

Clinical cure induced by pegylated interferon α-2b in the advantaged population of chronic hepatitis B virus infection: a retrospective cohort study

BackgroundAmong the advantaged population with clinical cure of chronic hepatitis B, chronic inactive hepatitis B virus carriers (IHCs) and nucleoside analog-experienced patients have similar serological manifestations. This study established non-interferon-treated groups as controls to compare the efficacy of pegylated interferon α-2b (Peg-IFNα-2b) in achieving clinical cure between IHCs and nucleoside analog (NA)-experienced patients.MethodA total of 270 patients were enrolled in this observational study. The IHC cohort comprised 55 patients who received Peg-IFNα-2b (Peg-IFN group), and the other 70 patients did not receive any antiviral treatment (untreated group). Patients treated with NAs were divided into two groups: one group (70 patients) receiving NA add-on Peg-IFNα-2b therapy regimen (NA add-on Peg-IFN group) and another group (75 patients) receiving continuous NA monotherapy (NA group). The primary endpoints were hepatitis B surface antigen (HBsAg) clearance and HBsAg seroconversion at 48 weeks and 72 weeks.ResultsAt 48 weeks, 65.5% (36/55) and 52.9% (37/70) patients achieved HBsAg clearance in the Peg-IFN group and NA add-on Peg-IFN group, respectively (p = 0.156). HBsAg seroconversion was achieved in 47.3% (26/55) of the Peg-IFN group and 34.3% (24/70) of the NA add-on Peg-IFN group (p = 0.141). At the follow-up of 72 weeks, 36 patients in the Peg-IFN group achieved HBsAg loss (65.5%, 36/55), and 33 patients in the NA add-on Peg-IFN group achieved HBsAg clearance (47.1%, 33/70), which were significantly higher than in the Peg-IFN group (p = 0.041). The HBsAg seroconversion rates in the Peg-IFN group and NA add-on Peg-IFN group at 72 weeks were 45.5% (25/55) and 32.9% (23/70), respectively (p = 0.151). No patient achieved HBsAg clearance or seroconversion in the NA group and untreated group. Furthermore, the receiver operating characteristic curve showed baseline HBsAg< 72 IU/mL, and the decline of HBsAg of more than 80% and 98% from baseline to 12 and 24 weeks provided good predictions for HBsAg clearance. Meanwhile, 77% of patients with baseline HBsAg< 100 IU/mL achieved a clinical cure at 48 weeks.ConclusionPeg-IFNα-2b results in a high rate of HBsAg clearance and seroconversion in both IHCs and NA-experienced patients, especially for those patients who have HBsAg below 100 IU/mL

HCV induces transforming growth factor β1 through activation of endoplasmic reticulum stress and the unfolded protein response

HCV replication disrupts normal endoplasmic reticulum (ER) function and activates a signaling network called the unfolded protein response (UPR). UPR is directed by three ER transmembrane proteins including ATF6, IRE1, and PERK. HCV increases TGF-β1 and oxidative stress, which play important roles in liver fibrogenesis. HCV has been shown to induce TGF-β1 through the generation of reactive oxygen species (ROS) and p38 MAPK, JNK, ERK1/2, and NFκB-dependent pathways. However, the relationship between HCV-induced ER stress and UPR activation with TGF-β1 production has not been fully characterized. In this study, we found that ROS and JNK inhibitors block HCV up-regulation of ER stress and UPR activation. ROS, JNK and IRE1 inhibitors blocked HCV-activated NFκB and TGF-β1 expression. ROS, ER stress, NFκB, and TGF-β1 signaling were blocked by JNK specific siRNA. Knockdown IRE1 inhibited JFH1-activated NFκB and TGF-β1 activity. Knockdown of JNK and IRE1 blunted JFH1 HCV up-regulation of NFκB and TGF-β1 activation. We conclude that HCV activates NFκB and TGF-β1 through ROS production and induction of JNK and the IRE1 pathway. HCV infection induces ER stress and the UPR in a JNK-dependent manner. ER stress and UPR activation partially contribute to HCV-induced NF-κB activation and enhancement of TGF-β1

MicroRNA 130a Regulates both Hepatitis C Virus and Hepatitis B Virus Replication through a Central Metabolic Pathway

ABSTRACT Hepatitis C virus (HCV) infection has been shown to regulate microRNA 130a (miR-130a) in patient biopsy specimens and in cultured cells. We sought to identify miR-130a target genes and to explore the mechanisms by which miR-130a regulates HCV and hepatitis B virus (HBV) replication. We used bioinformatics software, including miRanda, TargetScan, PITA, and RNAhybrid, to predict potential miR-130a target genes. miR-130a and its target genes were overexpressed or were knocked down by use of small interfering RNA (siRNA) or clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 guide RNA (gRNA). Selected gene mRNAs and their proteins, together with HCV replication in OR6 cells, HCV JFH1-infected Huh7.5.1 cells, and HCV JFH1-infected primary human hepatocytes (PHHs) and HBV replication in HepAD38 cells, HBV-infected NTCP-Huh7.5.1 cells, and HBV-infected PHHs, were measured by quantitative reverse transcription-PCR (qRT-PCR) and Western blotting, respectively. We selected 116 predicted target genes whose expression was related to viral pathogenesis or immunity for qPCR validation. Of these, the gene encoding pyruvate kinase in liver and red blood cell (PKLR) was confirmed to be regulated by miR-130a overexpression. miR-130a overexpression (via a mimic) knocked down PKLR mRNA and protein levels. A miR-130a inhibitor and gRNA increased PKLR expression, HCV replication, and HBV replication, while miR-130a gRNA and PKLR overexpression increased HCV and HBV replication. Supplemental pyruvate increased HCV and HBV replication and rescued the inhibition of HCV and HBV replication by the miR-130a mimic and PKLR knockdown. We concluded that miR-130a regulates HCV and HBV replication through its targeting of PKLR and subsequent pyruvate production. Our data provide novel insights into key metabolic enzymatic pathway steps regulated by miR-130a, including the steps involving PKLR and pyruvate, which are subverted by HCV and HBV replication. IMPORTANCE: We identified that miR-130a regulates the target gene PKLR and its subsequent effect on pyruvate production. Pyruvate is a key intermediate in several metabolic pathways, and we identified that pyruvate plays a key role in regulation of HCV and HBV replication. This previously unrecognized, miRNA-regulated antiviral mechanism has implications for the development of host-directed strategies to interrupt the viral life cycle and prevent establishment of persistent infection for HCV, HBV, and potentially other viral infections

Robust Drivable Road Region Detection for Fixed-Route Autonomous Vehicles Using Map-Fusion Images

Environment perception is one of the major issues in autonomous driving systems. In particular, effective and robust drivable road region detection still remains a challenge to be addressed for autonomous vehicles in multi-lane roads, intersections and unstructured road environments. In this paper, a computer vision and neural networks-based drivable road region detection approach is proposed for fixed-route autonomous vehicles (e.g., shuttles, buses and other vehicles operating on fixed routes), using a vehicle-mounted camera, route map and real-time vehicle location. The key idea of the proposed approach is to fuse an image with its corresponding local route map to obtain the map-fusion image (MFI) where the information of the image and route map act as complementary to each other. The information of the image can be utilized in road regions with rich features, while local route map acts as critical heuristics that enable robust drivable road region detection in areas without clear lane marking or borders. A neural network model constructed upon the Convolutional Neural Networks (CNNs), namely FCN-VGG16, is utilized to extract the drivable road region from the fused MFI. The proposed approach is validated using real-world driving scenario videos captured by an industrial camera mounted on a testing vehicle. Experiments demonstrate that the proposed approach outperforms the conventional approach which uses non-fused images in terms of detection accuracy and robustness, and it achieves desirable robustness against undesirable illumination conditions and pavement appearance, as well as projection and map-fusion errors

Real Pseudo-Lidar Point Cloud Fusion for 3D Object Detection

Three-dimensional object detection technology is an essential component of autonomous driving systems. Existing 3D object detection techniques heavily rely on expensive lidar sensors, leading to increased costs. Recently, the emergence of Pseudo-Lidar point cloud data has addressed this cost issue. However, the current methods for generating Pseudo-Lidar point clouds are relatively crude, resulting in suboptimal detection performance. This paper proposes an improved method to generate more accurate Pseudo-Lidar point clouds. The method first enhances the stereo-matching network to improve the accuracy of Pseudo-Lidar point cloud representation. Secondly, it fuses 16-Line real lidar point cloud data to obtain more precise Real Pseudo-Lidar point cloud data. Our method achieves impressive results in the popular KITTI benchmark. Our algorithm achieves an object detection accuracy of 85.5% within a range of 30 m. Additionally, the detection accuracies for pedestrians and cyclists reach 68.6% and 61.6%, respectively

MCF2Chem: A manually curated knowledge base of biosynthetic compound production

Abstract Background Microbes have been used as cell factories to synthesize various chemical compounds. Recent advances in synthetic biological technologies have accelerated the increase in the number and capacity of microbial cell factories; the variety and number of synthetic compounds produced via these cell factories have also grown substantially. However, no database is available that provides detailed information on the microbial cell factories and the synthesized compounds. Results In this study, we established MCF2Chem, a manually curated knowledge base on the production of biosynthetic compounds using microbial cell factories. It contains 8888 items of production records related to 1231 compounds that were synthesizable by 590 microbial cell factories, including the production data of compounds (titer, yield, productivity, and content), strain culture information (culture medium, carbon source/precursor/substrate), fermentation information (mode, vessel, scale, and condition), and other information (e.g., strain modification method). The database contains statistical analyses data of compounds and microbial species. The data statistics of MCF2Chem showed that bacteria accounted for 60% of the species and that “fatty acids”, “terpenoids”, and “shikimates and phenylpropanoids” accounted for the top three chemical products. Escherichia coli, Saccharomyces cerevisiae, Yarrowia lipolytica, and Corynebacterium glutamicum synthesized 78% of these chemical compounds. Furthermore, we constructed a system to recommend microbial cell factories suitable for synthesizing target compounds and vice versa by combining MCF2Chem data, additional strain- and compound-related data, the phylogenetic relationships between strains, and compound similarities. Conclusions MCF2Chem provides a user-friendly interface for querying, browsing, and visualizing detailed statistical information on microbial cell factories and their synthesizable compounds. It is publicly available at https://mcf.lifesynther.com . This database may serve as a useful resource for synthetic biologists

RDBridge: a knowledge graph of rare diseases based on large-scale text mining

Motivation: Despite low prevalence, rare diseases affect 300 million people worldwide. Research on pathogenesis and drug development lags due to limited commercial potential, insufficient epidemiological data, and a dearth of publications. The unique characteristics of rare diseases, including limited annotated data, intricate processes for extracting pertinent entity relationships, and difficulties in standardizing data, represent challenges for text mining. Results: We developed a rare disease data acquisition framework using text mining and knowledge graphs and constructed the most comprehensive rare disease knowledge graph to date, Rare Disease Bridge (RDBridge). RDBridge offers search functions for genes, potential drugs, pathways, literature, and medical imaging data that will support mechanistic research, drug development, diagnosis, and treatment for rare diseases. Availability and implementation: RDBridge is freely available at http://rdb.lifesynther.com/.ISSN:1367-4803ISSN:1460-205

Protective Effect of Ginsenoside Rg1 on Hematopoietic Stem/Progenitor Cells through Attenuating Oxidative Stress and the Wnt/β-Catenin Signaling Pathway in a Mouse Model of d-Galactose-induced Aging

Stem cell senescence is an important and current hypothesis accounting for organismal aging, especially the hematopoietic stem cell (HSC). Ginsenoside Rg1 is the main active pharmaceutical ingredient of ginseng, which is a traditional Chinese medicine. This study explored the protective effect of ginsenoside Rg1 on Sca-1+ hematopoietic stem/progenitor cells (HSC/HPCs) in a mouse model of d-galactose-induced aging. The mimetic aging mouse model was induced by continuous injection of d-gal for 42 days, and the C57BL/6 mice were respectively treated with ginsenoside Rg1, Vitamin E or normal saline after 7 days of d-gal injection. Compared with those in the d-gal administration alone group, ginsenoside Rg1 protected Sca-1+ HSC/HPCs by decreasing SA-β-Gal and enhancing the colony forming unit-mixture (CFU-Mix), and adjusting oxidative stress indices like reactive oxygen species (ROS), total anti-oxidant (T-AOC), superoxide dismutase (SOD), glutathione peroxidase (GSH-px) and malondialdehyde (MDA). In addition, ginsenoside Rg1 decreased β-catenin and c-Myc mRNA expression and enhanced the phosphorylation of GSK-3β. Moreover, ginsenoside Rg1 down-regulated advanced glycation end products (AGEs), 4-hydroxynonenal (4-HNE), phospho-histone H2A.X (r-H2A.X), 8-OHdG, p16Ink4a, Rb, p21Cip1/Waf1 and p53 in senescent Sca-1+ HSC/HPCs. Our findings indicated that ginsenoside Rg1 can improve the resistance of Sca-1+ HSC/HPCs in a mouse model of d-galactose-induced aging through the suppression of oxidative stress and excessive activation of the Wnt/β-catenin signaling pathway, and reduction of DNA damage response, p16Ink4a-Rb and p53-p21Cip1/Waf1 signaling

SynBioTools: a one-stop facility for searching and selecting synthetic biology tools

Abstract Background The rapid development of synthetic biology relies heavily on the use of databases and computational tools, which are also developing rapidly. While many tool registries have been created to facilitate tool retrieval, sharing, and reuse, no relatively comprehensive tool registry or catalog addresses all aspects of synthetic biology. Results We constructed SynBioTools, a comprehensive collection of synthetic biology databases, computational tools, and experimental methods, as a one-stop facility for searching and selecting synthetic biology tools. SynBioTools includes databases, computational tools, and methods extracted from reviews via SCIentific Table Extraction, a scientific table-extraction tool that we built. Approximately 57% of the resources that we located and included in SynBioTools are not mentioned in bio.tools, the dominant tool registry. To improve users’ understanding of the tools and to enable them to make better choices, the tools are grouped into nine modules (each with subdivisions) based on their potential biosynthetic applications. Detailed comparisons of similar tools in every classification are included. The URLs, descriptions, source references, and the number of citations of the tools are also integrated into the system. Conclusions SynBioTools is freely available at https://synbiotools.lifesynther.com/ . It provides end-users and developers with a useful resource of categorized synthetic biology databases, tools, and methods to facilitate tool retrieval and selection