Effects of Polysaccharides from Enteromorpha prolifera on Hepatorenal Syndrome in Mice

[Objectives]This study was conducted to evaluate the protective effect of polysaccharides from Enteromorpha prolifera(PEP)on mice with hepatorenal syndrome induced by carbon tetrachloride.[Methods]A mouse hepatorenal syndrome model was induced by carbon tetrachloride.The serum levels of lipid,total antioxidant capacity,liver and kidney function,pathological changes of liver and kidney were selected to clarity the effectiveness of PEP on hepatorenal syndrome in mice.[Results]PEP effectively lowered the serum levels of lipid,increased total antioxidant capacity,improved liver and kidney injury,and alleviated pathological changes of liver and kidney of mice induced by carbon tetrachloride.[Conclusions]PEP has a potent preventive effect on hepatorenal syndrome induced by carbon tetrachloride in mice,which provides theoretical support for future clinical application of PEP.

A self-monitoring microneedle patch for light-controlled synergistic treatment of melanoma

Melanoma is the most aggressive and malignant form of skin cancer.Current melanoma treatment methods generally suffer from frequent drug administration as well as difficulty in direct monitoring of drug release.Here,a self-monitoring microneedle(MN)-based drug delivery system,which integrates a dissolving MN patch with aggregation-induced emission(AIE)-active PATC microparticles,is designed to achieve light-controlled pulsatile chemo-photothermal synergistic therapy of melanoma.The PATC polymeric particles,termed D/I@PATC,encapsulate both of chemotherapeutic drug doxorubicin(DOX)and the photothermal agent indocyanine green(ICG).Upon light illumination,PATC gradually dissociates into smaller particles,causing the release of encapsulated DOX and subsequent fluorescence intensity change of PATC particles,thereby not only enabling direct observation of the drug release process under light stimuli,but also facilitating verification of drug release by fluorescence recovery after light trigger.Moreover,encapsulation of ICG in PATC particles displays significant improvement of its photothermal stability both in vitro and in vivo.In a tumor-bearing mouse,the application of one D/I@PATC MN patch combining with two cycles of light irradiation showed excellent controllable chemo-photothermal efficacy and exhibited~97%melanoma inhibition rate without inducing any evident systemic toxicity,suggesting a great potential for skin cancer treatment in clinics.

Construction and application of high-quality genome-scale metabolic model of Zymomonas mobilis to guide rational design of microbial cell factories

High-quality genome-scale metabolic models(GEMs)could play critical roles on rational design of microbial cell factories in the classical Design-Build-Test-Learn cycle of synthetic biology studies.Despite of the constant establishment and update of GEMs for model microorganisms such as Escherichia coli and Saccharomyces cerevisiae,high-quality GEMs for non-model industrial microorganisms are still scarce.Zymomonas mobilis subsp.mobilis ZM4 is a non-model ethanologenic microorganism with many excellent industrial characteristics that has been developing as microbial cell factories for biochemical production.Although five GEMs of Z.mobilis have been constructed,these models are either generating ATP incorrectly,or lacking information of plasmid genes,or not providing standard format file.In this study,a high-quality GEM iZM516 of Z.mobilis ZM4 was constructed.The information from the improved genome annotation,literature,datasets of Biolog Phenotype Microarray studies,and recently updated Gene-Protein-Reaction information was combined for the curation of iZM516.Finally,516 genes,1389 reactions,1437 metabolites,and 3 cell compartments are included in iZM516,which also had the highest MEMOTE score of 91%among all published GEMs of Z.mobilis.Cell growth was then predicted by iZM516,which had 79.4%agreement with the experimental results of the substrate utilization.In addition,the potential endogenous succinate synthesis pathway of Z.mobilis ZM4 was proposed through simulation and analysis using iZM516.Furthermore,metabolic engineering strategies to produce succinate and 1,4-butanediol(1,4-BDO)were designed and then simulated under anaerobic condition using iZM516.The results indicated that 1.68 mol/mol succinate and 1.07 mol/mol 1,4-BDO can be achieved through combinational metabolic engineering strategies,which was comparable to that of the model species E.coli.Our study thus not only established a high-quality GEM iZM516 to help understand and design microbial cell factories for economic biochemical production using Z.mobilis as the chassis,but also provided guidance on building accurate GEMs for other non-model industrial microorganisms.

Reconstruction and metabolic profiling of the genome-scale metabolic network model of Pseudomonas stutzeri A1501

Pseudomonas stutzeri A1501 is a non-fluorescent denitrifying bacteria that belongs to the gram-negative bacterial group.As a prominent strain in the fields of agriculture and bioengineering,there is still a lack of comprehensive understanding regarding its metabolic capabilities,specifically in terms of central metabolism and substrate utilization.Therefore,further exploration and extensive studies are required to gain a detailed insight into these aspects.This study reconstructed a genome-scale metabolic network model for P.stutzeri A1501 and conducted extensive curations,including correcting energy generation cycles,respiratory chains,and biomass composition.The final model,iQY1018,was successfully developed,covering more genes and reactions and having higher prediction accuracy compared with the previously published model iPB890.The substrate utilization ability of 71 carbon sources was investigated by BIOLOG experiment and was utilized to validate the model quality.The model prediction accuracy of substrate utilization for P.stutzeri A1501 reached 90%.The model analysis revealed its new ability in central metabolism and predicted that the strain is a suitable chassis for the production of Acetyl CoA-derived products.This work provides an updated,high-quality model of P.stutzeri A1501for further research and will further enhance our understanding of the metabolic capabilities.

Enzyme Commission Number Prediction and Benchmarking with Hierarchical Dual-core Multitask Learning Framework

Enzyme commission(EC)numbers,which associate a protein sequence with the biochemical reactions it catalyzes,are essential for the accurate understanding of enzyme functions and cellular metabolism.Many ab initio computational approaches were proposed to predict EC numbers for given input protein sequences.However,the prediction performance(accuracy,recall,and precision),usability,and efficiency of existing methods decreased seriously when dealing with recently discovered proteins,thus still having much room to be improved.Here,we report HDMLF,a hierarchical dual-core multitask learning framework for accurately predicting EC numbers based on novel deep learning techniques.HDMLF is composed of an embedding core and a learning core;the embedding core adopts the latest protein language model for protein sequence embedding,and the learning core conducts the EC number prediction.Specifically,HDMLF is designed on the basis of a gated recurrent unit framework to perform EC number prediction in the multi-objective hierarchy,multitasking manner.Additionally,we introduced an attention layer to optimize the EC prediction and employed a greedy strategy to integrate and fine-tune the final model.Comparative analyses against 4 representative methods demonstrate that HDMLF stably delivers the highest performance,which improves accuracy and F1 score by 60%and 40%over the state of the art,respectively.An additional case study of tyrB predicted to compensate for the loss of aspartate aminotransferase aspC,as reported in a previous experimental study,shows that our model can also be used to uncover the enzyme promiscuity.Finally,we established a web platform,namely,ECRECer(https://ecrecer.biodesign.ac.cn),using an entirely could-based serverless architecture and provided an offline bundle to improve usability.

海洋氮循环过程及基于基因组代谢网络模型的预测

海洋氮循环在地球元素循环中充当着必不可少的角色。海洋氮循环是由一系列氧化还原反应构成的生物化学过程。固氮作用和氮同化作用为生态系统提供了生物可用氮(铵盐)。硝化作用可进一步将铵盐氧化为硝酸盐,硝酸盐又可以通过反硝化作用转化为氮气。整个氮循环实现了海洋中不同含氮无机盐间的转换。微生物是海洋氮循环的重要驱动者,海洋氮循环的研究可以帮助理解海洋生物与地球环境相互作用及协同演化的机制,从而更好地保护地球生态环境。随着氮循环关键微生物基因组尺度代谢网络模型的发表,研究者可以利用代谢网络模型来研究不同氮循环过程的效率、环境因子对氮循环过程的影响以及解析氮循环及生物网络的内在机理等,从而帮助人们更深入地研究海洋氮转化机制。本文主要综述了海洋氮循环过程中各个转化过程的主要微生物,以及基因组尺度代谢网络模型在分析氮循环中的应用。

Estimating the quarantine failure rate for COVID-19

Quarantine is a crucial control measure in reducing imported COVID-19 cases and community transmissions.However,some quarantined COVID-19 patients may show symptoms after finishing quarantine due to a long median incubation period,potentially causing community transmissions.To assess the recommended 14-day quarantine policy,we develop a formula to estimate the quarantine failure rate from the incubation period distribution and the epidemic curve.We found that the quarantine failure rate increases with the exponential growth rate of the epidemic curve.We apply our formula to United States,Canada,and Hubei Province,China.Before the lockdown of Wuhan City,the quarantine failure rate in Hubei Province is about 4.1%.If the epidemic curve flattens or slowly decreases,the failure rate is less than 2.8%.The failure rate in US may be as high as 8.3%-11.5%due to a shorter 10-day quarantine period,while the failure rate in Canada may be between 2.5%and 3.9%.A 21-day quarantine period may reduce the failure rate to 0.3%-0.5%.

Construction and analysis of an integrated biological network of Escherichia coli

Escherichia coli is a model organism with a clear genetic background that is widely used in metabolic engineering and synthetic biology research.To gain a complete picture of the complexly metabolic and regulatory interactions in E.coli,researchers often need to retrieve information from various databases which cover diferent types of interactions.A central one-stop service integrating various molecular interactions in E.coli would be helpful for the community.We constructed a database called E.coli integrated network(EcoIN)by integrating known molecular interaction information from databases and literature.EcoIN contains nearly 160,000 pairs of interactions and users can easily search the diferent types of interacting partners for a metabolite,gene or protein,and thus gain access to a more comprehensive interaction map of E.coli.To illustrate the application of EcoIN,we used the full path algorithm to identify metabolic feedback/feedforward regulatory loops having at least two diferent types of regulatory interactions.Applying this algorithm to analyze the regulatory loops for the amino acid biosynthetic pathways,we found some multi-step regulation loops which may afect the metabolic fux and are potential new engineering targets.The EcoIN database is freely accessible at http://ecoin.ibiodesign.net/and analysis codes are available at GitHub:https://github.com/maozhitao/EcoIN.