基于雨课堂的学情分析在研究生教学中的探索与应用——以“系统生物学与生物信息学”课程为例

“系统生物学与生物信息学”是一门学科交叉性和实践性很强的课程,尤为重视学生综合应用知识和动手操作能力的培养,强调学生创新思维的形成。在成果导向教育理念的指导下,在以学生为中心的新型教学模式下,多种现代化教学工具应运而生。雨课堂带来的学生互动与情景教学模式,助力于传统的课堂教学。在课程教学中实施基于雨课堂的学情分析策略,贯穿课前、课中和课后各个环节,能够提高课堂学习效率,提升学生学习兴趣,培养学生创新思维,达成学生成为课堂主体这一目标。

基于师范教育改革背景下《生物信息学》课程建设探索与实践

师范教育改革下高师院校课程的重新建设已成为重中之重。如何在改革的新背景下建构合适的课程体系,成为高师院校要解决的问题。本文立足于师范教育改革背景下的需求,针对《生物信息学》课程的特点和教学中存在的问题进行初步探讨,就其在教学方法的更新、教学标准的编写、考核方法的改进等方面提出了一些思考,希望通过不断的完善从而提高《生物信息学》课程的教学质量。

脓肿分枝杆菌非溶血性磷脂酶C蛋白MAB_0555基因克隆测序及生物信息学分析

目的克隆脓肿分枝杆菌(Mycobacterium abscessus,M.abscessus)非溶血性磷脂酶C基因MAB_0555,并对其测序以及生物信息学分析,为进一步研究其生物学功能及其在脓肿分枝杆菌致病机制中的作用提供基础。方法以脓肿分枝杆菌基因组DNA为模板,PCR扩增非溶血性磷脂酶C的基因片段,克隆入pQE-30质粒,构建重组原核表达载体pQE-30-MAB_0555,将其转化入大肠埃希菌DH5α,并进行序列测定及利用生物信息学软件DNAstar 5.0分析其生物学特性。结果 PCR扩增获得长1440 bp的MAB_0555基因片段,编码479个氨基酸,DNAstar等软件预测其蛋白质相对分子量(Mr)约为53 kD,并显示出具有良好的抗原性。结论成功获得序列正确的脓肿分枝杆菌MAB-0555基因,为其重组蛋白的表达及其相关研究奠定基础。

基于生物信息学分析肺炎链球菌LytR蛋白特征

目的研究肺炎链球菌spr1759(LytR)蛋白的基本理化性质,初步分析预测该蛋白的结构与功能。方法利用Bioedit、TMHMM、TargetP和ExPASy等多种生物信息学软件对肺炎链球菌spr1759蛋白进行分析,并对其功能预测。利用TMHMM软件对比肺炎链球菌spr1759蛋白与炭疽芽孢杆菌BAS5115蛋白和枯草芽孢杆菌DJ97_1211二级结构差异;利用Megalign软件分析它们之间的氨基酸序列相似性。结果肺炎链球菌spr1759蛋白为一亲水性蛋白,其相对分子质量为37.56×10~3,等电点为5.11,存在1个跨膜区。肺炎链球菌spr1759蛋白属于LytR_cpsA_psr超家族,可能具有阴离子细胞壁多聚物合成相关酶的功能。与其他细菌蛋白比对发现,该蛋白与炭疽芽孢杆菌BAS5115蛋白和枯草芽孢杆菌DJ97_1211具有相似的跨膜结构域,均含有1跨膜结构;肺炎链球菌spr1759蛋白与炭疽芽孢杆菌BAS5115蛋白和枯草芽孢杆菌DJ97_1211蛋白氨基酸序列具有较高同源性,全长序列相似性分别为35.7%和32.5%。结论肺炎链球菌LytR蛋白是具有跨膜结构的亲水性蛋白,可能具有阴离子细胞壁多聚物合成相关酶学功能。

鸭坦布苏病毒E基因的分子特性分析

为给鸭坦布苏病毒(duck tembusu virus,DTMUV)囊膜糖蛋白选择良好的抗原域和宿主表达系统提供参考依据,本研究通过选取DTMUV QD株基因文库中的一个重组质粒并测序,结合NCBI的ORF Finder和BLAST工具发现一个全长为1488 bp完整开放阅读框架(Open Reading Frame,ORF)片段。将该ORF编码蛋白通过NCBI的BLASTP分析和DNAstar进化树分析,确定该蛋白与类黄病毒E基因编码的蛋白具有较高的相似性。随后应用生物信息学分析工具Conserved Domains确定保守结构域、运用Signal P4.1预测信号肽、TMHMM 2.0预测跨膜区。应用在线程序Net NGlyc1.0预测糖基化位点,Net Phos2.0预测磷酸化位点、Prot Scale进行疏水性分析。最后运用在线EMBOSS和自动蛋白同源建模数据库进行3D结构预测以及密码子偏爱性分析。结果表明,E蛋白与其它黄病毒衣壳蛋白具有相似的功能,没有信号肽切割位点,在451-468和475-492aa区域含有跨膜区,为相对低表达基因,含有较多种类的稀有密码子,与人密码子使用频率较为接近。这为进一步研究DTMUV E基因的体外表达和宿主选择提供了分子生物学依据。

脂肪干细胞来源外泌体在组织损伤修复中的蛋白组学分析

背景:脂肪干细胞促进损伤修复的研究较多,但从脂肪干细胞来源外泌体角度出发、基于蛋白质组学及生物信息学技术对其进行研究尚属少见。目的:通过蛋白质组学及生物信息学技术,分析糖尿病下肢溃疡患者和健康成年人脂肪干细胞来源外泌体差异表达蛋白,以期筛选诊断及预后标志物。方法:试验组为2018年10月至2019年5月在空军军医大学第二附属医院整形烧伤科接受清创植皮的糖尿病下肢溃疡患者25例、对照组为同期接受吸脂术的健康成年人10名。制备脂肪干细胞、提取外泌体并进行鉴定,从两组中分别随机抽取3例进行蛋白组学研究:利用LFQ技术行蛋白质定量分析;使用clueGO(version2.5.4)对差异表达蛋白行GO和Pathway分析;对差异蛋白进行了蛋白-蛋白间相互作用分析(数据库String,版本11.0,R软件cluster Profiler package,FDR<0.25)。结果与结论:①共筛选出可定量差异表达蛋白231种,其中31种差异有显著性意义,试验组下调表达蛋白29种,上调表达蛋白2种;②差异蛋白与营养、代谢类疾病相关性高;差异表达蛋白所处的细胞位置集中在细胞外囊泡、血小板α颗粒;差异表达蛋白参与的生物学过程为凝血过程及脂质转运;差异蛋白的主要分子功能与酶抑制剂活性、肝素结合能力有关;③PPI和KEGG通路分析显示,试验组表达下调显著的ITGA2B、ITGB3蛋白与病程密切相关,有望成为应用干细胞治疗糖尿病性下肢溃疡的新靶点。

SPARCL1, Shp2, MSH2, E-cadherin, p53, ADCY-2 and MAPK are prognosis-related in colorectal cancer

AIM: To investigate the expression of markers that are correlated with the prognosis of colorectal cancer (CRC) patients. METHODS: One hundred and fifty-six CRC patientswere followed up for more than 3 years after radical surgery. Immunohistochemical (IHC) analysis was performed to detect the expression of 14 pathway-related markers (p53, APC, p21ras, E-cadherin, endothelin-B receptor, Shp2, ADCY-2, SPARCL1, neuroligin1, hsp27, mmp-9, MAPK, MSH2 and rho) in specimens from these patients. Bioinformatics analysis involving a Support Vector Machine (SVM) was used to determine the best prognostic model from combinations of these markers. RESULTS: Seven markers (SPARCL1, Shp2, MSH2, E-cadherin, p53, ADCY-2 and MAPK) were significantly related to the prognosis and clinical pathological features of the CRC patients (P < 0.05). Prognostic models were established through SVM from combinations of these 7 markers and proved able to differentiate patients with dissimilar survival, especially in stage Ⅱ/Ⅲ patients. According to the best prognostic model, the p53/SPARCL1 model, patients having high p53 and low SPARCL1 expression had about 50% lower 3-year survival than others (P < 0.001). CONCLUSION: SPARCL1, Shp2, MSH2, E-cadherin, p53, ADCY-2 and MAPK are potential prognostic markers in CRC. A p53/SPARCL1 bioinformatics model may be used as a supplement to tumor-nodes-metastasis staging.

Network Pharmacology-based Analysis on the Molecular Biological Mechanisms of Xin Hui Tong Formula in Coronary Heart Disease Treatment

Objective To investigate the potential molecular mechanism of Xin Hui Tong Formula (XHTF) in the treatment of coronary heart disease (CHD) by using network pharmacology and bioinformatics. Methods The targets network of CHD was constructed through Therapeutic Targets Database (TTD) and Drugbank database;The XHTF pharmacodynamic molecule-targets network and the XHTF pharmacodynamic molecule-CHD targets network were explored by the traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP). And the multi-targets mechanism and molecular regulation network of XHTF in the treatment of CHD were explored from multiple perspectives by Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) database pathway enrichment analysis. Results A total of 88 CHD targets were screened out through the Therapeutic Targets and the Drugbank database. 393 compounds and corresponding 205 drug targets of XHTF were retrieved from TCMSP. A total of 13 known targets directly related to the development of CHD were retrieved from the disease-related databases: TP53, MAPK14, NFKB1, HSPA5, PLG, PTGS2, ADRB1, NOS2, CYP3A4, GRIA2, CYP2A6, GRIA1, PTGS1. XHTF also contained 118 drug targets that directly interact with CHD targets. GO enrichment analysis showed that the biological processes of 13 direct targets proteins were found to be mainly enriched in response to drug, cellular response to biotic stimulus, long-chain fatty acid metabolic process, fatty acid metabolic process and regulation of blood pressure. KEGG pathway enrichment analysis found that XHTF participated in the CHD pathological process mainly through retrograde endocannabinoid signaling, regulation of lipolysis in adipocytes, cAMP signaling pathway, chemical carcinogenesis and other pathways. Conclusions XHTF plays a role in the treatment of CHD through multiple targets and multiple pathways, and provides a scientific basis for the theory of "virtual standard" in the treatment of CHD.

Molecular cloning and transcriptional analysis of a NPY receptor-like in common Chinese cuttlefish Sepiella japonica

Neuropeptide Y(NPY) has a pivotal role in the regulation of many physiological processes. In this study, the gene encoding a NPY receptor-like from the common Chinese cuttlefish Sepiella japonica( SjNPYR-like) was identified and characterized. The full-length SjNPYR-like cDNA was cloned containing a 492-bp of 5′ untranslated region(UTR), 1 182 bp open reading frame(ORF) encoding a protein of 393 amino acid residues, and 228 bp of 3′ UTR. The putative protein was predicted to have a molecular weight of 45.54 kDa and an isoelectric point(pI) of 8.13. By informatic analyses, SjNPYR-like was identified as belonging to the class A G protein coupled receptor(GPCR) family(the rhodopsin-type). The amino acid sequence contained 12 potential phosphorylation sites and five predicted N-linked glycosylation sites. Multiple sequence alignment and 3D structure modeling were conducted to clarify SjNPYR bioinformatics characteristics. Phylogenetic analysis identifies it as an NPYR with identity of 33% to Lymnaea stagnalis NPFR. Transmembrane properties of SjNPYR-like were demonstrated in vitro using HEK293 cells and the p EGFP-N1 plasmid. Relative quantifi cation of SjNPYR-like mRNA level confi rmed a high level expression and broad distribution of SjNPYR-like in various tissues of female S. japonica. In addition, the transcriptional profile of SjNPYR-like in the brain, liver, and ovary during gonadal development was analyzed. The results provide basic understanding on the molecular characteristics of SjNPYR-like and its potentially physical functions.

Cloning and Bioinformatics Analysis of ZmERECTA-LIKE1 and Construction of Plant Expression Vector

[Objective] This study was conducted to clone and analyze ERECTA-LIKE1 gene in Zea mays by PCR and bioinformatics methods and to construct plant expression vector p Cambia3301-zm ERECTA-LIKE1. [Method] zm ERECTA-LIKE1(zm ERL1)gene was obtained using RT-PCR, and physical-chemical properties were analyzed by bioinformatics methods, including domains,transmembrane regions, N-Glycosylation potential sites phosphorylation sites, and etc. [Result] Bioinformatics results showed that zm ERL1 gene was 2 169 bp, which encoded a protein consisting of 722 amino acids, 11 N-glycosylation potential sites and 42 kinase specific phosphorylation sites. According to CDD2.23 and TMHMM Server v. 2.0 software, there were leucine-rich repeats,a PKC domain and a transmembrane region in this protein. The theoretical p I and molecular weight of zm ERL1 encoded protein was 6.20 and 79 184.8 using Compute PI/Mw tool. Furthermore, we constructed the plant expression vector p Cambia3301-zm ERECTA-LIKE1 by subcloning zm ERL1 gene into p Cambia3301 instead of GUS. [Conclusion] The results provide a theoretical basis for the application of zm ERL1 gene in future study.

Building a Tree Adjusted Logistic Classification Model in Biomarker Data Analyses

Researchers in bioinformatics, biostatistics and other related fields seek biomarkers for many purposes, including risk assessment, disease diagnosis and prognosis, which can be formulated as a patient classification. In this paper, a new method of using a tree regression to improve logistic classification model is introduced in biomarker data analysis. The numerical results show that the linear logistic model can be significantly improved by a tree regression on the residuals. Although the classification problem of binary responses is discussed in this research, the idea is easy to extend to the classification of multinomial responses.

Exploring the Action Mechanism of Yadanzi(Brucea javanica)in the Treatment of Glioblastoma Based on Bioinformatics and Network Pharmacology

ObjectiveThe aim of the study is to explore the molecular mechanism of Yadanzi(Brucea javanica)in the treatment of glioblastoma(GBM)by using the methods of bioinformatics and network pharmacology.Methods The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP)and literature retrieval method were applied to obtain the active ingredients of Yadanzi(Brucea javanica),and to predict the relevant targets of the active ingredients.The GBM-related targets were retrieved and screened through the Gene Expression Profling Interactive Analysis(GEPIA)database,and mapped to each other with the targets of the components of Yadanzi(Brucea javanica)to obtain the intersection targets.The GBM differentially expressed gene targets were imported into the String database to obtain the protein interaction relationship,the Cytoscape software was used to draw the protein interaction network,the Cytobba and MCODE plug-ins were used to screen the core genes and important protein interaction modules,and the GEPIA database was applied to make survival analysis of the core genes.The network map of“active ingredients-targets”was constructed through the Cytoscape 3.6.1 software.Gene Ontology(GO)biological function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway enrichment analysis for GBM differentially expressed genes were performed through the DAVID database.ResultsThrough TCMSP and literature retrieval,23 potential active ingredients and 129 related targets were obtained from Yadanzi(Brucea javanica).In the GEPIA database,247 GBM differentially expressed genes were screened,including 113 upregulated genes and 134 downregulated genes.After mapping with the targets related to the active ingredients of Yadanzi(Brucea javanica),six intersection targets were obtained,that is,the potential action targets of Yadanzi(Brucea javanica)in treating GBM,including MMP2,HMOX1,BIRC5,EGFR,CCNB2,and TOP2A.Cytoscape software was applied to build an“active ingredient-action target”network.Two active ingredients and five action targets of β-sitosterol(BS)and luteolin were found,and the targets were mainly concentrated in BS.It was found by KEGG pathway enrichment analysis that GBM differentially expressed genes were mainly involved in signaling pathways related to Staphylococcus aureus infection,phagosome formation,tuberculosis and systemic lupus erythematosus and other infectious and autoimmune diseases.It was found by GO enrichment analysis that the GBM differentially expressed genes mainly involved such biological processes(BP)as the processing and presentation of exogenous antigenic peptides and polysaccharide antigens through MHC Il molecules,y-interferon-mediated signaling pathways,extracellular matrix composition,and chemical synapses transmission;it involved cellular components such as cell junctions,axon terminal buttons,extracellular space,vesicle membranes for endocytosis,and MHC Il protein complexes;molecular functions such as calcium-mediated ionic protein binding,MHC Il molecular receptor activity,immunoglobulin binding,and phospholipase inhibitor activity were also involved.Survival analysis was conducted by GEPIA on the top 37 core targets in degree value,and a total of five genes related to GBM prognosis were obtained.Among them,FN1 and MMP2 were highly expressed while GABRD(v-aminobutyric acid A receptor delta subunit),RBFOX1,and SLC6A7 were expressed at a low level in cancer patients.Conclusion The pathogenesis of GBM is closely related to the human immune system,and BS and luteolin may be the main material basis of Yadanzi(Brucea javanica)for the treatment of GBM and the improvement of prognosis.The molecular mechanism may be related to the physical barrier formed by destroying the tumor cell stromal 68 Treatment of Glioblastoma Based on Bioinformatics and Network Pharmacology Zhao,Si.molecules and its involvement in tumor immune response.

Polyploid organisms

Polyploids are organisms with three or more complete chromosome sets. Polyploidization is widespread in plants and animals, and is an important mechanism of speciation. Genome sequencing and related molecular systematics and bioinformatics studies on plants and animals in recent years support the view that species have been shaped by whole genome duplication during evolution. The stability of polyploids depends on rapid genome recombination and changes in gene expression after formation. The formation of polyploids and subsequent diploidization are important aspects in long-term evolution. Polyploids can be formed in various ways. Among them, hybrid organisms formed by distant hybridization could produce unreduced gametes and thus generate offspring with doubled chromosomes, which is a fast, efficient method of polyploidization. The formation of fertile polyploids not only promoted the interflow of genetic materials among species and enriched the species diversity, but also laid the foundation for polyploidy breeding. The study of polyploids has both important theoretical significance and valuable applications. The production and application of polyploidy breeding have brought remarkable economic and social benefits.

Characterizing and annotating the genome using RNA-seq data

Bioinformatics methods for various RNA-seq data analyses are in fast evolution with the improvement of sequencing technologies. However, many challenges still exist in how to efficiently process the RNA-seq data to obtain accurate and comprehensive results. Here we reviewed the strategies for improving diverse transcriptomic studies and the annotation of genetic variants based on RNA-seq data. Mapping RNA-seq reads to the genome and transcriptome represent two distinct methods for quantifying the expression of genes/transcripts. Besides the known genes annotated in current databases, many novel genes/transcripts(especially those long noncoding RNAs) still can be identified on the reference genome using RNA-seq. Moreover, owing to the incompleteness of current reference genomes, some novel genes are missing from them. Genome-guided and de novo transcriptome reconstruction are two effective and complementary strategies for identifying those novel genes/transcripts on or beyond the reference genome. In addition, integrating the genes of distinct databases to conduct transcriptomics and genetics studies can improve the results of corresponding analyses.

Chemomics and drug innovation

Chemomics is an interdisciplinary study using approaches from chemoinformatics,bioinformatics,synthetic chemistry,and other related disciplines.Biological systems make natural products from endogenous small molecules (natural product building blocks) through a sequence of enzyme catalytic reactions.For each reaction,the natural product building blocks may contribute a group of atoms to the target natural product.We describe this group of atoms as a chemoyl.A chemome is the complete set of chemoyls in an organism.Chemomics studies chemomes and the principles of natural product syntheses and evolutions.Driven by survival and reproductive demands,biological systems have developed effective protocols to synthesize natural products in order to respond to environmental changes;this results in biological and chemical diversity.In recent years,it has been realized that one of the bottlenecks in drug discovery is the lack of chemical resources for drug screening.Chemomics may solve this problem by revealing the rules governing the creation of chemical diversity in biological systems,and by developing biomimetic synthesis approaches to make quasi natural product libraries for drug screening.This treatise introduces chemomics and outlines its contents and potential applications in the fields of drug innovation.

Rapid progress of DNA replication studies in Archaea,the third domain of life

Archaea,the third domain of life,are interesting organisms to study from the aspects of molecular and evolutionary biology.Archaeal cells have a unicellular ultrastructure without a nucleus,resembling bacterial cells,but the proteins involved in genetic information processing pathways,including DNA replication,transcription,and translation,share strong similarities with those of Eukaryota.Therefore,archaea provide useful model systems to understand the more complex mechanisms of genetic information processing in eukaryotic cells.Moreover,the hyperthermophilic archaea provide very stable proteins,which are especially useful for the isolation of replisomal multicomplexes,to analyze their structures and functions.This review focuses on the history,current status,and future directions of archaeal DNA replication studies.

Inferring gene regulatory networks by PCA-CMI using Hill climbing algorithm based on MIT score and SORDER method

Inferring gene regulatory networks （GRNs） is a challenging task in Bioinformatics. In this paper, an algorithm, PCHMS, is introduced to infer GRNs. This method applies the path consistency （PC） algorithm based on conditional mutual information test （PCA-CMI）. In the PC-based algorithms the separator set is determined to detect the dependency between variables. The PCHMS algorithm attempts to select the set in the smart way. For this purpose, the edges of resulted skeleton are directed based on PC algorithm direction rule and mutual information test （MIT） score. Then the separator set is selected according to the directed network by considering a suitable sequential order of genes. The effectiveness of this method is benchmarked through several networks from the DREAM challenge and the widely used SOS DNA repair network of Escherichia coll. Results show that applying the PCHMS algorithm improves the precision of learning the structure of the GRNs in comparison with current popular approaches.