SIK1作为miR-93新的靶基因抑制前列腺癌细胞增殖、侵袭和迁移

该文探讨了SIK1作为miR-93新的靶基因对前列腺癌细胞增殖、侵袭和迁移的抑制作用。采用重组质粒pcDNA3.1-SIK1上调前列腺癌细胞中SIK1的表达后,利用CCK8和克隆形成实验检测细胞增殖;利用细胞划痕和Transwell实验检测细胞侵袭和迁移;利用Western blot检测E-cadherin和Vimentin的蛋白表达。采用生物信息学方法预测靶向SIK1 mRNA的3’UTR的miRNAs并进行筛选;双荧光素酶报告实验和Western blot验证miR-93靶向调控SIK1。结果显示,上调SIK1的表达能抑制前列腺癌细胞的增殖、侵袭和迁移,并增加E-cadherin和减少Vimentin蛋白表达;miR-93能够靶向负调控SIK1。总之,SIK1可作为miR-93一个新的靶基因抑制前列腺癌细胞增殖、侵袭和迁移。     

基于表达谱芯片和下一代测序技术筛选先天性心脏病胎儿心肌组织差异表达的miRNA

目的 联合采用表达谱芯片和下一代测序技术同时高通量筛选先天性心脏病胎儿心肌组织表达差异的miRNA.方法 实验组为孕中期先天性畸形胎儿,对照组为同胎龄无心脏畸形的难免流产的胎儿,取胎儿心室心肌组织,联合采用Agilent Human 2.0 microRNAs表达谱芯片和SOLiD下一代测序技术同时观察心肌组织microRNA的表达变化,数据采用生物信息学方法进行分析,并用实时PCR方法验证芯片结果.结果 通过差异miRNA筛选,发现先天性心脏畸形组在表达谱芯片和下一代测序中共同差异的24个miRNA,生物信息学预测到1 606个靶基因,靶基因Gene Ontology分析表明其中与细胞进程、代谢过程、生物调控相关的靶基因为主,Pathway显著性分析表明,部分靶基因为生物信号通路中的关键因子;随机挑选共同表达差异的4个miRNA进行验证,结果表明定量PCR检测结果与芯片与下一代测序共同筛选结果基本相符.结论 这些在先天性心脏病中异常表达的miRNA为研究先天性心脏病分子水平上的发病机制提供了重要的线索,将有可能为心脏相关疾病的诊断和治疗提供新的靶点和研发新的药物.     

小鼠新分泌蛋白基因mBolA1的克隆与鉴定

采用生物信息学工具预测与实验相结合的方法得到了一个新的小鼠分泌蛋白基因mBolA1。该基因定位于染色体3F2,cDNA全长为730bp,编码137个氨基酸的蛋白,该蛋白含有一个保守的BolA结构域,等电点为9.05。用RT-PCR方法从鼠的混合cDNA库中克隆到mBolA1。Western blot实验表明mBolA1能从瞬转的COS 7细胞中分泌到细胞培养液中。亚细胞定位显示mBolA1定位于细胞浆,且与高尔基体不共定位,提示它是个非经典分泌途径的分泌蛋白。RT PCR显示mBolA1在组织中广泛表达。它的具体功能有待进一步研究。     

抑制性消减杂交法筛选炭样小单孢菌JXNU-1中抗生素合成相关基因

为了筛选炭样小单孢菌JXNU-1中抗生素合成相关基因,本研究以培养36 h(抗生素分泌前)的炭样小单孢菌JXNU-1菌体所合成c DNA为Driver,以培养108 h(抗生素分泌后)的菌体所合成的c DNA为Tester,构建炭样小单孢菌JXNU-1分泌抗生素前后的差异c DNA消减文库,筛选差异表达基因,荧光定量PCR验证其表达量,生物信息学方法分析其功能。研究结果表明,经抑制性消减杂交筛选得到5个与抗生素合成相关的差异表达基因;比照炭样小单孢菌JXNU-1全基因组序列,将所获5个基因定位到4个生物合成基因簇中,最后确定了炭样小单孢菌JXNU-1中抗生素生物合成相关的基因簇。本研究为阐明炭样小单孢菌JXNU-1中抗生素的生物合成机制提供了实验依据。     

感染球孢白僵菌的家蚕免疫应答差异表达基因分析

【目的】筛选家蚕Bombyx mori应对白僵菌Beauveria bassiana侵染的应答基因, 以进一步研究家蚕抵御真菌侵染的分子机制。【方法】采用新一代Solexa高通量测序技术对感染白僵菌及未感染白僵菌的对照组家蚕进行了测序分析, 筛选差异表达基因; 结合生物信息学工具分析差异表达基因的功能注释、 分类及涉及的信号通路等; 应用荧光定量PCR技术验证10个基因的差异表达。【结果】通过测序和生物信息学分析共获得377个差异表达基因, 其中表达上调基因236个, 下调基因141个; KEGG通路分析表明, 各通路中既有表达上调的基因, 也有下调基因; 12个上调基因、 26个下调基因参与3个显著性富集的KEGG通路, 即核糖体、 氨酰tRNA生物合成和剪接体通路。定量PCR与测序结果显示, 溶菌酶、 热激蛋白、 谷胱甘肽S-转移酶、 肽聚糖识别蛋白等与免疫应激相关的蛋白基因均呈现表达上调。【结论】本研究筛选获得的差异表达基因, 特别是上调表达的基因可能与家蚕应对白僵菌侵染的应答机制有关, 其中与免疫应激相关的蛋白基因如溶菌酶、 热激蛋白、 谷胱甘肽S 转移酶、 肽聚糖识别蛋白基因等可能直接参与了家蚕对白僵菌的免疫识别和防御, 研究结果为从分子水平阐明家蚕抵御真菌侵染的防御机制和白僵菌对家蚕的致病机理提供新的依据。     

浆液性卵巢癌铁死亡关键基因的筛选及[]生物信息学分析

利用生物信息学方法筛选浆液性卵巢癌相关铁死亡关键基因,并预测其生物学功能。从GEO数据库中获得有关浆液性卵巢癌的数据集GSE54388和GSE12470,采用R语言中的“Limma”包分析挑选浆液性卵巢癌上皮组织与正常卵巢上皮组织中差异表达基因,绘制火山图、热图。利用Venn软件在线工具绘制GSE54388,GSE12470,FerrDb三个数据集韦恩图。对相关基因进行功能富集分析、蛋白互作分析、生存分析,对关键基因绘制ROC曲线进行诊断分析。采用GEPIA2 数据库对筛选基因进行验证,并进行免疫浸润分析。结果发现:从GSE54388中筛选出2458个差异基因,其中上调1309个,下调1149个。从GSE12470中筛选出3534个差异基因,其中上调1 837个,下调1 697个。与铁死亡基因数据集取交集,共得到16个差异基因,蛋白互作网络筛选出7个基因构建的关键模块,绘制生存曲线发现浆液性卵巢癌患者中5个基因与患者总生存率不良相关,其中NRAS,PSAT1,CDKN2A,GDF15这4个基因高表达,CAV1低表达。ROC曲线显示这5个基因中CAV1,NRAS,PSAT1的AUC诊断曲线面积大于0.95,有较高的诊断价值。GEPIA2 数据库验证发现5个基因的表达情况与预测相符,仅NRAS基因表达在浆液性卵巢癌患者Ⅱ期、Ⅲ期、Ⅳ期有显著差异(P<0.05)。免疫浸润分析发现CDKN2A表达与aDC细胞浸润水平呈正相关(P<0.05,spearman相关系数0.353);CAV1表达与Mast细胞浸润正向关(P<0.05,spearman相关系数0.327);NRAS与T helper细胞浸呈正向关(P<0.05,spearman相关系数0.362)。通过生物信息学方法筛选出与浆液性卵巢癌铁死亡相关的5个基因CAV1,NRAS,PSAT1,CDKN2A,GDF15,可能在浆液性卵巢癌的发生发展中起重要作用,有望成为该病诊断、治疗和预后的潜在分子生物标志物。     

宫颈癌差异表达基因筛选及功能分析

目的:筛选参与宫颈癌发生、发展的关键基因,为临床诊疗提供新的靶点。方法:在NCBI-GEO数据库中筛选多组宫颈癌基因表达检测数据集,利用GEO2R分析工具筛选各组数据集的差异表达基因;应用R分析筛选不同数据集之间共有的差异表达基因;利用DAVID在线分析对差异表达基因进行功能聚类和通路分析;利用STRING分析差异表达基因编码蛋白之间的相互作用关系。结果:共选择6组表达数据集,筛选得到59个差异表达基因(宫颈癌组织vs正常组织),表达差异至少达2倍,其中包含50个表达上调基因及9个表达下调基因。这些差异表达基因参与细胞周期、DNA复制、细胞分裂等生物进程。蛋白互作分析表明,这些差异表达基因多数存在相互作用。结论:利用生物信息学方法对不同来源的基因检测数据进行整合分析,有助于更准确的筛选对宫颈癌发生、发展过程具有重要作用的关键基因,本文筛选的宫颈癌差异基因为进一步研究宫颈癌发生、发展的分子机制及临床诊疗提供思路。     

胰腺癌中CDK1的表达与预后的生物信息学分析

为探讨胰腺癌的发病机制并为胰腺癌的防治提供生物信息学依据,用GEO2R在线工具分析GSE16515中胰腺癌患者肿瘤组织和相应正常组织的差异表达基因(differentially expressed genes, DEGs),通过DAVID数据库对DEGs进行GO分析和KEGG通路富集分析,然后通过STRING数据库构建蛋白质相互作用(protein-protein interaction, PPI)网络,用Cytoscape软件进行关键基因(hub基因)筛选和功能模块分析,并在GEPIA数据库对hub基因进行验证,用CCLE数据库检测靶基因在胰腺癌组织及细胞系中的表达水平。分析结果显示胰腺癌中筛选出的376个DEGs主要涉及细胞周期、p53信号通路、蛋白质消化吸收、ECM-受体相互作用、PI3K-Akt信号通路、血小板激活信号通路。GEPIA数据库验证结果显示10个hub基因均在胰腺癌组织中高表达,其中8个hub基因与胰腺癌患者的不良预后有关。CCLE数据库检测结果显示周期蛋白依赖性激酶1 (cyclin-dependent kinase 1, CDK1)在胰腺癌组织和细胞中均有较高的表达水平。本研究结果表明CDK1可能与胰腺癌的发生发展最为相关,为进一步探究胰腺癌的发病机制提供了生物信息学依据。     

利用酵母双杂交系统从人胚胎肝脏cDNA文库中筛选与JNKK2相互作用的蛋白

目的:利用酵母双杂交系统,以149位赖氨酸突变成甲硫氨酸的c-Jun N端激酶激酶2(JNKK2)失活突变体(JNKK2KM)为诱饵,从人胎肝文库中筛选能与JNKK2作用的蛋白。方法:构建诱饵质粒p GBKT7-JNKK2KM,将其转化到AH109感受态酵母菌中进行扩增,而后检测融合蛋白表达、自激活活性以及对宿主的毒性;将诱饵酵母菌与含有人胎肝c DNA文库质粒的Y187交配进行酵母双杂交筛选,经缺陷型培养基筛选排除假阳性克隆;取阳性菌落抽提质粒进行酶切鉴定,对鉴定后的阳性克隆进行测序及生物信息学分析,明确筛选出的蛋白信息,通过免疫共沉淀实验验证筛选出的蛋白与JNKK2的相互作用。结果:构建了诱饵质粒,检测到融合蛋白的表达,且无自激活作用,未发现对宿主存在毒性;初步筛选到120个阳性克隆,经多轮重复验证得到阳性克隆11个,经生物信息学分析最后确定3个可以与JNKK2相互作用的新蛋白质分子为鸟嘌呤核苷酸结合蛋白β多肽2样蛋白1(GNB2L1)、开放读框60(ORF60)与泛素样修饰物激活酶3(UBA3),免疫共沉淀实验表明它们均能与JNKK2发生相互作用。结论:筛选到3个新的JNKK2相互作用蛋白,为深入探究JNKK2在肝脏中的作用奠定了基础。     

应用生物信息学方法筛选幽门螺杆菌疫苗候选抗原

目的：应用生物信息学分析方法筛选幽门螺杆菌新的疫苗候选抗原。方法：从TIGRCMR下载幽门螺杆菌26695和J99株全基因组序列,应用生物信息学SignalP、PredTMBB、LipoP、TMHMM、Phobius、PSORT-B和SubLoc等分析软件,筛选幽门螺杆菌新的外膜蛋白和分泌蛋白疫苗候选抗原。结果：从幽门螺杆菌26695株筛选得到54个编码β-桶型跨膜蛋白、脂蛋白或分泌表达蛋白的疫苗候选蛋白抗原,从幽门螺杆菌J99株得到61个呈现上述表达方式的疫苗候选蛋白抗原;且这2株细菌的疫苗候选蛋白呈现良好的交集状况,即有43个候选疫苗蛋白是相同的。结论：用生物信息学分析方法可以从全基因组范围内快速筛选到保守的分泌或表面暴露的疫苗候选抗原,为疫苗抗原的快速筛选与鉴定奠定了基础。     

Systematic Identification and Characterization of Novel Human Skin-Associated Genes Encoding Membrane and Secreted Proteins

Through bioinformatics analyses of a human gene expression database representing 105 different tissues and cell types, we identified 687 skin-associated genes that are selectively and highly expressed in human skin. Over 50 of these represent uncharacterized genes not previously associated with skin and include a subset that encode novel secreted and plasma membrane proteins. The high levels of skin-associated expression for eight of these novel therapeutic target genes were confirmed by semi-quantitative real time PCR, western blot and immunohistochemical analyses of normal skin and skin-derived cell lines. Four of these are expressed specifically by epidermal keratinocytes; two that encode G-protein-coupled receptors (GPR87 and GPR115), and two that encode secreted proteins (WFDC5 and SERPINB7). Further analyses using cytokine-activated and terminally differentiated human primary keratinocytes or a panel of common inflammatory, autoimmune or malignant skin diseases revealed distinct patterns of regulation as well as disease associations that point to important roles in cutaneous homeostasis and disease. Some of these novel uncharacterized skin genes may represent potential biomarkers or drug targets for the development of future diagnostics or therapeutics.     

hOLF44, a secreted glycoprotein with distinct expression pattern, belongs to an uncharacterized olfactomedin-like subfamily newly identified by phylogenetic analysis

Secreted proteins are indispensable for the development and differentiation of multicellular organisms. Cloning and characterization of novel or hypothetical genes encoding these proteins are therefore inviting great incentives. Using bioinformatics tools and experimental approaches, we isolated and characterized a human secreted glycoprotein, hOLF44, which contains a highly conserved olfactomedin-like (OLF) domain in the C-terminal. However, phylogenetic analysis revealed that hOLF44 is not clustered into any of the OLF subfamilies containing characterized members, and obviously falls into a newly identified uncharacterized OLF subfamily. Western blot analysis showed that hOLF44 protein is robustly secreted from the transfected COS-7 cells. Expression levels of hOLF44 mRNA are abundant in placenta, moderate in liver and heart, whereas fairly weak in other tissues examined. Immunohistochemical study on human term placenta demonstrated that hOLF44 is mainly localized extracellularly surrounding the syncytiotrophoblastic cells and very rarely expressed in the maternal decidua layer. These results suggest that hOLF44 may have matrix-related function involved in human placental and embryonic development, or play a similar role in other physiological processes. The further functional characterization of hOLF44 may provide insights into a better understanding of the newly identified OLF subfamily.     

卵巢癌肝转移灶高表达基因SFT2D1的生物信息学分析

目的:研究肿瘤原发灶和转移灶的基因表达差异,并采用生物信息学方法对一条卵巢癌肝转移灶高表达基因SFT2D1进行初步分析。方法:分别将卵巢癌原发灶和肝转移灶组织标本mRNA用Cy3-dUTP和Cy5-dUTP标记后与表达谱芯片杂交,通过信号扫描、处理后获得两者的表达差异基因。并用生物信息学方法对一条无功能研究的新基因SFT2D1进行初步分析,阐明了它的基因结构、染色体定位、编码蛋白质的理化性质、亚细胞定位、蛋白质功能域等信息。并对多物种中的相似性蛋白进行了系统进化分析。结果:表达谱芯片发现了共272条差异表达基因。对新基因SFT2D1的上述性质进行了有效的预测,基本明确了该基因编码蛋白为一内质网跨膜蛋白,可能参与肿瘤转移相关蛋白的合成与加工。结论:表达谱芯片技术是一种研究肿瘤转移基因表达差异的有效的高通量研究方法。通过生物信息学分析,表明新基因SFT2D1是一个有肿瘤转移研究价值的新靶点。     

Computational reconstruction of the human skeletal muscle secretome

In multicellular organisms, secreted proteins play pivotal regulatory roles in intercellular communication. Proteins secreted by skeletal muscle can act locally on muscle cells through autocrine/paracrine loops and on surrounding tissues such as muscle blood vessels, or they can be released into the blood stream, thus producing systemic effects. By a computational approach, we have screened 6255 products of genes expressed in normal human skeletal muscle. Putatively secreted proteins were identified by sequential steps of sieving, through prediction of signal peptide, recognition of transmembrane regions, and analysis of protein annotation. The resulting putative skeletal muscle secretome consists of 319 proteins, including 78 still uncharacterized proteins. This is the first human skeletal muscle secretome produced by computational analysis. Knowledge of proteins secreted by skeletal muscle could stimulate development of novel treatments for different diseases, including muscle atrophy and dystrophy. In addition, better knowledge of the secretion process in skeletal muscle can be useful for future gene therapy approaches.     

Bioinformatics,functional genomics,and proteomics study of Bacillus sp

The ability of bioinformatics to characterize genomic and proteomic sequences from bacteria Bacillus sp. for prediction of genes and proteins has been evaluated. Genomics coupling with proteomics, which is relied on integration of the significant advances recently achieved in two-dimensional (2-D) electrophoretic separation of proteins and mass spectrometry (MS), are now important and high throughput techniques for qualifying and analyzing gene and protein expression, discovering new gene or protein products, and understanding of gene and protein functions including post-genomic study. In addition, the bioinformatics of Bacillus sp. is embraced into many databases that will facilitate to rapidly search the information of Bacillus sp. in both genomics and proteomics. It is also possible to highlight sites for post-translational modifications based on the specific protein sequence motifs that play important roles in the structure, activity and compartmentalization of proteins. Moreover, the secreted proteins from Bacillus sp. are interesting and widely used in many applications especially biomedical applications that are the highly advantages for their potential therapeutic values.     

Computational prediction of human proteins that can be secreted into the bloodstream

We present a novel computational method for predicting which proteins from highly and abnormally expressed genes in diseased human tissues, such as cancers, can be secreted into the bloodstream, suggesting possible marker proteins for follow-up serum proteomic studies. A main challenging issue in tackling this problem is that our understanding about the downstream localization after proteins are secreted outside the cells is very limited and not sufficient to provide useful hints about secretion to the bloodstream. To bypass this difficulty, we have taken a data mining approach by first collecting, through extensive literature searches, human proteins that are known to be secreted into the bloodstream due to various pathological conditions as detected by previous proteomic studies, and then asking the question: 'what do these secreted proteins have in common in terms of their physical and chemical properties, amino acid sequence and structural features that can be used to predict them?' We have identified a list of features, such as signal peptides, transmembrane domains, glycosylation sites, disordered regions, secondary structural content, hydrophobicity and polarity measures that show relevance to protein secretion. Using these features, we have trained a support vector machine-based classifier to predict protein secretion to the bloodstream. On a large test set containing 98 secretory proteins and 6601 non-secretory proteins of human, our classifier achieved approximately 90% prediction sensitivity and approximately 98% prediction specificity. Several additional datasets are used to further assess the performance of our classifier. On a set of 122 proteins that were found to be of abnormally high abundance in human blood due to various cancers, our program predicted 62 as blood-secreted proteins. By applying our program to abnormally highly expressed genes in gastric cancer and lung cancer tissues detected through microarray gene expression studies, we predicted 13 and 31 as blood secreted, respectively, suggesting that they could serve as potential biomarkers for these two cancers, respectively. Our study demonstrated that our method can provide highly useful information to link genomic and proteomic studies for disease biomarker discovery. Our software can be accessed at http://csbl1.bmb.uga.edu/cgi-bin/Secretion/secretion.cgi.     

Discovery, cloning and heterologous expression of secreted potato proteins reveal erroneous pre-mRNA splicing in Aspergillus oryzae

A novel transposon assisted signal trapping (TAST) technology, developed to specifically select only the secreted proteins, was used to discover novel extracellular plant proteins from Solarium tuberosum infected with Phytophthora infestans. Analysis of 384 hits provided 191 P. infestans and S. tuberosum sequences of secreted proteins, with an approx. 2/3 of these originating from potato. Subsequent screening for interesting genes was carried out using bioinformatics. A selected variety of the discovered sequences are presented, including a novel S. tuberosum xyloglucan endotransglucosylase (StXTH), which was cloned and subjected to detailed heterologous expression studies in Aspergillus oryzae. RT-PCR analysis of mRNA from A. oryzae StXTH1 transformants revealed that parts of the mRNA pool had been incorrectly processed, and only weak and inconsistent indications of active protein could be detected. A high AT content of StXTH1 and the occurrence of A. oryzae intron donor, acceptor, and branch point recognition sites resulted in erroneous intron interpretation (cryptic introns) of parts of the mRNA coding sequence. This may explain the difficulties generally experienced in expressing plant genes in filamentous fungi.     

Proteomic analyses of apoplastic proteins from germinating Arabidopsis thaliana pollen

Pollen grains play important roles in the reproductive processes of flowering plants. The roles of apoplastic proteins in pollen germination and in pollen tube growth are comparatively less well understood. To investigate the functions of apoplastic proteins in pollen germination, the global apoplastic proteins of mature and germinated Arabidopsis thaliana pollen grains were prepared for differential analyses by using 2-dimensional fluorescence difference gel electrophoresis (2-D DIGE) saturation labeling techniques. One hundred and three proteins differentially expressed (p value≤0.01) in pollen germinated for 6h compared with un-germination mature pollen, and 98 spots, which represented 71 proteins, were identified by LC-MS/MS. By bioinformatics analysis, 50 proteins were identified as secreted proteins. These proteins were mainly involved in cell wall modification and remodeling, protein metabolism and signal transduction. Three of the differentially expressed proteins were randomly selected to determine their subcellular localizations by transiently expressing YFP fusion proteins. The results of subcellular localization were identical with the bioinformatics prediction. Based on these data, we proposed a model for apoplastic proteins functioning in pollen germination and pollen tube growth. These results will lead to a better understanding of the mechanisms of pollen germination and pollen tube growth.