Using gene expression noise to understand gene regulation

Phenotypic variation is ubiquitous in biology and is often traceable to underlying genetic and environmental variation. However, even genetically identical cells in identical environments display variable phenotypes. Stochastic gene expression, or gene expression "noise," has been suggested as a major source of this variability, and its physiological consequences have been topics of intense research for the last decade. Several recent studies have measured variability in protein and messenger RNA levels, and they have discovered strong connections between noise and gene regulation mechanisms. When integrated with discrete stochastic models, measurements of cell-to-cell variability provide a sensitive "fingerprint" with which to explore fundamental questions of gene regulation. In this review, we highlight several studies that used gene expression variability to develop a quantitative understanding of the mechanisms and dynamics of gene regulation.     

Noise propagation in gene networks

Accurately predicting noise propagation in gene networks is crucial for understanding signal fidelity in natural networks and designing noise-tolerant gene circuits. To quantify how noise propagates through gene networks, we measured expression correlations between genes in single cells. We found that noise in a gene was determined by its intrinsic fluctuations, transmitted noise from upstream genes, and global noise affecting all genes. A model was developed that explains the complex behavior exhibited by the correlations and reveals the dominant noise sources. The model successfully predicts the correlations as the network is systematically perturbed. This approach provides a step toward understanding and manipulating noise propagation in more complex gene networks.     

Noise in gene expression: origins, consequences, and control

Genetically identical cells and organisms exhibit remarkable diversity even when they have identical histories of environmental exposure. Noise, or variation, in the process of gene expression may contribute to this phenotypic variability. Recent studies suggest that this noise has multiple sources, including the stochastic or inherently random nature of the biochemical reactions of gene expression. In this review, we summarize noise terminology and comment on recent investigations into the sources, consequences, and control of noise in gene expression.     

Genetic properties influencing the evolvability of gene expression

Identifying the properties of gene networks that influence their evolution is a fundamental research goal. However, modes of evolution cannot be inferred solely from the distribution of natural variation, because selection interacts with demography and mutation rates to shape polymorphism and divergence. We estimated the effects of naturally occurring mutations on gene expression while minimizing the effect of natural selection. We demonstrate that sensitivity of gene expression to mutations increases with both increasing trans-mutational target size and the presence of a TATA box. Genes with greater sensitivity to mutations are also more sensitive to systematic environmental perturbations and stochastic noise. These results provide a mechanistic basis for gene expression evolvability that can serve as a foundation for realistic models of regulatory evolution.     

Variability and robustness in T cell activation from regulated heterogeneity in protein levels

In T cells, the stochasticity of protein expression could contribute to the useful diversification of biological functions within a clonal population or interfere with accurate antigen discrimination. Combining computer modeling and single-cell measurements, we examined how endogenous variation in the expression levels of signaling proteins might affect antigen responsiveness during T cell activation. We found that the CD8 co-receptor fine-tunes activation thresholds, whereas the soluble hematopoietic phosphatase 1 (SHP-1) digitally regulates cell responsiveness. Stochastic variation in the expression of these proteins generates substantial diversity of activation within a clonal population of T cells, but co-regulation of CD8 and SHP-1 levels ultimately limits this very diversity. These findings reveal how eukaryotic cells can draw on regulated variation in gene expression to achieve phenotypic variability in a controlled manner.     

含CpG序列PRRSV SD2 E基因真核表达载体质粒构建及表达

为了提高猪生殖与呼吸综合征病毒山东株(PRRSV SD2株)基因免疫的效果,将PRRSV SD2 E基因插入哺乳动物表达载体PVAX1中,构建出PVAX1-E质粒。再将已筛选出的CpG-ODN序列通过在其两端的粘性酶切末端定向插入含PVAX 1-E的真核表达载体,构建含CpG基因序列真核重组表达质粒CpG-pVAX 1-E。将重组质粒转染COS-7细胞,经RT-PCR检测E基因mRNA的转录和间接免疫荧光试验(IFA)证实:CpG-pVAX 1-E可表达PRRSV GP5蛋白。试验结果为进一步研究PRRSV SD2 ORF5动物免疫反应奠定基础。     

泛素结合酶UFC1基因的荧光表达载体构建

利用pEGFP-C3作为载体,构建与绿色荧光蛋白基因相连的泛素结合酶UFC1(ubiquitin-fold modifier conjugating enzyme 1)序列的真核表达质粒,观察其在真核细胞中的表达和定位,为进一步研究UFC1基因功能打下了基础。采用RT-PCR方法从宫颈癌Hela细胞中扩增UFC1基因全长cDNA,双酶切后克隆到真核表达载体pEGFP-C3中,构建并鉴定pEGFP-C3-UFC1质粒。经脂质体介导转染Hela细胞后,在荧光显微镜下观察目的蛋白在真核细胞内的表达情况。双酶切鉴定和测序分析均证实,已成功构建pEGFP-C3-UFC1重组载体。重组载体转染Hela细胞,观察到绿色荧光蛋白表达,还可见绿色荧光呈点状分布于细胞质中;而对照pEGFP-C3质粒转染Hela细胞,绿色荧光蛋白则呈弥散状分布。成功克隆了UFC1基因,构建了pEGFP-C3-UFC1重组质粒。     

Identifying autism loci and genes by tracing recent shared ancestry

To find inherited causes of autism-spectrum disorders, we studied families in which parents share ancestors, enhancing the role of inherited factors. We mapped several loci, some containing large, inherited, homozygous deletions that are likely mutations. The largest deletions implicated genes, including PCDH10 (protocadherin 10) and DIA1 (deleted in autism1, or c3orf58), whose level of expression changes in response to neuronal activity, a marker of genes involved in synaptic changes that underlie learning. A subset of genes, including NHE9 (Na+/H+ exchanger 9), showed additional potential mutations in patients with unrelated parents. Our findings highlight the utility of "homozygosity mapping" in heterogeneous disorders like autism but also suggest that defective regulation of gene expression after neural activity may be a mechanism common to seemingly diverse autism mutations.     

小鼠p300-HAT真核表达质粒的构建

[目的]构建小鼠p300-HAT的真核表达质粒。[方法]利用PCR技术扩增p300的HAT域,然后构建p300的HAT域的真核表达质粒（p300-HAT—EGFP）,并通过PCR验证和酶切验证重组质粒的正确性;提取不舍内毒素的质粒,转染HepG2细胞,通过观测绿色荧光检测转染效率。[结果]PcR产物的电泳结果显示,成功扩增了小鼠p300基因HAT结构域,构建了小鼠p300基因HAT结构域的真核表达质粒,将其命名为m-p300-HAT-pEGFP—C1。重组质粒可以成功表达融合绿色荧光蛋白目的基因蛋白。[结论]p300-HAT—EGFP重组质粒的成功构建为后续开展巨噬细胞NF—kB信号通路的研究奠定了基础。     

真菌RNA沉默研究进展

阻抑(Quelling)与减数分裂沉默(Meiotic silencing by unpaired DNA,MSUD)等真菌RNA沉默(RNA silencing)现象的研究拓展了我们当前对基因表达调控的认知。随着测序信息量的爆炸性增长与功能研究的不断深入,真菌RNA沉默展示出的复杂与多样为真核生物研究提供了全新的视角。本文就当前真菌RNA沉默及相关小分子RNA(Small RNA,sRNA)的研究现状做一简要概述。     

乙型肝炎病毒X基因真核表达载体的构建

目的：构建HBVX基因与pCI-neo相融合的高效真核表达载体。方法：设计并合成HBVX基因的引物,以HBVDNA阳性血清PCR扩增得到HBVX基因全序列,将X基因连接到真核表达载体pCI—neo上后,酶切图谱分析、PCR检测和扩增产物序列分析等,鉴定所构建的真核表达载体。结果：以重组载体为模板扩增得到的片段大小与已知HBVX基因大小相同,酶切也得到目的基因片段,测序结果也显示与已知X基因序列相同。结论：成功构建了HBVX基因的真核表达载体,为进一步研究HBVX基因及其产物的功能奠定了基础。     

甘蔗14-3-3基因真核表达载体构建及分析

该实验拟构建甘蔗14-3-3基因的真核表达载体,为体外研究该蛋白功能和高级构象特征奠定基础。用RT—PCR技术从甘蔗茎中扩增出编码14-3-3蛋白的全长基因,并连入pGEM—T载体中,双酶切和测序用于序列正确性的鉴定。结果表明,该基因的最大开放阅读框为771bp,编码6256个氨基酸。后将所得cDNA片段亚克隆至真核表达载体pPIC9K,经电转后在酵母细胞中表达,表达产物经Westernblot鉴定分子量约为28kD。表明已成功构建了甘蔗14—3—3蛋白真核表达载体,并获得了表达产物。     

广西巴马小型猪α干扰素基因克隆及其真核表达载体的构建

[目的]克隆广西巴马小型猪α干扰素基因（poIFN-α）全部编码序列并构建其哺乳动物真核表达载体,为研发重组猪干扰素类免疫佐剂及生物治疗制剂提供参考依据.[方法]应用RT-PCR扩增广西巴马小型猪poIFN-α编码序列,链接至pMD 18-T载体构建重组质粒,以测序正确的重组质粒为模板,PCR扩增带有酶切位点的poIFN-α基因,然后连接真核表达载体pTARGET构建重组表达载体pTARGET-poIFN-α,并转化感受态细胞DH5α,经双酶切初步鉴定正确后送至北京诺赛生物有限公司测序,用DNASTAR软件及Primer Premer 5.0等对获得的基因序列进行分析.[结果]以广西巴马小型猪总RNA为模板扩增获得的目的片段为618 bp,包含poIFN-α基因全部编码序列;将克隆获得的poIFN-α基因插入哺乳动物真核表达载体pTARGET中,可成功构建广西巴马小型猪重组表达载体pTAR-GET-poIFN-α.广西巴马小型猪poIFN-α与GenBank上已发表的猪、鼠、人IFN-α基因同源性分别为97.0％、78.2％和66.3％;其成熟肽与普通猪相比,共有17个位点发生碱基突变,其中第63、189、198、288、544、545位点为无义突变,第88、119、163、182、186、195、263、301、306、553、560位点为错义突变.[结论]IFN-α成熟肽在哺乳动物中保守性较差;克隆获得的广西巴马小型猪poIFN-α基因能成功插入哺乳动物真核表达载体pTARGET中构建重组表达载体pTAR-GET-poIFN-α,为研发重组猪干扰素类生物治疗制剂、免疫佐剂、构建小型猪疾病动物模型等奠定了基础.     

人LIF基因与增强型绿色荧光蛋白融合表达载体的构建及转染

目的：构建携带人LIF基因与增强型绿色荧光蛋白（EGFP）的融合表达载体,并转染人胚肺成纤维细胞,为研究LIF在维持人胚胎生殖细胞自我更新中的作用机制奠定基础．方法：以重组质粒pcDNA3．1／lif为模板,PCR扩增LIF基因,将扩增片断双酶切后连接到质粒pEGFP-N1中,形成重组表达载体pEGFP—N1／lif．并用脂质体法转染人胚肺成纤维细胞,荧光显微镜下观察,RT—PCR及Western杂交检测融合蛋白的表达．结果：成功构建融合表达载体pEGFP—N1／lif,在人胚肺成纤维细胞实现表达,检测到融合蛋白EGFP—LIF．结论重组pEGFP—N1／lif载体构建成功,可用于标记LIF蛋白、为进一步研究LIF在维持人胚胎生殖细胞自我更新中的作用机制奠定基础．     

CMV启动子指导pDsRed2-1基因在牛胎儿成纤维细胞中的表达

目的:为了检测扩增所得CMV启动子能够指导下游基因序列表达,从而可以为构建其它真核表达载体提供实验基础和依据。方法:对pEGFP质粒上的CMV启动子进行扩增,并将其插入pDsRed2-1质粒红色荧光蛋白上游,构建pCMV-Red质粒转染牛胎儿皮肤成纤维细胞,对其进行荧光检测。结果:质粒转染牛胎儿皮肤成纤维细胞48h后,荧光激发细胞,发红色荧光。结论:扩增所得CMV启动子具有启动其下游基因表达的功能。pCMV-Red质粒可用于构建其它真核表达载体。     

北京油鸡肠道肽转运蛋白PEPT1表达载体的构建及在293-T细胞的表达

本试验通过分子生物学手段建立了北京油鸡PEPT1细胞模型。根据GenBank的原鸡PEPT1保守区序列设计引物,从北京油鸡肠道粘膜组织中扩增出PEPT1基因,将其与pGEM-T载体连接并测定核苷酸序列,成功获得到测序正确的2145bp的基因,并将北京油鸡肠肽转运载体PEPT1基因克隆到真核表达载体pcDNA3.0,构建了真核表达载体pcDNA3-PEPT1。采用脂质体介导将表达质粒pcDNA3-PEPT1转染293-T细胞,同时转染pcDNA3.0-EGFP荧光蛋白进行转染体系荧光监测,流式细胞术检测转录后16、20、24h的荧光强度。分别在16、20、24、44h收集等量转染细胞,抽提转染细胞总RNA,DNAseⅠ处理残留的DNA污染,反转录合成cDNA,以构建不同稀释度的pGEM-T-PEPT1质粒为模板,建立SYBERGREEN实时荧光定量标准曲线,检测PEPT1在293-T细胞中的转录水平。结果表明,在质粒转染入293-T细胞后,在16、20、24、44h均有稳定的转录水平。从而建立了在293-T细胞表达北京油鸡PEPT1的外源模型,同时为研究该转运蛋白性质,进一步调控动物肠道肽的吸收奠定了基础。