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How bacteria adjust gene expression to cope with variable environments remains open to question. Here, we investigated the way global gene expression changes in E. coli correlated with the metabolism of seven carbon substrates chosen to trigger a large panel of metabolic pathways. Coarse-grained analysis of gene co-expression identified a novel regulation pattern: we established that the gene expression trend following immediately the reduction of growth rate (GR) was correlated to its initial expression level. Subsequent fine-grained analysis of co-expression demonstrated that the Crp regulator, coupled with a change in GR, governed the response of most GR-dependent genes. By contrast, the Cra, Mlc and Fur regulators governed the expression of genes responding to non-glycolytic substrates, glycolytic substrates or phosphotransferase system transported sugars following an idiosyncratic way. This work allowed us to expand additional genes in the panel of gene complement regulated by each regulator and to elucidate the regulatory functions of each regulator comprehensively. Interestingly, the bulk of genes controlled by Cra and Mlc were, respectively, co-regulated by Crp- or GR-related effect and our quantitative analysis showed that each factor took turns to work as the primary one or contributed equally depending on the conditions.  相似文献   

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基于转录组分析铜绿假单胞菌DN1降解荧蒽特性   总被引:1,自引:0,他引:1  
[背景]铜绿假单胞菌DN1是一株从石油污染土壤中分离筛选到的具有广谱降解功能的菌株。[目的]深入了解荧蒽胁迫条件下铜绿假单胞菌DN1降解污染物过程中重要的降解相关基因信息。[方法]通过高通量测序技术对铜绿假单胞菌DN1进行转录组测序,对其所有的转录本进行KEGG (kyoto encyclopedia of genes and genomes)分类和Pathway注释、GO (gene ontology)分类和富集分析。[结果]转录组测序显示:与对照组相比,荧蒽诱导组检测到6 189个基因,其中1 919个基因上调表达,1 603个基因下调表达。KEGG注释分析显示差异上调表达基因匹配到了112个KEGG代谢途径,注释到"代谢途径"的1 408个基因(约占总差异基因的73.4%)中有317个基因参与了碳氢化合物代谢及含有苯环结构的异源生物质的生物降解,占"代谢途径"的16.53%,暗示了菌株DN1降解荧蒽可能与这些途径有密切关系。另外,主要代谢途径中的差异表达基因主要集中在ABC转运系统、氨基酸生物合成、双组分系统及碳代谢,这些途径大多数参与了底物的识别转运、信号转导及基因表达调控。[结论]进一步拓展了铜绿假单胞菌DN1在荧蒽胁迫条件下的代谢途径和逆境反应,也为微生物修复环境污染物研究夯实了理论基础。  相似文献   

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Glucocorticoids and progestins bind to receptors that share many structural and functional similarities, including virtually identical DNA recognition specificity. Nonetheless, the two hormones mediate very distinct biological functions. For example, progestins are associated with the incidence and progression of breast cancer, whereas glucocorticoids are growth suppressive in mammary cancer cells. To understand the mechanisms that engender biological specificity, it is necessary to identify genes that are differentially regulated by the two receptors. Here we employ Affymetrix oligonucleotide arrays to compare glucocorticoid- and progestin-regulated gene expression in a human breast cancer cell line. This global analysis reveals that the two hormones regulate overlapping but distinct sets of genes, including 31 genes that are differentially regulated. Surprisingly, the set of differentially regulated genes was almost as large as the set of genes regulated by both hormones. Examination of the set of differentially regulated genes suggests mechanisms behind the distinct growth effects of the two hormones in breast cancer. The differential regulation of four genes representing different regulatory patterns was confirmed by RT-PCR and Northern blot analyses. Treatment with cycloheximide or RU486 indicates that the regulation is a primary, receptor-mediated event. Detailed analyses of genes identified in these studies will furnish a mechanistic understanding of differential regulation by glucocorticoids and progestins.  相似文献   

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