Afzal Muhammad, Manzoor Irfan, Kuipers Oscar P
Department of Molecular Genetics, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen; Department of Bioinformatics and Biotechnology, Government College University Faisalabad.
Department of Molecular Genetics, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen;
J Vis Exp. 2015 Apr 25(98):52649. doi: 10.3791/52649.
Gene expression and its regulation are very important to understand the behavior of cells under different conditions. Various techniques are used nowadays to study gene expression, but most are limited in terms of providing an overall picture of the expression of the whole transcriptome. DNA microarrays offer a fast and economic research technology, which gives a full overview of global gene expression and have a vast number of applications including identification of novel genes and transcription factor binding sites, characterization of transcriptional activity of the cells and also help in analyzing thousands of genes (in a single experiment). In the present study, the conditions for bacterial transcriptome analysis from cell harvest to DNA microarray analysis have been optimized. Taking into account the time, costs and accuracy of the experiments, this technology platform proves to be very useful and universally applicabale for studying bacterial transcriptomes. Here, we perform DNA microarray analysis with Streptococcus pneumoniae as a case-study by comparing the transcriptional responses of S. pneumoniae grown in the presence of varying L-serine concentrations in the medium. Total RNA was isolated by using a Macaloid method using an RNA isolation kit and the quality of RNA was checked by using an RNA quality check kit. cDNA was prepared using reverse transcriptase and the cDNA samples were labelled using one of two amine-reactive fluorescent dyes. Homemade DNA microarray slides were used for hybridization of the labelled cDNA samples and microarray data were analyzed by using a cDNA microarray data pre-processing framework (Microprep). Finally, Cyber-T was used to analyze the data generated using Microprep for the identification of statistically significant differentially expressed genes. Furthermore, in-house built software packages (PePPER, FIVA, DISCLOSE, PROSECUTOR, Genome2D) were used to analyze data.
基因表达及其调控对于理解细胞在不同条件下的行为非常重要。如今，人们使用各种技术来研究基因表达，但大多数技术在提供整个转录组表达的全貌方面都存在局限性。DNA微阵列提供了一种快速且经济的研究技术，它能全面概述全局基因表达，并有大量应用，包括鉴定新基因和转录因子结合位点、表征细胞的转录活性，还有助于在单个实验中分析数千个基因。在本研究中，已对从细胞收获到DNA微阵列分析的细菌转录组分析条件进行了优化。考虑到实验的时间、成本和准确性，该技术平台被证明对于研究细菌转录组非常有用且普遍适用。在此，我们以肺炎链球菌为案例进行DNA微阵列分析，比较在培养基中存在不同L-丝氨酸浓度时生长的肺炎链球菌的转录反应。使用RNA分离试剂盒通过Macaloid方法分离总RNA，并使用RNA质量检测试剂盒检查RNA质量。使用逆转录酶制备cDNA，并使用两种胺反应性荧光染料之一对cDNA样本进行标记。使用自制的DNA微阵列载玻片对标记的cDNA样本进行杂交，并使用cDNA微阵列数据预处理框架（Microprep）分析微阵列数据。最后，使用Cyber-T分析使用Microprep生成的数据，以鉴定具有统计学意义的差异表达基因。此外，还使用了内部构建的软件包（PePPER、FIVA、DISCLOSE、PROSECUTOR、Genome2D）来分析数据。
