Wilson Jayne Louise, McLean Samantha, Begg Ronald, Sanguinetti Guido, Poole Robert K
Department of Molecular Biology and Biotechnology, The University of Sheffield, Sheffield S10 2TN, UK.
School of Informatics, The University of Edinburgh, Edinburgh EH8 9AB, UK.
Genom Data. 2015 Jun 13;5:231-234. doi: 10.1016/j.gdata.2015.06.008. eCollection 2015 Sep.
This article describes in extended detail the methodology applied for acquisition of transcriptomic data, and subsequent statistical data modelling, published by Wilson . (2015) in a study of the effects of carbon monoxide-releasing molecule-3 (CORM-3 [Ru(CO)Cl(glycinate)]) on heme-deficient bacteria. The objective was to identify non-heme targets of CORM action. Carbon monoxide (CO) interacts with heme-containing proteins, in particular respiratory cytochromes; however, CORMs have been shown to elicit multifaceted effects in bacteria, suggesting that the compounds may have additional targets. We therefore sought to elucidate the activity of CORM-3, the first water-soluble CORM and one of the most characterised CORMs to date, in bacteria devoid of heme synthesis. Importantly, we also tested inactive CORM-3 (iCORM-3), a ruthenium co-ligand fragment that does not release CO, in order to differentiate between CO- and compound-related effects. A well-established mutant of was used for the study and, for comparison, parallel experiments were performed on the corresponding wild-type strain. Global transcriptomic changes induced by CORM-3 and iCORM-3 were evaluated using a Two-Color Microarray-Based Prokaryote Analysis (FairPlay III Labeling) by Agilent Technologies (Inc. 2009). Data acquisition was carried out using Agilent Feature Extraction software (v6.5) and data normalisation, as well as information about gene products and their function was obtained from GeneSpring GX v7.3 (Agilent Technologies). Functional category lists were created using KEGG (Kyoto Encyclopedia of Genes and Genomes). Relevant regulatory proteins for each gene were identified, where available, using regulonDB and EcoCyc (World Wide Web). Statistical data modelling was performed on the gene expression data to infer transcription factor activities. The transcriptomic data can be accessed through NCBI's Gene Expression Omnibus (GEO): series accession number GSE55097 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE55097).
本文详细介绍了用于获取转录组数据以及后续进行统计数据建模的方法，该方法由威尔逊（2015年）发表，用于研究一氧化碳释放分子-3（CORM-3 [Ru(CO)Cl(甘氨酸盐)]）对血红素缺乏细菌的影响。目的是确定CORM作用的非血红素靶点。一氧化碳（CO）与含血红素的蛋白质相互作用，特别是呼吸细胞色素；然而，已表明CORMs在细菌中会引发多方面的影响，这表明这些化合物可能还有其他靶点。因此，我们试图阐明CORM-3（第一种水溶性CORM，也是迄今为止特征最明确的CORM之一）在缺乏血红素合成的细菌中的活性。重要的是，我们还测试了无活性的CORM-3（iCORM-3），一种不释放CO的钌共配体片段，以便区分CO相关效应和化合物相关效应。使用一种成熟的 突变体进行该研究，并且为了进行比较，在相应的野生型菌株上进行了平行实验。使用安捷伦科技公司（2009年）基于双色微阵列的原核生物分析（FairPlay III标记）评估了CORM-3和iCORM-3诱导的全局转录组变化。使用安捷伦特征提取软件（v6.5）进行数据采集，并从GeneSpring GX v7.3（安捷伦科技公司）获得数据归一化以及有关基因产物及其功能的信息。使用KEGG（京都基因与基因组百科全书）创建功能类别列表。在可用的情况下，使用调控子数据库和EcoCyc（万维网）确定每个基因的相关调节蛋白。对基因表达数据进行统计数据建模以推断转录因子活性。转录组数据可通过NCBI的基因表达综合数据库（GEO）获取：系列登录号GSE55097（http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE55097）。
