Genomic Reconstruction of the Transcriptional Regulatory Network in Bacillus subtilis
Genomic Reconstruction of the Transcriptional Regulatory Network in Bacillus subtilis
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DOI：
10.1128/jb.00140-13
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发表时间：
2013-06-01
影响因子：
3.2
通讯作者：
Rodionov, Dmitry A.
中科院分区：
文献类型：
--
作者：
Leyn, Semen A.;Kazanov, Marat D.;Rodionov, Dmitry A.
微生物对环境的适应是由复杂的转录调控网络（TRN）控制的，即使对于模式物种，也只有部分了解。在基因组规模上对基因调控特征进行注释和TRN重建是微生物基因组学的挑战性任务。我们使用的知识驱动的比较基因组学的方法实施的RegPredict Web服务器中推断TRN模型革兰氏阳性菌枯草芽孢杆菌和10个相关的Bacillales物种。对于转录因子（TF）调节子，我们将DBTBS数据库和文献中的可用信息与生物信息学工具相结合，从而可以推断TF结合位点（TFBS），预测TFBS的基因组背景的比较分析，靶基因的功能分配和效应子预测。对于RNA调节子，我们使用Rfam数据库中收集的已知RNA调节基序来扫描基因组并分析新RNA位点的基因组背景。B中的推断TRN。枯草芽孢杆菌包含129个TF和24个调节RNA家族的调节子。首先，我们分析了B中具有先前已知的TFBS的66个TF调节子。枯草芽孢杆菌，并将它们投射到其他芽孢杆菌基因组，导致TFBS基序的细化和新的调节子成员的鉴定。其次，我们推断图案和描述调节子的28个实验研究TF与以前未知的TFBS。第三，我们发现了新的图案和重建调节子36个以前未知的TF。调节子的推断集合可在RegPrecise数据库（http：//regprecise.lbl.gov/）中获得，并且可用于遗传实验、代谢建模和进化分析。
The adaptation of microorganisms to their environment is controlled by complex transcriptional regulatory networks (TRNs), which are still only partially understood even for model species. Genome scale annotation of regulatory features of genes and TRN reconstruction are challenging tasks of microbial genomics. We used the knowledge-driven comparative-genomics approach implemented in the RegPredict Web server to infer TRN in the model Gram-positive bacterium Bacillus subtilis and 10 related Bacillales species. For transcription factor (TF) regulons, we combined the available information from the DBTBS database and the literature with bioinformatics tools, allowing inference of TF binding sites (TFBSs), comparative analysis of the genomic context of predicted TFBSs, functional assignment of target genes, and effector prediction. For RNA regulons, we used known RNA regulatory motifs collected in the Rfam database to scan genomes and analyze the genomic context of new RNA sites. The inferred TRN in B. subtilis comprises regulons for 129 TFs and 24 regulatory RNA families. First, we analyzed 66 TF regulons with previously known TFBSs in B. subtilis and projected them to other Bacillales genomes, resulting in refinement of TFBS motifs and identification of novel regulon members. Second, we inferred motifs and described regulons for 28 experimentally studied TFs with previously unknown TFBSs. Third, we discovered novel motifs and reconstructed regulons for 36 previously uncharacterized TFs. The inferred collection of regulons is available in the RegPrecise database (http://regprecise.lbl.gov/) and can be used in genetic experiments, metabolic modeling, and evolutionary analysis.