Bioinformatics Group, Wageningen University, Wageningen, The Netherlands; Molecular Biotechnology, Institute of Biology, Leiden University, Leiden, The Netherlands.
Bioinformatics Group, Wageningen University, Wageningen, The Netherlands.
J Mol Biol. 2024 Sep 1;436(17):168558. doi: 10.1016/j.jmb.2024.168558. Epub 2024 Apr 3.
Actinobacteria undergo a complex multicellular life cycle and produce a wide range of specialized metabolites, including the majority of the antibiotics. These biological processes are controlled by intricate regulatory pathways, and to better understand how they are controlled we need to augment our insights into the transcription factor binding sites. Here, we present LogoMotif (https://logomotif.bioinformatics.nl), an open-source database for characterized and predicted transcription factor binding sites in Actinobacteria, along with their cognate position weight matrices and hidden Markov models. Genome-wide predictions of binding site locations in Streptomyces model organisms are supplied and visualized in interactive regulatory networks. In the web interface, users can freely access, download and investigate the underlying data. With this curated collection of actinobacterial regulatory interactions, LogoMotif serves as a basis for binding site predictions, thus providing users with clues on how to elicit the expression of genes of interest and guide genome mining efforts.
放线菌经历复杂的多细胞生命周期,并产生广泛的特殊代谢物,包括大多数抗生素。这些生物过程受到复杂的调控途径控制,为了更好地了解它们是如何被控制的,我们需要增加我们对转录因子结合位点的了解。在这里,我们介绍了 LogoMotif(https://logomotif.bioinformatics.nl),这是一个用于放线菌中特征化和预测转录因子结合位点的开源数据库,以及它们的同源位置权重矩阵和隐马尔可夫模型。还提供了链霉菌模型生物中结合位点位置的全基因组预测,并以交互式调控网络的形式可视化。在网络界面中,用户可以自由访问、下载和研究基础数据。有了这个经过精心整理的放线菌调控相互作用集合,LogoMotif 可以作为结合位点预测的基础,从而为用户提供如何表达感兴趣基因的线索,并指导基因组挖掘工作。