Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Munich, Germany.
Sci Data. 2020 May 11;7(1):142. doi: 10.1038/s41597-020-0484-9.
We present the newest version of CoryneRegNet, the reference database for corynebacterial regulatory interactions, available at www.exbio.wzw.tum.de/coryneregnet/. The exponential growth of next-generation sequencing data in recent years has allowed a better understanding of bacterial molecular mechanisms. Transcriptional regulation is one of the most important mechanisms for bacterial adaptation and survival. These mechanisms may be understood via an organism's network of regulatory interactions. Although the Corynebacterium genus is important in medical, veterinary and biotechnological research, little is known concerning the transcriptional regulation of these bacteria. Here, we unravel transcriptional regulatory networks (TRNs) for 224 corynebacterial strains by utilizing genome-scale transfer of TRNs from four model organisms and assigning statistical significance values to all predicted regulations. As a result, the number of corynebacterial strains with TRNs increased twenty times and the back-end and front-end were reimplemented to support new features as well as future database growth. CoryneRegNet 7 is the largest TRN database for the Corynebacterium genus and aids in elucidating transcriptional mechanisms enabling adaptation, survival and infection.
我们展示了 CoryneRegNet 的最新版本,这是用于棒状杆菌调控相互作用的参考数据库,可在 www.exbio.wzw.tum.de/coryneregnet/ 上获得。近年来,下一代测序数据的指数级增长使我们能够更好地理解细菌的分子机制。转录调控是细菌适应和生存的最重要机制之一。这些机制可以通过生物体的调控相互作用网络来理解。尽管棒状杆菌属在医学、兽医和生物技术研究中很重要,但对于这些细菌的转录调控知之甚少。在这里,我们通过利用来自四个模式生物的 TRN 进行基因组规模的转移,为 224 株棒状杆菌菌株揭示了转录调控网络 (TRN),并为所有预测的调控赋予了统计学意义值。结果,具有 TRN 的棒状杆菌菌株数量增加了二十倍,后端和前端都进行了重新实现,以支持新功能和未来数据库的增长。CoryneRegNet 7 是最大的棒状杆菌属 TRN 数据库,有助于阐明使适应、生存和感染成为可能的转录机制。