Department of Bacteriology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
PLoS Genet. 2010 Jul 22;6(7):e1001027. doi: 10.1371/journal.pgen.1001027.
The processes underlying the evolution of regulatory networks are unclear. To address this question, we used a comparative genomics approach that takes advantage of the large number of sequenced bacterial genomes to predict conserved and variable members of transcriptional regulatory networks across phylogenetically related organisms. Specifically, we developed a computational method to predict the conserved regulons of transcription factors across alpha-proteobacteria. We focused on the CRP/FNR super-family of transcription factors because it contains several well-characterized members, such as FNR, FixK, and DNR. While FNR, FixK, and DNR are each proposed to regulate different aspects of anaerobic metabolism, they are predicted to recognize very similar DNA target sequences, and they occur in various combinations among individual alpha-proteobacterial species. In this study, the composition of the respective FNR, FixK, or DNR conserved regulons across 87 alpha-proteobacterial species was predicted by comparing the phylogenetic profiles of the regulators with the profiles of putative target genes. The utility of our predictions was evaluated by experimentally characterizing the FnrL regulon (a FNR-type regulator) in the alpha-proteobacterium Rhodobacter sphaeroides. Our results show that this approach correctly predicted many regulon members, provided new insights into the biological functions of the respective regulons for these regulators, and suggested models for the evolution of the corresponding transcriptional networks. Our findings also predict that, at least for the FNR-type regulators, there is a core set of target genes conserved across many species. In addition, the members of the so-called extended regulons for the FNR-type regulators vary even among closely related species, possibly reflecting species-specific adaptation to environmental and other factors. The comparative genomics approach we developed is readily applicable to other regulatory networks.
调控网络进化的背后机制尚不清楚。为了解决这个问题,我们采用了一种比较基因组学的方法,利用大量已测序的细菌基因组,预测了在系统发育上相关的生物体中,转录调控网络的保守和可变成员。具体来说,我们开发了一种计算方法来预测α-变形菌中转录因子的保守调节子。我们专注于 CRP/FNR 转录因子超家族,因为它包含几个特征明确的成员,如 FNR、FixK 和 DNR。虽然 FNR、FixK 和 DNR 分别被认为调节不同方面的厌氧代谢,但它们被预测识别非常相似的 DNA 靶序列,并且它们在各个α-变形菌物种中以不同的组合出现。在这项研究中,通过比较调节因子的系统发育轮廓与假定的靶基因的轮廓,预测了 87 种α-变形菌中各自的 FNR、FixK 或 DNR 保守调节子的组成。通过实验表征α-变形菌 Rhodobacter sphaeroides 中的 FnrL 调节子(一种 FNR 型调节因子),评估了我们预测的实用性。我们的结果表明,这种方法正确地预测了许多调节子成员,为这些调节因子的各自调节子的生物学功能提供了新的见解,并为相应转录网络的进化提出了模型。我们的发现还预测,至少对于 FNR 型调节因子而言,存在一个跨越许多物种的保守核心靶基因集。此外,即使在密切相关的物种中,FNR 型调节因子所谓的扩展调节子的成员也存在差异,这可能反映了物种对环境和其他因素的特定适应。我们开发的比较基因组学方法易于应用于其他调控网络。