Biphasic regulation of transcriptional surge generated by the gene feedback loop in a two-component system

Author:

Liu Wen1,Li Xiang12,Qi Hong3,Wu Yuning1,Qu Jing1,Yin Zhiyong1,Gao Xuejuan1,Han Aidong24,Shuai Jianwei125ORCID

Affiliation:

1. Research Institute for Biomimetics and Soft Matter, Fujian Provincial Key Lab for Soft Functional Materials Research, Department of Physics, Xiamen University, Xiamen 361005, China

2. State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, Xiamen University, Xiamen 361102, China

3. Complex Systems Research Center, Shanxi University, Taiyuan 030006, China

4. School of Life Sciences, Xiamen University, Xiamen 361102, China

5. National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen 361102, China

Abstract

Abstract Motivation Transcriptional surges generated by two-component systems (TCSs) have been observed experimentally in various bacteria. Suppression of the transcriptional surge may reduce the activity, virulence and drug resistance of bacteria. In order to investigate the general mechanisms, we use a PhoP/PhoQ TCS as a model system to derive a comprehensive mathematical modeling that governs the surge. PhoP is a response regulator, which serves as a transcription factor under a phosphorylation-dependent modulation by PhoQ, a histidine kinase. Results Our model reveals two major signaling pathways to modulate the phosphorylated PhoP (P-PhoP) level, one of which promotes the generation of P-PhoP, while the other depresses the level of P-PhoP. The competition between the P-PhoP-promoting and the P-PhoP-depressing pathways determines the generation of the P-PhoP surge. Furthermore, besides PhoQ, PhoP is also a bifunctional modulator that contributes to the dynamic control of P-PhoP state, leading to a biphasic regulation of the surge by the gene feedback loop. In summary, the mechanisms derived from the PhoP/PhoQ system for the transcriptional surges provide a better understanding on such a sophisticated signal transduction system and aid to develop new antimicrobial strategies targeting TCSs. Availability and implementation https://github.com/jianweishuai/TCS. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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