Open AccessOverlaid positive and negative feedback loops shape dynamical properties of PhoPQ two-component system
Author(s) -
Satyajit D. Rao,
Oleg A. Igoshin
Publication year - 2021
Publication title -
plos computational biology/plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/journal.pcbi.1008130
Subject(s) - negative feedback , positive feedback , robustness (evolution) , feedback control , feedback loop , biological system , feedback regulation , downregulation and upregulation , control theory (sociology) , steady state (chemistry) , biology , limiting , biophysics , microbiology and biotechnology , physics , computer science , chemistry , gene , control (management) , mathematics , biochemistry , artificial intelligence , mechanical engineering , mathematics education , computer security , quantum mechanics , voltage , control engineering , electrical engineering , engineering
Bacteria use two-component systems (TCSs) to sense environmental conditions and change gene expression in response to those conditions. To amplify cellular responses, many bacterial TCSs are under positive feedback control, i.e. increase their expression when activated. Escherichia coli Mg 2+ -sensing TCS, PhoPQ, in addition to the positive feedback, includes a negative feedback loop via the upregulation of the MgrB protein that inhibits PhoQ. How the interplay of these feedback loops shapes steady-state and dynamical responses of PhoPQ TCS to change in Mg 2+ remains poorly understood. In particular, how the presence of MgrB feedback affects the robustness of PhoPQ response to overexpression of TCS is unclear. It is also unclear why the steady-state response to decreasing Mg 2+ is biphasic, i.e. plateaus over a range of Mg 2+ concentrations, and then increases again at growth-limiting Mg 2+ . In this study, we use mathematical modeling to identify potential mechanisms behind these experimentally observed dynamical properties. The results make experimentally testable predictions for the regime with response robustness and propose a novel explanation of biphasic response constraining the mechanisms for modulation of PhoQ activity by Mg 2+ and MgrB. Finally, we show how the interplay of positive and negative feedback loops affects the network’s steady-state sensitivity and response dynamics. In the absence of MgrB feedback, the model predicts oscillations thereby suggesting a general mechanism of oscillatory or pulsatile dynamics in autoregulated TCSs. These results improve the understanding of TCS signaling and other networks with overlaid positive and negative feedback.