A slow response may not be desirable for many signaling tasks.
It has long been predicted, and later experimentally shown, that positive feedback slows down the kinetics of response protein synthesis ( Maeda and Sano, 2006 Savageau, 1974) because of the time required to produce the TF to a level sufficient for activation. Positive autoregulation also has a significant impact on response dynamics ( Maeda and Sano, 2006 Mitrophanov et al., 2010). All these features could potentially benefit or impair specific pathways. Positive autoregulation or auto-activation of a TF leads to more TF molecules and the consequent amplification of the TF-regulated output response ( Mitrophanov et al., 2010 Miyashiro and Goulian, 2008), as well as amplification of noise or cell-cell variations ( Chalancon et al., 2012 Miyashiro and Goulian, 2008). It has been established that positive autoregulation can increase the sensitivity to signals, produce a switch-like response, and promote bistability, history-dependent hysteretic responses, or memory ( Alon, 2007 Mitrophanov and Groisman, 2008 Tiwari et al., 2011 Xiong and Ferrell, 2003). Positive autoregulation occurs when a transcription factor (TF) activates its own expression. We used a bacterial two-component system to examine how cells balance the benefit and cost of positive autoregulation, a common motif widely distributed in diverse regulatory networks. Less experimental investigation has focused on how biochemical properties place constraints on individual motifs and how cells are evolved to overcome such restrictions. Molecular mechanisms, dynamic behaviors, and functional roles of these motifs have been extensively studied both experimentally and theoretically ( Maeda and Sano, 2006 Mitrophanov and Groisman, 2008 Rosenfeld et al., 2002 Shen-Orr et al., 2002), often in the context of how specific motifs perform certain functions to benefit cells.
A few recurring network motifs, such as feed-forward loops and autoregulatory circuits, constitute the basic building blocks for more sophisticated regulatory networks ( Alon, 2007 Lim et al., 2013 Wall et al., 2004). Such regulatory schemes offer great flexibility for accurate control of gene expression levels and dynamics upon environmental changes.Ĭells have evolved complex gene regulatory networks to produce appropriate amounts of proteins at appropriate times to adapt to ever-changing environments. We demonstrate the fitness advantages for the coupled feedbacks in both dynamic and stable environments. An observed fast response that exceeds the limit led to the prediction and discovery of a coupled negative autoregulation, which allows fast gene expression without increasing steady-state levels. Quantitation of the cellular activities enables accurate modeling of the response dynamics to describe how requirements for optimal protein concentrations place limits on response speed. coli PhoB-PhoR two-component system, which overcomes the cost of positive feedback and achieves both fast and optimal steadystate response for maximal fitness across different environments. Here, we describe a regulatory scheme in the E. A fundamental trade-off between rapid response and optimal expression of genes below cytotoxic levels exists for many signaling circuits, particularly for positively autoregulated systems with an inherent response delay.
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