Negative auto-regulation increases the input dynamic-range of the arabinose system of Escherichia coli

Cells use general stress response pathways to activate diverse target genes in response to a variety of stresses. However, general stress responses coexist with more specific pathways that are activated by individual stresses, provoking the fundamental question of whether and how cells control the generality or specificity of their response to a particular stress. Here we address this issue using quantitative time-lapse microscopy of the Bacillus subtilis environmental stress response, mediated by σ B . We analyzed σ B activation in response to stresses such as salt and ethanol imposed at varying rates of increase. Dynamically, σ B responded to these stresses with a single adaptive activity pulse, whose amplitude depended on the rate at which the stress increased. This rate-responsive behavior can be understood from mathematical modeling of a key negative feedback loop in the underlying regulatory circuit. Using RNAseq we analyzed the effects of both rapid and gradual increases of ethanol and salt stress across the genome. Because of the rate responsiveness of σ B activation, salt and ethanol regulons overlap under rapid, but not gradual, increases in stress. Thus, the cell responds specifically to individual stresses that appear gradually, while using σ B to broaden the cellular response under more rapidly deteriorating conditions. Such dynamic control of specificity could be a critical function of other general stress response pathways.systems biology | single-cell dynamics | computational biology C ells must respond to, and anticipate, a wide range of stresses that occur on multiple timescales. For this purpose, many species use general stress response pathways, which activate a diverse set of target regulons in response to a variety of stresses. For example, in mammals, p53 is activated by DNA damage (1-4) and hypoxia (5, 6), among others, and activates genes that impact cell cycle progression (7), DNA repair (8, 9), apoptosis, and angiogenesis (10, 11). In yeast, Msn2/4 responds to nutritional stress (12), as well as to salt (13), calcium (14), heat, and other stresses (15). Bacteria also contain general stress response pathways, including the alternative sigma factors RpoS in Escherichia coli (16) and σ B in Bacillus subtilis (17).It has been proposed that general stress response pathways enable cells to cross-protect, by anticipating stresses that may not be present at the moment, but are likely to occur soon (18). For example, preexposure to specific stresses is known to enhance bacterial resistance to different stresses applied subsequently (19)(20)(21). This raises a basic question: How do cells determine when to use the general stress response rather than activating more specific individual pathways?The σ B -mediated general stress response of B. subtilis provides an ideal model system to address these issues. σ B is activated by diverse stresses through a well-characterized and conserved transcriptional and posttranscriptional circuit mechanism (17). In response to stress, it activates ∼200 target ge...

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“…S6B). Both of these roles are consistent with previous analysis of negative feedback loops (37)(38)(39).…”

Section: Mathematical Modeling Shows That the Stressosome Can Enablesupporting

confidence: 81%

Rate of environmental change determines stress response specificity

Young

Locke

Elowitz

2013

Proc. Natl. Acad. Sci. U.S.A.

119

142

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“…To introduce negative feedback, we assume that binding of pSub to either form of the kinase causes its reversible inactivation. We observe a more graded response as a function of the signal in the presence of negative feedback, as has been reported for some other biochemical networks (35)(36)(37), while the threshold value is unchanged (Fig. 1D).…”

Section: Loss Of Negative Feedback Can Eradicate Information Transfer Bysupporting

confidence: 65%

Information transfer by leaky, heterogeneous, protein kinase signaling systems

Voliotis¹,

Perrett

McWilliams³

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

122

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Cells must sense extracellular signals and transfer the information contained about their environment reliably to make appropriate decisions. To perform these tasks, cells use signal transduction networks that are subject to various sources of noise. Here, we study the effects on information transfer of two particular types of noise: basal (leaky) network activity and cell-to-cell variability in the componentry of the network. Basal activity is the propensity for activation of the network output in the absence of the signal of interest. We show, using theoretical models of protein kinase signaling, that the combined effect of the two types of noise makes information transfer by such networks highly vulnerable to the loss of negative feedback. In an experimental study of ERK signaling by single cells with heterogeneous ERK expression levels, we verify our theoretical prediction: In the presence of basal network activity, negative feedback substantially increases information transfer to the nucleus by both preventing a near-flat average response curve and reducing sensitivity to variation in substrate expression levels. The interplay between basal network activity, heterogeneity in network componentry, and feedback is thus critical for the effectiveness of protein kinase signaling. Basal activity is widespread in signaling systems under physiological conditions, has phenotypic consequences, and is often raised in disease. Our results reveal an important role for negative feedback mechanisms in protecting the information transfer function of saturable, heterogeneous cell signaling systems from basal activity.cell sensing | MAPK signaling | mutual information | ultrasensitivity | biomolecular networks C ells must sense extracellular concentrations and transfer the information contained about their environment reliably to make appropriate decisions. Understanding the process of information transfer from the biological environment to the nucleus (1) and studying quantitatively how information about the signal is lost along the way are essential in understanding cellular decision-making (2, 3). The signal transduction networks used by cells are subject to various sources of noise, and we are only beginning to explore how these affect the process of information transfer (4, 5). Here we focus, in the context of protein kinase (PK) signaling, on the little-studied effects of two important types of biological noise: cell-to-cell variability in the componentry of the network and basal network activity. The effect on information transfer of cell-to-cell variation (heterogeneity) in the protein componentry of signaling networks remains largely unexplored. Such variation is expected under physiological conditions (6) and underlies the variable responses observed for genetically identical cells exposed to the same stimulus or drug treatment (7-9). By basal activity, we mean the propensity for activation of the signaling system in the absence of the stimulus or signal of interest. Basal activity is widespread in signaling system...

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“…The AraC TF regulates the ara operon [1,14,18,20,26,52,54,59].Recent studies have shown that araCand the ara operon share a common regulatory protein,cAMP Receptor Protein (CRP),which is activated by cAMP. AraC both activates and represses the ara operonusing a DNA looping mechanism.…”

Section: The L-arabinose Operonmentioning

confidence: 99%

“…In an NAR motif, a transcription factor (TF) negatively regulates the promoter of its own gene or operon. This has been found to 1. dramatically increase response acceleration and 2. increase the stability of the gene product concentration response to noise [26,41].…”

Section: The L-arabinose Operonmentioning

confidence: 99%