Two Component Systems: Physiological Effect of a Third Component

Signal transduction systems mediate the response and adaptation of organisms to environmental changes. In prokaryotes, this signal transduction is often done through Two Component Systems (TCS). These TCS are phosphotransfer protein cascades, and in their prototypical form they are composed by a kinase that senses the environmental signals (SK) and by a response regulator (RR) that regulates the cellular response. This basic motif can be modified by the addition of a third protein that interacts either with the SK or the RR in a way that could change the dynamic response of the TCS module. In this work we aim at understanding the effect of such an additional protein (which we call “third component”) on the functional properties of a prototypical TCS. To do so we build mathematical models of TCS with alternative designs for their interaction with that third component. These mathematical models are analyzed in order to identify the differences in dynamic behavior inherent to each design, with respect to functionally relevant properties such as sensitivity to changes in either the parameter values or the molecular concentrations, temporal responsiveness, possibility of multiple steady states, or stochastic fluctuations in the system. The differences are then correlated to the physiological requirements that impinge on the functioning of the TCS. This analysis sheds light on both, the dynamic behavior of synthetically designed TCS, and the conditions under which natural selection might favor each of the designs. We find that a third component that modulates SK activity increases the parameter space where a bistable response of the TCS module to signals is possible, if SK is monofunctional, but decreases it when the SK is bifunctional. The presence of a third component that modulates RR activity decreases the parameter space where a bistable response of the TCS module to signals is possible

A survey of HK, HPt, and RR domains and their organization in two-component systems and phosphorelay proteins of organisms with fully sequenced genomes

Two Component Systems and Phosphorelays (TCS/PR) are environmental signal transduction cascades in prokaryotes and, less frequently, in eukaryotes. The internal domain organization of proteins and the topology of TCS/PR cascades play an important role in shaping the responses of the circuits. It is thus important to maintain updated censuses of TCS/PR proteins in order to identify the various topologies used by nature and enable a systematic study of the dynamics associated with those topologies. To create such a census, we analyzed the proteomes of 7,609 organisms from all domains of life with fully sequenced and annotated genomes. To begin, we survey each proteome searching for proteins containing domains that are associated with internal signal transmission within TCS/PR: Histidine Kinase (HK), Response Regulator (RR) and Histidine Phosphotranfer (HPt) domains, and analyze how these domains are arranged in the individual proteins. Then, we find all types of operon organization and calculate how much more likely are proteins that contain TCS/PR domains to be coded by neighboring genes than one would expect from the genome background of each organism. Finally, we analyze if the fusion of domains into single TCS/PR proteins is more frequently observed than one might expect from the background of each proteome. We find 50 alternative ways in which the HK, HPt, and RR domains are observed to organize into single proteins. In prokaryotes, TCS/PR coding genes tend to be clustered in operons. 90% of all proteins identified in this study contain just one of the three domains, while 8% of the remaining proteins combine one copy of an HK, a RR, and/or an HPt domain. In eukaryotes, 25% of all TCS/PR proteins have more than one domain. These results might have implications for how signals are internally transmitted within TCS/PR cascades. These implications could explain the selection of the various designs in alternative circumstances

Steady state signal-response curves for the various TCS modules.

<p>Each plot shows the steady state levels of the phosphorylated RR in the y axis at different values of the signal k₁ (SK autophosphorylation rate constant) or k₂ (SKP dephosphorylation rate constant) in the x axis. When the signal modulates SK dephosphorylation (changes in k₂), the system behaves symmetrically to when SK phosphorylation (changes in k₁) is modulated. In the first case, increases in signal intensity cause the fraction of RRP to decrease, while in the latter, increases in signal intensity cause the fraction of RRP to increase. A, C, E: Response curves of TCS modules with monofunctional sensor. B, D, F: Response curves of TCS modules with bifunctional sensor. A, B, Response curves of Model A. C, D: Mathematically controlled comparison between the response curves of Model B and those of Model A. E, F: Mathematically controlled comparison between the response curves of Model C and those of Model A. Mathematical controls are implemented to make sure that the differences in response between the alternative modules are due to the presence of third component and not to other spurious differences.</p

Quantitative Operating Principles of Yeast Metabolism during Adaptation to Heat Stress

Summary: Microorganisms evolved adaptive responses to survive stressful challenges in ever-changing environments. Understanding the relationships between the physiological/metabolic adjustments allowing cellular stress adaptation and gene expression changes being used by organisms to achieve such adjustments may significantly impact our ability to understand and/or guide evolution. Here, we studied those relationships during adaptation to various stress challenges in Saccharomyces cerevisiae, focusing on heat stress responses. We combined dozens of independent experiments measuring whole-genome gene expression changes during stress responses with a simplified kinetic model of central metabolism. We identified alternative quantitative ranges for a set of physiological variables in the model (production of ATP, trehalose, NADH, etc.) that are specific for adaptation to either heat stress or desiccation/rehydration. Our approach is scalable to other adaptive responses and could assist in developing biotechnological applications to manipulate cells for medical, biotechnological, or synthetic biology purposes. : Evolution selects coordinated adaptive changes in gene expression and metabolism that ensure survival to stress challenges. Pereira et al. identify quantitative ranges for those changes in a set of genes and physiological variables (production of ATP, trehalose, NADH, etc.) that are specific for adaptation to heat stress, desiccation/rehydration, or pH. Keywords: biological design principles, systems biology, computational biology, multilevel modeling, integrative biology, metabolism, optimizatio

Temporal responsiveness curves of Models A, B, and C.

<p>The systems are at an initial steady state and, at time zero, the signal, represented in the x axis, changes instantaneously and the time it takes for the system to get to within 90% of the new steady state is measured and plotted in the y axis. A–D: Response times of TCS with monofunctional SK. E–H: Response times of TCS with bifunctional SK. The OFF to ON plots start with the systems at an OFF steady state (low levels of RRP) corresponding to a low value of k₁ (A, C, E, G) or a high value of k₂ (B, D, F, H). The signal is then changed to increase the steady state level of RRP. The ON to OFF plots start with the systems at an ON steady state (high levels of RRP) corresponding to a high value of k₁ or a low value of k₂. The signal is then changed to decrease the steady state level of RRP. Peaks that indicate slower response times are located immediately outside the range of bistability. The lack of a peak in a curve can be due to monostability or irreversibility. The dashed lines indicate the signal value at which Models B and C exit its bistable range. Absence of a dashed line indicates irreversible turning ON or OFF of the system (Model B in panel C ) or absence of bistability (see the signal-response curves of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031095#pone-0031095-g002" target="_blank">Figure 2</a>).</p

Experiments to analyze the effect of changes in different parameter values and protein concentrations on the range of bistability for the alternative TCS modules^a.

a<p>The steady state(s) for the three models by scanning a)k₁ (SK autophosphorylation reaction rate constant) and b)k₂ (SKP autodephosphorylation reaction rate constant) between 10⁻⁶ and 10 at different values of the parameters named in the table (see text for details).</p

Stochastic time trajectories after an instantaneous change in the signal, for the three systems modeled with a monofunctional SK.

<p>A mathematically controlled comparison between Models A and B, and between Models A and C was performed as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031095#s4" target="_blank">methods</a>. The results for three individual runs for each value of k1 or k2 are plotted in each panel. Panels in the first column correspond to Model A controlled to be as similar as possible to Model B. Panels in the second column correspond to Model B. Panels in the third column correspond to Model A controlled to be as similar as possible to Model C. Panels in the fourth column correspond to Model C. The circles indicate lines that are replicates of the same simulation. Simulations marked with an arrow correspond to a signal intensity close to the bistability threshold and show slower and noisier responses. The OFF to ON plots start with the systems at an OFF steady state (low levels of RRP) corresponding to a low value of k1 or a high value of k2. At time zero, there is an instantaneous increase in k1 or decrease in k2. The ON to OFF plots start with the systems at an ON steady state (high levels of RRP) corresponding to a high value of k1 or a low value of k2. At time zero, there is an instantaneous decrease in k1 or increase in k2. The values for k1 or k2 are chosen to be below, next to and above the threshold value at which the system switches from OFF to ON, or from ON to OFF. See text for further details.</p

Percentage of parameter space where a bistable response is possible for Models A, B, and C^a.

a<p>A|B stands for Model A controlled for Model B. A|C stands for Model A controlled for Model C.</p><p>k_i: kinetic constants for the reactions in the systems shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031095#pone-0031095-g001" target="_blank">Figure 1</a>. SKt: total concentration of SK. RRt: total concentration of RR. TCt: total concentration of third component protein. The parameter space for k_i,k_j, and k_k was scanned between absolute values of 10⁻⁶ and 10 for each of the parameters. Sampling was uniform in logarithmic space.</p>b<p>Percentage of the parameter space of k_i, k_j and k_k where bistability is found for Models A, B, and C respectively.</p>c<p>Percentage of the parameter space where bistability is found in Model A controlled for B and for C, respectively.</p><p>NA Non Applicable. Mono functional systems have k₈ = 0. The concentration of TC = 0 in Model A. Model A can not be scanned with respect to the concentration of SK in the controlled comparisons, because SK is independently fixed to make the dynamical response of Model A more similar to those of Models B and C.</p

Percentage of parameter space where bistable responses are possible^a.

a<p>Some bidimensional sections of the multidimensional parameter space of bistability are shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031095#pone.0031095.s002" target="_blank">Figure S2</a>. The results show that in TCS with a bifunctional SK, both a TC_SK and a TC_RR cause a decrease in the size of the parametric region of bistability, with one exception: Model C has a larger parametric region of bistability when the signaling target is SK autophosphorylation (k₁). However, in systems with a monofunctional SK, a TCSK causes an increase and a TCRR causes a decrease in the size of the parametric region of bistability if the environment modulates the SK dephosphorylation (k₂). A|B stands for Model A controlled for Model B. A|C stands for Model A controlled for Model C.</p

Summary of the comparison of physiologically relevant criteria between the alternative designs for TCS with bifunctional SK^a.

a<p>The model with the largest number of “+” signs for a given criterion is the one with the best performance with respect to that criterion.</p><p>A|B stands for Model A controlled for Model B. A|C stands for Model A controlled for Model C.</p