For T cell receptors, some breakups might not last forever.

Does the affinity or half-life of peptide-MHC-T cell receptor (TCR) interactions determine T cell activation? In this issue of Immunity, Aleksic et al. (2010) propose a role for the on rate through multiple rebindings to the same TCR.

Optimal resource allocation in cellular sensing systems.

Living cells deploy many resources to sense their environments, including receptors, downstream signaling molecules, time, and fuel. However, it is not known which resources fundamentally limit the precision of sensing, like weak links in a chain, and which can compensate each other, leading to trade-offs between them. We present a theory for the optimal design of the large class of sensing systems in which a receptor drives a push-pull network. The theory identifies three classes of resources that are required for sensing: receptors and their integration time, readout molecules, and energy (fuel turnover). Each resource class sets a fundamental sensing limit, which means that the sensing precision is bounded by the limiting resource class and cannot be enhanced by increasing another class--the different classes cannot compensate each other. This result yields a previously unidentified design principle, namely that of optimal resource allocation in cellular sensing. It states that, in an optimally designed sensing system, each class of resources is equally limiting so that no resource is wasted. We apply our theory to what is arguably the best-characterized sensing system in biology, the chemotaxis network of Escherichia coli. Our analysis reveals that this system obeys the principle of optimal resource allocation, indicating a selective pressure for the efficient design of cellular sensing systems.

Viral antigen density and confinement time regulate the reactivity pattern of CD4 T-cell responses to vaccinia virus infection.

T-cell recognition of ligands is polyspecific. This translates into antiviral T-cell responses having a range of potency and specificity for viral ligands. How these ligand recognition patterns are established is not fully understood. Here, we show that an activation threshold regulates whether robust CD4 T-cell activation occurs following viral infection. The activation threshold was variable because of its dependence on the density of the viral peptide (p)MHC displayed on infected cells. Furthermore, the activation threshold was not observed to be a specific equilibrium affinity (K(D)) or half-life (t(1/2)) of the TCR-viral pMHC interaction, rather it correlated with the confinement time of TCR-pMHC interactions, i.e., the half-life (t(1/2)) of the interaction accounting for the effects of TCR-pMHC rebinding. One effect of a variable activation threshold is to allow high-density viral pMHC ligands to expand CD4 T cells with a variety of potency and peptide cross-reactivity patterns for the viral pMHC ligand, some of which are only poorly activated by infections that produce a lower density of the viral pMHC ligand. These results argue that antigen concentration is a key component in determining the pattern of K(D), t(1/2) and peptide cross-reactivity of the TCRs expressed on CD4 T cells responding to infection.

Energy dissipation and noise correlations in biochemical sensing.

To measure chemical concentrations, cells need to extract information from stochastic receptor signals via signaling networks which are also inherently stochastic. Here, we study how the accuracy of sensing depends on the correlations between these extrinsic and intrinsic sources of noise. We find that the sensing precision of signaling networks that are not driven out of equilibrium is fundamentally limited by the fluctuation-dissipation theorem, which generates a tradeoff between the removal of extrinsic and intrinsic noise. As a result, the sensing precision of equilibrium systems is limited by the number of receptors; the downstream network can never improve sensing. To lift the tradeoff, energy dissipation is essential. This allows the receptor to transduce the signal as a catalyst and enables time integration of the receptor state. To beat the sensing limit of equilibrium systems, a canonical nonequilibrium signaling network based on the push-pull motif needs to dissipate at least 1k_{B}T per receptor.

Fast on-rates allow short dwell time ligands to activate T cells.

Two contrasting theories have emerged that attempt to describe T-cell ligand potency, one based on the t(1/2) of the interaction and the other based on the equilibrium affinity (K(D)). Here, we have identified and studied an extensive set of T-cell receptor (TCR)-peptide-MHC (pMHC) interactions for CD4(+) cells that have differential K(D)s and kinetics of binding. Our data indicate that ligands with a short t(1/2) can be highly stimulatory if they have fast on-rates. Simple models suggest these fast kinetic ligands are stimulatory because the pMHCs bind and rebind the same TCR several times. Rebinding occurs when the TCR-pMHC on-rate outcompetes TCR-pMHC diffusion within the cell membrane, creating an aggregate t(1/2) (t(a)) that can be significantly longer than a single TCR-pMHC encounter. Accounting for t(a), ligand potency is K(D)-based when ligands have fast on-rates (k(on)) and t(1/2)-dependent when they have slow k(on). Thus, TCR-pMHC k(on) allow high-affinity short t(1/2) ligands to follow a kinetic proofreading model.

Identifying dynamical bottlenecks of stochastic transitions in biochemical networks.

In biochemical networks, identifying key proteins and protein-protein reactions that regulate fluctuation-driven transitions leading to pathological cellular function is an important challenge. Using large deviation theory, we develop a semianalytical method to determine how changes in protein expression and rate parameters of protein-protein reactions influence the rate of such transitions. Our formulas agree well with computationally costly direct simulations and are consistent with experiments. Our approach reveals qualitative features of key reactions that regulate stochastic transitions.

Fundamental limits on sensing chemical concentrations with linear biochemical networks.

Living cells often need to extract information from biochemical signals that are noisy. We study how accurately cells can measure chemical concentrations with signaling networks that are linear. For stationary signals of long duration, they can reach, but not beat, the Berg-Purcell limit, which relies on uniformly averaging in time the fluctuations in the input signal. For short times or nonstationary signals, however, they can beat the Berg-Purcell limit, by nonuniformly time averaging the input. We derive the optimal weighting function for time averaging and use it to provide the fundamental limit of measuring chemical concentrations with linear signaling networks.

Stochastic responses may allow genetically diverse cell populations to optimize performance with simpler signaling networks.

Two theories have emerged for the role that stochasticity plays in biological responses: first, that it degrades biological responses, so the performance of biological signaling machinery could be improved by increasing molecular copy numbers of key proteins; second, that it enhances biological performance, by enabling diversification of population-level responses. Using T cell biology as an example, we demonstrate that these roles for stochastic responses are not sufficient to understand experimental observations of stochastic response in complex biological systems that utilize environmental and genetic diversity to make cooperative responses. We propose a new role for stochastic responses in biology: they enable populations to make complex responses with simpler biochemical signaling machinery than would be required in the absence of stochasticity. Thus, the evolution of stochastic responses may be linked to the evolvability of different signaling machineries.

Signaling cascades modulate the speed of signal propagation through space.

BACKGROUND: Cells are not mixed bags of signaling molecules. As a consequence, signals must travel from their origin to distal locations. Much is understood about the purely diffusive propagation of signals through space. Many signals, however, propagate via signaling cascades. Here, we show that, depending on their kinetics, cascades speed up or slow down the propagation of signals through space, relative to pure diffusion. METHODOLOGY/PRINCIPAL FINDINGS: We modeled simple cascades operating under different limits of Michaelis-Menten kinetics using deterministic reaction-diffusion equations. Cascades operating far from enzyme saturation speed up signal propagation; the second mobile species moves more quickly than the first through space, on average. The enhanced speed is due to more efficient serial activation of a downstream signaling module (by the signaling molecule immediately upstream in the cascade) at points distal from the signaling origin, compared to locations closer to the source. Conversely, cascades operating under saturated kinetics, which exhibit zero-order ultrasensitivity, can slow down signals, ultimately localizing them to regions around the origin. CONCLUSIONS/SIGNIFICANCE: Signal speed modulation may be a fundamental function of cascades, affecting the ability of signals to penetrate within a cell, to cross-react with other signals, and to activate distant targets. In particular, enhanced speeds provide a way to increase signal penetration into a cell without needing to flood the cell with large numbers of active signaling molecules; conversely, diminished speeds in zero-order ultrasensitive cascades facilitate strong, but localized, signaling.

Molecular origin and functional consequences of digital signaling and hysteresis during Ras activation in lymphocytes.

Activation of Ras proteins underlies functional decisions in diverse cell types. Two molecules, Ras-GRP and SOS (Ras-guanine nucleotide-releasing protein and Son of Sevenless, respectively), catalyze Ras activation in lymphocytes. Binding of active Ras to the allosteric pocket of SOS markedly increases the activity of SOS. Thus, there is a positive feedback loop regulating SOS. Combining in silico and in vitro studies, we demonstrate that "digital" signaling in lymphocytes (cells are "on" or "off") is predicated on this allosteric regulation of SOS. The SOS feedback loop leads to hysteresis in the dose-response curve, which may enable T cells to exhibit "memory" of past encounters with antigen. Ras activation by Ras-GRP alone is "analog" (a graded increase in activation in response to an increase in the amplitude of the stimulus). We describe how the complementary analog (Ras-GRP) and digital (SOS) pathways act on Ras to efficiently convert analog input to digital output and make predictions regarding the importance of digital signaling in lymphocyte function and development.