Nuclear localization of the transcriptional activator NF-kappaB (nuclear factor kappaB) is controlled in mammalian cells by three isoforms of NF-kappaB inhibitor protein: IkappaBalpha, -beta, and - epsilon. Based on simplifying reductions of the IkappaB-NF-kappaB signaling module in knockout cell lines, we present a computational model that describes the temporal control of NF-kappaB activation by the coordinated degradation and synthesis of IkappaB proteins. The model demonstrates that IkappaBalpha is responsible for strong negative feedback that allows for a fast turn-off of the NF-kappaB response, whereas IkappaBbeta and - epsilon function to reduce the system's oscillatory potential and stabilize NF-kappaB responses during longer stimulations. Bimodal signal-processing characteristics with respect to stimulus duration are revealed by the model and are shown to generate specificity in gene expression.

Molecular noise restricts the ability of an individual cell to resolve input signals of different strengths and gather information about the external environment. Transmitting information through complex signaling networks with redundancies can overcome this limitation. We developed an integrative theoretical and experimental framework, based on the formalism of information theory, to quantitatively predict and measure the amount of information transduced by molecular and cellular networks. Analyzing tumor necrosis factor (TNF) signaling revealed that individual TNF signaling pathways transduce information sufficient for accurate binary decisions, and an upstream bottleneck limits the information gained via multiple pathways together. Negative feedback to this bottleneck could both alleviate and enhance its limiting effect, despite decreasing noise. Bottlenecks likewise constrain information attained by networks signaling through multiple genes or cells.

Heart tissue possesses complex structural organization on multiple scales, from macro- to nano-, but nanoscale control of cardiac function has not been extensively analyzed. Inspired by ultrastructural analysis of the native tissue, we constructed a scalable, nanotopographically controlled model of myocardium mimicking the in vivo ventricular organization. Guided by nanoscale mechanical cues provided by the underlying hydrogel, the tissue constructs displayed anisotropic action potential propagation and contractility characteristic of the native tissue. Surprisingly, cell geometry, action potential conduction velocity, and the expression of a cell–cell coupling protein were exquisitely sensitive to differences in the substratum nanoscale features of the surrounding extracellular matrix. We propose that controlling cell–material interactions on the nanoscale can stipulate structure and function on the tissue level and yield novel insights into in vivo tissue physiology, while providing materials for tissue repair.

In addition to preventing crosstalk among related signaling pathways, scaffold proteins might facilitate signal transduction by preforming multimolecular complexes that can be rapidly activated by incoming signal. In many cases, such as mitogen-activated protein kinase (MAPK) cascades, scaffold proteins are necessary for full activation of a signaling pathway. To date, however, no detailed biochemical model of scaffold action has been suggested. Here we describe a quantitative computer model of MAPK cascade with a generic scaffold protein. Analysis of this model reveals that formation of scaffold-kinase complexes can be used effectively to regulate the specificity, efficiency, and amplitude of signal propagation. In particular, for any generic scaffold there exists a concentration value optimal for signal amplitude. The location of the optimum is determined by the concentrations of the kinases rather than their binding constants and in this way is scaffold independent. This effect and the alteration of threshold properties of the signal propagation at high scaffold concentrations might alter local signaling properties at different subcellular compartments. Different scaffold levels and types might then confer specialized properties to tune evolutionarily conserved signaling modules to specific cellular contexts.

Eukaryotic cells can detect shallow gradients of chemoattractants with exquisite precision and respond quickly to changes in the gradient steepness and direction. Here, we describe a set of models explaining both adaptation to uniform increases in chemoattractant and persistent signaling in response to gradients. We demonstrate that one of these models can be mapped directly onto the biochemical signal-transduction pathways underlying gradient sensing in amoebae and neutrophils. According to this scheme, a locally acting activator (PI3-kinase) and a globally acting inactivator (PTEN or a similar phosphatase) are coordinately controlled by the G-protein activation. This signaling system adapts perfectly to spatially homogeneous changes in the chemoattractant. In chemoattractant gradients, an imbalance between the action of the activator and the inactivator results in a spatially oriented persistent signaling, amplified by a substrate supply-based positive feedback acting through small G-proteins. The amplification is activated only in a continuous presence of the external signal gradient, thus providing the mechanism for sensitivity to gradient alterations. Finally, based on this mapping, we make predictions concerning the dynamics of signaling. We propose that the underlying principles of perfect adaptation and substrate supply-based positive feedback will be found in the sensory systems of other chemotactic cell types.

The architecture of the extracellular matrix (ECM) directs cell behavior by providing spatial and mechanical cues to which cells respond. In addition to soluble chemical factors, physical interactions between the cell and ECM regulate primary cell processes, including differentiation, migration, and proliferation. Advances in microtechnology and, more recently, nanotechnology provide a powerful means to study the influence of the ECM on cell behavior. By recapitulating local architectures that cells encounter in vivo, we can elucidate and dissect the fundamental signal transduction pathways that control cell behavior in critical developmental, physiological, and pathological processes.

Biological networks, such as those describing gene regulation, signal transduction, and neural synapses, are representations of large-scale dynamic systems. Discovery of organizing principles of biological networks can be enhanced by embracing the notion that there is a deep interplay between network structure and system dynamics. Recently, many structural characteristics of these non-random networks have been identified, but dynamical implications of the features have not been explored comprehensively. We demonstrate by exhaustive computational analysis that a dynamical property—stability or robustness to small perturbations—is highly correlated with the relative abundance of small subnetworks (network motifs) in several previously determined biological networks. We propose that robust dynamical stability is an influential property that can determine the non-random structure of biological networks.

Mechanical forces play important roles in the regulation of various biological processes at the molecular and cellular level, such as gene expression, adhesion, migration, and cell fate, which are essential to the maintenance of tissue homeostasis. In this review, we discuss emerging bioengineered tools enabled by microscale technologies for studying the roles of mechanical forces in cell biology. In addition to traditional mechanobiology experimental techniques, we review recent advances of microelectromechanical systems (MEMS)-based approaches for cell mechanobiology and discuss how microengineered platforms can be used to generate in vivo-like micromechanical environment in in vitro settings for investigating cellular processes in normal and pathophysiological contexts. These capabilities also have significant implications for mechanical control of cell and tissue development and cell-based regenerative therapies.