Computation and measurement of cell decision making errors using single cell data.

In this study a new computational method is developed to quantify decision making errors in cells, caused by noise and signaling failures. Analysis of tumor necrosis factor (TNF) signaling pathway which regulates the transcription factor Nuclear Factor κB (NF-κB) using this method identifies two types of incorrect cell decisions called false alarm and miss. These two events represent, respectively, declaring a signal which is not present and missing a signal that does exist. Using single cell experimental data and the developed method, we compute false alarm and miss error probabilities in wild-type cells and provide a formulation which shows how these metrics depend on the signal transduction noise level. We also show that in the presence of abnormalities in a cell, decision making processes can be significantly affected, compared to a wild-type cell, and the method is able to model and measure such effects. In the TNF-NF-κB pathway, the method computes and reveals changes in false alarm and miss probabilities in A20-deficient cells, caused by cell's inability to inhibit TNF-induced NF-κB response. In biological terms, a higher false alarm metric in this abnormal TNF signaling system indicates perceiving more cytokine signals which in fact do not exist at the system input, whereas a higher miss metric indicates that it is highly likely to miss signals that actually exist. Overall, this study demonstrates the ability of the developed method for modeling cell decision making errors under normal and abnormal conditions, and in the presence of transduction noise uncertainty. Compared to the previously reported pathway capacity metric, our results suggest that the introduced decision error metrics characterize signaling failures more accurately. This is mainly because while capacity is a useful metric to study information transmission in signaling pathways, it does not capture the overlap between TNF-induced noisy response curves.

Noise decomposition of intracellular biochemical signaling networks using nonequivalent reporters.

Experimental measurements of biochemical noise have primarily focused on sources of noise at the gene expression level due to limitations of existing noise decomposition techniques. Here, we introduce a mathematical framework that extends classical extrinsic-intrinsic noise analysis and enables mapping of noise within upstream signaling networks free of such restrictions. The framework applies to systems for which the responses of interest are linearly correlated on average, although the framework can be easily generalized to the nonlinear case. Interestingly, despite the high degree of complexity and nonlinearity of most mammalian signaling networks, three distinct tumor necrosis factor (TNF) signaling network branches displayed linearly correlated responses, in both wild-type and perturbed versions of the network, across multiple orders of magnitude of ligand concentration. Using the noise mapping analysis, we find that the c-Jun N-terminal kinase (JNK) pathway generates higher noise than the NF-κB pathway, whereas the activation of c-Jun adds a greater amount of noise than the activation of ATF-2. In addition, we find that the A20 protein can suppress noise in the activation of ATF-2 by separately inhibiting the TNF receptor complex and JNK pathway through a negative feedback mechanism. These results, easily scalable to larger and more complex networks, pave the way toward assessing how noise propagates through cellular signaling pathways and create a foundation on which we can further investigate the relationship between signaling system architecture and biological noise.

Engineering neuronal growth cones to promote axon regeneration over inhibitory molecules.

Neurons in the central nervous system (CNS) fail to regenerate axons after injuries due to the diminished intrinsic axon growth capacity of mature neurons and the hostile extrinsic environment composed of a milieu of inhibitory factors. Recent studies revealed that targeting a particular group of extracellular inhibitory factors is insufficient to trigger long-distance axon regeneration. Instead of antagonizing the growing list of impediments, tackling a common target that mediates axon growth inhibition offers an alternative strategy to promote axon regeneration. Neuronal growth cone, the machinery that derives axon extension, is the final converging target of most, if not all, growth impediments in the CNS. In this study, we aim to promote axon growth by directly targeting the growth cone. Here we report that pharmacological inhibition or genetic silencing of nonmuscle myosin II (NMII) markedly accelerates axon growth over permissive and nonpermissive substrates, including major CNS inhibitors such as chondroitin sulfate proteoglycans and myelin-associated inhibitors. We find that NMII inhibition leads to the reorganization of both actin and microtubules (MTs) in the growth cone, resulting in MT reorganization that allows rapid axon extension over inhibitory substrates. In addition to enhancing axon extension, we show that local blockade of NMII activity in axons is sufficient to trigger axons to grow across the permissive-inhibitory border. Together, our study proposes NMII and growth cone cytoskeletal components as effective targets for promoting axon regeneration.

Visualization of JNK activity dynamics with a genetically encoded fluorescent biosensor.

The signaling pathway mediated by JNK transduces different types of signals, such as stress stimuli and cytokines, into functional responses that mediate apoptosis, as well as proliferation, differentiation, and inflammation. To better characterize the dynamic information flow and signal processing of this pathway in the cellular context, a genetically encoded, fluorescent protein-based biosensor was engineered to detect endogenous JNK activity. This biosensor, named JNKAR1 (for JNK activity reporter), specifically detects stress- (ribotoxic and osmotic) and cytokine- (TNF-alpha) induced JNK activity in living cells with a 15 to 30% increase in the yellow-to-cyan emission ratio because of a phosphorylation-dependent increase in FRET between two fluorescent proteins. JNK activity was detected not only in the cytoplasm, but also in the nucleus, mitochondria, and plasma membrane with similar kinetics after induction of ribotoxic stress by anisomycin, suggesting relatively rapid signal propagation to the nuclear, mitochondrial, and plasma membrane compartments. Furthermore, quantitative single-cell analysis revealed that anisomycin-induced JNK activity exhibited ultrasensitivity, sustainability, and bimodality, features that are consistent with behaviors of bistable systems. The development of JNKAR1, therefore, laid a foundation for evaluating the signaling properties and behaviors of the JNK cascade in single living cells.

Nanoscale cues regulate the structure and function of macroscopic cardiac tissue constructs.

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.

The application of information theory to biochemical signaling systems.

Cell signaling can be thought of fundamentally as an information transmission problem in which chemical messengers relay information about the external environment to the decision centers within a cell. Due to the biochemical nature of cellular signal transduction networks, molecular noise will inevitably limit the fidelity of any messages received and processed by a cell's signal transduction networks, leaving it with an imperfect impression of its environment. Fortunately, Shannon's information theory provides a mathematical framework independent of network complexity that can quantify the amount of information that can be transmitted despite biochemical noise. In particular, the channel capacity can be used to measure the maximum number of stimuli a cell can distinguish based upon the noisy responses of its signaling systems. Here, we provide a primer for quantitative biologists that covers fundamental concepts of information theory, highlights several key considerations when experimentally measuring channel capacity, and describes successful examples of the application of information theoretic analysis to biological signaling.

High content cell screening in a microfluidic device.

A comprehensive, systems level understanding of cell signaling networks requires methods to efficiently assay multiple signaling species, at the level of single cells, responding to a variety of stimulation protocols. Here we describe a microfluidic device that enables quantitative interrogation of signaling networks in thousands of individual cells using immunofluorescence-based readouts. The device is especially useful for measuring the signaling activity of kinases, transcription factors, and/or target genes in a high throughput, high content manner. We demonstrate how the device may be used to measure detailed time courses of signaling responses to one or more soluble stimuli and/or chemical inhibitors as well as responses to a complex temporal pattern of multiple stimuli. Furthermore we show how the throughput and resolution of the device may be exploited in investigating the differences, if any, of signaling at the level of a single cell versus at the level of the population. In particular, we show that NF-kappaB activity dynamics in individual cells are not asynchronous and instead resemble the dynamics of the population average in contrast to studies of cells overexpressing p65-EGFP.

A scalable and integrative system for pathway bioinformatics and systems biology.

MOTIVATION: Progress in systems biology depends on developing scalable informatics tools to predictively model, visualize, and flexibly store information about complex biological systems. Scalability of these tools, as well as their ability to integrate within larger frameworks of evolving tools, is critical to address the multi-scale and size complexity of biological systems. RESULTS: Using current software technology, such as self-generation of database and object code from UML schemas, facilitates rapid updating of a scalable expert assistance system for modeling biological pathways. Distribution of key components along with connectivity to external data sources and analysis tools is achieved via a web service interface. AVAILABILITY: All sigmoid modeling software components and supplementary information are available through: http://www.igb.uci.edu/servers/sb.html.

Enhanced sensitivity to IGF-II signaling links loss of imprinting of IGF2 to increased cell proliferation and tumor risk.

Loss of imprinting (LOI) of the insulin-like growth factor-II gene (IGF2), leading to abnormal activation of the normally silent maternal allele, is a common human epigenetic population variant associated with a 5-fold increased frequency of colorectal neoplasia. Here, we show first that LOI leads specifically to increased expression of proliferation-related genes in mouse intestinal crypts. Surprisingly, LOI(+) mice also have enhanced sensitivity to IGF-II signaling, not simply increased IGF-II levels, because in vivo blockade with NVP-AEW541, a specific inhibitor of the IGF-II signaling receptor, showed reduction of proliferation-related gene expression to levels half that seen in LOI(-) mice. Signal transduction assays in microfluidic chips confirmed this enhanced sensitivity with marked augmentation of Akt/PKB signaling in LOI(+) cells at low doses of IGF-II, which was reduced in the presence of the inhibitor to levels below those found in LOI(-) cells, and was associated with increased expression of the IGF1 and insulin receptor genes. We exploited this increased IGF-II sensitivity to develop an in vivo chemopreventive strategy using the azoxymethane (AOM) mutagenesis model. LOI(+) mice treated with AOM showed a 60% increase in premalignant aberrant crypt foci (ACF) formation over LOI(-) mice. In vivo IGF-II blockade with NVP-AEW541 abrogated this effect, reducing ACF to a level 30% lower even than found in exposed LOI(-) mice. Thus, LOI increases cancer risk in a counterintuitive way, by increasing the sensitivity of the IGF-II signaling pathway itself, providing a previously undescribed epigenetic chemoprevention strategy in which cells with LOI are "IGF-II addicted" and undergo reduced tumorigenesis in the colon upon IGF-II pathway blockade.

Understanding NF-kappaB signaling via mathematical modeling.

Mammalian inflammatory signaling, for which NF-kappaB is a principal transcription factor, is an exquisite example of how cellular signaling pathways can be regulated to produce different yet specific responses to different inflammatory insults. Mathematical models, tightly linked to experiment, have been instrumental in unraveling the forms of regulation in NF-kappaB signaling and their underlying molecular mechanisms. Our initial model of the IkappaB-NF-kappaB signaling module highlighted the role of negative feedback in the control of NF-kappaB temporal dynamics and gene expression. Subsequent studies sparked by this work have helped to characterize additional feedback loops, the input-output behavior of the module, crosstalk between multiple NF-kappaB-activating pathways, and NF-kappaB oscillations. We anticipate that computational techniques will enable further progress in the NF-kappaB field, and the signal transduction field in general, and we discuss potential upcoming developments.

Information transduction capacity of noisy biochemical signaling networks.

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 integrated pathways. 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.

Integration of genotypic and phenotypic screening reveals molecular mediators of melanoma-stromal interaction.

Tumor-endothelium interactions are critical for tumor survival and metastasis. Melanomas can rapidly metastasize early in tumor progression, but the dependence of this aggressive behavior on tumor-stromal interaction is poorly understood. To probe the mechanisms involved, we developed a heterotypic coculture methodology, allowing simultaneous tracking of genomic and phenotypic changes in interacting tumor and endothelial cells in vitro. We found a dramatic rearrangement of endothelial cell networks into patterns reminiscent of vascular beds, even on plastic and glass. Multiple genes were upregulated in the process, many coding for cell surface and secreted proteins, including Neuropilin-2 (NRP2). A critical role of NRP2 in coordinated cell patterning and growth was confirmed using the coculture system. We conclude that NRP2 represents an important mediator of melanoma-endothelial interactions. Furthermore, the described methodology represents a powerful yet simple system to elucidate heterotypic intercellular interactions mediating diverse physiological and pathological processes.

Oscillatory signaling processes: the how, the why and the where.

Oscillatory processes in biological signal transduction have come under progressively increasing scrutiny in terms of their functional significance and mechanisms of emergence and regulation. Since oscillatory processes can be a by-product of rapid adaptation and can also easily emerge if the feedback underlying adaptive processes is inadvertently artificially enhanced, one needs to exercise caution in both claiming the existence of in vivo oscillations and seeking to assign to them a specific functional significance. Nevertheless, oscillations can be a powerful means of encoding and transferring information both in time and in space, thus possessing important potential advantages for evolutionary selection and stabilization. Thus periodicity in the cell responses to diverse persistent external stimuli might become a more recognized and even expected feature of signaling processes.

Models at the single cell level.

Many cellular behaviors cannot be completely captured or appropriately described at the cell population level. Noise induced by stochastic chemical reactions, spatially polarized signaling networks, and heterogeneous cell-cell communication are among the many phenomena that require fine-grained analysis. Accordingly, the mathematical models used to describe such systems must be capable of single cell or subcellular resolution. Here, we review techniques for modeling single cells, including models of stochastic chemical kinetics, spatially heterogeneous intracellular signaling, and spatial stochastic systems. We also briefly discuss applications of each type of model.

High-content screening in microfluidic devices.

IMPORTANCE OF THE FIELD: Miniaturization is the key to advancing the state of the art in high-content screening (HCS) in order to enable dramatic cost savings through reduced usage of expensive biochemical reagents and to enable large-scale screening on primary cells. Microfluidic technology offers the potential to enable HCS to be performed with an unprecedented degree of miniaturization. AREAS COVERED IN THIS REVIEW: This perspective highlights a real-world example from the authors' work of HCS assays implemented in a highly miniaturized microfluidic format. The advantages of this technology are discussed, including cost savings, high-throughput screening on primary cells, improved accuracy, the ability to study complex time-varying stimuli, and ease of automation, integration and scaling. WHAT THE READER WILL GAIN: The reader will understand the capabilities of anew microfluidics-based platform for HCS and the advantages it provides over conventional plate-based HCS. TAKE HOME MESSAGE: Microfluidics technology will drive significant advancements and broader usage and applicability of HCS in drug discovery.

An integrated micro-electro-fluidic and protein arraying system for parallel analysis of cell responses to controlled microenvironments.

Living cells have evolved sophisticated signaling networks allowing them to respond to a wide array of external stimuli. Microfluidic devices, facilitating the analysis of signaling networks through precise definition of the cellular microenvironment often lack the capacity of delivering multiple combinations of different signaling cues, thus limiting the throughput of the analysis. To address this limitation, we developed a microfabricated platform combining microfluidic definition of the cell medium composition with dielectrophoretic definition of cell positions and protein microarray-based presentation of diverse signaling inputs. Ligands combined at different concentrations were spotted along with an extracellular matrix protein onto a glass substratum in alignment with an electrode array. This substratum was combined with a polydimethylsiloxane chip for microfluidic control of the soluble medium components, in alignment with the electrode and protein arrays. Endothelial cells were captured by dielectrophoretic force, allowed to attach and spread on the protein spots; and the signaling output of the NF-kappaB pathway in response to diverse combinations of IGF1 and TNF was investigated, in the absence and presence of variable dose of the pathway inhibitor. The results suggested that cells can be potently activated by immobilized TNF with IGF1 having a modulating effect, and the response could be abolished to different degrees by the inhibitor. This study demonstrates considerable potential of combining precise cell patterning and liquid medium control with protein microarray technology for complex cell signaling studies in a high-throughput manner.

Subcellular-resolution delivery of a cytokine through precisely manipulated nanowires.

Precise delivery of molecular doses of biologically active chemicals to a pre-specified single cell among many, or a specific subcellular location, is still a largely unmet challenge hampering our understanding of cell biology. Overcoming this could allow unprecedented levels of cell manipulation and targeted intervention. Here, we show that gold nanowires conjugated with a cytokine such as tumour-necrosis factor-alpha can be transported along any prescribed trajectory or orientation using electrophoretic and dielectrophoretic forces to a specific location with subcellular resolution. The nanowire, 6 microm long and 300 nm in diameter, delivered the cytokine and activated canonical nuclear factor-kappaB signalling in a single cell. Combined computational modelling and experimentation indicated that cell stimulation was highly localized to the nanowire vicinity. This targeted delivery method has profound implications for controlling signalling events on the single cell level.

Using a microfluidic device for high-content analysis of cell signaling.

Quantitative analysis and understanding of signaling networks require measurements of the location and activities of key proteins over time, at the level of single cells, in response to various perturbations. Microfluidic devices enable such analyses to be conducted in a high-throughput and in a highly controlled manner. We describe in detail how to design and use a microfluidic device to perform such information-rich experiments.

Wires in the soup: quantitative models of cell signaling.

Living cells are capable of extracting information from their environments and mounting appropriate responses to a variety of challenges. The underlying signal transduction networks enabling this response can be quite complex, and so sophisticated computational modeling coupled with precise experimentation is required to unravel them. Although we are still at the beginning of this process, some recent examples of integrative analysis of cell signaling are very encouraging. Quantitative models of signaling pathways (e.g. NF-kappaB) can be gradually constructed through continuous experimental validation, and important lessons can be learnt from such exercises.