Fractional killing arises from cell-to-cell variability in overcoming a caspase activity threshold.

When cells are exposed to death ligands such as TRAIL, a fraction undergoes apoptosis and a fraction survives; if surviving cells are re-exposed to TRAIL, fractional killing is once again observed. Therapeutic antibodies directed against TRAIL receptors also cause fractional killing, even at saturating concentrations, limiting their effectiveness. Fractional killing arises from cell-to-cell fluctuations in protein levels (extrinsic noise), but how this results in a clean bifurcation between life and death remains unclear. In this paper, we identify a threshold in the rate and timing of initiator caspase activation that distinguishes cells that live from those that die; by mapping this threshold, we can predict fractional killing of cells exposed to natural and synthetic agonists alone or in combination with sensitizing drugs such as bortezomib. A phenomenological model of the threshold also quantifies the contributions of two resistance genes (c-FLIP and Bcl-2), providing new insight into the control of cell fate by opposing pro-death and pro-survival proteins and suggesting new criteria for evaluating the efficacy of therapeutic TRAIL receptor agonists.

Parallel adaptive feedback enhances reliability of the Ca2+ signaling system.

Despite large cell-to-cell variations in the concentrations of individual signaling proteins, cells transmit signals correctly. This phenomenon raises the question of what signaling systems do to prevent a predicted high failure rate. Here we combine quantitative modeling, RNA interference, and targeted selective reaction monitoring (SRM) mass spectrometry, and we show for the ubiquitous and fundamental calcium signaling system that cells monitor cytosolic and endoplasmic reticulum (ER) Ca(2+) levels and adjust in parallel the concentrations of the store-operated Ca(2+) influx mediator stromal interaction molecule (STIM), the plasma membrane Ca(2+) pump plasma membrane Ca-ATPase (PMCA), and the ER Ca(2+) pump sarco/ER Ca(2+)-ATPase (SERCA). Model calculations show that this combined parallel regulation in protein expression levels effectively stabilizes basal cytosolic and ER Ca(2+) levels and preserves receptor signaling. Our results demonstrate that, rather than directly controlling the relative level of signaling proteins in a forward regulation strategy, cells prevent transmission failure by sensing the state of the signaling pathway and using multiple parallel adaptive feedbacks.

Neuropilin-2 contributes to tumorigenicity in a mouse model of Hedgehog pathway medulloblastoma.

The Hedgehog (Hh) signaling pathway has been implicated in the most common childhood brain tumor, medulloblastoma (MB). Given the toxicity of post-surgical treatments for MB, continued need exists for new, targeted therapies. Based upon our finding that Neuropilin (Nrp) transmembrane proteins are required for Hh signal transduction, we investigated the role of Nrp in MB cells. Cultured cells derived from a mouse Ptch (+/-) ;LacZ MB (Med1-MB), effectively modeled the Hh pathway-related subcategory of human MBs in vitro. Med1-MB cells maintained constitutively active Hh target gene transcription, and consistently formed tumors within one month after injection into mouse cerebella. The proliferation rate of Med1-MBs in culture was dependent upon Nrp2, while reducing Nrp1 function had little effect. Knockdown of Nrp2 prior to cell implantation significantly increased mouse survival, compared to transfection with a non-targeting siRNA. Knocking down Nrp2 specifically in MB cells avoided any direct effect on tumor vascularization. Nrp2 should be further investigated as a potential target for adjuvant therapy in patients with MB.

Robust neuronal symmetry breaking by Ras-triggered local positive feedback.

Neuronal polarity is initiated by a symmetry-breaking event whereby one out of multiple minor neurites undergoes rapid outgrowth and becomes the axon [1]. Axon formation is regulated by phosphatidylinositol 3-kinase (PI3K)-related signaling elements [2-10] that drive local actin [11] and microtubule reorganization [3, 12], but the upstream signaling circuit that causes symmetry breaking and guarantees the formation of a single axon is not known. Here, we use live FRET imaging in hippocampal neurons and show that the activity of the small GTPase HRas, an upstream regulator of PI3K, markedly increases in the nascent axonal growth cone upon symmetry breaking. This local increase in HRas activity results from a positive feedback loop between HRas and PI3K, locally reinforced by vesicular transport of HRas to the axonal growth cone. Recruitment of HRas to the axonal growth cone is paralleled by a decrease in HRas concentration in the remaining neurites, suggesting that competition for a limited pool of HRas guarantees that only one axon forms. Mathematical modeling demonstrates that local positive feedback between HRas and PI3K, coupled to recruitment of a limited pool of HRas, generates robust symmetry breaking and formation of a single axon in the absence of extrinsic spatial cues.

Optimal experimental design for parameter estimation of a cell signaling model.

Differential equation models that describe the dynamic changes of biochemical signaling states are important tools to understand cellular behavior. An essential task in building such representations is to infer the affinities, rate constants, and other parameters of a model from actual measurement data. However, intuitive measurement protocols often fail to generate data that restrict the range of possible parameter values. Here we utilized a numerical method to iteratively design optimal live-cell fluorescence microscopy experiments in order to reveal pharmacological and kinetic parameters of a phosphatidylinositol 3,4,5-trisphosphate (PIP(3)) second messenger signaling process that is deregulated in many tumors. The experimental approach included the activation of endogenous phosphoinositide 3-kinase (PI3K) by chemically induced recruitment of a regulatory peptide, reversible inhibition of PI3K using a kinase inhibitor, and monitoring of the PI3K-mediated production of PIP(3) lipids using the pleckstrin homology (PH) domain of Akt. We found that an intuitively planned and established experimental protocol did not yield data from which relevant parameters could be inferred. Starting from a set of poorly defined model parameters derived from the intuitively planned experiment, we calculated concentration-time profiles for both the inducing and the inhibitory compound that would minimize the predicted uncertainty of parameter estimates. Two cycles of optimization and experimentation were sufficient to narrowly confine the model parameters, with the mean variance of estimates dropping more than sixty-fold. Thus, optimal experimental design proved to be a powerful strategy to minimize the number of experiments needed to infer biological parameters from a cell signaling assay.

Dynamic recruitment of the curvature-sensitive protein ArhGAP44 to nanoscale membrane deformations limits exploratory filopodia initiation in neurons.

In the vertebrate central nervous system, exploratory filopodia transiently form on dendritic branches to sample the neuronal environment and initiate new trans-neuronal contacts. While much is known about the molecules that control filopodia extension and subsequent maturation into functional synapses, the mechanisms that regulate initiation of these dynamic, actin-rich structures have remained elusive. Here, we find that filopodia initiation is suppressed by recruitment of ArhGAP44 to actin-patches that seed filopodia. Recruitment is mediated by binding of a membrane curvature-sensing ArhGAP44 N-BAR domain to plasma membrane sections that were deformed inward by acto-myosin mediated contractile forces. A GAP domain in ArhGAP44 triggers local Rac-GTP hydrolysis, thus reducing actin polymerization required for filopodia formation. Additionally, ArhGAP44 expression increases during neuronal development, concurrent with a decrease in the rate of filopodia formation. Together, our data reveals a local auto-regulatory mechanism that limits initiation of filopodia via protein recruitment to nanoscale membrane deformations.

Regulators of calcium homeostasis identified by inference of kinetic model parameters from live single cells perturbed by siRNA.

Assigning molecular functions and revealing dynamic connections between large numbers of partially characterized proteins in regulatory networks are challenges in systems biology. We showed that functions of signaling proteins can be discovered with a differential equations model of the underlying signaling process to extract specific molecular parameter values from single-cell, time-course measurements. By analyzing the effects of 250 small interfering RNAs on Ca(2+) signals in single cells over time, we identified parameters that were specifically altered in the Ca(2+) regulatory system. Analysis of the screen confirmed known functions of the Ca(2+) sensors STIM1 (stromal interaction molecule 1) and calmodulin and of Ca(2+) channels and pumps localized in the endoplasmic reticulum (ER) or plasma membrane. Furthermore, we showed that the Alzheimer's disease-linked protein presenilin-2 and the channel protein ORAI2 prevented overload of ER Ca(2+) and that feedback from Ca(2+) to phosphatidylinositol 4-kinase and PLCδ (phospholipase Cδ) may regulate the abundance of the plasma membrane lipid PI(4,5)P2 (phosphatidylinositol 4,5-bisphosphate) to control Ca(2+) extrusion. Thus, functions of signaling proteins and dynamic regulatory connections can be identified by extracting molecular parameter values from single-cell, time-course data.

Design of experiments to investigate dynamic cell signaling models.

This chapter describes approaches to make use of dynamic models of cell signaling systems in order to optimize experiments in cell biology. We are particularly focusing on the question of how small molecule inhibitors or activators can best be used to get the most information out of a limited number of experiments when only a handful of molecular species can be measured. One goal addressed by this chapter is to find time course experiments to discriminate between rivaling molecular mechanisms. The other goal is to find experiments that are useful for inferring rate constants, binding affinities, concentrations, and other model parameters from time course data. Both are treated as optimal control problems in which rapid pharmacological perturbation schemes are identified in silico in order to close an experimental cycle from modeling back to the laboratory bench.