Shinsuke Uda

Robustness and Compensation of Information Transmission of Signaling Pathways

Simple Signals? Cells process information about themselves and their surroundings through biochemical signaling pathways. Uda et al. (p. 5588) used a recently developed cytometric method to quantitate signaling through biochemical pathways in individual rat pheochromocytoma cells responding to growth factors. The signaling pathways studied provided about 1 bit of information, or only enough for a binary (on or off) decision. In spite of the simplicity, the results showed interactions between pathways with shared components. In some cases, information carried between inputs and intermediate outputs was less than that between the input and more “downstream” outputs, indicating that information was carried through multiple paths. Similarly, in the presence of pharmacological inhibitors of one pathway, others were able to compensate to allow robust transfer of information. Thus, in spite of noise and variation in signal intensities in individual cells, robust transfer of information from the growth factors was achieved. Information theory analysis of cell signaling reveals mechanisms for reliable cellular responses despite signal variability. Robust transmission of information despite the presence of variation is a fundamental problem in cellular functions. However, the capability and characteristics of information transmission in signaling pathways remain poorly understood. We describe robustness and compensation of information transmission of signaling pathways at the cell population level. We calculated the mutual information transmitted through signaling pathways for the growth factor–mediated gene expression. Growth factors appeared to carry only information sufficient for a binary decision. Information transmission was generally more robust than average signal intensity despite pharmacological perturbations, and compensation of information transmission occurred. Information transmission to the biological output of neurite extension appeared robust. Cells may use information entropy as information so that messages can be robustly transmitted despite variation in molecular activities among individual cells.

Analysis of CDMA systems that are characterized by eigenvalue spectrum

An approach to analyze the performance of the code division multiple access (CDMA) scheme, which is a core technology used in modern wireless communication systems, is provided. The approach characterizes the objective system by the eigenvalue spectrum of a cross-correlation matrix composed of signature sequences used in CDMA communication, which enable us to handle a wider class of CDMA systems beyond the basic model reported by Tanaka in Europhys. Lett., 54 (2001) 540. The utility of the scheme is shown by analyzing a system in which the generation of signature sequences is designed for enhancing the orthogonality.

Decoupling of Receptor and Downstream Signals in the Akt Pathway by Its Low-Pass Filter Characteristics

The Akt pathway can serve as a signal decoupler, converting a weak receptor signal into a strong effector signal. Converting Weak into Strong Signaling pathways have complex kinetics, amplifying a signal, delaying a signal, or filtering out a signal. Fujita et al. performed kinetic analysis of the phosphorylation of three components in the epidermal growth factor receptor (EGFR) pathway—EGFR, the downstream kinase Akt, and the Akt effector ribosomal protein S6—and found that the strongest phosphorylation of the downstream effector occurred with weak, but sustained, receptor activation. Mathematical analysis indicated that Akt served as a low-pass filter to convert weak, sustained receptor signals into strong effector signals and to limit the transmission of strong, transient receptor signals. Exposure of cells to a clinically used inhibitor of the EGFR triggered a paradoxically strong phosphorylation of S6, suggesting that inhibitor data must be analyzed carefully in light of this low-pass filter characteristic. In cellular signal transduction, the information in an external stimulus is encoded in temporal patterns in the activities of signaling molecules; for example, pulses of a stimulus may produce an increasing response or may produce pulsatile responses in the signaling molecules. Here, we show how the Akt pathway, which is involved in cell growth, specifically transmits temporal information contained in upstream signals to downstream effectors. We modeled the epidermal growth factor (EGF)–dependent Akt pathway in PC12 cells on the basis of experimental results. We obtained counterintuitive results indicating that the sizes of the peak amplitudes of receptor and downstream effector phosphorylation were decoupled; weak, sustained EGF receptor (EGFR) phosphorylation, rather than strong, transient phosphorylation, strongly induced phosphorylation of the ribosomal protein S6, a molecule downstream of Akt. Using frequency response analysis, we found that a three-component Akt pathway exhibited the property of a low-pass filter and that this property could explain decoupling of the peak amplitudes of receptor phosphorylation and that of downstream effectors. Furthermore, we found that lapatinib, an EGFR inhibitor used as an anticancer drug, converted strong, transient Akt phosphorylation into weak, sustained Akt phosphorylation, and, because of the low-pass filter characteristics of the Akt pathway, this led to stronger S6 phosphorylation than occurred in the absence of the inhibitor. Thus, an EGFR inhibitor can potentially act as a downstream activator of some effectors.

Timing-Dependent Actions of NGF Required for Cell Differentiation

Background Continuous NGF stimulation induces PC12 cell differentiation. However, why continuous NGF stimulation is required for differentiation is unclear. In this study, we investigated the underlying mechanisms of the timing-dependent requirement of NGF action for cell differentiation. Methodology/Principal Findings To address the timing-dependency of the NGF action, we performed a discontinuous stimulation assay consisting of a first transient stimulation followed by an interval and then a second sustained stimulation and quantified the neurite extension level. Consequently, we observed a timing-dependent action of NGF on cell differentiation, and discontinuous NGF stimulation similarly induced differentiation. The first stimulation did not induce neurite extension, whereas the second stimulation induced fast neurite extension; therefore, the first stimulation is likely required as a prerequisite condition. These observations indicate that the action of NGF can be divided into two processes: an initial stimulation-driven latent process and a second stimulation-driven extension process. The latent process appears to require the activities of ERK and transcription, but not PI3K, whereas the extension-process requires the activities of ERK and PI3K, but not transcription. We also found that during the first stimulation, the activity of NGF can be replaced by PACAP, but not by insulin, EGF, bFGF or forskolin; during the second stimulation, however, the activity of NGF cannot be replaced by any of these stimulants. These findings allowed us to identify potential genes specifically involved in the latent process, rather than in other processes, using a microarray. Conclusions/Significance These results demonstrate that NGF induces the differentiation of PC12 cells via mechanically distinct processes: an ERK-driven and transcription-dependent latent process, and an ERK- and PI3K-driven and transcription-independent extension process.

Reconstruction of Insulin Signal Flow from Phosphoproteome and Metabolome Data

Cellular homeostasis is regulated by signals through multiple molecular networks that include protein phosphorylation and metabolites. However, where and when the signal flows through a network and regulates homeostasis has not been explored. We have developed a reconstruction method for the signal flow based on time-course phosphoproteome and metabolome data, using multiple databases, and have applied it to acute action of insulin, an important hormone for metabolic homeostasis. An insulin signal flows through a network, through signaling pathways that involve 13 protein kinases, 26 phosphorylated metabolic enzymes, and 35 allosteric effectors, resulting in quantitative changes in 44 metabolites. Analysis of the network reveals that insulin induces phosphorylation and activation of liver-type phosphofructokinase 1, thereby controlling a key reaction in glycolysis. We thus provide a versatile method of reconstruction of signal flow through the network using phosphoproteome and metabolome data.

A quantitative image cytometry technique for time series or population analyses of signaling networks.

Background Modeling of cellular functions on the basis of experimental observation is increasingly common in the field of cellular signaling. However, such modeling requires a large amount of quantitative data of signaling events with high spatio-temporal resolution. A novel technique which allows us to obtain such data is needed for systems biology of cellular signaling. Methodology/Principal Findings We developed a fully automatable assay technique, termed quantitative image cytometry (QIC), which integrates a quantitative immunostaining technique and a high precision image-processing algorithm for cell identification. With the aid of an automated sample preparation system, this device can quantify protein expression, phosphorylation and localization with subcellular resolution at one-minute intervals. The signaling activities quantified by the assay system showed good correlation with, as well as comparable reproducibility to, western blot analysis. Taking advantage of the high spatio-temporal resolution, we investigated the signaling dynamics of the ERK pathway in PC12 cells. Conclusions/Significance The QIC technique appears as a highly quantitative and versatile technique, which can be a convenient replacement for the most conventional techniques including western blot, flow cytometry and live cell imaging. Thus, the QIC technique can be a powerful tool for investigating the systems biology of cellular signaling.

Latent process genes for cell differentiation are common decoders of neurite extension length

A latent process involving signal transduction and gene expression is needed as a preparation step for cellular function. We previously found that nerve growth factor (NGF)-induced cell differentiation has a latent process, which is dependent on ERK activity and gene expression and required for subsequent neurite extension. A latent process can be considered as a preparation step that decodes extracellular stimulus information into cellular functions; however, molecular mechanisms of this process remain unknown. We identified Metrnl, Dclk1 and Serpinb1a as genes that are induced during the latent process (LP) with distinct temporal expression profiles and are required for subsequent neurite extension in PC12 cells. The LP genes showed distinct dependency on the duration of ERK activity, and they were also induced during the latent process of PACAP- and forskolin-induced cell differentiation. Regardless of neurotrophic factors, expression levels of the LP genes during the latent process (0–12 hours), but not phosphorylation levels of ERK, always correlated with subsequent neurite extension length (12–24 hours). Overexpression of all LP genes together, but not of each gene separately, enhanced NGF-induced neurite extension. The LP gene products showed distinct spatial localization. Thus, the LP genes appear to be the common decoders for neurite extension length regardless of neurotrophic factors, and they might function in distinct temporal and spatial manners during the latent process. Our findings provide molecular insight into the physiological meaning of the latent process as the preparation step for decoding information for future phenotypic change.

Temporal Decoding of MAP Kinase and CREB Phosphorylation by Selective Immediate Early Gene Expression

A wide range of growth factors encode information into specific temporal patterns of MAP kinase (MAPK) and CREB phosphorylation, which are further decoded by expression of immediate early gene products (IEGs) to exert biological functions. However, the IEG decoding system remain unknown. We built a data-driven based on time courses of MAPK and CREB phosphorylation and IEG expression in response to various growth factors to identify how signal is processed. We found that IEG expression uses common decoding systems regardless of growth factors and expression of each IEG differs in upstream dependency, switch-like response, and linear temporal filters. Pulsatile ERK phosphorylation was selectively decoded by expression of EGR1 rather than c-FOS. Conjunctive NGF and PACAP stimulation was selectively decoded by synergistic JUNB expression through switch-like response to c-FOS. Thus, specific temporal patterns and combinations of MAPKs and CREB phosphorylation can be decoded by selective IEG expression via distinct temporal filters and switch-like responses. The data-driven modeling is versatile for analysis of signal processing and does not require detailed prior knowledge of pathways.

Sensitivity control through attenuation of signal transfer efficiency by negative regulation of cellular signalling

Sensitivity is one of the hallmarks of biological and pharmacological responses. However, the principle of controlling sensitivity remains unclear. Here we theoretically analyse a simple biochemical reaction and find that the signal transfer efficiency of the transient peak amplitude attenuates depending on the strength of negative regulation. We experimentally find that many signalling pathways in various cell lines, including the Akt and ERK pathways, can be approximated by simple biochemical reactions and that the same property of the attenuation of signal transfer efficiency was observed for such pathways. Because of this property, a downstream molecule should show higher sensitivity to an activator and lower sensitivity to an inhibitor than an upstream molecule. Indeed, we experimentally verify that S6, which lies downstream of Akt, shows lower sensitivity to an epidermal growth factor receptor inhibitor than Akt. Thus, cells can control downstream sensitivity through the attenuation of signal transfer efficiency by changing the expression level of negative regulators.

Analysis of cellular signal transduction from an information theoretic approach

Signal transduction processes the information of various cellular functions, including cell proliferation, differentiation, and death. The information for controlling cell fate is transmitted by concentrations of cellular signaling molecules. However, how much information is transmitted in signaling pathways has thus far not been investigated. Shannons information theory paves the way to quantitatively analyze information transmission in signaling pathways. The theory has recently been applied to signal transduction, and mutual information of signal transduction has been determined to be a measure of information transmission. We review this work and provide an overview of how signal transduction transmits informational input and exerts biological output.