Yasunori Komori

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.

Fluorescence microscopy for simultaneous observation of 3D orientation and movement and its application to quantum rod-tagged myosin V

Single molecule fluorescence polarization techniques have been used for three-dimensional (3D) orientation measurements to observe the dynamic properties of single molecules. However, only few techniques can simultaneously measure 3D orientation and position. Furthermore, these techniques often require complex equipment and cumbersome analysis. We have developed a microscopy system and synthesized highly fluorescent, rod-like shaped quantum dots (Q rods), which have linear polarizations, to simultaneously measure the position and 3D orientation of a single fluorescent probe. The optics splits the fluorescence from the probe into four different spots depending on the polarization angle and projects them onto a CCD camera. These spots are used to determine the 2D position and 3D orientation. Q rod orientations could be determined with better than 10° accuracy at 33 ms time resolution. We applied our microscopy and Q rods to simultaneously measure myosin V movement along an actin filament and rotation around its own axis, finding that myosin V rotates 90° for each step. From this result, we suggest that in the two-headed bound state, myosin V necks are perpendicular to one another, while in the one-headed bound state the detached trailing myosin V head is biased forward in part by rotating its lever arm about its own axis. This microscopy system should be applicable to a wide range of dynamic biological processes that depend on single molecule orientation dynamics.

The selective control of glycolysis, gluconeogenesis and glycogenesis by temporal insulin patterns

Insulin governs systemic glucose metabolism, including glycolysis, gluconeogenesis and glycogenesis, through temporal change and absolute concentration. However, how insulin‐signalling pathway selectively regulates glycolysis, gluconeogenesis and glycogenesis remains to be elucidated. To address this issue, we experimentally measured metabolites in glucose metabolism in response to insulin. Step stimulation of insulin induced transient response of glycolysis and glycogenesis, and sustained response of gluconeogenesis and extracellular glucose concentration (GLCex). Based on the experimental results, we constructed a simple computational model that characterises response of insulin‐signalling‐dependent glucose metabolism. The model revealed that the network motifs of glycolysis and glycogenesis pathways constitute a feedforward (FF) with substrate depletion and incoherent feedforward loop (iFFL), respectively, enabling glycolysis and glycogenesis responsive to temporal changes of insulin rather than its absolute concentration. In contrast, the network motifs of gluconeogenesis pathway constituted a FF inhibition, enabling gluconeogenesis responsive to absolute concentration of insulin regardless of its temporal patterns. GLCex was regulated by gluconeogenesis and glycolysis. These results demonstrate the selective control mechanism of glucose metabolism by temporal patterns of insulin.

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.

Glucose Homeostatic Law: Insulin Clearance Predicts the Progression of Glucose Intolerance in Humans

Homeostatic control of blood glucose is regulated by a complex feedback loop between glucose and insulin, of which failure leads to diabetes mellitus. However, physiological and pathological nature of the feedback loop is not fully understood. We made a mathematical model of the feedback loop between glucose and insulin using time course of blood glucose and insulin during consecutive hyperglycemic and hyperinsulinemic-euglycemic clamps in 113 subjects with variety of glucose tolerance including normal glucose tolerance (NGT), impaired glucose tolerance (IGT) and type 2 diabetes mellitus (T2DM). We analyzed the correlation of the parameters in the model with the progression of glucose intolerance and the conserved relationship between parameters. The model parameters of insulin sensitivity and insulin secretion significantly declined from NGT to IGT, and from IGT to T2DM, respectively, consistent with previous clinical observations. Importantly, insulin clearance, an insulin degradation rate, significantly declined from NGT, IGT to T2DM along the progression of glucose intolerance in the mathematical model. Insulin clearance was positively correlated with a product of insulin sensitivity and secretion assessed by the clamp analysis or determined with the mathematical model. Insulin clearance was correlated negatively with postprandial glucose at 2h after oral glucose tolerance test. We also inferred a square-law between the rate constant of insulin clearance and a product of rate constants of insulin sensitivity and secretion in the model, which is also conserved among NGT, IGT and T2DM subjects. Insulin clearance shows a conserved relationship with the capacity of glucose disposal among the NGT, IGT and T2DM subjects. The decrease of insulin clearance predicts the progression of glucose intolerance.

The Extraction of Simple Relationships in Growth Factor-Specific Multiple-Input and Multiple-Output Systems in Cell-Fate Decisions by Backward Elimination PLS Regression

Cells use common signaling molecules for the selective control of downstream gene expression and cell-fate decisions. The relationship between signaling molecules and downstream gene expression and cellular phenotypes is a multiple-input and multiple-output (MIMO) system and is difficult to understand due to its complexity. For example, it has been reported that, in PC12 cells, different types of growth factors activate MAP kinases (MAPKs) including ERK, JNK, and p38, and CREB, for selective protein expression of immediate early genes (IEGs) such as c-FOS, c-JUN, EGR1, JUNB, and FOSB, leading to cell differentiation, proliferation and cell death; however, how multiple-inputs such as MAPKs and CREB regulate multiple-outputs such as expression of the IEGs and cellular phenotypes remains unclear. To address this issue, we employed a statistical method called partial least squares (PLS) regression, which involves a reduction of the dimensionality of the inputs and outputs into latent variables and a linear regression between these latent variables. We measured 1,200 data points for MAPKs and CREB as the inputs and 1,900 data points for IEGs and cellular phenotypes as the outputs, and we constructed the PLS model from these data. The PLS model highlighted the complexity of the MIMO system and growth factor-specific input-output relationships of cell-fate decisions in PC12 cells. Furthermore, to reduce the complexity, we applied a backward elimination method to the PLS regression, in which 60 input variables were reduced to 5 variables, including the phosphorylation of ERK at 10 min, CREB at 5 min and 60 min, AKT at 5 min and JNK at 30 min. The simple PLS model with only 5 input variables demonstrated a predictive ability comparable to that of the full PLS model. The 5 input variables effectively extracted the growth factor-specific simple relationships within the MIMO system in cell-fate decisions in PC12 cells.

Three Dimensional Orientation Measurements of Single Fluorescent Molecules by Newly Developed Polarized Fluorescence Microscopy

Single molecule fluorescence techniques are increasingly important to observe the dynamic properties of single molecules. One such important dynamic property is the single molecules orientation. In order to observe three dimensional motions of proteins in solution, it is necessary to measure three dimensional orientations of proteins. We developed new microscopy for determining three dimensional orientations based on the principal of polarization analysis proposed by Fourkas. This method requires only that one collect fluorescence counts from a single molecule at three different polarizations followed by a simple mathematical calculation to yield the three dimensional orientations. In this method, the relatively small numbers of photons are sufficient for a reliable orientation measurement and this should decrease the time scale needed to determine the orientation of any given fluorophore. Here, we demonstrate axial rotation of actin filaments sliding over myosin molecules fixed on a glass surface by polarization measurement of individual rhodamine phalloidin fluorophores sparsely bound to filaments. This new microscopy will be available for investigating the wide range of dynamic processes through single molecule orientation dynamics in various biophysical studies.