Design of artificial genetic regulatory networks with multiple delayed adaptive responses

Genetic regulatory networks with adaptive responses are widely studied in biology. Usually, models consisting only of a few nodes have been considered. They present one input receptor for activation and one output node where the adaptive response is computed. In this work, we design genetic regulatory networks with many receptors and many output nodes able to produce delayed adaptive responses. This design is performed by using an evolutionary algorithm of mutations and selections that minimizes an error function defined by the adaptive response in signal shapes. We present several examples of network constructions with a predefined required set of adaptive delayed responses. We show that an output node can have different kinds of responses as a function of the activated receptor. Additionally, complex network structures are presented since processing nodes can be involved in several input-output pathways

Cooperative reliable response from sloppy gene-expression dynamics

Gene expression dynamics satisfying given input-output relationships were investigated by evolving the networks for an optimal response. We found three types of networks and corresponding dynamics, depending on the sensitivity of gene expression dynamics: direct response with straight paths, amplified response by a feed-forward network, and cooperative response with a complex network. When the sensitivity of each gene's response is low and expression dynamics is sloppy, the last type is selected, in which many genes respond collectively to inputs, with local-excitation and global-inhibition structures. The result provides an insight into how a reliable response is achieved with unreliable units, and on why complex networks with many genes are adopted in cells

The Dynamic Effect of Uncertainty on Corporate Investment through Internal and External Financing

Using firm-level data on the Japanese manufacturing industry, this study identifies the causal effect of uncertainty on the dynamic relation between corporate investment and financing conditions. It demonstrates that the cautionary effect is increasingly dominant under high uncertainty irrespective of the type of corporate investment—capital investment and R&D—and that this result remains even in the weak instrument robust inference. Hence, the dominance of the cautionary effect over the financing constraint effect makes actual corporate investment decisions under high uncertainty indifferent to the firm’s financing conditions

The Sensitivity Effect of Uncertainty on Corporate Investment through Internal and External Financing: Evidence on Cautionary Channel from Japanese Manufacturing Firms

Using firm-level data on the Japanese manufacturing industry, this paper studies the causal impact of uncertainty on the dynamic relation between corporate investment and financing conditions. It demonstrates that the cautionary effect that makes actual corporate investment decisions indifferent to the firm's financing conditions increases in higher uncertainty irrespective of the type of corporate investment---capital investment and R\&D---and is more pronounced in firms with less cash holdings. This result remains even in the weak and invalid instrument robust inference

The Dynamic Effect of Uncertainty on Corporate Investment through Internal and External Financing

Using firm-level data on the Japanese manufacturing industry, this study identifies the causal effect of uncertainty on the dynamic relation between corporate investment and financing conditions. It demonstrates that the cautionary effect is increasingly dominant under high uncertainty irrespective of the type of corporate investment—capital investment and R&D—and that this result remains even in the weak instrument robust inference. Hence, the dominance of the cautionary effect over the financing constraint effect makes actual corporate investment decisions under high uncertainty indifferent to the firm’s financing conditions

Circuit architecture explains functional similarity of bacterial heat shock responses

Heat shock response is a stress response to temperature changes and a consecutive increase in amounts of unfolded proteins. To restore homeostasis, cells upregulate chaperones facilitating protein folding by means of transcription factors (TF). We here investigate two heat shock systems: one characteristic to gram negative bacteria, mediated by transcriptional activator sigma32 in E. coli, and another characteristic to gram positive bacteria, mediated by transcriptional repressor HrcA in L. lactis. We construct simple mathematical model of the two systems focusing on the negative feedbacks, where free chaperons suppress sigma32 activation in the former, while they activate HrcA repression in the latter. We demonstrate that both systems, in spite of the difference at the TF regulation level, are capable of showing very similar heat shock dynamics. We find that differences in regulation impose distinct constrains on chaperone-TF binding affinities: the binding constant of free sigma32 to chaperon DnaK, known to be in 100 nM range, set the lower limit of amount of free chaperon that the system can sense the change at the heat shock, while the binding affinity of HrcA to chaperon GroE set the upper limit and have to be rather large extending into the micromolar range.Comment: 17 pages, 5 figure

Dynamics of Coupled Adaptive Elements : Bursting and Intermittent Oscillations Generated by Frustration in Networks

Adaptation to environmental change is a common property of biological systems. Cells initially respond to external changes in the environment, but after some time, they regain their original state. By considering an element consisting of two variables that show such adaptation dynamics, we studied a coupled dynamical system containing such elements to examine the diverse dynamics in the system and classified the behaviors on the basis of the network structure that determined the interaction among elements. For a system with two elements, two types of behaviors, perfect adaptation and simple oscillation, were observed. For a system with three elements, in addition to these two types, novel types of dynamics, namely, rapid burst-type oscillation and a slow cycle, were discovered; depending on the initial conditions, these novel types of dynamics coexisted. These behaviors are a result of the characteristic dynamics of each element, i.e., fast response and slow adaptation processes. The behaviors depend on the network structure (in specific, a combination of positive or negative feedback among elements). Cooperativity among elements due to a positive feedback loop leads to simple oscillation, whereas frustration involving alternating positive and negative interactions among elements leads to the coexistence of rapid bursting oscillation and a slow cycle. These behaviors are classified on the basis of the frustration indices defined by the network structure. The period of the slow cycle is much longer than the original adaptation time scale, while the burst-type oscillation is a continued response that does not involve any adaptation. We briefly discuss the universal applicability of our results to a network of a larger number of elements and their possible relevance to biological systems.Comment: 12 pages, 13 figure