Ruiqi Wang

Noise-induced cooperative behavior in a multicell system

MOTIVATIONnAll cell components exhibit intracellular noise on account of random births and deaths of individual molecules, and extracellular noise because of environment perturbations. Gene regulation in particular, is an inherently noisy process with transcriptional control, alternative splicing, translation, diffusion and chemical modification reactions, all of which involve stochastic fluctuations. Such stochastic noises may not only affect the dynamics of the entire system but may also be exploited by living organisms to actively facilitate certain functions, such as cooperative behavior and communication.nnnRESULTSnWe have provided a general model and an analytic tool to examine the cooperative behavior of a multicell system with both intracellular and extracellular stochastic fluctuations. A multicell system with a synthetic gene network is adopted to demonstrate the effects of noises and coupling on collective dynamics. These results establish not only a theoretical foundation but also a quantitative basis for understanding essential roles of noises on cooperative dynamics, such as synchronization and communication among cells.

Modeling and Analyzing Biological Oscillations in Molecular Networks

One of the major challenges for postgenomic biology is to understand how genes, proteins, and small molecules dynamically interact to form molecular networks which facilitate sophisticated biological functions. In this paper, we present a survey on recent developments on modelling molecular networks and analyzing synchronization of bio-oscillators in multicellular systems from the viewpoint of systems biology. Attention will be focused on deriving general theoretical results to understand the dynamical behaviors of biological systems based on nonlinear dynamical and control theory. Specifically, we first describe the stochastic and deterministic approaches to model molecular networks and give a brief comparison between them. Then, we explain how to construct a molecular network, in particular, a gene regulatory network with specific functions, e.g., switches and oscillators, in individual cells at the molecular level by using feedback systems, and how to model a general multicellular system with the consideration of external fluctuations and intercellular coupling to study the general cooperative behaviors for a population of bio-oscillators. Finally, as an illustrative example, a synthetic multicellular system is designed to show how synchronization is effectively achieved and how dynamics of individual cells is efficiently controlled. Some recent developments and perspectives of analysis on biological oscillations in future are also discussed.

Neural fate decisions mediated by trans-activation and cis-inhibition in Notch signaling

MOTIVATIONnIn the developing nervous system, the expression of proneural genes, i.e. Hes1, Neurogenin-2 (Ngn2) and Deltalike-1 (Dll1), oscillates in neural progenitors with a period of 2-3 h, but is persistent in post-mitotic neurons. Unlike the synchronization of segmentation clocks, oscillations in neural progenitors are asynchronous between cells. It is known that Notch signaling, in which Notch in a cell can be activated by Dll1 in neighboring cells (trans-activation) and can also be inhibited by Dll1 within the same cell (cis-inhibition), is important for neural fate decisions. There have been extensive studies of trans-activation, but the operating mechanisms and potential implications of cis-inhibition are less clear and need to be further investigated.nnnRESULTSnIn this article, we present a computational model for neural fate decisions based on intertwined dynamics with trans-activation and cis-inhibition involving the Hes1, Notch and Dll1 proteins. In agreement with experimental observations, the model predicts that both trans-activation and cis-inhibition play critical roles in regulating the choice between remaining as a progenitor and embarking on neural differentiation. In particular, trans-activation is essential for generation of oscillations in neural progenitors, and cis-inhibition is important for the asynchrony between adjacent cells, indicating that the asynchronous oscillations in neural progenitors depend on cooperation between trans-activation and cis-inhibition. In contrast, cis-inhibition plays more critical roles in embarking on neural differentiation by inactivating intercellular Notch signaling. The model presented here might be a good candidate for providing the first qualitative mechanism of neural fate decisions mediated by both trans-activation and cis-inhibition.

Synchronizing a multicellular system by external input: an artificial control strategy

MOTIVATIONnAlthough there are significant advances on elucidating the collective behaviors on biological organisms in recent years, the essential mechanisms by which the collective rhythms arise remain to be fully understood, and further how to synchronize multicellular networks by artificial control strategy has not yet been well explored.nnnRESULTSnA control strategy is developed to synchronize gene regulatory networks in a multicellular system when spontaneous synchronization cannot be achieved. We first construct an impulsive control system to model the process of periodically injecting coupling substances with constant or random impulsive control amounts into the common extracellular medium, and further study its effects on the dynamics of individual cells. We derive the threshold of synchronization induced by the periodic substance input. Therefore, we can synchronize the multicellular network to a specific collective behavior by changing the frequency and amplitude of the periodic stimuli. Moreover, a two-stage scheme is proposed to facilitate the synchronization in this paper. We show that the presence of the external input may also initiate different dynamics. The multicellular network of coupled repressilators is used to show the effectiveness of the proposed method. The results not only provide a perspective to understand the interactions between external stimuli and intrinsic physiological rhythms, but also may lead to development of realistic artificial control strategy and medical therapy.nnnAVAILABILITYnnnnCONTACTnaihara@sat.t.u-tokyo.ac.jp.

Bistability and Oscillations in Gene Regulation Mediated by Small Noncoding RNAs

The interplay of small noncoding RNAs (sRNAs), mRNAs, and proteins has been shown to play crucial roles in almost all cellular processes. As key post-transcriptional regulators of gene expression, the mechanisms and roles of sRNAs in various cellular processes still need to be fully understood. When participating in cellular processes, sRNAs mainly mediate mRNA degradation or translational repression. Here, we show how the dynamics of two minimal architectures is drastically affected by these two mechanisms. A comparison is also given to reveal the implication of the fundamental differences. This study may help us to analyze complex networks assembled by simple modules more easily. A better knowledge of the sRNA-mediated motifs is also of interest for bio-engineering and artificial control.

Designing Gene Regulatory Networks With Specified Functions

To design and construct gene regulatory networks with specified functions, such as gene switches or gene oscillators, a precise mathematical description of the networks and their properties are developed from the viewpoint of integrated systems biology. The theoretical results provide insights into the modular structures of gene regulatory networks and their quantitative functions. Specifically, based on priori knowledge of the structure of functional modules, we use feedback system to create gene regulatory networks performing basic tasks. Two typical biological networks: positive and cyclic feedback networks are used to create functions as bistable switches or oscillators. The hybrid feedback networks are adopted to provide a variety of functional designs, which demonstrate the crucial role of interactions between biological modules

Analysis on steady states of photosynthetic carbon metabolic system

In this paper, we propose a reduced molecular network of the photosynthetic carbon metabolism, which includes the nine major metabolites with 48 parameters. The reduced molecular network can represent the key ingredients of photosynthetic carbon metabolism, i.e. the autocatalytic cycle, the utilization of photosynthate, and the effect of photorespiration. Based on the model, we theoretically study steady states or stable equilibria of photosynthetic carbon metabolism, and prove that such a system actually has at most one feasible steady state in the domain of a parameter set defined around nominal values for that parameter set. Specifically, we first equivalently transform the original system into an independent 2-dimensional subsystem which contains just 10 parameters, and then show that steady states of the original system can be determined by the 2-dimensional subsystem uniquely. Finally, we show that when the 10 parameters for the 2-dimensional subsystem all stay in an appropriate domain around the nominal value of each parameter, the reduced model has at most one physiologically feasible steady state no matter how the other 38 parameters in the original model are taken. In addition, we also derive parameter domain to ensure such an asymptotical behavior.

The effect of coupled feedback on noise filtering in signal transduction networks

Many interacting biomolecular components in cells form different positive or negative feedback loops. When biological signals transduce through cascades consisting of various loops they will be affected or even distorted. Especially, how to process various signals buried in various intrinsic and extrinsic noises is an important issue. This paper analyzes how the response time influences noise filtering ability and how to enhance the ability by coupling different feedback loops. A parameter to measure the response time of the signal transduction, i.e., τ0.9, and its relationship between the response time and noise filtering will be discussed. The authors show clearly that the longer the response time is, the better the ability to filter noises will be. Therefore, to enhance the ability to filter noises, the authors can prolong the response time by coupling different positive or negative feedback loops. The results provide a possible approach to enhance the ability to filter noises in larger biomolecular networks.

Designing synthetic biological networks

We aim to design and construct synthetic biological networks, such as gene switch or gene oscillator in this paper from the viewpoint of integrated systems biology. The theoretical results provide insights into the modular structures of gene regulatory networks and their quantitative functions. A hybrid feedback network is adopted to provide a variety of functional designs, which demonstrate the crucial role of interactions between biological modules

A Linear Analysis on Robustness in Biochemical Networks

A linear analysis approach is developed to study the relative importance of components in biochemical networks for robustness in this paper. Moreover, by such an approach, robustness properties can be enhanced by modifying network structure or interactions. Our analysis focuses on a molecular network that produces spontaneous oscillations in Dictyotelium discoideum cells