Biomedical subjects

Tetsuya J Kobayashi

Publications and source records attributed to Tetsuya J Kobayashi.

5 recordsLinked to original sources

PubMed2006

An optimal number of molecules for signal amplification and discrimination in a chemical cascade.

Understanding the information processing ability of signal transduction pathways is of great importance because of their crucial roles in triggering various cellular responses. Despite continuing theoretical investigation, some important aspects of signal transduction such as a transient response and its connection to stochasticity originating from a small number of molecules have not yet been well understood. It is, however, through these aspects that unexpected and nontrivial properties of the information processing emerge. In this article, we analyze the transient behavior of a simple signaling cascade by taking into account the stochasticity originating from the small number of molecules. We identify several properties of the signaling cascade that emerge as a result of the interplay between the stochasticity and transient dynamics of the cascade. We specifically demonstrate that each step of the cascade has an optimal number of signaling molecules at which the average signal amplitude becomes maximal. We further investigate the connection between a finite number of molecules and the ability of the cascade to discriminate between true and error signals, which cannot be inferred from deterministic descriptions. The implications of our results are discussed from both biological and mathematical viewpoints.

Computer Simulation↗

PubMed2006

Feedback repression is required for mammalian circadian clock function.

Direct evidence for the requirement of transcriptional feedback repression in circadian clock function has been elusive. Here, we developed a molecular genetic screen in mammalian cells to identify mutants of the circadian transcriptional activators CLOCK and BMAL1, which were uncoupled from CRYPTOCHROME (CRY)-mediated transcriptional repression. Notably, mutations in the PER-ARNT-SIM domain of CLOCK and the C terminus of BMAL1 resulted in synergistic insensitivity through reduced physical interactions with CRY. Coexpression of these mutant proteins in cultured fibroblasts caused arrhythmic phenotypes in population and single-cell assays. These data demonstrate that CRY-mediated repression of the CLOCK/BMAL1 complex activity is required for maintenance of circadian rhythmicity and provide formal proof that transcriptional feedback is required for mammalian clock function.

3T3 Cells↗

PubMed2005

Evaluation of the performance of mechanisms for noise attenuation in a single-gene expression.

Experiments of synthetic gene regulatory modules and theoretical studies have clarified the stochastic nature of gene expression. The establishment of methods to control the fluctuation in gene expression is an indispensable step to the synthesis of robust and reliable genetic modules. In this study, we evaluate the performances of several major mechanisms to attenuate the fluctuation in a single-gene expression; noise attenuation through the control of the ratio of the transcription rate to the translation one, the interaction between synthesized proteins and background molecules, and an autoregulatory negative feedback. We analytically derive the dependence of the noise intensity on the parameter values related to elementary reaction processes, optimal conditions to attenuate the noise, and the limitation of the attenuation for those mechanisms. Our results can be an important basis for selecting the most efficient combination of the components in the design and synthesis of robust and reliable genetic modules. Furthermore, the knowledge on the performances that we obtain can also play a role in understanding the design principle of the intracellular gene regulatory networks.

Computational Biology↗

PubMed2004

Multivariate analysis of noise in genetic regulatory networks.

Stochasticity is an intrinsic property of genetic regulatory networks due to the low copy numbers of the major molecular species, such as, DNA, mRNA, and regulatory proteins. Therefore, investigation of the mechanisms that reduce the stochastic noise is essential in understanding the reproducible behaviors of real organisms and is also a key to design synthetic genetic regulatory networks that can reliably work. We use an analytical and systematic method, the linear noise approximation of the chemical master equation along with the decoupling of a stoichiometric matrix. In the analysis of fluctuations of multiple molecular species, the covariance is an important measure of noise. However, usually the representation of a covariance matrix in the natural coordinate system, i.e. the copy numbers of the molecular species, is intractably complicated because reactions change copy numbers of more than one molecular species simultaneously. Decoupling of a stoichiometric matrix, which is a transformation of variables, significantly simplifies the representation of a covariance matrix and elucidates the mechanisms behind the observed fluctuations in the copy numbers. We apply our method to three types of fundamental genetic regulatory networks, that is, a single-gene autoregulatory network, a two-gene autoregulatory network, and a mutually repressive network. We have found that there are multiple noise components differently originating. Each noise component produces fluctuation in the characteristic direction. The resulting fluctuations in the copy numbers of the molecular species are the sum of these fluctuations. In the examples, the limitation of the negative feedback in noise reduction and the trade-off of fluctuations in multiple molecular species are clearly explained. The analytical representations show the full parameter dependence. Additionally, the validity of our method is tested by stochastic simulations.

Animals↗

PubMed2004

Dynamics of gene regulatory networks with cell division cycle.

This paper focuses on modeling and analyzing the nonlinear dynamics of gene regulatory networks with the consideration of a cell division cycle with duplication process of DNA, in particular for switches and oscillators of synthetic networks. We derive two models that may correspond to the eukaryotic and prokaryotic cells, respectively. A biologically plausible three-gene model ( lac, tetR, and cI ) and a repressilator as switch and oscillator examples are used to illustrate our theoretical results. We show that the cell cycle may play a significant role in gene regulation due to the nonlinear dynamics of a gene regulatory network although gene expressions are usually tightly controlled by transcriptional factors.

Animals↗