論文

In vivo environments are highly crowded and inhomogeneous, which may affect reaction processes in cells. In this study we examined the effects of intracellular crowding and an inhomogeneity on the behavior of in vivo reactions by calculating the spectral dimension (d(s)), which can be translated into the reaction rate function. We compared estimates of anomaly parameters obtained from fluorescence correlation spectroscopy (FCS) data with fractal dimensions derived from transmission electron microscopy (TEM) image analysis. FCS analysis indicated that the anomalous property was linked to physiological structure. Subsequent TEM analysis provided an in vivo illustration; soluble molecules likely percolate between intracellular clusters, which are constructed in a self-organizing manner. We estimated a cytoplasmic spectral dimension d(s) to be 1.39 +/- 0.084. This result suggests that in vivo reactions initially run faster than the same reactions in a homogeneous space; this conclusion is consistent with the anomalous character indicated by FCS analysis. We further showed that these results were compatible with our Monte-Carlo simulation in which the anomalous behavior of mobile molecules correlates with the intracellular environment, leading to description as a percolation cluster, as demonstrated using TEM analysis. We confirmed by the simulation that the above-mentioned in vivo like properties are different from those of homogeneously concentrated environments. Additionally, simulation results indicated that crowding level of an environment might affect diffusion rate of reactant. Such knowledge of the spatial information enables us to construct realistic models for in vivo diffusion and reaction systems.

生命現象の理解には個別のコンポーネントについての理解に加え，それらの統合されたふるまいを知る必要がある．このような様々な分子のダイナミクスの背景にあるメカニズムを理解する上で強力なツールとなるのが数理モデルである．システムバイオロジーでは，数理モデルを用いて生命現象を司るメカニズムを理解する手法を頻用する．歴史的には解析的に解くことが可能なモデルが用いられたが，コンピュータの発達により，常微分方程式モデル，偏微分方程式モデル，確率モデル，これらのハイブリッドモデルなど多岐に渡る形式で記述されたモデルを数値計算によって解くようになった．こうした背景から，作成したモデルの正しい挙動を数値的に得るための，正確な数値計算技術が不可欠の要素となっている．本稿では，各モデル化手法の特徴を概説した後，システムバイオロジー研究において広く利用されている代表的なアプリケーション（シミュレータ）について，ソフトウェアの全体像から実装されているアルゴリズムまで，原典を挙げて解説する．数値計算手法の実装内容を正確に知ることは，ユーザにとってはモデルが備えるべき内容を理解し，結果を正しく解釈するために有用となる．また開発者にとっては，不必要な重複を避け，新しいブレークスルーを実現するための技術が何であるか，自らの創造性の発端を得るためにより重要な知識となるだろう．

© 2018, The Author(s). The larvae of the African midge, Polypedilum vanderplanki, can enter an ametabolic state called anhydrobiosis to overcome fatal desiccation stress. The Pv11 cell line, derived from P. vanderplanki embryo, shows desiccation tolerance when treated with trehalose before desiccation and resumes proliferation after rehydration. However, the molecular mechanisms of this desiccation tolerance remain unknown. Here, we performed high-throughput CAGE-seq of mRNA and a differentially expressed gene analysis in trehalose-treated, desiccated, and rehydrated Pv11 cells, followed by gene ontology analysis of the identified differentially expressed genes. We detected differentially expressed genes after trehalose treatment involved in various stress responses, detoxification of harmful chemicals, and regulation of oxidoreduction that were upregulated. In the desiccation phase, L-isoaspartyl methyltransferase and heat shock proteins were upregulated and ribosomal proteins were downregulated. Analysis of differentially expressed genes during rehydration supported the notion that homologous recombination, nucleotide excision repair, and non-homologous recombination were involved in the recovery process. This study provides initial insights into the molecular mechanisms underlying the extreme desiccation tolerance of Pv11 cells.

哺乳類着床前胚の発生過程に関する情報を経時的な顕微鏡観察画像から得ることは,近年基礎生物学のみならず生殖補助医療などでも重要な課題となっている.本研究では,細胞の移動・増殖などで形成される細胞系譜の情報をバイオイメージングデータから画像解析を用いて抽出する研究について概説し,整数計画法を用いたマウス着床前胚の発生細胞系譜の追跡についての我々の結果を報告する.

© 2020 by the authors. Mathematical model simulation is a useful method for understanding the complex behavior of a living system. The construction of mathematical models using comprehensive information is one of the techniques of model construction. Such a comprehensive knowledge-based network tends to become a large-scale network. As a result, the variation of analyses is limited to a particular kind of analysis because of the size and complexity of the model. To analyze a large-scale regulatory network of neural differentiation, we propose a contractive method that preserves the dynamic behavior of a large network. The method consists of the following two steps: comprehensive network building and network reduction. The reduction phase can extract network loop structures from a large-scale regulatory network, and the subnetworks were combined to preserve the dynamics of the original large-scale network. We confirmed that the extracted loop combination reproduced the known dynamics of HES1 and ASCL1 before and after differentiation, including oscillation and equilibrium of their concentrations. The model also reproduced the effects of the overexpression and knockdown of the Id2 gene. Our model suggests that the characteristic change in HES1 and ASCL1 expression in the large-scale regulatory network is controlled by a combination of four feedback loops, including a large loop, which has not been focused on. The model extracted by our method has the potential to reveal the critical mechanisms of neural differentiation. The method is applicable to other biological events.

In systems biology, biological phenomena are often modeled by Ordinary Differential Equations (ODEs) and distributed in the de facto standard file format SBML. The primary analyses performed with such models are dynamic simulation, steady-state analysis, and parameter estimation. These methodologies are mathematically formalized, and libraries for such analyses have been published. Several tools exist to create, simulate, or visualize models encoded in SBML. However, setting up and establishing analysis environments is a crucial hurdle for non-modelers. Therefore, easy access to perform fundamental analyses of ODE models is a significant challenge. We developed SBMLWebApp, a web-based service to execute SBML-based simulation, steady-state analysis, and parameter estimation directly in the browser without the need for any setup or prior knowledge to address this issue. SBMLWebApp visualizes the result and numerical table of each analysis and provides a download of the results. SBMLWebApp allows users to select and analyze SBML models directly from the BioModels Database. Taken together, SBMLWebApp provides barrier-free access to an SBML analysis environment for simulation, steady-state analysis, and parameter estimation for SBML models. SBMLWebApp is implemented in Java™ based on an Apache Tomcat® web server using COPASI, the Systems Biology Simulation Core Library (SBSCL), and LibSBMLSim as simulation engines. SBMLWebApp is licensed under MIT with source code freely available. At the end of this article, the Data Availability Statement gives the internet links to the two websites to find the source code and run the program online.

Active and dynamic migration and deformation of cells are universal research targets in cell biology. The leader cells that develop at the wound edge are required to actively reorganize their structure for migration and deformation. Such active reorganization of cellular morphology possibly affects the temperature inside the cells via biochemical reactions. On the other hand, it is also possible that changes of intracellular temperature may first trigger and induce active migration and cellular deformation. Recent development of temperature sensors for cells enables the display of temperature difference between two adjacent cell populations such as the leader and follower cells around a wound. We used two different temperature measurement methods to check the temperature of leader and follower cells in a wound healing assay system and found that leader cells were 10° ∼ 101°C warmer than follower cells. We also confirmed that, when the cells were artificially warmed with an infrared laser, they started moving, and when the laser was stopped, the cells also stopped moving. These results suggest that the warmth of the leader cells is not simply a result of their active movement, but also can play the role of a trigger for cell migration and deformation. Our results shed light on the possibility that various observed cases of intracellular temperature increase may trigger associated biological phenomena.

Inside cells, various biological systems work cooperatively for homeostasis and self-replication. These systems do not work independently as they compete for shared elements like ATP and NADH. However, it has been believed that such competition is not a problem in codependent biological systems such as the energy-supplying glycolysis and the energy-consuming translation system. In this study, we biochemically reconstituted the coupling system of glycolysis and translation using purified elements and found that the competition for ATP between glycolysis and protein synthesis interferes with their coupling. Both experiments and simulations revealed that this interference is derived from a metabolic tug-of-war between glycolysis and translation based on their reaction rates, which changes the threshold of the initial substrate concentration for the success coupling. By the metabolic tug-of-war, translation energized by strong glycolysis is facilitated by an exogenous ATPase, which normally inhibits translation. These findings provide chemical insights into the mechanism of competition among biological systems in living cells and provide a framework for the construction of synthetic metabolism in vitro.

近年、深層学習アーキテクチャを自動で設計するNeural Architecture Search (NAS)が注目されている。NASではアーキテクチャの部分構造の集合である探索空間から最適なアーキテクチャを決定する。しかしながら、現在提案されているNASの探索空間は計算量の膨大さゆえ限定されているため、高性能なアーキテクチャを見逃す可能性がある。そこで本研究は、タスク特異的な部分構造を有したアーキテクチャは高性能であると考え、NASの効率的な探索空間設計に資するタスク特異的な部分構造を同定する方法を開発した。 本手法はGraph Convolutional Networkを用いて既存のアーキテクチャのグラフ構造をタスクごとに分類する学習を行い、その分類に寄与した特徴を解析することで部分構造ごとにタスクへの特異度を出力する。実際に本手法により取得した部分構造ごとのタスクへの特異度と精度に有意な相関が確認できたことから、本手法により精度に貢献するタスク特異的な部分構造を同定可能であることが示された。本手法は、計算量を削減した上で高性能なアーキテクチャを決定可能なNASの開発に貢献することが期待される。

The centrosome is a major microtubule organizing center in animal cells. The position of the centrosomes inside the cell is important for cell functions such as cell cycle, and thus should be tightly regulated. Theoretical models based on the forces generated along the microtubules have been proposed to account for the dynamic movements of the centrosomes during the cell cycle. These models, however, often adopted inconsistent assumptions to explain distinct but successive movements, thus preventing a unified model for centrosome positioning. For the centration of the centrosomes, weak attachment of the astral microtubules to the cell cortex was assumed. In contrast, for the separation of the centrosomes during spindle elongation, strong attachment was assumed. Here, we mathematically analyzed these processes at steady state and found that the different assumptions are proper for each process. We experimentally validated our conclusion using nematode and sea urchin embryos by manipulating their shapes. Our results suggest the existence of a molecular mechanism that converts the cortical attachment from weak to strong during the transition from centrosome centration to spindle elongation.

Hyperthermia can be induced to exploit the thermal intolerance of cancer cells, which is worse than that of normal cells, as a potential noninvasive cancer treatment. To develop an effective hyperthermia treatment, thermal cytotoxicity of cells should be comprehensively investigated. However, to conduct such investigations, the culture temperature must be accurately regulated. We previously reported a culture system in which the culture temperature could be accurately regulated by employing metallic culture vessels. However, appropriate temperature conditions for hyperthermia depend on the cell species. Consequently, several experiments need to be conducted, which is a bottleneck of inducing hyperthermia. Hence, we developed a cell culture system with temperature gradation on a metallic culture surface. Michigan Cancer Foundation-7 cells and normal human dermal fibroblasts were used as cancer and normal cell models, respectively. Normal cells showed stronger thermal tolerance; this was because the novel system immediately exhibited a temperature gradation. Thus, the developed culture system can be used to investigate the optimum thermal conditions for effective hyperthermia treatment. Furthermore, as the reactions of cultured cells can be effectively assessed with the present results, further research involving the thermal stimulation of cells is possible.

Multistage Interconnection Networks (MIN) with multiple outlets are networks which can support higher bandwidth than those of nonblocking networks by passing multiple packets to the same destination. Fault recovery mechanisms are proposed for two of such networks (TBSF/PBSF) with the best use of their inherent fault tolerant capability. With these mechanisms, on-the-fly fault recovery is possible for multiple faults on switching elements. For the link fault, the networks are reconfigured after fault diagnosis, and the network is available with some performance degradation. The bandwidth degradation under multiple faults on link/element is analyzed with both theoretical models and simulation. Through the analysis, F-PBSF shows high fault tolerance under high traffic load and low reliability by using 3 or more banyan networks.