Publications by authors named "Akira Funahashi"

38 Publications

3D convolutional neural networks-based segmentation to acquire quantitative criteria of the nucleus during mouse embryogenesis.

NPJ Syst Biol Appl 2020 10 20;6(1):32. Epub 2020 Oct 20.

Department of Biosciences and Informatics, Keio University, Kanagawa, 223-8522, Japan.

During embryogenesis, cells repeatedly divide and dynamically change their positions in three-dimensional (3D) space. A robust and accurate algorithm to acquire the 3D positions of the cells would help to reveal the mechanisms of embryogenesis. To acquire quantitative criteria of embryogenesis from time-series 3D microscopic images, image processing algorithms such as segmentation have been applied. Because the cells in embryos are considerably crowded, an algorithm to segment individual cells in detail and accurately is needed. To quantify the nuclear region of every cell from a time-series 3D fluorescence microscopic image of living cells, we developed QCANet, a convolutional neural network-based segmentation algorithm for 3D fluorescence bioimages. We demonstrated that QCANet outperformed 3D Mask R-CNN, which is currently considered as the best algorithm of instance segmentation. We showed that QCANet can be applied not only to developing mouse embryos but also to developing embryos of two other model species. Using QCANet, we were able to extract several quantitative criteria of embryogenesis from 11 early mouse embryos. We showed that the extracted criteria could be used to evaluate the differences between individual embryos. This study contributes to the development of fundamental approaches for assessing embryogenesis on the basis of extracted quantitative criteria.
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http://dx.doi.org/10.1038/s41540-020-00152-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7575569PMC
October 2020

SBML Level 3: an extensible format for the exchange and reuse of biological models.

Mol Syst Biol 2020 08;16(8):e9110

Management & IT Consulting Division, Mizuho Information & Research Institute, Inc., Tokyo, Japan.

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution.
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http://dx.doi.org/10.15252/msb.20199110DOI Listing
August 2020

Identification of a master transcription factor and a regulatory mechanism for desiccation tolerance in the anhydrobiotic cell line Pv11.

PLoS One 2020 19;15(3):e0230218. Epub 2020 Mar 19.

Department of Biosciences and Informatics, Keio University, Yokohama, Kanagawa, Japan.

Water is essential for living organisms. Terrestrial organisms are incessantly exposed to the stress of losing water, desiccation stress. Avoiding the mortality caused by desiccation stress, many organisms acquired molecular mechanisms to tolerate desiccation. Larvae of the African midge, Polypedilum vanderplanki, and its embryonic cell line Pv11 tolerate desiccation stress by entering an ametabolic state, anhydrobiosis, and return to active life after rehydration. The genes related to desiccation tolerance have been comprehensively analyzed, but transcriptional regulatory mechanisms to induce these genes after desiccation or rehydration remain unclear. Here, we comprehensively analyzed the gene regulatory network in Pv11 cells and compared it with that of Drosophila melanogaster, a desiccation sensitive species. We demonstrated that nuclear transcription factor Y subunit gamma-like, which is important for drought stress tolerance in plants, and its transcriptional regulation of downstream positive feedback loops have a pivotal role in regulating various anhydrobiosis-related genes. This study provides an initial insight into the systemic mechanism of desiccation tolerance.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0230218PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7082025PMC
June 2020

XitoSBML: A Modeling Tool for Creating Spatial Systems Biology Markup Language Models From Microscopic Images.

Front Genet 2019 22;10:1027. Epub 2019 Oct 22.

Systems Biology Laboratory, Department of Biosciences and Informatics, Keio University, Yokohama, Japan.

XitoSBML is a software tool designed to create an SBML (Systems Biology Markup Language) Level 3 Version 1 document from microscopic cellular images. It is implemented as an ImageJ plug-in and is designed to create spatial models that reflect the three-dimensional cellular geometry. With XitoSBML, users can perform spatial model simulations based on realistic cellular geometry by using SBML-supported software tools, including simulators such as Virtual Cell and Spatial Simulator. XitoSBML is open-source and is available at https://github.com/spatialsimulator/XitoSBML/. XitoSBML is confirmed to run on most 32/64-bit operating systems: Windows, MacOS, and Linux.
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http://dx.doi.org/10.3389/fgene.2019.01027DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6842926PMC
October 2019

Predicting the future direction of cell movement with convolutional neural networks.

PLoS One 2019 4;14(9):e0221245. Epub 2019 Sep 4.

Department of Biosciences and Informatics, Keio University, Yokohama-shi, Kanagawa, Japan.

Image-based deep learning systems, such as convolutional neural networks (CNNs), have recently been applied to cell classification, producing impressive results; however, application of CNNs has been confined to classification of the current cell state from the image. Here, we focused on cell movement where current and/or past cell shape can influence the future cell movement. We demonstrate that CNNs prospectively predicted the future direction of cell movement with high accuracy from a single image patch of a cell at a certain time. Furthermore, by visualizing the image features that were learned by the CNNs, we could identify morphological features, e.g., the protrusions and trailing edge that have been experimentally reported to determine the direction of cell movement. Our results indicate that CNNs have the potential to predict the future direction of cell movement from current cell shape, and can be used to automatically identify those morphological features that influence future cell movement.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0221245PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6726366PMC
March 2020

Activation of cell migration via morphological changes in focal adhesions depends on shear stress in MYCN-amplified neuroblastoma cells.

J R Soc Interface 2019 03;16(152):20180934

3 Department of Pharmacy, Sanyo-Onoda City University , Yamaguchi , Japan.

Neuroblastoma is the most common solid tumour of childhood, and it metastasizes to distant organs. However, the mechanism of metastasis, which generally depends on the cell motility of the neuroblastoma, remains unclear. In many solid tumours, it has been reported that shear stress promotes metastasis. Here, we investigated the relationship between shear stress and cell motility in the MYCN-amplified human neuroblastoma cell line IMR32, using a microfluidic device. We confirmed that most of the cells migrated downstream, and cell motility increased dramatically when the cells were exposed to a shear stress of 0.4 Pa, equivalent to that expected in vivo. We observed that the morphological features of focal adhesion were changed under a shear stress of 0.4 Pa. We also investigated the relationship between malignancy and the motility of IMR32 cells under shear stress. Decreasing the expression of MYCN in IMR32 cells via siRNA transfection inhibited cell motility by a shear stress of 0.4 Pa. These results suggest that MYCN-amplified neuroblastoma cells under high shear stress migrate to distant organs due to high cell motility, allowing cell migration to lymphatic vessels and venules.
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http://dx.doi.org/10.1098/rsif.2018.0934DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6451396PMC
March 2019

Transcriptome analysis of the anhydrobiotic cell line Pv11 infers the mechanism of desiccation tolerance and recovery.

Sci Rep 2018 12 18;8(1):17941. Epub 2018 Dec 18.

Department of Biosciences and Informatics, Keio University, Yokohama, Kanagawa, 223-8522, Japan.

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.
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http://dx.doi.org/10.1038/s41598-018-36124-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6298976PMC
December 2018

Quantitative analysis of sensitivity to a Wnt3a gradient in determination of the pole-to-pole axis of mitotic cells by using a microfluidic device.

FEBS Open Bio 2018 Dec 9;8(12):1920-1935. Epub 2018 Nov 9.

Department of Biosciences and Informatics Keio University Yokohama Japan.

Proper determination of the cell division axis is essential during development. Wnt3a is a known regulator of the cell division axis; however, the sensitivity of cells to Wnt3a signalling and its role in determining the cell division axis have not been measured to date. To address this gap, we took advantage of the asymmetric distribution of outer dense fibre 2 (ODF2/cenexin) proteins on centrosomes in dividing cells. To precisely quantify the sensitivity of cells to Wnt3a signalling, we developed a microfluidic cell culture device, which can produce a quantitative gradient of signalling molecules. We confirmed that mitotic SH-SY5Y neuroblastoma cells could detect a 2.5 ~ 5 × 10 nm·μm Wnt3a concentration gradient and demonstrated that this gradient is sufficient to affect the determination of the pole-to-pole axis of cell division during the later stages of mitosis.
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http://dx.doi.org/10.1002/2211-5463.12525DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6275273PMC
December 2018

Editorial: Quantitative Biology: Dynamics of Living Systems.

Front Physiol 2016 2;7:196. Epub 2016 Jun 2.

Systems Biology Laboratory, Department of Biosciences and Informatics, Keio University Yokohama, Japan.

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http://dx.doi.org/10.3389/fphys.2016.00196DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4889605PMC
June 2016

Detection of Temperature Difference in Neuronal Cells.

Sci Rep 2016 Mar 1;6:22071. Epub 2016 Mar 1.

Keio University, Department of Biosciences and Informatics, 3-14-1, Hiyoshi, Kohoku-Ward, Yokohama, 223-8522, Japan.

For a better understanding of the mechanisms behind cellular functions, quantification of the heterogeneity in an organism or cells is essential. Recently, the importance of quantifying temperature has been highlighted, as it correlates with biochemical reaction rates. Several methods for detecting intracellular temperature have recently been established. Here we develop a novel method for sensing temperature in living cells based on the imaging technique of fluorescence of quantum dots. We apply the method to quantify the temperature difference in a human derived neuronal cell line, SH-SY5Y. Our results show that temperatures in the cell body and neurites are different and thus suggest that inhomogeneous heat production and dissipation happen in a cell. We estimate that heterogeneous heat dissipation results from the characteristic shape of neuronal cells, which consist of several compartments formed with different surface-volume ratios. Inhomogeneous heat production is attributable to the localization of specific organelles as the heat source.
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http://dx.doi.org/10.1038/srep22071DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4772094PMC
March 2016

Simulation technology and its application in Systems Biology.

Nihon Yakurigaku Zasshi 2016 02;147(2):101-6

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http://dx.doi.org/10.1254/fpj.147.101DOI Listing
February 2016

The principles of whole-cell modeling.

Curr Opin Microbiol 2015 Oct 24;27:18-24. Epub 2015 Jun 24.

Department of Biosciences and Informatics, Keio University, Yokohama 223-8522, Japan.

Whole-cell models which comprehensively predict how phenotypes emerge from genotype promise to enable rational bioengineering and precision medicine. Here, we outline the key principles of whole-cell modeling which have emerged from our work developing bacterial whole-cell models: single-cellularity; functional, genetic, molecular, and temporal completeness; biophysical realism including temporal dynamics and stochastic variation; species-specificity; and model integration and reproducibility. We also outline the whole-cell model construction process, highlighting existing resources. Numerous challenges remain to achieving fully complete models including developing new experimental tools to more completely characterize cells and developing a strong theoretical understanding of hybrid mathematics. Solving these challenges requires collaboration among computational and experimental biologists, biophysicists, biochemists, applied mathematicians, computer scientists, and software engineers.
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http://dx.doi.org/10.1016/j.mib.2015.06.004DOI Listing
October 2015

Acceleration of discrete stochastic biochemical simulation using GPGPU.

Front Physiol 2015 13;6:42. Epub 2015 Feb 13.

Systems Biology Laboratory, Department of Biosciences and Informatics, Keio University Yokohama, Japan.

For systems made up of a small number of molecules, such as a biochemical network in a single cell, a simulation requires a stochastic approach, instead of a deterministic approach. The stochastic simulation algorithm (SSA) simulates the stochastic behavior of a spatially homogeneous system. Since stochastic approaches produce different results each time they are used, multiple runs are required in order to obtain statistical results; this results in a large computational cost. We have implemented a parallel method for using SSA to simulate a stochastic model; the method uses a graphics processing unit (GPU), which enables multiple realizations at the same time, and thus reduces the computational time and cost. During the simulation, for the purpose of analysis, each time course is recorded at each time step. A straightforward implementation of this method on a GPU is about 16 times faster than a sequential simulation on a CPU with hybrid parallelization; each of the multiple simulations is run simultaneously, and the computational tasks within each simulation are parallelized. We also implemented an improvement to the memory access and reduced the memory footprint, in order to optimize the computations on the GPU. We also implemented an asynchronous data transfer scheme to accelerate the time course recording function. To analyze the acceleration of our implementation on various sizes of model, we performed SSA simulations on different model sizes and compared these computation times to those for sequential simulations with a CPU. When used with the improved time course recording function, our method was shown to accelerate the SSA simulation by a factor of up to 130.
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http://dx.doi.org/10.3389/fphys.2015.00042DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4327578PMC
March 2015

High-speed microscopy with an electrically tunable lens to image the dynamics of in vivo molecular complexes.

Rev Sci Instrum 2015 Jan;86(1):013707

Division of Electronics and Informatics, Gunma University, Kiryu, Japan.

We provide an evaluation for an electrically tunable lens (ETL), combined with a microscope system, from the viewpoint of tracking intracellular protein complexes. We measured the correlation between the quantitative axial focus shift and the control current for ETL, and determined the stabilization time for refocusing to evaluate the electrical focusing behaviour of our system. We also confirmed that the change of relative magnification by the lens and associated resolution does not influence the ability to find intracellular targets. By applying the ETL system to observe intracellular structures and protein complexes, we confirmed that this system can obtain 10 nm order z-stacks, within video rate, while maintaining the quality of images and that this system has sufficient optical performance to detect the molecules.
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http://dx.doi.org/10.1063/1.4905330DOI Listing
January 2015

A proteomic study of mitotic phase-specific interactors of EB1 reveals a role for SXIP-mediated protein interactions in anaphase onset.

Biol Open 2015 01 16;4(2):155-69. Epub 2015 Jan 16.

Department of Genetics, University of Cambridge, Cambridge, UK

Microtubules execute diverse mitotic events that are spatially and temporally separated; the underlying regulation is poorly understood. By combining drug treatments, large-scale immunoprecipitation and mass spectrometry, we report the first comprehensive map of mitotic phase-specific protein interactions of the microtubule-end binding protein, EB1. EB1 interacts with some, but not all, of its partners throughout mitosis. We show that the interaction of EB1 with Astrin-SKAP complex, a key regulator of chromosome segregation, is enhanced during prometaphase, compared to anaphase. We find that EB1 and EB3, another EB family member, can interact directly with SKAP, in an SXIP-motif dependent manner. Using an SXIP defective mutant that cannot interact with EB, we uncover two distinct pools of SKAP at spindle microtubules and kinetochores. We demonstrate the importance of SKAP's SXIP-motif in controlling microtubule growth rates and anaphase onset, without grossly disrupting spindle function. Thus, we provide the first comprehensive map of temporal changes in EB1 interactors during mitosis and highlight the importance of EB protein interactions in ensuring normal mitosis.
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http://dx.doi.org/10.1242/bio.201410413DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4365484PMC
January 2015

Modeling and simulation using CellDesigner.

Methods Mol Biol 2014 ;1164:121-45

The Systems Biology Institute, 5-6-9 Shirokanedai, Minato-ku, Tokyo, 108-0071, Japan.

In silico modeling and simulation are effective means to understand how the regulatory systems function in life. In this chapter, we explain how to build a model and run the simulation using CellDesigner, adopting the standards such as SBML and SBGN.
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http://dx.doi.org/10.1007/978-1-4939-0805-9_11DOI Listing
January 2015

Assessing uncertainty in model parameters based on sparse and noisy experimental data.

Front Physiol 2014 4;5:128. Epub 2014 Apr 4.

Systems Biology Laboratory, Department of Bioscience and Informatics, Keio University Yokohama, Japan.

To perform parametric identification of mathematical models of biological events, experimental data are rare to be sufficient to estimate target behaviors produced by complex non-linear systems. We performed parameter fitting to a cell cycle model with experimental data as an in silico experiment. We calibrated model parameters with the generalized least squares method with randomized initial values and checked local and global sensitivity of the model. Sensitivity analyses showed that parameter optimization induced less sensitivity except for those related to the metabolism of the transcription factors c-Myc and E2F, which are required to overcome a restriction point (R-point). We performed bifurcation analyses with the optimized parameters and found the bimodality was lost. This result suggests that accumulation of c-Myc and E2F induced dysfunction of R-point. We performed a second parameter optimization based on the results of sensitivity analyses and incorporating additional derived from recent in vivo data. This optimization returned the bimodal characteristics of the model with a narrower range of hysteresis than the original. This result suggests that the optimized model can more easily go through R-point and come back to the gap phase after once having overcome it. Two parameter space analyses showed metabolism of c-Myc is transformed as it can allow cell bimodal behavior with weak stimuli of growth factors. This result is compatible with the character of the cell line used in our experiments. At the same time, Rb, an inhibitor of E2F, can allow cell bimodal behavior with only a limited range of stimuli when it is activated, but with a wider range of stimuli when it is inactive. These results provide two insights; biologically, the two transcription factors play an essential role in malignant cells to overcome R-point with weaker growth factor stimuli, and theoretically, sparse time-course data can be used to change a model to a biologically expected state.
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http://dx.doi.org/10.3389/fphys.2014.00128DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3983526PMC
April 2014

In vivo oriented modeling with consideration of intracellular crowding.

Annu Int Conf IEEE Eng Med Biol Soc 2013 ;2013:2716-9

In vivo reaction space is constrained by complex structures which are made of entwined cytoskeletons and organelles; this create the difference between in vivo and in vitro in respect of molecular mobility, and it may affect reaction processes. Our motivation is to reveal the background mechanisms of the properties of molecular behaviors in vivo by numerical approach. For this object, we reassembled a pseudo-intracellular environment in 3D lattice space, and executed Monte Carlo simulation. By changing the relative amount of non-reactive obstacles in the simulation space, we tested the effect of the level of crowdedness to the molecular mobility and reaction processes. Our results showed that molecules demonstrated anomalous diffusion correlating to the restriction level of the reaction space. Reaction processes also showed distinct characteristics, that is increase of reaction rate at the beginning of reactions, with the decrease of the reaction rate at later time frame of reactions. Our results suggested that the anomalous behaviors at singe molecule level in vivo could bring an essential difference to the reaction processes and the results.
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http://dx.doi.org/10.1109/EMBC.2013.6610101DOI Listing
September 2015

Automated tracking of mitotic spindle pole positions shows that LGN is required for spindle rotation but not orientation maintenance.

Cell Cycle 2013 Aug 16;12(16):2643-55. Epub 2013 Jul 16.

Department of Genetics, University of Cambridge, Cambridge, UK.

Spindle orientation defines the plane of cell division and, thereby, the spatial position of all daughter cells. Here, we develop a live cell microscopy-based methodology to extract spindle movements in human epithelial cell lines and study how spindles are brought to a pre-defined orientation. We show that spindles undergo two distinct regimes of movements. Spindles are first actively rotated toward the cells' long-axis and then maintained along this pre-defined axis. By quantifying spindle movements in cells depleted of LGN, we show that the first regime of rotational movements requires LGN that recruits cortical dynein. In contrast, the second regime of movements that maintains spindle orientation does not require LGN, but is sensitive to 2ME2 that suppresses microtubule dynamics. Our study sheds first insight into spatially defined spindle movement regimes in human cells, and supports the presence of LGN and dynein independent cortical anchors for astral microtubules.
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http://dx.doi.org/10.4161/cc.25671DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3865054PMC
August 2013

The systems biology simulation core algorithm.

BMC Syst Biol 2013 Jul 5;7:55. Epub 2013 Jul 5.

Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, Tübingen, Germany.

Background: With the increasing availability of high dimensional time course data for metabolites, genes, and fluxes, the mathematical description of dynamical systems has become an essential aspect of research in systems biology. Models are often encoded in formats such as SBML, whose structure is very complex and difficult to evaluate due to many special cases.

Results: This article describes an efficient algorithm to solve SBML models that are interpreted in terms of ordinary differential equations. We begin our consideration with a formal representation of the mathematical form of the models and explain all parts of the algorithm in detail, including several preprocessing steps. We provide a flexible reference implementation as part of the Systems Biology Simulation Core Library, a community-driven project providing a large collection of numerical solvers and a sophisticated interface hierarchy for the definition of custom differential equation systems. To demonstrate the capabilities of the new algorithm, it has been tested with the entire SBML Test Suite and all models of BioModels Database.

Conclusions: The formal description of the mathematics behind the SBML format facilitates the implementation of the algorithm within specifically tailored programs. The reference implementation can be used as a simulation backend for Java™-based programs. Source code, binaries, and documentation can be freely obtained under the terms of the LGPL version 3 from http://simulation-core.sourceforge.net. Feature requests, bug reports, contributions, or any further discussion can be directed to the mailing list simulation-core-development@lists.sourceforge.net.
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http://dx.doi.org/10.1186/1752-0509-7-55DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3707837PMC
July 2013

LibSBMLSim: a reference implementation of fully functional SBML simulator.

Bioinformatics 2013 Jun 5;29(11):1474-6. Epub 2013 Apr 5.

Department of Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Kouhoku-ku, Yokohama, Japan.

Motivation: The Systems Biology Markup Language (SBML) is currently supported by >230 software tools, among which 160 support numerical integration of ordinary differential equation (ODE) models. Although SBML is a widely accepted standard within this field, there is still no language-neutral library that supports all features of SBML for simulating ODE models. Therefore, a demand exists for a simple portable implementation of a numerical integrator that supports SBML to enhance the development of a computational platform for systems biology.

Results: We implemented a library called libSBMLSim, which supports all the features of SBML and confirmed that the library passes all tests in the SBML test suite including those for SBML Events, AlgebraicRules, 'fast' attribute on Reactions and Delay. LibSBMLSim is implemented in the C programming language and does not depend on any third-party library except libSBML, which is a library to handle SBML documents. For the numerical integrator, both explicit and implicit methods are written from scratch to support all the functionality of SBML features in a straightforward implementation. We succeeded in implementing libSBMLSim as a platform-independent library that can run on most common operating systems (Windows, MacOSX and Linux) and also provides several language bindings (Java, C#, Python and Ruby).

Availability: The source code of libSBMLSim is available from http://fun.bio.keio.ac.jp/software/libsbmlsim/. LibSBMLSim is distributed under the terms of LGPL.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btt157DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3661052PMC
June 2013

Mathematical modeling of sustainable synaptogenesis by repetitive stimuli suggests signaling mechanisms in vivo.

PLoS One 2012 20;7(12):e51000. Epub 2012 Dec 20.

Dept. of Bioscience and Informatics, Keio University, Yokohama, Japan.

The mechanisms of long-term synaptic maintenance are a key component to understanding the mechanism of long-term memory. From biological experiments, a hypothesis arose that repetitive stimuli with appropriate intervals are essential to maintain new synapses for periods of longer than a few days. We successfully reproduce the time-course of relative numbers of synapses with our mathematical model in the same conditions as biological experiments, which used Adenosine-3', 5'-cyclic monophosphorothioate, Sp-isomer (Sp-cAMPS) as external stimuli. We also reproduce synaptic maintenance responsiveness to intervals of Sp-cAMPS treatment accompanied by PKA activation. The model suggests a possible mechanism of sustainable synaptogenesis which consists of two steps. First, the signal transduction from an external stimulus triggers the synthesis of a new signaling protein. Second, the new signaling protein is required for the next signal transduction with the same stimuli. As a result, the network component is modified from the first network, and a different signal is transferred which triggers the synthesis of another new signaling molecule. We refer to this hypothetical mechanism as network succession. We build our model on the basis of two hypotheses: (1) a multi-step network succession induces downregulation of SSH and COFILIN gene expression, which triggers the production of stable F-actin; (2) the formation of a complex of stable F-actin with Drebrin at PSD is the critical mechanism to achieve long-term synaptic maintenance. Our simulation shows that a three-step network succession is sufficient to reproduce sustainable synapses for a period longer than 14 days. When we change the network structure to a single step network, the model fails to follow the exact condition of repetitive signals to reproduce a sufficient number of synapses. Another advantage of the three-step network succession is that this system indicates a greater tolerance of parameter changes than the single step network.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0051000PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3530976PMC
June 2013

Physiological Intracellular Crowdedness is Defined by the Perimeter-to-Area Ratio of Sub-Cellular Compartments.

Front Physiol 2012 23;3:293. Epub 2012 Jul 23.

Department of Bioscience and Informatics, School of Fundamental Science and Technology, Keio University Yokohama, Japan.

The intracellular environment is known to be a crowded and inhomogeneous space. Such an in vivo environment differs from a well-diluted, homogeneous environment for biochemical reactions. However, the effects of both crowdedness and the inhomogeneity of environment on the behavior of a mobile particle have not yet been investigated sufficiently. As described in this paper, we constructed artificial reaction spaces with fractal models, which are assumed to be non-reactive solid obstacles in a reaction space with crevices that function as operating ranges for mobile particles threading the space. Because of the homogeneity of the structures of artificial reaction spaces, the models succeeded in reproducing the physiological fractal dimension of solid structures with a smaller number of non-reactive obstacles than in the physiological condition. This incomplete compatibility was mitigated when we chose a suitable condition of a perimeter-to-area ratio of the operating range to our model. Our results also show that a simulation space is partitioned into convenient reaction compartments as an in vivo environment with the exact amount of solid structures estimated from TEM images. The characteristics of these compartments engender larger mean square displacement of a mobile particle than that of particles in smaller compartments. Subsequently, the particles start to show confined particle-like behavior. These results are compatible with our previously presented results, which predicted that a physiological environment would produce quick response and slow exhaustion reactions.
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http://dx.doi.org/10.3389/fphys.2012.00293DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3424521PMC
October 2012

From microscopy data to in silico environments for in vivo-oriented simulations.

EURASIP J Bioinform Syst Biol 2012 Jun 26;2012. Epub 2012 Jun 26.

Department of BioSciences and Informatics, Keio University, Yokohama, Kanagawa, Japan.

Abstract: : In our previous study, we introduced a combination methodology of Fluorescence Correlation Spectroscopy (FCS) and Transmission Electron Microscopy (TEM), which is powerful to investigate the effect of intracellular environment to biochemical reaction processes. Now, we developed a reconstruction method of realistic simulation spaces based on our TEM images. Interactive raytracing visualization of this space allows the perception of the overall 3D structure, which is not directly accessible from 2D TEM images. Simulation results show that the diffusion in such generated structures strongly depends on image post-processing. Frayed structures corresponding to noisy images hinder the diffusion much stronger than smooth surfaces from denoised images. This means that the correct identification of noise or structure is significant to reconstruct appropriate reaction environment in silico in order to estimate realistic behaviors of reactants in vivo. Static structures lead to anomalous diffusion due to the partial confinement. In contrast, mobile crowding agents do not lead to anomalous diffusion at moderate crowding levels. By varying the mobility of these non-reactive obstacles (NRO), we estimated the relationship between NRO diffusion coefficient (Dnro) and the anomaly in the tracer diffusion (α). For Dnro=21.96 to 44.49 μm2/s, the simulation results match the anomaly obtained from FCS measurements. This range of the diffusion coefficient from simulations is compatible with the range of the diffusion coefficient of structural proteins in the cytoplasm. In addition, we investigated the relationship between the radius of NRO and anomalous diffusion coefficient of tracers by the comparison between different simulations. The radius of NRO has to be 58 nm when the polymer moves with the same diffusion speed as a reactant, which is close to the radius of functional protein complexes in a cell.
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http://dx.doi.org/10.1186/1687-4153-2012-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3698665PMC
June 2012

Software support for SBGN maps: SBGN-ML and LibSBGN.

Bioinformatics 2012 Aug 10;28(15):2016-21. Epub 2012 May 10.

EMBL European Bioinformatics Institute, Hinxton, UK.

Motivation: LibSBGN is a software library for reading, writing and manipulating Systems Biology Graphical Notation (SBGN) maps stored using the recently developed SBGN-ML file format. The library (available in C++ and Java) makes it easy for developers to add SBGN support to their tools, whereas the file format facilitates the exchange of maps between compatible software applications. The library also supports validation of maps, which simplifies the task of ensuring compliance with the detailed SBGN specifications. With this effort we hope to increase the adoption of SBGN in bioinformatics tools, ultimately enabling more researchers to visualize biological knowledge in a precise and unambiguous manner.

Availability And Implementation: Milestone 2 was released in December 2011. Source code, example files and binaries are freely available under the terms of either the LGPL v2.1+ or Apache v2.0 open source licenses from http://libsbgn.sourceforge.net.

Contact: sbgn-libsbgn@lists.sourceforge.net.
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http://dx.doi.org/10.1093/bioinformatics/bts270DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3400951PMC
August 2012

BioPAX support in CellDesigner.

Bioinformatics 2011 Dec 21;27(24):3437-8. Epub 2011 Oct 21.

Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA.

Motivation: BioPAX is a standard language for representing and exchanging models of biological processes at the molecular and cellular levels. It is widely used by different pathway databases and genomics data analysis software. Currently, the primary source of BioPAX data is direct exports from the curated pathway databases. It is still uncommon for wet-lab biologists to share and exchange pathway knowledge using BioPAX. Instead, pathways are usually represented as informal diagrams in the literature. In order to encourage formal representation of pathways, we describe a software package that allows users to create pathway diagrams using CellDesigner, a user-friendly graphical pathway-editing tool and save the pathway data in BioPAX Level 3 format.

Availability: The plug-in is freely available and can be downloaded at ftp://ftp.pantherdb.org/CellDesigner/plugins/BioPAX/ CONTACT: huaiyumi@usc.edu

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btr586DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3232372PMC
December 2011

Physiological environment induces quick response - slow exhaustion reactions.

Front Physiol 2011 21;2:50. Epub 2011 Sep 21.

Department of Biosciences and Informatics, Keio University Yokohama, Japan.

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.
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http://dx.doi.org/10.3389/fphys.2011.00050DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3177084PMC
November 2011