TY - JOUR
T1 - From microscopy data to in silico environments for in vivo-oriented simulations
AU - Hiroi, Noriko
AU - Klann, Michael
AU - Iba, Keisuke
AU - Heras Ciechomski, Pablo De
AU - Yamashita, Shuji
AU - Tabira, Akito
AU - Okuhara, Takahiro
AU - Kubojima, Takeshi
AU - Okada, Yasunori
AU - Oka, Kotaro
AU - Mange, Robin
AU - Unger, Michael
AU - Funahashi, Akira
AU - Koeppl, Heinz
N1 - Funding Information:
MK and RM acknowledge the funding through the Swiss Confederation’s Commission for Technology and Innovation (CTI) project 12532.1 PFLS-LS. HK acknowledges the support from the Swiss National Science Foundation, grant no. PP00P2_128503. TEM microscope imaging and the culturing the material cells by NH have been supported by SUNBOR grant (provided by SUNTORY Institute for Bioorganic Research, Japan) and Keio University (Japan).
PY - 2012
Y1 - 2012
N2 - 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 (D nro) and the anomaly in the tracer diffusion (α). For D nro=21.96 to 44.49 μ m 2/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.
AB - 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 (D nro) and the anomaly in the tracer diffusion (α). For D nro=21.96 to 44.49 μ m 2/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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U2 - 10.1186/1687-4153-2012-7
DO - 10.1186/1687-4153-2012-7
M3 - Article
AN - SCOPUS:84887104396
SN - 1687-4145
VL - 2012
JO - Eurasip Journal on Bioinformatics and Systems Biology
JF - Eurasip Journal on Bioinformatics and Systems Biology
IS - 1
M1 - 7
ER -