O7-1

Pattern formation in sol media using branched DNA motifs
Hiroshi Ogata 1
hiroshi.ogata.t2@dc.tohoku.ac.jp

Ibuki Kawamata 1,2
ibuki.kawamata@tohoku.ac.jp
12Keita Abe 1

keita.abe.t7@dc.tohoku.ac.jp

Satoshi Murata 1
satoshi.murata.a4@tohoku.ac.jp

Department of Robotics, School of Engineering, Tohoku University, 6 -6-01, AramakiAzaAoba,Aoba, Sendai, Miyagi, 980-0845, Japan
Natural Science Division, Faculty of Core Research, Ochanomizu University, 2 -1-1 Ohtsuka,Bunkyo-ku, Tokyo 112-8610, Japan

Keywords: Reaction-diffusion system, Self-assembly, Physical pattern formation, DNA hydrogel
Pattern formation in reaction-diffusion systems is a phenomenon in which molecules diffuse while
reacting, autonomously forming heterogeneous concentration distrib utions of chemical species [1].
Pattern formation is well known as a mechanism of morphogenesis in biological systems, such asembryogenesis in Drosophila and generation of patterns on the skin surface [2]. If we can artificiallyreconstruct this mechanism, we can construct macroscale molecular systems that far exceed the sizeof molecules. The technology for constructing macro -scale molecular systems is expected to beapplied to artificial organs in the future.
So far, we developed an autonomous linear pattern formation method using a reaction -diffusion
system of DNA in hydrogel media [3,4], in which a steep concentration distribution of chemicalspecies (DNA) forms a pattern and showed that it can be successfully cascaded. As a next step, we
consider here the possibility of pattern materialization by adding heterogeneity of physical andmechanical properties to the distribution of the chemical species formed.
The proposed reaction-diffusion system forms patterns by polymerization of branched DNA motifs(X motifs) in a highly viscous sol medium [5]. In this system, the four single -stranded DNAs thatcomprise the branched DNA motif are divided into two gro ups that do not polymerize into eachother and diffuse from sources on either side of the sol reaction field. DNA motifs are formed at
equidistant positions where these DNAs meet, and the motifs polymerize in a position -specificmanner to form a DNA hydrogel.
Fluorescence microscopy showed that a linear pattern (bisector pattern between sources) wasformed even in the sol medium. The fluorescence recovery inside and outside the reaction area wasmeasured to quantitatively evaluate the heterogeneity of t he diffusion coefficient. More surprisingly,
we observed that the once formed linear patterns gradually wave in the sol medium. The cause ofthis phenomenon is currently under investigation.
[1] Turing, A. M. "The chemical basis of morphogenesis. Philosophical Transactions of the Royal
Society." London, B 237 (1952): 337-72.
[2] St Johnston, Daniel, and Christiane Nüsslein-Volhard. "The origin of pattern and polarity in theDrosophila embryo." Cell 68.2 (1992): 201-219.
[3] Abe, Keita, et al. "Programmable reactions and diffusion using DNA for pattern formation inhydrogel medium." Molecular Systems Design & Engineering 4.3 (2019): 639-643.
[4] Abe, Keita, Satoshi Murata, and Ibuki Kawamata. "Cascaded pattern formation in hydrogel
medium using the polymerisation approach." Soft Matter 17.25 (2021): 6160-6167.
[5] Seeman, Nadrian C. "Nanomaterials based on DNA." Annual review of biochemistry 79 (2010):65.

O7-2
Force measurement of kinesin-propelled microtubules inswarming using electromagnetic tweezers

1
2

Mst Rubaya Rashid 1

Mousumi Akter 2

rubaya.rashid1993@gmail.com

akter80mousumi@gmail.com

Arif Md. Rashedul Kabir 2

Jakia Jannat Keya 2

kabir@sci.hokudai.ac.jp

jakiajannatk@gmail.com

Kazuki Sada 1,2

Akira Kakugo 1,2

sadatcm@sci.hokudai.ac.jp

kakugo@sci.hokudai.ac.jp

Graduate School of Chemical Sciences and Engineering, Hokkaido University, Sapporo, Japan
Faculty of Science, Hokkaido University, Sapporo, 060-0810, Japan

Keywords: Microtubule, Kinesin, DNA conjugation, Swarm formation, Force of swarm, Magnetic
bead, Electromagnetic tweezers
The Swarming of living organisms such as fishes, birds , and ants is a fascinating display of
coordinated behavior in nature (1). Swarming provides the organisms with several advantages
such as parallelism, robustness, flexibility, and permits exhibiting emergent functions by theorganisms (2). Such attractive features of the swarming of living beings have motivated researchers
working in material science, and engineering to utilize the swarming of self-propelled objects in
artificial environments for sophisticated applications (3, 4). Recently our group has successfully
demonstrated the swarming of a large number of kinesin-propelled microtubules (MTs), a selfpropelled biomolecular machine, where the swarms of MTs exhibited translational and rotationalmotion upon consumption of chemical energy of ATP hydrolysis by kinesins (5). The swarming of
MTs with rotational and translational motion holds great potential as their motion can be harnessedto perform work for nanotechnological applications, e. g. in molecular machines or devices,molecular robotics, etc. To ensure real-life applications of the MT swarms it is a prerequisite toquantify the amount of work that can be harnessed from the swarms. In this work, we attempt toquantify the force associated with the swarming of MTs driven by kinesins. Azide-labeled MTs wereprepared from azide-labeled tubulin using the polymerizing agent guanosine triphosphate. Twocomplementary DNA sequences were used to modify two sets of azide -MTs by azide-alkyne
cycloaddition reaction and the magnetic beads were modified with one of the DNAs. Swarming of
the DNA-modified MTs was performed on a kinesin-coated glass surface and observed by afluorescence microscope. A circular-shaped swarm was formed by the MTs, and the bead was loadedby the swarm. An electromagnetic tweezer (EMTw) was used to apply electromagnetic force (EMF)
on magnetic bead-attached rotational swarms. The force of the circular-shaped MT swarms wassuccessfully determined from its velocity by applying EMF. The force increases linearly withincreasing the size of the circular swarm. This increase in force arises from the higher number ofactive kinesins driving the larger swarms. Such estimation of the force of the swarm of MTs will
widen its application in nanotechnology as well as in robotics.
[1] Beshers, S. N.; Fewell, J. H. Models of division of labor in social insects , Annual Review ofEntomology, 2001, 46, 413–440.
[2] Niven, J. E. How honeybees break a decision-making deadlock, Science, 2011, 335, 43–44.
[3] Wei, H. X.; Chen, Y. D.; Tan, J. D. & Wang, T. M. Sambot: a self-assembly modular robot system.
IEEE/ASME Trans. Mechatron., 2011, 16, 745–757.
[4] Keya, J. J.; Suzuki, R.; Kabir, A. M. R.; Inoue, D.; Asanuma, H.; Sada, K.; Hess, H.; Kuzuya,
A. and Kakugo, A. DNA-assisted swarm control in a biomolecular motor system, Nature
Communications, 2018, 9, 453.

O7-3
Order Parameter Analysis of Microtubule Motility
Dynamics
Ma Chen 1,3

Masayuki Yamamura 1

ma.c.ab@m.titech.ac.jp

my@c.titech.ac.jp

Mousumi Akter 2,3
Akther80mousumi@gmail.com

Gutmann Gregory Spence 3
gutmann@molecular-robotics.co.jp
12
3Akira Kakugo 2,3
kakugo@sci.hokudai.ac.jp

Akihiko Konagaya 3
konagaya@molecular-robotics.co.jp

School of Computing, Tokyo Institute of Technology
Dept. Chemistry, Physical Chemistry, Hokkaido University
Molecular Robotics Research Institute, Co., Ltd.

Keywords: Molecular Robotics, Microtubule Motility Dynamics, Order Parameter Analysis
Microtubules often form streams at high density, which glide in the same directions on Kinesin
coated glass surface in microtubule motility assay. At higher density of microtubules, they tend tomove together (snuggling) to avoid collision and overriding of microtubules. As a result,microtubule groups emerge motion patterns showing straight, curved or wave like trajectories.
In order to analyze the microtubule group motion patterns, we applied dense and sparse opticalflow (DOF and SOF) methods followed by polarity analysis with order parameter. In case of DOF,
the polarity analysis revealed overall difference of microtubule motility dynamics depending tomicrotubule concentration, to some extent.
In order to identify the emergence of motion patterns, SOF method was attempted to the same
video data as used in the SOF method. In this presentation, we will discuss the limitation of
conventional order parameter definition when dealing with parallel and anti-parallel movement ofmicrotubule dynamics.

O7-4

Deep Learning Detection of Giant Vesicles
Using a Synthetic Data Setof Confocal Fluorescence Microscopy Images
Soichiro Hiroi 1,2

hiroi-soichiro1729@g.ecc.u-tokyo.ac.jp

Zhang Yuhui2zhang@molecular-robotics.co.jp

Taro Toyota 1,3

cttoyota@mail.ecc.u-tokyo.ac.jp

Akihiko Konagaya2

konagaya@molecular-robotics.co.jp

1

Graduate School of Arts and Science, The University of Tokyo, 3-8-1 Komaba, Meguro-ku,
Tokyo 153-8902, Japan2
Molecular Robotics Research Institute, Co., Ltd., W304, TITECH Yokohama Venture Plaza,4259-3, Nagatsuta, Yokohama Midori-ku, Kanagawa, 226-8510, Japan
3Universal Biology Institute, The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 1538902, Japan

Keywords: Confocal fluorescence microscopy, Giant vesicle, Deep learning
Confocal laser scanning microscopy has the capability of acquiring cross-section images byremoving fluorescence generated outside the focal plane to be observed. This means that we canconstruct a three-dimensional (3D) image of tiny structures that would be difficult to be physicallysectioned by acquiring multiple images in which the focal plane position is continuously changed.
Therefore, it has been widely used in many scientific fields and is a common method to visualize
the 3D morphology of cell-sized closed lipid bilayer membranes called giant vesicles (GVs).
On the other hand, virtual reality (VR) visualization of microscopic images[1] is useful for theobservation of molecular assemblies in which 3D morphology is important. GV is one of thosemolecular assemblies whose morphology is susceptible to surrounding disturbances[2]. However,when confocal fluorescence microscopy images of GVs are captured from the top to the bottom
while changing the focal plane, the GVs shift their centroid position due to advection or fluctuation
including Brownian motion, and the 3D structure of freely floating GVs could not be correctlyreconstructed.
Therefore, in order to correct the position of each focal plane prior to VR-ization, we conceived
the idea of detecting each GV using an object detection method based on deep learning. Deeplearning is a part of machine learning methods and several deep learning frameworks have been
applied to object detection tasks and achieved great results[3]. In this study, to aim at VR-ization,
we developed a synthetic model of confocal fluoresce microscopy images of GVs. Furthermore,using the teacher data images generated by the synthetic models, we constructed a GV detect modelwith transfer learning based on YOLO, one of the object detection models by convolutional neuralnetworks.
[1] Gutmann, G. S.; Azuma, R.; Konagaya, A. A virtual reality computational platform dedicated forthe emergence of global dynamics in a massive swarm of objects, J. Imaging Soc. Jpn., 2018, 57,647-653.
[2] Lipowsky, R. Remodeling of Membrane Compartments: Some Consequences of Membrane Fluidity,J. Biol. Chem., 2014, 395, 253–274.
[3] Anushka; Arya, C.; Tripathi, A.; Singh, P.; Diwakar, M.; Sharma, K.; Pandey, H. Object
Detection Using Deep Learning: A Review, J. Phys.: Conf. Ser., 2021, 1854, 012012.

O7-5
DNA AFM images in Super-resolution by VR system andDeep Learning
Hu Xiaoran 1,3

Masayuki Yamamura 1Qing Liu 2

Akinori Kuzuya 2,3

hu.x.ab@m.titech.ac.jp
r412989@kansai-u.ac.jp

Gutmann Gregory Spence 3

gutmann@molecular-robotics.co.jp
123

my@c.titech.ac.jp

kuzuya@kansai-u.ac.jp

Akihiko Konagaya 3

konagaya@molecular-robotics.co.jp

School of Computing, Tokyo Institute of Technology
Dept. Chemistry and Materials Engineering, Kansai University
Molecular Robotics Research Institute, Co., Ltd.

Keywords: Molecular Robotics, Super Resolution, Atomic Force Microscope Images, Deep
Learning
Atomic force microscopy (AFM) is one of the most popular imaging and characterization
techniques, which has the advantage of analyzing many types of surfaces in nano-scale. Manykinds of research have been done the studies on DNA dynamics and structures with the help ofAFM, so far. However, AFM's tip radius and resolution are still not enough to imaging results ofDNA nano structures, losing the vital information of DNA double strand structure like major
grooves and minor grooves. This study presents a super-resolution model combining VR molecularmodel and deep learning to visualize major and minor grooves from real DNA AFM images.
Applying the model, the reconstruction resolution can be beyond the limits set by tip radius andoriginal imaging resolution. To build high-resolution AFM images, VR DNA molecular model[1] isbuilt to obtain simulated DNA strands, and AFM imaging is simulated to build simulated AFM
images. Tip radius of AFM probe and image resolution are the parameters in the AFM imaging
process to obtain different images by the same simulated DNA model. Then deep learning method
based on Cycle GAN[2] is used to build a super-resolution network to construct detailed
information for DNA images. Finally, real AFM images are used to test the performance of themodel and determine the valid parameters in the image processing section.

[1] Gutmann, G.; Azuma, R.; Konagaya, A. A Virtual Reality Computational Platform Dedicatedfor the Emergence of Global Dynamics in a Massive Swarm of Objects. J. of the Imaging
Society of Japan; 2018, 57 (6); 647–653. https://doi.org/10.11370/isj.57.647[2] Zhu, J.-Y.; Park, T.; Isola, P.; Efros, A. A. Unpaired Image-To-Image Translation Using
Cycle-Consistent Adversarial Networks; 2017; pp 2223–2232.

O7-6

A 3D hydrodynamic ocean model simulation and its dataanalyses targeting waters off Niihama in Seto Inland Sea,
Japan
Masanori Niwano 1

Yoshihide Matoba 1

Fumio Horiguchi 2

Yuriko Ishikawa 2

niwanom@sc.sumitomo-chem.co.jp

12

Sumitomo Chemical Co., Ltd., 3-1-98 Kasugade-naka, Konohana-ku, Osaka 554-8558, Japan
National Institute of Advanced Industrial Science and Technology, 16-1 Onogawa, Tsukuba,
Ibaraki 305-8569, Japan

Keywords: hydrodynamic model, Seto Inland Sea, Niihama, tidal residual current, watertransparency, harmonic analyses
Toward a final goal for developing a model of chemical fate and its aquatic organism effect, ahigh-resolution hydrodynamic ocean model [1] was applied to waters off Niihama in the middle of
the Seto Inland Sea (SIS), Japan. A heating formula depending on distribution of water transparency
was newly incorporated into the model. Using this model, tidal current, temperature and salinity
were calculated in the areas covering the middle of SIS, and then the behaviors at the waters off
Niihama were simulated in detail by using results of the first calculation. The simulation wasperformed in 2016 summer when the effects of the chemicals to aquatic organisms seem highlyconcerned due to a suppressed convective mixing. The model accurately reproduced spatial andtemporal variations of tidal current, water temperature and salinity observed at the waters off
Niihama as well as the mid SIS [2-3]. Results from the simulation demonstrated that the waters off
Niihama experienced fast water exchange by tidal residual currents enhanced at steep bathymetry
and large vertical water displacement due to propagation of waves generated there in comparison
with the middle of the SIS.
[1] Shimada, N.; Tomiyama, A. A numerical method for solving compressible gas-liquid two-phaseflows, Kagaku Kogaku Ronbunshu, 2005, 31, 15-24.
[2] Takeoka, H. Hiuchi-Nada (in Japanese), in Coastal Oceanography of Japanese Islands,
edited by Coastal Oceanography Research Committee, Oceanogr. Soc. of Jpn, 694–698,
Tokai Univ. , Press, Tokyo, 1985 .
[3] Futamura, A.; Sugimoto, K. Observation of the oceanic structure of stratified region in HiuchiNada, Bull. Yuge Natl Coll. Maritime Tech, 2009, 31, 1-5.