Holding the 1st Molecular Cybernetics / Molecular Robotics Regular Meeting
The 1st Molecular Cybernetics / Molecular Robotics regular meeting (March 2021) will be held as follows.
Organizer: Grant-in-Aid for Transformative Research Areas (A) “Molecular Cybernetics”
Supported by: The Society of Instrument and Control Engineers (SICE), Systems and Information Division, “Intelligent Molecular Robotics Research Committee”
Date & Time: Wednesday, March 17 (scheduled from 13:00 to around 16:30)
Venue: The Zoom URL will be provided later.
Participation fee: Free
In this online regular meeting, we plan to have a talk by Dr. Ryo Mizuuchi (The University of Tokyo) titled “Construction and Evolution of a Molecular Replication System Mimicking Primitive Life,” and a talk by Dr. Naoki Honda (Kyoto University) titled “Data-Driven Modeling of Living Systems.”
In addition to the invited talks above, we are recruiting about two oral presentations from early-career researchers and students.
If you wish to present, please apply using the submission form below.
Students are asked to consult with their academic supervisor before applying.
Please register for a presentation by Wednesday, March 3.
Please register for attendance only (no presentation) by Wednesday, March 10.
Registration form https://forms.gle/kBudASqJLQLD4Hbs7
We look forward to your participation.
Keio University Taisuke Kotsuka tkotsuka [at] keio.jp
Tohoku University Shoji Iwabuchi hoji.iwabuchi.p5 [at] dc.tohoku.ac.jp
Organizer: Grant-in-Aid for Transformative Research Areas (A) “Molecular Cybernetics”
13:20 - 13:25 Opening remarks by the organizers
13:25 - 13:30 Introduction of Dr. Mizuuchi
13:30 - 14:20 Invited talk
Primitive life is thought to have emerged as self-replicating entities of simple informational molecules such as RNA, and to have gradually become more complex through evolution. One way to understand this process is to build an experimental model mimicking primitive replicators and actually let it evolve. We have therefore developed our own simple RNA replication system by combining RNA, proteins, and micro-compartments, and we investigate plausible evolutionary pathways of primitive life by evolving the system experimentally. In this talk, focusing mainly on our work on RNA replication systems, we will introduce how to build molecular replication systems and what kinds of evolution are possible.
In the first half, we will outline an evolvable molecular replication system and present our latest results on what kinds of evolution occurred in our RNA replication system. For example, when we replicated and evolved the RNA replication system over a long period, RNA that had originally been a clonal population accumulated diverse mutations and gradually diverged into five groups with different properties (unpublished). These diverged groups also formed a complex replication network through various interactions. We also investigate evolution of RNA replication systems that were artificially made more complex; in a system where two RNAs replicate cooperatively, under certain conditions evolution strengthened the cooperativity [1]. These results indicate that even simple molecular replicators can undergo stepwise increases in complexity and strengthening of complexity through evolution.
In the second half, we will also introduce studies on improving molecular replication systems, focusing on their construction. For example, we examined characteristics of RNA suitable for RNA replication systems and found that specific sequence/structural features are important for efficient replication via a simple mechanism [2]. In addition, we showed that membrane-free droplets formed by liquid–liquid phase separation can be used as compartments to encapsulate RNA and proteins, instead of commonly used lipid bilayers or water-in-oil droplets [3]. We believe these findings are important for constructing and utilizing artificial molecular replication systems that are more reminiscent of primitive life.
[2] Mizuuchi, R.; Usui, K.; Ichihashi, N. Structural transition of replicable RNAs during in vitro evolution with Qβ replicase. RNA 2020, 26, 83–89.
[3] Mizuuchi, R.; Ichihashi, N. Translation-coupled RNA replication and parasitic replicators in membrane-free compartments. Chem. Commun. 2020, 56, 13453–13456.
With advances in measurement technologies such as live imaging and next-generation sequencers, it has become possible to measure molecular activities and gene expression levels in living systems in a high-throughput manner, enabling us to obtain large-scale, high-dimensional data. As a result, we can now observe life phenomena that are dynamic and complex beyond what we previously imagined, making it difficult for humans to recognize the underlying regularities. Therefore, inverse-problem approaches that extract mechanisms of living systems from data are becoming increasingly important. In this lecture, we will discuss an approach that combines machine learning and mathematical modeling to decode the laws governing living systems in a data-driven manner. Specifically, we will show that it enables mechanistic understanding of information processing and optimal control performed by living systems across hierarchical levels—from cells to multicellular systems to organisms.