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EON Workshop "Sensors, Motors and Behaviour at the Origin of Life"

日付
July 26, 2017 - July 28, 2017
場所

ELSI Hall in ELSI-1 bldg., Tokyo Institute of Technology, Ookayama, Meguroku, Tokyo, Japan

Organizers: Matthew Egbert 1 Martin Hanczyc 2
1 Lecturer, University of Auckland, NZ 
2 Principal Investigator, Centre for Integrative Biology, University of Trento, Italy

Please refer to the EON official website (link below).
http://eon.elsi.jp/eon-workshop-sensors-motors-and-behaviour-at-the-origin-of-life/

Behaviour precedes evolution
The behaviour of modern organisms often involves intricate sensors and sophisticated motors that are too complicated to have spontaneously emerged in a prebiotic world. Evolution was required to produce these structures and for this reason, it might seem counterintuitive to consider the possibility that behaviour existed before evolution. However, numerous simple physical systems demonstrate surprisingly life-like behaviours. Motile oil-droplets (e.g., Hanczyc et al. 2014), autocatalytic reaction-diffusion spots (Virgo 2011), and ramified charge-transportation networks (Kondepudi et al. 2015) all move toward environments that benefit their persistence and away from damaging environments. These systems thus demonstrate a pre-biotic form of self-preservation, which in turn suggests that functionalities typically associated with life, such as sensing and actuating could have been available in pre-evolutionary contexts. In this workshop we will consider in detail what kinds of sensors, motors and behaviors might have been available to the earliest organisms and proto-organisms, and the role that these systems might have played in facilitating the emergence of life.

One focus of the workshop will be upon metabolism-based behaviours, where instead of responding directly to environmental properties (such as the presence of sugar), organisms act in response to how efficiently their metabolism is operating (e.g. in response to the state of the electron transport system). This kind of behaviour is observed in various modern bacteria (see e.g. Alexandre et al., 2000), and it is directly comparable to the mechanisms underlying the pre-biotic self-preserving behaviours mentioned above.

A number of recent theoretical contributions have suggested that metabolism-based behaviors can improve robustness, adaptivity and evolvability, by

(1) driving behaviour that responds appropriately to phenomena that neither they nor their ancestors have ever previously experienced (Egbert et al. 2012);

(2) driving behaviour that takes into account the history of the organism, such as which resources it has recently acquired, if it has sustained damaged, if a symbiont or parasite is affecting its metabolic dynamics etc. (Egbert et al. 2009; 2010; 2012, Egbert & Perez-Mercader, 2016);

(3) integrating numerous and simultaneous environmental effects into a coherent and self-preserving response without requiring any extra "computational" machinery for weighing the influence of the different factors (Egbert et al. 2009; 2010).

(4) allowing an organism to compensate behaviorally for changes in its internal operation, such as modification to a metabolic pathway (Egbert et al. 2010; 2012; Egbert & Perez-Mercader, 2016).

Given that metabolism-based behaviour (i) improves robustness, adaptivity and evolvability; (ii) is found in simple physical systems that almost certainly predate biological evolution and (iii) is also found in modern organisms, we set out to investigate The Origins of Behaviour in the context of the Origins of Life.

The invited participants come from a wide variety of backgrounds including experts in bacterial chemotaxis, complex chemical and physical systems, philosophy of biology, philosophy of science, computational modelling of complex biological systems, mathematical modelling of sensorimotor-based adaptive behaviour, artificial life, synthetic biology and artificial chemistry. It is our hope that gathering this group together will provide a community that will foster innovative inter- and trans-disciplinary research.