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Mechanosensation Mediates Long-Range Spatial Decision-Making in an Aneural Organism

N. Murugan,D. Kaltman,Hong Jin,Melanie Chien,R. M. Flores,C. Nguyen,D. Tuzoff,Alexey Minabutdinov,Anna Kane,R. Novák,D. Ingber,M. Levin

Published 2020 in bioRxiv

ABSTRACT

The unicellular protist Physarum polycephalum is an important emerging model for understanding how aneural organisms process information toward adaptive behavior. Here, we reveal that Physarum can use mechanosensation to reliably make decisions about distant objects its environment, preferentially growing in the direction of heavier, substrate-deforming but chemically-inert masses. This long-range mass-sensing is abolished by gentle rhythmic mechanical disruption, changing substrate stiffness, or addition of a mechanosensitive transient receptor potential channel inhibitor. Computational modeling revealed that Physarum may perform this calculation by sensing the fraction of its growth perimeter that is distorted above a threshold strain – a fundamentally novel method of mechanosensation. Together, these data identify a surprising behavioral preference relying on biomechanical features and not nutritional content, and characterize a new example of an aneural organism that exploits physics to make decisions about growth and form. Highlights The aneural Physarum makes behavioral decisions by control of its morphology It has a preference for larger masses, which it can detect at long range This effect is mediated by mechanosensing, not requiring chemical attractants Machine learning reveals that it surveys environment and makes decision in < 4 hours A biophysical model reveals how its pulsations enable long-distance mapping of environmental features

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