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Sea urchin sperm exploit extremum seeking control to find the egg

Mahmoud Abdelgalil, Yasser Aboelkassem, and Haithem Taha
Phys. Rev. E 106, L062401 – Published 9 December 2022
Physics logo See synopsis: Sea Urchin Sperm Follow Their Noses
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Abstract

Sperm cells perform extremely demanding tasks with minimal capabilities. The cells must quickly navigate in a noisy environment to find an egg within a short time window for successful fertilization without any global positioning information. Many research efforts have been dedicated to derive mathematical principles that explain their superb navigation strategy. Here we show that the navigation strategy of sea urchin sperm, also known as helical klinotaxis, is a natural implementation of a well-established adaptive control paradigm known as extremum seeking. This bridge between control theory and the biology of taxis in microorganisms is expected to deepen our understanding of the process. For example, the formulation leads to a coarse-grained model of the signaling pathway that offers new insights on the peculiar switching-like behavior between high- and low-gain steering modes observed in sea urchin sperm. Moreover, it may guide engineers in developing bioinspired miniaturized robots with minimal sensors.

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  • Received 16 February 2022
  • Accepted 3 November 2022

DOI:https://doi.org/10.1103/PhysRevE.106.L062401

©2022 American Physical Society

Physics Subject Headings (PhySH)

Physics of Living SystemsNonlinear Dynamics

synopsis

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Sea Urchin Sperm Follow Their Noses

Published 9 December 2022

Using concepts from control theory, researchers link the complex navigation behavior of a sea urchin sperm to a single parameter: its response to changing chemical “smells.”

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Authors & Affiliations

Mahmoud Abdelgalil*

  • Department of Mechanical and Aerospace Engineering, University of California, Irvine, California 92697, USA

Yasser Aboelkassem

  • College of Innovation and Technology, University of Michigan at Flint, Flint, Michigan 48502, USA and Michigan Institute for Data Science, University of Michigan, Ann Arbor, Michigan 48109, USA

Haithem Taha

  • Department of Mechanical and Aerospace Engineering, University of California, Irvine, California 92697, USA

  • *maabdelg@uci.edu
  • yassera@umich.edu
  • hetaha@uci.edu

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Issue

Vol. 106, Iss. 6 — December 2022

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