Sea urchins’ sperm pathway could help tiny robots find their way

"It can measure and track the dynamic signal from its current location without knowing the coordinates."
Nergis Firtina

Could sea urchins breeding guide robotics? According to scientists, that's possible.

According to a study released in Physical Review E on December 9, there are parallels between the path taken by sea urchin sperm and computer systems that employ an extremum seeking method of real-time search.

University of California, Irvine, and University of Michigan researchers prepared a mathematical model of sea urchin sperm's pathway to grasp its behavior, initially reported by Popular Science. The authors claim that understanding the biological makeup of the sea urchin can be used to create tiny robots that mimic its behavior while taking cues from their environment.

How do sea urchins breed?

Sea urchins are spiny marine animals of the class Echinoidea. They are found in oceans all over the world and have spherical shells covered with spines. The diameter of the shell is usually 3 to 10 cm in adults.

Sea urchins breed by dispersing clouds of eggs and sperm into the water. Only a small number of the millions of larvae that are produced return to the beach to grow into adults. It could appear to be a dangerous course of action; however, it functions in the ocean. From mussels to sea stars to some species of fish, almost every animal that inhabits the shore sends its young on an open ocean excursion before they return to their habitat to develop into adults along the shore.

Sea urchins’ sperm pathway could help tiny robots find their way
Cross sectional view of sea urchin.

Sea urchin sex probably isn't the first thing that springs to mind when thinking of robotic creations. But Mahmoud Abdelgalil, who studies dynamics and control at UC Irvine and is the lead author of the paper, considers that a relevant and extensively researched biological model.

Sea urchin sperm use chemotaxis, in which the cells migrate in response to a chemical stimulation, to locate an egg. Sperm-activating peptide is a substance that is only secreted by sea urchin eggs, and it interacts with the sperm's flagellum to regulate how it beats. This causes the sperm to turn and bend toward the direction of the egg.

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“Sperm don’t have a GPS,” Abdelgalil says. “They don’t know ahead of time where the egg is. So they measure the local concentration at the current position, then they use that information and move in the direction of increasing concentration levels—which we like to call the direction of the concentration gradient.”

Same for the robots

The same holds true for a robot that seeks extremes: The only thing it is aware of is that it can measure and track the dynamic signal from its current location without knowing the coordinates or any other details about the target's location. When Abdelgalil discovered a previously published work describing their activities under a microscope, he got the notion to investigate at-sea urchin sperm. A proposed model of an extremum-seeking unicycle robot, a basic machine that can only control its orientation and go forward, closely resembled the trajectory of the sperm.

“As soon as I saw the two pictures, I realized that this is more or less the same,” he says. So, in the new study, Abdelgalil and his colleagues illustrated how key components of the sea urchin sperm’s navigation strategy resemble hallmark features of extremum seeking.

Study 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.