Physicists solve mysteries of microtubule movers

Physicists solve mysteries of microtubule movers

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The three visible out-of-plane microtubule bundles are not aligned with the other microtubules in the lower left of the image. Credit: Georgia Institute of Technology

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The three visible out-of-plane microtubule bundles are not aligned with the other microtubules in the lower left of the image. Credit: Georgia Institute of Technology

Functional matter is any collection of materials or systems made up of independent units that can move on their own, due to self-propulsion or autonomous motion. They can be any size – think clouds of bacteria in a petri dish, or schools of fish.

Roman Grigoriev is very interested in the behavior that arises from the systems of active objects made of units at the molecular scale – small systems that convert stored energy into precise movement, which consumes energy as they move and use mechanical energy.

“Active matter systems have received significant attention in physics, biology, and materials science because of their unique properties and potential applications,” explains Grigoriev, a professor in the School of Physics at Georgia Tech.

“Researchers are exploring how functional materials can be applied to tasks such as designing new materials with tailored properties, understanding biological behavior, and developing new robotics and autonomous systems,” he said.

But that is only possible if scientists learn how the microscopic units that make up the active substance interact, and whether they can affect this interaction and thus the collective properties of the active substance on a larger scale.

Grigoriev and his research colleagues have found a possible first step by developing a new model of active matter that makes new sense in the physics of the problem. They describe their methods and results in a study published in Advances in Science“A data-driven model of functional data.”

Grigoriev’s co-authors include School of Physics graduate researchers Matthew Golden and Jyothishraj Nambisan, and Alberto Fernandez-Nieves, a professor in the Department of Physics at the University of Barcelona and a former associate professor of Physics at Georgia Tech.

A ‘two-sided’ solution?

The research team focused on one of the most common examples of active substances, the suspension of self-moving particles, such as bacteria or artificial microswimmers, in a liquid environment. These particles aggregate, flow, and otherwise form dynamic patterns due to their ability to move and interact.

“In our paper, we use data from an experimental system involving the formation of microtubules, which provide structural support, shape, and organization to eukaryotic cells (any cell with a well-defined nucleus),” explained Grigoriev.

Microtubules, along with actin filaments and other bacteria, are examples of nematics, rod-like objects whose invisible “heads” are “tails.”

The movement of microtubules is driven by molecular motors powered by the protein, kinesin, which consumes adenosine triphosphate (ATP) dissolved in the fluid to slide a pair of neighboring microtubules past each other. The researcher’s system used microtubules placed between the layers of oil and water, preventing their movement in two dimensions.

“That makes it easy to observe the microtubules and track their movement. By changing the kinesin or ATP concentrations, we can control the movement of the microtubules, which makes this experimental setup even the most popular in the study of active nematics and that in general, it is an effective, Grigoriev said.

‘This is where the story gets interesting’

Getting a clearer picture of microtubular movements was one of the findings of the study.

One was learning more about the relationship between the characteristic patterns that define the orientation and movement of nematic molecules on a large scale. Those patterns, or topological defects, determine how the nematics align at the oil-water interface, which is in two spatial dimensions.

“Understanding the relationship between flow – a global property of the system, or fluid – and topological defects, which define the spatial orientation of microtubules, is one of the main psychological questions facing researchers in the field,” said Grigoriev. “One must identify precisely the physical effects that govern the interaction between microtubules and the surrounding fluid.”

“And that’s where the story gets interesting,” Grigoriev added. “More than ten years, it was believed that the basic physics was well understood, and a large number of theoretical and mathematical studies based on the first widely accepted model” – that is, one that is based on science – “which came from the beginning. in the nematics working in three spatial dimensions.”

In the Georgia Tech model, however, the dynamics of active nematics – in particular, the length and time scales of the patterns that appear – are controlled by two of the animals that often define those things that are considered the main physical effects: the stiffness of the microtubules (their flexibility). ), and a function that describes the pressure, or force, produced by kinesin motors.

“Using a data-driven approach, we have presented a precise modeling approach that shows that, in one-dimensional active nematics, the outstanding physical effects are different from what was previously thought,” said Grigoriev. “In particular, the time scale is set by the rate at which the bundles of microtubules are stretched by kinesin.” It is this level, rather than the pressure, that lasts.

The danger of confirmation bias

Grigoriev said that the results of the study have important implications for the understanding of active nematics and their emerging behavior, explaining that they help to reconcile a number of recent experimental results that were not previously reported, such as the amount of topological properties measured with the concentration of kinesin. and viscosity of fluid layers.

“More importantly, our results show that the dangers associated with the traditional assumptions that have established the research community are persistent and difficult to overcome,” Grigoriev said. “While data-driven methods may have their own sources of bias, they provide a perspective different enough from conventional methods to be an important research tool in their own right.”

More information:
Matthew Golden et al, Physically based modeling of active nematics data, Advances in Science (2023). DOI: 10.1126/sciadv.abq6120

Journal information:
Advances in Science

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