Advancements in Biological Science: Unraveling the Mechanics of Cells and Tissues in 3D via Active Matter Theory

by Hiroshi Tanaka
Active Matter Theory

Researchers have made a breakthrough by devising a new algorithm to decipher the equations of active matter theory, shedding light on the formation of biological structures such as cells and tissues. This achievement, a result of a decade of research, is incorporated into a freely available supercomputer program, enhancing our understanding of living materials and potentially paving the way for the creation of synthetic biological devices.

This open-source supercomputer program offers predictions on the formation and activity of living materials, facilitating their study across both spatial and temporal dimensions.

These biological materials consist of individual elements, including microscopic motors that transform fuel into motion, resulting in movement patterns. This process enables the material to shape itself through consistent energy use. Termed “active matter,” this concept is key in explaining the mechanics of cells and tissues. Active matter theory, replete with complex mathematical equations, serves as a scientific model for understanding the formation and dynamics of living materials.

A collaboration involving the Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG) in Dresden, the Center for Systems Biology Dresden (CSBD), and the TU Dresden has led to the development of an algorithm, now part of an open-source supercomputer code. This innovation enables the first-ever solutions to the active matter theory equations in practical scenarios. These solutions are a significant step forward in deciphering how cells and tissues achieve their shape and in the design of artificial biological machines.

3D representation of active matter in a structure similar to a dividing cell. Acknowledgment: Singh et al. Physics of Fluids (2023) / MPI-CBG

The Intricacies of Biological Processes and Theories

Understanding the intricate behaviors and processes in biology often requires a solid theoretical foundation. The active matter theory offers a precise and quantitative approach to comprehend these phenomena. The theory describes active matter as materials made of components that convert chemical energy into mechanical forces. Pioneers in this field, such as Frank Jülicher of the Max Planck Institute for the Physics of Complex Systems and Stephan Grill of the MPI-CBG, contributed significantly to its development.

By applying physical principles, the dynamics of active living matter can be characterized and forecasted using mathematical equations. However, these equations are notably complex and challenging to solve, necessitating the use of supercomputers. Different methods exist to predict the behavior of active matter, focusing on various scales from individual particles and molecular levels to large-scale active fluids. These methodologies enable scientists to observe the behavior of active matter across different scales and over time.

Resolving Complex Mathematical Equations

The team led by Ivo Sbalzarini, a professor at the TU Dresden and part of the Center for Systems Biology Dresden (CSBD) and the Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG), has developed a computer algorithm capable of resolving the active matter equations. Their findings were published in the journal “Physics of Fluids” and featured on its cover. The algorithm they present can solve the complex equations of active matter in three dimensions and in varied shapes.

Abhinav Singh, a key author and mathematician, explains, “Our method can handle different shapes in three dimensions over time. It employs a novel numerical technique, effective even when data points are irregularly distributed, providing accurate solutions for biologically realistic scenarios. This allows us to comprehend the long-term behavior of active materials in both static and dynamic states for predicting their dynamics. Moreover, the theory and simulations could be instrumental in programming biological materials or constructing nano-scale engines for useful work.”

Philipp Suhrcke, another primary author and graduate of TU Dresden, notes, “Our work now enables scientists to predict the formation of tissues or the instability of biological materials, with significant implications for understanding growth and disease mechanisms.”

A Universal and Powerful Code

The software, utilizing the open-source library OpenFPM, is available for public use. Developed by the Sbalzarini group, OpenFPM democratizes large-scale scientific computing. The authors created a custom programming language allowing computational scientists to write supercomputer codes by translating mathematical equations directly into program code, significantly reducing the time required for code development in scientific research.

Given the high computational demands of studying three-dimensional active materials, this new code is scalable on both shared and distributed-memory multi-processor parallel supercomputers, thanks to OpenFPM. While designed for high-performance supercomputers, it can also be used on standard office computers for two-dimensional material studies.

Ivo Sbalzarini, the study’s Principal Investigator, summarizes: “A decade of our research has culminated in this simulation framework, greatly enhancing computational science productivity. This tool, open-source, scalable, and adept at handling complex scenarios, opens new pathways for modeling active materials. It could be crucial in understanding cell and tissue morphology – a long-standing question in morphogenesis – and in the development of minimalistic artificial biological machines.”

Reference: “A numerical solver for active hydrodynamics in three dimensions and its

Frequently Asked Questions (FAQs) about Active Matter Theory

What is the key advancement in the study of biological materials?

Researchers have developed a new algorithm to solve equations in active matter theory, enhancing understanding of how biological materials like cells and tissues form and potentially aiding in the creation of artificial biological machines.

How does the new algorithm improve the study of living materials?

The algorithm, implemented in open-source supercomputer code, enables the prediction and study of the behavior of living materials in both spatial and temporal dimensions, offering insights into the mechanics of cells and tissues.

What is active matter and its significance in this research?

Active matter consists of individual components that convert chemical energy into mechanical forces, forming patterns of movement. This concept is crucial for understanding the mechanics of cells and tissues, with the active matter theory providing a framework for this study.

Who were the key contributors to this development?

The development involved scientists from the Max Planck Institute of Molecular Cell Biology and Genetics, the Center for Systems Biology Dresden, and the TU Dresden, with significant contributions from Frank Jülicher and Stephan Grill.

What potential applications does this study open up?

The study’s findings could lead to a better understanding of how cells and tissues achieve their shape and may assist in designing artificial biological machines or nano-scale engines for practical applications.

More about Active Matter Theory

  • Active Matter Theory in Biological Mechanics
  • Open-Source Supercomputer Algorithms for Biology
  • Decoding Cell and Tissue Mechanics with 3D Simulations
  • Max Planck Institute’s Contributions to Biological Material Study
  • TU Dresden’s Research in Computational Biology

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Alex Gomez November 24, 2023 - 4:31 pm

There’s a lot of jargon here, but if I get it right, it’s about using computer models to predict how biological materials behave? That’s pretty cool.

Sarah K. November 25, 2023 - 9:51 am

I’m not a science person but this seems really important? like we’re getting closer to figuring out how living things work on a super small scale.

Michael Johnson November 25, 2023 - 12:03 pm

wow, this is some groundbreaking stuff, the way scientists are using supercomputers to understand cells and tissues, it’s like sci-fi becoming reality…

Emma T. November 25, 2023 - 12:36 pm

Did anyone else find this hard to follow? I mean, I know it’s important but it’s kinda dense with all the technical details.


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