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Selection in assembly space. (A) Diagrammatic representation of assembly space depicts the formation of a combinatorial object space from building blocks and physical constraints. (B) Copy number distribution of objects observed at different assembly indices as a result of selection or no selection. (C) Representation of the physical path to construct an object with undirected and directed paths (selection) leading to low and high copy numbers of the observed object. credit: arXiv (2022). DOI: 10.48550/arxiv.2206.02279
An international team of researchers has developed a new theoretical framework that bridges physics and biology, providing a unifying approach to understanding how complexity and evolution manifest in the natural world.
This new work on “Assembly Theory” was published today. Nature, represents a major advance in our fundamental understanding of biological evolution and how it is governed by the physical laws of the universe. The title of this paper is “Explaining and quantifying selection and evolution using assembly theory.”
The study builds on the team’s previous work that developed set theory as an empirically tested approach to life detection, and is also useful in the search for alien life forms and efforts to evolve new life forms in the laboratory. It’s making an impact.
In previous work, the team assigned molecules a complexity score called a molecular assembly index based on the minimum number of bond-forming steps required to construct the molecule. They showed how this index can be measured experimentally and how high values correlate with molecules of life origin.
The new research introduces a mathematical formalism centered around physical quantities called “sets.” Assemblage captures how many selections are required to produce a particular set of complex objects based on their abundance and assemblage index.
“Assembly theory provides a completely new lens through which to view physics, chemistry, and biology as different views of the same underlying reality,” said Dr. Schneider, a theoretical physicist and origin of life researcher at Arizona State University. One lead author, Professor Sarah Walker, explained:
“With this theory, we can begin to bridge the gap between reductionist physics and Darwin’s theory of evolution. This is a major step towards a fundamental theory that unifies inert and living matter.”
Researchers have demonstrated how assembly theory can be applied to quantify selection and evolution in systems ranging from simple molecules to complex polymers and cellular structures.
It accounts for both the discovery of new objects and the selection of existing objects, allowing for the unlimited increase in complexity that is characteristic of life and technology.
Professor Lee Cronin, a chemist at the university, said: “Assemblage theory makes up our world, defined not just by immutable particles, but by the memories needed to construct objects through choices over time.” “This provides an entirely new way to look at the materials that matter.” Co-lead author from Glasgow.
“With further research, this approach has the potential to transform the field from cosmology to computer science. This represents a new frontier at the intersection of physics, chemistry, biology, and information theory.”
The researchers aim to further refine set theory, characterize known and unknown life, and explore its applications to test hypotheses about how life emerges from inanimate objects.
“An important feature of this theory is that it can be tested experimentally,” Cronin says. “This opens up the exciting possibility of using ensemble theory to design new experiments that can elucidate the origins of life by creating living systems from scratch in the laboratory.”
This theory brings many new questions and research directions to the interface of physical and life sciences. Overall, set theory promises to provide deep new insights into the physics underlying biological complexity and evolutionary innovation.
For more information:
Leroy Cronin, Assembly Theory Explains and Quantifies Selection and Evolution. Nature (2023). DOI: 10.1038/s41586-023-06600-9. www.nature.com/articles/s41586-023-06600-9