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A team of mathematicians and biologists led by Carnegie’s Will Ludington and Technische Universität Berlin’s Michael Joswig developed a new approach to reveal key genes and species that regulate biological networks. Their work, published this week in Proceedings of the National Academy of Sciences, identifies genes in cells and species in ecosystems that sit at the top of a regulatory hierarchy and drive evolutionary and ecological trajectories.
Charles Darwin concluded On the Origin of Species with the famous “tangled bank” analogy to explain how organisms in an ecosystem affect one another’s fitness. “It is interesting to contemplate a tangled bank, clothed with many plants of many kinds, with birds singing on the bushes, with various insects flitting about, and with worms crawling through the damp earth,” Darwin wrote. “And to reflect that these elaborately constructed forms, so different from each other, and dependent upon each other in so complex a manner, have all been produced by laws acting around us.”
To map these interactions in ecosystems, ecologists use network analysis to study the connections. Keystone species, such as wolves, have a disproportionately large impact on their communities and the other organisms within them.
Geneticists take a similar approach to studying individual genes as part of larger genetic networks: genes in a cell must also work together. While one gene typically encodes one protein, that protein must interact well with other proteins—each produced by different genes —for it to help the organism’s evolutionary fitness. By looking at an entire network of genes and the proteins they produce, it is apparent that some of them—like wolves—have greater influence on the function of the whole than other genes.
However, many of these definitions are focused on relationships between pairs. The reality is that many of these pairs change their behavior in different contexts. Similar to a social setting, two might be company, but three can be a crowd.
“Increasingly, biology is devoted to understanding the interactions across scales—from genomes to ecosystems—between species in the context of an environment,” Ludington explained. “Rather than considering each species individually, we must attempt to understand how community interactions impact health and resilience across many spatial scales.”
This realization has driven a leap forward in microbiome research in recent years. The animal gut microbiome is a community of hundreds to thousands of microbial species living within the body. These populations affect health, fertility, and even longevity. Recent research has revealed that microbial communities can underpin the health and dynamics of entire ecosystems.
Since arriving at Carnegie in 2018, Ludington has advanced microbiome research using genetic, physiological, and computational approaches, revealing new information about how the microbiome acquires new species, the evolutionary trajectories of microbiome communities, and how microbiome interactions drive a new form of antibiotic resistance.
In this new paper, Ludington, with Joswig (co-supervisor) and Holger Eble of TU Berlin, as well as Lisa Lamberti of ETH Zurich, developed a high-dimensional geometrical approach for elucidating genetic relationships that change in different contexts.
“You may have encountered the concept of epistasis in high school biology class,” Joswig explained. “It’s based on the idea that one gene affects another, a phenomenon that is ubiquitous in nature, such as determining coat color in certain dog breeds like the Labrador Retriever. But the mathematical model used traditionally has limitations when we start talking about three or more genes. We sought to remedy that.”
The researchers layered a knowledge of epistasis with representations of evolutionary fitness to find both genes and species that act as regulators of an entire biological network.
By doing this, they showed that in the fruit fly gut microbiome, two different bacteria —Lactobacilli and Acetobacter, which are commercially important for their involvement in natural fermentation— can play a top-of-hierarchy master regulatory role in shaping their communities. Likewise, their method revealed genes in the bacteria E. coli that serve as master regulators, guiding evolution.
“In our analysis, we find that gene interactions in higher dimensions reshape the fitness landscape—a method of visualizing the relationship between organisms’ genetic material and reproductive success,” Ludington said. “The Red Queen hypothesis, which was put forward in the 1970s, positioned evolution as a sort of arms race driven by competition between co-evolving species. But our work indicates that the continuous genetic innovation seen in long-term evolution experiments might not be caused by competition—the prevailing wisdom for 50 years—but could actually be due to the mutation of key genes continuously altering the fitness landscape.”
Looking ahead, this new tool can be applied to explore high-dimensional interactions in other biological networks in greater depth.
Published in journal: Proceedings of the National Academy of Sciences
Source/Credit: Carnegie Institution for Science
Reference Number: mcb121523_01