Species evolve ways to back up life's machinery

Species evolve ways to back up life’s machinery
Understanding the interactome – the network of all protein interactions for a species – could shed light on how organisms adapt. Credit: Shuoshu / iStock

Scientists have learned a lot about evolution by studying fossils, by observing nature and, more recently, by unraveling the genetic code stored in DNA.

Now, a team of Stanford computer scientists and biologists has looked at evolution through a new lens, by analyzing how proteins – the biological machines produced by DNA – evolve to sustain the of upon which all life depends.

The scientists studied 1,840 – from bacteria to primates – to understand how evolution built that could survive in the face of natural adversities. What they discovered was profound yet intuitive: Every species has evolved backup plans that allow its to find bypasses and workarounds when nature tries to gum up the works. No previous study has ever surveyed such a broad swath of species to find a survival strategy common to all life: Develop a versatile and robust molecular machinery.

"Across our entire sample, we find that the resilience of a species is strongly correlated with having that are robust to failure and can interact in multiple ways to preserve life," said Stanford computer scientist Jure Leskovec, senior author of the paper that appears today in Proceedings of the National Academy of Sciences.

Evolutionary biologist Marcus Feldman, a co-author on the paper, said this is the most ambitious effort yet to understand what scientists call the interactome – the sum total of all the interactions for each species, just as genome describes the sum total of a species' DNA. "We're looking at the mechanism of evolution on an unprecedented scale, using the tools of data science to study the structure of the protein networks that make life possible," Feldman said.

To conduct the study, Stanford postdoctoral scholar Marinka Zitnik built the database of 1,840 organisms and collected data on 9 million protein interactions. The team's premise was that natural selection had already identified these organisms as fit to survive. By asking the right questions, and developing the right analytical techniques, they looked for patterns in the data to help reveal the principles of interactome evolution.

The researchers wanted to understand how protein machines deal with the unexpected. So, they ran a series of data science experiments to disrupt the protein networks that sustain life. In a computational analysis, they knocked out a certain percentage of each organisms' proteins at random. They did this systematically for all 1,840 species, constantly computing whether some sort of backup system would allow the protein networks to continue to function in a way that would support life, until at some point the disruptions caused the protein machinery to fall apart.

Leskovec likened this analytical approach to throwing a sheet of glass against the ground and counting how many pieces it breaks into. If only some small pieces of the glass break away, this indicates a high degree of resilience. Similarly, if an organism's protein networks remain largely intact even when some proteins are removed, this suggests that the organism is resilient. The study showed that organisms stave off collapse through all manner of backup and workaround mechanisms, revealed by the ability of their protein networks to maintain system integrity.

The researchers corroborated this notion of network resilience in a second way. They used this shattering technique to compare species over time. Based on and DNA studies, scientists know roughly the order in which various life forms in the sample appeared in evolution. If protein network resilience confers an , the researchers hypothesized, later-evolved organisms should have networks that are more shatterproof than preceding forms. This is exactly what they found.

Leskovec believes that by studying the genome and interactome together, data scientists can better understand how evolution works. Information about how organisms are built and improved over time is stored in the genome. But as this study shows, the interactome is important to , too: DNA creates and regulates protein networks, which develop backup processes to adapt to changing circumstances. In some cases, these adaptations prove so useful to a species that its genome preserves these protein improvements so they can be inherited.

"Genes can't explain it all," he said. "We can gain deep insights into many features of organisms by exploring quantitative properties of proteins and the computational patterns of networks of their interactions."


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Novel insights into the evolution of protein networks

More information: Marinka Zitnik et al. Evolution of resilience in protein interactomes across the tree of life, Proceedings of the National Academy of Sciences (2019). DOI: 10.1073/pnas.1818013116
Citation: Species evolve ways to back up life's machinery (2019, February 26) retrieved 20 May 2019 from https://phys.org/news/2019-02-species-evolve-ways-life-machinery.html
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Feb 26, 2019
Junk science. Scientists don't learn anything about evolution from studying fossils. Instead, they learn about species that have lived in the past. Period. The yet unproven theory of evolution remains a hugely weak explanation for the diversity we see in the fossil record. There is no science involved to show that species "evolved" certain traits. Science show that these species have certain traits. That's it.

mqr
Feb 26, 2019
Junk science. Scientists don't learn anything about evolution from studying fossils. Instead, they learn about species that have lived in the past. Period. The yet unproven theory of evolution remains a hugely weak explanation for the diversity we see in the fossil record. There is no science involved to show that species "evolved" certain traits. Science show that these species have certain traits. That's it.


I want to see what are the predictions of the theory of evolution by natural selection on what is going to be the next system of organs that "evolves" in the human body. Given the environmental pressures, which is going to be the next sensory system in the human body? I want to see what new functioning organs are showing babies around the world, that are going to be "selected" by evolution. Will humans have a new system to clean plastics or industrial pollutants out of their blood?

Scientific theories are selected based on their predictive power.

Feb 27, 2019
I want to see what are the predictions of the theory of evolution by natural selection on what is going to be the next system of organs that "evolves" in the human body.


Since processes are not time machines, they (and to a lesser degree we) cannot predict what will most likely evolve over geological times needed for new organs or new use for old ones. Instead of asking for the irrelevant, ask for what we actually test.

The usual tests of prediction from the evolutionary process is in front of you, the classical three, that phylogenies and genomes and biogeography make nested hierarchies such as lineage trees and common ancestors (a fact widely discussed in biology classes for nearly two centuries).

But we can also observe ongoing evolution and predict what will likely happen in the next few generations since it happened in the last one or two [ https://en.wikipe...volution ].

TL;DR: Two centuries of tests, spanning geological time.

Feb 27, 2019
The paper has no paywall and is interesting!

The interactome and its resilience grows by the usual suspects, such as gene duplication and diversification, and this I think from hasty browsing is also a main aspect how they track improvement over time.

They find use for information theory, which is rare in biology, as a measure for resilience. Interacting network growth as per above does not contribute Shannon information of broken off networks, but other resilience lowering mutations do. So as their artificial damage with its "damage information" grow, resilience decrease in quantifiable terms. (They don't study network healing, which is the reverse mutational process of evolving connecting enzyme paths by, say, gene duplication and diversification.)

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