Hayden contributes to international team studying origins of life

Biological Sciences Professor and Chair Eric Hayden participated on an international research team that recently published exciting findings in the journal Nature Communications. The research tackled one of the most difficult challenges in science, namely how did genetically replicating life that we see on Earth first start.

Currently, living organisms pass on the traits that help them survive to their offspring by replicating their genes and giving a copy to their offspring. To accomplish this, modern life forms have a complex interdependence of three major biological macromolecules, DNA, RNA and protein. Genes are made of DNA, use RNA to make proteins, and the proteins copy the genes. Numerous lines of evidence suggest that RNA could have taken on the roles that DNA and protein currently play, creating a much simpler "RNA World" that circumvents the need for three different types of complex molecules to emerge simultaneously. However, despite decades of research, the ability of RNA to copy itself has not been demonstrated.

Recently, the scientific community has called upon groups of scientists with different expertise to come together to tackle big challenges. In this spirit, a collaborative team was assembled to address this RNA World challenge.

Hayden provided expertise in RNA biochemistry and laboratory approaches. Philippe Nghe from ESCPI Paris, France provided expertise in biophysics and experimental evolution. Matteo Smerlak from Max Plank institute in Leipzig, Germany (and also ESPCI Paris) brought a background in applying theoretical physics to evolution. Arati Ramesh from the National Center for Biological Sciences in Bangalore, India, provided expertise in bioinformatics in RNA research. Martin Weigt from the Sorbonne University in Paris was included for his expertise in applying machine learning to protein engineering, with a plan to transfer this approach to RNA research. Francesco Zamponi from Sapienza Università in Rome, Italy, brought in theoretical physics expertise, with experience applying theory and methods of disordered systems to biological contexts, including how genetic sequence changes lead to evolutionary dynamics.

This team came up with an initial research plan, and recruited an exciting team of Ph.D. students and postdoctoral researchers who actually carried out the work over several years. Camille N. Lambert, Vaitea Opuu and Francesco Calvanese lead the execution of experiments and data analysis at the ESPCI in Paris, with very important contribution from Polina Pavlinova.

What this team produced was a new way to search for self-replicating RNA molecules. The approach involved cycles of machine learning and high-throughput experiments. The machine learning approach allowed extremely efficient experimental design, eliminating the need to study numerous RNA molecules that were unlikely to be informative. The data produced from high throughput experiments was more informative, and was able to feed back into the machine learning to make it even more accurate. In the end, the team found that there are an extraordinary number of RNA molecules (estimated to be more than 1039) that can carry out a simple form of copying themselves. The team proposed that this abundant amount of potential RNA replicators could form cooperative networks that jump start a form of evolution that could then lead to RNA that replicate and evolve similar to our current DNA genes. Many questions remain, and the team looks forward to future collaborations together.

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