For many decades, exploring fitness landscapes was primarily the reserve of theoreticians working with simulated organisms, or pioneering experimentalists working on a relatively small scale. But with the rise of easy, inexpensive gene editing technology, the team behind the new paper wondered if they could build a very large adaptive landscape using living organisms, said Andreas Wagner, a professor of biology of the University of Zurich and an author of the new paper.
They decided to plot the fitness effects of a single gene in the bacterium Escherichia coli. Dihydrofolate reductase, the enzyme that this gene encodes, is a target of the antibiotic trimethoprim, and mutations in the gene can make the bacterium resistant to the drug. Wagner and his colleagues, including lead author Andrei Papkou, a postdoc at the University of Zurich, created more than 260,000 genetically distinct strains of E. coli, each of which used a different permutation of nine amino acids in the functional core of its version of the enzyme.
They grew the strains in the presence of trimethoprim and kept track of which ones thrived. The plot of their data revealed a landscape with hundreds of peaks of various heights, representing how well each of the genetic variants (genotypes) enabled the bacteria to evade the drug.
Then the researchers looked at how hard it would be for the different strains to evolve to reach one of the highest peaks. For each genotype, they calculated what series of mutations would be necessary to transform it into one of the highly resistant strains.
As Wright predicted decades ago, some paths ended atop low peaks that left no opportunity for further improvement. But many of the paths — routes by which, one mutation at a time, organisms could change their genotypes — reached fairly high points.
“We got good statistics on how frequently they get stuck on low peaks,” Wagner said. “And it’s not frequently at all. … Seventy-five percent of our populations reach clinically relevant antibiotic resistances.”
That tallies with what Sam Scarpino, a biologist and disease modeler who is the director of AI + Life Sciences at Northeastern University, said he would expect. “They have this very nice result that we’ve predicted,” he said, pointing to a recent theoretical paper exploring the relationship between the ruggedness and navigability of fitness landscapes. When fitness landscapes are high-dimensional — when they go beyond the simple three dimensions of most people’s imaginations to, say, the nine dimensions used in Wagner’s study — very different networks of regulatory genes that produce the same physical traits are more likely to be close together on a landscape or to be connected by an accessible pathway.