An In-Depth Look at Yeast Evolution Suggests Theoretical Models Need Updating

The results of adaptive evolution can be seen throughout the natural world, from zebra stripes to camouflage in moth wings, but the events that lead to adaptations are often impossible to track. A study published on November 13 in Nature* presents a breakthrough. Harvard scientists marked yeast with barcodes and tracked their progeny in an evolution experiment that lasted 1000 generations. While the course that evolution took in this experiment generally agreed with existing theoretical models, certain events in the evolutionary process turned out to be more important than previously thought.

Although all organisms evolve, when it comes to studying evolutionary processes in the lab, single-celled microorganisms are easiest to work with. The authors of this study used yeast, a single-celled model organism that reproduces by budding. In laboratory yeast evolution experiments, the yeast jostle for survival in a test tube. As they grow and reproduce, they accumulate mutations, some of which affect how well they grow. A yeast ancestor and its progeny form a lineage. Over time, some yeast lineages take over while others die out.

DNA Barcoding

To keep track of the evolution going on in test tubes, researchers must be able to keep track of the yeast. This can be challenging from a technical standpoint, given that microbial evolution experiments can involve millions of cells and thousands of generations. In this study, the authors overcame these difficulties by improving upon an existing technique. They used DNA barcoding, in which unique identifying sequences are inserted into an organism’s DNA. The authors designed an updated version of this technique, adding a new barcode sequence into each yeast every 100 generations. After hundreds of generations, each yeast in the experiment contained a series of barcodes, arranged one after the other, in a single location in its DNA.  

The Travelling Wave

This reneweable barcoding technique is powerful. Through it, the yeast lineages could be divided more finely into sublineages. When some yeast got mutations that made them more successful, the increasing numbers of yeast in those sublineages could be tracked by their corresponding series of barcodes. Upon analyzing the data, the authors generally saw what evolutionary theory predicts for such an experiment: some yeast gained beneficial mutations and formed successful sublineages while other yeast lineages died out; however, the average overall fitness of the yeast in the experiment increased with every generation. This phenomenon is known as “the travelling wave” – the idea that fitness (represented by a bell-like curve) travels along an axis in the direction of increasing fitness.

Leapfrogging yeast disrupt the travelling wave.

While their results largely support this model, the authors did notice one surprising thing. Organisms are predicted to gain fitness gradually – the positive effects of beneficial mutations stack onto those of existing beneficial mutations. Sometimes, however, an event called “leapfrogging” can occur. In leapfrogging, a lineage will get a mutation that suddenly makes it much fitter, causing its fitness to “leapfrog” over that of other, previously fitter, lineages. These events weren’t thought to be very important, but in this experiment they happened regularly. A mutation would appear in a lineage, creating a sublineage, and within a few generations, yeast from that sublineage would make up a significant proportion of the test tube’s population. Contrary to what is predicted by the usual travelling wave model, in this experiment, small numbers of mutations had big impacts.

In the future, the renewable barcoding technique can be applied to answer a variety of questions. For example, to test the effects of mutations that are predicted to affect an organism’s ability to adapt. Overall, this experiment shows that there is more to learn about evolutionary processes, and that new technology can help.

Link to paper: “High-resolution lineage tracking reveals travelling wave of adaptation in laboratory yeast” https://www.nature.com/articles/s41586-019-1749-3#Sec9

*In the spirit of declaring conflicts of interest, my partner is the lead author.