Understanding coevolution across time – Fellows’ seminar by Dieter Ebert

12 August 2024

What can water fleas tell us about evolution? Is evolution linear or cyclical? And, how does evolution impact on areas like medicine, sustainable agriculture, pest control, and animal and plant breeding? These are some of the questions that Dieter Ebert of the Department of Environmental Sciences at the University of Basel studies and discussed in his STIAS seminar.

“The world is a dangerous place with antagonists everywhere – it’s been like this for a very long time. We can date predators and parasites in fossils from about 500 million years ago and, of course, T. rex from 100 million years ago. But the evolution of biological conflicts started most likely as early as four billion years ago,” he said.

“Parasites (including pathogens) are ubiquitous in our world and there is no organism that is not threatened by infection,” he continued. “Our enemies constantly evolve to maximise ways to exploit us, causing harm and suffering. But victims also evolve to become better at avoiding or defending themselves against antagonists and minimising the damage (fitness reduction) they cause. Therefore, the hosts and their parasites/pathogens are expected to coevolve.”

STIAS Fellow Dieter Ebert

Ebert explained that in this war the parasite is the offender and the host the defender. The parasite must know how to get into the host, which involves high specificity—like a key needing to fit into a lock. Even if all the locks are the same, the criminal with the wrong key still can’t enter. So, this will select for criminals with a different key that will fit the lock.

“This antagonism may cause the host and the pathogen to engage in endless coevolution. I am interested in understanding this coevolutionary process and how it compares to other forms of evolution, in particular the canonical Darwinian adaptive evolution.”

Ebert explained further that there are two models how coevolution works. The canonical view is that the host adapts via mutations to improve their situation and that these adaptations replace each other. “It’s about selection to become better. The old loses its value and the new replaces the old.” He likened it to an arms race in which there is no diversity in the arsenal only the best weapon remains – “mutations replace wild types with a better option.”

“The alternate view is that no single strategy wins. There is selection for being different and it is better to change often—so it’s not necessarily the best but a different strategy.”

In this model, a host–pathogen interaction matrix is assumed where specific combinations of host and parasite genotypes result in infection, other combinations leave the host uninfected. Here the benefit for the host comes from being different. A different type of lock will block the parasite. But after many generations, an old lock may be useful again, because parasites with the right key do not exist anymore. Thus, focusing on only one strategy would be a disadvantage for both host and pathogen. Instead, diversity is beneficial and evolution may proceed in a more cyclical rather than linear pattern.

This so-called Red Queen model of coevolution dates from the 1970s and gets its name from Lewis Carroll’s Through the Looking Glass in which the Red Queen tells Alice, “It takes all the running you can do to stay in the same place.”

“The evolutionary Red Queen model is unusual in that it goes in cycles,” added Ebert.

“It’s about maintaining genetic diversity over time. The host has to evolve/change constantly to keep pace with the antagonist and to survive. If you stop moving, the environment deteriorates,” he said.

In support of this, greater genetic diversity has been shown in plants and animals to be linked to greater resistance to disease-causing pathogens.

But the models of coevolution are not totally incompatible. “Linear and cyclical evolution are incompatible if you talk about the same gene—it can’t do both,” explained Ebert. “But different parts of the genome can evolve independently. Some parts may evolve linearly and some parts cyclically.” For example, some traits in humans and chimps can be explained with a linear model, while others are better explained with cyclical evolution.

Ebert and his colleagues are specifically trying to understand the Red Queen concept across time and are also interested in looking at the influence of local adaptation. With advances in technology, it’s possible to study the process and not just patterns, and, in so doing, add to the evidence base – “starting from the ‘now’ and going back many million years”.

Enter the water fleas

Their work uses a small planktonic crustacean, Daphnia (water fleas), that is a highly suitable model organism in biology. Daphnia can reproduce asexually producing eggs that are genetic clones of the mother, but can also be crosses through a sexual process. Daphnia also suffer from infections by diverse parasites, among them a highly virulent bacterium, Pasteuria ramosa.

Using sediment core samplers which allow the collection of cylindrical sections of underwater sediment, Ebert’s team have collected Daphnia and their parasites from up to 30 years ago. This makes it possible to infect contemporary Daphnia with parasites from different periods recreating how evolution changed relative to antagonists and how both host and parasite changed over time.

Ebert also explained that when the last Ice Age ended just over 10 000 years ago, Daphnia spread from the Middle East all over Europe including the most Northern Norway. They are currently found everywhere on the Northern Hemisphere north of the Sahara, with one exception – a population identified near Stellenbosch in 1891 which he, naturally, will investigate in more detail during his STIAS fellowship.

Work on samples from different areas thus far has found no correlation between their ability to resist infection and geography. “This was a big surprise,” said Ebert. “There was uniform distribution of both resistant and susceptible populations. We also looked for different traits – such as body length, length of the tail spine and tolerance to water salinity, and found that populations adapt to their respective habitats, producing a fine scale geographic picture. But not so in response to parasites.”

Ebert will take this work further in his STIAS project exploring local adaptation across a data set of more than 200 populations of Daphnia. The data include phenotypic traits, local habitat variables, geographic coordinates and genomic sequences. The project will investigate the phenotypic and genomic levels to understand how local adaptation evolves in complex environments. The aim is to bring local evolution and co-dependency into one framework.

“Our results and evidence thus far support predictions derived from the theoretical models of coevolution,” he said. “Understanding coevolution has important implications for understanding the evolutionary history of humans (as well as other organisms), but also for shaping the future of areas like sustainable agriculture, pest control and personalised medicine.”

In a wide-ranging discussion, he spoke about the vaccine and drug challenges of certain viruses and parasites. “In diseases like AIDS the virus evolves very fast—this means vaccines don’t work because the pathogen overcomes them.  In HIV infections, the virus can evolve drug resistance within about three months which is why drug cocktails are used. Likewise, for Malaria there are no good solutions yet, as the parasite evolves very fast to our means to control them.”

“Also in insects we see fast evolution. For example, mosquitos produce mutations constantly, so the possibility of evolving resistance against pesticides is very high.”

“Evolution is always conservative—it works with what is there now. There are no major innovations to be expected, rather there is a gradual change by recombining what you have now with occasional mutations adding more variation.”

How much can evolutionary concepts explain other phenomena? “Science tries to explain phenomena but our descriptions never explain 100% of what is out there,” answered Ebert. “Typically, we can only explain a certain proportion of a phenomenon. What is left is a grey zone, the parts that we don’t know (yet) or the noise in the data.”

Michelle Galloway: Part-time media officer at STIAS
Photograph: Ignus Dreyer

 

 

 

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