Mathematically modeled “landscapes” that describe the relative fitness of various mutations can in theory be used to project how SARS-CoV-2 and other viruses could evolve in the future.

Researchers around the world are trying to understand the virus’s evolution in more detail, and particularly how mutations in SARS-CoV-2 alter its ability to spread among humans.

Predicting exactly what the virus may do next may never be possible, but virologists around the world have been gaining insights into which components of SARS-CoV-2 are most prone to evolve and which key protein elements can’t change without tanking its survival.

Scientists have been able to make these discoveries by revisiting a concept proposed almost a century ago — fitness (or adaptive) landscapes — with modern technologies.

To Tobias Warnecke, a molecular evolutionary biologist at Imperial College London, fitness landscapes are an invaluable way to connect genotype to phenotype.

The value of fitness landscapes isn’t limited to comparisons between small numbers of changes in genomes or proteins.

The process can reveal unforeseen interactions between mutations that can help or hurt a virus — and it can identify paths for the future evolution of a virus that might pose new threats to humans.

What results is a landscape with a unique topography, explains Adam Lauring, an evolutionary biologist at the University of Michigan Medical School.

One complication is that a fitness landscape, whether for SARS-CoV-2 or a human, isn’t static.

Consequently, for decades fitness landscapes were conceptual aids rather than tools for concrete measurements.

With his colleagues, Daniel Weinreich, an evolutionary biology postdoctoral fellow at Harvard University at the time who now heads a laboratory at Brown University, noted that the evolution of the gene could potentially follow 120 paths to accumulate all five mutations.

But predicting the future evolutionary trajectory of even the smallest virus or protein requires a detailed knowledge of its fitness landscape, which is hard to obtain.

Historically, scientists had to create mutations one nucleotide or amino acid at a time, then purify the mutant protein and assess its function.

Researchers found that very few of the mutations in those swarms get passed on to new hosts, particularly when only a small amount of virus is required to cause an infection.

The researchers Tyler Starr (left) and Jesse Bloom of the Fred Hutchinson Cancer Research Center have studied a crucial domain of the SARS-CoV-2 spike protein to find out which parts of it tend to draw the attention of the immune system.

As SARS-CoV-2 began its global spread, Starr and Bloom realized that fitness landscapes provided a useful way to begin studying the novel pathogen.

Bloom and Starr knew that the spike protein would be the part of the coronavirus under the most intense evolutionary pressure because it is what the immune system recognizes most strongly and what the virus uses to break into the body’s cells.

With 1,273 amino acids, however, the spike protein is too sizable for rapid evaluation by a fitness landscape.

Starr therefore decided to focus on a subsection of the spike protein known as the receptor binding domain, which is just a few hundred amino acids — a much more tractable problem.

Starr used deep mutational scanning to create 4,000 different mutations of the receptor binding domain.

If SARS-CoV-2 couldn’t tolerate much variation in its receptor binding domain, Starr expected to see that the immune recognition or ACE2-binding functions would be severely compromised by mutations.

A model of the receptor domain of a SARS-CoV-2 spike protein (at bottom) binding to a cellular receptor, the interaction that allows the virus to enter cells.

“The receptor binding domain had a lot of different mutations that actually improved binding affinity,” Starr said.

While the receptor binding domain tolerated more variation than expected, not all parts of the spike protein did.

These parts of the spike protein may therefore be good targets for new vaccines and monoclonal antibodies, Starr says, since they are less likely to mutate over time.

Starr, Bloom and colleagues also created a map of all the possible mutations to the receptor binding domain that didn’t interfere with ACE2 binding.

Moreover, as Starr, Bloom and their colleagues described last summer in Nature Communications, several widespread mutations can each help SARS-CoV-2 evade some of the antibodies that the immune system typically directs against the most targeted parts of the receptor binding domain