Opinion
Measurably evolving pathogens in the genomic era

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Highlights

  • Pathogens are measurably evolving if new mutational changes are detectable between genetic samples taken at different times.

  • Whole-genome sequencing has massively increased the range of measurably evolving pathogens.

  • In the future we expect novel and important insights into pathogen population dynamics to come from genomic data.

  • Considerable analytical challenges will need to be overcome to fully realize this potential.

Current sequencing technologies have created unprecedented opportunities for studying microbial populations. For pathogens with comparatively low per-site mutation rates, such as DNA viruses and bacteria, whole-genome sequencing can reveal the accumulation of novel genetic variation between population samples taken at different times. The concept of ‘measurably evolving populations’ and related analytical approaches have provided powerful insights for fast-evolving RNA viruses, but their application to other pathogens is still in its infancy. We argue that previous distinctions between slow- and fast-evolving pathogens become blurred once evolution is assessed at a genome-wide scale, and we highlight important analytical challenges to be overcome to infer pathogen population dynamics from genomic data.

Section snippets

A changing landscape for studying pathogen evolution

Over a decade ago Drummond et al. [1] introduced the idea of ‘measurably evolving populations’. These populations exhibit detectable amounts of de novo evolutionary change among genetic sequences sampled at different timepoints. This concept, and the analytical methodology it has spawned, has revolutionized our ability to study population dynamic processes using genetic sequence data (Box 1). Until recently, RNA viruses were the primary target of such approaches owing to their high per-site

Measuring evolution on epidemiological time-scales

Genomic data from populations sampled through time are being generated for an increasing range of pathogens. As a consequence, estimates of evolutionary rates (nucleotide or amino acid substitutions per site or codon per year) are becoming available for many of these pathogens for the first time. A comparison of genome-wide evolutionary rates (as opposed to per-site rates), estimated from pathogens sampled over at least one decade, confirms that the dichotomy between ‘fast-evolving’ and

Time-dependency of evolutionary rates and its consequences

The power to detect measurable evolution grows as sequences are sampled further apart in time [1]. However, the length of the time-interval over which sequences are sampled can also affect the apparent rate of genetic change estimated from the data, with longer timescales yielding lower evolutionary rate estimates (Figure 3). The causes of this decline in the apparent rate of molecular evolution are not fully understood, but might include changes in selective constraint, nucleotide saturation

Biological complexities

Extending the concept of a measurably evolving population from RNA viruses to DNA viruses and bacteria requires taking into account several biological processes and patterns that are absent or rare in RNA viruses, and for which current analytical tools are insufficient. We highlight three key examples of such complexities that will require theoretical and methodological advances over the coming years.

Concluding remarks

Whole-genome sequencing promises to identify most, or even all, microbial pathogens as measurably evolving. There is thus a crucial need for increased scientific dialogue among evolutionary biologists, epidemiological modelers, and microbiologists, with a shared aim of developing methods that can accommodate the specific biological complexities inherent in many bacterial and virus systems. Box 4 summarizes some of the outstanding research questions that, in our view, warrant particular

Acknowledgments

This paper benefited from the discussions during a workshop at the University of Glasgow in 2013, funded by the RAPIDD program of the Science and Technology Directorate of the US Department of Homeland Security and National Institutes of Health (NIH) Fogarty International Center. We would like to thank the workshop participants for the contributions made during the workshop. We also thank Allen Rodrigo and one anonymous reviewer for their constructive comments on an earlier version of this

Glossary

DNA viruses
viruses that encode their genetic material as DNA. Double-stranded (ds)DNA viruses use host enzymes to replicate their genomes. Owing to the proof-reading activity in these replicases, mutational changes per replication event tend to be rare. By contrast, single-stranded (ss)DNA viruses can evolve at higher rates similar to those seen for RNA viruses.
Evolutionary rate
the estimated rate at which nucleotide changes (per site or per genome) are observed within a population sampled over

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