Symptom evolution following the emergence of maize streak virus
- Norwegian Veterinary Institute, Norway
- Université Libre de Bruxelles, Belgium
- University of Cape Town, South Africa
- Makerere University, Uganda
- Swedish University of Agricultural Sciences, Sweden
- CIRAD, Réunion
- University of Montpellier, Centre National de la Recherche Scientifique (CNRS), France
- KU Leuven - University of Leuven, Belgium
- University of the Western Cape, South Africa
- University of California, Los Angeles, United States
- Arizona State University, United States
Abstract
For pathogens infecting single host species evolutionary trade-offs have previously been demonstrated between pathogen-induced mortality rates and transmission rates. It remains unclear, however, how such trade-offs impact sub-lethal pathogen-inflicted damage, and whether these trade-offs even occur in broad host-range pathogens. Here, we examine changes over the past 110 years in symptoms induced in maize by the broad host-range pathogen, maize streak virus (MSV). Specifically, we use the quantified symptom intensities of cloned MSV isolates in differentially resistant maize genotypes to phylogenetically infer ancestral symptom intensities and check for phylogenetic signal associated with these symptom intensities. We show that whereas symptoms reflecting harm to the host have remained constant or decreased, there has been an increase in how extensively MSV colonizes the cells upon which transmission vectors feed. This demonstrates an evolutionary trade-off between amounts of pathogen-inflicted harm and how effectively viruses position themselves within plants to enable onward transmission.
Data availability
All data and R code used for analyses in this study are available on the following public repository:https://github.com/sdellicour/msv_symptom_evolution
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Data From: Symptom evolution following the emergence of maize streak virusGitHub, msv_symptom_evolution.
Article and author information
Author details
Funding
Swedish Institute (00448/2014)
- Adérito L Monjane
European Union (PIOF-GA-2013-622571)
- Philippe Roumagnac
European Research Council (725422-ReservoirDOCS)
- Philippe Lemey
Fonds Wetenschappelijk Onderzoek (G066215N)
- Philippe Lemey
Fonds Wetenschappelijk Onderzoek (G0D5117N)
- Philippe Lemey
Fonds Wetenschappelijk Onderzoek (G0B9317N)
- Philippe Lemey
Fonds De La Recherche Scientifique - FNRS (-)
- Simon Dellicour
Fonds Wetenschappelijk Onderzoek (-)
- Simon Dellicour
South African National Research Foundation (-)
- Kehinde A Oyeniran
The World Academy of Sciences (-)
- Kehinde A Oyeniran
European Union: European Regional Development Found (-)
- Pierre Lefeuvre
Conseil Regional de la Reunion (-)
- Pierre Lefeuvre
Centre de Coopération Internationale en Recherche Agronomique pour le Développement (-)
- Pierre Lefeuvre
South African National Research Foundation (TTK1207122745)
- Gordon W Harkins
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2020, Monjane et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Symptom evolution following the emergence of maize streak virus
eLife 9:e51984.
https://doi.org/10.7554/eLife.51984
Further reading
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- Computational and Systems Biology
- Evolutionary Biology
There is growing interest in designing multidrug therapies that leverage tradeoffs to combat resistance. Tradeoffs are common in evolution and occur when, for example, resistance to one drug results in sensitivity to another. Major questions remain about the extent to which tradeoffs are reliable, specifically, whether the mutants that provide resistance to a given drug all suffer similar tradeoffs. This question is difficult because the drug-resistant mutants observed in the clinic, and even those evolved in controlled laboratory settings, are often biased towards those that provide large fitness benefits. Thus, the mutations (and mechanisms) that provide drug resistance may be more diverse than current data suggests. Here, we perform evolution experiments utilizing lineage-tracking to capture a fuller spectrum of mutations that give yeast cells a fitness advantage in fluconazole, a common antifungal drug. We then quantify fitness tradeoffs for each of 774 evolved mutants across 12 environments, finding these mutants group into classes with characteristically different tradeoffs. Their unique tradeoffs may imply that each group of mutants affects fitness through different underlying mechanisms. Some of the groupings we find are surprising. For example, we find some mutants that resist single drugs do not resist their combination, while others do. And some mutants to the same gene have different tradeoffs than others. These findings, on one hand, demonstrate the difficulty in relying on consistent or intuitive tradeoffs when designing multidrug treatments. On the other hand, by demonstrating that hundreds of adaptive mutations can be reduced to a few groups with characteristic tradeoffs, our findings may yet empower multidrug strategies that leverage tradeoffs to combat resistance. More generally speaking, by grouping mutants that likely affect fitness through similar underlying mechanisms, our work guides efforts to map the phenotypic effects of mutation.
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- Evolutionary Biology
- Microbiology and Infectious Disease
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