Carl Trygger Postdoctoral Scholarship

Position details
Essential criteria
Desired criteria
Project background
Objectives
Methodology
Outcomes
How to apply

Position details:

A 2 year scholarship is available to study evolution in crop pests under variable versus stable selection pressures (see project description below). The scholarship pays 300 000 SEK per year to the recipient, but does not provide any additional social benefits. This normally means that only applicants with a pre-existing right to live and work in Sweden can be considered.

Quoting from the Carl Trygger Foundation:

The scholarship is intended to pay for the education of the postdoctoral fellow, and it is not compensation for work performed. The scholarship is, therefore, not subject to taxation. The scholarship is to be regarded as a gift from the Carl Trygger Foundation, and the Foundation thus has no employer responsibility. The scholarship cannot be combined with a teaching commitment and may not, without the Foundation’s consent, be combined with a scholarship from another financier.

Applicants should be within 6 years of receiving their doctorate at the time the scholarship begins, and cannot already be employed in the host department (Biology and Environmental Sciences at the University of Gothenburg). As a condition of the funder, this project must begin before the end of 2021.

Essential criteria

  • PhD in a relevant scientific discipline such as evolutionary biology, quantitative genetics, experimental evolution or biocontrol or sustainable agriculture, or a related discipline.
  • Be within 6 years of having completed their PhD at the time of appointment.
  • Candidates may not already be members of the host department, Biological and Environmental Sciences at the University of Gothenburg.
  • Be able to begin the scholarship before the end of 2021.
  • Have excellent organisational and data management skills that allow the coordination of large laboratory experiments including thousands of subjects.
  • Have strong quantitative skills and/or interests, preferably including experience with coding mixed models in R, in order to implement advanced statistical models needed to estimate genetic variance and covariance parameters.
  • Good communication skills in both written and spoken English are necessary since we work in an international environment.

Desired criteria

  • A strong record of achievement in publishing scientific research
  • A demonstrable ability to coordinate and integrate with a large team of researchers.
  • Experience with laboratory sterile microbiological techniques and applied biological control
  • An ability to work flexible hours to coordinate research during labour-intensive experiments.

Project background.

The UN Food and Agriculture Organisation estimates that by 2050, in order to satisfy demand we will need to produce 70% more food1. Ideally, this increase in production should not use any more land, lest we cause further degradations of natural habitat. As a consequence, there is an urgent need to increase food production efficiency. With as much as 35% of global crop production lost prior to harvest2, effective crop protection will play a key role in our efforts to enhance food security. Unfortunately, insect herbivores have proven incredibly efficient at overcoming our best efforts to defend crops, evolving pesticide resistance with predictable regularity3,4.

The situation is particularly acute in some developing countries that are experiencing the most agricultural intensification. For example, Brazil’s agricultural economy is immensely productive, but the extensive scale of cultivation and widespread deployment of single insect control measures has created serious problems for resistance management. Few originally effective insecticides remain so over time, as target pests almost inevitably evolve resistance. In response to reduced effectiveness, farmers apply higher concentrations of ineffective chemical agents, which can have devastating consequences for beneficial arthropods5,6, while at the same time hastening the fixation of prevalent resistance alleles. This conflict between food security and healthy environments is likely to worsen as populations grow and agricultural intensification continues. There is therefore an urgent need for new pesticide resistance management approaches that minimise disruptions to natural environments while sustainably safeguarding the ability to protect crops.

Because insecticide resistance is a form of evolutionary change, insecticide resistance management has historically involved trying to weaken selection (e.g. through varying the presence and nature of pesticides) and preserve susceptible genotypes in pest populations (e.g. by providing refuges where susceptible pests can thrive7,8). To sustain genetic variation in populations, insecticide researchers have sought groups of pesticides that exhibit “negatively correlated cross-resistance” (hereafter NCC-R), in which the ability to resist one pesticide trades-off with the ability to resist another9. In the presence of NCC-R, one could theoretically halt resistance evolution and rescue susceptible alleles for one pesticide, by exposing the pest population to a different pesticide, against which the initial resistance alleles had comparatively low fitness.

Alas, while these negative correlations in performance have long been sought for groups of synthetic pesticides, the ability of trade-offs to prevent resistance evolution has not been realised10. One reason is that costs of resistance tend to be context-dependent11,12. Furthermore, even if two pesticides confer NCC-R, the genetic covariances that produce trade-offs can themselves evolve over time, and lead to positive cross-resistance (in which insects resistant to one pesticide are also resistant to others)13.

Not all strong selection leads to directional evolution. There is reason for hope: nature provides many examples of strongly antagonistic interactions that do not drive rapid evolutionary change. There are many traits, including pathogen defence traits14, where substantial genetic variation is maintained despite strong selection. Trade-offs are an important contributor to this variation15,16, but their power may only be realised in variable environments17, which contrast strongly with agricultural monocultures. The role of environmental heterogeneity in promoting diversity has long been recognised18 and arises because the greater the difference between two habitats, the more likely it is that alleles promoting performance in one habitat negatively affect performance in the second.

A promising new approach to sustainable pest control. We have recently developed a revolutionary alternative approach to sustainable pest management that attempts to harness rather than resist evolution in the fight against insect pests. We exploit the fact that biocontrol agents present complex and diverse challenges to insect pests, and that some insects feed on multiple crops, to achieve enhanced agricultural landscape diversity. By overlaying diversity in crop and fungal biopesticide strain, it should be possible forestall directional evolution for resistance in the long term. Using Helicoverpa armigera (Fig 1 inset), a polyphagous noctuid moth that is an invasive and destructive global pest32,33, we have already revealed that diverse strains of two fungal genera that attack insects (Beauveria and Metarhizium) can kill this important pest (see Fig. 1).

Screenshot 2021-06-04 at 15.53.21

Three essential features required for our approach emerge clearly from these analyses. First, we demonstrate substantial variation among sire families, associated with significant heritabilities, indicating that resistance to fungi could evolve in this species if biopesticide use is not carefully managed. Second, we demonstrate strong strain specificity, which means that pest genotypes differ in their susceptibility to the fungi, and that the rank order of susceptibility depends sharply on fungal pathogen strain. In other words, the best genotypes for resisting these pathogenic fungi depend very much on the strain being applied. Finally, we have demonstrated that the context specificity of genotypes can be further enhanced by overlaying crop heterogeneity on top of fungal strain heterogeneity: the best genotypes for resisting a fungus depend not only on the strain of fungus, but on the precise combination of host crop plant and fungus. This can be formally demonstrated by quantifying cross-environment genetic correlations, which measure the extent to which genes for performance in one situation also encode high performance in another. By adding host plant heterogeneity to fungal pathogen heterogeneity, we are able to depress genetic correlations below zero; it is precisely those negative genetic correlations that exemplify trade-offs in performance across habitats and could make pest control sustainable in the long term.

However, while these results are tremendously exciting, we still do not know how stable these genetic correlations are over time. The genetic architecture of resistance traits is known to evolve34, and it may do so differently depending on heterogeneous environments35. For example, recombination between host genotypes resistant to different fungal strains could lead to cross-resistance to multiple biopesticides (i.e., the genetic correlations could become progressively less negative under selection). Therefore, the enormous evolutionary potential of insect pests justifies research on our system’s long-term sustainability, which is the subject of this proposal.

Objectives

This research has three main objectives, each of which should lead to a publication in a high-impact journal:

  • To quantify responses to consistent selection, and thereby assess the potential for intensive use of fungal biopesticides to engender resistance;
  • To assess whether fluctuations in selection caused by heterogeneity disrupt any directional evolution observed under consistent selection; and
  • To quantify changes in the genetic variance-covariance matrix over time under constant versus variable selection regimes, which will indicate the long-term sustainability of our approach to pesticide resistance management.

In addition, as a legacy of this project, the lines produced in the course of this work can be used in future projects to reveal phenotypic and genomic consequences of consistent and fluctuating selection, which will provide many avenues for future fundamental and applied research on environmental mediators of host pathogen coevolution.

Methodology

The successful candidate will conduct laboratory selection experiments to determine if applying a single fungal biopesticide leads to rapid pest resistance evolution, then assess whether this selective response is slowed or halted under a heterogeneous selection regime. More crucially, we will test whether genetic associations between resistance traits remain stable (indicating long-term sustainability) or whether recombination can easily generate lineages that are resistant to multiple biopesticide strains on multiple crops. We will start with a single outbred population, and divide its offspring into 12 replicate lines, split evenly into 3 contrasting selection regimes: a control reared on soya without fungal biopesticides; a “single biopesticide” regime reared on soya and exposed to a single Beauveria fungal isolate every generation; and a “variable biopesticide and crop” regime, in which each generation of larvae will be split across all possible combinations of soya and maize crop with either Beauveria and Metarhizium fungus (see Fig 2).

Screenshot 2021-06-04 at 15.56.11

After 6 and again after 12 generations of selection, we will rear a generation of moths on artificial diet without biopesticides to relax selection and minimise maternal effects, then perform a quantitative genetic experiment to assess how selection regime changes the genetic variance-covariance matrix (the G-matrix). Within each line, we will assay the survival ability of progeny in each of five environmental combinations: soya with no biopesticide, soya with Beauveria, soya with Metarhizium, maize with Beauveria, and maize with Metarhizium.

This experiment will quantify the response to selection under a variable selection landscape in comparison with a consistent landscape. We will further assess whether variable selection is less likely to change the genetic associations that make resistance evolution difficult (by measuring the angle between the major axes of genetic variation, gmax, in each line before and after selection36). Finally, we will directly compute and compare the unconditional evolvability in each treatment37, which provide standardised measures of evolutionary constraint across systems.

Outcomes

In addition to the anticipated three high-impact publications, the generation of these evolution lines will provide invaluable potential for further study in future projects. For example, we will archive genetic material before evolution and at every generation to permit follow-up work that traces genomic evolution under fluctuating versus consistent environments. Such studies may provide evidence for reversals in selection through time, and genomic signatures of selection could conceivably help trace nascent evolution of fungal biopesticide resistance in the field. If our findings continue to be as promising as they have been to date, we also anticipate future industrial partnerships to bring our approach to pest control to market in both developed and developing countries, for the betterment of farmers, food security, and wild arthropods worldwide.

References

1 FAO. The future of food and agriculture – trends and challenges. (2017);
2 Oerke, E.-C. et al. Crop Prot 23, 275–285 (2004);
3 Tabashnik, B. E. et al. J Econ Entomol 107, 496–507 (2014);
4 Bradshaw, C. J. et al. Nat Commun 7, 12986 (2016);
5 Hallmann, C. A. et al. PLoS One 12, e0185809 (2017);
6 Nicolopoulou-Stamati, P. et al. Front Publ Heal 4, (2016);
7 Tabashnik, B. E. et al. J Evol Biol 17, 904–912 (2004);
8 Carroll, S. P. et al. Science (80- ) 346, 1245993 (2014);
9 Chapman, R. B. et al. Nature 281, 298–299 (1979);
10 Tabashnik, B. E. J Econ Entomol 82, 1263–1269 (1989);
11 Blanford, S. et al. Ecol Lett 6, 2–5 (2003);
12 Jensen, K. et al. Sci Rep 6, 28731 (2016);
13 Szybalski, W. et al. J Bacteriol 64, 489–499 (1952);
14 Hall, A. R. et al. Ecol Lett 14, 635–642 (2011);
15 Melnyk, A. H. et al. Evol. Appl. 8, 273–283 (2015);
16 Johnston, S. E. et al. Nature 502, 93–95 (2013);
17 Reznick, D. et al. Trends Ecol Evol 15, 421–425 (2000);
18 Haldane, J. B. S. et al. Heredity (Edinb) 58, 237–242 (1963);
19 Decaestecker, E. et al. Evolution (N Y) 57, 784–792 (2003);
20 Lambrechts, L. et al. Malar J 4, 3 (2005);
21 Bürger, R. et al. Genet Res 80, 31–46 (2002);
22 Boots, M. Am Nat 178, 214–220 (2011);
23 Cory, J. S. et al. Evol. Appl. 5, 455–469 (2012);
24 Raymond, B. et al. Proc R Soc B 272, 1519–1524 (2005);
25 Raymond, B. E. N. et al. J Appl Ecol 44, 768–780 (2007);
26 Owusu, H. F. et al. Sci Rep 7, (2017);
27 Mascarin, G. M. et al. J Invertebr Pathol 165, 46–53 (2019);
28 Read, A. F. et al. Plos Biol 7, e1000058 (2009);
29 Asser-Kaiser, S. et al. Science (80- ) 317, 1916–1918 (2007);
30 Zichová, T. et al. BioControl 58, 525–534 (2013);
31 Schmitt, A. et al. J Appl Entomol 137, 641–649 (2013);
32 Sosa-Gómez, D. R. et al. Rev Bras Entomol 60, 101–104 (2016);
33 Tay, W. T. et al. PLoS One 8, e80134 (2013);
34 Arnold, S. J. et al. Evolution (N Y) 62, 2451–2461 (2008);
35 Björklund, M. et al. Evolution (N Y) 69, 1953–1958 (2015);
36 Blows, M. W. et al. Am Nat 163, 329–340 (2004);
37 Hansen, T. F. et al. J Evol Biol 21, 1201–1219 (2008)

How to apply

Interested candidates should submit a cover letter/statement of motivation, an up-to-date CV, and the names and contact details of at least 3 referees who can comment on the candidate’s research and scholarship to PI Luc Bussière (luc.bussiere (at) bioenv.gu.se). We will retain all applications until the position is filled, and reach out to promising candidates for video conference interviews in the first instance. Informal enquiries are always welcome; please contact the PI at the email above with any questions.

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