Host-pathogen interactions are often viewed as a conflict between two organisms: the pathogen thrives if it can exploit its host, and the host thrives if it can fend off infection. This restricted view, however, overlooks the fact that organisms in nature are exposed to many pathogens simultaneously, which can lead to co-infection by multiple pathogen strains or species within each host [1].
Interactions between co-infecting pathogens can profoundly alter the ability of individual pathogens to invade and exploit a host, with consequences for disease progression and host fitness. For example, we have previously found that pathogen strains lacking key virulence genes proliferate better during mixed infections with more aggressive strains [3]. In general, interactions among pathogens range from antagonistic to beneficial: microbes not only compete for resources but can also mount synergistic strategies to subvert host defenses and better exploit host resources [1,2]. How pathogens maximize their performance during co-infections, and the genes underlying these strategies, is largely unknown.
We are studying co-infections using a genetic model plant species, Arabidopsis thaliana, and one of its most abundant bacterial pathogens, Pseudomonas viridiflava. Recent ecological genomics work has revealed that co-infection is remarkably common in this system: most individual Arabidopsis plants in natural settings harbor multiple virulent P. viridflava strains within their leaves [4]. Our work uses high throughput assays to answer the following questions in this system:
- Do pathogen strains differ in performance depending on which other strains are present during co-infections? Our earliest results suggest this is overwhelmingly the case (Figure 1). We are therefore pursuing the genetic basis of these microbe-microbe interactions.
- What genes, and combinations of alleles, determine co-infection outcomes? This knowledge will help us understand pathogen ecology and evolution. But it also has practical applications: it could improve our ability to model, predict, and prevent disease outbreaks in natural populations.
One of the main advantages of the Arabidopsis-Pseudomonas study system is its amenity to large-scale experiments (Figure 2). Hundreds of plants can quickly be inoculated using pipetting robot, infection outcomes (pathogen abundance) can be monitored by high-throughput DNA sequencing, and new statistical approaches in two-organism genome-wide association mapping [5] are poised to identify combinations of alleles in the pathogens’ genomes with beneficial or deleterious effects on their performance. Although this project focuses on a single plant and pathogen species, we hope to generate conceptual and statistical insights relevant to ecological, evolutionary, and biomedical models of host-enemy interactions.
References
[1] Tollenaere, Charlotte, et al. “Evolutionary and epidemiological implications of multiple infection in plants.” Trends in Plant Science (2016).
[2] Abdullah, Araz S., et al. “Host–multi-pathogen warfare: pathogen interactions in co-infected plants.” Frontiers in Plant Science (2017).
[3] Barrett, Luke G., et al. “Cheating, trade‐offs and the evolution of aggressiveness in a natural pathogen population.” Ecology Letters (2011).
[4] Karasov, Talia L., et al. “Arabidopsis thaliana and Pseudomonas pathogens exhibit stable associations over evolutionary timescales.” Cell Host & Microbe (2018).
[5] Wang, Miaoyan, et al. “Two-way mixed-effects methods for joint association analysis using both host and pathogen genomes.” Proceedings of the National Academy of Sciences (2018).