PS 69-43 - Rapid metabolic evolution in Daphnia magna under predation risk

Friday, August 16, 2019
Exhibit Hall, Kentucky International Convention Center
Chao Zhang1,2, Martin Jones3, Mark Viant3, Mieke Jansen4, Luc De Meester4 and Robby Stoks4, (1)Environmental Research Instititute, Shandong University, Qingdao, China, (2)Environmental Research Insitute, Shandong University, Qingdao, China, (3)Department of Biology, University of Birmingham, Birmingham, United Kingdom, (4)Department of Biology, KU Leuven, Leuven, Belgium
Background/Question/Methods

Predation risk (non-consumptive effects) may have as strong effects as direct killing; it has not received enough attention yet. Predation risk could induce rapid evolution in organismal morphology, life history and physiology, however, the underlying mechanisms are unclear. Metabolomics is a powerful technique to unravel the metabolic pathways on how stressors affect organisms. How predation risk affects the organismal metabolome and whether the metabolomic profiles can evolve remains an open question. Capitalizing on a resurrection study, 18 genotypes were obtained from a natural Daphnia magna population rapidly tracked changes in fish predation (pre-fish, high-fish and reduced-fish). In this study, the metabolomes of these 18 genotypes under fish kairomone and control conditions were investigated using the nESI-DIMS (nano-electrospray ionization direct infusion mass spectrometry). Changes of metabolic profiles were analyzed by different multivariate analysis (principal component analysis, PCA; partial least square discriminant analysis, PLS-DA; and ANOVA-simultaneous component analysis, ASCA) and pathway analyses were conducted using KEGG Mapper and MetaboAnalyst.

Results/Conclusions

PCA and PLS-DA results showed predation risk significantly changed the metabolomes of all the tested D. magna genotypes. Pathway analyses revealed that mainly purine metabolism and sugar metabolism changed (e.g. galactose metabolism, starch and sucrose metabolism, fructose and mannose metabolism), adding valuable insight into the mechanisms of how predation risk affect prey. ASCA model showed the significant differences among the three sub-populations when they were under predation risk, demonstrating the rapid evolution in metabolic profiles. The high-fish subpopulation showed a stronger metabolomic response compared to the pre-fish and reduced-fish subpopulations as evidenced by that the high-fish subpopulation had the highest number of metabolites responsive to fish kairomones. Metabolic pathway analyses showed one carbon pool by folate, folate biosynthesis and glutathione metabolism were specific to different sub-population. In general, our results shed more light on the molecular mechanism of predation risk on prey. Moreover, by measuring the metabolomes of three subpopulations separated in time that belong to one continuous population, this is the first study to directly demonstrate metabolomic evolution in situ within a single natural population.