This project aims to understand how pathogens affect the toxicity of cyanobacterial blooms.
Advisors: Dedmer van de Waal, Prof. Jef Huisman, Bettina Scholz
Location: DC2 will perform the research at NIOO-KNAW in Wageningen, The Netherlands, and will graduate with a PhD degree at the University of Amsterdam.
How to apply for this position
The submission deadline for this project was May 15th, 2024 and we are not accepting any more applications at this time.
Objectives:
Cyanobacterial blooms are primarily driven by eutrophication, and enhanced by climate change. The toxicity of blooms depends on various ecological scales, from cellular toxic quota, to population and community structure. The overarching aim of this project is to understand how pathogens impact the toxicity by targeting different cyanobacterial species and toxic or non-toxic genotypes.
Specific aims include:
1) Identify and monitor the dynamics of pathogens infecting harmful cyanobacteria at recreational sites and drinking water reservoirs facilities using metabarcoding and flow-cytometry.
2) Isolate and culture pathogens infecting various cyanobacterial genotypes and species using flow-cytometry sorting.
3) Determine how pathogens affect cyanobacterial population dynamics using state of the art chemostats.
4) Assess the impacts of environmental factors that drive pathogen infection of cyanobacterial populations and communities using mesocosm systems.
Expected Results:
1) Freshwater harmful cyanobacteria and pathogen community profiles.
2) Isolates of pathogens for freshwater harmful cyanobacteria.
3) Defined key drivers that stimulate infection of harmful cyanobacteria.
4) Understand the role of pathogens in determining harmful cyanobacteria growth, population and community dynamics, and bloom toxicity.
Planned secondment(s):
At Water Insight with Steef Peters to learn interpretation of Earth Observation data to detect harmful cyanobacterial blooms
At FVB-IGB with Justyna Wolinska to perform experimental evolution assays
At UNIABDN with Pieter van West to analyse metabarcoding samples