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Mixotrophy in aquatic protists is pivotal for our understanding of aquatic microbial food web dynamics. This thesis is centered around aquatic unicellular mixotrophs, and comprises three methodological approaches aimed to tackle mixotroph ecology at single-cell resolution: the identification of actively feeding mixotrophs in natural samples, the determination of specific interactions among mixotrophs and bacterial prey, and the profiling of two distinct mixotrophic populations based on the gene expression of their constitutive individuals.

First, we investigated the feasibility of cytometrically sorting actively feeding mixotrophs from a natural community. The approach was based on the use of fluorescently labelled feeding tracers (FLTs) in conjunction with chloroplast autofluorescence from the feeding cell to retrieve mixotrophic individuals for subsequent single cell characterization by sequencing of a taxonomic marker gene. The preference for different FLT types showed that for mixotrophs in culture, FLT size was the strongest factor influencing FLT-based capture. This approach was then used to identify actively feeding mixotrophs from a lake water sample. The method proved to be both highly selective and specific and allowed the identification of an active natural mixotrophic community of unexpected diversity.

Secondly, we explored the potential of adapting emulsion, paired-isolation and concatenation PCR (epicPCR) to uncover physical connections between individual unicellular eukaryotes and their associated bacterial cohort. The results from three proof-of-concept experiments, however, did not conform to the expectations and showcased several deficiencies that need to be addressed. Mainly, the frequency of recovered links showed that the protocol, as deployed in our experiments, was prone to yield spurious abundance-driven associations between the eukaryotes and bacteria, since the most abundant bacteria were the ones driving the strongest associations with our test predators. Nevertheless, we identify possible solutions and point to avenues for future development to overcome the current limitations.

Finally, the capability of full-transcript single-cell RNA sequencing was surveyed to provide a reliable transcriptomic landscape of a non-mammalian, non-model eukaryotic organism with no available reference genome. We could show that, while some of the detailed functional information might remain uncharacterized, the workflow provide sufficient raw data to resolve population structure based on expression profiles.

In summary, with varying degrees of success, these attempts to expose and study mixotrophic unicellular eukaryotes demonstrate that the time is ripe to explore the ecology of mixotrophs at single-cell level.