Publikation: Analysis of dynamics and interactions within planktonic microbial communities in Lake Constance by Next-Generation Sequencing
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The advent of Next-Generation Sequencing (NGS) is helping to reveal much of the vast, yet hidden biodiversity of microbial communities in various habitats on Earth. Using DNA extracted from environmental samples, researchers now have access to phylogenetic and functional information, and thus to composition, dynamics and abiotic and biotic interactions of the microorganisms that make up these communities. The amount of information accumulated is enormous and allows worldwide comparisons. However, the accurate and optimal processing of such large NGS datasets is still an intensive field in development. Throughout this thesis, DNA sampling and NGS has been established and applied to the description of the microbial plankton community of the epilimnion of Lake Constance, while pushing scientific boundaries to optimise processing and accurately analysing these datasets. Planktothrix rubescens, a red-pigmented toxin-producing cyanobacterial species has regularly formed blooms in Alpine and pre-Alpine lakes. Lake Constance, however, has remained largely unaffected by blooms of this toxic cyanobacterium. The observation of red biomass on plankton filters collected from summer onwards in 2019 and 2020 raised the suspicion whether it was prominently present also in Upper Lake Constance (Überlinger See). DNA extraction and NGS sequencing of cyanobacteria-specific 16S-rDNA amplicons as well as Sanger sequencing of the mcy gene for toxin production, confirmed the presence of P. rubescens in Lake Constance, though at very low abundance. Two types of microcystin toxins were also detectable, though at extremely low concentrations. Indeed, Synechococcus spp. were responsible for the high abundance of red-pigmented biomass, and our phylogenetic analysis linked them to Lake Constance isolates already described in 2003. Plankton filtration for collecting biomass for DNA extraction is traditionally performed with a fixed sample volume, resulting in different amounts of biomass and thus DNA depending on the plankton density of the water samples. Further, this introduces a so called ‘filtration bias’ into the NGS community analysis. A new filtration approach was developed, using flowrate as a proxy for biomass loading and clogging of the filters. The new method successfully collected equivalent amounts of DNA regardless of plankton density, and the NGS results showed no ‘filtration bias’ when tested. This filtration method was used to collect plankton biomass for DNA extraction in the following study. The composition of the nanoplankton (here, organisms with 180 – 5 µm in diameter) and picoplankon (5 – 0.2 µm in diameter) of the epilimnion of Upper and Lower Lake Constance was analysed every two weeks from March 2018 to March 2019. Therefore, DNA was extracted from plankton samples taken of the water column between 0 – 20 m depth (integrated sample) and 18S- and 16S-rDNA amplicons were sequenced by NGS. While the temporal dynamics of the microbial community showed a similar seasonal pattern for both sampling sites, the phylogenetic analysis revealed specific taxa that were more abundant or even uniquely present in either Upper or Lower Lake Constance, which could be attributed to specific environmental factors in these different parts of the lake. For example, in Upper Lake Constance, the vertical mixing in winter brought a hypolimnion community into the epilimnion, while for Lower Lake Constance, a hypoxic event during summer and autumn allowed also for anaerobic microorganisms to thrive. The presence of several taxa capable of mixotrophy or predation at either the one or the other sampling site, also indicated specific predator-prey interactions in the different parts of the lake. The frequentist statistics used in biology have limitations that can affect the accuracy of the results and, by extension, the full analysis. The main problem is the lack of consideration of the statistics in the experimental design. Joint Species Distribution Models (JSDM) and Bayesian inference, which are widely used in (non-microbial) ecology, are less sensitive to such limitations. My aim was to apply this approach to the temporal dynamics of the microbial plankton community in ULC described above, with emphasis on the effects of winter vertical mixing and biotic interactions. Vertical mixing was confirmed to affect a high and diverse proportion of the plankton community, with for example Actinobacteria being highly sensitive. A large network of biotic interactions was observed, confirming known interactions such as the mycoloop or the association of Proteobacteria and Bacteroidota with specific phytoplankton species. The models also revealed additional, predicted interactions that require further experimental analysis. Hence, the models showed conclusive results, indicating that JSDM is applicable also to the NGS-based analysis of microbial communities.
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FOURNIER, Corentin, 2023. Analysis of dynamics and interactions within planktonic microbial communities in Lake Constance by Next-Generation Sequencing [Dissertation]. Konstanz: University of KonstanzBibTex
@phdthesis{Fournier2023Analy-69277, year={2023}, title={Analysis of dynamics and interactions within planktonic microbial communities in Lake Constance by Next-Generation Sequencing}, author={Fournier, Corentin}, address={Konstanz}, school={Universität Konstanz} }
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Using DNA extracted from environmental samples, researchers now have access to phylogenetic and functional information, and thus to composition, dynamics and abiotic and biotic interactions of the microorganisms that make up these communities. The amount of information accumulated is enormous and allows worldwide comparisons. However, the accurate and optimal processing of such large NGS datasets is still an intensive field in development. Throughout this thesis, DNA sampling and NGS has been established and applied to the description of the microbial plankton community of the epilimnion of Lake Constance, while pushing scientific boundaries to optimise processing and accurately analysing these datasets. Planktothrix rubescens, a red-pigmented toxin-producing cyanobacterial species has regularly formed blooms in Alpine and pre-Alpine lakes. Lake Constance, however, has remained largely unaffected by blooms of this toxic cyanobacterium. The observation of red biomass on plankton filters collected from summer onwards in 2019 and 2020 raised the suspicion whether it was prominently present also in Upper Lake Constance (Überlinger See). DNA extraction and NGS sequencing of cyanobacteria-specific 16S-rDNA amplicons as well as Sanger sequencing of the mcy gene for toxin production, confirmed the presence of P. rubescens in Lake Constance, though at very low abundance. Two types of microcystin toxins were also detectable, though at extremely low concentrations. Indeed, Synechococcus spp. were responsible for the high abundance of red-pigmented biomass, and our phylogenetic analysis linked them to Lake Constance isolates already described in 2003. Plankton filtration for collecting biomass for DNA extraction is traditionally performed with a fixed sample volume, resulting in different amounts of biomass and thus DNA depending on the plankton density of the water samples. Further, this introduces a so called ‘filtration bias’ into the NGS community analysis. A new filtration approach was developed, using flowrate as a proxy for biomass loading and clogging of the filters. The new method successfully collected equivalent amounts of DNA regardless of plankton density, and the NGS results showed no ‘filtration bias’ when tested. This filtration method was used to collect plankton biomass for DNA extraction in the following study. The composition of the nanoplankton (here, organisms with 180 – 5 µm in diameter) and picoplankon (5 – 0.2 µm in diameter) of the epilimnion of Upper and Lower Lake Constance was analysed every two weeks from March 2018 to March 2019. Therefore, DNA was extracted from plankton samples taken of the water column between 0 – 20 m depth (integrated sample) and 18S- and 16S-rDNA amplicons were sequenced by NGS. While the temporal dynamics of the microbial community showed a similar seasonal pattern for both sampling sites, the phylogenetic analysis revealed specific taxa that were more abundant or even uniquely present in either Upper or Lower Lake Constance, which could be attributed to specific environmental factors in these different parts of the lake. For example, in Upper Lake Constance, the vertical mixing in winter brought a hypolimnion community into the epilimnion, while for Lower Lake Constance, a hypoxic event during summer and autumn allowed also for anaerobic microorganisms to thrive. The presence of several taxa capable of mixotrophy or predation at either the one or the other sampling site, also indicated specific predator-prey interactions in the different parts of the lake. The frequentist statistics used in biology have limitations that can affect the accuracy of the results and, by extension, the full analysis. The main problem is the lack of consideration of the statistics in the experimental design. Joint Species Distribution Models (JSDM) and Bayesian inference, which are widely used in (non-microbial) ecology, are less sensitive to such limitations. My aim was to apply this approach to the temporal dynamics of the microbial plankton community in ULC described above, with emphasis on the effects of winter vertical mixing and biotic interactions. Vertical mixing was confirmed to affect a high and diverse proportion of the plankton community, with for example Actinobacteria being highly sensitive. A large network of biotic interactions was observed, confirming known interactions such as the mycoloop or the association of Proteobacteria and Bacteroidota with specific phytoplankton species. The models also revealed additional, predicted interactions that require further experimental analysis. 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