Speaker
Description
Heterotrophic protists occupy key nodes in terrestrial food webs due to their high abundance, fast turnover and functional importance as microbial grazers. However, their impact on groundwater bacterial communities and organic carbon transfer to higher trophic levels remains largely unknown. Assessing their role in trophic interactions using molecular techniques has been limited by the variability in 18S rRNA gene copy numbers, complicating the quantification of protists.
The key objective of our novel approach is the establishment of protist enumeration by Imaging Flow Cytometry (IFC), combined with qPCR assays and 18S rRNA gene targeted amplicon sequencing, to derive taxon-specific correction factors, facilitating precise estimation of key taxa abundances from molecular data and provide biomass estimates from IFC. In addition, we aim to compare protistan communities between carbonate-rock (Hainich Critical Zone Exploratory) and sandstone aquifers (Saale-Elster-Sandstone Observatory) located in Thuringia, using molecular and cultivation-dependent approaches as well as metatranscriptomics.
Protistan monocultures were used to successfully generate initial reference image datasets using IFC, covering sizes from 3 to 50 µm and various morphotypes. Convolutional neural network (CNN) training achieved 85% precision in predicting protistan taxa based on morphological features.
Enrichments of groundwater protistan communities initially exhibited predominance of nanoflagellates (3-15 µm) and flagellates (15-20 µm), followed by successional changes in favor of ciliates and amoebae (Acanthamoeba, Hartmannella, Vahlkampfia) within 1-2 weeks where differences between the geological settings were observed. By 4-6 weeks, occasionally heliozoans and Aspidisca sp. (Ciliates) emerged. Amplicon sequencing confirmed high abundances of previously identified groundwater taxa such as Cercomonas spp., Thaumatomonas sp., Neocercomonas sp. (Cercomonadida), Sandona sp., Allantion sp. (Glissomonadida), Spumella sp., Paraphysomonas sp. (Chrysomonada), Rhogostoma sp. and Glaucoma sp.
Our results show that IFC enables high-throughput automated quantification. Innovative abundance estimation and community assessment will enhance our understanding of food web structures in aquifers with different geological settings.
| Status Group | Postdoctoral Researcher |
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