During the first 18 months of the project, the groundwork for the project was laid. Next to hiring team members and acquiring equipment for the project, we started planning the initial drilling campaign in detail. It turned out that we needed to re-plan the timing of the drilling campaign and its scale. The approval from the geologic and mining authorities was granted almost instantaneously, but the water authorities were unfamiliar with research drilling and thus required multiple appraisals by external certified engineers, causing a considerable delay in the approval processes. Due to the rising interest in geothermal energy, drilling companies now have long lead times and have raised prices. Since the drill site in Glees (Germany) is located inside a Natura 2000 habitat protection area, we were only allowed to drill in winter, between November and March. Due to the delays in permitting and the restriction to winter times, it became clear that the first drilling could only be performed at the end of the second year of the project, and that only two large-scale drillings could be performed within the available budget. We will only be able to estimate whether this will affect the project once we have analysed the results of the first drilling.
To mitigate the delays in the drilling expedition, we placed a higher priority on sampling readily accessible sites. We sampled the high-CO2 geysers Geysir Andernach and Wallender Born Geysir (Rhineland-Palatinate, Germany), the sulfidic spring Mühlbacher Schwefelquelle (Germany) rich in carbonated minerals, and the Hartousov high-CO2 subsurface observatory (Czech Republic). Our aim was to analyse microbial communities (bacteria, archaea, viruses) by generating metagenomes and metalipidomes and by fluorescence microscopy, cultivation experiments and isotope tracer studies. At Andernach Geysir, we identified novel archaeal lipids, i.e. extended glycerol dialkyl and trialkyl glycerol tetraethers that may be diagnostic for high-CO2 environments and are likely synthesized by Altiarchaeum, the dominant species in the geyser’s microbiome.
Recent reconstruction of high-quality genomes of Altiarchaeum genus, which is unique to high-CO2 ecosystems, paved the way for detailed enzymological analyses right after the start of the project. These genomes encode potential enzymes from the bacterial and archaeal versions of the Wood–Ljungdahl (WL) pathway. Using an iterative metaenzymology approach, we studied two of these enzymes. The results indicate the presence of an active archaeal WL pathway in Altiarchaeum using NADPH rather than F420H2 as a reductant, enhancing the energetic efficiency of the altiarchaeal WL pathway. In line with this, we detected both THF and H4MPT, the cofactors used by bacteria and archaea, respectively, but only trace amounts of F420 in the biomass of Altiarchaeum obtained from Mühlbacher Schwefelquelle. We demonstrated activities of the studied NADPH- and H4MPT-dependent reductases in this biomass, confirming the reliability of our approach. We already started the enrichment culture, using the obtained samples.
To investigate how microbes react to different CO2 concentrations, Archean Park sets out to break new grounds in transcriptomic analyses. We developed a new assay for identification of newly synthesized RNA via Oxford Nanopore Technologies using RNA base analogons for batch cultures that will be used for the analysis of microbial communities from high-CO2 environments.
The Archean Park project is committed to FAIR data management and ensuring accessibility of all data by all project partners. As per ERC guidelines, a Data Management Plan (DMP) was established, outlining the different types of Data generated as well as lay out the foundations of a shared storage system. Following successful deployment and configuration of the CEPH storage nodes with S3 protocol, Dataverse (repository front-end) was implemented and is now fully functional. The metadata schema for the Dataverse was formulated based on detailed information from the DMP and existing community standards for the various types of data.
