Omics of deep biosphere/medium compute

SNIC 2019/3-141


SNIC Medium Compute

Principal Investigator:

Mark Dopson



Start Date:


End Date:


Primary Classification:

10610: Bioinformatics and Systems Biology (methods development to be 10203)

Secondary Classification:

10606: Microbiology (medical to be 30109 and agricultural to be 40302)



The deep terrestrial subsurface environment is distinct from the shallow subsurface due to significantly longer groundwater residence times and represents regional rather than local precipitation-responsive hydrology. The presence of a large, deep subsurface biomass has fundamental scientific implications as well as practical impact on large-scale engineering projects. Nutrient and energy transformation pathways in the Earth’s subsurface are poorly understood and it is not well known how such oligotrophic environments can support 2-19% of the earth’s biomass in the terrestrial deep biosphere. The extent of elemental cycling that actually occurs in the deep subsurface and the nature and diversity of major groups of organisms responsible for these processes is an active area of research. The deep subsurface is a true exploration frontier as such an environment faces extensive challenges of access to suitable sampling locations under pristine conditions. The deep subsurface is also important as a potential reservoir for microbes that evolved with evolutionary pressures distinct from those at the surface and may also be relevant for constraining putative life on other planets. Beyond the potential discovery of novel metabolic pathways and elemental cycles, there are also important societal and economic factors that drive the development of a detailed understanding of the deep biosphere. For instance, the storage of nuclear waste and excess CO2 and basic ecosystem services such as the clean-up of surface water through microbial transformation all involve biological aspects that must be understood in order to develop sustainable engineering solutions. In this proposal, we request computational resources to process and analyse high-throughput data (metagenomics, metatranscriptomics, single-cell genomics) produced to gauge a better knowledge of taxonomic, functional and metabolic diversity of the deep biosphere, which so far are poorly understood. The results will have implications for our understanding of global energy and nutrient cycles, the potential for deep terrestrial disposal of nuclear waste and geo-engineering for CO2 storage, while also providing insights about how life could be sustained on other planets. Computational resources requested in this proposal will add up to the ones already available for the PI research group (SNAC small project SNIC 2018/13-4) in order to provide adequate computational capacity for the data analysis entailed by the described research project. There are currently eight members or collaborators of the research group involved in data analyses (with a new PhD student starting 1 April 2019), among whom a bioinformatician from WABI long-term support who is running several computational intensive processes.