Periodic Reporting for period 2 - PROSPECTOMICS (Using Omics Techniques for Hydrocarbon Prospecting)
Okres sprawozdawczy: 2022-01-01 do 2022-12-31
In the framework of “Future and Emerging Technologies” of Horizon 2020, PROSPECTOMICS proposes a completely new approach that has the potential to reduce the environmental impact and financial burden of hydrocarbon exploration by providing cleaner and cheaper prospecting alternatives. The project main objective is to develop a biomolecular tool for rapid and minimally invasive screening of marine sediments for even minor hydrocarbon seepage from underlying reservoirs, and thereby guide hydrocarbon exploration with unprecedented sensitivity and precision. By combining high-throughput “multi-omics” data with the biogeochemical context of the surrounding sediments in which microorganisms live and feed, PROSPECTOMICS aims to detect inconspicuous sites with underlying oil and gas resources but without any visible surface manifestation.
PROSPECTOMICS will constrain biogeochemical reactions related to hydrocarbon seeps in the shallow subsurface, identify microbial fingerprints diagnostic of metabolic activities in the sediment and streamline their analysis via machine learning to deliver predictive models for prospecting. This can significantly reduce the amount of work, time and costs per sample and allow for screening large numbers of samples. By relying on gravity coring of the seabed and the use of biological instead of geological tools, PROSPECTOMICS’ approach will minimize environmental disturbances and financial costs related to hydrocarbon prospecting in European waters. The key objectives of PROSPECTOMICS will be reached through several consecutive tasks, namely:
(I) to develop an optimized protocol for DNA, RNA and protein extraction from replicate sediment samples
(II) to streamline the analyses of large biogeochemical “multi-omics” datasets via machine learning
(III) to identify “fingerprints” of hydrocarbon-related microbial taxa and hydrocarbon-fueled metabolisms that could lead to rapid, user-friendly omics-based detection methods for hydrocarbon seepage.
The resulting “multi-omics big data” will be sorted via machine learning to detect selective parameters for rapid identification of hydrocarbon seepage. PROSPECTOMICS will be thereby able to identify hitherto unknown key features that can serve as robust indicators of underlying hydrocarbon reservoirs, such as biogeochemical and metabolic processes, molecular subsystems or taxa. Combining multi-omics with already existing sedimentary data will provide a holistic understanding of seabed processes related to naturally-occurring petroleum seepage in marine sediments and its effects on benthic microbial ecosystems.
PROSPECTOMICS will constrain biogeochemical reactions related to hydrocarbon seeps in the shallow subsurface, identify microbial fingerprints diagnostic of metabolic activities in the sediment and streamline their analysis via machine learning to deliver predictive models for prospecting. This can significantly reduce the amount of work, time and costs per sample and allow for screening large numbers of samples. By relying on gravity coring of the seabed and the use of biological instead of geological tools, PROSPECTOMICS’ approach will minimize environmental disturbances and financial costs related to hydrocarbon prospecting in European waters. The key objectives of PROSPECTOMICS will be reached through several consecutive tasks, namely:
(I) to develop an optimized protocol for DNA, RNA and protein extraction from replicate sediment samples
(II) to streamline the analyses of large biogeochemical “multi-omics” datasets via machine learning
(III) to identify “fingerprints” of hydrocarbon-related microbial taxa and hydrocarbon-fueled metabolisms that could lead to rapid, user-friendly omics-based detection methods for hydrocarbon seepage.
The resulting “multi-omics big data” will be sorted via machine learning to detect selective parameters for rapid identification of hydrocarbon seepage. PROSPECTOMICS will be thereby able to identify hitherto unknown key features that can serve as robust indicators of underlying hydrocarbon reservoirs, such as biogeochemical and metabolic processes, molecular subsystems or taxa. Combining multi-omics with already existing sedimentary data will provide a holistic understanding of seabed processes related to naturally-occurring petroleum seepage in marine sediments and its effects on benthic microbial ecosystems.
From October 29 to November 8 2021, a sampling cruise to the Barents Sea successfully retrieved fifty gravity cores from five areas, three with known hydrocarbon anomalies and two as reference. Sediment cores were subsampled and optimally conditioned on board the research vessel using the BUGLab, GFZ’s mobile geomicrobiology laboratory. Sediments were delivered to each partner to resume biogeochemical and biomolecular analyses. The sampling cruise and related procedures were regularly featured on the PROSPECTOMICS website and social media.
Biogeochemical characterization of the sediment included high-resolution pore water profiles for alkalinity, major and trace ions. Sulfate reduction rates were measured and modeled in parallel with sulfide fluxes, and supplemented with cell counts. Although cell densities were similar across sampling sites, sediments affected by hydrocarbon seeps showed more pronounced biogeochemical trends, namely higher sulfate reduction rates and steeper gradients in pore water chemistry.
For biomolecular assays, we had to mitigate sample-inherent factors that prevented efficient extraction, e.g. humic acids, hydrocarbon residues, and strong binding properties of the clay matrix. Standard operation procedures were individually optimized for replicate samples. DNA was successfully extracted for the fifty gravity cores available in the project in sufficient amount and quality to proceed with high-throughput metagenomic sequencing. Initially, twelve metagenomes were sequenced to validate the optimized DNA extraction assay, and complemented with Nanopore sequencing data to allow hybrid de novo assembly of short and long reads. We thereby obtain over 170 metagenome-assembled genomes (MAGs) of high quality (>70% completeness; <10% contamination). The MAGs provided insights into the taxonomic and functional diversity of the sedimentary microbial populations. Several bacterial and archaeal clades dominated sites affected by hydrocarbon seepage. The clades’ MAGs included many genes predicted to be key in the anaerobic degradation of alkanes and aromatic hydrocarbons. For metaproteomics, continuous elution electrophoresis with a multiple collector was designed to perform protein extractions from large amounts of sediment slurry, which drastically increased the yield and quality of eluted proteins. Searches of mass spectrometric data against a comprehensive database of predicted proteins compiled from public repositories and PROSPECTOMICS’ specific MAGs allowed assigning over 800 protein groups taxonomically and functionally, which highlighted archaea with metabolic activities related to methane and C1 compounds. Initial comparative analysis of combined datasets statistically supported specific biogeochemical features as diagnostic of hydrocarbon seepage.
Biogeochemical characterization of the sediment included high-resolution pore water profiles for alkalinity, major and trace ions. Sulfate reduction rates were measured and modeled in parallel with sulfide fluxes, and supplemented with cell counts. Although cell densities were similar across sampling sites, sediments affected by hydrocarbon seeps showed more pronounced biogeochemical trends, namely higher sulfate reduction rates and steeper gradients in pore water chemistry.
For biomolecular assays, we had to mitigate sample-inherent factors that prevented efficient extraction, e.g. humic acids, hydrocarbon residues, and strong binding properties of the clay matrix. Standard operation procedures were individually optimized for replicate samples. DNA was successfully extracted for the fifty gravity cores available in the project in sufficient amount and quality to proceed with high-throughput metagenomic sequencing. Initially, twelve metagenomes were sequenced to validate the optimized DNA extraction assay, and complemented with Nanopore sequencing data to allow hybrid de novo assembly of short and long reads. We thereby obtain over 170 metagenome-assembled genomes (MAGs) of high quality (>70% completeness; <10% contamination). The MAGs provided insights into the taxonomic and functional diversity of the sedimentary microbial populations. Several bacterial and archaeal clades dominated sites affected by hydrocarbon seepage. The clades’ MAGs included many genes predicted to be key in the anaerobic degradation of alkanes and aromatic hydrocarbons. For metaproteomics, continuous elution electrophoresis with a multiple collector was designed to perform protein extractions from large amounts of sediment slurry, which drastically increased the yield and quality of eluted proteins. Searches of mass spectrometric data against a comprehensive database of predicted proteins compiled from public repositories and PROSPECTOMICS’ specific MAGs allowed assigning over 800 protein groups taxonomically and functionally, which highlighted archaea with metabolic activities related to methane and C1 compounds. Initial comparative analysis of combined datasets statistically supported specific biogeochemical features as diagnostic of hydrocarbon seepage.
Fifty sediment cores were processed for deep metagenomic sequencing. Machine learning integration of the meta-omics dataset will predict which biogeochemical and biomolecular features are diagnostic of underlying hydrocarbon resources seeping inconspicuously to the seabed. PROSPECTOMICS includes a validation phase during which the optimized biomolecular procedures and streamlined machine learning analysis will be applied on a set of samples without any a-priori knowledge of whether the sample is affected or not by hydrocarbon seepage. Applying the protocols developed in this project is expected to efficiently identify the (minor) presence-absence of hydrocarbon seepage and produce accurate predictive modeling based on data from unknown sources.
PROSPECTOMICS’ main goals will be fulfilled by streamlining the lab procedures and statistical protocol for industrial applications. The consortium will draft business models for potential market participants and define IPR in terms of services and subsequent exploitation development. PROSPECTOMICS’ novel approach has the potential to reduce the financial burden of hydrocarbon exploration and provide cleaner and cheaper alternatives. By relying on gravity coring in shallow sediment and biological indicators instead of geological deep drilling, PROSPECTOMICS’ final product will minimize environmental disturbances related to hydrocarbon prospecting, particularly in European waters. AKER BP’s connections to the oil and gas industry provide direct contact to the expected users of this new technology. Adding biogeochemical and multi-omics data to existing knowledge of the seafloor will provide a truly holistic understanding of on-site microbial processes related to petroleum leakage and its effects on benthic ecosystems. Therefore, environmental protection agencies and similar entities are also likely to be interested in PROSPECTOMICS’ findings to monitor hydrocarbon contamination and bioremediation.
PROSPECTOMICS’ main goals will be fulfilled by streamlining the lab procedures and statistical protocol for industrial applications. The consortium will draft business models for potential market participants and define IPR in terms of services and subsequent exploitation development. PROSPECTOMICS’ novel approach has the potential to reduce the financial burden of hydrocarbon exploration and provide cleaner and cheaper alternatives. By relying on gravity coring in shallow sediment and biological indicators instead of geological deep drilling, PROSPECTOMICS’ final product will minimize environmental disturbances related to hydrocarbon prospecting, particularly in European waters. AKER BP’s connections to the oil and gas industry provide direct contact to the expected users of this new technology. Adding biogeochemical and multi-omics data to existing knowledge of the seafloor will provide a truly holistic understanding of on-site microbial processes related to petroleum leakage and its effects on benthic ecosystems. Therefore, environmental protection agencies and similar entities are also likely to be interested in PROSPECTOMICS’ findings to monitor hydrocarbon contamination and bioremediation.