Hydrogen is a key energy source for subsurface microbial processes, particularly in subsurface environments with limited alternative electron donors, and environments that are not well connected to the surface. In addition to consumption of hydrogen, microbial processes such as fermentation and nitrogen fixation produce hydrogen. Hydrogen is also produced by a number of abiotic processes including radiolysis, serpentinization, graphitization, and cataclasis of silicate minerals. Both biotic and abiotically generated hydrogen may become available for consumption by microorganisms, but biotic production and consumption are usually tightly coupled. Understanding the microbiology of hydrogen cycling is relevant to subsurface engineered environments where hydrogen-cycling microorganisms are implicated in gas consumption and production and corrosion in a number of industries including carbon capture and storage, energy gas storage, and radioactive waste disposal. The same hydrogen-cycling microorganisms and processes are important in natural sites with elevated hydrogen and can provide insights into early life on Earth and life on other planets. This review draws together what is known about microbiology in natural environments with elevated hydrogen, and highlights where similar microbial populations could be of relevance to subsurface industry.

Rare earth elements (REE) are considered to be a critical resource, because of their importance in green energy applications and the overdependence on Chinese imports. REE rich ion-adsorption deposits (IAD) result from tropical weathering of REE enriched igneous rocks. Commercial REE leaching from IAD, using salt solutions occurs via an ion-exchange mechanism. Bioleaching of IAD by Aspergillus or Bacillus, was compared to Uninoculated Control and Salt leaching (0.5 M ammonium sulfate) over 60 days. Salt leaching was most effective, followed by Aspergillus, Bacillus then Uninoculated Control. Most of the REE and major elements released by Salt leaching occurred before day 3. With bioleaching, REE and major elements release increased with time and had a greater heavy to light REE ratio. Similar total heavy REE release was observed in Salt leaching and Aspergillus (73.1% and 70.7% Lu respectively). In bioleaching experiments, pH was inversely correlated with REE release (R² = 0.947 for Lu) indicating leaching by microbially produced acids. These experiments show the potential for bioleaching of REE from IAD, but dissolution of undesirable elements could cause problems in downstream processing. Further understanding of the bioleaching mechanisms could lead to optimization of REE recovery.

Approximately 300 million tonnes of bauxite are processed annually, primarily to extract alumina, and can contain moderate rare earth element (REE) concentrations, which are critical to a green energy future. Three bioleaching techniques (organic acid, reductive and oxidative) were tested on three karst bauxites using either Aspergillus sp. (organic acid bioleaching) or Acidithiobacillus ferrooxidans (reductive and oxidative bioleaching). Recovery was highest in relation to middle REE (generally Nd to Gd), with maximum recovery of individual REE between 26.2% and 62.8%, depending on the bauxite sample. REE recovery occurred at low pH (generally < 3), as a result of organic acids produced by Aspergillus sp. or sulphuric acid present in A. ferrooxidans growth media. Acid production was seen when A. ferrooxidans was present. However, a clear increase in REE recovery in the presence of A. ferrooxidans (compared to the control) was only seen with one bauxite sample (clay-rich) and only under oxidative conditions. The complex and varied nature of REE-bearing minerals in bauxite provides multiple targets for bioleaching, and although the majority of recoverable REE can be leached by organic and inorganic acids, there is potential for enhanced recovery by bioleaching.

The discovery over the past two decades of viable microbial communities within glaciers has promoted interest in the role of glaciers and ice sheets (the cryosphere) as contributors to subglacial erosion, global biodiversity, and in regulating global biogeochemical cycles. In situ or in-field detection and characterisation of microbial communities is becoming recognised as an important approach to improve our understanding of such communities. Within this context we demonstrate, for the first time, the ability to detect Gram-negative bacteria in glacial field-environments (including subglacial environments) via the detection of lipopolysaccharide (LPS); an important component of Gram-negative bacterial cell walls. In-field measurements were performed using the recently commercialised PyroGene® recombinant Factor C (rFC) endotoxin detection system and used in conjunction with a handheld fluorometer to measure the fluorescent endpoint of the assay. Twenty-seven glacial samples were collected from the surface, bed and terminus of a low-biomass Arctic valley glacier (Engabreen, Northern Norway), and were analysed in a field laboratory using the rFC assay. Sixteen of these samples returned positive LPS detection. This work demonstrates that LPS detection via rFC assay is a viable in-field method and is expected to be a useful proxy for microbial cell concentrations in low biomass environments.

Ground source heat pumps (GSHPs) are low‐carbon alternatives to gas boilers for decarbonizing heating. Open‐loop GSHP systems abstract groundwater, pass it through a heat exchanger, and return it to ground or surface water. Groundwater samples from the top and base of an abstraction and a recharge borehole of an open‐loop GSHP system in Cardiff, UK were assessed, and compared to two local boreholes in the same aquifer. Groundwater samples were taken when the GSHP system was active (once) and inactive (twice) and analyzed for changes in geochemistry, viable cell counts, and microbial community (16S rRNA gene sequencing). The GSHP had a distinct geochemistry and microbial community compared to the control boreholes, and the abstraction borehole showed greater variability than the recharge borehole. The microbial community of the GSHP system showed an increase in relative abundance of genera involved in oxidation of methane and methylated compounds, of which Methylotenera was the most abundant (up to 83.9% of 16S rRNA gene sequences). There were also changes in genera associated with nitrification (Nitrospira, Nitrosomonas) and those with potential for sulfur and iron cycling (Rhodoferax). Methane concentration was analyzed after identification of methylotrophs and found that methane concentrations were up to 2855 μg L⁻¹, thus likely having had a significant impact on the bacterial communities present. Understanding the microbiology and biogeochemistry of GSHP systems provides insight into potential issues with local infrastructure and long‐term system performance, and supports modeling to maximize efficient and sustainable use of the subsurface.

The ability to perform microbial detection and characterization in-field at extreme environments, rather than on returned samples, has the potential to improve the efficiency, relevance and quantity of data from field campaigns. To date, few examples of this approach have been reported. Therefore, we demonstrate that the approach is feasible in subglacial environments by deploying four techniques for microbial detection: real-time polymerase chain reaction; microscopic fluorescence cell counts, adenosine triphosphate bioluminescence assay and recombinant Factor C assay (to detect lipopolysaccharide). Each technique was applied to 12 subglacial ice samples, 12 meltwater samples and two snow samples from Engabreen, Northern Norway. Using this multi-technique approach, the detected biomarker levels were as expected, being highest in debris-rich subglacial ice, moderate in glacial meltwater and low in clean ice (debris-poor) and snow. Principal component analysis was applied to the resulting dataset and could be performed in-field to rapidly aid the allocation of resources for further sample analysis. We anticipate that in-field data collection will allow for multiple rounds of sampling, analysis, interpretation and refinement within a single field campaign, resulting in the collection of larger and more appropriate datasets, ultimately with more efficient science return.