Densely populated biofilms and linked iron and sulfur cycles in the fractured-rock continental subsurface
Bibliographic record
Abstract
The deep continental biosphere is supported by chemolithoautotrophy and depends on rock-derived substrates for energy. The majority of microorganisms in these crustal environments are likely attached to mineral surfaces within rock fractures, making characterization of deep life challenging. To better understand both biogeochemical cycling and mineral-hosted microbial communities in the deep subsurface, we characterized naturally occurring mineral particulate and associated biomass collected from boreholes drilled into a 2.7 Ga banded iron formation within the southern Canadian Shield. Particulate mineralogy was characterized via X-ray diffraction and Fe X-ray absorption near edge structure (XANES) spectroscopy. The particulate in one borehole was identified as a mixture of hematite and quartz, while the other borehole contained a mixture of the iron sulfides mackinawite and greigite, suggesting an active sulfur cycle mediated by microbial activity. Carbon associated with the particulate was imaged via scanning transmission X-ray microscopy and characterized via C XANES spectroscopy. In both boreholes, the particulate was colonized by microbial cells; many samples contained abundant biofilm. The cells and biofilm were chemically distinct, with the C XANES spectra for the cells consisting primarily of a protein-like signal and the biofilm resembling a mixture of protein, saccharide, and lipid. In the borehole containing the sulfidic particulate, the abundance of cells and biofilm increased with sample depth. Mineral particulate found in boreholes, whether forming in situ or as a result of drilling and weathering, are a valuable way to access the deep subsurface without the contamination and disturbance caused by drilling new cores. To better understand the microbial community composition and function associated with the particulate-biofilm aggregates and surrounding groundwater, filtered-water and particulate samples were characterized via shotgun metagenomic sequencing. Metagenomic analyses showed that while microbial communities were distinct between boreholes, all communities contained the genetic potential for the oxidation and reduction of a variety of sulfur phases. This suggests that the biogeochemical cycling of S, potentially connected to Fe cycling in this iron-rich habitat, could be fueling life in deep crustal environments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".