What do membrane lipids tell us about the microorganisms living in extreme environments?
Bibliographic record
Abstract
To search for extraterrestrial life surrogate extreme environments on Earth have been chosen for investigation. An example of a surrogate site is the Canadian subpermafrost. Investigations into microbial communities occurred by access fracture borehole water in the Lupin gold mine, and drill rock cores and drilling waters in the High Lake region of Nunavut, Canada. Membrane lipid analyses uses GC/MS and HPLC/ES/MS/MS to provide estimates of biomass, phospholipid (PLFA) and respiratory quinone composition, and compositional changes related to membrane stress caused by nutritional limitations or exposure to toxic conditions. Lupin fracture borehole waters were collected from 800 to 1200 meters, while the High Lake rock cores were collected from 335 to 535 meters. Biomass estimates based on PLFA ranged from 0.25 to 22 pmol L-1 for the Lupin waters. High Lake drill waters had biomass that ranged from below detection limits (bdl) to 595 pmol/ml, while rock core samples had biomass estimates ranging from bdl to 32 pmol g-1. PLFA profiles revealed the presence of both Gram +/- bacteria and sulfatereducing bacteria. Specific PLFA ratios indicate that the bacterial communities were physiologically stressed. Menaquinones were the most abundant but varied in the dominant isoprene units between the two sites. Ubiquinone to menaquinone ratio indicated that these samples have been anoxic for a long time. Methods to detect life signatures at surrogate sites on Earth will be critical for assessing extraterrestrial life. Currently, the membrane lipid analyses provide additional information not easily provided by other molecular techniques.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".