Isotopologue Ratios Identify <sup>13</sup> C‐Depleted Biomarkers in Environmental Samples Impacted by Methane Turnover
Bibliographic record
Abstract
ABSTRACT Rationale The stable carbon isotopic composition (δ 13 C) of individual lipids is of great value in studying carbon cycling. Among those, microbial lipids in sediments impacted by high methane turnover stand out due to their uniquely depleted isotopic fingerprint. However, gas chromatography/isotope ratio mass spectrometry (GC/irMS) is limited to volatile compounds, whereas intact polar lipids require extensive preprocessing, which results in the loss of chemotaxonomic information. Expanding compound‐specific isotopic information to intact polar lipids would enhance insights into the microbial turnover of methane. Methods We performed ultra‐high‐performance liquid chromatography/electrospray ionization/high‐resolution mass spectrometry (UHPLC/ESI/HRMS) to analyze standards of archaeol and lipid extracts from a diverse set of sediment samples of a hydrothermal methane seep system. Using the ratio of the M1 isotopologue over the monoisotopic isotopologue M0, we calculated the δ 13 C values of archaeol and various polar, non‐GC‐amenable lipids. The δ 13 C values of archaeol obtained via ratios were compared to those measured via GC/irMS. Results δ 13 C values of archaeol determined in natural samples via GC/irMS and the UHPLC/HRMS approach were strongly correlated ( R 2 = 0.94; N = 76–82) across a wide range of δ 13 C values (GC‐irMS = −119‰ to −34‰). Biomarkers associated with methane turnover consistently yielded δ 13 C values below −60‰, whereas the δ 13 C values of compounds presumably associated with the photosynthesis‐based food web remained above −45‰. UHPLC/HRMS measurements of archaeol standard further indicated that δ 13 C values can be reliably determined across an M0 signal‐intensity range of approximately one order of magnitude. Conclusions Our results highlight that the M1/M0 ratio from UHPLC/HRMS measurements can be utilized to evaluate the carbon isotopic fingerprint of non‐GC‐amenable lipids and to reliably detect lipid biomarkers putatively associated with microbial methane turnover carrying extremely depleted isotopic signatures. This paves the way for a comprehensive exploration of intact lipids associated with microbial methane turnover in environmental samples.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".