A liquid chromatography – mass spectrometry method to measure <sup>13</sup>C-isotope enrichment for DNA stable-isotope probing
Bibliographic record
Abstract
DNA stable-isotope probing (DNA-SIP) is a cultivation-independent technique that makes it possible to associate metabolic function and taxonomic identity in a wide range of terrestrial and aquatic environments. In DNA-SIP, DNA is labeled via the assimilation of a labeled growth substrate that is subsequently used to identify microorganisms involved in assimilation of the substrate. However, the labeling time has to be sufficient to obtain labeled DNA but not so long such that cross-feeding of ¹³C-labeled metabolites from the primary consumers to nontarget species can occur. Confirmation that the DNA is isotopically labeled in DNA-SIP assays can be achieved using an isotope ratio mass spectrometer. In this study, we describe the development of a method using liquid chromatography (HPLC) coupled to a quadrupole mass spectrometer (QMS) to measure the ¹³C enrichment of thymine incorporated into DNA in Escherichia coli cultures fed with [¹³C]acetate. The method involved the hydrolysis of DNA extracted from the cultures that released the nucleotides, followed by the separation of the thymine by HPLC on a reverse-phase C₈ column in isocratic elution mode and the detection and quantification of ¹³C-labeled thymine by QMS. To mimic a DNA-SIP assay, a DNA mixture was made using ¹³C-labeled E. coli DNA with DNA extracted from five bacterial species. The HPLC-MS method was able to measure the correct proportion of ¹³C-DNA in the mix. This method can then be used as an alternative to the use of isotope ratio mass spectrometry in DNA-SIP assays.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.007 |
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".