Stable Isotope Probing and Metagenomics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Two promising culture-independent approaches that have been employed to assess the function and metabolic potential of uncultivated microorganisms are stable isotope probing (SIP) and metagenomics. This chapter discusses the methodology of metagenomics within the context of DNA stable isotope probing (DNA-SIP), and provides a description of the possible limitations and how these limitations can be overcome, summarizes the combined DNA-SIP and meta-genomic studies to date, and highlights future directions. The chapter also focuses on metagenomics as it relates to SIP and highlights some of the methodological considerations for cloning and characterization of labeled DNA from active and uncultivated microorganisms. A study using SIP and metagenomics with increasingly low substrate concentrations to characterize marine methylotrophs involved in C1 cycling of surface seawater was a proof-of-concept approach that utilized multiple displacement amplification (MDA) for the first time in association with DNA-SIP and metagenomics. The study also demonstrated that DNA-SIP employing near-in situ substrate concentrations may be used because the resulting low yields of DNA are still amenable to metagenomic analysis through MDA amplification. The combination of SIP, MDA, and metagenomics provides powerful access to the genomes of active-but-uncultivated microorganisms. An alternative approach for combining SIP and metagenomics is to profile the purified 13C-labeled DNA with high-throughput sequencing of cloned DNA fragments. DNA-SIP paired with metagenomics is expected to yield invaluable insight into the uncultured microbial world as the techniques become increasingly commonplace, isotopes become increasingly available and affordable, and experiments become increasingly well designed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it