Design and Application of an Internal Amplification Control to Improve Dehalococcoides mccartyi 16S rRNA Gene Enumeration by qPCR
Bibliographic record
Abstract
Dehalococcoides mccartyi (Dhc) strains are keystone bacteria for reductive dechlorination of chlorinated ethenes to nontoxic ethene in contaminated aquifers. Enumeration of Dhc biomarker genes using quantitative real-time PCR (qPCR) in groundwater is a key component of site assessment and bioremediation monitoring. Unfortunately, standardized qPCR procedures that recognize impaired measurements due to PCR inhibition, low template DNA concentrations, or analytical error are not available, thus limiting confidence in qPCR data. To improve contemporary approaches for enumerating Dhc in environmental samples, multiplex qPCR assays were designed to quantify the Dhc 16S rRNA gene and one of two different internal amplification controls (IACs): a modified Dhc 16S rRNA gene fragment (Dhc*) and the firefly luciferase gene luc. The Dhc* IAC exhibited competitive inhibition in qPCR with the Dhc 16S rRNA gene template when the ratio of either target was 100-fold greater than the other target. A multiplex qPCR assay with the luc IAC avoided competitive inhibition and accurately quantified Dhc abundances ranging from ∼10 to 10(7) 16S rRNA gene copies per reaction. The addition of ∼10(6) E. coli luc IAC to simulated groundwater amended with the Dhc-containing consortium KB-1 yielded reproducible luc counts after DNA extraction and multiplex qPCR enumeration. The application of the luc IAC assay improved Dhc biomarker gene quantification from simulated groundwater samples and is a valuable approach for "ground truthing" qPCR data obtained in different laboratories, thus reducing ambiguity associated with qPCR enumeration and reproducibility.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".