Characterisation of MutaTMMouse gt10-lacZ transgene: evidence for in vivo rearrangements
Bibliographic record
Abstract
The multicopy λgt10-lacZ transgene shuttle vector of Muta™Mouse serves as an important tool for genotoxicity studies. Here, we describe a model for λgt10-lacZ transgene molecular structure, based on characterisation of transgenes recovered from animals of our intramural breeding colony. Unique nucleotide sequences of the 47 513 bp monomer are reported with GenBank® assigned accession numbers. Besides defining ancestral mutations of the λgt10 used to construct the transgene and the Muta™Mouse precursor (strain 40.6), we validated the sequence integrity of key λ genes needed for the Escherichia coli host-based mutation reporting assay. Using three polymerase chain reaction (PCR)-based chromosome scanning and cloning strategies, we found five distinct in vivo transgene rearrangements, which were common to both sexes, and involved copy fusions generating ∼10 defective copies per haplotype. The transgene haplotype was estimated by Southern hybridisation and real-time-polymerase chain reaction, which yielded 29.0 ± 4.0 copies based on spleen DNA of Muta™Mouse, and a reconstructed CD2F(1) genome with variable λgt10-lacZ copies. Similar analysis of commercially prepared spleen DNA from Big Blue® mouse yielded a haplotype of 23.5 ± 3.1 copies. The latter DNA is used in calibrating a commercial in vitro packaging kit for E.coli host-based mutation assays of both transgenic systems. The model for λgt10-lacZ transgene organisation, and the PCR-based methods for assessing copy number, integrity and rearrangements, potentially extends the use of Muta™Mouse construct for direct, genomic-type assays that detect the effects of clastogens and aneugens, without depending on an E.coli host, for reporting effects.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".