A Modular, Tn <i>7</i> -Based System for Making Bioluminescent or Fluorescent Salmonella and Escherichia coli Strains
Bibliographic record
Abstract
UNLABELLED: Our goal was to develop a robust tagging method that can be used to track bacterial strains in vivo To address this challenge, we adapted two existing systems: a modular plasmid-based reporter system (pCS26) that has been used for high-throughput gene expression studies in Salmonella and Escherichia coli and Tn7 transposition. We generated kanamycin- and chloramphenicol-resistant versions of pCS26 with bacterial luciferase, green fluorescent protein (GFP), and mCherry reporters under the control of σ(70)-dependent promoters to provide three different levels of constitutive expression. We improved upon the existing Tn7 system by modifying the delivery vector to accept pCS26 constructs and moving the transposase genes from a nonreplicating helper plasmid into a temperature-sensitive plasmid that can be conditionally maintained. This resulted in a 10- to 30-fold boost in transposase gene expression and transposition efficiencies of 10(-8) to 10(-10) in Salmonella enterica serovar Typhimurium and E. coli APEC O1, whereas the existing Tn7 system yielded no successful transposition events. The new reporter strains displayed reproducible signaling in microwell plate assays, confocal microscopy, and in vivo animal infections. We have combined two flexible and complementary tools that can be used for a multitude of molecular biology applications within the Enterobacteriaceae This system can accommodate new promoter-reporter combinations as they become available and can help to bridge the gap between modern, high-throughput technologies and classical molecular genetics. IMPORTANCE: This article describes a flexible and efficient system for tagging bacterial strains. Using our modular plasmid system, a researcher can easily change the reporter type or the promoter driving expression and test the parameters of these new constructs in vitro Selected constructs can then be stably integrated into the chromosomes of desired strains in two simple steps. We demonstrate the use of this system in Salmonella and E. coli, and we predict that it will be widely applicable to other bacterial strains within the Enterobacteriaceae This technology will allow for improved in vivo analysis of bacterial pathogens.
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How this classification was reachedexpand
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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".