Rapid, Serial, Non-invasive Assessment of Drug Efficacy in Mice with Autoluminescent Mycobacterium ulcerans Infection
Bibliographic record
Abstract
BACKGROUND: Buruli ulcer (BU) caused by Mycobacterium ulcerans is the world's third most common mycobacterial infection. There is no vaccine against BU and surgery is needed for patients with large ulcers. Although recent experience indicates combination chemotherapy with streptomycin and rifampin improves cure rates, the utility of this regimen is limited by the 2-month duration of therapy, potential toxicity and required parenteral administration of streptomycin, and drug-drug interactions caused by rifampin. Discovery and development of drugs for BU is greatly hampered by the slow growth rate of M. ulcerans, requiring up to 3 months of incubation on solid media to produce colonies. Surrogate markers for evaluating antimicrobial activity in real-time which can be measured serially and non-invasively in infected footpads of live mice would accelerate pre-clinical evaluation of new drugs to treat BU. Previously, we developed bioluminescent M. ulcerans strains, demonstrating proof of concept for measuring luminescence as a surrogate marker for viable M. ulcerans in vitro and in vivo. However, the requirement of exogenous substrate limited the utility of such strains, especially for in vivo experiments. METHODOLOGY/PRINCIPAL FINDING: For this study, we engineered M. ulcerans strains that express the entire luxCDABE operon and therefore are autoluminescent due to endogenous substrate production. The selected reporter strain displayed a growth rate and virulence similar to the wild-type parent strain and enabled rapid, real-time monitoring of in vitro and in vivo drug activity, including serial, non-invasive assessments in live mice, producing results which correlated closely with colony-forming unit (CFU) counts for a panel of drugs with various mechanisms of action. CONCLUSIONS/SIGNIFICANCE: Our results indicate that autoluminescent reporter strains of M. ulcerans are exceptional tools for pre-clinical evaluation of new drugs to treat BU due to their potential to drastically reduce the time, effort, animals, compound, and costs required to evaluate drug activity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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 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".