A high-throughput anaerobic method for viability assays
Bibliographic record
Abstract
ABSTRACT Viability testing for anaerobes is a time-consuming and expensive process, posing challenges for research and public health settings. Here, we present a rapid, economical, and reliable method for testing anaerobe viability using the Geometric Viability Assay (GVA) with Clostridium perfringens as our model, a bacterium known for causing toxin-related systemic and enteric diseases. This method is efficient and cost-effective, requiring one pipette tip per sample, and is compatible with the economical anaerobic jar system. The results align with traditional plate-based assays in terms of colony-forming unit (CFU) measurements. Anaerobic GVA has low technical bias and a dynamic range extending over 5 orders of magnitude. In addition, our method determined the bactericidal activity of antibiotics in a dose-dependent manner, when an antibiotic sensitivity testing (AST) was performed with a panel of four antibiotics (ampicillin, gentamicin, meropenem, and tetracycline). Furthermore, the minimum concentrations for complete bactericidal activity (MBC) of four clinical isolates were determined and the MBC concentration for tetracycline was up to 8× higher than the concentration for complete growth inhibition (MIC). Additional tests involving Clostridium bifermentans and Clostridium sporogenes demonstrated the generality of our method for other anaerobic species. Beyond viability testing, the GVA measured spore concentrations of various Clostridium perfringens isolates, showing consistency with classical plating methods. Our study confirms that the anaerobic GVA is a valuable tool for rapid, accurate viability screening in anaerobic settings and is compatible with routine assays, such as AST and spore screening. This method enhances the scalability and utility of anaerobic viability-based assays. IMPORTANCE The routine assessment for the viability of anaerobes is based on bacterial plating, but so far, it has been limited in throughput by the long preparation steps and the tedious anaerobic culturing. Thus, comparatively little is known about the susceptibility pattern, and the sporulation of anaerobes because of the absence of the proper method. Here, we show GVA can quantify the anaerobic Clostridiums colonies accurately by utilizing an anaerobic jar to measure viable cells and spores in high throughput with minimal volumes of reagents and at a comparable time to the traditional viability testing practice. Furthermore, this method enabled high-throughput detection of the bactericidal activity of the antibiotics against anaerobes and allowed for the quantification of hetero-tolerant/resistant subpopulation, which was previously unattainable. Our approach is rapid and easy to use, making it ideal for various applications where high-throughput capabilities can drive innovation, including drug-microbe interactions, host-microbe interactions, and microbe-microbe interactions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".