Assessing Microbial Monitoring Methods for Challenging Environmental Strains and Cultures
Bibliographic record
Abstract
This paper focuses on the comparison of microbial biomass increase (cell culture growth) using field-relevant testing methods and moving away from colony counts. Challenges exist in exploring the antimicrobial growth of fastidious strains, poorly culturable bacteria and bacterial communities of environmental interest. Thus, various approaches have been explored to follow bacterial growth that can be efficient surrogates for classical optical density or colony-forming unit measurements. Here, six species grown in pure culture were monitored using optical density, ATP assays, DNA concentrations and 16S rRNA qPCR. Each of these methods have different advantages and disadvantages concerning the measurement of growth and activity in complex field samples. The species used as model systems for monitoring were: Acetobacterium woodii, Bacillus subtilis, Desulfovibrio vulgaris, Geoalkalibacter subterraneus, Pseudomonas putida and Thauera aromatica. All four techniques were found to successfully measure and detect cell biomass/activity differences, though the shape and accuracy of each technique varied between species. DNA concentrations were found to correlate the best with the other three assays (ATP, DNA concentrations and 16S rRNA-targeted qPCR) and provide the advantages of rapid extraction, consistency between replicates and the potential for downstream analysis. DNA concentrations were determined to be the best universal monitoring method for complex environmental samples.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".