Synergistic effect of UV-A and UV-C light is traced to UV-induced damage of the transfer RNA
Bibliographic record
Abstract
UV light emitting diodes (LEDs) are considered the new frontier of UV water disinfection. As UV technologies continue to evolve, so does the need to understand disinfection mechanisms to ensure that UV treatment continues to adequately protect public health. In this research, two Escherichia coli (E. coli) strains (the wild type K12 MG1655 and K12 SP11 (ThiI E342K)) were irradiated with UV-C at 268 nm both independently and after exposure to UV-A (365 nm). A synergistic effect was found on the viability of the wild type E. coli K12 strain when UV-A irradiation was applied prior to UV-C. Sublethal UV-A doses, which had a negligible effect on cell viability alone, enhanced UV-C inactivation by several orders of magnitude. This indicated a specific cellular response mechanism to UV-A irradiation, which was traced to direct photolysis of the transfer RNA (tRNA), which are critical links in the translation of messenger RNA to proteins. The wild type K12 strain MG1655, containing tRNAs with a thiolated uridine, directly absorbs the UV-A light, which leads to a reduction in protein synthesis, making them more susceptible to UV-C induced damage. However, the K12 strain SP11 (ThiI E342K), with a point mutation in the thiI gene that prevents a post-transcriptional modification of tRNA, experienced less inactivation upon subsequent irradiation by UV-C. The growth rate of cells, which was inhibited by sublethal UV-A doses, was not inhibited in this mutant strain with the modified tRNA. Time-lapse microscopy with microfluidics showed that sub-lethal UV-A caused a transient, reversible, growth arrest in E. coli. However, once the growth resumed, the cell division time resembled that of unirradiated cells. Damage induced by UV-A impaired the recovery of damage induced by UV-C. Depending on the UV-A dose applied, the synergistic effect remained even when there was a time delay of several hours between UV-A and UV-C exposures. The effect of sublethal UV-A was reversible over time; therefore, the synergistic effect was strongest when UV-C was applied immediately after UV-A. Combining UV-A and UV-C irradiation may serve as a practical tool to increase UV disinfection efficacy, which could potentially reduce costs while still adequately protecting public health.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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 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".