Chemical-genetic identification of the biochemical targets of polyalkyl guanidinium biocides
Bibliographic record
Abstract
Alkylated guanidinium compounds exhibit microbiocidal activity in marine environments, yet the mode of action of these compounds has not been defined. A comprehensive chemical-genetic approach in budding yeast was used to define the biological processes affected by these compounds. N-Butyl-N'-decylguanidinium and N-hexyl-N'-(3-hydroxypropyl)-N''-octylguanidinium chlorides were shown to prevent yeast growth in a dose-dependent manner. All non-essential genes required for tolerance of sub-lethal amounts of these biocides were identified. These unbiased and systematic screens reveal the two related guanidinium compounds have a non-overlapping spectrum of targets in vivo. A functional tryptophan biosynthetic pathway is essential for tolerance of both biocides, which identifies tryptophan amino acid import as one process affected by these compounds. Further analysis of hypersensitive gene lists demonstrates that the substitutions on alkylated guanidiums confer important functional differences in vivo: one derivative renders the ability to generate acidic vacuoles essential, while the other is synthetically lethal with mutants in the transcriptional response to chemical stress. Altogether the results define the common and distinct biological processes affected by biocidal alkylated guanidinium salts.
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 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) | 0.000 | 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 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".