Genetic and Chemical Screening in Human Blood Serum Reveals Unique Antibacterial Targets and Compounds against Klebsiella pneumoniae
Bibliographic record
Abstract
Antibiotics halt the growth of bacteria by targeting core, essential physiology that is required for life on standard microbiological media. Many more biochemical and virulence processes, however, are required for bacteria to cause infection in a host. Indeed, chemical inhibitors of the latter processes are overlooked using conventional antibiotic drug discovery approaches. Here, we use human blood serum as an alternative growth medium to explore new targets and compounds. High-throughput screening of genetic and chemical libraries identified compounds targeting biological activities required by Klebsiella pneumoniae to grow in serum, such as nucleobase biosynthesis and iron acquisition, and showed that serum can chemically transform compounds to reveal cryptic antibacterial activity. One of these compounds, ruthenium red, was effective in a rat bloodstream infection model. Our data demonstrate that human serum is an effective tool to find new chemical matter to address the current antibiotic resistance crisis.
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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 | 0.000 |
| 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 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".