ANTIBIOTIC DISCOVERY AND INFECTION TREATMENT AND PREVENTION
Bibliographic record
Abstract
As antimicrobial resistance proliferates, standard treatments for bacterial infections are rendered ineffective. There is therefore a need to both prevent infections and develop new treatment options. This need is especially urgent for priority pathogens like methicillin-resistant strains of Staphylococcus aureus (MRSA). Developing new antibiotics is difficult for a variety of reasons, including virulence traits like the formation of biofilms, surface-associated bacterial communities that are less susceptible to antibiotics. Here we used biofilms to our advantage, since their formation is stimulated when bacteria are exposed to sub-lethal concentrations of antibiotics, allowing us to screen for compounds with antimicrobial activity that would be missed with traditional methods. Using this approach, we identified the anti-inflammatory compound BAY 11-7082 as an antibiotic. We showed that it inhibits growth of priority pathogens including MRSA and provide evidence to suggest it has a novel (and potentially multifaceted) mechanism. We also found it re-sensitizes MRSA to inexpensive and readily available β-lactam antibiotics like penicillin G. This finding was of particular interest since using antibiotic adjuvants in combination with existing antibiotics provides a promising and complementary strategy to antibiotic discovery. We showed that wall teichoic acids, polymer chains anchored to the S. aureus cell wall, were required for sensitization to occur; however, unlike existing adjuvants, BAY 11-7082 did not appear to impact cell morphology or division, suggesting it instead targets a factor of β-lactam resistance that may be less well understood. Lastly, we examined the impact of common surgical antiseptics on bacterial growth and biofilm formation, with a goal of preventing infections following joint replacement. We found these solutions to be effective; however, it is important to define the concentrations at which they inhibit microbial growth in vivo, since sub-lethal concentrations stimulate biofilm formation. Taken together, the findings in this thesis bolster our understanding of how to reduce and treat resistant infections.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".