In search of Broad Applicable, Small Molecule Inhibitors of Salmonella Biofilm Formation. (ICAR2010)
Bibliographic record
Abstract
Salmonella is one of the leading causes of foodborne infections worldwide. A major difficulty in the prevention and treatment of Salmonella infections is the fact that Salmonella is able to form biofilms on various biotic and abiotic surfaces. Biofilms are multicellular structures, in which the bacteria live in a self-produced gel-like matrix. Within these biofilms, Salmonella is protected against a wide range of environmental influences such as desiccation, antibiotics, disinfectants and the host immune system. As such, biofilm formation is an important survival strategy of Salmonella, both in- and outside the host. Therefore, the prevention and/or eradication of these biofilms could be an effective way to limit the spread of Salmonella. To identify new Salmonella biofilm inhibitors we conducted a high-throughput screening (using the ‘Calgary Biofilm device’) of a compound library, consisting of > 20.000 small molecules, in search of Salmonella biofilm inhibitors which are active at a temperature ranging from 16 °C to 37 °C, and therefore have potential to be used both in- and outside the host. The library contains a broad range of compounds, selected on their possible drug ability. The compounds have a molecular weight between 200 and 500 dalton and the screening was executed both at 16 °C and 37 °C, with a compound concentration between 20 µM and 50 µM. We aim at identifying compounds that inhibit biofilm formation, but that do not kill the bacteria. In this way, the development of resistance, which is a major drawback of classical antibiotics, is less likely. As such, these biofilm inhibitors could be a sustainable alternative in the production of safe and healthy food. Out of the 20.000 compounds tested, we identified 144 (0.72 %) possible biofilm inhibitors (‘hits’), of which 68 are active at 16 °C, 34 compounds at 37 °C, and 38 compounds are active at both temperatures. Subsequently, the dose-response relationship of the ‘hits’ was determined, as well as the effect of the compounds on the planktonic growth of Salmonella, using a ‘bioscreen’ (Labsystems). The compounds with maximum biofilm inhibitory activity and minimal effect on planktonic growth, were studied further, both with respect to prevention and destruction of biofilms from Salmonella Typhimurium and Pseudomonas aeruginosa, at different temperatures (16 °C, 25 °C, 30 °C and 37 °C). Using these results we identified 9 ‘lead’ families, from which analogues were purchased (± 20 analogues/family resulting in a library of 184 analogues). Using these analogues the “structure-activity relationship” of the ‘leads’ will be determined, to select and/or optimize the most potent compounds. This will yield several ‘lead-compounds’. From these ‘lead-compounds’ the activity in different in vitro and in vivo test systems will be determined, as well as the ‘Mode of Action’.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".