Reformulating Surfactant for the Delivery of Cathelicidins
Bibliographic record
Abstract
Background The complex branching structure of the lung makes direct delivery of drugs, such as the antimicrobial peptides cathelicidins, to the small and distal airways a major challenge. To address this issue our lab has been investigating the use of exogenous surfactant (BLES), to facilitate the pulmonary delivery of cathelicidins. BLES is a lipoprotein complex capable of spreading through the lung. Its major lipid components are phosphatidylglycerol (PG; 10%), phosphatidylcholine (PC; 40%) and dipalmitoylphosphatidylcholine (DPPC;40%). Although, BLES in combination with cathelicidins has shown promising results, the presence of BLES has also been shown to significantly reduce the ability of these peptides to kill bacteria. Objectives 1) Determine the lipid components of BLES that are limiting the bactericidal effects of cathelicidins, 2) reconstitute BLES to reduce its inhibitory effect on the antimicrobial properties of cathelicidins, and 3) assess the spreading and bacterial killing of reformulated BLES/cathelicidin preparations at a distal site. Hypothesis A reformulated BLES will improve the bacterial killing of BLES/cathelicidin mixtures, without reducing spreading to distal sites in vitro . Methods Antimicrobial assays were performed against a lab strain of Pseudomonas aeruginosa for four cathelicidins in the presence of individual surfactant lipids. BLES was also supplemented with different lipids to generate different relative amounts of PG (5–40%), PC (20–70%) and DPPC (20–70%). These different versions of BLES were combined with cathelicidins for bacterial killing curves and assessment on our newly developed wet bridge transfer system. This in vitro system was utilized to assess spreading and bacterial killing at distal sites. P. aeruginosa was seeded to the distal well and cathelicidins alone or resuspended in a reformulated BLES were administered to the delivery well. Results At concentrations found in BLES, PG was the only lipid component to significantly inhibit the bacterial killing of all cathelicidins tested. Furthermore, all reformulated surfactant preparations with lower PG concentrations than BLES were shown to significantly enhance peptide function compared to BLES. Experiments performed on the wet bridge transfer system showed that altering BLES to limit PG content (6–9%) significantly enhanced bacterial killing in the distal dish for suspended cathelicidins compared to BLES/cathelicidin. However, reducing the PG content of BLES to 5% was shown to significantly inhibit its ability to spread across the wet bridge transfer system. Moreover, when combined with cathelicidins it was shown have significantly lower bacterial killing in the distal dish compared to BLES. Discussion These results suggest that PG is the major component of BLES inhibiting the bacterial killing properties of cathelicidins. Furthermore, the data from the wet bridge experiments indicated that altering the lipid composition of BLES to limit PG‐content creates a more effective cathelicidin/surfactant preparation. Therefore, future studies should utilize artificial surfactants with lower levels of PG to delivery cathelicidins to the peripheral airways. However, some PG may be needed for peptide transfer and normal surfactant function. Support or Funding Information Lawson Internal Research Fund This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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) | 0.000 | 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 | 0.001 | 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".