Hybrid antigens expressing surface loops of BauA from Acinetobacter baumannii are capable of inducing protection against infection
Bibliographic record
Abstract
Acinetobacter baumannii is a human bacterial pathogen of increasing concern in clinical settings due to the emergence of antibiotic resistant strains and the lack of effective therapeutics. Researchers have been exploring new treatment options such as novel drug candidates and vaccines to prevent severe infections and mortality. Bacterial surface antigens that are essential to A. baumannii for acquiring micronutrients (e.g. iron, zinc) from nutrient restricted environments are being considered as targets for vaccines or immunotherapy due to their crucial role for growth and pathogenesis in the human host. BauA, the outer membrane receptor for the siderophore acinetobactin was targeted for vaccine development in this study. Due to challenges in the commercial production of membrane proteins for vaccines, a novel hybrid antigen method developed by our group was used. Exposed loops of BauA were selected and displayed on a foreign scaffold to generate novel hybrid antigens designed to elicit an immune response against the native BauA protein. The potential epitopes were incorporated into a scaffold derived from the C-lobe of Neisseria meningitidis transferrin binding protein B (TbpB), named the loopless C-lobe (LCL). Hybrid proteins displaying three selected loops (5, 7 and 8) individually or in combination were designed and produced and evaluated in an A. baumannii murine sepsis model as vaccine antigens. Immunization with the recombinant BauA protein protected 100% of the mice while immunization with hybrid antigens displaying individual loops achieved between 50 and 100% protection. The LCL scaffold did not induce a protective immune response, enabling us to attribute the observed protection elicited by the hybrid antigens to the displayed loops. Notably, the mice immunized with the hybrid antigen displaying loop 7 were completely protected from infection. Taken together, these results suggest that our hybrid antigen approach is a viable method for generating novel vaccine antigens that target membrane surface proteins necessary for bacterial growth and pathogenesis and the loop 7 hybrid antigen can be a foundation for approaches to combat A. baumannii infections.
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) | 0.001 | 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".