Shigella Mutant with Truncated O-Antigen as an Enteric Multi-Pathogen Vaccine Platform
Bibliographic record
Abstract
Background/Objectives: Rising antibiotic resistance underscores the urgent need for effective vaccines against shigellosis. Our previous research identified the Shigella flexneri 2a truncated mutant (STM), a wzy gene knock-out strain cultivated in shake-flasks, as a promising broadly protective Shigella vaccine candidate. Expanding on this finding, our current study explores the feasibility of transitioning to a fermentor-grown STM as a vaccine candidate for further clinical development. Methods: The STM and STM-Cj, engineered to express the conserved Campylobacter jejuni N-glycan antigen, were grown in animal-free media, inactivated with formalin, and evaluated for key antigen retention and immunogenicity in mice. Results: The fermentor-grown STM exhibited significantly increased production yields and retained key antigens after inactivation. Immunization with the STM, particularly along with the double-mutant labile toxin (dmLT) adjuvant, induced robust immune responses to the conserved proteins IpaB, IpaC, and PSSP-1. Additionally, it provided protection against homologous and heterologous Shigella challenges in a mouse pulmonary model. The STM-Cj vaccine elicited antibody responses specific to the N-glycan while maintaining protective immune responses against Shigella. These findings underscore the potential of the fermentor-grown STM as a safe and immunogenic vaccine platform for combating shigellosis and possibly other gastrointestinal bacterial infections. Conclusions: Further process development to optimize growth and key antigen expression as well as expanded testing in additional animal models for the assessment of protection against Shigella and Campylobacter are needed to build on these encouraging initial results. Ultimately, clinical trials are essential to evaluate the efficacy and safety of STM-based vaccines in humans.
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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 | 0.000 | 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".