A highly immunogenic vaccine platform against encapsulated pathogens using chimeric probiotic Escherichia coli membrane vesicles
Bibliographic record
Abstract
Abstract Vaccines against infectious diseases should elicit potent and long-lasting immunity, ideally even in those with age-related decline in immune response. Here we report a rational polysaccharide vaccine platform using probiotic Escherichia coli-derived membrane vesicles (MVs). First, we constructed a probiotic E. coli clone harboring the genetic locus responsible for biogenesis of serotype 14 pneumococcal capsular polysaccharides (CPS14) as a model antigen. CPS14 was found to be polymerized and mainly localized on the outer membrane of the E. coli cells. The glycine-induced MVs displayed the exogenous CPS14 at high density on the outermost surface, on which the CPS14 moiety was covalently tethered to a lipid A-core oligosaccharide anchor. In in vivo immunization experiments, CPS14+MVs, but not a mixture of free CPS14 and empty MVs, strongly elicited IgG class-switch recombination with a Th1/Th2-balanced IgG subclass distribution without any adjuvant. In addition, CPS14+MVs were structurally stable with heat treatment and immunization with the heat-treated MVs-elicited CPS14-specific antibody responses in mouse serum to levels comparable to those of non-treated CPS14+MVs. Notably, the immunogenicity of CPS14+MVs was significantly stronger than those of two currently licensed vaccines against pneumococci. The CPS14+MV-elicited humoral immune responses persisted for 1 year in both blood and lung. Furthermore, the CPS14+MV vaccine was widely efficacious in mice of different ages. Even in aged mice, vaccination resulted in robust production of CPS14-specific IgG that bound to the pneumococcal cell surface. Taken together, the present probiotic E. coli MVs-based vaccine platform offers a promising, generalizable solution against encapsulated pathogens.
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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) | 0.000 | 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".