Characterization and Functional Activity of Murine Monoclonal Antibodies Specific for α1,6-Glucan Chain of Helicobacter pylori Lipopolysaccharide
Bibliographic record
Abstract
BACKGROUND: The outer core region of H. pylori lipopolysaccharide (LPS) contains α1,6-glucan previously shown to contribute to colonizing efficiency of a mouse stomach. The aim of the present study was to generate monoclonal antibodies (mAbs) specific for α1,6-glucan and characterize their binding properties and functional activity. MATERIALS AND METHODS: BALB/c mice were injected intraperitoneally with 10(8) formalin-fixed H. pylori O:3 0826::Kan cells 3× over 56 days to achieve significant titer. Anti-α1,6-glucan-producing hybridomas were screened by indirect ELISA using purified H. pylori O:3 0826::Kan LPS. One clone, 1C4F9, was selected for further characterization. The specificities of mAbs were determined by indirect and inhibition ELISA using structurally defined H. pylori LPS and synthetic oligosaccharides, and whole-cell indirect ELISA (WCE) of clinical isolates. They were further characterized by indirect immunofluorescent (IF) microscopy and their functional activity in vitro determined by serum bactericidal assays against wild-type and mutant strains of H. pylori. RESULTS: The generated anti-α1,6-glucan IgM, 1C4F9, has demonstrated an excellent specificity for the glucan chain containing 5 to 6 α1,6-linked glucose residues and showed surface accessibility by IF microscopy with H. pylori cells adherent to gastric adenocarcinoma cells monolayers. Of 38 isolates from Chile, 17 strains reacted with antiglucan mAbs in WCE (OD450 ≥ 0.2). Bactericidal activity was observed against selective wild-type and mutant H. pylori strains exhibiting OD450 values of ≥ 0.45 in WCE. CONCLUSIONS: Anti-α1,6-glucan mAbs could have potential application in typing and surveillance of H. pylori isolates as well as offer insights into structural requirements for the development of LPS-based vaccine against H. pylori infections.
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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) | 0.001 | 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".