Genetic and Phenotypic Characterization of GII-4 Noroviruses That Circulated during 1987 to 2008
Bibliographic record
Abstract
The predominance and continual emergence of new variants in GII-4 noroviruses (NVs) in recent years have raised questions about the role of host immunity and histo-blood group antigens (HBGAs) in NV evolution. To address these questions, we performed a genetic and phenotypic characterization of GII-4 variants circulating in the past decade (1998 to 2008). Ninety-three GII-4 sequences were analyzed, and of them, 16 strains representing 6 genetic clusters were selected for further characterization. The HBGA binding properties were determined by both saliva- and oligosaccharide-binding assays using P particles as a model of NV capsid. The antigenic properties were also examined by enzyme immunoassay (EIA), Western blot analysis, and receptor blocking assay, using P-particle-specific antibodies from immunized mice and GII-4 virus-infected patients. Our results showed that 15 of the 16 GII-4 viruses bound to saliva of all A, B, and O secretors. Oligosaccharide binding assays yielded largely consistent results, although the binding affinities to some oligosaccharides varied among some strains. The only nonbinder had a mutation in the binding site. While antigenic variations were detected among the 16 strains, significant cross-blocking on the HBGA binding was also noted. Sequence alignment revealed high conservation of HBGA binding interfaces with some variations in adjacent regions. Taken together, our data suggested that the ability of GII-4 to recognize different secretor HBGAs persisted over the past decade, which may explain the predominance of GII-4 over other genotypes. Our data also indicated that both the host immunity and HBGAs play a role in NV evolution. While host immunity may continue driving NV for antigenic change, the functional selection by the HBGAs tends to lock the architecture of the capsid/HBGA interfaces and allows only limited variations outside the HBGA binding sites. A potential outcome of such counterselection between theses two factors in NV evolution is discussed.
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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 | 0.001 |
| 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".