The Spike Glycoprotein of Murine Coronavirus MHV-JHM Mediates Receptor-Independent Infection and Spread in the Central Nervous Systems of<i>Ceacam1a</i><sup>−/−</sup>Mice
Bibliographic record
Abstract
The MHV-JHM strain of the murine coronavirus mouse hepatitis virus is much more neurovirulent than the MHV-A59 strain, although both strains use murine CEACAM1a (mCEACAM1a) as the receptor to infect murine cells. We previously showed that Ceacam1a(-/-) mice are completely resistant to MHV-A59 infection (E. Hemmila et al., J. Virol. 78:10156-10165, 2004). In vitro, MHV-JHM, but not MHV-A59, can spread from infected murine cells to cells that lack mCEACAM1a, a phenomenon called receptor-independent spread. To determine whether MHV-JHM could infect and spread in the brain independent of mCEACAM1a, we inoculated Ceacam1a(-/-) mice. Although Ceacam1a(-/-) mice were completely resistant to i.c. inoculation with 10(6) PFU of recombinant wild-type MHV-A59 (RA59) virus, these mice were killed by recombinant MHV-JHM (RJHM) and a chimeric virus containing the spike of MHV-JHM in the MHV-A59 genome (SJHM/RA59). Immunohistochemistry showed that RJHM and SJHM/RA59 infected all neural cell types and induced severe microgliosis in both Ceacam1a(-/-) and wild-type mice. For RJHM, the 50% lethal dose (LD(50)) is <10(1.3) in wild-type mice and 10(3.1) in Ceacam1a(-/-) mice. For SJHM/RA59, the LD(50) is <10(1.3) in wild-type mice and 10(3.6) in Ceacam1a(-/-) mice. This study shows that infection and spread of MHV-JHM in the brain are dependent upon the viral spike glycoprotein. RJHM can initiate infection in the brains of Ceacam1a(-/-) mice, but expression of mCEACAM1a increases susceptibility to infection. The spread of infection in the brain is mCEACAM1a independent. Thus, the ability of the MHV-JHM spike to mediate mCEACAM1a-independent spread in the brain is likely an important factor in the severe neurovirulence of MHV-JHM in wild-type mice.
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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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".