Comprehensive Mapping of Receptor-Functioning Domains in Feline Leukemia Virus Subgroup C Receptor FLVCR1
Bibliographic record
Abstract
Infection of cells by the highly anemogenic feline leukemia virus subgroup C (FeLV-C) is mediated by the heme exporter FLVCR1, a cell surface protein containing 12 potential transmembrane segments with six presumptive extracellular loops (ECLs). To identify FLVCR1 residues critical for mediating FeLV-C infection, we first independently isolated a human cDNA encoding the FLVCR2 protein that shares 52% identity to human FLVCR1, and we show that FLVCR2 does not function as a receptor for FeLV-C. Then, by generating specific hybrids between FLVCR1 and FLVCR2 and testing susceptibility of mouse cells expressing these hybrids to beta-galactosidase encoding FeLV-C, we identify FLVCR1 ECLs 1 and 6 as critical for mediating FeLV-C infection. Mouse cells expressing a hybrid protein containing FLVCR2 backbone with the ECL6 sequence from FLVCR1 were highly susceptible to FeLV-C infection. Using site-directed mutagenesis, we show that a single mutation of Asn463 in FLVCR2 ECL6 to an acidic Asp residue (a residue present in the corresponding position 487 in FLVCR1 ECL6) is sufficient to render FLVCR2 functional as an FeLV-C receptor. However, an Asp487Asn mutation in FLVCR1 ECL6 or substitution of the entire FLVCR1 ECL6 sequence for FLVCR2 ECL6 sequence does not disrupt receptor function. Subsequent substitutions show that residues within FLVCR1 ECL1 also contribute to mediating FeLV-C infection. Furthermore, our results suggest that FLVCR1 regions that mediate FeLV-C surface unit binding are distinct from ECL1 and ECL6. Our results are consistent with previous conclusions that infection of cells by gammaretroviruses involves interaction of virus with multiple receptor regions.
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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 | 0.001 |
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".