A Sorting Signal Suppresses IFITM1 Restriction of Viral Entry
Bibliographic record
Abstract
The interferon-induced transmembrane proteins (IFITMs) broadly inhibit virus infections, particularly at the viral entry level. However, despite this shared ability to inhibit fusion, IFITMs differ in the potency and breadth of viruses restricted, an anomaly that is not fully understood. Here, we show that differences in the range of viruses restricted by IFITM1 are regulated by a C-terminal non-canonical dibasic sorting signal KRXX that suppresses restriction of some viruses by governing its intracellular distribution. Replacing the two basic residues with alanine (KR/AA) increased restriction of jaagsiekte sheep retrovirus and 10A1 amphotropic murine leukemia virus. Deconvolution microscopy revealed an altered subcellular distribution for KR/AA, with fewer molecules in LAMP1-positive lysosomes balanced by increased levels in CD63-positive multivesicular bodies, where jaagsiekte sheep retrovirus pseudovirions are colocalized. IFITM1 binds to cellular adaptor protein complex 3 (AP-3), an association that is lost when the dibasic motif is altered. Although knockdown of AP-3 itself decreases some virus entry, expression of parental IFITM1, but not its KR/AA mutant, potentiates inhibition of viral infections in AP-3 knockdown cells. By using the substituted cysteine accessibility method, we provide evidence that IFITM1 adopts more than one membrane topology co-existing in cellular membranes. Because the C-terminal dibasic sorting signal is unique to human IFITM1, our results provide novel insight into understanding the species- and virus-specific antiviral effect of IFITMs.
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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 | 0.001 |
| 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".