Identification of Residues Controlling Restriction versus Enhancing Activities of IFITM Proteins on Entry of Human Coronaviruses
Bibliographic record
Abstract
ABSTRACT Interferon-induced transmembrane proteins (IFITMs) are restriction factors that inhibit the infectious entry of many enveloped RNA viruses. However, we demonstrated previously that human IFITM2 and IFITM3 are essential host factors facilitating the entry of human coronavirus (HCoV) OC43. In a continuing effort to decipher the molecular mechanism underlying IFITM differential modulation of HCoV entry, we investigated the roles of structural motifs important for IFITM protein posttranslational modifications, intracellular trafficking, and oligomerization in modulating the entry of five HCoVs. We found that three distinct mutations in IFITM1 or IFITM3 converted the host restriction factors to enhance entry driven by the spike proteins of severe acute respiratory syndrome coronavirus (SARS-CoV) and/or Middle East respiratory syndrome coronavirus (MERS-CoV). First, replacement of IFITM3 tyrosine 20 with either alanine or aspartic acid to mimic unphosphorylated or phosphorylated IFITM3 reduced its activity to inhibit the entry of HCoV-NL63 and -229E but enhanced the entry of SARS-CoV and MERS-CoV. Second, replacement of IFITM3 tyrosine 99 with either alanine or aspartic acid reduced its activity to inhibit the entry of HCoV-NL63 and SARS-CoV but promoted the entry of MERS-CoV. Third, deletion of the carboxyl-terminal 12 amino acid residues from IFITM1 enhanced the entry of MERS-CoV and HCoV-OC43. These findings suggest that these residues and structural motifs of IFITM proteins are key determinants for modulating the entry of HCoVs, most likely through interaction with viral and/or host cellular components at the site of viral entry to modulate the fusion of viral envelope and cellular membranes. IMPORTANCE The differential effects of IFITM proteins on the entry of HCoVs that utilize divergent entry pathways and membrane fusion mechanisms even when using the same receptor make the HCoVs a valuable system for comparative investigation of the molecular mechanisms underlying IFITM restriction or promotion of virus entry into host cells. Identification of three distinct mutations that converted IFITM1 or IFITM3 from inhibitors to enhancers of MERS-CoV or SARS-CoV spike protein-mediated entry revealed key structural motifs or residues determining the biological activities of IFITM proteins. These findings have thus paved the way for further identification of viral and host factors that interact with those structural motifs of IFITM proteins to differentially modulate the infectious entry of HCoVs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".