Comparative Genomics of Viral Genomes and Identification of Three Novel Viroporin-Like Superfamilies
Bibliographic record
Abstract
INTRODUCTION: Viroporins are small multifunctional proteins that modify cellular membranes facilitating processes such as viral nucleic acid entry and the release of virions from infected cells. We are interested in studying the evolutionary relationships among these proteins, in particular their organization into families and superfamilies. METHODS: We applied a variety of computational strategies to perform comparative genomics analyses of 120 viral genomes, using the phylogenetic profile method. This allowed the identification of 12 families, organized into four functionally related groups. Additionally, we compiled a list of 40 families from the Transporter Classification Database (TCDB) with viroporin-like attributes (i.e., length ≤300 aas, similar topologies, and/or documented viroporin activities). We then used TCDB as a reference to search for evidence of homology among families. Our well-established bioinformatic pipeline for inference of homology included (1) sequence similarity, (2) compatibility of topology and hydropathy profiles, (3) similarity of family-based HMM profiles, (4) shared motifs, and (5) conserved domains. RESULTS: We were able to infer homology among 15 families, four of which (Vpu-C, p10 viroporin/GDU1, FAST, and R-FAST) expanded the established Influenza A/B Virus M2 Protein (M2) superfamily. The other families constituted three novel superfamilies: viroporin-1, consisting of three families (RVP10, NS3, and NSP4); viroporin-2, composed of two functionally linked families (SARS-VP and M-protein); and viroporin-3 composed of 3 functionally related families (viroporin E, IBV-E, and PRRSV). CONCLUSION: The application of comparative genomics and remote homology identification strategies allowed the classification of homologous and functionally related viroporin-like families into superfamilies. These results will be useful in future functional, mechanistic, and evolutionary studies of viroporins.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
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".