DOI: 10.5281/zenodo.17201048
title: Prevalent pemivibart escape constellations in global SARS-CoV-2 genomes (R346T, K444T, F456L, F486P)
title: Emergence of Pemivibart-Resistant SARS-CoV-2 Variants Harboring F456L and F486P in Early 2025 Danish Surveillance

description: PEMIVIBART ESCAPE MUTATION SUMMARY (2022 till 2024) (Early Chunk)============================================================

Input file: D:\tahirhb\pemivibart_escape_mutations.csvReport generated: pemivibart_escape_summary.py

Total sequences with ≥1 escape mutation: 33,372Total escape mutation events detected:      60,709

Mutation counts (Wuhan-Hu-1 numbering):   F456L:      8,631   R346T:     24,943   K444T:      7,860   F486P:     19,275

Sequences by number of escape mutations:  1 mutation:   11,935  2 mutations:   15,567  3 mutations:    5,840  4 mutations:       30

Top 10 sequences with most escape mutations:  1. USA/PR-CVL-022162/2024 → 4 mutations: F456L, F486P, K444T, R346T  2. USA/NMDOH-2023049605/2023 → 4 mutations: F456L, F486P, K444T, R346T  3. USA/NMDOH-2024010914/2024 → 4 mutations: F456L, F486P, K444T, R346T  4. USA/NY-PRL-231130_83E05/2023 → 4 mutations: F456L, F486P, K444T, R346T  5. USA/MN-MDH-38077/2023 → 4 mutations: F456L, F486P, K444T, R346T  6. USA/CO-CDPHE-41525514/2023 → 4 mutations: F456L, F486P, K444T, R346T  7. USA/CO-CDPHE-41556934/2023 → 4 mutations: F456L, F486P, K444T, R346T  8. USA/NJ-CDC-LC1073612/2023 → 4 mutations: F456L, F486P, K444T, R346T  9. USA/CO-CDPHE-41491811/2023 → 4 mutations: F456L, F486P, K444T, R346T  10. Denmark/DCGC-660941/2023 → 4 mutations: F456L, F486P, K444T, R346T

Interpretation:- Sequences with ≥2 mutations (e.g., F456L + R346T) are likely LP.8.1-like- Expected IC50 > 0.0189 µg/mL (probable)- F486P is rare but high-impact (predicted IC50 >> 0.04 µg/mL)-------------------------------------Early chunk of the bulk summary-------------------------------------

 
description: Targeted Investigation of Pemivibart (VYD222) Escape Mutations in SARS-CoV-2 Clinical Samples

This release documents a comprehensive analysis of Pemivibart escape mutations in SARS-CoV-2, focusing on the high-priority mutation constellation F456L + R346T + K444T + F486P.

Key Findings:





Sample ERR15656806 (hCoV-19/Denmark/DCGC-692746/2025) shows robust evidence of a partial but clinically relevant Pemivibart escape profile




Confirmed mutations: F456L and F486P - two potent Pemivibart resistance mutations




Absent mutations: R346T and K444T, with reference residues retained




High-quality data: ARTIC v3 amplicon sequencing with 1,694× mean depth



Lineage Classification & Significance:The detection of F456L+F486P in a 2025 Danish surveillance sample is epidemiologically significant. While the mutation pattern suggests XBB-lineage ancestry, the 2025 collection date indicates this represents either:





Persistent circulation of XBB-derived variants with key escape mutations




Convergent evolution where newer variants (potentially JN.1 descendants) independently acquired these resistance mutations




Recombinant variants maintaining these fitness-enhancing mutations



Technical Validation:Our pipeline successfully identified this constellation in contemporary surveillance data, demonstrating that Pemivibart resistance mutations continue to circulate and evolve. The ARTIC v3 amplicon approach provides high confidence in these variant calls.

Clinical Implications:This 2025 sample serves as critical evidence that:





Pemivibart resistance mutations persist in circulating populations




Continuous genomic surveillance is essential for monitoring therapeutic efficacy




Alternative evolutionary pathways can lead to similar escape profiles



All data and analysis code are included to support reproducibility and further investigation into antiviral resistance evolution in contemporary SARS-CoV-2 variants.

 

Study by: TahirHB@Hotmail.Com
description: In prior investigations, we conducted extensive reanalysis of multiple publicly available SRA datasets from 2023 (including ERR13079612 and related accessions) using our validated local surveillance pipeline comprising read alignment (BWA-MEM), variant calling (iVar and bcftools), consensus generation, codon-aware CDS translation, and escape mutation screening against the Pemivibart resistance constellation (R346T, K444T, F456L, F486P, among others).

Despite high coverage depth (>1,000×) and stringent quality thresholds, these SRA-derived runs consistently failed to detect the expected escape mutations, even though the same sample was reported in our surveillance pipeline as harboring such variants.

We systematically ruled out technical causes including reference bias, alignment artifacts, low-frequency variant filtering, and FASTQ quality degradation yet the discrepancy persisted in later analysis.

This contrasted sharply with our analysis of freshly processed, high-integrity samples like ERR15656806 (hCoV-19/Denmark/DCGC-692746/2025), where F456L and F486P were robustly observed, confirming both our pipeline’s sensitivity and the biological reality of Pemivibart-resistant lineages emerging in even early 2025.

The failure to recover the same mutations in historical SRA runs despite identical bioinformatic procedures highlights potential limitations in probably legacy submission data, including possible consensus masking, incomplete metadata, or post-hoc filtering in public archives that may obscure critical therapeutic escape signatures or perhaps data / folder restructuring even.