ArticleMolecular cell2025
Mutability and hypermutation antagonize immunoglobulin codon optimality.
Article in Molecular cell, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Highlights of 2025: advances in germinal centers.Immunology and cell biology · 2026Review
- Immunoglobulin gene loci structure and diversity of raccoon dog (Nyctereutes procyonoides).BMC genomics · 2025Article
- Molecular characterization and complexity of the immunoglobulin repertoire in the silver-black fox (Vulpes vulpes).BMC veterinary research · 2025Article
- Structure and sequence engineering approaches to improve in vivo expression of nucleic acid-delivered antibodies.Molecular therapy : the journal of the American Society of Gene Therapy · 2025Article
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Authors and funding
17 authors.
Funding
Abstract
The efficacy of antibody responses is inherently linked to paratope diversity, as generated through V(D)J recombination and somatic hypermutation. Despite this, it is unclear how genetic diversification mechanisms evolved alongside codon optimality and affect antibody expression. Here, we analyze germline immunoglobulin (IG) genes, natural V(D)J repertoires, serum IgG, and monoclonal antibody (mAb) expression through the lens of codon optimality. Germline variable genes (IGVs) exhibit diverse optimality that is inversely related to mutability. Hypermutation deoptimizes heavy-chain (IGH) VDJ repertoires within human tonsils, bone marrow, lymph nodes (including SARS-CoV-2-specific clones), blood (HIV-1-specific clones), mice, and zebrafish. Analyses of mutation-affected codons show that targeting to complementarity-determining regions constrains deoptimization. Germline IGHV optimality correlates with serum variable fragment (VH) usage after influenza vaccination, while synonymous deoptimization attenuated mAb yield. These findings provide unanticipated insights into an antagonistic relationship between diversification mechanisms and codon optimality. Ultimately, the need for diversity takes precedence over that for the most optimal codon usage.
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Registered trials
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