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Mutability and hypermutation antagonize immunoglobulin codon optimality (preprint)
biorxiv; 2024.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2024.03.13.584690
ABSTRACT
The efficacy of polyclonal antibody responses is inherently linked to paratope diversity, as generated through V(D)J recombination and somatic hypermutation (SHM). These processes arose in early jawed vertebrates; however, little is known about how immunoglobulin diversity, mutability, and hypermutation have evolved in tandem with another more ubiquitous feature of protein-coding DNA - codon optimality. Here, we explore these relationships through analysis of germline IG genes, natural V(D)J repertoires, serum VH usage, and monoclonal antibody (mAb) expression, each through the lens of multiple optimality metrics. Strikingly, proteomic serum IgG sequencing showed that germline IGHV codon optimality positively correlated with VH representation after influenza vaccination, and in vitro, codon deoptimization of mAbs with synonymous amino acid sequences caused consistent expression loss. Germline V genes exhibit a range of codon optimality that is maintained by functionality, and inversely related to mutability. SHM caused a load-dependent deoptimization of IGH VDJ repertoires within human tonsils, bone marrow, and lymph nodes (including SARS-CoV-2-specific clones from mRNA vaccinees), influenza-infected mice, and zebrafish. Comparison of natural mutation profiles to true random suggests the presence of selective pressures that constrain deoptimization. These findings shed light on immunoglobulin evolution, providing unanticipated insights into the antagonistic relationship between variable region diversification, codon optimality, and antibody secretion; ultimately, the need for diversity takes precedence over that for the most efficient expression of the antibody repertoire.
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Full text: Available Collection: Preprints Database: bioRxiv Main subject: Influenza, Human Language: English Year: 2024 Document Type: Preprint

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Full text: Available Collection: Preprints Database: bioRxiv Main subject: Influenza, Human Language: English Year: 2024 Document Type: Preprint