Gene Conversion-Like Events in the Diversification of Human Rearranged IGHV3-23*01 Gene Sequences

Abstract

Gene conversion (GCV), a mechanism mediated by activation-induced cytidine deaminase (AID) is well established as a mechanism of immunoglobulin diversification in a few species. However, definitive evidence of GCV-like events in human immunoglobulin genes is scarce. The lack of evidence of GCV in human rearranged immunoglobulin gene sequences is puzzling given the presence of highly similar germline donors and the presence of all the enzymatic machinery required for GCV. In this study, we undertook a computational analysis of rearranged IGHV3-23*01 gene sequences from common variable immunodeficiency (CVID) patients, AID-deficient patients, and healthy individuals to survey “GCV-like” activities. We analyzed rearranged IGHV3-23*01 gene sequences obtained from total PBMC RNA and single-cell polymerase chain reaction of individual B cell lysates. Our search identified strong evidence of GCV-like activity. We observed that GCV-like tracts are flanked by AID hotspot motifs. Structural modeling of IGHV3-23*01 gene sequence revealed that hypermutable bases flanking GCV-like tracts are in the single stranded DNA (ssDNA) of stable stem-loop structures (SLSs). ssDNA is inherently fragile and also an optimal target for AID. We speculate that GCV could have been initiated by the targeting of hypermutable bases in ssDNA state in stable SLSs, plausibly by AID. We have observed that the frequency of GCV-like events is significantly higher in rearranged IGHV3-23-*01 sequences from healthy individuals compared to that of CVID patients. We did not observe GCV-like events in rearranged IGHV3-23-*01 sequences from AID-deficient patients. GCV, unlike somatic hypermutation (SHM), can result in multiple base substitutions that can alter many amino acids. The extensive changes in antibody affinity by GCV-like events would be instrumental in protecting humans against pathogens that diversify their genome by antigenic shift.

Immunoglobulin gene conversion identification and analysis

“…Immunoglobulin gene conversion (GC) events are common in some organisms, such as rabbit [18] and chicken [18], while there is some evidence that it rarely occurs in human [8,9]. Despite the fact that studies have analyzed GC events from limited sequencing data, there does not exist a tool for identifying gene conversio in immunoglobulin sequences.…”

“…Lavinder et al, 2014 [18] approach analyzing GC using a variation of the GENECONV permutation test. Duvvuri et al, 2012 [9] use two approaches: GENECONV [23] and visual assessment.…”

“…Other studies use visual inspection in a multiple sequence alignment to confirm their suspicion of gene conversion events. Lavinder et al, [18] recreated an internal version of GENECONV for their study, while Winstead et al, [30] used visual inspection, and Duvvuri et al, [9] used both GENECONV and visual inspection. Visual inspection is low throughput and unable to systematically characterize repertoire level patterns of gene conversion, in addition to not providing a formal framework for their identification.…”

Kinetic models reveal the in vivo mechanisms of mutagenesis in microbes and man

“…Kim et al [14] have used mfg for analyses of transcription-associated mutations, and suggest that the genome sequence has evolved to increase protein evolvability under stress. In mfg analyses of human rearranged IGHV3-2301 gene sequences Duvvuri et al [20] found that hypermutable bases were located in the ssDNA of stable SLSs.…”

“…However, models are only valid and useful if they have demonstrated predictive value. Kinetic models created by our computer program, mfg , have frequently demonstrated predictive value in the analyses of mutagenesis in three very different systems: Escherichia coli [11–15], the p53 tumor suppressor gene [10, 16], and in somatic hypermutation (SHM) during the immune response [17–20]. In these analyses, mutation frequencies were determined experimentally during transcription and during mfg -simulated transcription in order to predict: (1) the location of mutable bases in loops of high-stability secondary structures, and (2) the effects of transcription, supercoiling, and secondary structure stabilities on base mutability.…”