A Simple and Reliable Strategy for BK Virus Subtyping and Subgrouping

Abstract

ABSTRACT BK virus (BKV)-associated diseases in transplant recipients are an emerging issue. However, identification of the various BK virus subtypes/subgroups is a long and delicate process on the basis of currently available data. Therefore, we wanted to define a simple and effective one-step strategy for characterizing all BK virus strains from the VP1 gene sequence. Based on the analysis of 199 available complete DNA VP1 sequences, phylogenetic trees, alignments, and isolated polymorphisms were used to define an effective strategy for distinguishing the 12 different BK virus subtypes/subgroups. Based on the 12 subtypes identified from the 199 complete BKV VP1 sequences (1,089 bp), 60 mutations that can be used to differentiate these various subtypes/subgroups were identified. Some genomic areas were more variable and comprised mutational hot spots. From a subregion of only 100 bp in the VP1 region (1977 through 2076), we therefore constructed an algorithm that enabled rapid determination of all BKV subtypes/subgroups with 99% agreement (197/199) relative to the complete VP1 sequence. We called this domain of the BK viral genome the BK typing and grouping region (BKTGR). Finally, we validated our viral subtype identification process in a population of 100 transplant recipients with 100% efficiency. The new simpler method of BKV subtyping/subgrouping reported here constitutes a useful tool for future studies that will help us to more clearly understand the impact of BKV subtypes/subgroups on diagnosis, infection, and BK virus-associated diseases.