Bovine leukemia virus (BLV) is closely related to human T-cell leukemia virus (HTLV) and is the etiological agent of enzootic bovine leukosis, a disease characterized by a highly extended course that often involves persistent lymphocytosis and culminates in B-cell lymphomas. BLV provirus remains integrated in cellular genomes, even in the absence of detectable BLV antibodies. Therefore, to understand the mechanism of BLV-induced leukemogenesis and carry out the selection of BLV-infected animals, a detailed evaluation of changes in proviral load throughout the course of disease in BLV-infected cattle is required. The aim of this study was to develop a new quantitative real-time polymerase chain reaction (PCR) method using Coordination of Common Motifs (CoCoMo) primers to measure the proviral load of known and novel BLV variants in clinical animals.
Degenerate primers were designed from 52 individual BLV long terminal repeat (LTR) sequences identified from 356 BLV sequences in GenBank using the CoCoMo algorithm, which has been developed specifically for the detection of multiple virus species. Among 72 primer sets from 49 candidate primers, the most specific primer set was selected for detection of BLV LTR by melting curve analysis after real-time PCR amplification. An internal BLV TaqMan probe was used to enhance the specificity and sensitivity of the assay, and a parallel amplification of a single-copy host gene (the bovine leukocyte antigen DRA gene) was used to normalize genomic DNA. The assay is highly specific, sensitive, quantitative and reproducible, and was able to detect BLV in a number of samples that were negative using the previously developed nested PCR assay. The assay was also highly effective in detecting BLV in cattle from a range of international locations. Finally, this assay enabled us to demonstrate that proviral load correlates not only with BLV infection capacity as assessed by syncytium formation, but also with BLV disease progression.
Using our newly developed BLV-CoCoMo-qPCR assay, we were able to detect a wide range of mutated BLV viruses. CoCoMo algorithm may be a useful tool to design degenerate primers for quantification of proviral load for other retroviruses including HTLV and human immunodeficiency virus type 1.