Comparison of decoy and antisense transcripts to inhibit HIV-1 replication by gene transfer

Major targets for anti-HIV gene therapy are the conserved regulatory sequences on the HIV-1 genome and mRNA, the transactivation response (TAR) region and the Rev response element (RRE). The viral regulatory protein Tat binds to TAR as an elongation factor to increase HIV-1 RNA transcription after proviral activation. The RRE is the binding site for the viral protein Rev, which transports singly and unspliced transcripts out of the nucleus. Both systems are required for production of new virions, making them attractive targets for gene therapy to decrease viral load in HIV+ patients. Antisense and sense (decoy) transcripts targeting these two regions have been shown to inhibit the production of virions after infection in vitro, as determined by p24 production and reverse transcriptase activity. Retroviral vectors were using a tRNA promoter to express decoy and antisense TAR, alone or in combination with decoy RRE. A major limitation of this approach is that at increasing multiplicities of infection and increasing lengths of time of infection, the protection lessens, perhaps due to insufficient levels of the therapeutic transcript. To overcome this, new antisense TAR constructs were developed with predicted stem-loop structures that may prevent RNA degradation and enhance accumulation of the antisense RNA within the cell. These vectors were compared during in vitro infections and determined that the single gene decoy transcripts (RRE or TAR alone) without added secondary structure confer the most protection to both a T cell line and primary peripheral blood lymphocytes. Furthermore, the decoy RRE was shown to have significant levels of accumulation in the nucleus as well as cytoplasm, while TAR-based transcripts were located only in the cytoplasm, a characteristic that may impact efficacy. In addition to the comparison of anti-HIV retroviral vectors, the gene expression of retrovirally-transduced and G418-selected cell lines was analyzed using the newly-developed cDNA microarray. Although expression differences were detected in various cell-cycle associated genes, reproducibility was discovered to be a major issue in analyzing microarray data.