April 12, 2021
By Julie Gould
Jenn Zerbato, PhD, post-doctoral research fellow, Peter Doherty Institute for Infection and Immunity, breaks down why HIV RNA could serve as a better measure of efficient latency reversal in both pre-clinical and clinical assessment of latency reversing agents (LRAs).
What existing data led you and your co-investigators to conduct this research?
It has been a longstanding question in the field as to how to best measure latency reversal efficacy both in vitro and in vivo. One common way is to measure the viral RNA within the infected cell as this can tell us if the latency of the provirus is being reversed. There are many differently spliced variants of HIV RNA found inside the infected cell. Most clinical studies to date have measured the unspliced variant of cell associated HIV RNA and often find that LRAs in clinical assessment increase this form of HIV RNA, however, they do not have an effect of the size of the latent reservoir, suggesting that unspliced HIV RNA may not be the best measure of latency reversal. We wanted to know if a different form of HIV RNA known as multiply spliced (Tat-rev) HIV RNA could serve as a better measure of efficient latency reversal in both pre-clinical and clinical assessment of LRAs.
Please briefly describe your study and its findings. Were any of the outcomes particularly surprising?
In this study, we used three different measures of latency reversal, unspliced and multiply spliced cell-associated HIV RNA as well as supernatant HIV RNA (a measure of the release of virus from the infected cell). We sought to try and better understand which measure of latency reversal was the best measure following treatment with an LRA. As viral proteins and/or virus production are required for immune mediated killing, we focused on correlations of unspliced and multiply spliced HIV RNA with supernatant RNA. Our data showed whilst is it much harder to induce multiply spliced HIV RNA with different LRAs, we found that increases in multiply spliced HIV RNA strongly associated with increases in supernatant HIV RNA whereas unspliced HIV RNA did not. This therefore suggests that multiply spliced HIV RNA is a better marker of efficient latency reversal.
What are the possible real-world applications of these findings in clinical practice?
The most practical applications for our findings are in the pre-clinical and clinical assessment of novel LRAs. Based on these data, measurement of multiply spliced HIV RNA should be included in all studies assessing latency reversal. We now include multiply spliced HIV RNA as a standard measure in all of our LRA analyses and will be incorporating this into future clinical studies.
Do you and your co-investigators intend to expand upon this research?
In our future studies we aim to understand why some LRAs induced the production of multiply spliced HIV RNA very efficiently, while others did not. This information will be critical in further elucidating the mechanisms of latency reversal and will help in the design of better LRAs.
Is there anything else pertaining to your research and findings that you would like to add?
It is important for us to acknowledge the critical role that people living with HIV play in our studies. Without their generous donation of blood, tissue samples, and their time, our studies would simply not be possible.
About Dr Zerbato
Jenn Zerbato is a post-doctoral research fellow in Professor Sharon Lewin’s lab at the Peter Doherty Institute for Infection and Immunity. Jenn joined her lab in January of 2017 after earning a PhD at the University of Pittsburgh in Pittsburgh, PA USA. During her PhD, Jenn studied HIV latency, specifically the establishment and reversal of HIV latency in specific CD4+ T cell subsets. Jenn did not know Sharon at the of joining her lab, however, she knew of her world class reputation and her research and wanted to have an exciting and new experience for Jenn’s post-doc.
Zerbato JM, Khoury G, Zhao W, et al. Multiply spliced HIV RNA is a predictive measure of virus production ex vivo and in vivo following reversal of HIV latency. EBioMedicine. 2021;65:103241. doi:10.1016/j.ebiom.2021.103241