Understanding HIV reactivation and latency
Antiretroviral therapy is able to suppress HIV replication in most people living with HIV, so the virus becomes undetectable in blood. However, treatment must be continued for life in most cases, as the virus rapidly regrows from a latent reservoir if antiretroviral treatment is stopped. A number of drugs and interventions are being developed to reduce the size of the latent reservoir, to prevent or delay the regrowth of virus when antiretroviral treatment is stopped. However, measuring the levels of this latent virus and the effects of these anti-latency interventions is challenging. IAP collaborates with a number of experimental and clinical teams to use modelling to help us understand HIV latency and develop a functional cure for HIV.
We use mathematical modelling to estimate key parameters such as the rate of formation of the latent reservoir, durability of latency, and frequency of reactivation from latency. This helps us understand the natural history of latency. We can then apply these approaches to measure how anti-latency treatments and interventions affect these parameters. We collaborate with a number of experimentalists and clinicians both in Australia and around the world who provide data from animal studies and clinical trials testing different interventions.
We use a combination of mathematical modelling and viral sequence analysis to estimate the rate of HIV reactivation from latency and are exploring new ways to study this. In addition to analysing data from new studies, our expertise in mathematical modelling enables us to combine and re-apply data from previous studies towards novel questions. In this manner, we are able to accelerate the field forward while optimizing funding and resources.
We have provided the first direct estimate of how often HIV successfully ‘wakes up’ from latency after treatment interruption – and find this is only around once a week. We have worked with collaborators at the National Cancer Institute in the US to develop a novel ‘barcoded’ virus for studying latency in animals, finding that SIV (a primate version of HIV) wakes up more frequently. We have used this and other experimental models to study how drugs and antibodies affect latency.
The techniques we are developing will be essential for discovery and optimising application of new anti-latency interventions.
