henhaobio
Sign in

bioRxivMicrobiologyPreprint

AZD5582 robustly reactivates latently infected cells and clears the majority of those reactivated from the SIV reservoir

Tin PhaniD, Maud MavigneriD, Amir Dashti, Ann ChahroudiiD, Ruy Miguel RibeiroiD, Ruian KeiD, Alan S. PerelsoniD

PDFDOI

Abstract

AZD5582 (AZD) is a latency reversing agent used to support the "shock-and-kill" strategy in HIV-1 cure research. Previous studies in ART-suppressed rhesus macaques have shown that AZD can promote reactivation of latently infected cells, resulting in 2-3 log increases in on-ART viral load and significant reductions in SIV reservoir size over 5-10 doses. To quantify the impact of AZD on the reservoir, we developed an ensemble of mechanistic viral dynamic models and fit them to longitudinal plasma SIV RNA and SIV CA-DNA data from 23 macaques treated with AZD in combination with other therapies. The aggregate predictions of the model ensemble recapitulate the reactivation patterns observed in both SIV RNA and SIV CA-DNA and provide robust estimates of key parameters associated with reactivated cells. We found that AZD reactivates approximately 25% of cells in the latent reservoir per dose, with a mean reactivation duration of about 5-6 days. Of the reactivated cells, 60-79% are eventually cleared, while the remainder enter a state refractory to AZD stimulation before returning to latency. Because of this refractory state, each consecutive weekly dose reactivates about 28% fewer cells than the previous one, an effect that could be more pronounced if the refractory period substantially exceeds the interval between doses. However, the duration of this refractory state remains uncertain. Altogether, our results suggest that AZD-reactivated cells are effectively cleared. Future work should focus on improving LRAs that safely reactivate a larger fraction of the latent reservoir. Furthermore, designing experiments with varying dosing schedules can help better quantify the duration of refractoriness, which will be important for informing optimal treatment schedules and maximizing the effect of LRAs.

Citations
0

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.