Table 3 Models addressing the effects of MME reconfiguration of HIV gene-expression

From: Mathematical modeling and mechanisms of HIV latency for personalized anti latency therapies

 

Study

Aims

Data

Results

Latency Reversal

A. K. Chavali et al.30

Understand the factors and mechanisms related to the MME that modulate HIV gene-expression noise, eventually inducing latency-reversal upon induced MME reconfiguration.

LTR-driven GFP expression of 105 HIV-infected Jurkat T-cell clones upon Aza and TNF stimulation.

(i) The two- and three-state LTR models captures the mechanisms by which basal HIV gene-expression may induce latency-reversal; (ii) The Fano-factor proves to be a useful noise metric to compare models’ prediction. (iii) The three-state LTR model well captures changes in basal viral activity after LRAs-driven MMEs reconfigurations.

V. G. Wong et al.31

Understand the factors and mechanisms related to the MME that modulate HIV gene-expression noise, eventually inducing latency-reversal upon induced MME reconfiguration.

time-resolved, single-cell transcriptional data over multiple IS upon NF-κB stimulation.

(i) The TNF-induced increase of transcription variability at the provirus level is higher than its mean HIV transcripts count; (ii) TNF-induced NF-kb activation correlates with latency-reversal. (iii) NF-kb levels, must be combined with chromatin structure and RNAPII regulation to explain the observed provirus-specific variability

Y. Cao et al.34

(i) Identify targetable key reactions critical for Tat-amplification to shorten stochastic delays and speed-up latency reversal; (ii) Build HIV gene-expression model for in-silico LRAs efficacy testing

Parameters estimates taken from the literature

(i) The Tat circuit exhibits a bimodal probability landscape, where a peak is associated with latency, and another with the active fate; (ii) Enhancing Tat acetylation may increase Tat and viral production; (iii) Increasing the binding affinity between the LTR and Tat may induce an easier transition to the viral-phase; (i) Adopting a modeling framework is a valid approach to search and discovery potentially effective therapeutic strategies and compounds