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An in vivo model for HIV resistance development
B Zuber1, D Böttiger, R Benthin
1Virology Department, Swedish Institute for Infectious Disease Control, 171 82 Solna, Sweden. bartek.zuber@smi.ki.se
AIDS Research and Human Retroviruses
|May 26, 2001
Summary
Developing an animal model is crucial for studying drug resistance in human immunodeficiency virus (HIV-1). This study demonstrates that a monkey model using RT-SHIV can effectively replicate HIV-1 nevirapine resistance, aiding therapy development.
Area of Science:
- Virology
- Pharmacology
- Animal Models
Background:
- Antiretroviral therapy for HIV-1 rapidly selects for drug-resistant strains.
- Developing reliable animal models is essential for studying the emergence and reversal of drug resistance.
- A hybrid simian-human immunodeficiency virus (SHIV) with HIV-1 reverse transcriptase (RT) was previously established.
Purpose of the Study:
- To evaluate a monkey model using RT-SHIV for studying drug resistance development.
- To investigate the emergence of nevirapine resistance in cynomolgus monkeys infected with RT-SHIV.
- To assess the impact of nevirapine dosage and therapy interruptions on resistance mutations.
Main Methods:
- Cynomolgus monkeys infected with RT-SHIV were treated with nevirapine.
- Drug administration mimicked clinical nevirapine monotherapy duration (2-3 weeks).
- Selection of drug-resistant mutations and monitoring of viral populations were performed.
Main Results:
- Nevirapine treatment selected for RT mutations Y181C and K103N, mirroring HIV-1 resistance mutations.
- Mutant and wild-type viruses coexisted, allowing monitoring of resistance dynamics.
- Low-dose nevirapine was not more effective in inducing mutations than a virus-inhibiting dose.
- Structured therapy interruptions were feasible within the model.
Conclusions:
- The RT-SHIV monkey model provides a viable in vivo system for studying HIV-1 drug resistance.
- This model can be used to assess the effects of various therapies on resistance development.
- Understanding resistance dynamics is critical for optimizing HIV-1 treatment strategies.