Decreasing prevalence of transmitted drug resistance among ART-naive HIV-1-infected patients in Iceland, 1996-2012

Drug Resistance Mechanism of M46I-Mutation-Induced Saquinavir Resistance in HIV-1 Protease Using Molecular Dynamics Simulation and Binding Energy Calculation

Drug-resistance-associated mutation in essential proteins of the viral life cycle is a major concern in anti-retroviral therapy. M46I, a non-active site mutation in HIV-1 protease has been clinically associated with saquinavir resistance in HIV patients. A 100 ns molecular dynamics (MD) simulation and MM-PBSA calculations were performed to study the molecular mechanism of M46I-mutation-based saquinavir resistance. In order to acquire deeper insight into the drug-resistance mechanism, the flap curling, closed/semi-open/open conformations, and active site compactness were studied. The M46I mutation significantly affects the energetics and conformational stability of HIV-1 protease in terms of RMSD, RMSF, Rg, SASA, and hydrogen formation potential. This mutation significantly decreased van der Waals interaction and binding free energy (∆G) in the M46I–saquinavir complex and induced inward flap curling and a wider opening of the flaps for most of the MD simulation period. The predominant open conformation was reduced, but inward flap curling/active site compactness was increased in the presence of saquinavir in M46I HIV-1 protease. In conclusion, the M46I mutation induced structural dynamics changes that weaken the protease grip on saquinavir without distorting the active site of the protein. The produced information may be utilized for the discovery of inhibitor(s) against drug-resistant HIV-1 protease.

Transmitted drug resistance and transmission clusters among HIV-1 treatment-naïve patients in Guangdong, China: a cross-sectional study

BACKGROUND

Transmitted drug resistance (TDR) that affects the effectiveness of the first-line antiretroviral therapy (ART) regimen is becoming prevalent worldwide. However, its prevalence and transmission among HIV-1 treatment-naïve patients in Guangdong, China are rarely reported. We aimed to comprehensively analyze the prevalence of TDR and the transmission clusters of HIV-1 infected persons before ART in Guangdong.

METHODS

The HIV-1 treatment-naïve patients were recruited between January 2018 and December 2018. The HIV-1 pol region was amplified by reverse transcriptional PCR and sequenced by sanger sequencing. Genotypes, surveillance drug resistance mutations (SDRMs) and TDR were analyzed. Genetic transmission clusters among patients were identified by pairwise Tamura-Nei 93 genetic distance, with a threshold of 0.015.

RESULTS

A total of 2368 (97.17%) HIV-1 pol sequences were successfully amplified and sequenced from the enrolled 2437 patients. CRF07_BC (35.90%, 850/2368), CRF01_AE (35.56%, 842/2368) and CRF55_01B (10.30%, 244/2368) were the main HIV-1 genotypes circulating in Guangdong. Twenty-one SDRMs were identified among fifty-two drug-resistant sequences. The overall prevalence of TDR was 2.20% (52/2368). Among the 2368 patients who underwent sequencing, 8 (0.34%) had TDR to protease inhibitors (PIs), 22 (0.93%) to nucleoside reverse transcriptase inhibitors (NRTIs), and 23 (0.97%) to non-nucleoside reverse transcriptase inhibitors (NNRTIs). Two (0.08%) sequences showed dual-class resistance to both NRTIs and NNRTIs, and no sequences showed triple-class resistance. A total of 1066 (45.02%) sequences were segregated into 194 clusters, ranging from 2 to 414 sequences. In total, 15 (28.85%) of patients with TDR were included in 9 clusters; one cluster contained two TDR sequences with the K103N mutation was observed.

CONCLUSIONS

There is high HIV-1 genetic heterogeneity among patients in Guangdong. Although the overall prevalence of TDR is low, it is still necessary to remain vigilant regarding some important SDRMs.

The Estimation of Transmitted Drug Resistance Mutation Strains Probability in the Treatment of HIV Using the Beta-Binomial Model

The human immunodeficiency virus (HIV) is a viral infection that destroys the human immune system resulting in acquired immunodeficiency syndrome (AIDS). The Zambia HIV prevalence rate (11.3%) remains among the highest in the sub-Saharan Africa. In the treatment of HIV-naive patients, a problem that relates to the transmitted drug resistance mutation strains (TDRMs) occurs in the administration of antiretroviral (ARV) drugs. To address this problem, we propose the use of transition probabilities when prescribing a switch from the first-line to the second-line or to the third-line regimen on the ARV drugs combination. We formulate a statistical technique to determine an optimal ARV drugs combination. To compute a transition probability matrix chart on ARV drugs combinations of the first-line and second-line regimens, we apply a beta-binomial hierarchical model on HIV data. The transition probability matrices corresponding to the ARV drugs combinations TDF+ETC+NVP, TDF+FTC+EFV, AZT+3TC+NVP, AZT+3TC+EFV, D4T+3TC+NVP, and D4T+3TC+EFV provide an upper triangular matrix of probabilities. We observe a higher probability of remaining in the same regimen state than moving to another state. A transition probability chart provides information on the most effective combination to prescribe to a patient in the presence of transmitted drug resistance mutation (TDRM) test results. The transmission probabilities play a major role in aiding the physicians make an informed decision to prescribe an optimal ARV drugs combination. We suggest a TDRM test to be carried out to all newly diagnosed HIV individuals before prescribing any of the ARV drugs combination.

Epidemiological surveillance of HIV-1 transmitted drug resistance among newly diagnosed individuals in Shijiazhuang, northern China, 2014-2015

BACKGROUND

The widespread use of antiretroviral therapy (ART) has led to considerable concerns about the prevalence of transmitted drug resistance (TDR). Sexual contact, particularly men who have sex with men (MSM) was the most prevalent form of HIV transmission in Shijiazhuang. Hence, we conducted an epidemiological surveillance study on TDR among newly diagnosed individuals who infected-HIV through sexual contact in from 2014-2015.

METHODS

Genotypic resistance mutations were defined using the WHO-2009 surveillance list. Potential impact on antiretroviral drug was predicted according to the Stanford HIV db program version 7.0. The role of transmission clusters in drug resistant strains was evaluated by phylogenetic and network analyses.

RESULTS

In this study, 589 individuals were recruited and 542 samples were amplified and sequenced successfully. The over prevalence of TDR was 6.1%: 1.8% to nucleoside reverse transcriptase inhibitors (NRTIs), 2.0% to non- NRTIs (NNRTIs) and 2.4% to protease inhibitors (PIs), respectively. We did not find significant differences in the TDR prevalence by demographic and clinical characteristics (p > 0.05). Using network and phylogenetic analysis, almost 60.0% sequences were clustered together. Of these clusters, 2 included at least two individuals carrying the same resistance mutation, accounting for 21.2% (7/33) individuals with TDR. No significant difference was observed in the clustering rate between the individuals with and without TDR.

CONCLUSIONS

We obtained a moderate level TDR rate in studied region. These findings enhance our understanding of HIV-1 drug resistance prevalence in Shijiazhuang, and may be helpful for the comprehensive prevention and control of HIV-1.