46 research outputs found
Low-Abundance HIV Drug-Resistant Viral Variants in Treatment-Experienced Persons Correlate with Historical Antiretroviral Use
BACKGROUND: It is largely unknown how frequently low-abundance HIV drug-resistant variants at levels under limit of detection of conventional genotyping (<20% of quasi-species) are present in antiretroviral-experienced persons experiencing virologic failure. Further, the clinical implications of low-abundance drug-resistant variants at time of virologic failure are unknown. METHODOLOGY/PRINCIPAL FINDINGS: Plasma samples from 22 antiretroviral-experienced subjects collected at time of virologic failure (viral load 1380 to 304,000 copies/mL) were obtained from a specimen bank (from 2004-2007). The prevalence and profile of drug-resistant mutations were determined using Sanger sequencing and ultra-deep pyrosequencing. Genotypes were interpreted using Stanford HIV database algorithm. Antiretroviral treatment histories were obtained by chart review and correlated with drug-resistant mutations. Low-abundance drug-resistant mutations were detected in all 22 subjects by deep sequencing and only in 3 subjects by Sanger sequencing. In total they accounted for 90 of 247 mutations (36%) detected by deep sequencing; the majority of these (95%) were not detected by standard genotyping. A mean of 4 additional mutations per subject were detected by deep sequencing (p<0.0001, 95%CI: 2.85-5.53). The additional low-abundance drug-resistant mutations increased a subject's genotypic resistance to one or more antiretrovirals in 17 of 22 subjects (77%). When correlated with subjects' antiretroviral treatment histories, the additional low-abundance drug-resistant mutations correlated with the failing antiretroviral drugs in 21% subjects and correlated with historical antiretroviral use in 79% subjects (OR, 13.73; 95% CI, 2.5-74.3, p = 0.0016). CONCLUSIONS/SIGNIFICANCE: Low-abundance HIV drug-resistant mutations in antiretroviral-experienced subjects at time of virologic failure can increase a subject's overall burden of resistance, yet commonly go unrecognized by conventional genotyping. The majority of unrecognized resistant mutations correlate with historical antiretroviral use. Ultra-deep sequencing can provide important historical resistance information for clinicians when planning subsequent antiretroviral regimens for highly treatment-experienced patients, particularly when their prior treatment histories and longitudinal genotypes are not available
Modeling HIV transmission from sexually active alcohol-consuming men in ART programs to seronegative wives
Background: The rollout of antiviral therapy in Low and Middle Income Countries (LMICs) has reduced HIV transmission rates at the potential risk of resistant HIV transmission. We sought to predict the risk of wild type and antiviral resistance transmissions in these settings. Methods: A predictive model utilizing viral load, ART adherence, genital ulcer disease, condom use, and sexual event histories was developed to predict risks of HIV transmission to wives of 233 HIV+ men in 4 antiretroviral treatment centers in Maharashtra, India. Results: ARV Therapy predicted a 5.71-fold reduction in transmissions compared to a model of using condoms alone, with 79.9%, of remaining transmissions resulting in primary ART-resistance. Conclusions: ART programs reduce transmission of HIV to susceptible partners at a substantial increased risk for transmission of resistant virus. Enhanced vigilance in monitoring adherence, use of barrier protections, and viral load may reduce risks of resistant HIV transmissions in LMIC settings
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Contamination-resistant, rapid emulsion-based isothermal nucleic acid amplification with Mie-scatter inspired light scatter analysis for bacterial identification
An emulsion loop-mediated isothermal amplification (eLAMP) platform was developed to reduce the impact that contamination has on assay performance. Ongoing LAMP reactions within the emulsion droplets cause a decrease in interfacial tension, causing a decrease in droplet size, which results in decreased light scatter intensity due to Mie theory. Light scatter intensity was monitored via spectrophotometers and fiber optic cables placed at 30° and 60°. Light scatter intensities collected at 3 min, 30° were able to statistically differentiate 103 and 106 CFU/µL initial Escherichia coli O157:H7 concentrations compared to NTC (0 CFU/µL), while the intensity at 60° were able to statistically differentiate 106 CFU/µL initial concentrations and NTC. Control experiments were conducted to validate nucleic acid detection versus bacterial adsorption, finding that the light scatter intensities change is due specifically to ongoing LAMP amplification. After inducing contamination of bulk LAMP reagents, specificity lowered to 0% with conventional LAMP, while the eLAMP platform showed 87.5% specificity. We have demonstrated the use of angle-dependent light scatter intensity as a means of real-time monitoring of an emulsion LAMP platform and fabricated a smartphone-based monitoring system that showed similar trends as spectrophotometer light scatter data, validating the technology for a field deployable platform. © 2021, The Author(s).Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]