Background Viral load measurement is commonly applicable to monitor HIV infection in patients to determine the number of HIV-RNA in serum samples of individuals. The aim of the present study was to set up a highly specific, sensitive, and reproducible home-brewed Real-time PCR assay based on TaqMan chemistry to quantify HIV-1 RNA genome. Methods In this study, three sets of primer pairs and a TaqMan probe were designed for HIV subtypes conserved sequences. An internal control was included in this assay to evaluate the presence of inhibition. Standard curve and threshold cycle values were determined using in vitro transcribed RNA from int region of HIV-1. A serial dilution of RNA standards was generated by in vitro transcription, from 10 to 109 copies/ml to find the sensitivity and the limit of detection (LOD) of the assay and to evaluate its performance in a quantitative RT-PCR assay. Results The assay has a low LOD equivalent to 33.13 copies/ml of HIV-1 RNA and a linear range of detection from 10 to 109 copies/ml. The coefficient of variation (CV) for Inter and Intra-assay precision of this in-house HIV Real-time RT-PCR ranged from 0.28 to 2.49% and 0.72 to 4.47%, respectively. The analytical and clinical specificity was 100%. Conclusions The results indicate that the developed method has a suitable specificity and sensitivity and is highly reproducible and cost-benefit. Therefore, it will be useful to monitor HIV infection in plasma samples of individuals.
Keyphrases
- real time pcr
- antiretroviral therapy
- hiv positive
- hiv infected
- hiv testing
- human immunodeficiency virus
- hiv aids
- hepatitis c virus
- men who have sex with men
- high throughput
- end stage renal disease
- healthcare
- transcription factor
- newly diagnosed
- computed tomography
- chronic kidney disease
- magnetic resonance imaging
- ejection fraction
- gene expression
- liquid chromatography tandem mass spectrometry
- magnetic resonance
- ms ms
- peritoneal dialysis
- single molecule
- drug discovery
- contrast enhanced
- genetic diversity