Background
In recent years there have been significant advances in the development of assays to quantify and characterize the HIV-1 reservoir. As these assays are incorporated into HIV-1 cure clinical trials, ensuring the reliability and reproducibility of assay results across different laboratories becomes crucial. This study aimed to evaluate the inter-laboratory performance of assays measuring intact proviruses (AMIP) as part of the National Institute of Allergy and Infectious Disease (NIAID) Virology Quality Assurance (VQA) program at Duke (contract # 75N93019C00015).
Methods
We conducted a multi-site study involving seven laboratories routinely performing AMIP. A panel of standardized samples comprising serial dilutions of HIV-1 infected cell lines with known proviral DNA levels were distributed blinded to the participating sites. Each laboratory performed the AMIP following their standard operating procedures. Results were collected and analyzed to establish the degree of concordance among laboratories and to identify discrepancies and potential sources of variability in assay outcomes.
Results
We observed significant variability in AMIP results across laboratories, with several labs exhibiting discrepancies for both experimental and biological replicates. For some laboratories the reported results differed from the expected values by 3 to 10-fold. Factors such as sample handling, assay reagents, and differences in analytical protocols were identified as potential contributors to this variability. Recommendations for standardization and training are currently being evaluated to mitigate these issues.
Conclusions
The establishment of a virology quality assurance program is essential in harmonizing inter-laboratory performances of assays to measure the size and expression of the HIV-1 reservoir. Enhanced quality assurance measures are necessary to ensure consistent and accurate results across laboratories, thereby strengthening the utility of these assays in clinical and research applications. Further investigations will focus on rigorous inter-laboratory training and the development of standardized protocols to minimize variability and improve assay performance and data comparability.
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