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Defining stable reference genes in HIV latency reversal experiments.

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|March 25, 2021
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Summary
This summary is machine-generated.

Selecting stable reference genes (RGs) is crucial for accurately measuring HIV RNA with latency-reversing agents (LRAs). LRA treatment significantly impacts RG stability, with TBP, UBE2D2, and RPL27A showing the most reliability.

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Area of Science:

  • Virology
  • Molecular Biology
  • Immunology

Background:

  • Cell-associated HIV RNA (ca-RNA) quantification is vital for assessing latency-reversing agents (LRAs) in HIV cure strategies.
  • qPCR normalization typically uses reference genes (RGs), but their stability under LRA treatment is unverified.
  • Biological variability and technical errors can affect normalization if RGs are not stable.

Purpose of the Study:

  • To evaluate the stability of commonly used reference genes (RGs) in human PBMCs and CD4+ T cells after exposure to LRAs.
  • To identify the most stable RGs for accurate quantification of HIV ca-RNA and host gene expression.
  • To assess the impact of unstable RGs on experimental outcomes in LRA-treated cells.

Main Methods:

  • Analyzed the expression stability of six reference genes (GAPDH, TBP, YWHAZ, UBE2D2, HPRT1, RPL27A) in human PBMCs and CD4+ T cells.
  • Treated cells with LRAs to mimic experimental conditions.
  • Quantified HIV ca-RNA and host gene expression using qPCR and assessed RG stability using established algorithms.

Main Results:

  • LRA exposure significantly altered the expression stability of most tested RGs.
  • TBP, UBE2D2, and RPL27A demonstrated the highest stability across all tested conditions.
  • GAPDH exhibited the most variability, while TBP was generally the most stable.
  • Using unstable RGs for normalization led to altered results in both host and HIV gene expression.

Conclusions:

  • Reference gene stability is significantly compromised by LRA treatment.
  • TBP, UBE2D2, and RPL27A are recommended as stable RGs for LRA studies.
  • Accurate evaluation of LRA efficacy requires careful selection and validation of reference genes to avoid data misinterpretation.