1921
Volume 100, Issue 2
  • ISSN: 0002-9637
  • E-ISSN: 1476-1645

Abstract

Abstract.

Current diagnostic protocols of acute Zika virus (ZIKV) infection focus on detection of viral RNA in serum or urine using reverse transcription quantitative polymerase chain reaction (RT-qPCR); however, detecting infection can be a challenge, given that 80% of people with acute ZIKV infection are asymptomatic, and the window to detect viremia in serum is short. The ability to extend that window is needed to detect ZIKV at later time points after infection, particularly in high-risk individuals such as pregnant women. We evaluated RNA extraction methods to optimize detection of ZIKV in various body fluids using RT-qPCR as a means of improving the analytical sensitivity of detection. We optimized methods for ZIKV RNA recovery from a number of body fluids by spiking with three varying concentrations of virus, then comparing recovery with that of spiked buffer control. RNA extraction protocols were adjusted as necessary for maximum RNA recovery. Adjustment of the elution step was essential for improved ZIKV RNA recovery from whole blood, saliva, vaginal secretions, and breast milk. Optimal recovery from urine samples required the addition of Urine Conditioning Buffer, and the use of RLT Plus buffer and RNeasy Mini Spin Columns was necessary for RNA extractions from semen samples. Optimized QIAamp MinElute Virus Spin Kit (QIAGEN, Valencia, CA) protocol followed by the singleplex ZIKV RT-qPCR assay provided a reliable method for detection of ZIKV RNA in a variety of biological samples. Improved diagnostics are crucial for timely detection and diagnosis, particularly during pregnancy when the consequences of ZIKV infection can greatly impact the developing fetus.

[open-access] This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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  • Received : 14 Sep 2018
  • Accepted : 23 Oct 2018

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