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A Scalable and Accurate Method for Quantifying Vector Genomes of Recombinant Adeno-Associated Viruses in Crude Lysate

Overview of attention for article published in Human Gene Therapy, April 2017
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Title
A Scalable and Accurate Method for Quantifying Vector Genomes of Recombinant Adeno-Associated Viruses in Crude Lysate
Published in
Human Gene Therapy, April 2017
DOI 10.1089/hgtb.2016.173
Pubmed ID
Authors

Jianzhong Ai, Raed Ibraheim, Phillip W.L. Tai, Guangping Gao

Abstract

Increasing interest and application of recombinant adeno-associated viruses (rAAVs) in basic and clinical research have urged efforts to improve rAAV production quality and yield. Standard vector production workflows call for genome titration of purified vectors at the endpoint of production to assess yield. Unfortunately, quality control measures for preparations during mid-production steps and economical means to assess the fidelity of multiple batches of rAAV preparations are lacking. Here we describe a scalable and accurate method for the direct quantitative polymerase chain reaction (qPCR) titration of rAAV genomes in crude lysate. Lysate samples are pretreated with DNase I to remove vector and packaging plasmid DNAs, followed by proteinase K to release endonuclease-resistant packaged viral genomes and to proteolyze factors inherent to crude lysates that can impinge upon quantitative PCR efficiencies. We show that this method is precise, scalable, and applicable for vector genome titrations of both single-stranded and self-complementary AAV genomes irrespective of serotype differences-a major limitation for standard lysate transduction methods that indirectly screen for vector packaging efficiency. Our described method therefore represents a significant improvement to rAAV vector production in terms of alleviating time and cost burdens, in-process quality control assessment, batch/lot monitoring in large-scale preparations, and good manufacturing practices.

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Mendeley readers

The data shown below were compiled from readership statistics for 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Unknown 104 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 20%
Student > Ph. D. Student 18 17%
Student > Master 8 8%
Student > Bachelor 8 8%
Other 7 7%
Other 15 14%
Unknown 28 27%
Readers by discipline Count As %
Agricultural and Biological Sciences 22 21%
Biochemistry, Genetics and Molecular Biology 22 21%
Engineering 7 7%
Chemical Engineering 6 6%
Neuroscience 4 4%
Other 13 12%
Unknown 31 30%