Dataset Information

Quantitation of Residual Host Cell DNA in Recombinant Adeno-Associated Virus Using Droplet Digital Polymerase Chain Reaction.

ABSTRACT: Recombinant adeno-associated virus (rAAV) is a viral vector commonly used in gene therapy. Residual host cell DNA is an impurity that has been associated with the risk of infection and oncogenicity. Thus, it needs to be monitored for quality control. We aimed to develop a droplet digital polymerase chain reaction (ddPCR) method targeting 18S ribosomal RNA (rRNA) genes to quantitate residual host cell DNA. The copy number of the 18S rRNA gene was determined using two sets of primer pairs for 116- and 247-bp amplicons sharing the C-terminus. For conversion of the copy number of the 18S rRNA gene into the mass concentration of genomic DNA, the accurate copy number of 18S rRNA genes in HEK293 genomic DNA was determined by comparison with copy numbers of three reference genes (EIF5B, DCK, and HBB). Results showed that 88.6-97.9% of HEK293 genomic DNA spiked into rAAV preparations was recovered. The ddPCR-based assay was applied to rAAV preparations to quantitate residual host cell DNA as an impurity. Our findings indicate that the assay can be used for the quantitation and size distribution of residual host cell DNA in rAAV products.

SUBMITTER: Higashiyama K

PROVIDER: S-EPMC10285681 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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Quantitation of Residual Host Cell DNA in Recombinant Adeno-Associated Virus Using Droplet Digital Polymerase Chain Reaction.

Higashiyama Kiyoko K Yuan Yuzhe Y Hashiba Noriko N Masumi-Koizumi Kyoko K Yusa Keisuke K Uchida Kazuhisa K

Human gene therapy 20230522 11-12

Recombinant adeno-associated virus (rAAV) is a viral vector commonly used in gene therapy. Residual host cell DNA is an impurity that has been associated with the risk of infection and oncogenicity. Thus, it needs to be monitored for quality control. We aimed to develop a droplet digital polymerase chain reaction (ddPCR) method targeting 18S ribosomal RNA (rRNA) genes to quantitate residual host cell DNA. The copy number of the 18S rRNA gene was determined using two sets of primer pairs for 116- ...[more]

PMID: 37058356

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Project description:Digital PCR in droplets (ddPCR) is an emerging method for more and more applications in DNA (and RNA) analysis. Special requirements when establishing ddPCR for analysis of genetically modified organisms (GMO) in a laboratory include the choice between validated official qPCR methods and the optimization of these assays for a ddPCR format. Differentiation between droplets with positive reaction and negative droplets, that is setting of an appropriate threshold, can be crucial for a correct measurement. This holds true in particular when independent transgene and plant-specific reference gene copy numbers have to be combined to determine the content of GM material in a sample. Droplets which show fluorescent units ranging between those of explicit positive and negative droplets are called 'rain'. Signals of such droplets can hinder analysis and the correct setting of a threshold. In this manuscript, a computer-based algorithm has been carefully designed to evaluate assay performance and facilitate objective criteria for assay optimization. Optimized assays in return minimize the impact of rain on ddPCR analysis. We developed an Excel based 'experience matrix' that reflects the assay parameters of GMO ddPCR tests performed in our laboratory. Parameters considered include singleplex/duplex ddPCR, assay volume, thermal cycler, probe manufacturer, oligonucleotide concentration, annealing/elongation temperature, and a droplet separation evaluation. We additionally propose an objective droplet separation value which is based on both absolute fluorescence signal distance of positive and negative droplet populations and the variation within these droplet populations. The proposed performance classification in the experience matrix can be used for a rating of different assays for the same GMO target, thus enabling employment of the best suited assay parameters. Main optimization parameters include annealing/extension temperature and oligonucleotide concentrations. The droplet separation value allows for easy and reproducible assay performance evaluation. The combination of separation value with the experience matrix simplifies the choice of adequate assay parameters for a given GMO event.

Dataset Information

Quantitation of Residual Host Cell DNA in Recombinant Adeno-Associated Virus Using Droplet Digital Polymerase Chain Reaction.

Publications

Quantitation of Residual Host Cell DNA in Recombinant Adeno-Associated Virus Using Droplet Digital Polymerase Chain Reaction.

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