Droplet Digital PCR, the new tool in HIV reservoir quantification? Ward De Spiegelaere
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1 Droplet Digital PCR, the new tool in HIV reservoir quantification? Ward De Spiegelaere
2 Droplet Digital PCR, the new tool in HIV reservoir quantification? Content: - Digital PCR - Applications - Total HIV DNA - 2LTR - CA HIV RNA - Conclusions
3 What is digital PCR (dpcr)? qpcr dpcr pos pos pos pos pos pos pos 10 amplicons
4 Droplet digital PCR (ddpcr) 20 µl 20,000 reactions PCR fluorescent read-out
5 Advantages of digital PCR Direct absolute quantification: - No standard curve - LOD = LOQ End point PCR: - Less susceptible to inhibition - input - mismatches - Higher flexibility in assay design Low level detection - Higher accuracy vs qpcr - Not higher sensitivity
6 Accuracy of ddpcr for DNA quantification Hindson CM, Chevillet JR, Briggs HA et al. Nat Methods (2013):
7 Implementing PCR-based HIV reservoir diagnostics on the ddpcr platform - Total HIV - 2LTR - HIV RNA - Integrated HIV DNA? Poster nr. 74
8 Pitfalls Maximal amount of total DNA input False positive droplets Treshold setting Qualitative assessment of droplets - raw ddpcr data needed - droplet loss Molecular dropout: failed amplification in some droplets
9 Detected copies/µl in sample Detected copies/µl sample Maximal input gdna Different total gdna amounts HIV DNA LTR Input gdna Input gdna Limited to < 200,000 cell equivalents/20µl reactions Solution? Pool droplets from separate wells
10 Fluorescence amplitude False positives NTC NTC NTC NTC NTC NTC NTC Freqeuncy of occurence: 1/3 or <1/10 wells Maximally 3 droplets/well LOD LOQ Pooling data from multiple wells is not possible
11 Droplet Digital PCR, the new tool in HIV reservoir quantification? Content: - Digital PCR - Applications - Total HIV DNA - 2LTR - CA HIV RNA - Conclusions
12 qpcr HIV DNA/10 6 PBMCs HIV DNA Good correlation Slight overestimation with ddpcr compared to qpcr Patient samples y = x R² = Possibly due to mismatches in patient samples 100 n= ddpcr HIV DNA/10 6 PBMCs In collaboration with Una O Doherty, UPENN
13 Droplet Digital PCR, the new tool in HIV reservoir quantification? Content: - Digital PCR - Applications - Total HIV DNA - 2LTR - CA HIV RNA - Conclusions
14 2LTR Low abundance of 2LTR! Plasmid purification: Total gdna Pro: - High cellular input Pro: - Internal reference gene Contra: - Loss of low abundant episomal DNA? - Normalization strategy? Contra: - High DNA content: inhibition?
15 Detected copies per 10 6 PBMCs Plasmid pur vs gdna Modified plasmid purification Addition of a non HIV reference plasmid before plasmid pur psif (6.3 kb) FIV-based Serial dilution of infected cells in 10 7 PBMCs gdna plasmid pur Expected copies per 10 6 PBMCs
16 2LTR/10 6 PBMCs Patient derived PBMCs gdna: < 2x10 5 cells/reaction Plasmid pur: 2x cells/reaction gdna Plasmid pur pt1 pt2 pt3 pt4 pt5 pt6 pt7
17 Raw data pt5 gdna Plasmid purified DNA NTC NTC NTC NTC
18 Raw data: pt6 gdna Plasmid purified DNA
19 Droplet Digital PCR, the new tool in HIV reservoir quantification? Content: - Digital PCR - Applications - Total HIV DNA - 2LTR - CA HIV RNA - Conclusions
20 Estimated copy nr ddpcr CA HIV RNA DdPCR vs seminested PCR Standard Dilution series RNA-cDNA conversion slope: fold underestimation Need for conversion factor! usrna input copy nr Kiselinova, Pasternak, De Spiegelaere, et al., Plos One (in revision)
21 CA HIV RNA (ddpcr vs seminested PCR) Patient samples Unspliced HIV RNA Good correlation in higher ranges Sample error in low abundant samples n=34 Kiselinova, Pasternak, De Spiegelaere, et al., Plos One (in revision)
22 CA HIV RNA (ddpcr vs seminested PCR) Patient samples Multiple spliced HIV RNA Good correlation in higher ranges Higher estimation with ddpcr mismatches n=14
23 Summary Total HIV 2LTR RNA Comparison with qpcr Pre PCR processing? Restriction digestion Plasmid pur + reference plasmid RT Effect of false positives sufficient template Close monitoring required Close monitoring required Sequence variation Standard required No Reference plasmid RT conversion factor
24 Conclusion advantages over qpcr: - Accuracy - Mismatches - Inhibition But suffers drawbacks - False positives - Maximal input Guidelines for reporting ddpcr methods are required!
25 Guidelines To improve interpretation and reproducibility Number of replicates Template input/sample Normalization strategy Raw data Number of droplets assessed/sample Number of droplets found positive Level of False positives Guidelines should be set-up and adopted by the community!
26 Acknowledgements Ghent University Linos Vandekerckhove Maja Kiselinova Eva Malatinkova Karen Vervisch Pawel Bonckskowski Wim Trypsteen UPENN Una O Doherty Lindsay Lynch University of Amsterdam Alexander Pasternak
27
28 Positive droplets 2LTR droplet count gdna Plasmid pur pt1 pt2 pt3 pt4 pt5 pt6 pt7
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