Cong Wang1, Qiang Ding2, Pamela Plant2, Mayada Basheer3, Chuance Yang2, Eriny Tawedrous2, Adriana Krizova4, Carl Boulos2, Mina Farag2, Yufeng Cheng5, George M Yousef6. 1. Department of Radiation Oncology, Qilu Hospital of Shandong University, Shandong, China; Keenan Biomedical Research Centre, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, ON, Canada. 2. Keenan Biomedical Research Centre, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, ON, Canada. 3. Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada. 4. Keenan Biomedical Research Centre, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, ON, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada. 5. Department of Radiation Oncology, Qilu Hospital of Shandong University, Shandong, China. Electronic address: qlcyf@sdu.edu.cn. 6. Keenan Biomedical Research Centre, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, ON, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada. Electronic address: george.yousef@sickids.ca.
Abstract
OBJECT: Quantification of urinary miRNAs can be challenging especially for low abundance miRNAs. We aimed to optimize the quantification of urinary exosomal miRNAs and compare the performance efficiency between droplet digital PCR (ddPCR) and real-time quantitative PCR (qPCR). METHODS: We optimized a number of parameters for ddPCR such as annealing temperatures, annealing time and PCR cycle number. We also compared the performance of ddPCR and qPCR. RESULTS: By comparing the fluorescence amplification separation, the optimal annealing temperature was 59 °C, optimal annealing time was 60s and optimal cycle number was 45 for measuring urinary exosomal miRNAs. ddPCR had much higher technical sensitivity compared to qPCR. The minimal detectable concentration of miR-29a was <50 copies/μL by ddPCR compared to 6473 copies/μL for qPCR. Also, ddPCR generated more consistent results for serially diluted samples compared to qPCR. ddPCR generated smaller within-run variations than qPCR though this did not reach statistical significance. It also resulted in better reproducibility with smaller between-run variations. CONCLUSIONS: Optimization of urinary exosomal miRNA ddPCR assay is dependent on assessing key variables including experimental annealing temperature and time as well as the number of PCR cycles. ddPCR has a higher sensitivity, reproducibility, and accuracy in comparison to qPCR.
OBJECT: Quantification of urinary miRNAs can be challenging especially for low abundance miRNAs. We aimed to optimize the quantification of urinary exosomal miRNAs and compare the performance efficiency between droplet digital PCR (ddPCR) and real-time quantitative PCR (qPCR). METHODS: We optimized a number of parameters for ddPCR such as annealing temperatures, annealing time and PCR cycle number. We also compared the performance of ddPCR and qPCR. RESULTS: By comparing the fluorescence amplification separation, the optimal annealing temperature was 59 °C, optimal annealing time was 60s and optimal cycle number was 45 for measuring urinary exosomal miRNAs. ddPCR had much higher technical sensitivity compared to qPCR. The minimal detectable concentration of miR-29a was <50 copies/μL by ddPCR compared to 6473 copies/μL for qPCR. Also, ddPCR generated more consistent results for serially diluted samples compared to qPCR. ddPCR generated smaller within-run variations than qPCR though this did not reach statistical significance. It also resulted in better reproducibility with smaller between-run variations. CONCLUSIONS: Optimization of urinary exosomal miRNA ddPCR assay is dependent on assessing key variables including experimental annealing temperature and time as well as the number of PCR cycles. ddPCR has a higher sensitivity, reproducibility, and accuracy in comparison to qPCR.
Authors: Bethany Sanchez; Xixi Zhou; Amy S Gardiner; Guy Herbert; Selita Lucas; Masako Morishita; James G Wagner; Ryan Lewandowski; Jack R Harkema; Chris Shuey; Matthew J Campen; Katherine E Zychowski Journal: Part Fibre Toxicol Date: 2020-07-01 Impact factor: 9.400
Authors: Ho Won Kang; Hee Youn Lee; Young Joon Byun; Pildu Jeong; Jin Sun Yoon; Dong Ho Kim; Won Tae Kim; Yong-June Kim; Sang-Cheol Lee; Seok Joong Yun; Wun-Jae Kim Journal: Investig Clin Urol Date: 2020-05-29