LAB ON A CHIP
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2023
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IF 6.1
xiaoliang zhang,Shun Wang,Jinxian Wang,Xiaojie Sun,Jinbing Xue,Zhenya Wang,Tianhang Yang,Liangfei Weng,Bidou Wang,Gangyin Luo
Droplet digital PCR (ddPCR) is a powerful method for absolute nucleic acid quantification with high precision and accuracy. However, complicated operational steps have hampered the use and diffusion of ddPCR. Therefore, an automated, easy-to-use, low-sample-consumption, and portable ddPCR platform is urgently needed. This paper proposes a microfluidic ddPCR platform based on a microfluidic chip that can realize the sample-to-result function by switching the rotary valve, achieving the dual function of the flow-focusing structure for droplet generation and readout. Sample, generation oil, and analysis oil were pre-added to the reservoirs. Droplets were generated due to focusing flow, and after passing through the integrated temporary storage bin in the rotary valve, the droplets and oil subsequently entered the collecting tube, improving the droplet-to-oil volume ratio for enhanced thermal cycle performance. Droplets with an average diameter of 107.44 μm and a CV of 2.38% were generated using our chip under the optimal pressures. High-performance thermal cycling was achieved through improvements of the droplet-to-oil volume ratio of the sample, the integrated heating lid, the pure copper heating base, and the temperature-controlling algorithm. Gradient quantification experiments were conducted for the HER2 and CEP17 genes extracted from breast cancer cells, yielding strong linear correlations with R2 values of 0.9996 for FAM and 0.9989 for CY5. Moreover, pronounced linearity was obtained between the detected concentrations of HER2 and CEP17, indicated by a slope of 1.0091 and an R² of 0.9997, signifying consistent HER2:CEP17 ratios across various sample dilutions. The outcomes of the quantitative analysis, encompassing the dynamic range and the consistency of the HER2:CEP17 ratio using our ddPCR platform, meet the standards required for breast cancer assessment and therapy. Our ddPCR platform is automated, portable, and capable of stable droplet generation, high-efficiency amplification, realization of the sample-to-result function based on dual-function flow-focusing structure, and accuracy absolute quantification, underscoring its significant potential for ddPCR analysis in clinical diagnostics.
研究领域:
生物医学工程
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分子生物学
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临床诊断
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产品关联
DOI
PubMed
高影响因子
JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS
·
2023
·
IF 3.4
Yuxiang Zhou,Yanyun Wang,Mengyuan Song,Lanrui Jiang,Chaoran Sun,Shuangshuang Wang,Hewen Yao,Zefei Wang,Xindi Wang,Chunhui Liu,Haibo Luo,Feng Song
The droplet digital Polymerase Chain Reaction (ddPCR) has garnered recognition for its distinctive attribute of absolute quantification. And it has found practical utility in age prediction through DNA methylation profiles. However, a prevalent limitation in current ddPCR methodologies is the restricted capacity to detect only two targets concurrently in most instruments, leading to high costs, sample wastage, and labor-intensive procedures. To address the limitations, a novel high-throughput ddPCR system allowing for the simultaneous detection of eight targets was developed. Through the implementation of a new 8-plex ddPCR assay, coupled with comprehensive linear regression analyses involving primers and probes ratios, diverse inputs of single CpG sites with distinct primers and probes, and varying plex assay configurations, stable DNA methylation values for four CpGs and stable measurement precisions for distinct multiplex systems were consistently observed. These findings pave the way for advancing the field of chemistry science by enabling more efficient and cost-effective methods. Furthermore, the comparative validation of ddPCR and SNaPshot demonstrated a remarkable concordance in results, and the system also displayed well in the field of various aspects, including species specificity, DNA input, and aged samples. In this study, the recommended input of bisulfite-converted DNA was determined to be 10–50 ng due to the double-positive droplets. Notably, the Pearson correlation coefficient squared values of four CpGs were 0.4878 (ASPA), 0.4832 (IGSF1), 0.6881 (COL1A1), and 0.6475 (MEIS1-AS3). And the testing set exhibited a mean absolute error of 4.5923 years, indicating the robustness and accuracy of the age-predictive model.
研究领域:
分子生物学
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法医学
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化学科学
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产品关联
DOI
PubMed
高影响因子
ANALYST
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2019
·Vol. 144
·期 16
·4757-4771
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IF 4.019
Xiurui Zhu,Shisheng Su,Mingzhu Fu,Zhiyong Peng,Dong Wang,Xiao Rui,Fang Wang,Xiaobin Liu,Baoxia Liu,Lingxiang Zhu,Wenjun Yang,Na Gao,Guoliang Huang,Gaoshan Jing,Yong Guo
Droplet digital PCR (ddPCR) is a single-molecule amplification technology with broad applications in precision medicine and clinical diagnosis. Dual-fluorescence and four-cluster ddPCR (two/four-ddPCR) assay is an effective way to quantify copy numbers. Currently, two/four-ddPCR data are usually classified with manual thresholds. For clinical applications, automatic and accurate methods are required to avoid subjectivity in diagnosis. Although there are some automatic classification algorithms, their accuracy and robustness still need to be improved to meet the needs of clinical diagnosis. Therefore, a new method is in high demand to automatically classify two/four-ddPCR data in an accurate and robust way. Here, a novel density-watershed algorithm (DWA) method was developed for the accurate, automatic and unsupervised classification of two/four-ddPCR data. First, data gridding was applied to a scatter plot of the fluorescence signal intensity to calculate data densities. Based on the data densities, the watershed algorithm was used to divide the gridded scatter plot into isolated regions automatically. Next, an optimal cluster pattern was determined based on these isolated regions, and excess regions were merged. Finally, the two/four-ddPCR data were classified based on the merged regions, and DNA template copy numbers were calculated accordingly. Using the DWA method for the quantification of both wild types and mutants of epidermal growth factor receptor (EGFR) L858R and T790M, the classification results were highly consistent with expectations, and significantly better than commonly-used automatic algorithms for now. The computed template copy numbers scaled proportionally to the relative concentration of input templates (r2 > 0.998) in four orders of magnitude with a good reproducibility, and achieved a limit of detection over 40 times lower than the commonly-used automatic algorithms. Furthermore, the DWA method was validated on 254 clinical DNA samples derived from frozen tissues, formalin-fixed paraffin-embedded tissues and peripheral blood. In most cases, the DWA method derived accurate and valid classification results. This highly effective DWA method may be widely used for automatically classifying two/four-ddPCR data, and it will greatly promote the application of ddPCR in clinical diagnosis.
研究领域:
生物信息学
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分子生物学
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临床诊断
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精准医疗
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产品关联
DOI
PubMed
高影响因子
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