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Xing Y, Wang Y, Li X, Pang S. Digital microfluidics methods for nucleic acid detection: A mini review. BIOMICROFLUIDICS 2024; 18:021501. [PMID: 38456173 PMCID: PMC10917463 DOI: 10.1063/5.0180125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Accepted: 02/01/2024] [Indexed: 03/09/2024]
Abstract
Many serious infectious diseases have occurred throughout human history. Rapid and accurate detection as well as the isolation of infected individuals, through nucleic acid testing, are effective means of containing the spread of these viruses. However, traditional nucleic acid testing methods rely on complex machines and specialized personnel, making it difficult to achieve large-scale, high-throughput, and rapid detection. In recent years, digital microfluidics has emerged as a promising technology that integrates various fields, including electrokinetics, acoustics, optics, magnetism, and mechanics. By leveraging the advantages of these different technologies, digital microfluidic chips offer several benefits, such as high detection throughput, integration of multiple functions, low reagent consumption, and portability. This rapid and efficient testing is crucial in the timely detection and isolation of infected individuals to prevent the virus spread. Another advantage is the low reagent consumption of digital microfluidic chips. Compared to traditional methods, these chips require smaller volumes of reagents, resulting in cost savings and reduced waste. Furthermore, digital microfluidic chips are portable and can be easily integrated into point-of-care testing devices. This enables testing to be conducted in remote or resource-limited areas, where access to complex laboratory equipment may be limited. Onsite testing reduces the time and cost associated with sample transportation. In conclusion, bioassay technologies based on digital microfluidic principles have the potential to significantly improve infectious disease detection and control. By enabling rapid, high-throughput, and portable testing, these technologies enhance our ability to contain the spread of infectious diseases and effectively manage public health outbreaks.
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Affiliation(s)
- Youqiang Xing
- School of Mechanical Engineering, Southeast University, Nanjing 211189, Jiangsu Province, People’s Republic of China
| | - Yan Wang
- Clinical Laboratory, Yantai Yuhuangding Hospital, Yantai 264000, Shandong Province, People’s Republic of China
| | - Xiang Li
- Bio-manufacturing Engineering Laboratory, Tsinghua Shenzhen International Graduate School, Tsinghua University, Guangdong 518000, Shenzhen, People’s Republic of China
| | - Shangran Pang
- Jinzhong Normal Junior College, 189 Guang'an Street, Yuci District, Jinzhong 030600, Shanxi Province, People’s Republic of China
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Zang P, Xu Q, Li C, Tao M, Zhang Z, Li J, Zhang W, Li S, Li C, Yang Q, Guo Z, Yao J, Zhou L. Self-correction of cycle threshold values by a normal distribution-based process to improve accuracy of quantification in real-time digital PCR. Anal Bioanal Chem 2024:10.1007/s00216-024-05208-w. [PMID: 38400940 DOI: 10.1007/s00216-024-05208-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 01/29/2024] [Accepted: 02/12/2024] [Indexed: 02/26/2024]
Abstract
The digital polymerase chain reaction (dPCR) is a new and developing nucleic acid detection technology with high sensitivity that can realize the absolute quantitative analysis of samples. In order to improve the accuracy of quantitative results, real-time digital PCR emphasizes the kinetic information during amplification to identify prominent abnormal data. However, it is challenging to use a unified standard to accurately classify the amplification curve of each well as negative and positive, due to the interference caused by various factors in the experiment. In this work, a normal distribution-based cycle threshold value self-correcting model (NCSM) was established, which focused on the feature of the cycle threshold values in amplification curves and conducted continuous detection and correction on the whole. The cycle threshold value distribution was closer to the ideal normal distribution to avoid the influence of interference. Thus, the model achieves a more accurate classification between positive and negative results. The corrective process was applied to plasmid samples and resulted in an accuracy improvement from 92 to 99%. The coefficient of variation was below 5% when considering the quantitation of a range between 100 and 10,000 copies. At the same time, by utilizing this model, the distribution of cycle threshold values at the endpoint can be predicted with fewer thermal cycles, which can reduce the cycling time by around 25% while maintaining a consistency of more than 98%. Therefore, using the NCSM can effectively enhance the quantitative accuracy and increase the detection efficiency based on the real-time dPCR platform.
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Affiliation(s)
- Peilin Zang
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China
- CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Qi Xu
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China
- CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Chuanyu Li
- CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Mingli Tao
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China
- CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Zhiqi Zhang
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China
- CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
- Suzhou CASENS Co., Ltd, Suzhou, 215163, China
| | - Jinze Li
- CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Wei Zhang
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China
- CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
- Suzhou CASENS Co., Ltd, Suzhou, 215163, China
| | - Shuli Li
- CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Chao Li
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China
- CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Qi Yang
- CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
| | - Zhen Guo
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China.
- CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China.
| | - Jia Yao
- CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China.
| | - Lianqun Zhou
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China.
- CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China.
- Suzhou CASENS Co., Ltd, Suzhou, 215163, China.
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Kwak SY, Park JH, Won HY, Jang H, Lee SB, Jang WI, Park S, Kim MJ, Shim S. CXCL10 upregulation in radiation-exposed human peripheral blood mononuclear cells as a candidate biomarker for rapid triage after radiation exposure. Int J Radiat Biol 2024; 100:541-549. [PMID: 38227479 DOI: 10.1080/09553002.2023.2295300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 11/13/2023] [Indexed: 01/17/2024]
Abstract
PURPOSE In case of a nuclear accident, individuals with high-dose radiation exposure (>1-2 Gy) should be rapidly identified. While ferredoxin reductase (FDXR) was recently suggested as a radiation-responsive gene, the use of a single gene biomarker limits radiation dose assessment. To overcome this limitation, we sought to identify reliable radiation-responsive gene biomarkers. MATERIALS AND METHODS Peripheral blood mononuclear cells (PBMCs) were isolated from mice after total body irradiation, and gene expression was analyzed using a microarray approach to identify radiation-responsive genes. RESULTS In light of the essential role of the immune response following radiation exposure, we selected several immune-related candidate genes upregulated by radiation exposure in both mouse and human PBMCs. In particular, the expression of ACOD1 and CXCL10 increased in a radiation dose-dependent manner, while remaining unchanged following lipopolysaccharide (LPS) stimulation in human PBMCs. The expression of both genes was further evaluated in the blood of cancer patients before and after radiotherapy. CXCL10 expression exhibited a distinct increase after radiotherapy and was positively correlated with FDXR expression. CONCLUSIONS CXCL10 expression in irradiated PBMCs represents a potential biomarker for radiation exposure.
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Affiliation(s)
- Seo Young Kwak
- Korea Institute of Radiological & Medical Science, Laboratory of Radiation Exposure & Therapeutics, National Radiation Emergency Medical Center, Seoul, South Korea
| | - Ji-Hye Park
- Korea Institute of Radiological & Medical Science, Laboratory of Radiation Exposure & Therapeutics, National Radiation Emergency Medical Center, Seoul, South Korea
- OPTOLANE Technologies Inc., Seongnam, South Korea
| | | | - Hyosun Jang
- Korea Institute of Radiological & Medical Science, Laboratory of Radiation Exposure & Therapeutics, National Radiation Emergency Medical Center, Seoul, South Korea
| | - Seung Bum Lee
- Korea Institute of Radiological & Medical Science, Laboratory of Radiation Exposure & Therapeutics, National Radiation Emergency Medical Center, Seoul, South Korea
| | - Won Il Jang
- Korea Institute of Radiological & Medical Science, Laboratory of Radiation Exposure & Therapeutics, National Radiation Emergency Medical Center, Seoul, South Korea
- Department of Radiation Oncology, Korea Cancer Center Hospital, Korea Institute of Radiological and Medical Sciences, Seoul, South Korea
| | - Sunhoo Park
- Korea Institute of Radiological & Medical Science, Laboratory of Radiation Exposure & Therapeutics, National Radiation Emergency Medical Center, Seoul, South Korea
- Department of Pathology, Korea Cancer Center Hospital, Korea Institute of Radiological & Medical Science, Seoul, South Korea
| | - Min-Jung Kim
- Korea Institute of Radiological & Medical Science, Laboratory of Radiation Exposure & Therapeutics, National Radiation Emergency Medical Center, Seoul, South Korea
| | - Sehwan Shim
- Korea Institute of Radiological & Medical Science, Laboratory of Radiation Exposure & Therapeutics, National Radiation Emergency Medical Center, Seoul, South Korea
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Dobre EG, Constantin C, Neagu M. Skin Cancer Research Goes Digital: Looking for Biomarkers within the Droplets. J Pers Med 2022; 12:jpm12071136. [PMID: 35887633 PMCID: PMC9323323 DOI: 10.3390/jpm12071136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 07/12/2022] [Accepted: 07/12/2022] [Indexed: 12/24/2022] Open
Abstract
Skin cancer, which includes the most frequent malignant non-melanoma carcinomas (basal cell carcinoma, BCC, and squamous cell carcinoma, SCC), along with the difficult to treat cutaneous melanoma (CM), pose important worldwide issues for the health care system. Despite the improved anti-cancer armamentarium and the latest scientific achievements, many skin cancer patients fail to respond to therapies, due to the remarkable heterogeneity of cutaneous tumors, calling for even more sophisticated biomarker discovery and patient monitoring approaches. Droplet digital polymerase chain reaction (ddPCR), a robust method for detecting and quantifying low-abundance nucleic acids, has recently emerged as a powerful technology for skin cancer analysis in tissue and liquid biopsies (LBs). The ddPCR method, being capable of analyzing various biological samples, has proved to be efficient in studying variations in gene sequences, including copy number variations (CNVs) and point mutations, DNA methylation, circulatory miRNome, and transcriptome dynamics. Moreover, ddPCR can be designed as a dynamic platform for individualized cancer detection and monitoring therapy efficacy. Here, we present the latest scientific studies applying ddPCR in dermato-oncology, highlighting the potential of this technology for skin cancer biomarker discovery and validation in the context of personalized medicine. The benefits and challenges associated with ddPCR implementation in the clinical setting, mainly when analyzing LBs, are also discussed.
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Affiliation(s)
- Elena-Georgiana Dobre
- Faculty of Biology, University of Bucharest, Splaiul Independentei 91–95, 050095 Bucharest, Romania;
- Correspondence:
| | - Carolina Constantin
- Immunology Department, “Victor Babes” National Institute of Pathology, 050096 Bucharest, Romania;
- Pathology Department, Colentina Clinical Hospital, 020125 Bucharest, Romania
| | - Monica Neagu
- Faculty of Biology, University of Bucharest, Splaiul Independentei 91–95, 050095 Bucharest, Romania;
- Immunology Department, “Victor Babes” National Institute of Pathology, 050096 Bucharest, Romania;
- Pathology Department, Colentina Clinical Hospital, 020125 Bucharest, Romania
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Shin W, Lee CJ, Lee YM, Choi YB, Mun S, Han K. Rapid identification of SARS-CoV-2 in the point-of-care using digital PCR-based Dr. PCR™ Di20K COVID-19 Detection Kit without viral RNA extraction. Genes Genomics 2022; 44:617-628. [PMID: 35353341 PMCID: PMC8965542 DOI: 10.1007/s13258-022-01242-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Accepted: 03/11/2022] [Indexed: 11/28/2022]
Abstract
BACKGROUND Since COVID-19 was declared the pandemic by the WHO, it has continued to spread. There is a need for rapid, efficient, and accurate diagnostic kits and techniques to control its spread. OBJECTIVE The diagnostic capability of the qRT-PCR-based Real-Q 2019-nCoV Detection Kit and dPCR-based Dr. PCR™ Di20K COVID-19 Detection Kit was compared and evaluated. METHODS Diagnostic tests for COVID-19 were performed using two different COVID-19 kits and 301 individual specimens with confirmed COVID-19 positive/negative at the government-accredited medical institution. Assessment of diagnostic capability was measured through diagnostic sensitivity, specificity, Cohen's Kappa coefficient, and dilutional linearity tests. RESULTS The COVID-19 diagnostic test results using two kits and 301 individual specimens perfectly matched the pre-diagnosis results of the medical institution. In addition, the measurement results of diagnostic sensitivity and specificity were "1", indicating high diagnostic capability. Cohen's Kappa coefficient value is "1", which means that the diagnosis concordance between the two kits is "Almost Perfect". As a result of dilutional linearity tests to evaluate their detection capability, both kits were measured with very high detection reliability. CONCLUSION Here, we propose that the dPCR-based Dr. PCR™ Di20K COVID-19 Detection Kit has the advantages of the dPCR method reported in the previous study and is suitable for point-of-care testing (POCT) by overcoming the limitations of space, test time, cross-over contamination, and biosafety due to omitting RNA extraction process.
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Affiliation(s)
- Wonseok Shin
- NGS Clinical Laboratory, Dankook University Hospital, Cheonan, 31116, Republic of Korea
| | - Cherl-Joon Lee
- Department of Bio-Convergence Engineering, Dankook University, Jukjeon, 16890, Republic of Korea
| | - Yong-Moon Lee
- Department of Pathology, Dankook University College of Medicine, Chenonan, 31116, Republic of Korea
| | - Young-Bong Choi
- Department of Chemistry, College of Science and Technology, Dankook University, Cheonan, 31116, Republic of Korea
| | - Seyoung Mun
- Center for Bio-Medical Engineering Core Facility, Dankook University, Cheonan, 31116, Republic of Korea.
- Department of Nanobiomedical Science, Dankook University, Cheonan, 31116, Republic of Korea.
| | - Kyudong Han
- NGS Clinical Laboratory, Dankook University Hospital, Cheonan, 31116, Republic of Korea.
- Department of Bio-Convergence Engineering, Dankook University, Jukjeon, 16890, Republic of Korea.
- Center for Bio-Medical Engineering Core Facility, Dankook University, Cheonan, 31116, Republic of Korea.
- Department of Microbiology, College of Science and Technology, Dankook University, Cheonan, 31116, Republic of Korea.
- DKU-Theragen Institute for NGS Analysis (DTiNa), Cheonan, 31116, Republic of Korea.
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