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Chen W, Zhang K, Huang F, Zhao L, Waldren GC, Jiang Q, Chen SX, Wang B, Guo W, Zhang DY, Zhang JX. Advancing quantitative PCR with color cycle multiplex amplification. Nucleic Acids Res 2024; 52:e81. [PMID: 39119904 PMCID: PMC11417387 DOI: 10.1093/nar/gkae683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 07/01/2024] [Accepted: 08/02/2024] [Indexed: 08/10/2024] Open
Abstract
Quantitative PCR (qPCR) is the gold standard for detection and quantitation of known DNA targets, but the scarcity of spectrally distinct fluorophores and filter sets limits the number of detectable targets. Here, we introduce color cycle multiplex amplification (CCMA) to significantly increase the number of detectable DNA targets in a single qPCR reaction using standard instrumentation. In CCMA, presence of one DNA target species results in a pre-programmed pattern of fluorescence increases. This pattern is distinguished by cycle thresholds (Cts) through rationally designed delays in amplification. For example, we design an assay wherein Staphylococcus aureus sequentially induces FAM, then Cy5.5, then ROX fluorescence increases with more than 3 cycles between each signal. CCMA offers notably higher potential for multiplexing because it uses fluorescence permutation rather than combination. With 4 distinct fluorescence colors, CCMA theoretically allows the detection of up to 136 distinct DNA target sequences using fluorescence permutation. Experimentally, we demonstrated a single-tube qPCR assay screening 21 sepsis-related bacterial DNA targets in samples of blood, sputum, pleural effusion and bronchoalveolar lavage fluid, with 89% clinical sensitivity and 100% clinical specificity, showing its potential as a powerful tool for advanced quantitative screening in molecular diagnostics.
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Affiliation(s)
- Wei Chen
- Department of Innovation, NuProbe USA, Houston, TX 77054, USA
| | - Kerou Zhang
- Department of Innovation, NuProbe USA, Houston, TX 77054, USA
| | - Fei Huang
- Department of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai, Shanghai 200032, China
| | - Lan Zhao
- Department of Respiratory and Critical Care Medicine, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai 200433, China
| | | | - Qi Jiang
- Department of Innovation, NuProbe USA, Houston, TX 77054, USA
| | - Sherry X Chen
- Department of Innovation, NuProbe USA, Houston, TX 77054, USA
| | - Bonnie Wang
- Department of Innovation, NuProbe USA, Houston, TX 77054, USA
| | - Wei Guo
- Department of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai, Shanghai 200032, China
| | - David Y Zhang
- Department of Innovation, NuProbe USA, Houston, TX 77054, USA
| | - Jinny X Zhang
- Department of Innovation, NuProbe USA, Houston, TX 77054, USA
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Bao M, Waitkus J, Liu L, Chang Y, Xu Z, Qin P, Chen J, Du K. Micro- and nanosystems for the detection of hemorrhagic fever viruses. LAB ON A CHIP 2023; 23:4173-4200. [PMID: 37675935 DOI: 10.1039/d3lc00482a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/08/2023]
Abstract
Hemorrhagic fever viruses (HFVs) are virulent pathogens that can cause severe and often fatal illnesses in humans. Timely and accurate detection of HFVs is critical for effective disease management and prevention. In recent years, micro- and nano-technologies have emerged as promising approaches for the detection of HFVs. This paper provides an overview of the current state-of-the-art systems for micro- and nano-scale approaches to detect HFVs. It covers various aspects of these technologies, including the principles behind their sensing assays, as well as the different types of diagnostic strategies that have been developed. This paper also explores future possibilities of employing micro- and nano-systems for the development of HFV diagnostic tools that meet the practical demands of clinical settings.
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Affiliation(s)
- Mengdi Bao
- Department of Chemical and Environmental Engineering, University of California, Riverside, CA, USA.
| | - Jacob Waitkus
- Department of Chemical and Environmental Engineering, University of California, Riverside, CA, USA.
| | - Li Liu
- Department of Chemical and Environmental Engineering, University of California, Riverside, CA, USA.
| | - Yu Chang
- Department of Chemical and Environmental Engineering, University of California, Riverside, CA, USA.
| | - Zhiheng Xu
- Department of Industrial Engineering, Rochester Institute of Technology, Rochester, NY, USA
| | - Peiwu Qin
- Institute of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China
| | - Juhong Chen
- Department of Biological Systems Engineering, Virginia Tech, Blacksburg, VA, USA
| | - Ke Du
- Department of Chemical and Environmental Engineering, University of California, Riverside, CA, USA.
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Zhang Z, Zhang L, Liu Y, Hu C, Liu Q. Sensitive DNA Detection using a Branched DNA as a Sensor Coupled with Hybridization Chain Reaction. ChemistrySelect 2022. [DOI: 10.1002/slct.202201891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Affiliation(s)
- Zhikun Zhang
- School of Chemical and Pharmaceutical Engineering Hebei University of Science and Technology Shijiazhuang 050018 China
| | - Liu Zhang
- School of Chemical and Pharmaceutical Engineering Hebei University of Science and Technology Shijiazhuang 050018 China
| | - Yumin Liu
- School of Chemical and Pharmaceutical Engineering Hebei University of Science and Technology Shijiazhuang 050018 China
| | - Cuixia Hu
- School of Chemical and Pharmaceutical Engineering Hebei University of Science and Technology Shijiazhuang 050018 China
| | - Qingju Liu
- Beijing Research Center for Agriculture Standards and Testing Beijing Academy of Agriculture and Forestry Sciences Beijing 100097 China
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Chen FE, Trick AY, Hasnain AC, Hsieh K, Chen L, Shin DJ, Wang TH. Ratiometric PCR in a Portable Sample-to-Result Device for Broad-Based Pathogen Identification. Anal Chem 2022; 94:9372-9379. [PMID: 35730588 DOI: 10.1021/acs.analchem.2c01357] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Polymerase chain reaction (PCR)-based diagnostic testing is the gold standard method for pathogen identification (ID) with recent developments enabling automated PCR tests for point-of-care (POC) use. However, multiplexed identification of several pathogens in PCR assays typically requires optics for an equivalent number of fluorescence channels, increasing instrumentation's complexity and cost. In this study, we first developed ratiometric PCR that surpassed one target per color barrier to allow multiplexed identification while minimizing optical components for affordable POC use. We realized it by amplifying pathogenic targets with fluorescently labeled hydrolysis probes with a specific ratio of red-to-green fluorophores for each bacterial species. We then coupled ratiometric PCR and automated magnetic beads-based sample preparation within a thermoplastic cartridge and a portable droplet magnetofluidic platform. We named the integrated workflow POC-ratioPCR. We demonstrated that the POC-ratioPCR could detect one out of six bacterial targets related to urinary tract infections (UTIs) in a single reaction using only two-color channels. We further evaluated POC-ratioPCR using mock bacterial urine samples spiked with good agreement. The POC-ratioPCR presents a simple and effective method for enabling broad-based POC PCR identification of pathogens directly from crude biosamples with low optical instrumentation complexity.
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Affiliation(s)
- Fan-En Chen
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Alexander Y Trick
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Alexander C Hasnain
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Kuangwen Hsieh
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Liben Chen
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Dong Jin Shin
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Tza-Huei Wang
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States.,Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States.,Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, Maryland 21218, United States
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