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Yan Z, Hao T, Yan Y, Zhao Y, Wu Y, Tan Y, Bi Y, Cui Y, Yang R, Zhao Y. Quantitative and dynamic profiling of human gut core microbiota by real-time PCR. Appl Microbiol Biotechnol 2024; 108:396. [PMID: 38922447 DOI: 10.1007/s00253-024-13204-4] [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: 08/09/2023] [Revised: 05/05/2024] [Accepted: 05/27/2024] [Indexed: 06/27/2024]
Abstract
The human gut microbiota refers to a diverse community of microorganisms that symbiotically exist in the human intestinal system. Altered microbial communities have been linked to many human pathologies. However, there is a lack of rapid and efficient methods to assess gut microbiota signatures in practice. To address this, we established an appraisal system containing 45 quantitative real-time polymerase chain reaction (qPCR) assays targeting gut core microbes with high prevalence and/or abundance in the population. Through comparative genomic analysis, we selected novel species-specific genetic markers and primers for 31 of the 45 core microbes with no previously reported specific primers or whose primers needed improvement in specificity. We comprehensively evaluated the performance of the qPCR assays and demonstrated that they showed good sensitivity, selectivity, and quantitative linearity for each target. The limit of detection ranged from 0.1 to 1.0 pg/µL for the genomic DNA of these targets. We also demonstrated the high consistency (Pearson's r = 0.8688, P < 0.0001) between the qPCR method and metagenomics next-generation sequencing (mNGS) method in analyzing the abundance of selected bacteria in 22 human fecal samples. Moreover, we quantified the dynamic changes (over 8 weeks) of these core microbes in 14 individuals using qPCR, and considerable stability was demonstrated in most participants, albeit with significant individual differences. Overall, this study enables the simple and rapid quantification of 45 core microbes in the human gut, providing a promising tool to understand the role of gut core microbiota in human health and disease. KEY POINTS: • A panel of original qPCR assays was developed to quantify human gut core microbes. • The qPCR assays were evaluated and compared with mNGS using real fecal samples. • This method was used to dynamically profile the gut core microbiota in individuals.
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Affiliation(s)
- Ziheng Yan
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China
| | - Tongyu Hao
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China
| | - Yanfeng Yan
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China
| | - Yanting Zhao
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China
| | - Yarong Wu
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China
| | - Yafang Tan
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China
| | - Yujing Bi
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China
| | - Yujun Cui
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China
| | - Ruifu Yang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China.
- Beijing Key Laboratory of POCT for Bioemergency and Clinic, Beijing, 100071, China.
| | - Yong Zhao
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China.
- Beijing Key Laboratory of POCT for Bioemergency and Clinic, Beijing, 100071, China.
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Liu Y, Liu Y, Guo L, Wu Y, Wang Y, Xu L, Xu M, Huang S, Chen P, Wang T, Huang Q, Li Q. Multiplex Asymmetric PCR by Combining the Amplification Refractory Mutation System with the Homo-Tag-Assisted Nondimer System. Anal Chem 2024; 96:9200-9208. [PMID: 38771984 DOI: 10.1021/acs.analchem.4c01322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/23/2024]
Abstract
Asymmetric PCR is widely used to produce single-stranded amplicons (ss-amplicons) for various downstream applications. However, conventional asymmetric PCR schemes are susceptible to events that affect primer availability, which can be exacerbated by multiplex amplification. In this study, a new multiplex asymmetric PCR approach that combines the amplification refractory mutation system (ARMS) with the homo-Tag-assisted nondimer system (HANDS) is described. ARMS-HANDS (A-H) PCR utilizes equimolar-tailed forward and reverse primers and an excess Tag primer. The tailed primer pairs initiate exponential symmetric amplification, whereas the Tag primer drives linear asymmetric amplification along fully matched strands but not one-nucleotide mismatched strands, thereby generating excess ss-amplicons. The production of ss-amplicons is validated using agarose gel electrophoresis, sequencing, and melting curve analysis. Primer dimer alleviation is confirmed by both the reduced Loss function value and a 20-fold higher sensitivity in an 11-plex A-H PCR assay than in an 11-plex conventional asymmetric PCR assay. Moreover, A-H PCR demonstrates unbiased amplification by its allele quantitative ability in correct identification of all 31 trisomy 21 samples among 342 clinical samples. A-H PCR is a new generation of multiplex asymmetric amplification approach with various applications, especially when sensitive and quantitative detection is required.
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Affiliation(s)
- Ying Liu
- Engineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Xiamen University, Xiamen 361102, China
| | - Yinghua Liu
- Centre for Reproduction and Genetics, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou 215002, China
| | - Liu Guo
- Engineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Xiamen University, Xiamen 361102, China
| | - Yazhe Wu
- Engineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Xiamen University, Xiamen 361102, China
| | - Yafang Wang
- Engineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Xiamen University, Xiamen 361102, China
| | - Lingzhen Xu
- Engineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Xiamen University, Xiamen 361102, China
| | - Mingzhu Xu
- Engineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Xiamen University, Xiamen 361102, China
| | - Siyu Huang
- Engineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Xiamen University, Xiamen 361102, China
| | - Ping Chen
- NHC Key Laboratory of Thalassemia Medicine, Key Laboratory of Thalassemia Medicine, Chinese Academy of Medical Sciences, Guangxi Key Laboratory of Thalassemia Research, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China
| | - Ting Wang
- Centre for Reproduction and Genetics, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou 215002, China
| | - Qiuying Huang
- Engineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Xiamen University, Xiamen 361102, China
| | - Qingge Li
- Engineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Xiamen University, Xiamen 361102, China
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Kim MJ, Jung DR, Lee JM, Kim I, Son H, Kim ES, Shin JH. Microbial dysbiosis index for assessing colitis status in mouse models: A systematic review and meta-analysis. iScience 2024; 27:108657. [PMID: 38205250 PMCID: PMC10777064 DOI: 10.1016/j.isci.2023.108657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 09/07/2023] [Accepted: 12/04/2023] [Indexed: 01/12/2024] Open
Abstract
Although countless gut microbiome studies on colitis using mouse models have been carried out, experiments with small sample sizes have encountered reproducibility limitations because of batch effects and statistical errors. In this study, dextran-sodium-sulfate-induced microbial dysbiosis index (DiMDI) was introduced as a reliable dysbiosis index that can be used to assess the state of microbial dysbiosis in DSS-induced mouse models. Meta-analysis of 189 datasets from 11 independent studies was performed to construct the DiMDI. Microbial dysbiosis biomarkers, Muribaculaceae, Alistipes, Turicibacter, and Bacteroides, were selected through four different feature selection methods and used to construct the DiMDI. This index demonstrated a high accuracy of 82.3% and showed strong robustness (88.9%) in the independent cohort. Therefore, DiMDI may be used as a standard for assessing microbial imbalance in DSS-induced mouse models and may contribute to the development of reliable colitis microbiome studies in mouse experiments.
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Affiliation(s)
- Min-Ji Kim
- Department of Applied Biosciences, Kyungpook National University, Daegu 41566, Republic of Korea
| | - Da-Ryung Jung
- Department of Applied Biosciences, Kyungpook National University, Daegu 41566, Republic of Korea
| | - Ji-Min Lee
- Cell & Matrix Research Institute, Kyungpook National University, Daegu 41940, Republic of Korea
| | - Ikwhan Kim
- NGS Core Facility, Kyungpook National University, Daegu 41566, Republic of Korea
| | - HyunWoo Son
- Department of Applied Biosciences, Kyungpook National University, Daegu 41566, Republic of Korea
| | - Eun Soo Kim
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu 41944, Republic of Korea
| | - Jae-Ho Shin
- Department of Applied Biosciences, Kyungpook National University, Daegu 41566, Republic of Korea
- NGS Core Facility, Kyungpook National University, Daegu 41566, Republic of Korea
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Lee PW, Chen L, Hsieh K, Traylor A, Wang TH. Harnessing Variabilities in Digital Melt Curves for Accurate Identification of Bacteria. Anal Chem 2023; 95:15522-15530. [PMID: 37812586 DOI: 10.1021/acs.analchem.3c01654] [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] [Indexed: 10/11/2023]
Abstract
Digital PCR combined with high resolution melt (HRM) is an emerging method for identifying pathogenic bacteria with single cell resolution via species-specific digital melt curves. Currently, the development of such digital PCR-HRM assays entails first identifying PCR primers to target hypervariable gene regions within the target bacteria panel, next performing bulk-based PCR-HRM to examine whether the resulting species-specific melt curves possess sufficient interspecies variability (i.e., variability between bacterial species), and then digitizing the bulk-based PCR-HRM assays with melt curves that have high interspecies variability via microfluidics. In this work, we first report our discovery that the current development workflow can be inadequate because a bulk-based PCR-HRM assay that produces melt curves with high interspecies variability can, in fact, lead to a digital PCR-HRM assay that produces digital melt curves with unwanted intraspecies variability (i.e., variability within the same bacterial species), consequently hampering bacteria identification accuracy. Our subsequent investigation reveals that such intraspecies variability in digital melt curves can arise from PCR primers that target nonidentical gene copies or amplify nonspecifically. We then show that computational in silico HRM opens a window to inspect both interspecies and intraspecies variabilities and thus provides the missing link between bulk-based PCR-HRM and digital PCR-HRM. Through this new development workflow, we report a new digital PCR-HRM assay with improved bacteria identification accuracy. More broadly, this work can serve as the foundation for enhancing the development of future digital PCR-HRM assays toward identifying causative pathogens and combating infectious diseases.
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Affiliation(s)
- Pei-Wei Lee
- 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
| | - Kuangwen Hsieh
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Amelia Traylor
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Tza-Huei Wang
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland 21205, United States
- Institute of NanoBioTechnology, Johns Hopkins University, Baltimore, Maryland 21218, United States
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Cui X, Ngang S, Liu DD, Cheow LF. Rapid Single-Round Pool Testing of Infectious Disease Enabled by Multicolor Digital Melting PCR. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2023; 19:e2205636. [PMID: 37209020 DOI: 10.1002/smll.202205636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 04/27/2023] [Indexed: 05/21/2023]
Abstract
Pooled nucleic acid amplification test is a promising strategy to reduce cost and resources for screening large populations for infectious disease. However, the benefit of pooled testing is reversed when disease prevalence is high, because of the need to retest each sample to identify infected individual when a pool is positive. Split, Amplify, and Melt analysis of Pooled Assay (SAMPA) is presented, a multicolor digital melting PCR assay in nanoliter chambers that simultaneously identify infected individuals and quantify their viral loads in a single round of pooled testing. This is achieved by early sample tagging with unique barcodes and pooling, followed by single molecule barcode identification in a digital PCR platform using a highly multiplexed melt curve analysis strategy. The feasibility is demonstrated of SAMPA for quantitative unmixing and variant identification from pools of eight synthetic DNA and RNA samples corresponding to the N1 gene, as well as from heat-inactivated SARS-CoV-2 virus. Single round pooled testing of barcoded samples with SAMPA can be a valuable tool for rapid and scalable population testing of infectious disease.
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Affiliation(s)
- Xu Cui
- Department of Biomedical Engineering & Institute for Health Innovation and Technology, National University of Singapore, Singapore, 119077, Singapore
| | - Shaun Ngang
- Department of Biomedical Engineering & Institute for Health Innovation and Technology, National University of Singapore, Singapore, 119077, Singapore
| | - Dong Dong Liu
- Department of Biomedical Engineering & Institute for Health Innovation and Technology, National University of Singapore, Singapore, 119077, Singapore
| | - Lih Feng Cheow
- Department of Biomedical Engineering & Institute for Health Innovation and Technology, National University of Singapore, Singapore, 119077, Singapore
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Liu DD, Muliaditan D, Viswanathan R, Cui X, Cheow LF. Melt-Encoded-Tags for Expanded Optical Readout in Digital PCR (METEOR-dPCR) Enables Highly Multiplexed Quantitative Gene Panel Profiling. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2301630. [PMID: 37485651 PMCID: PMC10520687 DOI: 10.1002/advs.202301630] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 06/27/2023] [Indexed: 07/25/2023]
Abstract
Digital PCR (dPCR) is an important tool for precise nucleic acid quantification in clinical setting, but the limited multiplexing capability restricts its applications for quantitative gene panel profiling. Here, this work describes melt-encoded-tags for expanded optical readout in digital PCR (METEOR-dPCR), a simple two-step assay that enables simultaneous quantification of a large panel of arbitrary genes in a dPCR platform. Target genes are quantitatively converted into DNA tags with unique melting temperatures through a ligation approach. These tags are then counted and distinguished by their melt-curve profiles on a dPCR platform. A multiplexing capacity of M^N, where M is the number of resolvable melting temperature and N is the number of fluorescence channel, can be achieved. This work validates METEOR-dPCR with simultaneous DNA copy number profiling of 60 targets using dPCR in cancer cells, and demonstrates its sensitivity for estimating tumor fraction in mixed tumor and normal DNA samples. The rapid, quantitative, and highly multiplexed METEOR-dPCR assay will have wide appeal for many clinical applications.
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Affiliation(s)
- Dong Dong Liu
- Institute for Health Innovation and TechnologyNational University of SingaporeSingapore117599Singapore
| | - Daniel Muliaditan
- Department of Biomedical EngineeringFaculty of EngineeringNational University of SingaporeSingapore117583Singapore
- Genome institute of SingaporeAgency for ScienceTechnology and ResearchSingapore138672Singapore
| | - Ramya Viswanathan
- Institute for Health Innovation and TechnologyNational University of SingaporeSingapore117599Singapore
- Department of Biomedical EngineeringFaculty of EngineeringNational University of SingaporeSingapore117583Singapore
| | - Xu Cui
- Department of Biomedical EngineeringFaculty of EngineeringNational University of SingaporeSingapore117583Singapore
| | - Lih Feng Cheow
- Institute for Health Innovation and TechnologyNational University of SingaporeSingapore117599Singapore
- Department of Biomedical EngineeringFaculty of EngineeringNational University of SingaporeSingapore117583Singapore
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Cai D, Wang Y, Zou J, Li Z, Huang E, Ouyang X, Que Z, Luo Y, Chen Z, Jiang Y, Zhang G, Wu H, Liu D. Droplet Encoding-Pairing Enabled Multiplexed Digital Loop-Mediated Isothermal Amplification for Simultaneous Quantitative Detection of Multiple Pathogens. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2205863. [PMID: 36646503 PMCID: PMC9982564 DOI: 10.1002/advs.202205863] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 12/06/2022] [Indexed: 06/01/2023]
Abstract
Despite the advantages of digital nucleic acid analysis (DNAA) in terms of sensitivity, precision, and resolution, current DNAA methods commonly suffer a limitation in multiplexing capacity. To address this issue, a droplet encoding-pairing enabled DNAA multiplexing strategy is developed, wherein unique tricolor combinations are deployed to index individual primer droplets. The template droplets and primer droplets are sequentially introduced into a microfluidic chip with a calabash-shaped microwell array and are pairwise trapped and merged in the microwells. Pre-merging and post-amplification image analysis with a machine learning algorithm is used to identify, enumerate, and address the droplets. By incorporating the amplification signals with droplet encoding information, simultaneous quantitative detection of multiple targets is achieved. This strategy allows for the establishment of flexible multiplexed DNAA by simply adjusting the primer droplet library. Its flexibility is demonstrated by establishing two multiplexed (8-plex) droplet digital loop-mediated isothermal amplification (mddLAMP) assays for individually detecting lower respiratory tract infection and urinary tract infection causative pathogens. Clinical sample analysis shows that the microbial detection outcomes of the mddLAMP assays are consistent with those of the conventional assay. This DNAA multiplexing strategy can achieve flexible high-order multiplexing on demand, making it a desirable tool for high-content pathogen detection.
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Affiliation(s)
- Dongyang Cai
- Department of Laboratory Medicinethe Second Affiliated HospitalSchool of MedicineSouth China University of TechnologyGuangzhou510180China
| | - Yu Wang
- Department of Laboratory Medicinethe Second Affiliated HospitalSchool of MedicineSouth China University of TechnologyGuangzhou510180China
| | - Jingjing Zou
- College of Food Science and EngineeringSouth China University of TechnologyGuangzhou510640China
| | - Zhujun Li
- Department of Laboratory Medicinethe Second Affiliated HospitalSchool of MedicineSouth China University of TechnologyGuangzhou510180China
| | - Enqi Huang
- Department of Laboratory Medicinethe Second Affiliated HospitalSchool of MedicineSouth China University of TechnologyGuangzhou510180China
| | - Xiuyun Ouyang
- College of Food Science and EngineeringSouth China University of TechnologyGuangzhou510640China
| | - Zhiquan Que
- Department of Laboratory Medicinethe Second Affiliated HospitalSchool of MedicineSouth China University of TechnologyGuangzhou510180China
| | - Yanzhang Luo
- Department of Laboratory Medicinethe Second Affiliated HospitalSchool of MedicineSouth China University of TechnologyGuangzhou510180China
| | - Zhenhua Chen
- Department of Laboratory Medicinethe Second Affiliated HospitalSchool of MedicineSouth China University of TechnologyGuangzhou510180China
| | - Yanqing Jiang
- Beijing Baicare Biotechnology Co., LtdBeijing102206China
| | - Guohao Zhang
- Beijing Baicare Biotechnology Co., LtdBeijing102206China
| | - Hongkai Wu
- Department of ChemistryHong Kong University of Science and TechnologyHong KongChina
| | - Dayu Liu
- Department of Laboratory Medicinethe Second Affiliated HospitalSchool of MedicineSouth China University of TechnologyGuangzhou510180China
- Guangdong Engineering Technology Research Center of Microfluidic Chip Medical DiagnosisGuangzhou510180China
- Clinical Molecular Medicine and Molecular Diagnosis Key Laboratory of Guangdong ProvinceGuangzhou510180China
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