RESEARCH
Peer reviewed scientific video journal
Video encyclopedia of advanced research methods
Visualizing science through experiment videos
EDUCATION
Video textbooks for undergraduate courses
Visual demonstrations of key scientific experiments
BUSINESS
Video textbooks for business education
OTHERS
Interactive video based quizzes for formative assessments
Products
RESEARCH
JoVE Journal
Peer reviewed scientific video journal
JoVE Encyclopedia of Experiments
Video encyclopedia of advanced research methods
EDUCATION
JoVE Core
Video textbooks for undergraduates
JoVE Science Education
Visual demonstrations of key scientific experiments
JoVE Lab Manual
Videos of experiments for undergraduate lab courses
BUSINESS
JoVE Business
Video textbooks for business education
Solutions
Language
English
Menu
Menu
Menu
Menu
A subscription to JoVE is required to view this content. Sign in or start your free trial.
Research Article
Yu-Liang Huang*1, Hua-Mei Chen*2, Hua-Wei He1, Zi-Huan Lu3, Xin-Qiang Zhang3, You-Wei Zheng3, Jin-xin Lai3, Cheng-Yuan He3, Xiao-Cheng Luo1, Zheng-Kang Li3
1the Fourth People's Hospital of Nanning, 2The Fangchenggang Hospital of the People's Hospital of Guangxi Zhuang Autonomous Region - The First People's Hospital of Fangchenggang City, 3Department of Clinical Laboratory, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences),Southern Medical University
Erratum Notice
Important: There has been an erratum issued for this article. View Erratum Notice
Retraction Notice
The article Assisted Selection of Biomarkers by Linear Discriminant Analysis Effect Size (LEfSe) in Microbiome Data (10.3791/61715) has been retracted by the journal upon the authors' request due to a conflict regarding the data and methodology. View Retraction Notice
This article recommends a fully automated integrated system that employs triple PCR technology to simultaneously diagnose co-infections of Chikungunya, Dengue, and Zika virus using a single sample, thereby optimizing testing efficiency in clinical and primary care laboratories.
Chikungunya fever (CHIKF), an acute viral illness transmitted by mosquitoes and first discovered in Tanzania in 1952, has shown intermittent spread in China, with increasing local outbreaks. By July 2025, Guangdong Province, currently the outbreak's center, had reported 4,824 local cases, including nearly 3,000 new infections in just one week. This rapid surge creates an urgent need for advanced diagnostic technologies. Such tools are critical to support containment efforts on the front lines. We propose a solution for the rapid simultaneous detection of dengue (DENV), chikungunya (CHIKV), and Zika virus (ZIKV) infections to enhance early epidemic prevention and control capabilities. This approach involves developing customized testing protocols for border checkpoints and primary healthcare facilities.
Traditional diagnostic methods for CHIKV and DENV often lack sensitivity/specificity in coinfection cases. Since CHIKV, DENV, and ZIKV share similar transmission patterns and symptoms, simultaneous monitoring is crucial. This protocol presents a triplex qPCR method using TaqMan probes to detect these arboviruses in a single tube within 90 min. Compared to viral culture and serological tests, this method improves efficiency by identifying active infections and coinfections with high specificity while simplifying workflow and eliminating specialized equipment requirements.
Validation with clinical and External Quality Assessment (EQA) samples confirmed 100% concordance with gold-standard singleplex assays. This method serves as an effective tool for monitoring febrile illnesses in endemic regions, particularly in resource-limited settings where rapid outbreak containment is critical.
Chikungunya fever (CHIKF) is an increasingly prevalent arboviral disease primarily transmitted by the mosquito vectors Aedes aegypti and Aedes albopictus. Characterized by recurrent outbreaks in tropical regions, this disease clinically manifests as an acute febrile illness, often accompanied by severe joint pain and persistent arthritis1. As of July 26, the cumulative total of laboratory-confirmed chikungunya cases in Foshan City had reached 4,824, with a remarkable 87.2% of these cases occurring in Shunde District. This pronounced geographic concentration imposes a substantial burden on the regional public health infrastructure and results in significant healthcare costs, along with broader macroeconomic challenges2.
In the context of the increasingly overlapping circulation of CHIKV, DENV, and ZIKV viruses, current diagnostic methodologies encounter three primary limitations. First, serological assays are unable to distinguish acute infections due to the prolonged persistence of antibodies following viral clearance1. Second, viral culture techniques exhibit sensitivity rates low and require several days, thereby impeding timely clinical decision-making. Third, although quantitative PCR assays demonstrate high specificity (exceeding 95%), they cannot detect co-infections within a single reaction, which is a significant drawback given the reported 12.8% CHIKV-DENV co-infection rate in India3. Phylogenetic monitoring indicates a paradigm shift. The ECSA lineage, which was dominant during India's 2019-2022 epidemic, has acquired convergent mutations in its envelope proteins: E1-A226V (enhancing mosquito infectivity) and E2-K252Q (associated with immune evasion). These mutations have resulted in a genotype with documented higher virulence, as reported in recent surveillance studies from Kerala and Maharashtra3. Concurrently, China faces challenges from the importation of the ECSA genotype, as documented in the Yunnan outbreak, and other genotypes, with autochthonous transmission reported in multiple provinces, including Yunnan4.
These realities create urgent, resource-limited needs for (i) differential diagnosis despite overlapping clinical manifestations5, (ii) diagnostic assays that eliminate the complexity of instrumentation typically required by conventional real-time quantitative PCR (qPCR)6, and (iii) comprehensive validation of novel point-of-care technologies, including RT-LAMP and CRISPR-based methods5. To address these diagnostic challenges, we propose a rapid triple-PCR assay that uses a fully automated integrated system, enabling simultaneous detection of CHIKV, DENV, and ZIKV in a single reaction. We validated the performance of our triplex qPCR assay through direct comparison with established singleplex assays5, which served as the reference standard. The following sections detail the procedures for both the triplex assay and the reference singleplex assays. The comparative analysis of results from both methods is presented in the Representative Results section.
This study adheres to the ethical guidelines established by the Ethics Committee of Guangdong Provincial People's Hospital, Southern Medical University, Guangzhou, China (approval no: KY2025-510-01). Detailed information regarding the materials used in this research (reagents, chemicals, equipment, and software) can be found in the Table of Materials.
1. Participant selection
2. Sample collection and processing
3. Automated Triplex qPCR Detection of CHIKV, DENV, and ZIKV
4. Reference Singleplex qPCR assays for method comparison
5. Biosafety and waste disposal
To validate the stability and accuracy of the triple PCR detection system, we selected five clinically representative samples from our internal laboratory and ten external EQA blind samples for verification. These five representative clinical samples include both negative and positive cases (S1-S5), including samples positive for CHIKV and DENV, selected to demonstrate the assay's clinical applicability and to support internal validation of test performance (Table 1). The 2025 EQA blinded sample panel for emerging mosquito-borne pathogens comprised 10 inactivated plasma samples (DZC2511-2520). These contained various concentrations and combinations of CHIKV, DENV, and ZIKV. These concentrations and combinations were pre-determined by the NCCL. Analysis of this panel using our triple qPCR platform was entirely consistent with reference results (Table 2), confirming the robustness and clinical applicability of the assay.
The triplex qPCR assay reliably distinguished between negative and positive infections across all validation samples (Figure 1). In the clinical cohort, the assay identified two samples (S2, S3) as positive for CHIKV and one sample (S5) for DENV, while samples S1 and S4 were negative for all three targets (Figure 2, Table 1). The amplification curves for these targets exhibited characteristic sigmoidal kinetics, with clear separation from the baseline, and all internal controls amplified as expected, confirming assay validity.
The singleplex qPCR assay reliably distinguished between negative and positive infections across all validation samples (Figure 3). It is worth noting that the singleplex test results of the same batch of clinical samples are entirely consistent with the singleplex qPCR test results (Figure 4, Table 1). This demonstrates that the multiplexed format does not compromise diagnostic accuracy.
The assay's performance was further confirmed through an external validation using a blinded quality assessment panel. The triplex qPCR results achieved 100% qualitative agreement with the reference outcomes across all 10 samples, accurately identifying CHIKV, DENV, and ZIKV in the respective panels, without any false positives or negatives (Table 2). This confirms the method's robustness and readiness for deployment in routine diagnostic and public health settings.

Figure 1: Quality control results of triplex qPCR detection of negative and positive controls. Negative controls must exhibit an S-shaped growth curve in the CY5-IC detection channel, with a Ct value ≤ 40.00. In contrast, fluorescence signals in the FAM-DENV, HEX-ZIKV, and ROX-CHIKV channels should not demonstrate significant increases, resulting in Ct values > 40.00 or no discernible signal. Positive controls are required to display S-shaped curves across all detection channels, with Ct values ≤ 37.00. Please click here to view a larger version of this figure.

Figure 2: Detection of CHIKV, DENV, and ZIKV nucleic acids in blood samples performed using triplex qPCR. Each fluorescent signal corresponds to a specific gene, with ROX (yellow) indicating CHIKV virus genes, FAM (blue) indicating DENV virus genes, HEX (orange) indicating ZIKV virus genes, and CY5 (green) indicating the internal control gene. Sample phenotypes were as follows: S1 was negative for CHIKV (no signal above threshold); S2 and S3 were positive for CHIKV (ROX signal above threshold); S4 was negative for CHIKV (no signal above threshold); and S5 was positive for DENV (FAM signal above threshold). Please click here to view a larger version of this figure.

Figure 3: Quality control results of Singleplex qPCR detection of negative and positive controls. Negative controls must not exhibit significant increases in fluorescence signals for the FAM and VIC channels, with Ct values exceeding 40.00 or no discernible signal. In contrast, positive controls should display S-shaped curves in all detection channels, with Ct values equal to or less than 32.00. Please click here to view a larger version of this figure.

Figure 4: Detection of CHIKV and dengue virus nucleic acids in blood samples using Singleplex qPCR. Each color denotes a distinct fluorescent signal, with different signals corresponding to specific genes. The fluorescence channels include FAM fluorescent labeling (blue) for CHIKV genes and CY5 fluorescent labeling (green) for the internal control gene. The sample phenotypes are as follows: S1 is a Chikungunya-negative sample (no signal above threshold); S2 is a CHIKV-positive sample (FAM signal above threshold); S3 is also a CHIKV-positive sample (FAM signal above threshold); S4 is a CHIKV-negative sample (no signal above threshold); and S5 is a dengue-positive sample (FAM signal above threshold). Please click here to view a larger version of this figure.
| sample | The triplex qPCR assay | The singleplex qPCR assay | ||
| CHIKV( ROX) | DENV(FAM) | CHIKV( FAM) | DENV( FAM) | |
| Ct(+/−) | Ct(+/−) | Ct(+/−) | Ct(+/−) | |
| S1 | NA(−) | NA(−) | NA(−) | NA(−) |
| S2 | 13.71(+) | NA(−) | 16.67(+) | NA(−) |
| S3 | 15.19(+) | NA(−) | 18.02(+) | NA(−) |
| S4 | NA(−) | NA(−) | NA(−) | NA(−) |
| S5 | NA(−) | 27.7(+) | NA(−) | 33.1(+) |
| negative | NA(−) | NA(−) | NA(−) | NA(−) |
| posetive | 27.57(+) | 30.35(+) | 14.78(+) | 28.17(+) |
Table1: Results of qPCR for five representative clinical samples. The table provides the qualitative results of detection in samples S2 and S3 indicates that these two patients are infected with the CHIKV virus, while detection in sample S5 signifies infection with the dengue virus. "NA" denotes that no Ct value was detected. Legend: +/- indicates qualitative results; "+" represents a positive result, whereas "-" indicates a negative result.
| sample | The triplex qPCR assay | The singleplex qPCR assay | ||||
| CHIK(ROX) | DENV (FAM) | ZIKa (HEX) | CHIKV( FAM) | DENV( FAM) | ZIKa ( FAM) | |
| Ct(+/−) | Ct(+/−) | Ct(+/−) | Ct(+/−) | Ct(+/−) | Ct(+/−) | |
| 2511 | 26.16(+) | NA(−) | NA(−) | 29.30(+) | NA(−) | NA(−) |
| 2512 | NA(−) | 34.68(+) | NA(−) | NA(−) | 34.64(+) | NA(−) |
| 2513 | NA(−) | NA(−) | 28.68(+) | NA(−) | NA(−) | 32.70(+) |
| 2514 | 23.4(+) | NA(−) | NA(−) | 26.36(+) | NA(−) | NA(−) |
| 2515 | NA(−) | NA(−) | NA(−) | NA(−) | NA(−) | NA(−) |
| 2516 | 29.28(+) | NA(−) | NA(−) | 32.14(+) | NA(−) | NA(−) |
| 2517 | NA(−) | 33.24(+) | NA(−) | NA(−) | 38.63(+) | NA(−) |
| 2518 | NA(−) | NA(−) | NA(−) | NA(−) | NA(−) | NA(−) |
| 2519 | NA(−) | NA(−) | 28.56(+) | NA(−) | NA(−) | 33.87(+) |
| 2520 | NA(−) | NA(−) | NA(−) | NA(−) | NA(−) | NA(−) |
| negative | NA(−) | NA(−) | NA(−) | NA(−) | NA(−) | NA(−) |
| posetive | 12.7(+) | 14.47(+) | 13.07(+) | 23.00(+) | 28.27(+) | 26.55(+) |
Table 2: The qualitative outcomes of qPCR analysis from the 2025 EQA panel for emerging and re-emerging mosquito-borne pathogens transmitted through blood. The table provides the qualitative results of samples 2511, 2514, and 2516 tested positive for CHIKV RNA, samples 2512 and 2517 showed positivity for DENV RNA, and samples 2513 and 2519 exhibited positivity for ZIKV RNA. The notation "NA" indicates the absence of a recorded Ct value. In this context, symbols such as "+/-" are used to denote qualitative assessments, with "+" indicating a positive outcome and "-" indicating a negative result.
CHIKV is a positive-sense, single-stranded RNA virus classified within the alphavirus genus of the Togaviridae family7. Accelerated global warming, intensified international commerce, and expanding tourism networks have collectively heightened the risk of human exposure to arboviral threats8. Over the past decade, the rapid evolution of molecular diagnostics has fundamentally transformed the landscape of infectious disease management. Among these technologies, qPCR has gained particular prominence in clinical laboratories across China due to its rapid turnaround, exceptional analytical sensitivity, high quantitative accuracy, and significantly reduced risk of cross-contamination during routine operations2. By integrating a single blood draw with a triplex qPCR platform that simultaneously detects CHIKV, DENV, and ZIKV, we can now screen for both mono- and co-infections within a single analytical window.This streamlined workflow provides clinicians with actionable laboratory evidence that supports early, precise, and decisive public health interventions.
This study advances arboviral diagnostics by integrating triplex qPCR into a fully automated, closed-tube platform optimized for point-of-care use. Unlike conventional multiplex PCR, which requires specialized equipment9,10,11, our system consolidates extraction and amplification within a single device, delivering simultaneous results for CHIKV, DENV, and ZIKV from one blood sample in 90 min.As shown in Tables 1 and 2, the assay demonstrated perfect agreement with both gold-standard singleplex PCR and EQA samples. This confirms that the streamlined, contamination-resistant workflow enhances operational efficiency in resource-constrained settings without compromising diagnostic accuracy. Illustrated in Methodological Steps 3 and 4, the integrated system maintains diagnostic precision while simplifying procedures, significantly reducing manual handling time, cross-contamination risk, and operator skill requirements. Thus, our system translates laboratory-grade testing into a practical tool for rapid screening and outbreak management in resource-limited environments.
Quality control standards are crucial for qPCR detection, encompassing instrument calibration, verification of detection system performance, evaluation of nucleic acid extraction efficiency, and batch experiment quality control. Sampling instruments undergo biannual calibration, while extraction and amplification equipment are calibrated annually, along with reagent batch calibration.Post-calibration, performance validation is carried out using the SLAN 96S Fluorescence Quantitative PCR system and specific detection kits, extraction reagents, sample tubes, pipettes, and tips. The criteria evaluated include conformity rate, detection limit, anti-interference, cross-reaction, and precision, with unqualified samples necessitating reextraction. Ensuring valid results requires daily adherence to quality control procedures and adherence to established standards for meticulous analysis. Run validity mandates a sigmoidal amplification curve with Ct ≤ 30.00 in the CY5 channel for the negative control.In contrast, no amplification (Ct > 40.00 or undetectable fluorescence) is acceptable in the FAM, HEX, and ROX channels. The positive control should show sigmoidal curves in all four channels, with Ct values ≤ 37.00 in each channel. If one or more pathogen targets are detected, the corresponding internal control is exempt from acceptance criteria if sigmoidal amplification with Ct ≤ 37.00 is observed.
The consistently high performance of qPCR in prior studies underscores its utility in arboviral diagnosis. Direct application to blood samples has proven highly effective in detecting chikungunya and dengue viruses with exceptional sensitivity and specificity11,12,13. The strong concordance observed across these studies confirms that qPCR serves as a cornerstone methodology for reliable virus monitoring and clinical diagnostics in high-endemic settings. Building on this methodology, our research integrates nucleic acid extraction and amplification into a fully automated system. This innovation minimizes operator-dependent variability and eliminates cross-contamination risks, enabling rapid sample-to-result analysis. The system performs end-to-end processing, from nucleic acid purification to automated report generation, ensuring contact-free operation while maintaining contamination-free conditions. This integrated approach achieves laboratory-grade biosafety throughout the workflow, making it particularly suitable for high-throughput screening scenarios with limited personnel and equipment resources. We rigorously assessed the diagnostic performance of our newly developed triplex qPCR assay using a dual-validation approach.
We initially compared our internal assay to a certified singleplex PCR kit using five clinical samples (S1-S5) from patients with similar symptoms, such as fever and joint pain. The results, depicted in Figures 2,4 and Table 1, showed complete agreement between the two methods, confirming their equal sensitivity and specificity in detecting CHIKV, DENV, and ZIKV. To assess the assay's robustness, we conducted an external validation with 10 blinded plasma samples from the 2025 EQA program. Our Triplex qPCR showed perfect concordance with the reference method across a range of viral concentrations. This dual-verification approach validates the assay's accuracy across multiple targets and its reliability in both laboratory-controlled and external quality-assessment settings. The successful validation of this Triplex qPCR system highlights its significant clinical value. By consolidating the detection of three common arboviruses into a single, rapid test, it streamlines the precise identification of the causative agent, crucial for prompt diagnosis and patient care. This capability is especially vital for distinguishing between infections with similar symptoms, particularly in outbreak scenarios. The method offers a streamlined, efficient, and robust solution for clinical laboratories, with the potential to significantly improve diagnostic throughput and facilitate appropriate public health responses. It is essential to consider pre-analytical variables when assessing the diagnostic accuracy of any blood-based qPCR approach. Factors such as gross lipemia, hemolysis, or the use of heparinized specimens can significantly impact results, potentially leading to false-negative results. Furthermore, RNA arboviruses exhibit rapid evolutionary changes in mosquito vectors, leading to nucleotide divergence over time. While the primers and probes utilized in this study were designed to target conserved genomic regions, it is important to note that rare or emergent mutations occurring outside the specified amplicons may go undetected, potentially affecting the overall completeness of the results14.
Future research should prioritize developing innovative methodologies to improve mutational surveillance, such as utilizing next-generation sequencing for samples with inconclusive qPCR outcomes to identify undetected viral genomes missed by standard assays, particularly in complex or unusual cases. Simultaneously, public health initiatives need to emphasize comprehensive vector-monitoring schemes and robust mosquito control measures, particularly in high-risk areas, to reduce Aedes mosquito populations and prevent local transmission15,16. Additionally, enhanced health education programs targeting travelers and communities near borders are crucial for reinforcing personal protective practices and sustaining integrated strategies for reducing arboviral risks.
Despite its proven effectiveness, our triplex qPCR test has limitations that require attention. The primer and probe sequences are not disclosed due to commercial patent constraints. However, the specific genomic regions targeted (e.g., E1 for CHIKV, NS5 for DENV, and ZIKV) are provided to promote scientific transparency. Moreover, as with all molecular tests, pre-analytical factors (e.g., hemolysis, lipemia, heparin use) are critical; deviations can compromise RNA quality and lead to false negatives. Finally, this study did not establish the limit of detection via serial dilution of standardized controls for all targets-a key aspect of analytical validation that remains to be addressed in future work.
The authors declare that they have no competing interests.
This study was funded by the Guangdong Medical Research Foundation (A2025034). The funders had no role in the study design, data collection and analysis, the decision to publish, or the preparation of the manuscript. This work was also supported by the Guangxi Key Research and Development Program (Guike-AB25069058).
| Automated nucleic acid extractor | DAAN | Smart 32 | For DNA extraction |
| BECKMAN X-12 | BECKMAN | ALA04H01 | For serum centrifugation |
| BSC-1500IIA2-X | BIOBASE | SEDA 20143222263 | Biosafety cabinet |
| E-Centrifuge | WEALTEC | Centrifuge the residual liquid off the wall of the tube | |
| Fully automatic medical PCR analyzer | Bioustar | UP0102 | Fluorescent quantitative PCR amplification |
| Nucleic acid detection kit for chikungunya virus (PCR-fluorescent probe method) | DAAN | 20250804 | Detection of chikungunya virus genes |
| Nucleic acid detection kit for Dengue virus (PCR-fluorescent probe method) | DAAN | 202504003 | Detection of Dengue virusvirus genes |
| Nucleic acid detection kit for Dengue virus, Zika virus and chikungunya virus (PCR-fluorescent probe method) | Bioustar | 20250724 | Detection of Dengue virus, Zika virus and chikungunya virus genes |
| Nucleic acid detection kit for Zika virus (PCR-fluorescent probe method) | DAAN | 202508041 | Detection of Zika virus genes |
| Nucleic acid extraction kit | DAAN | Extract nucleic acid | |
| SLAN Fully automatic medical PCR analysis system | HONGSHI | Data Analysis | |
| SLAN-96S Real-Time PCR machine | HONGSHI | SLAN-96S | Fluorescent quantitative PCR amplification |
| Ultra-low temperature freezers (DW-YL450) | MELING | SEDA 20172220091 | -20 °C for storing reagents |
| Vortex-5 | Kylin-bell | For mixing reagent |