Novel point-of-care rapid detection of monkeypox virus

Hui Chen^ab, Yuhong Guan^b, Xinyu Zhang^b, Yuting Chen^b, Song Li^a, Yan Deng^a and Yanqi Wu*^cd
aInstitute of Cytology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
^bHunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou, China
^cState Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Taipa, China. E-mail: wyin360@126.com
^dShenzhen LemnisCare Medical Technology Co., Ltd, Shenzhen, China

First published on 27th August 2024

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1. Introduction

Monkeypox is a viral zoonotic disease with symptoms resembling those of historical smallpox patients. The monkeypox virus, an enveloped, double-stranded DNA virus, has emerged as a significant Orthopoxvirus for public health due to the decline in smallpox cases.^1–5 Primarily found in central and western Africa, particularly near tropical rainforests, monkeypox is now increasingly affecting urban areas.^6–8 Since 2017, cases caused by travel have been reported in many countries, including Israel, the United Kingdom, Singapore, and the United States of America.^9–14

Confirmation of monkeypox relies on the quality and type of specimen as well as the laboratory testing method. Therefore, specimens should be handled and transported following national and international guidelines. Polymerase chain reaction (PCR) is the preferred laboratory test due to its accuracy and sensitivity.^15–18 Lesion samples should be stored in dry, sterile tubes with virus-free transport medium and kept cold.¹⁹ Serological and antigen testing methods cannot confirm monkeypox specificity due to cross-reactivity with orthopoxviruses.²⁰ The World Health Organization advises against using these methods for diagnosis or case investigation in resource-limited settings. Given the global public health importance of monkeypox, surveillance and swift identification of new cases are crucial for epidemic control. Point-of-care testing (POCT) offers a solution for lesion sample collection and preservation, providing high sensitivity and cost-effective rapid detection, particularly for diseases prevalent in African communities.²¹

Point-of-care testing (POCT) products are extensively utilized in various public health sectors including clinical testing, major epidemic detection, food safety monitoring, drug testing, and alcohol testing. They can also play a role in individual health management.^22,23 These products streamline the sample transmission process and reduce reporting time. In comparison to traditional department or laboratory diagnosis methods, POCT maintains the fundamental steps of ‘sampling–analysis–quality control–output’, leading to a significant reduction in diagnosis time and space requirements for testing. The flexibility of POCT allows non-professionals or even the individuals being tested to operate the equipment.²⁴ The process is simple, does not necessitate professional expertise, has minimal steps, provides rapid results, offers personalized testing, and features portable instruments and reagents with constantly expanding application fields. For rapid and low-demand detection of the monkeypox virus, Loop-Mediated Isothermal Amplification (LAMP) technology can be considered due to its simplicity in operation and instrument requirements compared to PCR technology.^25,26 This technology has been successfully utilized in the development of home-use rapid nucleic acid detection kits for the novel coronavirus, enabling detection within 20 minutes.

In this study, an efficient LAMP detection system for monkeypox virus was established to achieve rapid detection. Testing was conducted in an integrated system with samples processed and results obtained, and performance was compared with conventional laboratory instruments and PCR detection. The goal was to accurately detect monkeypox qualitatively, aiming for sensitivity and specificity similar to the gold standard QPCR but with reduced time and operational requirements. The ultimate aim is to help mitigate or control the epidemic.

2. Materials and method

2.1 Integrated system inspection process

The integrated detection system incorporates nucleic acid extraction and amplification detection processes, facilitating sample entry and result output. Nucleic acid extraction in this system utilizes the magnetic bead method, offering advantages in automation, process optimization, and efficiency compared to other extraction methods. The higher sample concentration post-extraction enhances downstream detection sensitivity. The amplification detection module enables temperature cycling and fluorescence detection, allowing real-time fluorescence PCR and LAMP detection. To align with the requirements of point-of-care testing (POCT), preference is given to LAMP detection on the all-in-one machine for testing purposes.

The integrated detection process of monkeypox virus is illustrated in Fig. 1. Initially, samples of the virus are collected and processed before being introduced into the integrated system. This system comprises a closed detection cartridge and an automated detection system. The detection cartridge serves as a vessel for viral nucleic acid detection, containing all necessary reagents pre-packaged within. During testing, the collected virus sample is first added to the lysis well in the cartridge and mixed by pipetting. Subsequently, the lysis well is sealed, inserted into the automated instrument via the entire cartridge, and the reaction parameters are set through the human–computer interaction interface on the instrument. The experiment is then initiated, allowing users to monitor the progress and results in real-time through the amplification curve. Upon completion of the experiment, the test report is presented on the human–computer interaction interface. The process involves minimal manual steps, and the detection time of real-time fluorescent LAMP is brief, with the time from sample addition to result detection being as short as 45 minutes.

2.2 Nucleic acid extraction and primer design

Nucleic acid extraction was performed using a commercial magnetic bead method kit (Lemniscare Medical, Shenzhen, China). The latest monkeypox genome sequences from 2001 (MN702453) and 2022 (ON563414) in the NCBI database were compared using LAMP and QPCR assays to identify conserved sequences for detection. Plasmid fragments with a length of 3487 bp were synthesized, along with vaccinia virus plasmids, variola virus plasmids, and cowpox virus plasmids (Langjing Biotech, Shanghai, China) for primer specificity verification. The copy number of the synthesized plasmid for subsequent LAMP and PCR experiments was calculated using the formula ((6.02 × 10²³)/(X Dalton of the plasmid containing the fragment) × (X ng μL⁻¹ ×10⁻⁹)), resulting in a fragment concentration of 1.3 × 10¹⁰ copies per μL. We diluted this concentration 130 times to obtain a plasmid concentration of 1 × 10⁸ copies per μL.

Real-time fluorescent LAMP primers and qPCR primer probes were designed based on the target sequence to be detected, following the details provided in Table 1. The qPCR reaction system was set up according to the system of a commercially purchased kit from Yeasen Biotechnology (Shanghai) Co., Ltd, China. For the LAMP reaction system, the components included 2 μL of Bst DNA polymerase from Meridian Life Science Co., Ltd Beijing, China, 2.5 μL of buffer, 1.5 μL of Mg₂SO₄, 3.5 μL of dNTP, 0.5 μL of Fluorescent dyes from New England Biolabs, USA, 2 μL each of FIP and BIP, 1 μL each of F3 and B3, all made up to 25 μL with sterile water. The entire LAMP process was maintained at 65 °C for 45 minutes, with fluorescence readings taken every minute.

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2.3 Optimization of nucleic acid extraction particle size

The nucleic acid extraction process in the integrated system differs from that in laboratory testing, where a fully automatic nucleic acid extractor is used. The extractor in the laboratory utilizes magnetic beads for extraction, while the integrated system employs pipetting. This difference in methods directly impacts the efficiency of nucleic acid extraction, with the particle size of the magnetic beads being a crucial factor. To optimize this process, we experimented with magnetic beads of three different sizes 200 nm, 500 nm, and 1000 nm. These beads were used in both the integrated system and the commercial automated nucleic acid extraction instrument to extract 10⁵ copies per μL plasmid. Subsequently, the extracted magnetic beads underwent qPCR detection on a real-time fluorescence PCR instrument. By comparing the results, we were able to determine the optimal magnetic bead particle size and approximate nucleic acid extraction recovery rate R of the integrated system. The calculation formula used for this determination is:

In the formula, represents the average value of n measured concentrations (ng μL⁻¹), represents the initial concentration (ng μL⁻¹), and λ represents the total volume after extraction and the body-machine ratio of the standard substance added before extraction.

2.4 Sensitivity test

The monkeypox virus plasmid underwent a 10-fold serial dilution from 10⁶ copies per μL to 10⁻¹ copies per μL. Real-time fluorescent LAMP and qPCR were then used for detection in an integrated system and a real-time fluorescent PCR instrument, respectively, to determine the detection limit and test the sensitivity of the system. The study also compared the detection limits between LAMP and qPCR within the same system, as well as the performance differences in detection methods across different systems.

2.5 Specificity

The basic reaction systems of LAMP and qPCR were set up, including the addition of monkeypox virus plasmid, vaccinia virus plasmid, smallpox virus plasmid, cowpox virus plasmid, and sterile water as a negative control. Subsequently, LAMP and qPCR were carried out using a commercial real-time fluorescence PCR instrument. The specificity of the primers against monkeypox virus was confirmed through the qPCR test.

2.6 Stability testing

Due to the high amplification efficiency and strong specificity of LAMP technology, sample concentration that is either too high or too low can impact the amplification efficiency. To assess the stability of the experimental system in the integrated detection system, we conducted five tests using samples with varying concentrations – high, medium, and low. Statistical analysis was then performed on the results of these five tests to evaluate the overall system performance.

2.7 Linearity range and linearity testing

To test the linear range of LAMP detection, we conducted detections at high concentrations (10⁸ to 10⁴ copies per μL) and low concentrations (10³ to 10⁻¹ copies per μL). Following the completion of detection, the R² value was determined by plotting a standard curve to analyze linearity within the detection limit range of 10⁸ to 10⁻¹ copies per μL.

2.8 Simulated sample testing

To evaluate the clinical application of the integrated system, we randomly mixed monkeypox virus plasmids at a concentration ranging from 10⁶ to 10⁰ copies per μL and subsequently combined them with human sputum in a 1:1 volume ratio to create simulated samples. A blind test was then conducted using the integrated system for nucleic acid extraction, qPCR, and LAMP detection. The results were compared with those obtained using a fully automatic nucleic acid extractor and a real-time fluorescence PCR instrument.

3. Results

3.1 Analysis of the optimization results of nucleic acid extraction particle size

Magnetic beads of various particle sizes (200 nm, 500 nm, and 1000 nm) were utilized in nucleic acid extraction processes within an integrated system and a fully automatic nucleic acid extractor, respectively. Subsequently, the nucleic acid extraction products underwent detection using a PCR system to compare the outcomes associated with different magnetic bead sizes. The nucleic acid extraction efficiency is detailed in Table 2. Analysis of the data reveals that the integrated system extraction process was unsuccessful when employing 200 nm magnetic beads, as indicated by PCR amplification resulting in no cycle threshold (C_t) value. In contrast, successful extraction was achieved using magnetic beads sized at 500 nm and 1000 nm. Notably, the nucleic acid extraction efficiency of the fully automatic nucleic acid extractor surpassed that of the integrated system. This discrepancy can be attributed to the distinct extraction principles underlying each method, with the integrated system relying on fixed magnetic beads to facilitate the transfer of various extraction reagents, while the fully automatic nucleic acid extractor operates by transferring magnetic beads to different extraction reagents through magnetic adsorption. Consequently, the extraction efficiency of the integrated system remains within a manageable range. Furthermore, the extraction efficiency associated with 500 nm magnetic beads within the integrated system exceeded that of the 1000 nm beads, highlighting the optimal magnetic bead size for nucleic acid extraction in the integrated system as 500 nm.

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3.2 Analysis of sensitivity test results

Using 8 concentration gradient monkeypox virus plasmids as templates, PCR detection was conducted on the commercial qPCR instrument Gentier mini and the integrated system. The results, depicted in Fig. 2A and C, indicate that both systems exhibit stable amplification with high efficiency. The sensitivity was found to be 10² copies per μL, with a PCR time of 90 minutes. However, the R² value for the detection line of the commercial qPCR instrument was 0.996, while the integrated system PCR detection line had an R² of 0.985. In terms of linearity, the commercial qPCR instruments showed slightly better results. Similarly, utilizing the same 8 concentration gradient monkeypox virus plasmids, LAMP detection was carried out on the commercial qPCR instrument Gentier mini and integrated system, as illustrated in Fig. 2B and D. Both systems demonstrated a sensitivity of 10⁰ copies per μL; the R² value for the detection line of the commercial qPCR instrument was 0.937, whereas the integrated system PCR detection line had an R² of 0.962. Comparing the linearity of the two systems, the integrated system performed better, suggesting potential quantitative capabilities of the LAMP system. In terms of the standard curve's linearity, LAMP exhibited lower performance compared to qPCR, particularly in low concentration detection.

3.3 Specificity test analysis

When utilizing the monkeypox virus PCR and LAMP systems for detecting monkeypox virus, cowpox virus, smallpox virus, and vaccinia virus, the results show amplification curves specific to the monkeypox virus template only (see Fig. 3A and C) along with corresponding amplification products (refer to Fig. 3B and D). The agarose gel electrophoresis outcomes of PCR and LAMP amplification products reveal the presence of the target gene band solely when the monkeypox virus template is used, with the band size aligning with the target gene fragment length. Notably, no bands are evident for other viruses, signifying absence of non-specific amplification in the monkeypox virus PCR and LAMP systems, thus underscoring the high specificity of the primers employed.

3.4 Analysis of stability test results

High, medium, and low concentrations of the five experiments all showed normal amplification in Table 3. The average time to threshold (T_t) value and CV value of the five experiments at the three concentrations were calculated. The CV values for high, medium, and low concentrations were 1.55%, 0.92%, and 4.58% respectively. The experiment was repeated five times, demonstrating stable amplification at all concentrations. This suggests that the monkeypox virus LAMP detection reagent, combined with the magnetic bead nucleic acid extraction kit, can consistently extract and detect the monkeypox virus plasmid within an integrated system. The integrated system, extraction reagents, and monkeypox virus LAMP detection reagents all exhibit good stability.

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3.5 Analysis of linearity range and linearity test results

Fig. 4A–C displays amplification curves at high concentrations (10⁸ to 10⁴ copies per μL), low concentrations (10³ to 10⁻¹ copies per μL), and within the detection limit (10⁸ to 10⁻¹ copies per μL). It can be inferred that the detection limit is 10⁰ copies per μL, aligning with the sensitivity test results. Standard curves were derived from the amplification curve, as depicted in Fig. 4D–F. The R² value of the high concentration range (10⁸ to 10⁴ copies per μL) was 0.999, indicating excellent linearity. Conversely, the linearity of the standard curve from the low concentration range (10³ to 10⁻¹ copies per μL) was slightly lower with an R² value of 0.9265. The standard curve within the detection limit (10⁸ to 10⁻¹ copies per μL) exhibited good linearity with an R² value of 0.9658. These experimental findings demonstrate that both the integrated system and the monkeypox LAMP detection system exhibit strong adaptability and sensitivity.

3.6 Analysis of test results from simulated samples

The integrated system was utilized to assess 28 simulated samples and compared with the conventional laboratory testing method involving qPCR and LAMP detection post-extraction using a fully automated nucleic acid extraction instrument. The results are detailed in Table 4. Upon comparing the two methods, the experimental outcomes align consistently, whether utilizing PCR or LAMP detection. Notably, LAMP detection exhibits significantly shorter detection times compared to PCR, thereby reducing the time needed for clinical diagnosis and enhancing pathogen detection efficiency. The experiment is user-friendly, and the closed cartridge design helps prevent experimental issues and environmental contamination.

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4. Discussion

This study has demonstrated that the monkeypox virus LAMP detection reagent, when combined with the magnetic bead nucleic acid extraction kit, can effectively extract the monkeypox virus plasmid within an integrated system, enabling easy detection of the virus in approximately 1 hour. Currently, several detection technologies for rat pox are in use, as illustrated in Table 5. For instance, Q. Chen et al.²⁷ demonstrated a portable system based on CRISPR-Cas for the naked-eye detection of the monkey bean virus. This system utilizes the high selectivity of CRISPR-Cas12 combined with the isothermal nucleic acid amplification capabilities of recombinase polymerase amplification, achieving a detection limit of 15 copies per μL in a one-pot system. When compared to quantitative polymerase chain reaction, satisfactory consistency was obtained. Lateral flow analysis (LFA), also known as immunochromatography, is driven by capillary action and facilitates rapid detection using colloidal gold nanoparticles as immunolabels. Ye et al.³¹ developed a colloidal gold immunochromatographic method for the detection of the monkeypox virus, utilizing the A29 17-49 peptide sequence as an immunogen to generate monkeypox-specific monoclonal antibodies. A rapid test strip was created employing a double-antibody sandwich method, which demonstrated high specificity and sensitivity. The optimal sensitivity and detection limit for two specific antibodies, mAb-7C5 and 5D8, targeting the A29 protein was determined to be 50 pg mL⁻¹ (Table 5). Additionally, Yang et al.³⁴ established a lateral flow immunoassay (LFIA) system based on dual-signal nanotags for the rapid and sensitive detection of the A29L protein. By optimizing the signal-to-noise ratio (SNR) of the test line at various time intervals, they found that a reaction time of 15 minutes was adequate for the quantitative detection of MPXV, achieving a sensitivity of 5 ng mL⁻¹. Surface-enhanced Raman spectroscopy (SERS) is frequently employed to detect harmful microorganisms due to its low cost,³⁵ speed, high sensitivity, specificity, and non-invasiveness. However, certain technical challenges must be addressed to facilitate the identification of unlabeled viruses, including difficulties in signal recording and the lack of applicability stemming from size discrepancies between SERS ‘hotspots’ and viruses. To overcome these limitations in unlabeled MPXV detection using SERS, Zhang et al.³² utilized silver nanoparticles incubated with iodide ions and polymerized with calcium ions as substrates. The results indicate that this novel method can detect the MPXV A29L protein at concentrations as low as 5 ng mL⁻¹ within 2 minutes. Electrochemical biosensors represent a promising approach,³⁶ as demonstrated by de Lima et al.,³³ who reported the first electrochemical point-of-care (POC) detection method utilizing paper laser-cut graphene (LSG) nanobiosensors for the detection of MPXV protein. The results indicate that the test requires a minimal sample volume of 2.5 μL, can yield results within 15 minutes, and achieves detection limits (LODs) for A29 protein as low as 3.0 × 10⁻¹⁶ g mL⁻¹. Typically, laboratory testing necessitates the involvement of professional laboratory personnel to conduct experimental procedures, particularly for nucleic acid testing, which must be performed following sample extraction. This process requires various experimental equipment and is both time-consuming and demanding in terms of responsibility. In contrast, the integrated system simplifies this process: once the sample is introduced into the sample hole, it can be processed, yielding results efficiently. This system enables non-professional experimenters to carry out experimental operations, significantly reducing the time required and greatly enhancing the efficiency of pathogen detection, while also maintaining relatively high sensitivity.

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5. Conclusion

Although smallpox no longer occurs naturally, global health authorities remain vigilant for any potential reappearance of the disease, whether through natural means, laboratory accidents, or intentional releases. In order to ensure readiness for the possible return of smallpox, ongoing efforts are being made to develop new vaccines, diagnostics, and antiviral drugs. These advancements could also be beneficial in preventing and managing monkeypox outbreaks. The World Health Organization (WHO) is collaborating with health authorities worldwide to contain the spread of the disease. Guidance materials are being disseminated to assist countries in enhancing surveillance, laboratory procedures, clinical care, infection control, and risk communication, aiming to educate high-risk populations and the general public on monkeypox prevention measures. Furthermore, WHO is actively engaging with African nations, regional organizations, and technical and financial partners to bolster laboratory capabilities, disease monitoring, preparedness, and response activities to mitigate the risk of further infections.

In the future, the system will be evaluated for performance under varying temperatures and humidity levels to optimize its functionality by enhancing reagents and streamlining operating procedures, thereby reducing costs and improving user-friendliness. Additionally, the design of the closed kit will be further refined to ensure greater safety and convenience. Expanding the diversity of sample types, sources, and applicability studies to include other similar viruses will enhance the broad applicability of this method. Strengthening collaboration with public health institutions will facilitate the on-site application and promotion of this technology.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Author contributions

YW: ideas, formulation or evolution of overarching research goals and aims; HC: supervision, oversight and leadership of the planning and execution of research activities, including guidance of the core team; YG: writing original draft, including substantive translation; YD: provide financial support for research projects. SL: investigation conducting a research and investigation process, specifically performing the experiments, or data/evidence collection; XZ: verification, whether as a part of the activity or separate, of the overall replication/reproducibility of results/experiments and other research outputs; YC: development or design of research methods; study model building and data processing.

Conflicts of interest

There are no conflicts to declare.

Acknowledgements

Natural Science Foundation of Hunan Province of China (No. 2022JJ50052), Outstanding Youth Project of Hunan Provincial Department of Education (22B0605).

References

1. A. Ullah, F. A. Shahid, M. Ul Haq, M. T. ul Qamar, M. Irfan, B. Shaker, S. Ahmad, F. Alrumaihi, K. S. Allemailem and A. Almatroudi, J. Biomol. Struct. Dyn., 2023, 41, 7821–7834 CrossRef CAS .
2. N. Luna, A. L. Ramirez, M. Munoz, N. Ballesteros, L. H. Patino, S. A. Castaneda, D. K. Bonilla-Aldana, A. Paniz-Mondolfi and J. D. Ramirez, Travel Med. Infect. Dis., 2022, 49, 102402 CrossRef CAS .
3. M. Chmel, O. Bartos, H. Kabícková, P. Pajer, P. Kubícková, I. Novotná, Z. Bartovská, M. Zláal, A. Burantová, M. Holub, H. Jirincová, A. Nagy, L. Cerníková, H. Záoucká and J. Dresler, Viruses, 2022, 14, 1773 CrossRef PubMed .
4. L. Mao, J. Ying, B. Selekon, E. Gonofio, X. Wang, E. Nakoune, G. Wong and N. Berthet, Viruses, 2022, 14, 2112 CrossRef CAS PubMed .
5. M. H. Temsah, F. Aljamaan, S. Alenezi, K. Alhasan, B. Saddik, A. Al-Barag, A. Alhaboob, N. Bahabri, F. Alshahrani, A. Alrabiaah, A. Alaraj, F. Bahkali, K. Alkriadees, A. Jamal, R. Halwani, F. AlZamil, S. Al-Subaie, M. Barry, Z. A. Memish and J. A. Al-Tawfiq, Travel Med. Infect. Dis., 2022, 49, 102426 CrossRef PubMed .
6. J. Dyall, R. F. Johnson, S. Chefer, C. Leyson, D. Thomasson, J. Seidel, D. R. Ragland, R. Byrum, C. Jett, J. A. Cann, M. St Claire, E. Jagoda, R. C. Reba, D. Hammoud, J. E. Blaney and P. B. Jahrling, J. Virol., 2017, 91, e00897–e00917 CrossRef CAS .
7. A. A. Jairoun, S. S. Al-Hemyari, N. M. Abdulla, F. El-Dahiyat, M. Shahwan, N. Hassan, O. J. Dr, N. G. Alyousef, S. Sharif and A. A. S. Jaber, J. Infect. Public Heal., 2022, 15, 1065–1071 CrossRef PubMed .
8. A. El-Mesady, A. Elsonbaty and W. Adel, Chaos Solition. Fract., 2022, 164, 112716 CrossRef CAS .
9. N. Erez, H. Achdout, E. Milrot, Y. Schwartz, Y. Wiener-Well, N. Paran, B. Politi, H. Tamir, T. Israely, S. Weiss, A. Beth-Din, O. Shifman, O. Israeli, S. Yitzhaki, S. C. Shapira, S. Melamed and E. Schwartz, Emerging Infect. Dis., 2019, 25, 980–983 CrossRef .
10. J. Y. Lin, G. Y. Li, P. L. Zhong, Q. Zeng, L. Liu and L. Chen, Front. Public Health, 2022, 10, 995965 CrossRef PubMed .
11. D. M. Meaney-Delman, R. R. Galang, B. W. Petersen and D. J. Jamieson, Obstet. Gynecol., 2022, 140, 391–397 CrossRef CAS PubMed .
12. O. A. Adegboye, M. Eugenia Castellanos, F. O. Alele, A. Pak, H. C. Ezechukwu, K. Hou and T. I. Emeto, Viruses, 2022, 14, 1283 CrossRef CAS PubMed .
13. S. E. F. Yong, O. T. Ng, Z. J. M. Ho, T. M. Mak, K. Marimuthu, S. Vasoo, T. W. Yeo, Y. K. Ng, L. Cui, Z. Ferdous, P. Y. Chia, B. J. W. Aw, C. M. Manauis, C. K. K. Low, G. H. Chan, X. Y. Peh, P. L. Lim, L. P. A. Chow, M. Chan, V. J. M. Lee, R. T. P. Lin, M. K. D. Heng and Y. S. Leo, Emerging Infect. Dis., 2020, 26, 1826–1830 CrossRef .
14. A. Antinori, V. Mazzotta, S. Vita, F. Carletti, D. Tacconi, L. E. Lapini, A. D'Abramo, S. Cicalini, D. Lapa, S. Pittalis, V. Puro, M. R. Capparuccia, E. Giombini, C. E. M. Gruber, A. R. Garbuglia, A. Marani, F. Vairo, E. Girardi, F. Vaia, E. Nicastri and I. M. Grp, Eurosurveillance, 2022, 27, 2200421 CrossRef CAS PubMed .
15. D. Gribanyov, G. Zhdanov, A. Olenin, G. Lisichkin, A. Gambaryan, V. Kukushkin and E. Zavyalova, Int. J. Mol. Sci., 2021, 22, 1842 CrossRef CAS .
16. S. Liu, X. L. He, T. Zhang, K. X. Zhao, C. H. Xiao, Z. R. Tong, L. Jin, N. Y. He, Y. Deng, S. Li, Y. Guo and Z. Chen, Chin. Chem. Lett., 2022, 33, 1933–1935 CrossRef CAS .
17. S. E. Turbett, M. N. Anahtar, V. Pattanayak, M. M. Azar, K. C. Coffey, G. Eng, J. W. Rudolf, K. B. Lewandrowski, J. Baron, E. S. Rosenberg and J. A. Branda, Clin. Infect. Dis., 2020, 70, 1215–1221 CrossRef .
18. H. Chen, X. Y. Ma, X. Y. Zhang, G. Hu, Y. Deng, S. Li, Z. Chen, N. Y. He, Y. Q. Wu and Z. H. Jiang, Chin. Chem. Lett., 2023, 34, 107701 CrossRef CAS .
19. C. B. Engstrom, K. M. Yakimovich and L. M. Quarmby, Front. Microbiol., 2020, 11, 569 CrossRef PubMed .
20. J. Y. Liu, L. M. Zhang, W. T. Zeng, L. H. Zhang, N. Y. He and Z. X. Lu, Chin. Chem. Lett., 2023, 34, 108141 CrossRef CAS .
21. R. H. Doshi, S. A. J. Guagliardo, J. B. Doty, A. D. Babeaux, A. Matheny, J. Burgado, M. B. Townsend, C. N. Morgan, P. S. Satheshkumar, N. Ndakala, T. Kanjingankolo, L. Kitembo, J. Malekani, L. Kalemba, E. Pukuta, T. N'Kaya, F. Kangoula, C. Moses, A. M. McCollum, M. G. Reynolds, J. V. Mombouli, Y. Nakazawa and B. W. Petersen, Emerging Infect. Dis., 2019, 25, 281–289 CrossRef PubMed .
22. H. H. Rao, H. X. Liu, M. Y. Luo, X. Xue, M. M. Wei and Z. H. Xue, Chin. J. Anal. Chem., 2021, 49, 1–13 CAS .
23. Y. Wei, X. T. Zhang, X. Chen, H. B. Pan, Z. L. Vasic, M. Cifrek and Y. M. Gao, IEEE Sens. J., 2023, 23, 3699–3709 CAS .
24. Y. T. Zhang and N. D. Zhou, Electroanalysis, 2022, 34, 168–183 CrossRef CAS .
25. R. R. Huang, L. He, L. Jin, Z. Y. Li, N. Y. He and W. J. Miao, Chin. Chem. Lett., 2023, 34, 101–110 Search PubMed .
26. M. Nakhaie, N. Arefinia, J. Charostad, D. Bashash, M. H. Abdolvahab and M. Zarei, Rev. Med. Virol., 2023, 33, e2404 CrossRef PubMed .
27. Q. Chen, I. Gul, C. Y. Liu, Z. Y. Lei, X. Y. Li, M. A. Raheem, Q. He, H. H. Zhang, E. Leeansyah, C. Y. Zhang, V. Pandey, K. Du and P. W. Qin, J. Med. Virol., 2023, 95, e28385 CrossRef CAS PubMed .
28. Y. D. Peng, R. L. Hu, S. Xue, Y. G. He, L. L. Tian, Z. H. Pang, Y. L. He, Y. Q. Dong, Y. H. Shi, S. Q. Wang, B. X. Hong, K. Liu, R. X. Wang, L. H. Song, H. H. Fan, M. Z. Li and Y. G. Tong, Anal. Chim. Acta, 2024, 1311, 342720 CrossRef CAS PubMed .
29. X. Chen, W. Yuan, X. Yang, Y. Shi, X. Zeng, J. Huang, Y. Wang and S. Li, Microbiol. Spectrum, 2023, 11, e0403522 CrossRef PubMed .
30. S. D. Davi, J. Kissenkötter, M. Faye, S. Böhlken-Fascher, C. Stahl-Hennig, O. Faye, O. Faye, A. A. Sall, M. Weidmann, O. G. Ademowo, F. T. Hufert, C. P. Czerny and A. Abd El Wahed, Diagn. Microbiol. Infect. Dis., 2019, 95, 41–45 CrossRef CAS PubMed .
31. L. Y. Ye, X. L. Lei, X. X. Xu, L. G. Xu, H. Kuang and C. L. Xu, Analyst, 2023, 148, 985–994 RSC .
32. Z. Zhang, H. Jiang, S. Jiang, T. Dong, X. T. Wang, Y. P. Wang and Y. Li, ACS Appl. Mater. Interfaces, 2023, 15, 34419–34426 CrossRef CAS PubMed .
33. L. F. de Lima, P. P. Barbosa, C. L. Simeoni, R. F. de Paula, J. L. Proenca-Modena and W. R. de Araujo, ACS Appl. Mater. Interfaces, 2023, 15, 58079–58091 CrossRef CAS PubMed .
34. X. S. Yang, X. D. Cheng, H. J. Wei, Z. J. Tu, Z. Rong, C. W. Wang and S. Q. Wang, J. Nanobiotechnol., 2023, 21, 450 CrossRef CAS PubMed .
35. M. Hussain, X. L. Liu, J. Zou, J. Yang, Z. Ali, H. U. Rehman, N. Y. He, J. G. Dai and Y. J. Tang, Chin. Chem. Lett., 2022, 33, 1885–1888 CrossRef CAS .
36. N. Shi, H. N. Jia, J. X. Zhang, P. Y. Lu, C. L. Cai, Y. X. Zhang, L. Q. Zhang, N. Y. He, W. R. Zhu, Y. Cai, Z. Q. Feng and T. Wang, Chin. Chem. Lett., 2024, 35, 109302 CrossRef CAS .

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