Applying improved ddPCR to reliable quantification of MPXV in clinical settings

Abstract

Monkeypox virus (MPXV) poses a global health threat. Droplet digital PCR (ddPCR) holds potential as an accurate diagnostic tool for clinical microbiology. However, there is limited literature on the applicability of ddPCR in clinical settings. In this study, the clinical features of patients with MPXV during the initial outbreak in China in June 2023 were reviewed, and an optimized ddPCR method with dilution and/or inhibitor removal was developed to enhance MPXV detection efficiency. Eighty-two MPXV samples were tested from nine different clinical specimen types, including feces, urine, pharyngeal swabs, anal swabs, saliva, herpes fluid, crust, and semen, and the viral load of each specimen was quantified. A comparative analysis was performed with qPCR to assess sensitivity and specificity and to investigate the characteristics of MPXV infection by analyzing viral loads in different clinical specimens. Consequently, common pharyngeal and gastrointestinal symptoms were observed in patients with MPXV. The optimized ddPCR method demonstrated relatively high sensitivity for MPXV quantification in the clinical materials, with a limit of detection of 0.1 copies/μL. This was particularly evident in low-concentration samples like whole blood, semen, and urine. The optimized ddPCR demonstrated greater detection accuracy compared with normal ddPCR and qPCR, with an area under the curve (AUC) of 0.939. Except for crust samples, viral loads in the specimens gradually decreased as the disease progressed. Virus levels in feces and anal swabs kept a high detection rate at each stage of post-symptom onset, and feces and anal swabs samples may be suitable for clinical diagnosis and continuous monitoring of MPXV.

Importance: The ddPCR technique proved to be a sensitive and valuable tool for accurately quantifying MPXV viral loads in various clinical specimen types. The findings provided valuable insights into the necessary pre-treatment protocols for MPXV diagnosis in ddPCR detection and the potentially suitable sample types for collection. Therefore, such results can aid in comprehending the potential characteristics of MPXV infection and the usage of ddPCR in clinical settings.

Keywords: Mpox; ddPCR; monkeypox virus; quantification; viral loads.

Fig 1

Flowchart of MPXV detection clinically using the optimized ddPCR method. Clinical specimens should be collected based on the patient’s stage of onset. Each sample should be pre-treated accordingly, including dilution and/or inhibitor removal. Once optimized, perform the ddPCR assay to quantify MPXV.

Fig 2

Establishment of the ddPCR method for MPXV targeting F3L. (A) The optimal annealing temperature for ddPCR using a positive standard of F3L DNA fragmentation. (B) The detectable range of ddPCR using a positive standard of F3L DNA fragmentation at a 10-fold dilution. Panels C07–E07 were duplicated samples. (C) The copy numbers of MPXV in each clinical sample were calculated using the optimized ddPCR assay. Each dot represents one sample, and the data are shown with the mean.

Fig 3

Effectiveness of the ddPCR assay for MPXV after optimization. (A–D) The viral copy numbers in feces, anal swabs, semen, and whole blood samples. ED, exceed detection limit; ND, not detected; D, dilution; IR, inhibitors removal. (E) The receiver operating characteristic (ROC) curve comparing ddPCR and optimized ddPCR. The value of AUC is shown in the figure.

Fig 4

Comparative analysis between optimized ddPCR and qPCR for MPXV and collection strategies of clinical specimen types for ddPCR detection clinically. (A) Correlation between optimized ddPCR and qPCR assays. The Cq values measured by qPCR in each clinical sample with the same pre-treatment are represented on x-axis, whereas their corresponding copy numbers evaluated by ddPCR are represented on the y-axis. (B) Bland-Altman plots for quantifying MPXV clinical samples using optimized ddPCR and qPCR methods. The red line represents the average of measures, whereas the black line represents the 95% limits of agreement. (C) The receiver operating characteristic (ROC) curve comparing ddPCR and qPCR in clinical settings. The value of AUC area is shown in the figure. (D) Appropriate pre-treatment strategies employed for various clinical specimen types when using ddPCR for detection.

Fig 5

Viral loads of MPXV in various clinical specimens at different onset times and collection strategies of clinical specimen types for ddPCR detection. (A) The changes in viral loads of MPXV in various clinical sample types as the onset progressed. The copy numbers were measured by the optimized ddPCR assay. Each dot represented one sample, and the text indicated the copy numbers of samples in non-logarithmic value. The black text represented the mean copy number, whereas the blue text represented the median. (B) Flowchart for obtaining appropriate clinical sample types from individuals suspected of MPXV infection at various stages of onset. When selecting sample types for detection, consider both the detectability and convenience of samples, taking into account the patient’s onset.