Introduction

Respiratory tract infection (RTI) is one of the most important causes for extensive morbidity and mortality among patients worldwide [1]. Different pathogens could induce similar symptoms and signs of RTI, which is mainly characterized by upper respiratory infections such as rhinitis, pharyngitis, laryngitis, tonsillitis, etc. [2]. And some patients with RTI show severe symptoms of lower respiratory infections including tracheitis, bronchitis and pneumonia [3]. It has been demonstrated that most acute respiratory tract infections are induced by viruses including respiratory syncytial virus, adenovirus, influenza A and B viruses, parainfluenza virus, and so on [4]. Respiratory virus infection is one of the most common diseases for people in all age groups [5]. Notably, treatment method, curative effect and disease course vary between patients with RTI induced by different pathogens [6]. Therefore, accurate and timely etiological analysis is not only essential for diagnosis of RTI, but also the basis for reasonable selection of appropriate therapeutic regimen [7, 8]. And it is also urgent to develop new methods of rapid detection of respiratory viruses.

Single-tube multiplex fluorescent probe melting curve (FPMC) technology (four channel detection: Fam, Vic, Rox, Cy5) and fusion curve analysis employed in the new detection method is evaluated in this study. Detection using this new method covers a wide range of 12 kinds of pathogen nucleic acids, including chlamydia pneumoniae, mycoplasma pneumoniae, adenovirus, influenza A virus, influenza B virus, parainfluenza virus (types 1, 2, 3 and 4), rhinovirus, respiratory syncytial virus, Boca virus, metapneumovirus, coronavirus (229E, hku1, nl63 and OC43), or novel coronavirus. Specifically, three channels (Fam, Vic and Rox) were employed to detect the target pathogen, and pathogens in a sample are identified according to the cycle threshold (CT) values in each channel during the process of PCR amplification and the corresponding change rate of peak height within a range of the melting temperatures of the targeted pathogens. Additionally, Cy5 channel was used for detecting the endogenous internal standard in order to monitor the quality of samples and the accuracy of experimental processes.

To have insight into the novel diagnostic assay for clinical application, we here provide important evidence comparing the diagnostic accuracy of the FPMC analysis method and Sanger sequencing method for the detection of RTI.

Methods

Study population

This study included 635 patients of all ages and both genders showing with signs and/or symptoms of respiratory tract infection such as cough, nasal congestion, runny nose, sore throat, loss of smell or taste, dyspnea, lung related diseases, etc. These patients were all from the second affiliated hospital of ** of multiple pathogens with strong sensitivity and high specificity by using the technology of hybridization or polymerase chain reaction. Moreover, on the basis of ensuring the sensitivity and specificity of analysis, it could perform detection by micro-sample handling and make operation procedures more easily.

Our results demonstrate that the overall performance of the FPMC analysis method has an overall percent agreement (true-positive and true-negative results) of > 99% for all available targets tested compared with the sequencing method. Discrepancy between the FPMC analysis method and the sequencing method may be due to three main factors. Firstly, the sensitivity of the sequencing method may be low, which will lead to the negative results for those weakly positive samples with CT value being near the cut off of the FPMC analysis method. Secondly, primers of the sequencing method may not be able to cover all sub-types of organisms, and thus some organisms in a sample could not be detected using the sequencing method. Finally, FPMC analysis method is a new assay based on PCR reaction. So there are occasionally false-positive results due to the PCR contamination during the process of experiments. In this study, the performance characteristics of the new FPMC analysis method were evaluated by assessing agreement with the results of the sequencing method, a generally accepted standard method.

However, there are still some limitations in our study. Firstly, this study is lack of another molecular-based method for discordant sample adjudications. Comparisons of this FPMC analysis method with another multiplex panel would provide useful information about discordant results with the sequencing method. But this is beyond the designs of our current study. Secondly, the pathogen spectrum of the FPMC analysis method does not include all pathogens. Therefore, combination of the FPMC analysis method and other molecular methods detecting bacteria could help to improve ability in diagnostic testing of respiratory pathogens. Finally, the lack of detection of influenza A virus and Covid-2019 in this study limits the data on the performance for these targets. In our subsequent research, relevant samples will be collected to elucidate the diagnostic efficacy of the new assay kit for influenza A virus and Covid-19. Overall, the FPMC analysis method is a rapid, accurate, and easy-to-use assay for detection of organisms in clinical specimens from the respiratory tract in clinical laboratories.