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μCaler Respiratory Pathogen Solution

Background

According to the World Health Organization (WHO), respiratory infections result in millions of deaths annually, particularly from diseases such as influenza, pneumonia, bronchitis, and COVID-19. In recent years, the speed of transmission and the complexity of respiratory infections have been exacerbated by environmental changes, viral mutations, and increasing antibiotic resistance. Respiratory infections involve various pathogens, including viruses, bacteria, fungi, mycoplasma, and chlamydia. As the symptoms caused by different pathogens are similar and may interact with each other, single-pathogen detection often fails to accurately diagnose "mixed infections," which in turn impacts clinical treatment outcomes.

Traditional respiratory pathogen detection methods, such as enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR), typically detect only specific pathogens and are limited in addressing the dynamic spectrum of pathogens. Multiplex detection methods based on targeted sequencing can quickly and accurately identify the source of infection, providing comprehensive pathogen information for epidemiological surveillance and assisting clinicians in making precise treatment decisions. This is especially beneficial for mixed infections, as it enables efficient differentiation of various pathogens, improving diagnostic accuracy. Therefore, Nanodigmbio has launched the μCaler Respiratory Pathogen Solution, designed for the precise identification, typing, and mutation tracking of respiratory infection-related pathogens, including influenza viruses.


Solution

μCaler Respiratory Pathogen Solution (referred to as μCaler RP Solution) integrates the RNA & DNA Library Co-Preparation Kit, the exclusive patented μCaler Hybrid System, and the XCapViz Bioinformatics Analysis Visual System. It enables a seamless "sample in, result out" workflow within a single day. This solution is designed to cover over 99% of common respiratory pathogens, including viruses, bacteria, fungi, mycoplasma, and chlamydia. It provides comprehensive support for multiplex respiratory pathogen co-detection, precise identification and typing, as well as variants tracking of influenza A virus, facilitating the rapid and accurate diagnosis of complex respiratory infections and the surveillance and management of epidemiology.

Figure 1


Pre-library Preparation Blocker μCaler Hybrid System Bioinformatics Analysis Automated Workstation
NadPrep RNA & DNA Library Co-Preparation Module coupled with NadPrep Universal Stubby Adapter (UDI) Module μCaler NanoBlockers (for Illumina®) μCaler Hybrid Capture Reagents v2 Coupled with μCaler RP Panel v1.0 • XCapViz Bioinformation Analysis Visual System
• Prebuilt Pipelines (NEX-tRP)

• NadAuto-16R Fully-automated NGS Workstation

For research use only. Not for use in diagnostic procedures.

Accurate Detection of Pathogens in Clinical Samples
To validate the accuracy of the μCaler RP Solution, we tested 28 clinical samples with known pathogen infections. For the 32 reference pathogens identified by qPCR, the μCaler RP Solution successfully detected all of them. Additionally, in the testing of 28 clinical samples, the μCaler RP Solution showed significant advantages in virus typing and identification. Beyond the results provided by qPCR, the μCaler RP Solution provided additional identification or subtype information for 10 samples (Throat Swab: TS-7; Sputum: S-1, S-3, S-6, S-8, S-9, S-12, S-14, S-15, S-17) (Table 1.).

Table 1. Summary of consistency in pathogen detection across different technical approaches for 28 clinical samples.


Table 1
Sensitive Detection of Trace Pathogens in Clinical Samples
To further assess the solution's detection performance, we tested clinical samples with varying pathogen loads. The test results show that the μCaler RP Solution can detect Human Parainfluenza Virus 2 with a maximum Ct value of 35. The average detection limit for Ct values exceeds 28, demonstrating exceptional sensitivity for low-copy pathogens. This indicates its high sensitivity in detecting low-copy pathogens (Table 2.).

Table 2. Sensitivity of the μCaler RP Solution for single and multiplex pathogen detection.


Table 2
Accurate Virus Typing and Identification
Pathogen typing is crucial in epidemiological investigations as it provides a foundation for analyzing viral mutation patterns and is key to developing vaccines targeting specific viral subtypes. Testing confirmed that the μCaler RP Solution demonstrates exceptional typing and identification capabilities, accurately distinguishing and identifying various common respiratory pathogens such as respiratory syncytial virus and parainfluenza virus. This provides robust technical support for preventive measures and vaccine development.

Table 3. Virus Typing and Identification of μCaler RP Solution.


Table 3
Coverage of Influenza A Virus Coding Genes

Globally, approximately 10% of the population is infected with influenza A virus annually, resulting in 290,000 to 650,000 deaths. Influenza A virus has a complex structure comprising eight negative-strand RNA segments, with hemagglutinin (HA) and neuraminidase (NA) being the critical surface antigens essential for viral entry and release. The virus is classified based on the serotypes of HA (1-16 subtypes) and NA (1-9 subtypes), offering a scientific basis for precise viral identification.

To enable accurate tracking of influenza A virus mutations, the μCaler RP Solution includes full-length probes targeting all 16 HA and 9 NA subtypes. Testing demonstrated that when the Ct value of H1 is 32 or 34, the μCaler RP Solution efficiently and comprehensively covered the full-length sequences of HA and NA coding genes, showcasing exceptional detection performance.

Figure 2

Figure 2. μCaler RP Solution exhibits comprehensive coverage of influenza A virus coding genes. Coverage for coding genes of A & C. HA_NA and B & D. NA_N1 in influenza A virus.

Note: A & B: Ct = 32; C & D: Ct = 34.

In summary, the μCaler RP Solution demonstrates outstanding performance in clinical respiratory pathogen detection. It offers comprehensive pathogen coverage, efficient identification capabilities, and precise typing. Particularly in tracking influenza A virus variants, it provides robust technical support for epidemiological research and vaccine development.

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