Fever, Cough, Runny Nose … How Can Respiratory Syndrome Be Diagnosed Rapidly and Precisely?

01 From “Empirical Therapy” to “Precision Diagnosis”: The Practical Dilemma in Respiratory Infection Management

Respiratory tract infections remain one of the leading causes of morbidity and mortality among adults and children worldwide. Pathogen infections can not only cause acute respiratory diseases but may also have long-term health impacts in certain populations. Both upper and lower respiratory tract infections can be caused by a wide range of microorganisms, including viruses, bacteria, fungi, and atypical pathogens, characterized by pathogen diversity, frequent variation, and a high incidence of co-infections. These conditions are particularly severe in children, the elderly, and immunocompromised individuals, where disease progression is often rapid outcomes more critical, posing a significant public health burden.  

Clinically, respiratory tract infections often present with highly similar symptoms and signs; however, the underlying etiological agents may differ substantially, leading to markedly different treatment strategies. In the absence of definitive pathogen identification, empirical antimicrobial therapy is commonly adopted, which may result in the overuse or misuse of antimicrobial agents, thereby accelerating the emergence and spread of antimicrobial-resistant strains. With the continuous rise of antimicrobial resistance (AMR), the therapeutic window for empirical treatment is increasingly constrained. Treatment strategies are shifting from oral to intravenous administration and relying more heavily on second-line and even “last-resort” antibiotics. This not only increases the healthcare burden, but also raises higher demands for standardized and precise clinical management.  

Against this backdrop, the clinical objective of respiratory infection management has evolved from a simple determination of “whether infection exists” to a more refined and comprehensive assessment—namely, “identifying the causative pathogen(s),” “determining the presence of co-infections,” “characterizing potential antimicrobial resistance,” and “enabling rapid therapeutic decision-making.” Therefore, early and accurate identification of the causative pathogen is a critical foundation for the prevention, control, diagnosis, and management, guiding rational antimicrobial use, optimizing treatment strategies, and supporting epidemiological surveillance and public health decision-making. However, achieving comprehensive, rapid, and precise pathogen identification in real-world clinical practice remains highly challenging.

02 The Real Challenge Is Not Just “Detection”, but Being “Comprehensive, Rapid, and Interpretable”

Traditional methods such as culture-based isolation, antigen/antibody assays, PCR/qPCR remain essential tools in the respiratory infection diagnostics and play an indispensable role in detecting common pathogens. However, in complex clinical scenarios, these methods often exhibit limitations, including stringent culture conditions, prolonged turnaround time, low positive detection rates, and insufficient sensitivity. These limitations are particularly evident for fastidious microorganisms, viruses, atypical pathogens, and low-abundance pathogens. With the continuous technological advancements, pathogen detection has evolved from single-target assays toward multi-pathogen and high-throughput approaches. From conventional PCR and multiplex PCR to metagenomic next-generation sequencing (mNGS) and targeted NGS (tNGS), these innovations have significantly expanded detection breadth and depth, improving our understanding of complex infection profiles and epidemiological patterns, and accelerating the development of clinical-grade diagnostic solutions. Nevertheless, in real-world clinical applications, improvements in detection capability have not fully translated into simplified clinical decision-making. Accurate pathogen identification and result interpretation still face multiple challenges：

Given the complexity and diversity of respiratory pathogens, there is a pressing need for an integrated solution that enables multiplex pathogen detection, antimicrobial resistance profiling and intelligent result interpretation, thereby achieving effective translation from “data generation” to “clinical decision-making.” 。Driven by clinical needs and technology trends, Nanodigmbio has launched the μCaler Respiratory Pathogen Identification and AMR Solution (hereafter referred to as the μCaler RIA Solution). Addressing key pain points in precision respiratory infection management, it enables rapid, comprehensive, and accurate identification of causative pathogens in a single test, while simultaneously performing AMR gene detection and source-organism attribution. This provides reliable decision support for rational antimicrobial therapy, precision intervention, and AMR stewardship, helping improve diagnostic efficiency and overall clinical management of respiratory infections.

03 From “Seeing" to“Understanding”：μCaler RIA Solution Empowers Clinical Decision-Making?

μCaler RIA Solution is built on EZ RNA & DNA Library Co-Preparation kit, combined with the μCaler Hybrid System, μCaler RIA Panel v1.0, and the XCapViz Bioinformatics Analysis Visual System. Together, they deliver an integrated workflow spanning sample processing, library preparation, hybrid capture, bioinformatics analysis, and report interpretation, enabling a streamlined “sample-in, result-out” process with a turnaround time (TAT) as little as 12 hr. In addition, the flexible NadAuto-series Fully Automated NGS Workstations can further reduce hands-on labor and increase throughput and efficiency for clinical respiratory pathogen testing.

Figure 1. Integrated workflow and duration of the μCaler RIA Solution.

3.1 Scope

3.2 Application

●  Upper respiratory tract infections (URTIs): common cold, influenza, rhinitis, pharyngitis, tonsillitis, laryngitis, etc.

●  Lower respiratory tract infections (LRTIs): tracheitis, bronchitis, bronchiectasis, bronchiolitis, pneumonia, lung abscess, etc.

●  Mycobacterial infections: pulmonary tuberculosis and nontuberculous mycobacteria (NTM)l lung disease, etc.

●  Chronic respiratory infections: chronic obstructive pulmonary disease (COPD), asthma, etc.

3.3 Highlight

3.3.1 Broad Coverage of Respiratory Pathogens to Improve Diagnostic & Treatment Efficiency

μCaler RIA Panel v1.0 is designed to target specific genomic regions from hundreds of respiratory pathogens—including RNA viruses, DNA viruses, bacteria, fungi, Mycoplasma, and Chlamydia—as well as ~200 AMR markers associated with commonly used antimicrobials. It provides targeted coverage for > 99% of common clinically relevant respiratory pathogens, enabling comprehensive support for multiplex respiratory pathogen testing, precise identification, AMR gene-based resistance prediction, and variant tracking of specific viruses. This helps clinicians rapidly differentiate complex respiratory infections, achieve accurate diagnosis, enable precision antimicrobial therapy, and strengthen surveillance and management.

3.3.2 Streamlined Workflow for Accelerated Processing

The integrated solution covers the entire process from library preparation to hybrid capture, enabling the simultaneous analysis of DNA and RNA in a single process. The overall design adopts a premixed reagent system, substantially reducing the number of reagents required and minimizing reagent preparation and pipetting steps, thereby effectively lowering operational complexity and the risk of error. In addition, several key optimizations are incorporated into the workflow design, such as eliminating the second-strand cDNA synthesis and post-ligation cleanup steps commonly used in standard library co-preparation workflows, as well as the beads washing procedures in conventional hybrid capture workflows. While maintaining stable and reliable detection performance and data quality, this solution significantly shortens TAT and improves overall throughput and laboratory operating efficiency.

3.3.3 End-to-End Quality Control (QC) to Reduce False Positives

A systematic QC assessment framework is implemented, including positive controls (PCs), spike-in internal controls (Spike ICs), and contamination identifiers (Tags), to strengthen contamination monitoring at the source. By integrating multi-dimensional QC with stringent calling rules and dynamically updated local databases, suspected pathogens are subjected to systematic screening and graded management, effectively reducing false positives and providing trustworthy evidence for clinical interpretation.

Figure 2. Principles for clinical management of pathogens by risk group in the μCaler RIA Solution.

3.3.4 Evidence-based Reporting of Reliable Results

Based on a pathogenicity grading framework and a multidimensional interpretation strategy, detected pathogens are stratified for evaluation and result presentation. For pathogens classified as risk group 1/2, background contamination and suspected pathogens are distinguished by incorporating results from negative control results. For pathogens classified as risk group 3, interpretation is performed based on their presence in negative controls, combined with predefined thresholds or the ratio of pathogen-specific RPM between clinical samples and negative controls. In addition, by integrating sequence abundance, specimen type, and clinical relevance, suspected pathogens are prioritized and reported in a structured format, thereby improving result interpretability and clinical utility.

Figure 3. Interpretation principles for suspected pathogens in the μCaler RIA Solution.  

Note: For results classified as suspected contamination, interpret cautiously and review whether the same (or related) pathogen is also detected in other samples within the same batch before making a final call.

3.3.5 Precision Identification to Guide Individualized Therapy

Powered by proprietary intelligent algorithms, the system effectively resolves ambiguity in genus- and species-level identification. In parallel, it jointly outputs the AMR markers profile, a list of associated antimicrobials, and pathogen attribution information to generate interpretable, prioritized list of candidate therapies and confirmation targets. This provides key molecular evidence to support precision antimicrobial prescribing, reduce empiric antibiotic use, and promotes standardized clinical management of respiratory infectious diseases.

Table 1. AMR markers list of the μCaler RIA Solution.

Contact us

μCaler RIA Solution is designed to bridge the gap between “data generation” to “clinical decision-making,” enabling actionable insights from complex pathogen detection results. In upcoming sections, we will further present clinical application cases and performance evaluations. For more information, please contact sales@njnad.com or your local representative.