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Unveiling the secrets of microorganisms: How does mNGS identify hidden pathogens in clinical practice?
With the advancement of science and technology, clinical microbiology is ushering in a new round of changes. Among them, clinical metabolic genomics (mNGS) uses advanced gene sequencing technology to comprehensively analyze the genetic material (DNA or RNA) of microorganisms and hosts from patients' clinical samples. This technology not only improves the ability to detect pathogens, but also demonstrates its potential, especially when traditional detection methods fail.
mNGS can identify and characterize the genomes of bacteria, fungi, parasites, and viruses directly from clinical specimens without prior knowledge of the specific pathogen.
Traditional pathogen detection methods are often limited by pre-set assumptions about known pathogens, which makes it impossible to determine the cause in some cases. The emergence of mNGS changed all that. At its core, the technology can detect all potential pathogens in a specimen, which is critical for diagnosing infectious diseases, especially when other more targeted tests, such as PCR, fail.
mNGS Workflow
A typical mNGS workflow includes the following steps:
- Sample collection: includes blood, stool, cerebrospinal fluid, urine or nasopharyngeal swab, etc.
- RNA/DNA extraction: Use a dedicated extraction kit to extract the genetic material in the sample.
- Library preparation and optimization strategy: Mainly includes target selection and background noise removal.
- High-throughput sequencing: Select a suitable sequencing platform to sequence nucleic acid fragments.
- Bioinformatics analysis: Process and interpret sequencing data.
Bioinformatics analysis requires professional knowledge and computing resources, and in-depth data analysis provides the necessary support for clinical diagnosis.
Each step in this process is crucial and has a profound impact on the final test results. In particular, high-throughput sequencing technology, such as the Illumina MiSeq system, has become one of the mainstream tools for diagnosing infectious diseases. With the support of this technology, scientists can quickly and accurately identify potential pathogens.
Application of mNGS in infectious diseases
mNGS shows great potential in infectious disease diagnosis, especially when faced with unknown etiologies:
- Diagnosing meningitis and encephalitis: This technology can identify a variety of pathogenic microorganisms when traditional tests are unable to confirm the diagnosis.
- Study of antimicrobial resistance: With mNGS, the drug resistance genes of pathogens can be quickly detected, which helps to develop more appropriate treatment plans.
- Epidemic response: In the prevention and control of emerging infectious diseases, mNGS can identify pathogens in a timely manner and assist in public health decision-making.
mNGS provides a comprehensive identification framework for potential disease-causing microorganisms, capable of identifying multiple pathogens in a single test.
For example, in patients with pneumonia, mNGS can rapidly identify the presence of pathogenic bacteria, which is critical for developing an effective treatment plan. Compared with traditional methods, mNGS provides a wider range of detection and may show mixed infections with many bacteria, viruses or fungi.
Challenges
Although mNGS shows great potential in clinical applications, it also faces many challenges:
- Clinical practicality: Currently, most mNGS data come from case reports, and there are still few cases that are truly implemented in clinical practice.
- Laboratory Validation: Many tests have not been validated, which affects the credibility of mNGS in clinical settings.
- Accuracy and Sensitivity: High noise background may affect the accuracy of the test, especially in the case of mixed infection.
- Cost considerations: Currently, the cost of mNGS is still relatively high, limiting its widespread clinical application.
With the development of technology, how to overcome these challenges and make mNGS better serve clinical practice in the future will be the direction that scientists and medical workers need to work together.
Looking back at the development of mNGS, this technology has unveiled the mystery of the microbial world for us, but in daily clinical applications, are there still many potential pathogens that have not yet been identified and understood?
