With the advancement of technology, traditional pathogen diagnosis methods are facing unprecedented challenges. Clinical metabolic genomic next-generation sequencing (mNGS) has gradually shown its unique advantages, especially in the diagnosis of complex infectious diseases. Its comprehensive detection capabilities make it as important as a superhero.
Clinical metabolic genomics next-generation sequencing provides the possibility for comprehensive detection of potential pathogens, which is particularly valuable when traditional methods are difficult to work.
mNGS refers to the analysis of genetic material (DNA or RNA) of microorganisms and hosts in clinical samples through next-generation sequencing technology without the need to know the specific pathogen. A key advantage of this approach is its ability to detect multiple pathogens simultaneously, particularly when other more targeted detection methods (such as PCR) fail.
The typical workflow of mNGS includes sample collection, RNA/DNA extraction, stock preparation, high-throughput sequencing, and bioinformatics analysis. The quality of sample collection directly affects the test results, so it should be carried out with caution.
The most commonly used sample sources include blood, stool, cerebrospinal fluid (CSF), urine and nasopharyngeal swabs. When extracting samples, choose the appropriate extraction kit to exclude background interferences and focus on the RNA or DNA of the pathogen.
Due to the influence of background noise, strategies to increase pathogen signals are particularly important. The choice of high-throughput sequencing platform depends on the research goals and experience of the laboratory. Currently, the Illumina MiSeq system is the most common choice, but emerging technologies such as MinION also show great potential.
The improvement of high-throughput sequencing technology has made the time-sensitive monitoring and epidemiological applications of various unknown causes more immediate and accurate.
mNGS shows significant potential in infectious disease diagnosis, especially for pathogens that cannot be located by traditional detection methods. For example, mNGS outperforms traditional microbiological testing in diagnosing meningitis and encephalitis.
As antibiotic resistance becomes a growing problem, mNGS provides a new way to detect and characterize these genes, helping the medical community better understand and address this challenge.
Although mNGS has applications in multiple fields, challenges such as its clinical utility, laboratory validity, and economics still need to be addressed. Many studies are still in the case report stage and lack widespread clinical application.
ConclusionIn the future, if the current challenges can be overcome, mNGS will demonstrate its indispensable value in public health and epidemic prevention and control.
With the demand for rapid diagnostic tools continuing to rise, will mNGS become more common and standard practice in infectious disease diagnosis in the future?