Infectious lower respiratory diseases and diarrheal diseases are the leading causes of death globally. And the ongoing COVID-19 pandemic, which has contributed to 4.1 million deaths in 2019, once again is reminding the necessity of proactively identifying early signs of infectious disease outbreaks before things are getting worse. Conventional microbial diagnostics techniques would identify pathogens under specific culture conditions by serological detection of pathogen-associated antibodies or microbial genetic investigation using PCR, but these methods have been seen obvious shortcomings in pathogen coverage. It's highly required to find advanced scientific tools that are more sensitive even with a low microbial load or when targeted microorganisms are not suitable for in vitro culture, for which metagenomic approaches that can profile all DNA or RNA of a patient sample are increasingly catching the eyes of researchers.
How metagenomics can be used in infectious disease surveillance?
Metagenomics, as a matter of fact, is not a novel technology and has been extensively applied to characterize environmental and forensic samples. But its application in infectious disease surveillance is slightly different as metagenomic sequencing now has been combined with next-generation sequencing (NGS) technologies for higher throughput than microarray methods. Metagenomic next-generation sequencing (mNGS) now is a key player in identifying causes of antibiotic resistance and infectious disease outbreaks due to high throughput and decreased cost.
The workflow of metagenomics based on NGS sequencing includes total nucleic acid extraction of DNA and RNA from the sample, RNA reverse transcription into cDNA, DNA and cDNA sequencing with NGS instruments, and assignment of DNA and cDNA materials to reference genomes to determine their microbial populations and relative numbers. It's undeniable that conventional methods like molecular PCR diagnostics assay are relatively time- and cost-effective, but metagenomic next-generation sequencing definitely can detect and identify a wider range of pathogens, including viruses, bacteria, fungi, and parasites, from samples by recognizing their unique DNA or RNA sequences. The most important thing is that mNGS allows acquired data to be integrated and characterized through other bioinformatic techniques, for instance, the RNA sequencing result of humans, which means researchers can more easily and intuitively surveil the disease progression, responses to the pathogens, as well as the treatment against them.
Indeed, in a recent study of infectious community-acquired pneumonia co-worked by the Chinese People's Liberation Army General Hospital and the Vision Medicals Center for Medical Research, researchers can only detect 38% of 100 infected patients with 105 pathogens, only bacteria and fungi, by conventional culture methods. On the contrary, the control group, 59 patients having the same condition in several health indicators, using mNGS was detected with 179 pathogens, including bacteria, fungi, and viruses. mNGS techniques have obvious advantages over traditional approaches in detecting a broader range of pathogens, which is significantly important especially when it comes to infectious diseases like community-acquired pneumonia that could be a result of more than 100 viral, bacterial, fungal, and parasitic species.
Summary
Infectious diseases remain one of the most worrying lethal diseases, but early detection of pathogens means a higher survival rate only if with improved surveillance. Metagenomic next-generation sequencing technology may have limitations in turnaround times and sensitivity in pathogen detection, but it's more reliable than conventional culture methods with wider coverage of pathogens. Metagenomics–related techniques and tools for bioinformatic analysis are promising in the surveillance of infectious diseases with the improvement of sample processing approaches and algorithms.
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