Infectious diseases cause a considerable health burden worldwide. The World Health Organization predicts that even in the year 2050, 13 million deaths
will be attributed to infectious diseases. An overwhelming majority of these deaths are a result of a few species of bacteria and viruses, with 20 out of the 1400 recognized species being the major culprits. To make matters worse, many of these pathogens have developed antibiotic resistance to the drugs conventionally used to treat them. A priority in treating these diseases is the rapid and accurate identification of the pathogen responsible for the disease, which is oftentimes complicated by the fact that some infections caused by different pathogens have indistinguishable clinical manifestations.
Traditionally, identification relies on methods such as culturing the organism and performing antimicrobial susceptibility tests, which can take up to a few weeks for slow-growing species like mycobacteria. These methods often lead to missed or unknown diagnoses prompting physicians to prescribe broad-spectrum antibiotics which also limits the use of more effective, target therapeutics. Consequently, a better diagnostic tool is needed to overcome the limitations of traditional tools. In a new study
published in Clinical Infectious Diseases
), lead investigator Patricia J. Simner, PhD, and her colleagues examine the advantages and drawbacks of using one such diagnostic tool, metagenomic next-generation sequencing (mNGS), for the identification of pathogens.
Next-generation sequencing (NGS) technologies are now more feasible to use than ever before, because of recent progress on the tool that has lowered the cost and made the process more user-friendly. An application of NGS, unbiased metagenomic next-generation sequencing, has the potential to replace current identification methods because it allows for identification of pathogens directly from clinical specimens, without the need for culturing. The strength of NGS is that it allows the sequencing of many DNA molecules, without the need of targeted sequencing, resulting in millions of reads per instrument run. In addition, mNGS, allows for the sequencing of all the nucleic acid present, whether DNA or RNA, in a specimen in parallel. This allows for the amplification of both host and pathogen DNA, which can make interpretation of results more difficult as host DNA will dominate the number of reads. However, studies have demonstrated that even if a pathogen nucleic acid yields only .00001 to .7% of the total reads, an accurate diagnosis can still be made, highlighting the power and sensitivity of this tool.
Moreover, protocols for mNGS can utilize either a DNA- or an RNA-based approach, depending on the study. If a DNA approach is utilized, all pathogen types except for RNA viruses will be detected. However, to detect RNA viruses, an RNA-based approach must be utilized. This approach also provides key information about which organisms in the specimen are transcriptionally active.
Overall, mNGS promises to be a useful and universal pathogen identification tool that could overcome many of the limitations for infectious disease diagnostics. In addition, the investigators of the CID
study envision the use of this tool for other avenues, such as understanding how the host immune system responds to pathogens or to detect genes important for pathogenesis. Currently, mNGS methods are being developed and progress is being made to overcome potential limitations of the tool.
Samar Mahmoud graduated from Drew University in 2011 with a BA in Biochemistry and Molecular Biology. After two years of working in the industry as a Quality Control Technician for a blood bank, she went back to school and graduated from Montclair State University in 2016 with an MS in Pharmaceutical Biochemistry. She is currently pursuing her PhD in Molecular and Cellular Biology at the University of Massachusetts at Amherst.
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