According to the findings of a new study conducted by experts at Johns Hopkins Medicine, Next Generation Sequencing enables clinicians to rapidly and accurately identify a single pathogen from among hundreds of probable possibilities by continuously sequencing multiple DNA strands detected in patient samples.
The researchers compared the pathogen detecting ability of an NGS system — the Respiratory Pathogen Infectious Diseases/Antimicrobial Resistance Panel (RPIP) — with a previously studied NGS system and standard of care (SOC) diagnostic methods for samples obtained with bronchoalveolar lavage in a paper first published online on June 13, 2022, in the Journal of Clinical Microbiology of the American Society for Microbiology.
A bronchoscope is inserted through the mouth or nose into the lungs, and a fluid wash is collected for evaluation. According to the researchers, their investigation is one of the first to compare NGS and SOC diagnoses for respiratory infections.
“We evaluated two NGS diagnostic techniques, one of which was the RPIP, and found that in both cases, the ability of NGS to identify specific pathogens was nearly comparable to the battery of diagnostic tests clinicians have been using for decades,” says study senior author Patricia Simner, Ph.D., M.Sc., associate professor of pathology at Johns Hopkins University.
“While this indicates tremendous potential for the RPIP and NGS diagnostics in general, we believe that additional work is required to develop the technology before NGS can be regarded equivalent to or superior than existing SOC approaches.”
Simner and colleagues initially assessed the diagnostic capability of metagenomic NGS, a previously described workflow procedure in which all DNA recovered from a bronchoalveolar lavage is sequenced – including genetic material specific to the patient (the “host read” or “human read”) and the desired pathogen (the “microbial read”). By removing the host DNA, physicians may focus their search on the remaining genetic information in the hopes of finding the microbial read and, eventually, determining the source of the patient’s disease.
The researchers used the RPIP system to test a different NGS method termed focused NGS in the second half of their experiment. As with metagenomic NGS, everything in the patient respiratory sample is sequenced, but capture probes — small segments of single-stranded DNA that correspond structurally to the DNA of certain diseases — are utilised to improve the searching ability.
“Using NGS to find pathogen genetic signatures is like searching for information on a specific topic in a library with a huge number of books,” says study lead author David Gaston, M.D., Ph.D., a former pathology fellow at the Johns Hopkins University School of Medicine who now works at Vanderbilt University Medical Center.
“When it comes to metagenomic NGS, you have to read through all of the literature to find the ones that mention the issue. However, with targeted NGS, you first ask the librarian to retrieve the volumes most likely to contain the topic, and then you do a more focused, promising search.”
The researchers discovered that the efficiency of both metagenomic and targeted NGS differed depending on the type of organism sought. Both NGS approaches effectively identified viruses, with herpes viruses being the most easily recognised. The results for bacteria and mycobacteria (which includes the organism that causes TB) neared the level of SOC diagnostics, but dropped down as the number of species reduced – even when the capture probes were used in targeted NGS. Fungi were not found using either NGS technique.
Overall, the RIPP targeted process agreed with standard diagnostics 66% of the time, according to the researchers. They discovered a 46% agreement for focused NGS to detect pathogens of clinical significance and an 86% agreement for demonstrating pathogen absence.
Along with the ability to correctly identify more than 300 pathogenic organisms from a bronchoalveolar lavage, the researchers believe that focused NGS has tremendous promise for one day revealing 1,200 genetic markers in pathogens that indicate which species are most likely to withstand antibiotics.
“Overall, the present accuracy of both metagenomic and targeted NGS approaches that of current diagnostic techniques, which is a big lesson from our work,” Gaston adds.
“We discovered that while NGS can detect many infections, it cannot detect all of them, and that in some situations, both NGS approaches might identify pathogens that conventional diagnostics would have missed.”
“There are now advantages and disadvantages to using NGS as a microbiological diagnostic tool,” Simner explains. “The RPIP targeted procedure, for example, necessitates more time and reagents but requires less bioinformatic analysis of the generated data. Metagenomic NGS, on the other hand, is less technically difficult but requires more complicated analysis.”
Based on their findings, the researchers believe that metagenomic and tailored NGS processes can be used in conjunction with, but not as a replacement for, SOC diagnostic approaches.
They predict that with further improvement, NGS systems will one day become the gold standard for respiratory pathogen detection.
Karen Carroll, John Fissel, Ethan Gough, Emily Jacobs, Eili Klein, Heather Miller, and Jaijun Wu are part of the Johns Hopkins Medicine study team, along with Gaston and Simner.
The study was funded by the Sherrilyn and Ken Fisher Center for Environmental Infectious Diseases at the Johns Hopkins University School of Medicine’s Division of Infectious Diseases. The RPIP panel and the Explify automated system, which were utilised for bioinformatic analysis of RPIP targeted NGS data, were given by their respective vendors, Illumina and IDbyDNA.
The researchers, however, state that these entities had no involvement in the study’s design, data collecting and analysis, or the choice to submit the work for publication. The authors of the paper disclose no conflicts of interest.