The Role of Metagenomics and Next-Generation Sequencing in Infectious Disease Diagnosis

Abstract

Background: Metagenomic next-generation sequencing (mNGS) for pathogen detection is becoming increasingly available as a method to identify pathogens in cases of suspected infection. mNGS analyzes the nucleic acid content of patient samples with high-throughput sequencing technologies to detect and characterize microorganism DNA and/or RNA. This unbiased approach to organism detection enables diagnosis of a broad spectrum of infection types and can identify more potential pathogens than any single conventional test. This can lead to improved ability to diagnose patients, although there remains concern regarding contamination and detection of nonclinically significant organisms.

Content: We describe the laboratory approach to mNGS testing and highlight multiple considerations that affect diagnostic performance. We also summarize recent literature investigating the diagnostic performance of mNGS assays for a variety of infection types and recommend further studies to evaluate the improvement in clinical outcomes and cost-effectiveness of mNGS testing.

Summary: The majority of studies demonstrate that mNGS has sensitivity similar to specific PCR assays and will identify more potential pathogens than conventional methods. While many of these additional organism detections correlate with the expected pathogen spectrum based on patient presentations, there are relatively few formal studies demonstrating whether these are true-positive infections and benefits to clinical outcomes. Reduced specificity due to contamination and clinically nonsignificant organism detections remains a major concern, emphasizing the importance of careful interpretation of the organism pathogenicity and potential association with the clinical syndrome. Further research is needed to determine the possible improvement in clinical outcomes and cost-effectiveness of mNGS testing.

Keywords: Clinical metagenomics; infectious disease diagnostics; next-generation sequencing.