Unified metagenomic method for rapid detection of microorganisms in clinical samples.

ABSTRACT

BACKGROUND: Clinical metagenomics involves the genomic sequencing of all microorganisms in clinical samples ideally after depletion of human DNA to increase sensitivity and reduce turnaround times. Current human DNA depletion methods preferentially preserve either DNA or RNA containing microbes, but not both simultaneously. Here we describe and present data using a practical and rapid mechanical host-depletion method allowing simultaneous detection of RNA and DNA microorganisms linked with nanopore sequencing. METHODS: The human cells from respiratory samples are lysed mechanically using 1.4 mm zirconium-silicate spheres and the human DNA is depleted using a nonspecific endonuclease. The RNA is converted to dsDNA to allow the simultaneous sequencing of DNA and RNA. RESULTS: The method decreases human DNA concentration by a median of eight Ct values while detecting a broad range of RNA & DNA viruses, bacteria, including atypical pathogens (Legionella, Chlamydia, Mycoplasma) and fungi (Candida, Pneumocystis, Aspergillus). The first automated reports are generated after 30 min sequencing from a 7 h end-to-end workflow. Sensitivity and specificity for bacterial detection are 90% and 100%, respectively, and viral detection are 92% and 100% after 2 h of sequencing. Prospective validation on 33 consecutive lower respiratory tract samples from ventilated patients with suspected pneumonia shows 60% concordance with routine testing, detection of additional pathogens in 21% of samples and pathogen genomic assembly achieve for 42% of viruses and 33% of bacteria. CONCLUSIONS: Although further workflow refinement and validation on samples containing a broader range of pathogens is required, it holds promise as a clinically deployable workflow suitable for evaluation in routine microbiology laboratories.

Metagenomics is the analysis of genetic material from microbes such as bacteria and viruses in a sample. There are limitations with existing metagenomics methods, such as not being able to detect the full range of microbes present in a sample. This paper introduces an approach that identifies multiple types of microbes. This is accomplished through the mechanical disruption of human cells, which allows for an effective depletion of human genetic material. Our method demonstrates encouraging preliminary results within a 7 h process, achieving good sensitivity for the detection of bacteria and viruses. We demonstrate the identification of relevant microbes in samples from patients with respiratory infections. This technique holds promise for adoption in clinical settings, potentially enhancing our ability to diagnose respiratory infections quickly.