
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.
570, R, 610, Medicine, Article
570, R, 610, Medicine, Article
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 10 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
