Metagenomic identification of severe pneumonia pathogens with rapid Nanopore sequencing in mechanically-ventilated patients

Background Metagenomic sequencing of respiratory microbial communities for etiologic pathogen identification in pneumonia may help overcome the limitations of current culture-based methods. We examined the feasibility and clinical validity of rapid-turnaround metagenomics with Nanopore™ sequencing of respiratory samples for severe pneumonia diagnosis. Methods and Findings We conducted a case-control study of mechanically-ventilated patients with pneumonia (nine culture-positive and five culture-negative) and without pneumonia (eight controls). We collected endotracheal aspirate samples (ETAs) and applied a microbial DNA enrichment method prior to performing metagenomic sequencing with the Oxford Nanopore MinION device. We compared Nanopore results against clinical microbiologic cultures and bacterial 16S rRNA gene sequencing. In nine culture-positive cases, Nanopore revealed communities with low alpha diversity and high abundance of the bacterial (n=8) or fungal (n=1) species isolated by clinical cultures. In four culture-positive cases with resistant organisms, Nanopore detected antibiotic resistance genes corresponding to the phenotypic resistance identified by clinical antibiograms. In culture-negative pneumonia, Nanopore revealed probable bacterial pathogens in 1/5 cases and airway colonization by Candida species in 3/5 cases. In controls, Nanopore showed high abundance of oral bacteria in 5/8 subjects, and identified colonizing respiratory pathogens in the three other subjects. Nanopore and 16S sequencing showed excellent concordance for the most abundant bacterial taxa. Conclusion We demonstrated technical feasibility and proof-of-concept clinical validity of Nanopore metagenomics for severe pneumonia diagnosis, with striking concordance with positive microbiologic cultures and clinically actionable information offered from the sequencing profiles of culture-negative samples. Prospective studies with real-time metagenomics are warranted to examine the impact on antimicrobial decision-making and clinical outcomes. ### Competing Interest Statement Dr. Bryan J. McVerry is a consultant for Vapotherm, Inc. Dr. Georgios Kitsios receives research funding from Karius, Inc. Dr. Justin O'Grady receives (or received) research funding and consumable support from Oxford Nanopore Technologies (ONT) and financial support for attending conferences and for speaking at ONT headquarters. The other authors have no conflicts of interest to declare. ### Funding Statement Funding support: National Institutes of Health [K23 HL139987 (GDK); U01 HL098962 (AM); P01 HL114453 (BJM); R01 HL097376 (BJM); K24 HL123342 (AM); K23 GM122069 (FS)]. This paper presents independent research funded by the National Institute for Health Research (NIHR) under its Program Grants for Applied Research Program (reference no. RP-PG-0514-20018, JOG.), the UK Antimicrobial Resistance Cross Council Initiative (no. MR/N013956/1, JOG), Rosetrees Trust (no. A749, JOG) and the Biotechnology and Biological Sciences Research Council (BBSRC) Institute Strategic Programme Microbes in the Food Chain BB/R012504/1 and its constituent projects BBS/E/F/000PR10348 and BBS/E/F/000PR10349 (JOG). ### Author Declarations All relevant ethical guidelines have been followed and any necessary IRB and/or ethics committee approvals have been obtained. Yes All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes Any clinical trials involved have been registered with an ICMJE-approved registry such as ClinicalTrials.gov and the trial ID is included in the manuscript. Not Applicable I have followed all appropriate research reporting guidelines and uploaded the relevant Equator, ICMJE or other checklist(s) as supplementary files, if applicable. Yes Data Sharing Statements: All de-identified sequencing data were submitted to Sequence Read Archive (SRA) database, accession numbers 12268279 - 12268349. All de-identified datasets for this study are provided in . .