Thousands of pathogens are known to infect humans, but only a fraction are readily identifiable using current diagnostic methods. Microbial cell-free DNA sequencing offers the potential to non-invasively identify a wide range of infections throughout the body, but the challenges of clinical-grade metagenomic testing must be addressed. Here we describe the analytical and clinical validation of a next-generation sequencing test that identifies and quantifies microbial cell-free DNA in plasma from 1,250 clinically relevant bacteria, DNA viruses, fungi and eukaryotic parasites. Test accuracy, precision, bias and robustness to a number of metagenomics-specific challenges were determined using a panel of 13 microorganisms that model key determinants of performance in 358 contrived plasma samples, as well as 2,625 infections simulated in silico and 580 clinical study samples. The test showed 93.7% agreement with blood culture in a cohort of 350 patients with a sepsis alert and identified an independently adjudicated cause of the sepsis alert more often than all of the microbiological testing combined (169 aetiological determinations versus 132). Among the 166 samples adjudicated to have no sepsis aetiology identified by any of the tested methods, sequencing identified microbial cell-free DNA in 62, likely derived from commensal organisms and incidental findings unrelated to the sepsis alert. Analysis of the first 2,000 patient samples tested in the CLIA laboratory showed that more than 85% of results were delivered the day after sample receipt, with 53.7% of reports identifying one or more microorganisms.
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The core software used as part of the Karius test is described in the Clinical-grade microbial cfDNA sequencing for infectious disease section in Methods, under the sub-sections Sequence data processing and alignment, Microorganism abundance estimation and Pathogen detection. The open source software includes the following external tools: bcl2fastq v184.108.40.206, Trimmomatic v0.32, Bowtie v2.2.4 and BLAST v2.2.30. A description of all open source code is included in Methods and further details are available on request. The proprietary portions of the code are not available.
The data that support the findings of this study are available from the corresponding author on request. Sequencing data that support the finding of this study (with human reads removed) have been deposited in NCBI SRA and can be accessed with the BioProject identifier PRJNA507824.
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The authors would like to thank S. Sinha for assistance with the preparation of the manuscript, as well as H. Quach, R. Davila, S. Madan, V. Baichwal, C. Ho, H. Seng, R. Aquino, A. Parham, R. Mann, I. Brown, P. Callagy, A. Visweswaran, C. Keller, C. Bucsit and A. Araya for their contributions to these validation studies.
Supplementary Figures 1–9, Supplementary Tables 1–4 and Supplementary Table 8.
Subjects with definite and probable infections identified by NGS.
Aetiology of infection for patients with positive NGS results adjudicated as possible.
Subjects with ‘unlikely’ infections identified by NGS.
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Rapid detection of invasive Mycobacterium chimaera disease via a novel plasma-based next-generation sequencing test
BMC Infectious Diseases (2019)
Nature Microbiology (2019)
Nature Reviews Genetics (2019)