Laboratory validation of a clinical metagenomic sequencing assay for pathogen detection in cerebrospinal fluid
- Steve Miller1,2,10,
- Samia N. Naccache1,2,3,10,
- Erik Samayoa1,
- Kevin Messacar4,
- Shaun Arevalo1,2,
- Scot Federman1,2,
- Doug Stryke1,2,
- Elizabeth Pham1,
- Becky Fung1,
- William J. Bolosky5,
- Danielle Ingebrigtsen1,
- Walter Lorizio1,
- Sandra M. Paff1,
- John A. Leake6,
- Rick Pesano6,
- Roberta DeBiasi7,8,
- Samuel Dominguez4 and
- Charles Y. Chiu1,2,9
- 1Department of Laboratory Medicine, University of California, San Francisco, San Francisco, California 94143, USA;
- 2UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, California 94143, USA;
- 3Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles, Los Angeles, California 90027, USA;
- 4Department of Pediatrics, Children's Hospital Colorado and University of Colorado School of Medicine, Aurora, Colorado 80045, USA;
- 5Microsoft Research, Redmond, Washington 98052, USA;
- 6Quest Diagnostics Nichols Institute, San Juan Capistrano, California 92675, USA;
- 7Department of Pediatrics, Division of Pediatric Infectious Diseases, Children's National Health System, Washington, DC 20010, USA;
- 8Department of Pediatrics, Microbiology, Immunology, and Tropical Medicine, The George Washington University School of Medicine, Washington, DC 20037, USA;
- 9Department of Medicine, Division of Infectious Diseases, University of California, San Francisco, San Francisco, California 94143, USA
-
↵10 These authors contributed equally to this work.
Abstract
Metagenomic next-generation sequencing (mNGS) for pan-pathogen detection has been successfully tested in proof-of-concept case studies in patients with acute illness of unknown etiology but to date has been largely confined to research settings. Here, we developed and validated a clinical mNGS assay for diagnosis of infectious causes of meningitis and encephalitis from cerebrospinal fluid (CSF) in a licensed microbiology laboratory. A customized bioinformatics pipeline, SURPI+, was developed to rapidly analyze mNGS data, generate an automated summary of detected pathogens, and provide a graphical user interface for evaluating and interpreting results. We established quality metrics, threshold values, and limits of detection of 0.2–313 genomic copies or colony forming units per milliliter for each representative organism type. Gross hemolysis and excess host nucleic acid reduced assay sensitivity; however, spiked phages used as internal controls were reliable indicators of sensitivity loss. Diagnostic test accuracy was evaluated by blinded mNGS testing of 95 patient samples, revealing 73% sensitivity and 99% specificity compared to original clinical test results, and 81% positive percent agreement and 99% negative percent agreement after discrepancy analysis. Subsequent mNGS challenge testing of 20 positive CSF samples prospectively collected from a cohort of pediatric patients hospitalized with meningitis, encephalitis, and/or myelitis showed 92% sensitivity and 96% specificity relative to conventional microbiological testing of CSF in identifying the causative pathogen. These results demonstrate the analytic performance of a laboratory-validated mNGS assay for pan-pathogen detection, to be used clinically for diagnosis of neurological infections from CSF.
Footnotes
-
[Supplemental material is available for this article.]
-
Article published online before print. Article, supplemental material, and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.238170.118.
-
Freely available online through the Genome Research Open Access option.
- Received April 6, 2018.
- Accepted February 25, 2019.
This article, published in Genome Research, is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.
