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Laboratory validation of a clinical metagenomic sequencing assay for pathogen detection in cerebrospinal fluid

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...

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Autores principales: Miller, Steve, Naccache, Samia N., Samayoa, Erik, Messacar, Kevin, Arevalo, Shaun, Federman, Scot, Stryke, Doug, Pham, Elizabeth, Fung, Becky, Bolosky, William J., Ingebrigtsen, Danielle, Lorizio, Walter, Paff, Sandra M., Leake, John A., Pesano, Rick, DeBiasi, Roberta, Dominguez, Samuel, Chiu, Charles Y.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6499319/
https://www.ncbi.nlm.nih.gov/pubmed/30992304
http://dx.doi.org/10.1101/gr.238170.118
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author Miller, Steve
Naccache, Samia N.
Samayoa, Erik
Messacar, Kevin
Arevalo, Shaun
Federman, Scot
Stryke, Doug
Pham, Elizabeth
Fung, Becky
Bolosky, William J.
Ingebrigtsen, Danielle
Lorizio, Walter
Paff, Sandra M.
Leake, John A.
Pesano, Rick
DeBiasi, Roberta
Dominguez, Samuel
Chiu, Charles Y.
author_facet Miller, Steve
Naccache, Samia N.
Samayoa, Erik
Messacar, Kevin
Arevalo, Shaun
Federman, Scot
Stryke, Doug
Pham, Elizabeth
Fung, Becky
Bolosky, William J.
Ingebrigtsen, Danielle
Lorizio, Walter
Paff, Sandra M.
Leake, John A.
Pesano, Rick
DeBiasi, Roberta
Dominguez, Samuel
Chiu, Charles Y.
author_sort Miller, Steve
collection PubMed
description 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.
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spelling pubmed-64993192019-05-17 Laboratory validation of a clinical metagenomic sequencing assay for pathogen detection in cerebrospinal fluid Miller, Steve Naccache, Samia N. Samayoa, Erik Messacar, Kevin Arevalo, Shaun Federman, Scot Stryke, Doug Pham, Elizabeth Fung, Becky Bolosky, William J. Ingebrigtsen, Danielle Lorizio, Walter Paff, Sandra M. Leake, John A. Pesano, Rick DeBiasi, Roberta Dominguez, Samuel Chiu, Charles Y. Genome Res Method 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. Cold Spring Harbor Laboratory Press 2019-05 /pmc/articles/PMC6499319/ /pubmed/30992304 http://dx.doi.org/10.1101/gr.238170.118 Text en © 2019 Miller et al.; Published by Cold Spring Harbor Laboratory Press http://creativecommons.org/licenses/by-nc/4.0/ 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/.
spellingShingle Method
Miller, Steve
Naccache, Samia N.
Samayoa, Erik
Messacar, Kevin
Arevalo, Shaun
Federman, Scot
Stryke, Doug
Pham, Elizabeth
Fung, Becky
Bolosky, William J.
Ingebrigtsen, Danielle
Lorizio, Walter
Paff, Sandra M.
Leake, John A.
Pesano, Rick
DeBiasi, Roberta
Dominguez, Samuel
Chiu, Charles Y.
Laboratory validation of a clinical metagenomic sequencing assay for pathogen detection in cerebrospinal fluid
title Laboratory validation of a clinical metagenomic sequencing assay for pathogen detection in cerebrospinal fluid
title_full Laboratory validation of a clinical metagenomic sequencing assay for pathogen detection in cerebrospinal fluid
title_fullStr Laboratory validation of a clinical metagenomic sequencing assay for pathogen detection in cerebrospinal fluid
title_full_unstemmed Laboratory validation of a clinical metagenomic sequencing assay for pathogen detection in cerebrospinal fluid
title_short Laboratory validation of a clinical metagenomic sequencing assay for pathogen detection in cerebrospinal fluid
title_sort laboratory validation of a clinical metagenomic sequencing assay for pathogen detection in cerebrospinal fluid
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6499319/
https://www.ncbi.nlm.nih.gov/pubmed/30992304
http://dx.doi.org/10.1101/gr.238170.118
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