Rapid pathogen detection by metagenomic next-generation sequencing of infected body fluids

Gu, Wei; Deng, Xianding; Lee, Marco; Sucu, Yasemin D.; Arevalo, Shaun; Stryke, Doug; Federman, Scot; Gopez, Allan; Reyes, Kevin; Zorn, Kelsey C.; Sample, Hannah; Yu, Guixia; Ishpuniani, Gurpreet; Briggs, Benjamin; Chow, Eric D.; Berger, Amy; Wilson, Michael R.; Wang, Candace; Hsu, Elaine; Miller, Steve; DeRisi, Joseph L.; Chiu, Charles Y.

doi:10.1038/s41591-020-1105-z

Cited by 400 publications

(405 citation statements)

References 61 publications

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“…Demonstrating these benefits is necessary to support the introduction of CMg into predominantly culture-based microbiology laboratories, and for the multidisciplinary team to change their clinical practice to accommodate rapid comprehensive information on ICU-pathogens. Previous studies have given examples of how CMg can diagnose respiratory infection (20, 23, 30-35), predict AMR (18, 36, 37) and provide genotyping data (37-39), but here for the first time, all these outputs are combined in a single test demonstrating the impact CMg would have when applied in a challenging real-world setting.…”

Section: Discussionmentioning

confidence: 99%

“…Clinical metagenomic (CMg) using nanopore technology has potential to meet these needs due to its unbiased pan-microbial coverage (18, 19) and ability to provide real-time data acquisition and analysis (20). It has been evaluated for respiratory, urinary tract and prosthetic joint infections (20-23), however, the full clinical potential required for laboratories and clinical teams to change their long-standing practice has not been demonstrated. We therefore prospectively assessed whether CMg testing of respiratory samples from COVID-19 patients with suspected secondary bacterial or fungal pneumonia, could significantly improve their initial antimicrobial treatment and detect outbreaks affecting a large COVID-19 patient cohort across 7 ICUs.…”

Section: Introductionmentioning

confidence: 99%

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Application of respiratory metagenomics for COVID-19 patients on the intensive care unit to inform appropriate initial antimicrobial treatment and rapid detection of nosocomial transmission

Charalampous

Alcolea-Medina

Snell

et al. 2020

Preprint

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BackgroundClinical metagenomics (CMg) is being evaluated for translation from a research tool into routine diagnostic service, but its potential to significantly improve management of acutely unwell patients has not been demonstrated. The SARS-CoV-2 pandemic provides impetus to determine that benefit given increased risk of secondary infection and nosocomial transmission by multi-drug resistant (MDR) pathogens linked with expansion of critical care capacity.MethodsProspective evaluation of CMg using nanopore sequencing was performed on 43 respiratory samples over 14 weeks from a cohort of 274 intubated patients across seven COVID-19 intensive care units.ResultsBacteria or fungi were cultured from 200 (73%) patients, with a predominance of Klebsiella spp. (31%) and C. striatum (7%) amongst other common respiratory pathogens. An 8 hour CMg workflow was 93% sensitive and 81% specific for bacterial identification compared to culture, and reported presence or absence of β-lactam resistance genes carried by Enterobacterales that would modify initial guideline-recommended antibiotics in every case. CMg was also 100% concordant with quantitative PCR for detecting Aspergillus fumigatus (4 positive and 39 negative samples). Single nucleotide polymorphism (SNP)-typing using 24 hour sequence data identified an MDR-K. pneumoniae ST307 outbreak involving 4 patients and an MDR-C. striatum outbreak potentially involving 14 patients across three ICUs.ConclusionCMg testing for ICU patients provides same-day pathogen detection and antibiotic resistance prediction that significantly improves initial treatment of nosocomial pneumonia and rapidly detects unsuspected outbreaks of MDR-pathogens.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Application of respiratory metagenomics for COVID-19 patients on the intensive care unit to inform appropriate initial antimicrobial treatment and rapid detection of nosocomial transmission

Charalampous

Alcolea-Medina

Snell

et al. 2020

Preprint

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“…The first study incorporated residual body fluid samples sent to the UCSF Clinical Laboratories (San Francisco, CA, USA) between 2017 to 2019 for flow cytometry, cell count, chemistries, and microbiological testing. All samples matching inclusion criteria (see below) in a recent metagenomics study were used, except five samples were excluded because they had less than 450,000 reads [ 20 ]. Serial dilutions of the sample input and downsampling of sequencing reads suggested that results are interpretable down to 1.6 pg input and 276,000 reads (Additional file 1 ).…”

Section: Methodsmentioning

confidence: 99%

“…Patients who were being actively treated for malignancy at the time of sample collection and not positive by cytology or cytometry were excluded. Negative controls were taken from the prior metagenomics study [ 20 ], and we included patients with a microbiologically proven infection, who lacked clinical history of cancer, and who were negative for malignancy by cytology and cytometry.…”

Section: Methodsmentioning

confidence: 99%

Detection of cryptogenic malignancies from metagenomic whole genome sequencing of body fluids

Talevich

Hsu

et al. 2021

Genome Med

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Background Metagenomic next-generation sequencing (mNGS) of body fluids is an emerging approach to identify occult pathogens in undiagnosed patients. We hypothesized that metagenomic testing can be simultaneously used to detect malignant neoplasms in addition to infectious pathogens. Methods From two independent studies (n = 205), we used human data generated from a metagenomic sequencing pipeline to simultaneously screen for malignancies by copy number variation (CNV) detection. In the first case-control study, we analyzed body fluid samples (n = 124) from patients with a clinical diagnosis of either malignancy (positive cases, n = 65) or infection (negative controls, n = 59). In a second verification cohort, we analyzed a series of consecutive cases (n = 81) sent to cytology for malignancy workup that included malignant positives (n = 32), negatives (n = 18), or cases with an unclear gold standard (n = 31). Results The overall CNV test sensitivity across all studies was 87% (55 of 63) in patients with malignancies confirmed by conventional cytology and/or flow cytometry testing and 68% (23 of 34) in patients who were ultimately diagnosed with cancer but negative by conventional testing. Specificity was 100% (95% CI 95–100%) with no false positives detected in 77 negative controls. In one example, a patient hospitalized with an unknown pulmonary illness had non-diagnostic lung biopsies, while CNVs implicating a malignancy were detectable from bronchoalveolar fluid. Conclusions Metagenomic sequencing of body fluids can be used to identify undetected malignant neoplasms through copy number variation detection. This study illustrates the potential clinical utility of a single metagenomic test to uncover the cause of undiagnosed acute illnesses due to cancer or infection using the same specimen.

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“…To detect CNS infections, our group and others have reported on the utility of metagenomic next-generation sequencing (mNGS) for detecting a wide array of pathogens in CSF [4][5][6][7][8][9][10][11][12] . mNGS generates sequences from all the genetic material in a sample, and the vast majority of the sequences in CSF are human.…”

Section: Introductionmentioning

confidence: 99%

Detection of Neoplasms by Metagenomic Sequencing of Cerebrospinal Fluid

Hsu

et al. 2021

Preprint

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Importance: Malignant neoplasms of the central nervous system (CNS) are frequently not detected by cerebrospinal fluid (CSF) flow cytometry or cytology, and clinical phenotypes can overlap with inflammatory meningoencephalitis. Objective: To determine whether an existing CSF metagenomic next-generation sequencing (mNGS) assay can identify a hallmark of malignant neoplasms -aneuploidy - in difficult-to-diagnose cases of CNS malignancy. Design: Two retrospective, case-control studies included a total of 155 samples from patients with an eventual diagnosis of a CNS malignancy (n=59 patients) and controls with other CNS diseases (n=73 patients). The first study was used to evaluate test performance in positive and negative controls. The second study was used to assess the potential utility of aneuploidy detection in patients whose CSF was sent for mNGS because of suspected neuroinflammatory disease who were ultimately found to have a CNS malignancy. Setting: This is a single site study at a large tertiary care center, University of California San Francisco, that enrolled from 2014 to 2019. Participants: The test performance case-control study enrolled positive control patients with a CNS malignancy (n=47 patients) and negative controls with other neurologic diseases (n=56 patients) who had had CSF flow cytometry and/or cytology performed. The second case-control study enrolled patients with suspected neuroinflammatory disease who were ultimately diagnosed with a CNS malignancy (n=12) and other neurologic disease controls (n=17). Main Outcome(s) and Measure(s): The primary outcome measures were the performance characteristics of detecting aneuploidy in CSF by a cell-free DNA mNGS assay compared to cytology and/or flow cytometry and the tumor fraction in CSF from patients with CNS malignancies. Results: Across the two case-control studies, the overall sensitivity of the CSF mNGS assay for detecting aneuploidy in patients ultimately diagnosed with a CNS malignancy was 75% (63-96%, 95% CI), and specificity was 100% (96-100%, 95% CI). Notably, CSF mNGS detected aneuploidy in 64% of the non-diagnostic cytology and flow cytometry cases in the test performance study and in 55% of the cases with suspected neuroinflammatory disease who were ultimately diagnosed with a CNS malignancy. Of the cases in whom aneuploidy was detected, 90% had multiple chromosomal copy number variants with tumor fractions ranging from 31% to 49%. Conclusions and Relevance: Metagenomic NGS of CSF, originally designed to diagnose neurologic infections, detects evidence of CNS malignancies (i.e., aneuploidy) in cases where CSF flow cytometry and/or cytology were negative with a low risk of false positive results.

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Rapid pathogen detection by metagenomic next-generation sequencing of infected body fluids

Cited by 400 publications

References 61 publications

Application of respiratory metagenomics for COVID-19 patients on the intensive care unit to inform appropriate initial antimicrobial treatment and rapid detection of nosocomial transmission

Application of respiratory metagenomics for COVID-19 patients on the intensive care unit to inform appropriate initial antimicrobial treatment and rapid detection of nosocomial transmission

Detection of cryptogenic malignancies from metagenomic whole genome sequencing of body fluids

Detection of Neoplasms by Metagenomic Sequencing of Cerebrospinal Fluid

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