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Development and Optimization of Metagenomic Next-Generation Sequencing Methods for Cerebrospinal Fluid Diagnostics
Patricia J Simner1, Heather B Miller2, Florian P Breitwieser3
1Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA psimner1@jhmi.edu.
Journal of Clinical Microbiology
|July 7, 2018
Summary
Optimizing metagenomic next-generation sequencing (mNGS) for cerebrospinal fluid (CSF) involves refining processing, extraction, and sequencing methods. Neat CSF processing and combined DNA/RNA sequencing improved pathogen detection accuracy compared to standard methods.
Area of Science:
- Clinical microbiology
- Genomics
- Infectious disease diagnostics
Background:
- Metagenomic next-generation sequencing (mNGS) offers a culture-independent method for pathogen detection in clinical specimens.
- Cerebrospinal fluid (CSF) analysis is critical for diagnosing central nervous system infections.
- Optimization of mNGS protocols is essential for improving sensitivity and accuracy in CSF diagnostics.
Purpose of the Study:
- To develop and optimize various processing, extraction, amplification, and sequencing methods for mNGS of CSF specimens.
- To evaluate the performance of different mNGS approaches against known standard-of-care (SoC) testing results.
- To identify the most effective protocols for sensitive and agnostic pathogen detection in CSF.
Main Methods:
- Applied mNGS to 10 CSF samples (8 positive, 2 negative) using nine distinct method variations.
- Varied sample processing (supernatant, pellet, neat CSF), pretreatment (bead beating), and nucleic acid amplification (DNA sequencing with/without whole-genome amplification [WGA], RNA sequencing [RNASeq]).
- Utilized negative extraction controls (NECs) and performed host depletion (HD) on a subset of samples.
Main Results:
- mNGS correctly identified pathogens in 7 of 8 positive samples and both negative samples compared to SoC.
- Processing neat CSF specimens proved most successful across all pathogen types.
- Whole-genome amplification (WGA) aided pathogen definition, combined DNA/RNA sequencing increased confidence, and host depletion (HD) was crucial for low-level detection.
Conclusions:
- Optimized mNGS protocols, particularly neat CSF processing and combined DNA/RNA sequencing, enhance pathogen detection in CSF.
- Understanding common contaminants and utilizing NECs are critical for accurate mNGS interpretation.
- While mNGS shows promise, careful optimization is needed to match or exceed the sensitivity of SoC tools for all scenarios.
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