Evidence map›Paper›PMID 29976594›Full record

ArticleJournal of clinical microbiology2018

Development and Optimization of Metagenomic Next-Generation Sequencing Methods for Cerebrospinal Fluid Diagnostics.

Patricia J Simner, Heather B Miller, Florian P Breitwieser, Gabriel Pinilla Monsalve, Carlos A Pardo, Steven L Salzberg, Cynthia L Sears, David L Thomas, Charles G Eberhart, Karen C Carroll

Abstract readComparative Study
In one paragraph

Article in Journal of clinical microbiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

56 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Patricia J SimnerDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA psimner1@jhmi.edu.
Heather B MillerDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Florian P BreitwieserCenter for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Gabriel Pinilla MonsalveDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Carlos A PardoDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Steven L SalzbergCenter for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Cynthia L SearsDepartment of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
David L ThomasDepartment of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Charles G EberhartDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Karen C CarrollDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Funding

Bioinformatics Software for Analyzing Microbial GenomesR01GM083873 · NIGMS · UNIV OF MARYLAND, COLLEGE PARK · PI SALZBERG, STEVEN L. · 2008 to 2017
$2.1M
NIGMS NIH HHS R01 GM083873
6 · The paper itself

Abstract

The purpose of this study was to develop and optimize different processing, extraction, amplification, and sequencing methods for metagenomic next-generation sequencing (mNGS) of cerebrospinal fluid (CSF) specimens. We applied mNGS to 10 CSF samples with known standard-of-care testing (SoC) results (8 positive and 2 negative). Each sample was subjected to nine different methods by varying the sample processing protocols (supernatant, pellet, neat CSF), sample pretreatment (with or without bead beating), and the requirement of nucleic acid amplification steps using DNA sequencing (DNASeq) (with or without whole-genome amplification [WGA]) and RNA sequencing (RNASeq) methods. Negative extraction controls (NECs) were used for each method variation (4/CSF sample). Host depletion (HD) was performed on a subset of samples. We correctly determined the pathogen in 7 of 8 positive samples by mNGS compared to SoC. The two negative samples were correctly interpreted as negative. The processing protocol applied to neat CSF specimens was found to be the most successful technique for all pathogen types. While bead beating introduced bias, we found it increased the detection yield of certain organism groups. WGA prior to DNASeq was beneficial for defining pathogens at the positive threshold, and a combined DNA and RNA approach yielded results with a higher confidence when detected by both methods. HD was required for detection of a low-level-positive enterovirus sample. We demonstrate that NECs are required for interpretation of these complex results and that it is important to understand the common contaminants introduced during mNGS. Optimizing mNGS requires the use of a combination of techniques to achieve the most sensitive, agnostic approach that nonetheless may be less sensitive than SoC tools.

Indexed as

BacteriaCerebrospinal FluidClinical Laboratory TechniquesComputational BiologyFungiHigh-Throughput Nucleotide SequencingHumansMetagenomicsSensitivity and SpecificitySequence Analysis, DNASpecimen HandlingVirusesCSFmetagenomicsnext-generation sequencing

Identifiers

PMID29976594
PMCPMC6113476

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.