A Refined, Controlled 16S rRNA Gene Sequencing Approach Reveals Limited Detection of Cerebrospinal Fluid Microbiota in Children with Bacterial Meningitis

Microbiol Spectr. 2023 Jun 15;11(3):e0036123. doi: 10.1128/spectrum.00361-23. Epub 2023 May 4.

Abstract

Advances in both laboratory and computational components of high-throughput 16S amplicon sequencing (16S HTS) have markedly increased its sensitivity and specificity. Additionally, these refinements have better delineated the limits of sensitivity, and contributions of contamination to these limits, for 16S HTS that are particularly relevant for samples with low bacterial loads, such as human cerebrospinal fluid (CSF). The objectives of this work were to (i) optimize the performance of 16S HTS in CSF samples with low bacterial loads by defining and addressing potential sources of error, and (ii) perform refined 16S HTS on CSF samples from children diagnosed with bacterial meningitis and compare results with those from microbiological cultures. Several bench and computational approaches were taken to address potential sources of error for low bacterial load samples. We compared DNA yields and sequencing results after applying three different DNA extraction approaches to an artificially constructed mock-bacterial community. We also compared two postsequencing computational contaminant removal strategies, decontam R and full contaminant sequence removal. All three extraction techniques followed by decontam R yielded similar results for the mock community. We then applied these methods to 22 CSF samples from children diagnosed with meningitis, which has low bacterial loads relative to other clinical infection samples. The refined 16S HTS pipelines identified the cultured bacterial genus as the dominant organism for only 3 of these samples. We found that all three DNA extraction techniques followed by decontam R generated similar DNA yields for mock communities at the low bacterial loads representative of CSF samples. However, the limits of detection imposed by reagent contaminants and methodologic bias precluded the accurate detection of bacteria in CSF from children with culture-confirmed meningitis using these approaches, despite rigorous controls and sophisticated computational approaches. Although we did not find current DNA-based diagnostics to be useful for pediatric meningitis samples, the utility of these methods for CSF shunt infection remains undefined. Future advances in sample processing methods to minimize or eliminate contamination will be required to improve the sensitivity and specificity of these methods for pediatric meningitis. IMPORTANCE Advances in both laboratory and computational components of high-throughput 16S amplicon sequencing (16S HTS) have markedly increased its sensitivity and specificity. These refinements have better delineated the limits of sensitivity, and contributions of contamination to these limits, for 16S HTS that are particularly relevant for samples with low bacterial loads such as human cerebrospinal fluid (CSF). The objectives of this work were to (i) optimize the performance of 16S HTS in CSF samples by defining and addressing potential sources of error, and (ii) perform refined 16S HTS on CSF samples from children diagnosed with bacterial meningitis and compare results with those from microbiological cultures. We found that the limits of detection imposed by reagent contaminants and methodologic bias precluded the accurate detection of bacteria in CSF from children with culture-confirmed meningitis using these approaches, despite rigorous controls and sophisticated computational approaches.

Keywords: bacterial meningitis; cerebrospinal fluid; high-throughput sequencing.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Bacteria / genetics
  • Cerebrospinal Fluid / microbiology
  • Child
  • DNA, Bacterial / genetics
  • Genes, rRNA
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Meningitis, Bacterial* / diagnosis
  • Meningitis, Bacterial* / microbiology
  • Microbiota*
  • Polymerase Chain Reaction / methods
  • RNA, Ribosomal, 16S / genetics

Substances

  • RNA, Ribosomal, 16S
  • DNA, Bacterial