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

Abstract

We developed a metagenomic next-generation sequencing (mNGS) test using cell-free DNA from body fluids to identify pathogens. The performance of mNGS testing of 182 body fluids from 160 patients with acute illness was evaluated using two sequencing platforms in comparison to microbiological testing using culture, 16S bacterial PCR and/or 28S-internal transcribed ribosomal gene spacer (28S-ITS) fungal PCR. Test sensitivity and specificity of detection were 79 and 91% for bacteria and 91 and 89% for fungi, respectively, by Illumina sequencing; and 75 and 81% for bacteria and 91 and 100% for fungi, respectively, by nanopore sequencing. In a case series of 12 patients with culture/PCR-negative body fluids but for whom an infectious diagnosis was ultimately established, seven (58%) were mNGS positive. Real-time computational analysis enabled pathogen identification by nanopore sequencing in a median 50-min sequencing and 6-h sample-to-answer time. Rapid mNGS testing is a promising tool for diagnosis of unknown infections from body fluids.

Figures

Figure 1.

(A) Schematic of mNGS body fluid analysis workflow. The composite gold standard consisted of aggregated available results from bacterial and fungal cultures, 16S PCR, confirmatory digital PCR and Sanger sequencing, and clinical adjudication. (B) Timing for mNGS testing relative to culture. Whereas culture-based pathogen identification can take days to weeks, mNGS testing has a 5-24 hr overall turnaround time. (C) Analysis workflow for the 92 total body fluid samples in the study. 87 total samples were included in the accuracy assessment and 5 samples collected from patients with a clinical diagnosis of infection but negative microbiological testing was included for prospective mNGS analysis. The pie chart shows the sample type of all 92 body fluids. **Other body fluids are: Vitreous Fluid, Perihepatic Fluid, Surgical Swab, Subgaleal Fluid, Heel Fluid Swab, Peri-graft Fluid Swab, Anterior Mediastinal Fluid, Chest Fluid, Chest Mass Fluid, Wound Swab.

Figure 2.. Accuracy of mNGS testing accuracy and relative pathogen burden in body fluid samples.

(A) ROC curves of Illumina mNGS performance. Plotted are mNGS test sensitivities and specificities at normalized RPM (nRPM) threshold values ranging from 0.1 to 100. ROC curves of Illumina training and validation dataset performance are plotted relative to clinical and composite gold standards. In all panels, the displayed n represents counts used for the contingency table as described in the methods section and shown in Table S11. (B) ROC curves of nanopore mNGS performance. (C) ROC curves comparing Illumina and nanopore performance. ROC curves of training and validation dataset performance are plotted relative to composite gold standard testing alone. (D) ROC curves stratified by body fluid type. Plotted is the performance of the combined Illumina training and validation datasets relative to composite gold standard testing. Plasma is not counted as a body fluid in panels D and F, but is plotted as a separate set. (E) Comparison of Illumina with nanopore sequencing. The yield of pathogen-specific reads based on a normalized RPM (nRPM) metric is linearly correlated and comparable between nanopore and Illumina sequencing. (F) Relative pathogen burden in body fluids, stratified by body fluid and organism type. The burden of pathogen cfDNA in body fluid samples is estimated using calculated nRPM values. Based on Illumina data, bacterial cfDNA in plasma was significantly lower on average than in local body fluids (p=0.011), and pathogen cfDNA in body fluids was significantly higher for bacteria than fungi (p=0.014).

Figure 3.. Comparison of mNGS with 16S PCR for 8 culture-negative body fluids.

Krona plots depict genus and species levels of all sequence-matched bacterial reads. (A) Concordant cases (n=6). (B) Discordant cases (n=2). In Case S31 (left), pleural fluids from a pediatric, immunosuppressed patient with necrotizing pneumonia (chest x-ray) were negative by culture. 16S PCR was positive for Streptococcus mitis group, an organism that would rarely be the cause of a necrotizing pneumonia. In contrast, mNGS sequencing revealed 83% of the bacterial reads to be specific for Klebsiella pneumoniae and no reads detected from Streptococcus mitis, a result that was orthogonally confirmed. In case S88 (right), CSF obtained before removal of an infected deep brain stimulator (DBS) was negative by culture and 16S PCR. However, culture of the surgically extracted DBS was positive for Klebsiella aerogenes, as was mNGS sequencing of the CSF (86% of the sequence-matched bacterial reads were specific for Klebsiella aerogenes). CT imaging of the brain revealed that the infected DBS was located upstream of the lumbar puncture site (drawing and axial slice), explaining the presence of trace pathogen cfDNA in CSF that was detectable by mNGS. For both cases S31 and S88, nanopore sequencing was able to detect Klebsiella pneumoniae and Klebsiella aerogenes within 3 minutes after start of sequencing, respectively (xy scatter plots with the dotted line showing the 3-read threshold). Abbreviations: BAL, bronchoalveolar lavage fluid; CT, computed tomography).

Figure 4.. Comparison of relative pathogen burden in paired body fluid and plasma samples.

(A) Schematic showing concurrent collection of blood plasma and body fluid samples from the same patient. (B) Bar plot of the normalized RPM corresponding to 9 organisms in paired body fluid and plasma samples from 7 patients. The vertical lines show the thresholds used for a positive bacterial or fungal detection. The checkboxes denote organisms that were not identified by conventional microbiological testing (culture and/or 16S PCR) but that were orthogonally confirmed by dPCR, serology, and/or clinical adjudication (Supplemental Materials, “Case Vignettes”).