Evaluation of Metagenomic and Targeted Next-Generation Sequencing Workflows for Detection of Respiratory Pathogens from Bronchoalveolar Lavage Fluid Specimens.

Next-generation sequencing (NGS) workflows applied to bronchoalveolar lavage (BAL) fluid specimens could enhance the detection of respiratory pathogens, although optimal approaches are not defined. This study evaluated the performance of the Respiratory Pathogen ID/AMR (RPIP) kit (Illumina, Inc.) with automated Explify bioinformatic analysis (IDbyDNA, Inc.), a targeted NGS workflow enriching specific pathogen sequences and antimicrobial resistance (AMR) markers, and a complementary untargeted metagenomic workflow with in-house bioinformatic analysis. Compared to a composite clinical standard consisting of provider-ordered microbiology testing, chart review, and orthogonal testing, both workflows demonstrated similar performances. The overall agreement for the RPIP targeted workflow was 65.6% (95% confidence interval, 59.2 to 71.5%), with a positive percent agreement (PPA) of 45.9% (36.8 to 55.2%) and a negative percent agreement (NPA) of 85.7% (78.1 to 91.5%). The overall accuracy for the metagenomic workflow was 67.1% (60.9 to 72.9%), with a PPA of 56.6% (47.3 to 65.5%) and an NPA of 77.2% (68.9 to 84.1%). The approaches revealed pathogens undetected by provider-ordered testing (Ureaplasma parvum, Tropheryma whipplei, severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2], rhinovirus, and cytomegalovirus [CMV]), although not all pathogens detected by provider-ordered testing were identified by the NGS workflows. The RPIP targeted workflow required more time and reagents for library preparation but streamlined bioinformatic analysis, whereas the metagenomic assay was less demanding technically but required complex bioinformatic analysis. The results from both workflows were interpreted utilizing standardized criteria, which is necessary to avoid reporting nonpathogenic organisms. The RPIP targeted workflow identified AMR markers associated with phenotypic resistance in some bacteria but incorrectly identified blaOXA genes in Pseudomonas aeruginosa as being associated with carbapenem resistance. These workflows could serve as adjunctive testing with, but not as a replacement for, standard microbiology techniques.

Metagenomic Next-Generation Sequencing of Nasopharyngeal Specimens Collected from Confirmed and Suspect COVID-19 Patients.

Metagenomic next-generation sequencing (mNGS) offers an agnostic approach for emerging pathogen detection directly from clinical specimens. In contrast to targeted methods, mNGS also provides valuable information on the composition of the microbiome and might uncover coinfections that may associate with disease progression and impact prognosis. To evaluate the use of mNGS for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and/or other infecting pathogens, we applied direct Oxford Nanopore long-read third-generation metatranscriptomic and metagenomic sequencing. Nasopharyngeal (NP) swab specimens from 50 patients under investigation for CoV disease 2019 (COVID-19) were sequenced, and the data were analyzed by the CosmosID bioinformatics platform. Further, we characterized coinfections and the microbiome associated with a four-point severity index. SARS-CoV-2 was identified in 77.5% (31/40) of samples positive by RT-PCR, correlating with lower cycle threshold (Ct) values and fewer days from symptom onset. At the time of sampling, possible bacterial or viral coinfections were detected in 12.5% of SARS-CoV-2-positive specimens. A decrease in microbial diversity was observed among COVID-19-confirmed patients (Shannon diversity index, P = 0.0082; Chao richness estimate, P = 0.0097; Simpson diversity index, P = 0.018), and differences in microbial communities were linked to disease severity (P = 0.022). Furthermore, statistically significant shifts in the microbiome were identified among SARS-CoV-2-positive and -negative patients, in the latter of whom a higher abundance of Propionibacteriaceae (P = 0.028) and a reduction in the abundance of Corynebacterium accolens (P = 0.025) were observed. Our study corroborates the growing evidence that increased SARS-CoV-2 RNA detection from NP swabs is associated with the early stages rather than the severity of COVID-19. Further, we demonstrate that SARS-CoV-2 causes a significant change in the respiratory microbiome. This work illustrates the utility of mNGS for the detection of SARS-CoV-2, for diagnosing coinfections without viral target enrichment or amplification, and for the analysis of the respiratory microbiome.IMPORTANCE SARS-CoV-2 has presented a rapidly accelerating global public health crisis. The ability to detect and analyze viral RNA from minimally invasive patient specimens is critical to the public health response. Metagenomic next-generation sequencing (mNGS) offers an opportunity to detect SARS-CoV-2 from nasopharyngeal (NP) swabs. This approach also provides information on the composition of the respiratory microbiome and its relationship to coinfections or the presence of other organisms that may impact SARS-CoV-2 disease progression and prognosis. Here, using direct Oxford Nanopore long-read third-generation metatranscriptomic and metagenomic sequencing of NP swab specimens from 50 patients under investigation for COVID-19, we detected SARS-CoV-2 sequences by applying the CosmosID bioinformatics platform. Further, we characterized coinfections and detected a decrease in the diversity of the microbiomes in these patients. Statistically significant shifts in the microbiome were identified among COVID-19-positive and -negative patients, in the latter of whom a higher abundance of Propionibacteriaceae and a reduction in the abundance of Corynebacterium accolens were observed. Our study also corroborates the growing evidence that increased SARS-CoV-2 RNA detection from NP swabs is associated with the early stages of disease rather than with severity of disease. This work illustrates the utility of mNGS for the detection and analysis of SARS-CoV-2 from NP swabs without viral target enrichment or amplification and for the analysis of the respiratory microbiome.