Alterations in the Nasopharyngeal Microbiome Associated with SARS-CoV-2 Infection Status and Disease Severity

ObjectivesThe COVID-19 pandemic and ensuing public health emergency has emphasized the need to study SARS-CoV-2 pathogenesis. The human microbiome has been shown to regulate the host immune system and may influence host susceptibility to viral infection, as well as disease severity. Several studies have assessed whether compositional alterations in the nasopharyngeal microbiota are associated with SARS-CoV-2 infection. However, the results of these studies were varied, and many did not account for disease severity. This study aims to examine whether compositional differences in the nasopharyngeal microbiota are associated with SARS-CoV-2 infection status and disease severity. MethodsWe performed Nanopore full-length 16S rRNA sequencing on 194 nasopharyngeal swab specimens from hospitalized and community-dwelling SARS-CoV-2-infected and uninfected individuals. Sequence data analysis was performed using the BugSeq 16S analysis pipeline. ResultsWe found significant beta (PERMANOVA p < 0.05), but not alpha (Kruskal-Wallis p > 0.05) diversity differences in the nasopharyngeal microbiota among our study groups. We identified several differentially abundant taxa associated with SARS-CoV-2 infection status and disease severity using ALDEx2. Finally, we observed a trend towards higher abundance of Enterobacteriaceae in specimens from hospitalized SARS-CoV-2-infected patients. ConclusionsThis study identified several alterations in the nasopharyngeal microbiome associated with SARS-CoV-2 infection status and disease severity. Understanding the role of the microbiome in infection susceptibility and severity may open new avenues of research for disease prevention and treatment.

BugSplit: highly accurate taxonomic binning of metagenomic assemblies enables genome-resolved metagenomics

A large gap remains between sequencing a microbial community and characterizing all of the organisms inside of it. Here we develop a novel method to taxonomically bin metagenomic assemblies through alignment of contigs against a reference database. We show that this workflow, BugSplit, bins metagenome-assembled contigs to species with a 33% absolute improvement in F1-score when compared to alternative tools. We perform nanopore mNGS on patients with COVID-19, and using a reference database predating COVID-19, demonstrate that BugSplits taxonomic binning enables sensitive and specific detection of a novel coronavirus not possible with other approaches. When applied to nanopore mNGS data from cases of Klebsiella pneumoniae and Neisseria gonorrhoeae infection, BugSplits taxonomic binning accurately separates pathogen sequences from those of the host and microbiota, and unlocks the possibility of sequence typing, in silico serotyping, and antimicrobial resistance prediction of each organism within a sample. BugSplit is available at https://bugseq.com/academic.

Nanopore Metagenomic Sequencing for Detection and Characterization of SARS-CoV-2 in Clinical Samples

The COVID-19 pandemic has underscored the need for rapid novel diagnostic strategies to detect and characterize pathogens from clinical specimens. The MinION sequencing device allows for rapid, cost-effective, high-throughput sequencing; useful features for translation to clinical laboratory settings. Metagenomic Next-Generation Sequencing (mNGS) approaches provide the opportunity to examine the entire genomic material of a sample; allowing for detection of emerging and clinically relevant pathogens that may be missed in targeted assays. Here we present a pilot study on the performance of Sequence-Independent Single Primer Amplification (SISPA) to amplify RNA randomly for the detection and characterization of SARS-CoV-2. We designed a classifier that corrects for barcode crosstalk between specimens. Our assay yielded 100% specificity overall and 95.2% sensitivity for specimens with a RT-qPCR cycle threshold value less than 30. We assembled 10 complete (>95% coverage at 20x depth), and one near-complete (>80% coverage at 20x depth) genomes from 20 specimens that were classified as positive by mNGS. We characterized these genomes through phylogenetic analysis and found that 10/11 specimens from British Columbia had a closest relative to another British Columbian specimen. Of five samples that we had both assembled genomes, as well as Variant of Concern (VOC) PCR results, we found 100% concordance between these results. Additionally, our assay was able to distinguish between the Alpha and Gamma variants, which was not possible with our VOC PCR technique. This study supports future work examining the broader feasibility of SISPA as a diagnostic strategy for the detection and characterization of viral pathogens.