Validation of an Automated, End-to-End Metagenomic Sequencing Assay for Agnostic Detection of Respiratory Viruses.

Background: Current molecular diagnostics are limited in the number and type of detectable pathogens. Metagenomic next-generation sequencing (mNGS) is an emerging, and increasingly feasible, pathogen-agnostic diagnostic approach. Translational barriers prohibit the widespread adoption of this technology in clinical laboratories.

Agnostic Sequencing for Detection of Viral Pathogens.

The advent of next-generation sequencing (NGS) technologies has expanded our ability to detect and analyze microbial genomes and has yielded novel molecular approaches for infectious disease diagnostics. While several targeted multiplex PCR and NGS-based assays have been widely used in public health settings in recent years, these targeted approaches are limited in that they still rely on knowledge of a pathogen's genome, and an untargeted or unknown pathogen will not be detected. Recent public health crises have emphasized the need to prepare for a wide and rapid deployment of an agnostic diagnostic assay at the start of an outbreak to ensure an effective response to emerging viral pathogens.

Alterations in the nasopharyngeal microbiome associated with SARS-CoV-2 infection status and disease severity.

Objectives: The 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.

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

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.

Nanopore metagenomic sequencing for detection and characterization of SARS-CoV-2 in clinical samples.

Objectives: The COVID-19 pandemic has underscored the need for rapid novel diagnostic strategies. Metagenomic Next-Generation Sequencing (mNGS) may allow for the detection of pathogens that can be missed in targeted assays. The goal of this study was to assess the performance of nanopore-based Sequence-Independent Single Primer Amplification (SISPA) for the detection and characterization of SARS-CoV-2.

A Molecular Analysis of Microalgae from Around the Globe to Revise Raphidonema (Trebouxiophyceae, Chlorophyta).

We isolated five microalgal strains from alpine snow near Vancouver, Canada, which display morphological features suggestive of the genera Koliella and Raphidonema. Due to variations in cell size and shape, we could not make a clear delimitation based on morphology. We proceeded to a molecular analysis and included 22 strains from the CCCryo culture collection, previously identified as members of four closely related genera: Raphidonema, Koliella, Stichococcus, and Pseudochlorella.