Exploration of the lung-associated virome utilising shotgun metagenomics data

TALYA Conradie

The virome is a subpopulation of the microbiota that colonise the human body, encompassing eukaryotic and prokaryotic viruses, which include bacteriophages. The lung virome is an understudied portion of the human microbiome, with estimations suggesting that up to 95% of the virome remains uncharacterised (1-7). Because of its public health significance, characterising the viral component of the microbiome is gaining increasing attention. The current state of lung virome literature is concentrated in identification of known viruses in disease states. With increases in lung virome studies, current viral databases are not comprehensive enough to characterise all the putative viral sequences generated. The present study aims to catalogue the virome associated with the human respiratory tract by reanalysing publicly available data using a newly-developed bioinformatic method, pipEline for Viral assEmbly and chaRactEriSaTion (EVEREST) aimed at capturing and taxonomically classifying reads of viral origin. Virome studies utilising shotgun metagenomics and lung-attributed samples were gathered from the public databases PubMed, NCBI Sequence Read Archive (SRA), and European Nucleotide Archive European Molecular Biology Laboratory European Bioinformatics Institute (ENA EMBL-EBI) (n=85). Those BioProjects with publicly available sequence data were identified (n=43), and downloaded from NCBI SRA and ENA. A total of 868 samples from 30 BioProjects was then inputted into EVEREST (https://agudeloromero.github.io/EVEREST/), with 201 samples (23.2%) from 16 BioProjects producing new viral assemblies. Complete and high-quality contigs were assessed for genomic characterisation and taxonomic classification of known and unknown viruses using nucleotide and amino acid databases. The resulting pipeline output includes contig length, GC content, lowest common ancestors, nearest taxonomic match, and probability of virulent or temperate bacteriophage. Further analysis includes insight into alpha and beta diversity of the lung virome, predicted hosts, and viral clustering. These results show the application of this novel bioinformatic pipeline for viral identification and discovery, which facilitates understanding of virus-host interactions within the pulmonary system. This study highlights the rich value in publicly available sequence data from metagenome studies.

Exploration of the lung-associated virome utilising shotgun metagenomics data

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