SMART-RNA-Metavirome: a practical RNA metavirome platform compatible with high-throughput sequencing of both short and long reads.

Abstract

BACKGROUND: The RNA virosphere's extensive diversity and its role in emerging infectious diseases underscore the importance of non-targeted sequencing for identifying unknown or rare pathogens, including co-infections. However, enriching low-abundance viral sequences in RNA metaviromics, particularly in the preparation of cDNA libraries and their compatibility with next-generation sequencing (NGS) and third-generation sequencing (TGS), remains challenging. Therefore, our objective is to develop and systematically assess a practical RNA metavirome methodology specifically tailored for the enrichment of low-abundance viral sequences within samples. METHODS: We developed the SMART-RNA-Metavirome platform, integrating SMART-9n library preparation with NGS and TGS technologies. Total RNA was extracted from two field-collected wild Aedes albopictus pools, along with one laboratory-infected Ae. albopictus pool harboring dengue virus (DENV). This RNA was subjected to reverse transcription using both this optimized protocol and random primer-based methods, followed by high-throughput sequencing on Illumina, Oxford Nanopore, and QitanTech Nanopore technologies. Welch's t-test was employed for comparative analysis of the subsequent RNA metavirome data, specifically to evaluate differences in viral species composition and abundance of viral reads between experimental groups. Furthermore, the effectiveness of this platform was systematically validated via RT-qPCR and SMART-RNA-Metavirome-based Oxford Nanopore sequencing across multiple sample types, including mosquito specimens from DENV-infected Ae. albopictus, serum samples from dengue patients and viral isolates of Japanese encephalitis virus (JEV) and Zika virus (ZIKV). RESULTS: The SMART-RNA-Metavirome platform has been systematically validated to excel in enriching the composition and diversity of the RNA virome (P = 0.04), providing sufficient coverage for the complete reconstruction of viral genomes. When employed in the detection of DENV-infected Ae. albopictus, clinical serum samples, and viral isolates of JEV and ZIKV, this technique exhibits a robust correlation with RT-qPCR (r2 > 0.95). Notably, it demonstrates exceptional sensitivity, ensuring sufficient coverage even in samples of DENV-infected Ae. albopictus with a Ct-value of 35.3, attaining an impressive 99.88% genome coverage. Furthermore, this platform possesses the capability to identify virus species and determine their serotypes. CONCLUSIONS: In our study, the SMART-RNA-Metavirome platform outperforms traditional methods, enriching RNA virome composition and diversity, enabling practical compatibility with both NGS and TGS technologies. It demonstrates significant proficiency in detecting both known and unknown arboviruses, even in low-titer samples such as those from wild mosquitoes and clinical sera. This platform facilitates comprehensive monitoring, risk assessment, and early warning of RNA virus transmissions, enhancing our understanding of RNA virome diversity and ecological patterns.