mSphereMolecular BiologyPeer-reviewed journal article
Amplicon and metagenomic analysis of MERS-CoV and the microbiome in patients with severe Middle East respiratory syndrome (MERS)
Waleed A. AljabriD, Muhannad AlruwailiiD, Rebekah Penrice-RandaliD, Abdulrahman F. AlrezaihiiD, Abbie HarrisoniD, Yan RyaniD, Eleanor G. BentleyiD, Benjamin JonesiD, Bader Y. AlhatlaniiD, Dayel A. AlShahrani, Zana H. MahmoodiD, Natasha Y. RickettiD, Bandar AlosaimiiD, Asif NaeemiD, Saad Saeed AlamriiD, Hadel Alsran, Maaweya E. Hamed, Xiaofeng DongiD, Abdullah Mufareh AssiriiD, Abdullah R. Alrasheed, Muaawia Ahmed HamzaiD, Miles W. CarrolliD, Matthew GemmelliD, Alistair C. DarbyiD, I’ah Donovan-BanfieldiD, , Julian A. HiscoxiD
Abstract
Middle East Respiratory Syndrome coronavirus (MERS-CoV) is a zoonotic infection that emerged in the Middle East in 2012. Symptoms range from mild to severe and include both respiratory and gastrointestinal illnesses. The virus is mainly present in camel populations with occasional spill overs into humans. The severity of infection in humans is influenced by numerous factors and similar to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) underlying health complications can play a major role. Currently, MERS-CoV and SARS-CoV-2 are co-incident in the Middle East and a rapid way is required of sequencing MERS-CoV to derive genotype information for molecular epidemiology. Additionally, complicating factors in MERS-CoV infections are co-infections that require clinical management. The ability to rapidly characterise these infections would be advantageous. To rapidly sequence MERS-CoV, we developed an amplicon-based approach coupled to Oxford Nanopore long read length sequencing. The advantage of this approach is that insertions and deletions can be identified - which are the major drivers of genotype change in coronaviruses. This and a metagenomic approach were evaluated on clinical samples from patients with MERS. The data illustrated that whole genome or near whole genome information on MERS-CoV could be rapidly obtained. This approach provided data on both consensus genomes and the presence of minor variants including deletion mutants. Whereas, the metagenomic analysis provided information of the background microbiome.
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- 22
- FWCI
- 1.27
- Field percentile
- top 16%
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