Identification of missed respiratory viruses by metagenomic sequencing of clinical respiratory samples from Kenya

Autor: Phan, My V. T., Agoti, Charles N., Munywoki, Patrick K., Otieno, Grieven Paul, Ngama, Mwanajuma, Kellam, Paul, Cotton, Matthew, Nokes, D. James
Jazyk: angličtina
Rok vydání: 2022
Předmět:
ISSN: 2045-2322
Popis: Pneumonia remains a major cause of mortality and morbidity. Most molecular diagnoses of viruses rely on polymerase chain reaction (PCR) assays that however can fail due to primer mismatch. We investigated the performance of routine virus diagnostics in Kilifi, Kenya, using random-primed viral next generation sequencing (viral NGS) on respiratory samples which tested negative for the common viral respiratory pathogens by a local standard diagnostic panel. Among 95 hospitalised pneumonia patients and 95 household-cohort individuals, analysis of viral NGS identified at least one respiratory-associated virus in 35 (37%) and 23 (24%) samples, respectively. The majority (66%; 42/64) belonged to the Picornaviridae family. The NGS data analysis identified a number of viruses that were missed by the diagnostic panel (rhinovirus, human metapneumovirus, respiratory syncytial virus and parainfluenza virus), and these failures could be attributed to PCR primer/probe binding site mismatches. Unexpected viruses identified included parvovirus B19, enterovirus D68, coxsackievirus A16 and A24 and rubella virus. The regular application of such viral NGS could help evaluate assay performance, identify molecular causes of missed diagnoses and reveal gaps in the respiratory virus set used for local screening assays. The results can provide actionable information to improve the local pneumonia diagnostics and reveal locally important viral pathogens.\ud \ud
Databáze: OpenAIRE
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