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Unbiased Metagenomic Sequencing for Pediatric Meningitis in Bangladesh Reveals Neuroinvasive Chikungunya Virus Outbreak and Other Unrealized Pathogens

The burden of meningitis in low-and-middle-income countries remains significant, but the infectious causes remain largely unknown, impeding institution of evidence-based treatment and prevention decisions. We conducted a validation and application study of unbiased metagenomic next-generation sequen...

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Detalles Bibliográficos
Autores principales: Saha, Senjuti, Ramesh, Akshaya, Kalantar, Katrina, Malaker, Roly, Hasanuzzaman, Md, Khan, Lillian M., Mayday, Madeline Y., Sajib, M. S. I., Li, Lucy M., Langelier, Charles, Rahman, Hafizur, Crawford, Emily D., Tato, Cristina M., Islam, Maksuda, Juan, Yun-Fang, de Bourcy, Charles, Dimitrov, Boris, Wang, James, Tang, Jennifer, Sheu, Jonathan, Egger, Rebecca, De Carvalho, Tiago Rodrigues, Wilson, Michael R., Saha, Samir K., DeRisi, Joseph L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6918088/
https://www.ncbi.nlm.nih.gov/pubmed/31848287
http://dx.doi.org/10.1128/mBio.02877-19
Descripción
Sumario:The burden of meningitis in low-and-middle-income countries remains significant, but the infectious causes remain largely unknown, impeding institution of evidence-based treatment and prevention decisions. We conducted a validation and application study of unbiased metagenomic next-generation sequencing (mNGS) to elucidate etiologies of meningitis in Bangladesh. This RNA mNGS study was performed on cerebrospinal fluid (CSF) specimens from patients admitted in the largest pediatric hospital, a World Health Organization sentinel site, with known neurologic infections (n = 36), with idiopathic meningitis (n = 25), and with no infection (n = 30), and six environmental samples, collected between 2012 and 2018. We used the IDseq bioinformatics pipeline and machine learning to identify potentially pathogenic microbes, which we then confirmed orthogonally and followed up through phone/home visits. In samples with known etiology and without infections, there was 83% concordance between mNGS and conventional testing. In idiopathic cases, mNGS identified a potential bacterial or viral etiology in 40%. There were three instances of neuroinvasive Chikungunya virus (CHIKV), whose genomes were >99% identical to each other and to a Bangladeshi strain only previously recognized to cause febrile illness in 2017. CHIKV-specific qPCR of all remaining stored CSF samples from children who presented with idiopathic meningitis in 2017 (n = 472) revealed 17 additional CHIKV meningitis cases, exposing an unrecognized meningitis outbreak. Orthogonal molecular confirmation, case-based clinical data, and patient follow-up substantiated the findings. Case-control CSF mNGS surveys can complement conventional diagnostic methods to identify etiologies of meningitis, conduct surveillance, and predict outbreaks. The improved patient- and population-level data can inform evidence-based policy decisions.