PT - JOURNAL ARTICLE AU - Senjuti Saha, PhD AU - Akshaya Ramesh, PhD AU - Katrina Kalantar, PhD AU - Roly Malaker, MS AU - Md Hasanuzzaman, MS AU - Lillian M. Khan, BS AU - Madeline Y Mayday, BS AU - M S I Sajib, MS AU - Lucy M. Li, PhD AU - Charles Langelier, MD,PhD AU - Hafizur Rahman, BS AU - Emily D. Crawford, PhD AU - Cristina M. Tato, PhD AU - Maksuda Islam, BA AU - Yun-Fang Juan, BS AU - Charles de Bourcy, PhD AU - Boris Dimitrov, BS AU - James Wang, BS AU - Jennifer Tang, BA AU - Jonathan Sheu, BS AU - Rebecca Egger, BS AU - Tiago Rodrigues De Carvalho, PhD AU - Michael R. Wilson, MD,MAS AU - Samir K Saha, PhD AU - Joseph L DeRisi, PhD TI - Unbiased metagenomic sequencing for pediatric meningitis in Bangladesh reveals neuroinvasive Chikungunya virus outbreak and other unrealized pathogens AID - 10.1101/579532 DP - 2019 Jan 01 TA - bioRxiv PG - 579532 4099 - http://biorxiv.org/content/early/2019/03/15/579532.short 4100 - http://biorxiv.org/content/early/2019/03/15/579532.full AB - The disease burden due to meningitis in low and middle-income countries remains significant and failure to determine an etiology impedes appropriate treatment for patients and evidence-based policy decisions for populations. Broad-range pathogen surveillance using metagenomic next-generation sequencing (mNGS) of RNA isolated from cerebral spinal fluid (CSF) provides an unbiased assessment for possible infectious etiologies. In this study, our objective was to use mNGS to identify etiologies of pediatric meningitis in Bangladesh.We conducted a retrospective case-control mNGS study on CSF from patients with known neurologic infections (n=36), idiopathic meningitis (n=25), without infection (n=30) and six environmental samples collected between 2012-2018. Using an open-access, cloud-based bioinformatics pipeline (IDseq) and machine learning, we identified potential pathogens which were confirmed through qPCR and Sanger sequencing. These cases were followed-up through phone/home-visits. The CSF samples were collected from children with WHO-defined meningeal signs during prospective meningitis surveillance at the largest pediatric referral hospital in Bangladesh.The 91 participants (42% female) ranged in age from 0-160 months (median: 9 months). In samples with known infectious causes of meningitis and without infections (n=66), there was 83% concordance between mNGS and conventional testing. In idiopathic cases (n=25), mNGS identified a potential etiology in 40% (n=10), including bacterial and viral pathogens. There were three instances of neuroinvasive Chikungunya virus (CHIKV). The CHIKV genomes were >99% identical to each other and to a Bangladeshi strain only previously recognized to cause systemic illness in 2017. CHIKV qPCR of all remaining stored CSF samples from children who presented with idiopathic meningitis in 2017 at the same hospital (n=472) revealed 17 additional CHIKV meningitis cases. Orthogonal molecular confirmation of each mNGS-identified infection, case-based clinical data, and follow-up of patients substantiated the key findings.Using mNGS, we obtained a microbiological diagnosis for 40% of idiopathic meningitis cases and identified a previous unappreciated pediatric CHIKV meningitis outbreak. Case-control CSF mNGS surveys can complement conventional diagnostic methods to identify etiologies of meningitis and facilitate informed policy decisions.