Deploying Metagenomics to Characterize Microbial Pathogens During Outbreak of Acute Febrile Illness Among Children in Tanzania

Outbreaks of infectious diseases contribute significantly to morbidity and mortality in resource-limited settings, yet the capacity to identify their etiology remains limited. We aimed to characterize microbes and antimicrobial resistance (AMR) genes in Tanzanian children affected by an acute febrile illness (AFI) outbreak using metagenomic next-generation sequencing (mNGS). A cross-sectional study was conducted on archived blood samples from children who presented with AFI between 2018 and 2019. Total nucleic acids were extracted from 200 µL of blood, and complementary DNA (cDNA), along with enriched pathogenic DNA, was sequenced using the Illumina MiSeq platform. mNGS data were analyzed using CZ-ID Illumina mNGS bioinformatics pipeline v7.0. Results were obtained from 25 participants (mean age: 11.6 years; SD ± 5), of whom 36% had a moderate to high-grade fever. The following five potential microbial causes of AFI were identified: <i>Escherichia coli</i> (n = 19), <i>Paraclostridium bifermentans</i> (n = 2), <i>Pegivirus C</i> (n = 2), <i>Shigella flexneri</i> (n = 1) and <i>Pseudomonas fluorescens</i> (n = 1), with <i>E. coli</i> being the most prevalent. Twelve AMR genes were detected, including <i>mdtC</i>, <i>acrF</i>, <i>mdtF</i>, and <i>emrB. E. coli</i> harbored most of the AMR genes previously associated with resistance to commonly used antibiotics. mNGS offers a promising complementary approach to conventional diagnostics for identifying pathogens and AMR profiles in vulnerable populations.