bioRxivGenomicsPreprint
Etiology of fever in Ugandan children: identification of microbial pathogens using metagenomic next-generation sequencing and IDseq, a platform for unbiased metagenomic analysis
Akshaya RameshiD, Sara Nakielny, Jennifer Hsu, Mary KyohereiD, Oswald Byaruhanga, Charles F. A. de BourcyiD, Rebecca Egger, Boris DimitroviD, Yun-Fang Juan, Jonathan SheuiD, James WangiD, Katrina KalantariD, Charles LangelieriD, Theodore RueliD, Arthur MpimbazaiD, Michael R. WilsoniD, Philip Joseph RosenthaliD, Joseph L. DeRisiiD
- Citations
- 7
Abstract
BackgroundFebrile illness is a major burden in African children, and non-malarial causes of fever are uncertain. We built and employed IDseq, a cloud-based, open access, bioinformatics platform and service to identify microbes from metagenomic next-generation sequencing of tissue samples. In this pilot study, we evaluated blood, nasopharyngeal, and stool specimens from 94 children (aged 2-54 months) with febrile illness admitted to Tororo District Hospital, Uganda.\n\nResultsThe most common pathogens identified were Plasmodium falciparum (51.1% of samples) and parvovirus B19 (4.4%) from blood; human rhinoviruses A and C (40%), respiratory syncytial virus (10%), and human herpesvirus 5 (10%) from nasopharyngeal swabs; and rotavirus A (50% of those with diarrhea) from stool. Among other potential pathogens, we identified one novel orthobunyavirus, tentatively named Nyangole virus, from the blood of a child diagnosed with malaria and pneumonia, and Bwamba orthobunyavirus in the nasopharynx of a child with rash and sepsis. We also identified two novel human rhinovirus C species.\n\nConclusionsThis exploratory pilot study demonstrates the utility of mNGS and the IDseq platform for defining the molecular landscape of febrile infectious diseases in resource limited areas. These methods, supported by a robust data analysis and sharing platform, offer a new tool for the surveillance, diagnosis, and ultimately treatment and prevention of infectious diseases.
- organism: human
- assay: metagenomics
- research focus: differential expression
- research focus: database / resource
- research focus: benchmarking
- approach: statistical model
- approach: experimental assay
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