Real-Time Metagenomics Next-Generation Sequencing for Diagnosing Polymicrobial Meningoencephalitis in Niger: A Case Report

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Background: Real-time metagenomics next-generation sequencing (RT-mNGS) has emerged as a high-throughput technique for directly identifying pathogen genomes from clinical samples. This study aimed to document a case of nonroutinely diagnosed meningoencephalitis using RT-mNGS in the Niger Republic. Case presentation: The patient was a 12-year-old African Nigerien female who reported fever for two weeks before she visited our hospital, as her fever had worsened with focal neurologic deficits. All other physical examinations yielded no notable findings or abnormalities. A brain abscess was first presumed in this patient and empirical treatment with ceftriaxone and metronidazole was initiated before diagnosis. Conventional bacteriological tests yielded negative results and the lesions seen on brain-computed tomography images are not specific for brain abscesses. Using real-time metagenomic next-generation sequencing (RT-mNGS), the pathogen's genomes were detected after a one-hour sequencing run, directly from leftover cerebrospinal fluid. WU polyomavirus strain W33 (GenBank accession no: GU296367.1) was identified in the patient’s sample. Haemophilus influenzae-specific reads (667 reads) were also detected, which explains the possible bacteria–DNA virus coinfection in this case. Furthermore, Achromobacter xylosoxidans (599 reads) was detected in this patient. Based on these findings, we classified this case as polymicrobial meningoencephalitis. Conclusion: This case report highlights the significance of RT-mNGS in diagnosing non-routinely detectable pathogens. RT-mNGS can rapidly and accurately characterize meningoencephalitis pathogen and might contribute to a reduction in mortality. However, the issue of sample contamination should always be addressed with high priority.

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