Genome MedicineGenomicsPeer-reviewed journal article
Clinical metagenomic identification of Balamuthia mandrillaris encephalitis and assembly of the draft genome: the critical need for reference strain sequencing
Alexander L Greninger, Kevin MessacariD, Thelma Dunnebacke-Dixon, Samia N Naccache, Scot FedermaniD, Jerome Bouquet, David Mirsky, Yosuke Nomura, Shigeo Yagi, Carol Glaser, Michael Vollmer, Craig A. Press, Bette K Klenschmidt-DeMasters, Samuel R Dominguez, Charles Y Chiu
Abstract
Primary amoebic meningoencephalitis (PAM) is a rare, often lethal cause of encephalitis, for which early diagnosis and prompt initiation of combination antimicrobials may improve clinical outcomes. In this study, we present the first draft assembly of the Balamuthia mandrillaris genome recovered from a rare survivor of PAM, in total comprising 49 Mb of sequence. Comparative analysis of the mitochondrial genome and high-copy number genes from 6 additional Balamuthia mandrillaris strains demonstrated remarkable sequence variation, with the closest homologs corresponding to other amoebae, hydroids, algae, slime molds, and peat moss. We also describe the use of unbiased metagenomic next-generation sequencing (NGS) and SURPI bioinformatics analysis to diagnose an ultimately fatal case of Balamuthia mandrillaris encephalitis in a 15-year old girl. Real-time NGS testing of a hospital day 6 CSF sample detected Balamuthia on the basis of high-quality hits to 16S and 18S ribosomal RNA sequences present in the National Center for Biotechnology Information (NCBI) nt reference database. Retrospective analysis of a day 1 CSF sample revealed that more timely identification of Balamuthia by metagenomic NGS, potentially resulting in a better outcome, would have required availability of the complete genome sequence. These results underscore the diverse evolutionary origins underpinning this eukaryotic pathogen, and the critical importance of whole-genome reference sequences for microbial detection by NGS.
- assay: metagenomics
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: benchmarking
- research focus: database / resource
- approach: experimental assay
- approach: statistical model
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