Abstract

Metagenomic sequence data can be used to detect the presence of infectious viruses and bacteria, but normal microbial flora make this process challenging. We re-analyzed metagenomic RNA sequence data collected during a recent outbreak of acute flaccid myelitis (AFM), caused in some cases by infection with enterovirus D68. We found that among the patients whose symptoms were previously attributed to enterovirus D68, one patient had clear evidence of infection with Haemophilus influenzae, and a second patient had a severe Staphylococcus aureus infection caused by a methicillin-resistant strain. Neither of these bacteria were identified in the original study. These observations may have relevance in cases that present with flaccid paralysis because bacterial infections, co-infections or post-infection immune responses may trigger pathogenic processes that may present as poliomyelitis-like syndromes and may mimic AFM. A separate finding was that large numbers of human sequences were present in each of the publicly released samples, although the original study reported that human sequences had been removed before deposition.

Highlights

  • Metagenomic shotgun sequencing, in which DNA or RNA is extracted from a tissue sample and sequenced, has the potential to detect a wide range of infections

  • Deep whole-genome shotgun (WGS) sequencing can detect bacteria, viruses, and eukaryotic pathogens with equal effectiveness, as long as the infectious agent is similar to a species that has been previously sequenced

  • In 2014, a large outbreak of infection with enterovirus D68 was associated with both severe respiratory illness and acute paralysis, which the U.S Centers for Disease Control and Prevention (CDC) named acute flaccid myelitis (AFM)[1]

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Summary

13 Jul 2015 report report version 1

Any reports and responses or comments on the article can be found at the end of the article. Metagenomics , neurological infections , computational biology , next-generation sequencing , sequence alignment. This article is included in the Preclinical Reproducibility and Robustness gateway

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