Critical steps in clinical shotgun metagenomics for the concomitant detection and typing of microbial pathogens.

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PubMed ID: 30213965

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Couto N, Schuele L, Raangs EC, Machado MP, Mendes CI, Jesus TF, Chlebowicz M, Rosema S, Ramirez M, Carriço JA, Autenrieth IB, Friedrich AW, Peter S, Rossen JW

Sci Rep. Sep 2018. doi: 10.1038/s41598-018-31873-w

COMMENT: Shotgun metagenomics can help in the identification and typing of microbial pathogens directly from patient samples added or instead of to the classical microbial cultured used routinely in clinical microbiology.

Shotgun metagenomics is a culture-independent technique that provides information at the level of molecular characterization. This could be used for infection prevention and can be helpful when there is a need to a quick response, thus the whole procedure is shorter than culture-based methods (if one includes typing). Also, sometimes, this method can be more sensitive than culture in identifying pathogens.


In this study, the aim was to identify the critical steps when using SMg for the identification and characterization of microbial pathogens directly from clinical specimens using methods that are likely to be available in clinical microbiology laboratories wanting to implement genomics for pathogen identification or molecular epidemiology studies.

Main results:

- In 8 samples, all the microorganisms identified by classical culture were also identified through metagenomics (using at least one method). In sample 2, two of the bacterial species identified by classical culture, i.e., E. coli and one Enterococcus avium were not identified through shotgun metagenomics and in sample 3 there was no concordance between the results of MALDI-TOF and the taxonomical classification methods at the species level.

- Different bioinformatics pipelines were evaluated to identify potential differences between them and identify those which could provide the clinical microbiologist with the maximum of relevant and accurate information. In terms of microbial identification, in both Unix and web-based approaches we would recommend MetaPhlAn, since it has good sensitivity and a good positive predictive value (PPV).


In conclusion, this study showed the potential but also highlighted the problems of implementing shotgun metagenomics (SMg) for the identification and typing of pathogens directly from clinical samples. Based on the results obtained here we can conclude that the tools and databases used for taxonomic classification and antimicrobial resistance will have a key impact on the results, cautioning about the comparison between studies using different methods and suggesting that efforts need to be directed towards standardization of the analysis methods if SMg is to be used routinely in clinical microbiology


Carmen Martín