Identification of pathogens in culture-negative infective endocarditis cases by metagenomic analysis

Jun Cheng†,
Huan Hu†,
Yue Kang†,
Weizhi Chen,
Wei Fang,
Kaijuan Wang,
Qian Zhang,
Aisi Fu,
Shuilian Zhou,
Chen Cheng,
Qingqing Cao,
Feiyan WangEmail author,
Shela LeeEmail author and
Zhou ZhouEmail author

†Contributed equally

Annals of Clinical Microbiology and Antimicrobials201817:43

https://doi.org/10.1186/s12941-018-0294-5

Received: 8 June 2018
Accepted: 24 November 2018
Published: 20 December 2018

Abstract

Background

Pathogens identification is critical for the proper diagnosis and precise treatment of infective endocarditis (IE). Although blood and valve cultures are the gold standard for IE pathogens detection, many cases are culture-negative, especially in patients who had received long-term antibiotic treatment, and precise diagnosis has therefore become a major challenge in the clinic. Metagenomic sequencing can provide both information on the pathogenic strain and the antibiotic susceptibility profile of patient samples without culturing, offering a powerful method to deal with culture-negative cases.

Methods

To assess the feasibility of a metagenomic approach to detect the causative pathogens in resected valves from IE patients, we employed both next-generation sequencing and Oxford Nanopore Technologies MinION nanopore sequencing for pathogens and antimicrobial resistance detection in seven culture-negative IE patients. Using our in-house developed bioinformatics pipeline, we analyzed the sequencing results generated from both platforms for the direct identification of pathogens from the resected valves of seven clinically culture-negative IE patients according to the modified Duke criteria.

Results

Our results showed both metagenomics methods can be applied for the causative pathogen detection in all IE samples. Moreover, we were able to simultaneously characterize respective antimicrobial resistance features.

Conclusion

Metagenomic methods for IE detection can provide clinicians with valuable information to diagnose and treat IE patients after valve replacement surgery. However, more efforts should be made to optimize protocols for sample processing, sequencing and bioinformatics analysis.