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. 2024 Dec 2;16(1):141.
doi: 10.1186/s13073-024-01416-2.

Comprehensive pathogen identification and antimicrobial resistance prediction from positive blood cultures using nanopore sequencing technology

Po-Yu Liu  1   2   3   4 , Han-Chieh Wu  5 , Ying-Lan Li  1 , Hung-Wei Cheng  6 , Ci-Hong Liou  5 , Feng-Jui Chen  7   8 , Yu-Chieh Liao  9
Affiliations

Comprehensive pathogen identification and antimicrobial resistance prediction from positive blood cultures using nanopore sequencing technology

Po-Yu Liu et al. Genome Med. .

Abstract

Background: Blood cultures are essential for diagnosing bloodstream infections, but current phenotypic tests for antimicrobial resistance (AMR) provide limited information. Oxford Nanopore Technologies introduces nanopore sequencing with adaptive sampling, capable of real-time host genome depletion, yet its application directly from blood cultures remains unexplored. This study aimed to identify pathogens and predict AMR using nanopore sequencing.

Methods: In this cross-sectional genomic study, 458 positive blood cultures from bloodstream infection patients in central Taiwan were analyzed. Parallel experiments involved routine microbiologic tests and nanopore sequencing with a 15-h run. A bioinformatic pipeline was proposed to analyze the real-time sequencing reads. Subsequently, a comparative analysis was performed to evaluate the performance of species identification and AMR prediction.

Results: The pipeline identified 76 species, with 88 Escherichia coli, 74 Klebsiella pneumoniae, 43 Staphylococcus aureus, and 9 Candida samples. Novel species were also discovered. Notably, precise species identification was achieved not only for monomicrobial infections but also for polymicrobial infections, which was detected in 23 samples and further confirmed by full-length 16S rRNA amplicon sequencing. Using a modified ResFinder database, AMR predictions showed a categorical agreement rate exceeding 90% (3799/4195) for monomicrobial infections, with minimal very major errors observed for K. pneumoniae (2/186, 1.1%) and S. aureus (1/90, 1.1%).

Conclusions: Nanopore sequencing with adaptive sampling can directly analyze positive blood cultures, facilitating pathogen detection, AMR prediction, and outbreak investigation. Integrating nanopore sequencing into clinical practices signifies a revolutionary advancement in managing bloodstream infections, offering an effective antimicrobial stewardship strategy, and improving patient outcomes.

Keywords: Adaptive sampling; Antimicrobial resistance prediction; Nanopore sequencing; Pathogen identification; Positive blood cultures; Real-time.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: This study was approved by the Institutional Review Board at Taichung Veterans General Hospital (CE22004B). All participants provided written informed consent prior to participation. The research conformed to the principles of the Helsinki Declaration. Consent for publication: Not applicable. Competing interests: The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
A Frequency distribution of the predominant pathogens responsible for bloodstream infections identified via MALDI-TOF in this study. B Frequency of antimicrobial susceptibility testing (AST) for various antibiotics (grouped by antibiotic class) by species. Sau, Staphylococcus aureus; Scn, Staphylococcus, coagulase negative, i.e., S. epidermidis, and S. not aureus identified by MALDI-TOF; Efa, Enterococcus faecalis; Ecc, Enterobacter cloacae complex; Eco, Escherichia coli; Kpn, Klebsiella pneumoniae; Sma, Serratia marcescens; Pae, Pseudomonas aeruginosa; SXT, trimethoprim-sulfamethoxazole; CZA, ceftazidime-avibactam; SAM, ampicillin-sulbactam; TZP, piperacillin-tazobactam; ETP, ertapenem; IPM, imipenem; CFZ, cefazolin; FEP, cefepime; CRO, ceftriaxone; CAZ, ceftazidime; CFP, cefoperazone; FMOX, flomoxef; FOX, cefoxitin; PEN, penicillin; OX, oxacillin; CIP, ciprofloxacin; VAN, vancomycin; GEN, gentamicin; TGC, tigecycline; CLI, clindamycin; ERY, erythromycin; LZD, linezolid; DAP, daptomycin. CL, colistin
Fig. 2
Fig. 2
Analytic pipeline and the corresponding prediction results using nanopore sequencing with adaptive sampling
Fig. 3
Fig. 3
A Inconsistent pairs of species identification between nanopore sequencing and MALDI-TOF. B–E Genome coverages aligned with contigs and their average identities to reference genomes. Please note that the sequencing depth information was extracted from assembly_info.txt generated by Flye
See this image and copyright information in PMC

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