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Enhancing antimicrobial resistance monitoring: Core Plasmid Multi-Locus sequence typing (cpMLST) with Oxford Nanopore sequencing technology (ONT)

Xavier, B. B.; Bari, A. K.; Severs, T. T.; Cardoso, M. J.; Savin Hoffmeyer, M.; Sinha, B.; Rossen, J. W. A.

2024-10-25 microbiology
10.1101/2024.10.25.620091 bioRxiv
Show abstract

BackgroundThe spread of antimicrobial resistance (AMR) poses a significant threat to global public health, primarily driven by the horizontal gene transfer of resistance genes via plasmids. Understanding the dynamics of plasmid transmission within (intra) and between (inter) bacterial species is crucial for developing effective countermeasures. In this study, we utilize long-read sequencing technology to develop an innovative approach called core plasmid Multi-Locus Sequence Typing (cpMLST) and track the global plasmid transmission pathways. MethodsWe collected wastewater samples from six different hospitals in Germany. Within 24 hours of collection, we isolated extensively drug-resistant (XDR) bacteria using CHROMagar plates (CHROMagar, Paris, France). Species identification was done using MALDI-TOF MS (Bruker Daltonics, Bremen, Germany). Genomic DNA from the isolates was extracted using the PureLink Genomic DNA Mini Kit (Invitrogen, Carlsbad, USA) and subsequently sequenced using Oxford Nanopore Technologies (ONT) sequencing (Oxford Nanopore Technologies). We employed the SQK-RBK114.24 kit on an R10.4.1 flow cell, achieving a minimum of 250 Mb of raw data for each isolate with an accuracy of 98.9%. The reads were assembled using Unicycler, and the quality of the assemblies was assessed using QUAST and Bandage. The assembled genomes were then uploaded to the Center for Genomic Epidemiology (CGE) https://www.genomicepidemiology.org/ platform to determine incompatibility (Inc) types and antimicrobial resistance (AMR) genes. Additionally, we performed core plasmid analysis using chewBBACA v.3.3.10 to assess plasmid relatedness. ResultsThe analysis confirmed the identification of various bacterial isolates. Among the most prevalent XDR isolate were Enterobacter roggenkampii (n=38), Serratia marcescens (n=12), Klebseilla oxytoca (n=11), Klebseilla michiganensis (n=8), and Citrobacter freundii (n=7). We conducted a cpMLST analysis to examine the highly prevalent plasmids and reveal evolutionary relationships and transmission patterns. Each isolate harbored different types of complete plasmids. Among those were the IncFII (n=45), IncHI (n=26), IncX3 (n=21), and other incompatibility groups. By focusing on shared Inc types among the bacterial species, their transfer within a single bacterial species (intra-species transfer) and between different species (inter-species transfer) were identified. The allelic differences ranged from 3-55 (IncHI), 2-32 (IncFII) and 2-24 (IncX3). Moreover, these plasmids, typically identified as smaller plasmids (IncX3), were larger than their commonly reported sizes. The analysis of plasmid dynamics across diverse bacterial hosts provides valuable insight into the mechanisms driving the spread of antimicrobial resistance, offering potential strategies for better controlling the dissemination of antimicrobial resistance and its transmission in clinical environments. ConclusionIn conclusion, long-read sequencing technologies emerge as an essential tool for investigating the transmission dynamics of antimicrobial resistance genes among plasmids. By implementing cp-MLST, we anticipate achieving an unparalleled understanding of the global dissemination and evolutionary patterns of resistance-carrying plasmids. This approach offers superior resolution to conventional plasmid typing methods, potentially opening new avenues for innovative strategies to combat the escalating AMR crisis.

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