Determining antimicrobial resistance profiles and identifying novel mutations of Neisseria gonorrhoeae genomes obtained by multiplexed MinION sequencing

Gonorrhea is one of the most common sexually transmitted diseases worldwide. To cure infection and prevent transmission, timely and appropriate antimicrobial therapy is necessary. Unfortunately, Neisseria gonorrhoeae, the etiological agent of gonorrhea, has acquired nearly all known mechanisms of antimicrobial resistance (AMR), thereby compromising the efficacy of antimicrobial therapy. Treatment failure resulting from AMR has become a global public health concern. Whole-genome sequencing is an effective method to determine the AMR characteristics of N. gonorrhoeae. Compared with next-generation sequencing, the MinION sequencer (Oxford Nanopore Technologies (ONT)) has the advantages of long read length and portability.

Based on a pilot study using MinION to sequence the genome of N. gonorrhoeae, we optimized the workflow of sequencing and data analysis in the current study. Here we sequenced nine isolates within one flow cell using a multiplexed sequencing strategy. After hybrid assembly with Illumina reads, nine integral circular chromosomes were obtained. By using the online tool Pathogenwatch and a BLAST-based workflow, we acquired complete AMR profiles related to seven classes of antibiotics.

We also evaluated the performance of ONT-only assemblies. Most AMR determinants identified by ONT-only assemblies were the same as those identified by hybrid assemblies. Moreover, one of the nine assemblies indicated a potentially novel antimicrobial-related mutation located in mtrR which results in a frame-shift, premature stop codon, and truncated peptide. In addition, this is the first study using the MinION sequencer to obtain complete genome sequences of N. gonorrhoeae strains which are epidemic in China.

This study shows that complete genome sequences and antimicrobial characteristics of N. gonorrhoeae can be obtained using the MinION sequencer in a simple and cost-effective manner, with hardly any knowledge of bioinformatics required. More importantly, this strategy provides us with a potential approach to discover new AMR determinants.

Authors: Chi Zhang, Feng Wang, Cansheng Zhu, Leshan Xiu, Yamei Li, Li Li, Bo Liu, Yizhun Li, Yaling Zeng, Boyang Guo, Junping Peng