Development of an NGS-Based Workflow for Improved Monitoring of Circulating Plasmids in Support of Risk Assessment of Antimicrobial Resistance Gene Dissemination

Abstract

Antimicrobial resistance (AMR) is one of the most prominent public health threats. AMR genes localized on plasmids can be easily transferred between bacterial isolates by horizontal gene transfer, thereby contributing to the spread of AMR. Next-generation sequencing (NGS) technologies are ideal for the detection of AMR genes; however, reliable reconstruction of plasmids is still a challenge due to large repetitive regions. This study proposes a workflow to reconstruct plasmids with NGS data in view of AMR gene localization, i.e., chromosomal or on a plasmid. Whole-genome and plasmid DNA extraction methods were compared, as were assemblies consisting of short reads (Illumina MiSeq), long reads (Oxford Nanopore Technologies) and a combination of both (hybrid). Furthermore, the added value of conjugation of a plasmid to a known host was evaluated. As a case study, an isolate harboring a large, low-copy mcr-1-carrying plasmid (>200 kb) was used. Hybrid assemblies of NGS data obtained from whole-genome DNA extractions of the original isolates resulted in the most complete reconstruction of plasmids. The optimal workflow was successfully applied to multidrug-resistant Salmonella Kentucky isolates, where the transfer of an ESBL-gene-containing fragment from a plasmid to the chromosome was detected. This study highlights a strategy including wet and dry lab parameters that allows accurate plasmid reconstruction, which will contribute to an improved monitoring of circulating plasmids and the assessment of their risk of transfer.

Keywords: DNA extraction; Flongle; MiSeq; MinION; antimicrobial resistance; conjugation; hybrid assembly; mobile elements; next-generation sequencing; plasmids; surveillance.

Figure 1

Overview of workflow to reconstruct plasmids with next-generation sequencing and the parameters that were tested. The arrows in bold represent the parameters that were found to be most suitable for reconstructing plasmids. The dashed, bold arrows represent parameters that are optional for the workflow but were determined to be more useful than the nonbold arrows. The box encapsulated in a dashed line represents a parameter that is very similar to the one it is adjacent to.

Figure 2

Visualizations of the assembly graphs with Bandage of the MiSeq, MinION and hybrid assemblies performed on the whole-genome DNA extractions (Genomic Tip 100) of the original E. coli COL20160015 (a–c) and the conjugate R274 (d–f). Each line represents a contig, and a red line represents a contig occurring in higher coverage compared to the other contigs within the same assembly. The thinner black lines are the most likely paths between contigs.

Figure 3

Visualization with Bandage of the MiSeq, MinION and hybrid assemblies performed on the whole-genome and plasmid DNA extractions (G100, MagCore, G500, phenol and phenol-ampli) of Salmonella isolate S15BD05371 (extractions 3–5 and 7–8 (Table 1), assemblies 1–15 (Table 2)). Each line represents a contig, and a red line is in higher coverage compared to the other contigs within the same assembly. * There was not enough MinION read coverage to complete the assembly of phenol-ampli with only MinION reads.

Figure 4

Percentage of MiSeq and MinION reads from the G100 (extr-3), MagCore (extr-4), G500 (extr-5), phenol (extr-7) and phenol-ampli (extr-8) DNA extractions of Salmonella isolate S15BD05371 mapped to the complete plasmid sequence.

Figure 5

Similarity between the chromosomes of S16BD08730 and S18BD03394 and the plasmid of S18BD05011 (contig 2). The location and orientation of the genes is indicated with blue arrows. There is a 1 bp difference between the chromosomal and plasmid-located bla_CTX-M14b gene.