Evaluating the genome and resistome of extensively drug-resistant Klebsiella pneumoniae using native DNA and RNA Nanopore sequencing

Abstract

Background: Klebsiella pneumoniae frequently harbours multidrug resistance, and current diagnostics struggle to rapidly identify appropriate antibiotics to treat these bacterial infections. The MinION device can sequence native DNA and RNA in real time, providing an opportunity to compare the utility of DNA and RNA for prediction of antibiotic susceptibility. However, the effectiveness of bacterial direct RNA sequencing and base-calling has not previously been investigated. This study interrogated the genome and transcriptome of 4 extensively drug-resistant (XDR) K. pneumoniae clinical isolates; however, further antimicrobial susceptibility testing identified 3 isolates as pandrug-resistant (PDR).

Results: The majority of acquired resistance (≥75%) resided on plasmids including several megaplasmids (≥100 kb). DNA sequencing detected most resistance genes (≥70%) within 2 hours of sequencing. Neural network-based base-calling of direct RNA achieved up to 86% identity rate, although ≤23% of reads could be aligned. Direct RNA sequencing (with ∼6 times slower pore translocation) was able to identify (within 10 hours) ≥35% of resistance genes, including those associated with resistance to aminoglycosides, β-lactams, trimethoprim, and sulphonamide and also quinolones, rifampicin, fosfomycin, and phenicol in some isolates. Direct RNA sequencing also identified the presence of operons containing up to 3 resistance genes. Polymyxin-resistant isolates showed a heightened transcription of phoPQ (≥2-fold) and the pmrHFIJKLM operon (≥8-fold). Expression levels estimated from direct RNA sequencing displayed strong correlation (Pearson: 0.86) compared to quantitative real-time PCR across 11 resistance genes.

Conclusion: Overall, MinION sequencing rapidly detected the XDR/PDR K. pneumoniae resistome, and direct RNA sequencing provided accurate estimation of expression levels of these genes.

Figure 1:

Time required to detect antibiotic resistance genes via the real-time emulation analysis using MinION native DNA and RNA sequencing. (A) 1_GR_13, (B) 2_GR_12, (C) 16_GR_13, and (D) 20_GR_12. Legend colours identify the class of antibiotic to which the gene confers resistance, a slash on the y-axis label indicates reads that detected >1 resistance gene, and the pound sign indicates a family of genes detected (>3). An asterisk indicates the inability for direct RNA sequencing to detect this gene. Albacore 2.2.7. base-called sequences were used, and all reads (pass and fail) were included in this analysis.

Figure 2:

Expression of resistance genes via direct RNA sequencing when aligned to completed genomes. (A) 1_GR_13, (B) 2_GR_12, (C) 16_GR_13, and (D) 20_GR_12. The x-axis depicts the resistance genes, which are grouped on the basis of the location in the genome, where P indicates a plasmid followed by replicon identity. Albacore 2.2.7 base-called pass and fail reads were used for analysis. Values indicate counts per million mapped reads (cpm) (after removal of reads mapping to rRNA), and dotted line is set to 300 cpm. Genes are represented in order of appearance on contig, and plus sign indicates the co-expression of genes.

Figure 3:

Correlation between resistance genes detected via direct RNA sequencing and validated using qRT-PCR. Relative expression was calculated via normalizing to the housekeeping gene, rpsL, for both direct RNA sequencing (log₂(gene/rpsL)) and qRT-PCT (2^{−(gene/rpsL)}). Owing to high similarity between certain genes, several primers recognize >1 gene (underlined). These include aac(6’)Ib: aac(6’)Ib-cr, aadA24; strA: aph(3'')-Ib, and blaTEM-1: blaTEM-1A, blaTEM-1B. Values are log₁₀ transformed and shifted +0.001 to display genes with no detectable expression.

Figure 4:

Correlation between the 4 XDR K. pneumoniae isolates for gene expression via direct RNA sequencing. Top panels display Spearman correlation coefficients. The diagonal panel shows the density of gene expression levels in counts per million mapped reads for each sample (after removal of rRNA mapped reads). Bottom panels depict the correlation of gene expression between isolates as a scatter plot. Colours indicate categorization of gene: antimicrobial resistance genes (AMR) as per ResFinder 3.0, virulence genes (VIR) determined via RAST, and all other genes or background genes (BG) are displayed. cpm was capped at 2,000.

Figure 5:

Expression of genes associated with the polymyxin resistance pathway. Comparison between direct RNA sequencing (log₂(gene/rpsL)) and qRT-PCR (2^{−(gene/rpsL)}). All isolates except 20_GR_12 harboured resistance to polymyxin (MIC: >2 µg/mL), and genes were normalized to the housekeeping gene rpsL. Values are log₁₀ transformed and shifted +0.001 to display genes with no detectable expression.