Comparative genomic analysis of paired clinical isolates from a patient with recurrent melioidosis reveals a low within-host mutation rate

Abstract

Introduction. Relapse of melioidosis is not uncommon and can occur due to shorter oral antibiotic therapy in the first episode. In such isolates, low mutation rates were identified amongst paired clinical isolates during relapse, but large-scale structural variants were also common.Hypothesis. Using pair-wise comparison, a low number of mutations, especially amongst the virulence and antibiotic resistance genes, may be present amongst the paired isolates obtained during the study period.Aim. A pair of clinical isolates obtained from a patient with recurrent melioidosis during the study period (January 2018 to June 2021) was analysed for identifying the genomic relatedness and DNA changes that may have caused the relapse.Methodology. Using paired-end Illumina sequencing, following appropriate data quality checks, the genomes were assembled using Shovill pipeline, whilst the variants were called using Snippy. Structural variants were detected using TIDDIT, and functional associations were identified using the STRING database searches.Results. One of the isolates (from the second episode) had a highly fragmented genome, but very few structural variants and SNPs were identified. Both the isolates had similar virulence and antibiotic resistance genes; however, owing to the few structural changes, a slightly lower number of virulence genes were observed. Together, they shared 99.8% of the proteomes, and most variants identified spanned either hypothetical proteins or un-annotated regions.Conclusions. Based on comprehensive genome analysis the two strains were genetically similar, with a few structural variants, implying the second episode to be a relapse rather than a re-infection. There was no difference in the antibiotic resistance or virulence genes that may have explained the relapse.

Keywords: Burkholderia pseudomallei; genome sequencing; melioidosis; relapse.

Fig. 1.. Comparative analysis of two isolates with the reference MSHR7901 genome (black). As observed, the genome EX7035 is highly fragmented (regions of low similarity and breaks) when compared with EX14915. Image created using BRIG v0.95 with max and min identity set at 100 and 70, respectively.

Fig. 2.. Mash distance of the isolates with respect to the complete genomes available in the RefSeq database. The X-axis represents various genomes and is omitted for image clarity [refer to File S1, for raw data (available in the online version of this article)].

Fig. 3.. Virulence genes identified exclusively in EX14915. Proteins that are exclusive for the isolate are colored cyan while those from the STRING database are in light green. The clusters are labelled according to their biological function: type III secretion system (GO: 0030254), flagellar assembly (GO: 0044781), pilus assembly (CL: 4673), and protein transmembrane transport (CL: 10280).

Fig. 4.. Comparison of read coverages of the tagC-5 gene (as an example) in EX7035 (above) and EX14915 (below). No coverage was observed for the region spanning 50–550 bp in EX7035, with a few reads soft-clipped (indicated in blue) towards the end of the gene. The gene sequences were obtained from VFDB, reads were mapped using Snippy and an image was generated using IGV v2.15.1.

Fig. 5.. (a) Common and unique clusters amongst the two isolates. (b–d) The percentage of genes amongst the 5,449 clusters with each GO term. The figure is obtained using OrthoVenn3.

Fig. 6.. Percentage of genes amongst the protein clusters unique to EX14915 that are associated with biological process GO terms.

Fig. 7.. Protein interactions amongst the major clusters identified unique to EX14915. Of the 27 proteins identified, 24 were mapped to proteins in the database. For better visualization, nodes with no interactions were removed. The edges indicate a confidence score (>700) of interactions, and each cluster is identified as follows: (a) type II secretion system (CL: 6312), (b) pentose phosphate system (CL: 3105), (c) ABC transporters (bp02010), (d) pentose and glucuronate interconversions (KEGG: bps00040) and (e) two major clusters involved in arginine and proline metabolism (KEGG: bps00330) and butanoate metabolism (KEGG: bps00650) with shared interactions coloured in pink. Cluster images were created using Cytoscape v3.10.3 and using the Y-files circular layout plugin.