The effect of sequencing and assembly on the inference of horizontal gene transfer on chromosomal and plasmid phylogenies

Abstract

The spread of antibiotic resistance genes on plasmids is a threat to human and animal health. Phylogenies of bacteria and their plasmids contain clues regarding the frequency of plasmid transfer events, as well as the co-evolution of plasmids and their hosts. However, whole genome sequencing data from diverse ecological or clinical bacterial samples are rarely used to study plasmid phylogenies and resistance gene transfer. This is partially due to the difficulty of extracting plasmids from short-read sequencing data. Here, we use both short- and long-read sequencing data of 24 clinical extended-spectrum β -lactamase (ESBL)-producing Escherichia coli to estimate chromosomal and plasmid phylogenies. We compare the impact of different sequencing and assembly methodologies on these phylogenies and on the inference of horizontal gene transfer. We find that chromosomal phylogenies can be estimated robustly with all methods, whereas plasmid phylogenies have more variable topology and branch lengths across the methods used. Specifically, hybrid methods that use long reads to resolve short-read assemblies (HybridSPAdes and Unicycler) perform better than those that started from long reads during assembly graph generation (Canu). By contrast, the inference of plasmid and antibiotic resistance gene transfer using a parsimony-based criterion is mostly robust to the choice of sequencing and assembly method. This article is part of a discussion meeting issue ‘Genomic population structures of microbial pathogens’.

Host-specific plasmid evolution explains the variable spread of clinical antibiotic-resistance plasmids

“…Strains 1, 15, and 19 were sampled from different patients in a transmission study at the University Hospital Basel, Switzerland. We have previously described phenotypes and genotypes of ancestral strains 1 (ST117, GCA_016433325.1) and 15 (ST40, GCA_008370755.1) and the genome sequence of the ancestral strain 19 (ST131, commonly associated with ESBL-plasmids, GCA_020907505.1) (Tschudin-Sutter et al ., 2016; Benz et al ., 2020; Huisman et al ., 2021). These strains are natively associated with conjugative ESBL-plasmids of the type IncIγ, non-conjugative IncF for strain 19, and carry a range of other (non-focal, non-ESBL) plasmids ( Fig.…”

“…Strains 1, 15 and 19 were previously sequenced with Illumina MiSeq (WGS, paired-end, 2 × 250 bp) and Oxford Nanopore MinION methods to generate hybrid assemblies (Huisman et al ., 2021). Ancestral and evolved clones of the strain-plasmid combinations generated here ( Fig.…”

“…Parallel genetic changes in ESBL-plasmids and chromosomes are specific to the strainplasmid combination. We whole-genome sequenced ancestral strain-plasmid combinations (short-and long read-sequencing Huisman et al, 2021)) and single endpoint clones (p + /p -, Illumina only) from each replicate population. First, we found each evolved clone maintained all their native non-ESBL plasmids.…”

Genomic population structures of microbial pathogens

“…This is of increasing interest in the field of infection control genomics, because the transfer between strains of plasmids and antimicrobial resistance (AMR) genes is now well documented as playing a pivotal role in the emergence and persistence of hospital-associated outbreaks of drug resistant infections [ 11 ]. In their article, Huisman et al [ 12 ] consider how the choice of sequencing and assembly methods can impact inferences of HGT of plasmids and AMR genes. They use a set of 24 Escherichia coli isolates, sequenced with the three currently most-popular technology platforms (Illumina, Oxford Nanopore and PacBio), and use cgMLST gene alignments for phylogenetic inference of chromosomal trees with BEAST2.…”

“…Inference and comparisons of plasmid trees are challenging because plasmid sequences can be fragmented across contigs. Huisman et al [ 12 ] use an interesting approach of aligning all genes that are annotated on the same contig as a shared plasmid replicon marker. This approach revealed substantial variation in the plasmid trees generated using different sequencing and assembly methods.…”