Mobile genetic element insertions drive antibiotic resistance across pathogens
Durrant MG, Li MM, Siranosian B, Bhatt AS doi: http://dx.doi.org/10.1101/527788. Posted in BioRxiv on Jan. 23, 2019.
COMMENT: This work describes a new method for identifying mobile elements from short-read sequencing data which is based on. The method is focused on the Mobile Genetic Elements (MGE) insertion sites. First consensus sequences from the clipped ends of locally-aligned reads are generated. Second, clipped ends are used to identify the exact site where the inserted element begins and ends with respect to the reference genome used. It allows reconstructing the inserted element flanks. Third, the reads of the bacterial genome under analysis is de novo assembled using the SPAdes assembler (Bankevich et al. 2012). Fourth, the candidate insertion site sequences are aligned to the de novo assembled genome to define the full inserted Mobile Genetic Element (MGE). Finally, a de novo database of elements across all analyzed samples is built.
The authors analyzing with this tool many genomes from human pathogens:
We applied this tool, which we call mustache, in an analysis of thousands of publicly-available sequenced isolates of the prevalent bacterial pathogens Acinetobacter baumannii, Enterococcus faecium, Escherichia coli, Klebsiella pneumoniae, Mycobacterium tuberculosis, Neisseria gonorrhoeae, Neisseria meningitidis, Pseudomonas aeruginosa, and Staphylococcus aureus. Short-read sequence data for a random subset of these isolates were downloaded from the Sequence Read Archive (SRA).
Using this approach the authors get to detect the importance of MGE in the acquisition of antibiotic resistance across pathogens:
We use our de novo approach to analyze 12,419 sequenced isolates of nine pathogenic bacterial species and demonstrate large differences in the overall MGE repertoire and the rate of MGE insertion between species. We characterize MGE insertion hotspots across species and demonstrate that these insertions alter the activity of genes in clinically relevant biological pathways, such as those related to antibiotic resistance.