Background: Recent adva1nces in whole genome sequencing (WGS) based technologies have facilitated multi-step applications for predicting antimicrobial resistance (AMR) and investigating the molecular epidemiology of Neisseria gonorrhoeae. However, generating full scaffolds of N. gonorrhoeae genomes from short reads, and the assignment of molecular epidemiological information (NG-MLST, NG-MAST, and NG-STAR) to multiple assembled samples, is challenging due to required manual tasks such as annotating antimicrobial resistance determinants with standard nomenclature for a large number of genomes.
Results: We present Gen2Epi, a pipeline that assembles short reads into full scaffolds and automatically assigns molecular epidemiological and AMR information to the assembled genomes. Gen2Epi is a command-line tool integrating third-party software and tailored specifically for N. gonorrhoeae. For its evaluation, the Gen2Epi pipeline successfully assembled the WGS short reads from 1484 N. gonorrhoeae samples into full-length genomes for both chromosomes and plasmids and was able to assign in silico molecular determinant information to each dataset automatically. The assemblies were generated using raw as well as trimmed short reads. The median genome coverage of full-length scaffolds and "N" statistics (N50, NG50, and NGA50) were higher than, or comparable to, previously published results and the scaffolding process improved the quality of the draft genome assemblies. Molecular antimicrobial resistant (AMR) determinants identified by Gen2Epi reproduced information for the 1484 samples as previously reported, including NG-MLST, NG-MAST, and NG-STAR molecular sequence types.
Conclusions: Gen2Epi can be used to assemble short reads into full-length genomes and assign accurate molecular marker and AMR information automatically from NG-STAR, NG-MAST, and NG-MLST. Gen2Epi is publicly available under "CC BY-NC 2.0 CA" Creative Commons licensing as a VirtualBox image containing the constituent software components running on the LINUX operating system (CentOS 7). The image and associated documentation are available via anonymous FTP at ftp://www.cs.usask.ca/pub/combi or ftp://ftp.cs.usask.ca/pub/combi.
Keywords: Antimicrobial resistance; Bioinformatics; De novo genome assembly; Molecular epidemiology; Molecular typing; Neisseria gonorrhoeae; Scaffolding; Strain typing; Whole-genome sequencing (WGS).