CABGen: A Web Application for the Bioinformatic Analysis of Bacterial Genomes

Due to recent developments in NGS technologies, genome sequencing is generating large volumes of new data containing a wealth of biological information. Understanding sequenced genomes in a biologically meaningful way and delineating their functional and metabolic landscapes is a first-level challenge. Considering the global antimicrobial resistance (AMR) problem, investments to expand surveillance and improve existing genome analysis technologies are pressing. In addition, the speed at which new genomic data is generated surpasses our capacity to analyze it with available bioinformatics methods, thus creating a need to develop new, user-friendly and comprehensive analytical tools. To this end, we propose a new web application, CABGen,(1) developed with open-source software. CABGen allows storing, organizing, analyzing, and interpreting bioinformatics data in a friendly, scalable, easy-to-use environment and can process data from bacterial isolates of different species and origins. CABGen has three modules: Upload Sequences, Analyze Sequences, and Verify Results. Functionalities include coverage estimation, species identification, de novo genome assembly, and assembly quality, genome annotation, MLST mapping, searches for genes related to AMR, virulence, and plasmids, and detection of point mutations in specific AMR genes. Visualization tools are also available, greatly facilitating the handling of biological data. The reports include those results that are clinically relevant. To illustrate the use of CABGen, whole-genome shotgun data from 181 bacterial isolates of different species collected in 5 Brazilian regions between 2018 and 2020 were uploaded and submitted to the platform's modules.

Automated summary

With the recent advancements in NGS technologies, genome sequencing is generating vast amounts of data with valuable biological information. Understanding genomes and their functions in a biologically meaningful way is a challenge that needs to be addressed, especially in the context of global antimicrobial resistance. In order to properly analyze the rapidly accumulating genomic data, there is a need for new, user-friendly and comprehensive analytical tools. This article proposes a web application called CABGen, which provides an easy-to-use and scalable environment for storing, organizing, analyzing, and interpreting bioinformatics data.