A reproducible microbiome pipeline for the identification of horizontally acquired mobile genetic elements

Abstract

Microbial communities of bacteria, fungi, archaea, and viruses are the most numerically abundant biological entities and regulate ecosystem services. However, the intricate and complex community interactions complicate efforts to disentangle the precise mechanisms underlying their relationships. As a result, several fundamental insights regarding microbial communities remain unclear. For instance, we lack a clear understanding regarding the extent of intra and inter-community interactions among microbial communities. These interactions may have profound effects, due to the known importance of microbial communities as mediators of biogeochemical cycling. In addition to the biological complexity, there is a lack of computational tools providing functional insights regarding evolutionary insights including the extent of intra and inter-community interactions through processes such as horizontal gene transfer. Computational tools are important for understanding microbial interactions in complex ecosystems. To reduce this knowledge deficit, we developed BioGeochemical Horizontal Gene Transfer (BioG-HGT), an automated, standalone, and reproducible pipeline. This pipeline associates horizontally transferred biogeochemical genes with their mobile genetic elements. Using a metagenomic dataset, comprised of 33 million reads and a Linux Ubuntu 20.04 LTS system with 4 cores and 24Gb RAM, BioG-HGT analyzed the dataset within 9 hours. The resultant tab delimited file includes information on the metagenome assembled genome (MAG) bins produced from the input sequence dataset. The file also includes information regarding the position of the putative mobile genetic elements, and the corresponding biogeochemical cycling genes located in the same contig. Taken together, BioG-HGT provides an easy-to-use computational tool for understanding the adaptation of microbial communities to environmental disturbances. The pipeline expands the available resources for exploring environmental mobile genetic elements and their role in the dissemination of biogeochemical cycling genes. We anticipate that this tool will facilitate studies aimed at elucidating horizontal gene transfer events in environ- mental sequence datasets. BioG-HGT is available at https://github.com/Shaedeycool/BioG-HGT_wd.