Efficient System Wide Metabolic Pathway Comparisons in Multiple Microbes Using Genome to KEGG Orthology (G2KO) Pipeline Tool

Interdiscip Sci. 2020 Sep;12(3):311-322. doi: 10.1007/s12539-020-00375-7. Epub 2020 Jul 6.

Abstract

Comparison of system-wide metabolic pathways among microbes provides valuable insights of organisms' metabolic capabilities that can further assist in rationally screening organisms in silico for various applications. In this work, we present a much needed, efficient and user-friendly Genome to KEGG Orthology (G2KO) pipeline tool that facilitates efficient comparison of system wide metabolic networks of multiple organisms simultaneously. The optimized strategy primarily involves automatic retrieval of the KEGG Orthology (KO) identifiers of user defined organisms from the KEGG database followed by overlaying and visualization of the metabolic genes using the KEGG Mapper reconstruct pathway tool. We demonstrate the applicability of G2KO via two case studies in which we processed 24,314 genes across 15 organisms, mapped on to 530 reference pathways in KEGG, while focusing on pathways of interest. First, an in-silico designing of synthetic microbial consortia towards bioprocessing of cellulose to valuable products by comparing the cellulose degradation and fermentative pathways of microbes was undertaken. Second, we comprehensively compared the amino acid biosynthetic pathways of multiple microbes and demonstrated the potential of G2KO as an efficient tool for metabolic studies. We envisage the tool will find immensely useful to the metabolic engineers as well as systems biologists. The tool's web-server, along with tutorial is publicly available at https://faculty.iitmandi.ac.in/~shyam/tools/g2ko/g2ko.cgi . Also, standalone tool can be downloaded freely from https://sourceforge.net/projects/g2ko/ , and from the supplementary.

Keywords: Bioprocess; Cellulose degradation; KEGG; Metabolic networks.

MeSH terms

  • Cellulose / metabolism
  • Computational Biology / methods*
  • Databases, Genetic*
  • Humans
  • Metabolic Networks and Pathways

Substances

  • Cellulose