The design of synthetic cells requires a detailed understanding of the relevance of genes and gene networks underlying complex cellular phenotypes. Transposon-sequencing (Tn-seq) and constraint-based metabolic modeling can be used to probe the core genetic and metabolic networks underlying a biological process. Integrating these highly complementary experimental and in silico approaches has the potential to yield a highly comprehensive understanding of the core networks of a cell. Specifically, it can facilitate the interpretation of Tn-seq data sets and identify gaps in the data that could hinder the engineering of the cellular system, while also providing refined models for the accurate predictions of cellular metabolism. Here, we present Tn-Core, the first easy-to-use computational pipeline specifically designed for integrating Tn-seq data with metabolic modeling, prepared for use by both experimental and computational biologists. Tn-Core is a MATLAB toolbox that contains several custom functions, and it is built upon existing functions within the COBRA Toolbox and the TIGER Toolbox. Tn-Core takes as input a genome-scale metabolic model, Tn-seq data, and optionally RNA-seq data, and returns: (i) a context-specific core metabolic model; (ii) an evaluation of redundancies within core metabolic pathways, and optionally (iii) a refined genome-scale metabolic model. A simple, user-friendly workflow, requiring limited knowledge of metabolic modeling, is provided that allows users to run the analyses and export the data as easy-to-explore files of value to both experimental and computational biologists. We demonstrate the utility of Tn-Core using Sinorhizobium meliloti, Pseudomonas aeruginosa, and Rhodobacter sphaeroides genome-scale metabolic reconstructions as case studies.
Keywords: COBRA models; bacterial metabolism; metabolic network reconstruction; systems biology; transposon sequencing.