In the era of next-generation sequencing and ubiquitous assembly and binning of metagenomes, new putative genome sequences are being produced from isolate and microbiome samples at ever-increasing rates. Genome-scale metabolic models have enormous utility for supporting the analysis and predictive characterization of these genomes based on sequence data. As a result, tools for rapid automated reconstruction of metabolic models are becoming critically important for supporting the analysis of new genome sequences. Many tools and algorithms have now emerged to support rapid model reconstruction and analysis. Here, we are comparing and contrasting the capabilities and output of a variety of these tools, including ModelSEED, Raven Toolbox, PathwayTools, SuBliMinal Toolbox and merlin.
The image represents a simplified ‘open’ cell of the gram-positive bacterium Streptomyces coelicolor and selected components of its zinc metabolism. The zinc sensor protein – zinc uptake regulator (Zur) – is shown in metallic blue in the middle, bound to DNA (green) where it works as a transcriptional repressor when zinc levels are adequate. The Zur-regulated high-affinity zinc uptake system ZnuABC is shown in purple. Synthesis of the secreted zincophore coelibactin is also Zur-regulated. Zinc ions are shown as silver balls surrounding the cell, and bound to Zur; for details see pages 983–1001.
The image has been created by Alevtina Mikhaylina with the help of Claudia A. Blindauer and David J. Scanlan.
Methods for automated genome-scale metabolic model reconstruction
José P. Faria, Miguel Rocha, Isabel Rocha, Christopher S. Henry; Methods for automated genome-scale metabolic model reconstruction. Biochem Soc Trans 20 August 2018; 46 (4): 931–936. doi: https://doi.org/10.1042/BST20170246
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