Christopher Henry, Assistant Computational Scientist at Argonne National Laboratory, will give a colloquium titled, "Metabolic Modeling Across the Tree of Life."
Over the past decade, genome-scale metabolic models have emerged as a valuable resource for generating predictions of global organism behavior based on the sequence of nucleotides in the genome. These models can accurately predict essential genes, organism phenotypes, organism response to mutation, and metabolic engineering strategies. In this talk, I will describe our ongoing work to develop and apply improved algorithms for the automated reconstruction of metabolic models across the microbial tree of life. We have made substantial progress recently in the automated reconstruction of high quality models of central metabolism for over 3000 prokaryotic genomes, representing a global survey of known electron transport chains and fermentative capabilities of these organisms, and substantially improving the quality of genome-scale models built on these central carbon core models. We have also applied our genome-scale algorithms to build full-scale models for over 3000 organisms, revealing new insights into microbial diversity. This large-scale availability of models has unlocked the use of statistical approaches to predict phenotypes and evaluate our confidence in genome annotations. All of our tools are being released within the KBase platform, placing them at the fingertips of the experimental biologist for use in analyzing experimental data. I will discuss one example of the application of these models directly to driving experimental work in our effort to minimize the B. subtilis genome. We have made over 150 large-scale knockouts in B. subtilis, representing 75% of the genome, and over 23 of the largest knockouts have been combined in a single reduced strain. I will explore how our metabolic model of B. subtilis has facilitated this process.
Originally published at acms.nd.edu.