Large-Scale Comparative Metabolic Modeling to Build an Understanding of Enzyme and Genome Evolution Among Diverse Species

Event Sponsor: 
Mathematics and Computer Science Seminar
Start Date: 
Mar 7 2018 - 10:30am
Building 240/Room 4301
Argonne National Laboratory
Janaka N. Edirisinghe
Speaker(s) Title: 
University of Chicago/Argonne National Laboratory
Christopher Henry

Systems-level approaches are the new and essential paradigm in interpreting genomic, metagenomic, and other omics data. Here we highlight several examples where we have used metabolic modeling and comparative genomics approaches to address important biological questions in a variety of scientific contexts.

One of our examples involves the modeling of central metabolism and energy biosynthesis across the bacterial tree of life. In this work, we constructed 8000 models of core metabolism for diverse microbial genomes, studying alternative strategies employed by these species for energy biosynthesis, while also exploring how these central metabolic pathways co-evolve.

In our second example, we constructed metabolic models for key members of a complex electrosynthetic biofilm. We use these models explain the physiology and carbon flow of each organism, and we reconcile and validate our models with meta-transcriptomic data.

In a third example, we have used metabolic modeling and phylogenomics to detect bacterial species that are evolving by gene loss, with the finding that Actinomycetaceae genomes from human cavities are undergoing sizable reductions, including loss of L-histidine and L-tryptophan biosynthesis.

In our final example, we describe the development of a new pipeline for the automated construction of genome-scale metabolic models for fungal genomes in the DOE Knowledgebase (KBase). We apply this pipeline to construct models of 130 diverse fungal genomes in the Joint Genome Institute's (JGI) MycoCosm resource, and we explore the variation of metabolism among all of these fungal species.

Miscellaneous Information: 

This seminar will be streamed, see details at