KBase’s modeling tools to be presented at American Institute of Chemical Engineers (AIChE) 2017 Annual Meeting

KBase is used by scientists in a range of fields, including systems biology, genomics, biochemistry and even chemical engineering. That last group is the focus of the American Institute of Chemical Engineers (AIChE) 2017 Annual Meeting, which will draw about 7000 chemical engineering researchers to Minneapolis the week of October 29 – November 3, 2017. Several KBase scientists will make presentations to attendees explaining how KBase can aid their research.

KBase scientist Chris Henry, with collaborators at Argonne National Laboratory and Pacific Northwest National Laboratory, will present “Development and Application of Integrated Pipeline for the Modeling and Analysis of Microbial Communities in the DOE Systems Biology Knowledgebase” (https://aiche.confex.com/aiche/2017/meetingapp.cgi/Paper/505501). Dr. Henry will describe the KBase pipeline for development and analysis of community metabolic models starting from metagenomic data, and show how it has been applied to elucidate the ecology and trophic interactions occurring within three microbiome-based datasets: (i) a lab-constructed community comprised of the cyanobacterium Thermosynechococcus elongatus supporting the heterotrophic bacterium, Meiothermus ruber; (ii) ten naturally occurring highly coupled communities comprised of 2-3 species each; and (iii) a larger 18-species natural community comprising an epsomitic phototrophic microbial mat in Hot Lake, Washington. The KBase Narrative for this study can be found at https://narrative.kbase.us/narrative/ws.24490.obj.1.

José P. Faria, another KBase scientist at ANL, will present a poster at AIChE about “Improving Automated Model Reconstruction Across Phylogenetically Diverse Genome-Scale Metabolic Models” using KBase (https://aiche.confex.com/aiche/2017/meetingapp.cgi/Paper/506549). Dr. Faria and collaborators selected a phylogenetically diverse set of approximately 1000 genomes and built draft genome-scale metabolic models using the ModelSEED pipeline in KBase, improved the ModelSEED templates by introducing new gene/reaction mappings, and then used these templates to improve the models.