An Ecology of Modeling Methods, Data, and Tools to Decipher Functional Delegation and Species Interactions within a Microbiome Conference: Conference on Constraint-Based Reconstruction and Analysis (COBRA)Year: 2018Proceeding: 5th Conference on Constraint-Based Reconstruction and Analysis (COBRA 2018)Group: General SubmissionsSession: Methods & Software 2 Time: Tuesday, October 16, 2018 - 4:00pm-4:25pm Authors: Henry, C. S., Argonne National Laboratory Weisenhorn, P., Argonne National Laboratory van der Lelie, D., Gusto Global Jeffryes, J. G., Argonne National Laboratory Chivian, D. C., Joint BioEnergy Institute Faria, J. P., Argonne National Laboratory Edirisinghe, J. N., Argonne National Laboratory Liu, F., Argonne National Laboratory Seaver, S. M. D., Argonne National Laboratory Dudley, H., University of Colorado Boulder Zhang, Q., Argonne National Laboratory Sadkhin, B., Argonne National Laboratory Gupta, N., Argonne National Laboratory Gu, T., Argonne National Laboratory Taylor, R. C., Pacific Northwest National Laboratory Song, H. S., Pacific Northwest National Laboratory Bernstein, H. C., Pacific Northwest National Laboratory Zucker, J., Pacific Northwest National Laboratory Lindemann, S. R., Pacific Northwest National Laboratory Gilbert, J., Argonne National Laboratory Cottingham, R., Oak Ridge National Laboratory Arkin, A., University of California, Berkeley The term metagenome was first used in the literature 20 years ago, and in that time, we have witnessed a revolution in our capacity to gather data, model, and understand microbiome systems in natural and engineered environments. Finally we have sufficient data available to support the validation and refinement of metabolic models for microbiome systems. Here, I describe an ecology of tools, pipelines, and data that we have developed to support the modeling and simulation of microbiome systems. One of the initial challenges in modeling a microbiome system is to obtain species genomes from metagenomic data. To aid with this challenge, the KBase team recently implemented a pipeline for metagenome assembly, binning, QC, and annotation comprised of available open-source tools (e.g. metaSPAdes, MaxBin2). Another challenge is to rapidly construct predictive genome-scale models from newly assembled and binned genomes. To address this challenge, we have developed publicly accessible tools to generate interoperable models for microbial, plant, and fungal genomes (with recent significant improvements to our microbial model reconstruction pipeline). Even with models, these community systems are typically under-determined, with species interactions difficult to identify from noise. For this, we developed tools to predict auxotrophy from genomic data, revealing exciting new insights into how microbiome systems evolve and build stable interconnections. We also developed tools and pipelines to support the mapping of models and microbiome systems in general to metabolomics data, applying network approaches to enable models to slice through noise. Finally, we recently developed a new approach that explores the balance of protein-resources that plays a significant role in the delegation of functions in microbiome systems. In my talk, I describe these tools and explore the results from their application to a variety of microbiome systems, including a photo-autotrophic microbial mat, an electrosynthetic microbiome, and a microbiome on a built surface.