Building Single-Cell Models of Planktonic Metabolism Using PSAMM

Ying Zhang, Keith Dufault-Thompson and Jon Lund Steffensen, University of Rhode Island, Department of Cell and Molecular Biology, Kingston, RI, United States
Abstract:
The Genome-scale models (GEMs) of metabolic networks simulate the metabolic activities of individual cells by integrating omics data with biochemical and physiological measurements. GEMs were applied in the simulation of various photo-, chemo-, and heterotrophic organisms and provide significant insights into the function and evolution of planktonic cells. Despite the quick accumulation of GEMs, challenges remain in assembling the individual cell-based models into community-level models. Among various problems, the lack of consistencies in model representation and model quality checking has hindered the integration of individual GEMs and can lead to erroneous conclusions in the development of new modeling algorithms. Here, we present a Portable System for the Analysis of Metabolic Models (PSAMM). Along with the software a novel format of model representation was developed to enhance the readability of model files and permit the inclusion of heterogeneous, model-specific annotation information. A number of quality checking procedures was also implemented in PSAMM to ensure stoichiometric balance and to identify unused reactions. Using a case study of Shewanella piezotolerans WP3, we demonstrated the application of PSAMM in simulating the coupling of carbon utilization and energy production pathways under low-temperature and high-pressure stress. Applying PSAMM, we have also analyzed over 50 GEMs in the current literature and released an updated collection of the models with corrections on a number of common inconsistencies. Overall, PSAMM opens up new opportunities for integrating individual GEMs for the construction and mathematical simulation of community-level models in the scope of entire ecosystems.