496978 Uncovering and Correcting the Effect of Biomass Molecular Weight Discrepancies in FBA Calculations

Siu Hung Joshua Chan, Chemical Engineering, The Pennsylvania State University, University Park, PA, Jingyi Cai, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, China, Lin Wang, Department of Chemcial Engineering, The Pennsylvania State University, University Park, PA, Margaret Simons-Senftle, The Pennsylvania State University, University Park, PA and Costas D. Maranas, Chemical Engineering, The Pennsylvania State Univeristy, University Park, PA

In genome-scale metabolic models, the biomass has by definition a molecular weight of 1 g mmol-1. This is critical for correctly predicting growth yields, contrasting multiple models and more importantly modeling microbial communities. Nevertheless, we identified significant departures after examining 64 published models. The biomass weights of 34 models differed by 5 – 50%, while 8 models have discrepancies >50%. 20 models were manually curated. By maximizing the original vs. corrected biomass reactions, flux balance analysis revealed >10% differences in growth yields for 12 of the curated models. Biomass molecular weight discrepancies are accentuated in microbial community simulations as they can cause significant and systematic errors in the community composition. Microbes with underestimated biomass molecular weights are overpredicted in the community whereas microbes with overestimated biomass weights are underpredicted. The observed departures in community composition are disproportionately larger than the discrepancies in the biomass weight estimate. Here we introduce a systematic procedure for checking and correcting the biomass weight, which we propose as a standard practice for metabolic reconstructions.

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