Modeling Metabolic Variability in Methanosarcina Acetivorans

Abstract

Anaerobic archaea M. acetivorans, a versatile salt-water adapted methanogen, is capable of converting seven different organic molecules into methane. Utilization of these substrates involves three main reaction pathways that are differentially regulated by the organism depending on growth conditions. We have developed a kinetic model for methanogenesis using RNA-seq data, single molecule enumeration of protein abundance (SiMPull) and kinetic parameters from literature the. RNA-seq data generated on different growth conditions was also used to create a transcriptional regulatory model. Stochasticity in gene expression is known to create heterogeneity in an isogenic population. Such heterogeneity in transcriptional regulators, which are known to be present in small copy numbers, can effect formation of different cell phenotypes allowing cells in a colony to utilize different energy sources. Integrating the kinetic model of methanogenesis with a transcriptional regulation model results in a most comprehensive model for methanogenesis to date. We simulate this model using reaction-diffusion master equation (RDME) based Lattice Microbes software package to simulate monoclonal cells and study the variability in pathway and substrate usage under environmental and industrial conditions. Simulated behaviors allow identification and analysis of phenotypes that arise and the resulting sensitivity of methanogenesis to protein copy number, substrate availability and transcriptional regulation noise. These results lay the groundwork necessary for studying the individual behaviors to ultimately simulate a colony of methanogens sharing space and resources.