A Guild-Based Metabolic Model Improves Understanding of a Medium-Chain Fatty Acid Producing Microbiome | AIChE

A Guild-Based Metabolic Model Improves Understanding of a Medium-Chain Fatty Acid Producing Microbiome

Authors 

Scarborough, M. J. - Presenter, University of Vermont
Donohue, T. J., University of Wisconsin-Madison
Noguera, D., University of Wisconsin-Madison
Microbiomes can be harnessed to produce beneficial chemicals from renewable resources. Recently, microbiome fermentations have been studied for producing medium-chain fatty acids (MCFA). Predictive and diagnostic models of MCFA-producing microbiomes, however, are limited. To address this, we constructed two metabolic models of a MCFA-producing microbiome fed residues from lignocellulosic biorefining. The first model is a single-unit model (iFerment156) that contains a diverse set of fermentation pathways while the second model (iFermGuilds564) separates fermentation activities into functional guilds. Both models predicted an energetic advantage for production of octanoic acid (a desirable MCFA) as a major fermentation product. In simulating behavior of our bioreactor microbiome, iFermGuilds564 predicted that MCFA were largely produced by a sugar-consuming guild, while short-chain fatty acids were mainly produced by a guild consuming lactate. Other guilds were predicted to ferment sugars and complex carbohydrates to lactate, acetate, H2, and CO2. Acetate, H2, and CO2 are all predicted to be terminal products rather than MCFA intermediates. Using iFermGuilds564, we also predicted that a community of MCFA-producing sugar and acetate consumers and homoacetogens could improve production of octanoic acid. In conjunction with past metagenomic and metatranscriptomic data, these results provide an improved understanding of MCFA production. The first generation metabolic models for MCFA production (https://github.com/mscarbor/Mixed-Culture-Fermentation-Models) represent a step towards predictive models for designing microbiomes to produce MCFAs.