Abstract
Intelligent biorefinery design that addresses both the composition of the biomass feedstock as well as fermentation microorganisms could benefit from dedicated tools for computational simulation and computer-assisted optimization. Here we present the BioLego Vn2.0 framework, based on Microsoft Azure Cloud, which supports large-scale simulations of biomass serial fermentation processes by two different organisms. BioLego enables the simultaneous analysis of multiple fermentation scenarios and the comparison of fermentation potential of multiple feedstock compositions. Thanks to the effective use of cloud computing it further allows resource intensive analysis and exploration of media and organism modifications. We use BioLego to obtain biological and validation results, including (1) exploratory search for the optimal utilization of corn biomasses—corn cobs, corn fiber and corn stover—in fermentation biorefineries; (2) analysis of the possible effects of changes in the composition of K. alvarezi biomass on the ethanol production yield in an anaerobic two-step process (S. cerevisiae followed by E. coli); (3) analysis of the impact, on the estimated ethanol production yield, of knocking out single organism reactions either in one or in both organisms in an anaerobic two-step fermentation process of Ulva sp. into ethanol (S. cerevisiae followed by E. coli); and (4) comparison of several experimentally measured ethanol fermentation rates with the predictions of BioLego.
Highlights
Efficient and sustainable conversion of biomass into commerciable products, including food products, chemicals and fuels, currently is a major challenge for science, governments and industry across the globe [1]
Our biological and validation results include (1) exploratory search for optimal biomass utilization setup for three different types of corn biomasses—corn cobs, corn fiber and corn stover; (2) analysis of possible effects of changes in the composition of K. alvarezi algal biomass on the ethanol production yield in the anaerobic two-step process (S. cerevisiae followed by E. coli); (3) analysis of impact on the estimated ethanol production yield of knocking out single organism reactions either in one or in both organisms in anaerobic two-step process that ferments Ulva sp. into ethanol (S. cerevisiae followed by E. coli); and (4) comparison of experimental measurements of ethanol fermentation efficiency with the efficiency predicted by BioLego system
For each tested biomass and fermentation target we performed simulations for both singlestep and for two-step fermentations under either aerobic or anaerobic conditions for four organism models (E.coli based on model iJO1366[23], C. acetobutylicum based on model iCAC490[40] and two models of S. cerevisiae based on Yeast5[41]—with and without xylose digestion mechanism) currently integrated in BioLego flow
Summary
Efficient and sustainable conversion of biomass into commerciable products, including food products, chemicals and fuels, currently is a major challenge for science, governments and industry across the globe [1]. Designing biorefineries requires addressing all aspects of the process, including biomass growth, harvesting and fermentation and the distribution of products and handling waste [2]. The feedstock composition and its amenability to efficient fermentation by microorganisms are two important determinants of the efficiency of biorefineries [3]. While feedstock composition is constrained by local resources [4], there is much. Funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
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