Distributed flux balance analysis simulations of serial biomass fermentation by two organisms.

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...

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Main Authors: Edward Vitkin, Amichai Gillis, Mark Polikovsky, Barak Bender, Alexander Golberg, Zohar Yakhini
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0227363
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spelling doaj-a7cfbdde83b34fc48e4f66331fb611132021-03-03T21:31:41ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-01151e022736310.1371/journal.pone.0227363Distributed flux balance analysis simulations of serial biomass fermentation by two organisms.Edward VitkinAmichai GillisMark PolikovskyBarak BenderAlexander GolbergZohar YakhiniIntelligent 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.https://doi.org/10.1371/journal.pone.0227363
collection DOAJ
language English
format Article
sources DOAJ
author Edward Vitkin
Amichai Gillis
Mark Polikovsky
Barak Bender
Alexander Golberg
Zohar Yakhini
spellingShingle Edward Vitkin
Amichai Gillis
Mark Polikovsky
Barak Bender
Alexander Golberg
Zohar Yakhini
Distributed flux balance analysis simulations of serial biomass fermentation by two organisms.
PLoS ONE
author_facet Edward Vitkin
Amichai Gillis
Mark Polikovsky
Barak Bender
Alexander Golberg
Zohar Yakhini
author_sort Edward Vitkin
title Distributed flux balance analysis simulations of serial biomass fermentation by two organisms.
title_short Distributed flux balance analysis simulations of serial biomass fermentation by two organisms.
title_full Distributed flux balance analysis simulations of serial biomass fermentation by two organisms.
title_fullStr Distributed flux balance analysis simulations of serial biomass fermentation by two organisms.
title_full_unstemmed Distributed flux balance analysis simulations of serial biomass fermentation by two organisms.
title_sort distributed flux balance analysis simulations of serial biomass fermentation by two organisms.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2020-01-01
description 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.
url https://doi.org/10.1371/journal.pone.0227363
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