Literature DB >> 23983023

Dynamic model-based analysis of furfural and HMF detoxification by pure and mixed batch cultures of S. cerevisiae and S. stipitis.

Timothy J Hanly1, Michael A Henson.   

Abstract

Inhibitory compounds that result from biomass hydrolysis are an obstacle to the efficient production of second-generation biofuels. Fermentative microorganisms can reduce compounds such as furfural and 5-hydroxymethyl furfural (HMF), but detoxification is accompanied by reduced growth rates and ethanol yields. In this study, we assess the effects of these furan aldehydes on pure and mixed yeast cultures consisting of a respiratory deficient mutant of Saccharomyces cerevisiae and wild-type Scheffersomyces stipitis using dynamic flux balance analysis. Uptake kinetics and stoichiometric equations for the intracellular reduction reactions associated with each inhibitor were added to genome-scale metabolic reconstructions of the two yeasts. Further modification of the S. cerevisiae metabolic network was necessary to satisfactorily predict the amount of acetate synthesized during HMF reduction. Inhibitory terms that captured the adverse effects of the furan aldehydes and their corresponding alcohols on cell growth and ethanol production were added to attain qualitative agreement with batch experiments conducted for model development and validation. When the two yeasts were co-cultured in the presence of the furan aldehydes, inoculums that reduced the synthesis of highly toxic acetate produced by S. cerevisiae yielded the highest ethanol productivities. The model described here can be used to generate optimal fermentation strategies for the simultaneous detoxification and fermentation of lignocellulosic hydrolysates by S. cerevisiae and/or S. stipitis.
© 2013 Wiley Periodicals, Inc.

Entities:  

Keywords:  S. cerevisiae; S. stipitis; ethanol; flux balance analysis; lignocellulosic hydrolysate

Mesh:

Substances:

Year:  2013        PMID: 23983023     DOI: 10.1002/bit.25101

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


  13 in total

1.  Single and combined effects of acetic acid, furfural, and sugars on the growth of the pentose-fermenting yeast Meyerozyma guilliermondii.

Authors:  Michelle Dos Santos Cordeiro Perna; Reinaldo Gaspar Bastos; Sandra Regina Ceccato-Antonini
Journal:  3 Biotech       Date:  2018-02-07       Impact factor: 2.406

Review 2.  Metabolic network modeling of microbial communities.

Authors:  Matthew B Biggs; Gregory L Medlock; Glynis L Kolling; Jason A Papin
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2015-06-24

Review 3.  Genome-scale modelling of microbial metabolism with temporal and spatial resolution.

Authors:  Michael A Henson
Journal:  Biochem Soc Trans       Date:  2015-12       Impact factor: 5.407

Review 4.  Synthetic Ecology of Microbes: Mathematical Models and Applications.

Authors:  Ali R Zomorrodi; Daniel Segrè
Journal:  J Mol Biol       Date:  2015-11-11       Impact factor: 5.469

Review 5.  Dynamic flux balance analysis for synthetic microbial communities.

Authors:  Michael A Henson; Timothy J Hanly
Journal:  IET Syst Biol       Date:  2014-10       Impact factor: 1.615

6.  Genome-scale NAD(H/(+)) availability patterns as a differentiating feature between Saccharomyces cerevisiae and Scheffersomyces stipitis in relation to fermentative metabolism.

Authors:  Alejandro Acevedo; German Aroca; Raul Conejeros
Journal:  PLoS One       Date:  2014-01-29       Impact factor: 3.240

7.  Perspectives and Challenges in Microbial Communities Metabolic Modeling.

Authors:  Emanuele Bosi; Giovanni Bacci; Alessio Mengoni; Marco Fondi
Journal:  Front Genet       Date:  2017-06-21       Impact factor: 4.599

8.  Ethanol production improvement driven by genome-scale metabolic modeling and sensitivity analysis in Scheffersomyces stipitis.

Authors:  Alejandro Acevedo; Raúl Conejeros; Germán Aroca
Journal:  PLoS One       Date:  2017-06-28       Impact factor: 3.240

9.  Investigating metabolic interactions in a microbial co-culture through integrated modelling and experiments.

Authors:  Aarthi Ravikrishnan; Lars M Blank; Smita Srivastava; Karthik Raman
Journal:  Comput Struct Biotechnol J       Date:  2020-03-30       Impact factor: 7.271

10.  Bridging substrate intake kinetics and bacterial growth phenotypes with flux balance analysis incorporating proteome allocation.

Authors:  Hong Zeng; Aidong Yang
Journal:  Sci Rep       Date:  2020-03-09       Impact factor: 4.379

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