Literature DB >> 18513813

Energy-based models for environmental biotechnology.

Jorge Rodríguez1, Juan M Lema, Robbert Kleerebezem.   

Abstract

Environmental biotechnology is evolving. Current process objectives include the production of chemicals and/or energy carriers (biofuels) in addition to the traditional objective of removing pollutants from waste. To maximise product yields and minimise biomass production, future processes will rely on anaerobic microbial communities. Anaerobic processes are characterised by small Gibbs energy changes in the reactions catalysed, and this provides clear thermodynamic process boundaries. Here, a Gibbs-energy-based methodology is proposed for mathematical modelling of energy-limited anaerobic ecosystems. This methodology provides a basis for the description of microbial activities as a function of environmental factors, which will allow enhanced catalysis of specific reactions of interest for process development.

Mesh:

Year:  2008        PMID: 18513813     DOI: 10.1016/j.tibtech.2008.04.003

Source DB:  PubMed          Journal:  Trends Biotechnol        ISSN: 0167-7799            Impact factor:   19.536


  11 in total

1.  Microbial catabolic activities are naturally selected by metabolic energy harvest rate.

Authors:  Rebeca González-Cabaleiro; Irina D Ofiţeru; Juan M Lema; Jorge Rodríguez
Journal:  ISME J       Date:  2015-07-10       Impact factor: 10.302

2.  Consistent microbial dynamics and functional community patterns derived from first principles.

Authors:  Hadrien Delattre; Elie Desmond-Le Quéméner; Christian Duquennoi; Ahlem Filali; Théodore Bouchez
Journal:  ISME J       Date:  2018-09-07       Impact factor: 10.302

3.  Chemical tethering of motile bacteria to silicon surfaces.

Authors:  Jane Bearinger; Lawrence Dugan; Ligang Wu; Haley Hill; Allen Christian; Jeffrey Hubbell
Journal:  Biotechniques       Date:  2009-03       Impact factor: 1.993

4.  MI-Sim: A MATLAB package for the numerical analysis of microbial ecological interactions.

Authors:  Matthew J Wade; Jordan Oakley; Sophie Harbisher; Nicholas G Parker; Jan Dolfing
Journal:  PLoS One       Date:  2017-03-08       Impact factor: 3.240

5.  Metabolic energy-based modelling explains product yielding in anaerobic mixed culture fermentations.

Authors:  Rebeca González-Cabaleiro; Juan M Lema; Jorge Rodríguez
Journal:  PLoS One       Date:  2015-05-18       Impact factor: 3.240

6.  Inoculum composition determines microbial community and function in an anaerobic sequential batch reactor.

Authors:  Allison R Perrotta; Rajkumari Kumaraswamy; Juan R Bastidas-Oyanedel; Eric J Alm; Jorge Rodríguez
Journal:  PLoS One       Date:  2017-02-14       Impact factor: 3.240

7.  Impacts of chemical gradients on microbial community structure.

Authors:  Jianwei Chen; Anna Hanke; Halina E Tegetmeyer; Ines Kattelmann; Ritin Sharma; Emmo Hamann; Theresa Hargesheimer; Beate Kraft; Sabine Lenk; Jeanine S Geelhoed; Robert L Hettich; Marc Strous
Journal:  ISME J       Date:  2017-01-17       Impact factor: 10.302

8.  Low Substrate Loading Limits Methanogenesis and Leads to High Coulombic Efficiency in Bioelectrochemical Systems.

Authors:  Tom H J A Sleutels; Sam D Molenaar; Annemiek Ter Heijne; Cees J N Buisman
Journal:  Microorganisms       Date:  2016-01-05

9.  In situ Biofilm Quantification in Bioelectrochemical Systems by using Optical Coherence Tomography.

Authors:  Sam D Molenaar; Tom Sleutels; Joao Pereira; Matteo Iorio; Casper Borsje; Julian A Zamudio; Francisco Fabregat-Santiago; Cees J N Buisman; Annemiek Ter Heijne
Journal:  ChemSusChem       Date:  2018-06-07       Impact factor: 8.928

10.  Microbial diversity arising from thermodynamic constraints.

Authors:  Tobias Großkopf; Orkun S Soyer
Journal:  ISME J       Date:  2016-04-01       Impact factor: 10.302

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