Cargando…

Synthetic Feedback Loop Model for Increasing Microbial Biofuel Production Using a Biosensor

Current biofuel production methods use engineered bacteria to break down cellulose and convert it to biofuel. A major challenge in microbial fuel production is that increasing biofuel yields can be limited by the toxicity of the biofuel to the organism that is producing it. Previous research has dem...

Descripción completa

Detalles Bibliográficos
Autores principales: Harrison, Mary E., Dunlop, Mary J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3481154/
https://www.ncbi.nlm.nih.gov/pubmed/23112794
http://dx.doi.org/10.3389/fmicb.2012.00360
_version_ 1782247695499395072
author Harrison, Mary E.
Dunlop, Mary J.
author_facet Harrison, Mary E.
Dunlop, Mary J.
author_sort Harrison, Mary E.
collection PubMed
description Current biofuel production methods use engineered bacteria to break down cellulose and convert it to biofuel. A major challenge in microbial fuel production is that increasing biofuel yields can be limited by the toxicity of the biofuel to the organism that is producing it. Previous research has demonstrated that efflux pumps are effective at increasing tolerance to various biofuels. However, when overexpressed, efflux pumps burden cells, which hinders growth and slows biofuel production. Therefore, the toxicity of the biofuel must be balanced with the toxicity of pump overexpression. We have developed a mathematical model for cell growth and biofuel production that implements a synthetic feedback loop using a biosensor to control efflux pump expression. In this way, the production rate will be maximal when the concentration of biofuel is low because the cell does not expend energy expressing efflux pumps when they are not needed. Additionally, the microbe is able to adapt to toxic conditions by triggering the expression of efflux pumps, which allow it to continue biofuel production. Sensitivity analysis indicates that the feedback sensor model is insensitive to many system parameters, but a few key parameters can influence growth and production. In comparison to systems that express efflux pumps at a constant level, the feedback sensor increases overall biofuel production by delaying pump expression until it is needed. This result is more pronounced when model parameters are variable because the system can use feedback to adjust to the actual rate of biofuel production.
format Online
Article
Text
id pubmed-3481154
institution National Center for Biotechnology Information
language English
publishDate 2012
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-34811542012-10-30 Synthetic Feedback Loop Model for Increasing Microbial Biofuel Production Using a Biosensor Harrison, Mary E. Dunlop, Mary J. Front Microbiol Microbiology Current biofuel production methods use engineered bacteria to break down cellulose and convert it to biofuel. A major challenge in microbial fuel production is that increasing biofuel yields can be limited by the toxicity of the biofuel to the organism that is producing it. Previous research has demonstrated that efflux pumps are effective at increasing tolerance to various biofuels. However, when overexpressed, efflux pumps burden cells, which hinders growth and slows biofuel production. Therefore, the toxicity of the biofuel must be balanced with the toxicity of pump overexpression. We have developed a mathematical model for cell growth and biofuel production that implements a synthetic feedback loop using a biosensor to control efflux pump expression. In this way, the production rate will be maximal when the concentration of biofuel is low because the cell does not expend energy expressing efflux pumps when they are not needed. Additionally, the microbe is able to adapt to toxic conditions by triggering the expression of efflux pumps, which allow it to continue biofuel production. Sensitivity analysis indicates that the feedback sensor model is insensitive to many system parameters, but a few key parameters can influence growth and production. In comparison to systems that express efflux pumps at a constant level, the feedback sensor increases overall biofuel production by delaying pump expression until it is needed. This result is more pronounced when model parameters are variable because the system can use feedback to adjust to the actual rate of biofuel production. Frontiers Media S.A. 2012-10-26 /pmc/articles/PMC3481154/ /pubmed/23112794 http://dx.doi.org/10.3389/fmicb.2012.00360 Text en Copyright © 2012 Harrison and Dunlop. http://www.frontiersin.org/licenseagreement This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.
spellingShingle Microbiology
Harrison, Mary E.
Dunlop, Mary J.
Synthetic Feedback Loop Model for Increasing Microbial Biofuel Production Using a Biosensor
title Synthetic Feedback Loop Model for Increasing Microbial Biofuel Production Using a Biosensor
title_full Synthetic Feedback Loop Model for Increasing Microbial Biofuel Production Using a Biosensor
title_fullStr Synthetic Feedback Loop Model for Increasing Microbial Biofuel Production Using a Biosensor
title_full_unstemmed Synthetic Feedback Loop Model for Increasing Microbial Biofuel Production Using a Biosensor
title_short Synthetic Feedback Loop Model for Increasing Microbial Biofuel Production Using a Biosensor
title_sort synthetic feedback loop model for increasing microbial biofuel production using a biosensor
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3481154/
https://www.ncbi.nlm.nih.gov/pubmed/23112794
http://dx.doi.org/10.3389/fmicb.2012.00360
work_keys_str_mv AT harrisonmarye syntheticfeedbackloopmodelforincreasingmicrobialbiofuelproductionusingabiosensor
AT dunlopmaryj syntheticfeedbackloopmodelforincreasingmicrobialbiofuelproductionusingabiosensor