Computational modeling of horticultural crops under different light conditions

B. Wijnen, Huili Yuan, P.A.J. Hilbers, Y. Ren, G. Zhou, J. Yu, N.A.W. Riel, van

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic

Abstract

Light regulates many aspects of plant growth and developmental processes as well as disease resistance in plants. Computational models can be used to provide more detailed insights in how processes are regulated in plants and can contribute to investigating the mechanisms underlying these processes. The current study is performed to assess the influence of light conditions on several horticultural crops of commercial importance by developing systems biology models. Genome-scale modeling of the plant metabolic network in combination with flux balance analysis (FBA) could be suitable to model the influence of lighting conditions on horticultural crops. With FBA, the influence of light dependent enzymes on for instance biomass accumulation could be explored, without the need of hard-to-determine kinetic parameters of these enzymes. FBA was performed on a metabolic network reconstruction of Arabidopsis and generated some preliminary results. For instance, different effects and even opposite effects of catalase activity on biomass accumulation were found for catalase located in different compartments. Constrained-based reconstruction and analysis (COBRA) methods, including FBA, have often been applied for bacteria. COBRA methods are only able to model steady state reaction fluxes, therefore do not incorporate metabolite concentrations. Moreover, FBA performed on metabolic network reconstructions often leads to thermodynamically infeasible loops, resulting in unrealistic predictions. Despite the challenges revealed during this study, reaction fluxes predicted by FBA have often been reported to be quite accurate and efforts have already been made to overcome these limitations. For example, one of the solutions to overcome thermodynamically infeasible loops is by performing a loopless flux variability analysis (FVA), generating a set of boundary conditions that are thermodynamically feasible. It is expected that COBRA methods can be successfully applied for plant species, however, this has only scarcely been done to date and solely for the model plant Arabidopsis.
LanguageEnglish
Title of host publicationProceedings of the 15th Workshop of the International Study Group for Systems Biology (ISGSB 2012), 24-28 September 2012, Groningen and Ameland, The Netherlands
StatePublished - 2012
Eventconference; International Study Group for Systems Biology (ISGSB) 2012, Ameland, Netherlands; 2012-09-24; 2012-09-28 -
Duration: 24 Sep 201228 Sep 2012

Conference

Conferenceconference; International Study Group for Systems Biology (ISGSB) 2012, Ameland, Netherlands; 2012-09-24; 2012-09-28
Period24/09/1228/09/12
OtherInternational Study Group for Systems Biology (ISGSB) 2012, Ameland, Netherlands

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horticultural crops
biomass production
catalase
Arabidopsis
enzymes
disease resistance
lighting
methodology
plant growth
metabolites
kinetics
Biological Sciences
genome
prediction
bacteria

Cite this

Wijnen, B., Yuan, H., Hilbers, P. A. J., Ren, Y., Zhou, G., Yu, J., & Riel, van, N. A. W. (2012). Computational modeling of horticultural crops under different light conditions. In Proceedings of the 15th Workshop of the International Study Group for Systems Biology (ISGSB 2012), 24-28 September 2012, Groningen and Ameland, The Netherlands
Wijnen, B. ; Yuan, Huili ; Hilbers, P.A.J. ; Ren, Y. ; Zhou, G. ; Yu, J. ; Riel, van, N.A.W./ Computational modeling of horticultural crops under different light conditions. Proceedings of the 15th Workshop of the International Study Group for Systems Biology (ISGSB 2012), 24-28 September 2012, Groningen and Ameland, The Netherlands. 2012.
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abstract = "Light regulates many aspects of plant growth and developmental processes as well as disease resistance in plants. Computational models can be used to provide more detailed insights in how processes are regulated in plants and can contribute to investigating the mechanisms underlying these processes. The current study is performed to assess the influence of light conditions on several horticultural crops of commercial importance by developing systems biology models. Genome-scale modeling of the plant metabolic network in combination with flux balance analysis (FBA) could be suitable to model the influence of lighting conditions on horticultural crops. With FBA, the influence of light dependent enzymes on for instance biomass accumulation could be explored, without the need of hard-to-determine kinetic parameters of these enzymes. FBA was performed on a metabolic network reconstruction of Arabidopsis and generated some preliminary results. For instance, different effects and even opposite effects of catalase activity on biomass accumulation were found for catalase located in different compartments. Constrained-based reconstruction and analysis (COBRA) methods, including FBA, have often been applied for bacteria. COBRA methods are only able to model steady state reaction fluxes, therefore do not incorporate metabolite concentrations. Moreover, FBA performed on metabolic network reconstructions often leads to thermodynamically infeasible loops, resulting in unrealistic predictions. Despite the challenges revealed during this study, reaction fluxes predicted by FBA have often been reported to be quite accurate and efforts have already been made to overcome these limitations. For example, one of the solutions to overcome thermodynamically infeasible loops is by performing a loopless flux variability analysis (FVA), generating a set of boundary conditions that are thermodynamically feasible. It is expected that COBRA methods can be successfully applied for plant species, however, this has only scarcely been done to date and solely for the model plant Arabidopsis.",
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Wijnen, B, Yuan, H, Hilbers, PAJ, Ren, Y, Zhou, G, Yu, J & Riel, van, NAW 2012, Computational modeling of horticultural crops under different light conditions. in Proceedings of the 15th Workshop of the International Study Group for Systems Biology (ISGSB 2012), 24-28 September 2012, Groningen and Ameland, The Netherlands. conference; International Study Group for Systems Biology (ISGSB) 2012, Ameland, Netherlands; 2012-09-24; 2012-09-28, 24/09/12.

Computational modeling of horticultural crops under different light conditions. / Wijnen, B.; Yuan, Huili; Hilbers, P.A.J.; Ren, Y.; Zhou, G.; Yu, J.; Riel, van, N.A.W.

Proceedings of the 15th Workshop of the International Study Group for Systems Biology (ISGSB 2012), 24-28 September 2012, Groningen and Ameland, The Netherlands. 2012.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic

TY - GEN

T1 - Computational modeling of horticultural crops under different light conditions

AU - Wijnen,B.

AU - Yuan,Huili

AU - Hilbers,P.A.J.

AU - Ren,Y.

AU - Zhou,G.

AU - Yu,J.

AU - Riel, van,N.A.W.

PY - 2012

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N2 - Light regulates many aspects of plant growth and developmental processes as well as disease resistance in plants. Computational models can be used to provide more detailed insights in how processes are regulated in plants and can contribute to investigating the mechanisms underlying these processes. The current study is performed to assess the influence of light conditions on several horticultural crops of commercial importance by developing systems biology models. Genome-scale modeling of the plant metabolic network in combination with flux balance analysis (FBA) could be suitable to model the influence of lighting conditions on horticultural crops. With FBA, the influence of light dependent enzymes on for instance biomass accumulation could be explored, without the need of hard-to-determine kinetic parameters of these enzymes. FBA was performed on a metabolic network reconstruction of Arabidopsis and generated some preliminary results. For instance, different effects and even opposite effects of catalase activity on biomass accumulation were found for catalase located in different compartments. Constrained-based reconstruction and analysis (COBRA) methods, including FBA, have often been applied for bacteria. COBRA methods are only able to model steady state reaction fluxes, therefore do not incorporate metabolite concentrations. Moreover, FBA performed on metabolic network reconstructions often leads to thermodynamically infeasible loops, resulting in unrealistic predictions. Despite the challenges revealed during this study, reaction fluxes predicted by FBA have often been reported to be quite accurate and efforts have already been made to overcome these limitations. For example, one of the solutions to overcome thermodynamically infeasible loops is by performing a loopless flux variability analysis (FVA), generating a set of boundary conditions that are thermodynamically feasible. It is expected that COBRA methods can be successfully applied for plant species, however, this has only scarcely been done to date and solely for the model plant Arabidopsis.

AB - Light regulates many aspects of plant growth and developmental processes as well as disease resistance in plants. Computational models can be used to provide more detailed insights in how processes are regulated in plants and can contribute to investigating the mechanisms underlying these processes. The current study is performed to assess the influence of light conditions on several horticultural crops of commercial importance by developing systems biology models. Genome-scale modeling of the plant metabolic network in combination with flux balance analysis (FBA) could be suitable to model the influence of lighting conditions on horticultural crops. With FBA, the influence of light dependent enzymes on for instance biomass accumulation could be explored, without the need of hard-to-determine kinetic parameters of these enzymes. FBA was performed on a metabolic network reconstruction of Arabidopsis and generated some preliminary results. For instance, different effects and even opposite effects of catalase activity on biomass accumulation were found for catalase located in different compartments. Constrained-based reconstruction and analysis (COBRA) methods, including FBA, have often been applied for bacteria. COBRA methods are only able to model steady state reaction fluxes, therefore do not incorporate metabolite concentrations. Moreover, FBA performed on metabolic network reconstructions often leads to thermodynamically infeasible loops, resulting in unrealistic predictions. Despite the challenges revealed during this study, reaction fluxes predicted by FBA have often been reported to be quite accurate and efforts have already been made to overcome these limitations. For example, one of the solutions to overcome thermodynamically infeasible loops is by performing a loopless flux variability analysis (FVA), generating a set of boundary conditions that are thermodynamically feasible. It is expected that COBRA methods can be successfully applied for plant species, however, this has only scarcely been done to date and solely for the model plant Arabidopsis.

M3 - Conference contribution

BT - Proceedings of the 15th Workshop of the International Study Group for Systems Biology (ISGSB 2012), 24-28 September 2012, Groningen and Ameland, The Netherlands

ER -

Wijnen B, Yuan H, Hilbers PAJ, Ren Y, Zhou G, Yu J et al. Computational modeling of horticultural crops under different light conditions. In Proceedings of the 15th Workshop of the International Study Group for Systems Biology (ISGSB 2012), 24-28 September 2012, Groningen and Ameland, The Netherlands. 2012.