Team:Edinburgh/Modelling

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(Cellulase models)
(Other models and calculations)
 
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<p class="h1">Modelling</p>
<p class="h1">Modelling</p>
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One way of assessing the feasibility of the <span class="hardword" id="synergy">synergistic</span> approach to biorefineries is to use computer ''("in silico")'' modelling. In particular, we would like to confirm that synergistic use of enzymes can make the process of <span class="hardword" id="cellulose">cellulose</span> degradation more efficient.
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One way of assessing the feasibility of the <span class="hardword" id="synergy">synergistic</span> approach to biorefineries is to use <span class="hardword" id="insilico">in silico</span> modelling. In particular, we would like to confirm that synergistic use of enzymes can make the process of <span class="hardword" id="cellulose">cellulose</span> degradation more efficient.
Some other models, calculations, and tools were also developed by the team.
Some other models, calculations, and tools were also developed by the team.
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* [[Team:Edinburgh/Synergy (C model)|C model]] &mdash; a simple model that showed a difference between synergistic and non-synergistic systems
* [[Team:Edinburgh/Synergy (C model)|C model]] &mdash; a simple model that showed a difference between synergistic and non-synergistic systems
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* [[Team:Edinburgh/Synergy (Kappa model)|Kappa model]] &mdash; a more complex model that showed a difference between synergistic and non-synergistic systems
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* [[Team:Edinburgh/Synergy (Kappa model)|Kappa model]] &mdash; a more complex model that also showed a difference
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* [[Team:Edinburgh/Synergy (MATLAB model)|MATLAB model]] &mdash; worked well for the non-synergistic system
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* [[Team:Edinburgh/Synergy (MATLAB model)|MATLAB model]] &mdash; the most complex model, only worked well for the non-synergistic system
===Comparison of different modelling tools===
===Comparison of different modelling tools===
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Within the reactor tasked with degrading cellulose into glucose in the biorefinery, temperature, enzyme concentration, substrate reactivity as well as xylose, cellobiose and glucose inhibition all govern the amount of glucose product. Deterministic modelling using a set of ordinary differential equations highlights the essential kinetic relationship among the enzymes, exo/endo-glucanase and &beta;-glucosidase. By solving these governing equations using the numerical tool MATLAB the level of degradation is qualitatively predicted.
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Our analysis of the advantages and disadvantages of the various modelling approaches, together with conclusions, are on our [[Team:Edinburgh/Model Comparison | model comparison]] page.
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However, we found that the equations we used for the deterministic modelling only gave sensible answers when the model parameters remained within certain limits. Outside those limits, results could be physically impossible; e.g. producing negative amounts of cellobiose.
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As an alternative, <span class="hardword" id="stochastic">stochastic</span> models were created using the Kappa language tool. These incorporate indeterminacy in the evolution of the state of the system. Rules are defined which describe how the model moves from one state to the next.
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==Other models and calculations==
==Other models and calculations==
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===Energy efficiency===
===Energy efficiency===
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Consider this: for a bacteria to produce <span class="hardword" id="phage">phage</span> or <span class="hardword" id="inp">INP</span> requires energy. This energy could have been spent producing extra copies of the cellulases. In order for the phage and cell display projects to make sense, the benefits of synergy must outweigh the cost of producing all these extra proteins.
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Consider this: for bacteria to produce <span class="hardword" id="phage">phage</span> or <span class="hardword" id="inp">INP</span> requires energy. This energy could have been spent producing extra copies of the cellulases. In order for the phage and cell display projects to make sense, the benefits of synergy must outweigh the cost of producing all these extra proteins.
This question can probably be investigated using [[Team:Edinburgh/Efficiency|simple maths and back-of-envelope calculations]]...
This question can probably be investigated using [[Team:Edinburgh/Efficiency|simple maths and back-of-envelope calculations]]...
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One potential benefit of attaching enzymes to the cell surface rather than secreting them into the media is that any mutations that increase enzyme efficiency will specifically benefit the cell with the mutation, as the increased sugar yield will be physically present at the cell. The mutation will thus confer a fitness advantage, potentially allowing it to take over the culture.
One potential benefit of attaching enzymes to the cell surface rather than secreting them into the media is that any mutations that increase enzyme efficiency will specifically benefit the cell with the mutation, as the increased sugar yield will be physically present at the cell. The mutation will thus confer a fitness advantage, potentially allowing it to take over the culture.
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By contrast, if a cell produces a ''secreted'' protein that is of higher efficiency, it will disperse and benefit random cells in the culture.
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By contrast, if a cell produces a ''secreted'' protein that is of higher efficiency, it will disperse and benefit random cells in the culture. To investigate this difference, we created our [[Team:Edinburgh/Artificial Selection|artificial selection]] model.
===Phage replication===
===Phage replication===
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The phage display system requires infected ''E. coli'' to dominate the system and not be outcompeted by uninfected ''E. coli''. Our [[Team:Edinburgh/Phage Replication|phage replication model]] verifies that this is indeed the expected outcome.
The phage display system requires infected ''E. coli'' to dominate the system and not be outcompeted by uninfected ''E. coli''. Our [[Team:Edinburgh/Phage Replication|phage replication model]] verifies that this is indeed the expected outcome.
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==Genetic stability tool==
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==Genetic Stability Tool==
Our projects involve having multiple fusion proteins expressed, each of which uses a genetically identical carrier protein (e.g. ice-nucleation protein or the M13 pVIII gene). The presence of repeated sequences in DNA (i.e. the same sequence in multiple locations) can lead to genetic instability.
Our projects involve having multiple fusion proteins expressed, each of which uses a genetically identical carrier protein (e.g. ice-nucleation protein or the M13 pVIII gene). The presence of repeated sequences in DNA (i.e. the same sequence in multiple locations) can lead to genetic instability.

Latest revision as of 08:20, 12 October 2011

Modelling

One way of assessing the feasibility of the synergistic approach to biorefineries is to use in silico modelling. In particular, we would like to confirm that synergistic use of enzymes can make the process of cellulose degradation more efficient.

Some other models, calculations, and tools were also developed by the team.

Contents

Cellulase models

Approaches

As it happens, our team includes:

  1. Two engineers experienced in using MATLAB.
  2. An informatician who quickly learned the Kappa modelling language.
  3. A biologist who, for no good reason, knows the C programming language.

This led to three different attempts to model cellulase action.

Results

  • C model — a simple model that showed a difference between synergistic and non-synergistic systems
  • Kappa model — a more complex model that also showed a difference
  • MATLAB model — the most complex model, only worked well for the non-synergistic system

Comparison of different modelling tools

Our analysis of the advantages and disadvantages of the various modelling approaches, together with conclusions, are on our model comparison page.

Other models and calculations

Energy efficiency

Consider this: for bacteria to produce phage or INP requires energy. This energy could have been spent producing extra copies of the cellulases. In order for the phage and cell display projects to make sense, the benefits of synergy must outweigh the cost of producing all these extra proteins.

This question can probably be investigated using simple maths and back-of-envelope calculations...

Evolutionary analysis of cell-display vs. secretion

One potential benefit of attaching enzymes to the cell surface rather than secreting them into the media is that any mutations that increase enzyme efficiency will specifically benefit the cell with the mutation, as the increased sugar yield will be physically present at the cell. The mutation will thus confer a fitness advantage, potentially allowing it to take over the culture.

By contrast, if a cell produces a secreted protein that is of higher efficiency, it will disperse and benefit random cells in the culture. To investigate this difference, we created our artificial selection model.

Phage replication

The phage display system requires infected E. coli to dominate the system and not be outcompeted by uninfected E. coli. Our phage replication model verifies that this is indeed the expected outcome.

Genetic Stability Tool

Our projects involve having multiple fusion proteins expressed, each of which uses a genetically identical carrier protein (e.g. ice-nucleation protein or the M13 pVIII gene). The presence of repeated sequences in DNA (i.e. the same sequence in multiple locations) can lead to genetic instability.

However, it ought to be possible to design and synthesise different versions of the genes that code for the same amino acids but use different codons and so are as distinct as possible.

To prove this, we made our Genetic Stability Tool.

References

  • Van Zyl WH, Lynd LR, Den Haan R, McBride EJ (2007) [http://www.springerlink.com/content/4l4m28lp06120253/ Consolidated bioprocessing for bioethanol production using Saccharomyces cerevisiae]. Advances in Biochemical Engineering/Biotechnology 108: 205-235 (doi: 10.1007/10_2007_061).