Team:Edinburgh/Phage Replication

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<p class="h1">Phage Replication</p>
<p class="h1">Phage Replication</p>
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A basic activity in biorefinery consists of the degradation of cellulose, due to the presence of enzymes. We are not only concerned with the activities and the amount of enzymes, but also with metabolism and activities of bacteriophage.
+
A basic activity in our biorefinery is the degradation of <span class="hardword" id="cellulose">cellulose</span>, due to the presence of enzymes. For our [[Team:Edinburgh/Phage_Display | phage system]], we are not only concerned with the activities and amount of enzymes, but also with the metabolism and activities of <span class="hardword" id="phage">bacteriophage</span>.
 +
 
 +
In particular, it would be good to verify that infected ''E. coli'' in the system don't get outcompeted and die out, since they are necessary for the system to work.
== M13 Replication ==
== M13 Replication ==
 +
<span class="hardword" id="m13">M13</span> is a filamentous bacteriophage: a worm-like virus approximately 1 um long with a 10 nm diameter that infects only ''E. coli''.
 +
*The viral particle consists of a single-stranded, closed circular DNA core surrounded by a protein coat.
 +
*Prior to virus assembly, the coat proteins are fixed in the bacterial membrane by transmembrane domains.
 +
*During assembly, viral DNA is extruded through the membrane and enveloped by coat proteins.
 +
*The ends of the assembled virus are capped by four minor coat proteins, and the length of the filament is covered by several thousand copies of the major coat protein <span class="hardword" id="p8">pVIII</span>.
 +
*The M13 phage attacks ''E. coli'' (host), multiplies in the host cell cytoplasm, and is released without causing the bacteria's death (non-lytic).
 +
== Model construction ==
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*The M13 phage attacks ''E. coli'' (host), multiplies in the host cell cytoplasm, and is released without causing the bacteria’s death (non-lytic).
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As a fundamental rule, '''the rate of change of population = production rate of population - loss rate of population'''
 +
Model for non-lytic M13 phage:
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[[File:Sfmb2e_eTopic_1101_4.jpg|center|thumb|700px|caption|From Slonczewski and Foster (2010).]]
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[[File:Edinburgh-phagerepcycle.png|center|thumb|655px|caption|]]
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== Equations ==
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=== Phage dynamic model ===
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*'''dx/dt=a*k1*x-b*v*x '''  
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+
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*'''dx/dt=ax-bvx '''  
+
      
      
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:(Rate of change of quantity of uninfected ''E. coli'' equals to the uninfected ''E. coli'' replicate itself minus the ''E. coli'' infected by M13 phage.
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: The rate of change in the number of uninfected ''E. coli'' equals the rate at which they replicate, minus the rate at which they become infected by phage.
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*'''dy/dt=ay+bvx '''  
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*'''dy/dt=a*k2*y+b*v*x '''  
      
      
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:(Rate of change of quantity of infected ''E. coli'' equals to the quantity of infected ''E. coli'' replicate itself plus the ''E. coli'' infected by M13 phage.
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: The rate of change in the number of infected ''E. coli'' equals the rate at which they replicate, plus the rate at which uninfected ''E. coli'' become infected by phage.
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*'''dv/dt=cy-bvx-mv '''
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*'''dv/dt=c*y-b*v*x-m*v '''
    
    
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:(Rate of change of quantity of free phage equals to the phage released by infected ''E. coli'' minus the phage which is to infect an ''E. coli'' and the decayed phage.
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: The rate of change in the number of free phage equals the rate at which phage are released by infected ''E. coli'', minus the rate at which phage infect ''E. coli'', and also minus the rate at which phage decay.
: X(t) &mdash; uninfected ''E. coli''
: X(t) &mdash; uninfected ''E. coli''
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: c &mdash; replication coefficient of phage
: c &mdash; replication coefficient of phage
: m &mdash; decay rate of phage
: m &mdash; decay rate of phage
 +
: K1, K2 &mdash; account for the difference of the rate of replication between infected ''E. coli'' and uninfected ''E. coli''
-
 
+
== Simulations ==
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=== Simulations ===
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The [[:File:Matlab_code_phagerep.txt | MATLAB code]] uses a <span class="hardword" id="rk">Runge-Kutta method</span> of order four to solve the system.
The [[:File:Matlab_code_phagerep.txt | MATLAB code]] uses a <span class="hardword" id="rk">Runge-Kutta method</span> of order four to solve the system.
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[[File:Phage dyn.jpg|center|thumb|700px|caption|simulation value: x0=y0=v0=2.00E5]]
 
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:The above figure shows a simulation going over 15 hours.
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We tried modelling a number of different starting conditions.
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:The simulation shows the infected ''E. coli'' population dominates. And the phage population decreases at first then increases.
+
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== Synergy on each phage ==
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[[File:Phage dyn.jpg|center|thumb|700px|caption|Figure1  simulation value: x0=2.00E3 y0=v0=2.00E5]]
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The synergy function, which means having enzymes closer together, is supposed to increase the efficiency of cellulose degradation. We attempted to construct a model of cellulase with regard of synergy.
+
-
For the model we construct, we assume that
+
The simulation above starts with the condition that the amount of uninfected ''E. coli'' is significantly smaller than the other two. The quantity of uninfected ''E. coli'' stays at a low level, which may have economic significance in practice, since our goal is to get free displayed phage. Besides, the figure also shows that the infected ''E. coli'' population dominates the population of free phage.  
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:1. Endoglucanase cuts cellulose chains in the middle,exoglucanase chews away at the end of a cellulase chain, they work together to produce cellobiose.
+
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:2. Because of the proximity of the β-glucosidase and the other two enzymes, as well as the sufficient amount of β-glucosidase on each phage, we assume the mdiate production, cellobiose, is all converted to glucose.
+
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:3. Production, which refers to glucose here, inhibits the action of the above enzymes.
+
-
 
+
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=== Cellulase model ===
+
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Substrate reactivity
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[[File:Phage dyn2.jpg|center|thumb|700px|caption|Figure2  simulation value: x0=v0=2.00E5 y0=2.00E3]]
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:*'''Rs = S/S0'''
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 +
In the above case, we start with a large excess of uninfected ''E. coli''. This results in a large number of phage infecting ''E. coli'' rather than staying free. Therefore, over 15 hours, this simulation produces the least free phage. However, the rate at which free phage are created rises significantly in this case; this is probably because a large number of phage infect ''E. coli'', all of which can release free phage later.
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Rate of reaction
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[[File:Phage dyn3.jpg|center|thumb|700px|caption|Figure3  simulation value: x0=y0=v0=2.00E5]]
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:*'''dG/dt = 1.056*2*(k1r*E1B*S*Rs) /(1+(G/K1IG))'''
+
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:*'''dS/dt = -(k1r*E1B*S*Rs) /(1+(G/K1IG))'''
+
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=== Simulations ===
+
In the above simulation, we start with large numbers of both infected and uninfected ''E. coli''. As the population of free phage increases, more ''E. coli'' are infected by phage. In the first 8 hours, the number of uninfected ''E. coli'' stops rising and begins to fall. After 15 hours, this simulation has produced the most free phage.
-
[[File:Cellulase.jpg|center|thumb|700px|caption|]]
+
From these results it is evident that the population of the bacteriophage M13 primarily depends on the the population of infected ''E. coli'', which is the host of bacteriophage. Additionly, the slowing down of bacterial metabolism seems to have little effect on the reproduction of phage.
-
 
+
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== in biorefinery ==
+
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The idea here is to bring the two models above together, which gives us a panaramic view of cellulose degradation using displayed phage, as well as make it possible to calculate the cost and profit in a biorefinery.
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== References ==
== References ==
 +
* Cattoen C (2003) ''[http://msor.victoria.ac.nz/twiki/pub/Groups/GravityGroup/PreviousProjectsInAppliedMathematics/bacteria-phage_REPORT.pdf  Bacteriaphage mathematical model applied to the cheese industry]'', Massey University, College of Sciences.
 +
* Gregory AW, Sachdev SS (2000) [http://dx.doi.org/10.1006/jmbi.2000.3845 Design and Evolution of Artificial M13 coat Proteins], ''Journal of Molecular Biology'', '''300'''(1): 213-219, doi: 10.1006/jmbi.2000.3845
 +
* Payne RJH, jansen VAA (2001) [http://dx.doi.org/doi:10.1006/jtbi.2000.2198 Understanding Bacteriaphage therapy as a density-dependent kinetic process], ''Journal of Theoretical Biology'', '''208'''(1): 37-48, doi:10.1006/jtbi.2000.2198
* Slonczewski JL, Foster JW (2010) ''[http://www.wwnorton.com/college/biology/microbiology2/ch/11/etopics.aspx Microbiology: An Evolving Science]'', 2nd edition. W. W. Norton &amp; Company
* Slonczewski JL, Foster JW (2010) ''[http://www.wwnorton.com/college/biology/microbiology2/ch/11/etopics.aspx Microbiology: An Evolving Science]'', 2nd edition. W. W. Norton &amp; Company
-
* Robert J.H Payne, Vincent A. A. Jansen(2011)''[ http://personal.rhul.ac.uk/ujba/115/jtb01.pdf:Understanding Bacteriaphage therapy as a density-dependent kinetic process]''
 
-
* Cattoen C (2003) ''[http://msor.victoria.ac.nz/twiki/pub/Groups/GravityGroup/PreviousProjectsInAppliedMathematics/bacteria-phage_REPORT.pdf  Bacteriaphage mathematical model applied to the cheese industry]''
 
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*A.O. Converse, J.D. Optekar(1993) ''[http://onlinelibrary.wiley.com/doi/10.1002/bit.260420120/pdf: A synergistic Kinetics Model for Enzymatic Cellulose Hydrolysis Compared to degree-of-synergism Experimental Results]''
 
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* Kadam KL, Rydholm EC, McMillan JD (2004) [http://onlinelibrary.wiley.com/doi/10.1021/bp034316x/full: Development and Validation of a Kinetic Model for Enzymatic Saccharification of Lignocellulosic Biomass]
 
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Latest revision as of 16:26, 3 October 2011

Phage Replication

A basic activity in our biorefinery is the degradation of cellulose, due to the presence of enzymes. For our phage system, we are not only concerned with the activities and amount of enzymes, but also with the metabolism and activities of bacteriophage.

In particular, it would be good to verify that infected E. coli in the system don't get outcompeted and die out, since they are necessary for the system to work.

Contents

M13 Replication

M13 is a filamentous bacteriophage: a worm-like virus approximately 1 um long with a 10 nm diameter that infects only E. coli.

  • The viral particle consists of a single-stranded, closed circular DNA core surrounded by a protein coat.
  • Prior to virus assembly, the coat proteins are fixed in the bacterial membrane by transmembrane domains.
  • During assembly, viral DNA is extruded through the membrane and enveloped by coat proteins.
  • The ends of the assembled virus are capped by four minor coat proteins, and the length of the filament is covered by several thousand copies of the major coat protein pVIII.
  • The M13 phage attacks E. coli (host), multiplies in the host cell cytoplasm, and is released without causing the bacteria's death (non-lytic).

Model construction

As a fundamental rule, the rate of change of population = production rate of population - loss rate of population

Model for non-lytic M13 phage:

Edinburgh-phagerepcycle.png

Equations

  • dx/dt=a*k1*x-b*v*x
The rate of change in the number of uninfected E. coli equals the rate at which they replicate, minus the rate at which they become infected by phage.
  • dy/dt=a*k2*y+b*v*x
The rate of change in the number of infected E. coli equals the rate at which they replicate, plus the rate at which uninfected E. coli become infected by phage.
  • dv/dt=c*y-b*v*x-m*v
The rate of change in the number of free phage equals the rate at which phage are released by infected E. coli, minus the rate at which phage infect E. coli, and also minus the rate at which phage decay.
X(t) — uninfected E. coli
Y(t) — infected E. coli
V(t) — free phage
a — replication coefficient of E. coli
b — transmission coefficient of phage
c — replication coefficient of phage
m — decay rate of phage
K1, K2 — account for the difference of the rate of replication between infected E. coli and uninfected E. coli

Simulations

The MATLAB code uses a Runge-Kutta method of order four to solve the system.

We tried modelling a number of different starting conditions.

Figure1 simulation value: x0=2.00E3 y0=v0=2.00E5

The simulation above starts with the condition that the amount of uninfected E. coli is significantly smaller than the other two. The quantity of uninfected E. coli stays at a low level, which may have economic significance in practice, since our goal is to get free displayed phage. Besides, the figure also shows that the infected E. coli population dominates the population of free phage.

Figure2 simulation value: x0=v0=2.00E5 y0=2.00E3

In the above case, we start with a large excess of uninfected E. coli. This results in a large number of phage infecting E. coli rather than staying free. Therefore, over 15 hours, this simulation produces the least free phage. However, the rate at which free phage are created rises significantly in this case; this is probably because a large number of phage infect E. coli, all of which can release free phage later.

Figure3 simulation value: x0=y0=v0=2.00E5

In the above simulation, we start with large numbers of both infected and uninfected E. coli. As the population of free phage increases, more E. coli are infected by phage. In the first 8 hours, the number of uninfected E. coli stops rising and begins to fall. After 15 hours, this simulation has produced the most free phage.

From these results it is evident that the population of the bacteriophage M13 primarily depends on the the population of infected E. coli, which is the host of bacteriophage. Additionly, the slowing down of bacterial metabolism seems to have little effect on the reproduction of phage.

References

  • Cattoen C (2003) [http://msor.victoria.ac.nz/twiki/pub/Groups/GravityGroup/PreviousProjectsInAppliedMathematics/bacteria-phage_REPORT.pdf Bacteriaphage mathematical model applied to the cheese industry], Massey University, College of Sciences.
  • Gregory AW, Sachdev SS (2000) [http://dx.doi.org/10.1006/jmbi.2000.3845 Design and Evolution of Artificial M13 coat Proteins], Journal of Molecular Biology, 300(1): 213-219, doi: 10.1006/jmbi.2000.3845
  • Payne RJH, jansen VAA (2001) [http://dx.doi.org/doi:10.1006/jtbi.2000.2198 Understanding Bacteriaphage therapy as a density-dependent kinetic process], Journal of Theoretical Biology, 208(1): 37-48, doi:10.1006/jtbi.2000.2198
  • Slonczewski JL, Foster JW (2010) [http://www.wwnorton.com/college/biology/microbiology2/ch/11/etopics.aspx Microbiology: An Evolving Science], 2nd edition. W. W. Norton & Company