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Comparison of simulated vs. analytical solutions for degradation of PrP in cell culture
# Eric Minikel
# CureFFI.org
# 2013-12-03
# Comparison of numerically simulated and analytically derived PrP degradation models
# half lives from literature
mrna_thalf = 7 # Pfeiffer 1993 http://www.ncbi.nlm.nih.gov/pubmed/8095862
prpc_thalf = 5 # Borcheldt 1990 http://www.ncbi.nlm.nih.gov/pubmed/1968466/
prpsc_thalf = 30 # Peretz 2001 http://www.ncbi.nlm.nih.gov/pubmed/11507642
division_time = 24 # Ghaemmaghami 2007 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2084281/
# values at initial steady state
l0 = log(2) / mrna_thalf # lambda_0
m0 = log(2) / prpc_thalf # mu_0
v0 = log(2) / prpsc_thalf # nu_0
xi = log(2) / division_time
hrs = 8*24 # number of hours to model and plot. here, set to 8 days
# values of parameters, which you can tweak to explore the effects of diff. compounds
r = (l0+xi) * 0.50 # try setting to 0.50 to reduce transcription rate by half
l = (l0+xi) * 1.00 # try setting to 2.00 to double the mRNA degradation rate
a = (m0+xi) * 1.00
m = (m0+xi) * 1.00
b = (v0+xi) * 1.00
v = (v0+xi) * 1.00
# initial steady state
R0 = 1
S0 = 1
T0 = 1
########### simulation #################
mrna_produced = numeric(hrs)
mrna_degraded = numeric(hrs)
mrna_present = numeric(hrs)
mrna_present[1] = R0
mrna_produced = rep(r, hrs)
for (i in 2:hrs) {
mrna_degraded[i] = l * mrna_present[i-1]
mrna_present[i] = mrna_present[i-1] + mrna_produced[i] - mrna_degraded[i]
}
prpc_produced = numeric(hrs)
prpc_degraded = numeric(hrs)
prpc_present = numeric(hrs)
prpc_present[1] = S0
prpc_produced = a * mrna_present
for (i in 2:hrs) {
prpc_degraded[i] = m * prpc_present[i-1]
prpc_present[i] = prpc_present[i-1] + prpc_produced[i] - prpc_degraded[i]
}
prpsc_produced = numeric(hrs)
prpsc_degraded = numeric(hrs)
prpsc_present = numeric(hrs)
prpsc_present[1] = T0
prpsc_produced = b * prpc_present
for (i in 2:hrs) {
prpsc_degraded[i] = v * prpsc_present[i-1]
prpsc_present[i] = prpsc_present[i-1] + prpsc_produced[i] - prpsc_degraded[i]
}
plottitle = 'Degradation of PrP mRNA, PrPC and PrPSc over time \n 50% transcription reduction, 30% translation reduction and 2x PrPSc degradation'
png('degradation.model.png',width=600,height=400)
# plot mRNA, PrPC and PrPSc values from simulation
plot(1:hrs,mrna_present,pch=1,col='red',ylim=c(0,1),ylab='normalized level',xlab='hours of incubation',main=plottitle,cex.main=.8,xaxt='n')
points(1:hrs,prpc_present,pch=1,col='orange')
points(1:hrs,prpsc_present,pch=1,col='purple')
######### analytical solutions #############
# to compare to simulated solutions, plot 1:hrs vs. 0:(hrs-1) because
# in simulation, knockdown begins at t = 1 hr, while in analytical
# solution, knockdown begins at t = 0 hr
mrna = function(t) {
return ( r/l + (R0 - r/l)*exp(-l*t) )
}
points(1:hrs, mrna(0:(hrs-1)), type='l', lwd=2, col='red')
prpc = function(t) {
if (l == m) {
return ( a*r/(m^2) + a*(R0 - r/m)*t*exp(-m*t) + (S0 - a*r/(m^2))*exp(-m*t) )
} else {
return ( a*r/(m*l) + a*((R0 - r/l)/(m-l))*exp(-l*t) + (S0 - a*r/(m*l) - a*(R0 - r/l)/(m-l))*exp(-m*t) )
}
}
points(1:hrs, prpc(0:(hrs-1)), type='l', lwd=2, col='orange')
prpsc = function(t) {
if (l == m && m == v) {
return ( b*a*r/(v^3) + exp(-v*t)*(T0 - b*a*r/(v^3) - b*a*(R0-r/v)*(1-t^2)/2 + b*(S0-a*r/(v^2))*t ) )
} else if (m == v) {
return ( T0*exp(-v*t) + (b*a*r/(l*v^2))*(1-exp(-v*t)) + (b*a*(R0-r/l)/((v-l)^2))*(exp(-l*t)-exp(-v*t)) +
b*(S0 - a*r/(v*l) - a*(R0 - r/l)/(v-l))*t*exp(-v*t) )
} else if (l == m) {
stop("I didn't solve those equations.")
} else if (l == v) {
stop("I didn't solve those equations.")
} else {
return ( b*a*r/(v*m*l) + b*a*(R0-r/l)/((v-l)*(m-l))*exp(-l*t) + b*(S0 - a*r/(m*l) - a*(R0-r/l)/(m-l))/(v-m)*exp(-m*t) +
(T0 - b*a*r/(v*m*l) - b*a*(R0-r/l)/((v-l)*(m-l)) - b*(S0 - a*r/(m*l) - a*(R0-r/l)/(m-l))/(v-m))*exp(-v*t) )
}
}
points(1:hrs, prpsc(0:(hrs-1)), type='l', lwd=2, col='purple')
legend('topright',c('PrPSc simulated','PrPC simulated','mRNA simulated','PrPSc analytical','PrPC analytical','mRNA analytical'),
col=c('purple','orange','red','purple','orange','red'),
pch=c(1,1,1,NA,NA,NA), lwd=c(NA,NA,NA,2,2,2))
dev.off()
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