Transcript Production kinetics

Engineering of Biological
Processes
Lecture 4: Production kinetics
Mark Riley, Associate Professor
Department of Ag and Biosystems
Engineering
The University of Arizona, Tucson, AZ
2007
Objectives: Lecture 4
• Investigate production kinetics and
limiting factors.
• Characterize product formation based
on yields
Production kinetics
• Classified based on the relationship between
product synthesis and energy generation in
the cell
– Growth associated
– Non-growth associated
– Mixed-growth associated
Products
• Growth-associated
– produced at the same time as cell growth
• constitutive enzymes (ones that are normally present)
– glucose isomerase
• metabolic intermediates
– pyruvate, citrate, acetate
• Non-growth-associated
– takes place during the stationary phase (m=0)
• secondary metabolites
– antibiotics
• Mixed - growth associated
– takes place during growth and stationary phases
• metabolic byproducts
– lactate, ethanol
• secondary metabolites
Product generation
X,
P
X,
P
Time
Growth-associated
X,
P
Time
Mixed-growth
associated
Time
Non-growth
associated
Protein production
• Antibody (MAb) production by mammalian
cells (hybridomas)?
– Growth associated
– Non-growth associated
– Other?
• In 1990, Suzuki and Ollis (NCSU) developed
a structured model that suggested "negatively
growth associated" MAb production kinetics.
Biotechnol Prog. 1990 May-Jun;6(3):231-6.
Suzuki E, Ollis DF.
• Hybridoma cultures where growth was slowed by
either a DNA synthesis inhibitor or by a selective
inhibitor of initiation of nonantibody protein exhibited
50-130% MAb production rate enhancement for
growth slowed up to 50%.
• Experiments inconsistent with this approach showed
other behavior: general inhibition of protein chain
elongation (by cycloheximide) or inhibition of
ribosomal RNA (rRNA) synthesis (by actinomycin D)
each slowed both growth and the specific MAb
production rate, leading to net "positive" growth
associated MAb production rates.
How can we account for this
behavior?
Generalized production equation
dP
 rp  qp X
dt
Direct coupling to energy metabolism
• For products formed in pathways which
generate ATP, rate of production is related to
cellular energy demand.
• Growth is usually the major energy-requiring
function of cells; therefore, if production is
coupled to energy metabolism, product will be
formed whenever there is growth.
Direct coupling to energy metabolism
rp  qp X
dX
rX  μX 
dt
rP qp
Yp/x  
rX
μ
The above is a gross over-simplification of production rates.
Maintenance
• ATP is also required for other activities
called maintenance.
– cell motility
– turnover of cellular components
– adjustment of membrane potentials and
internal pH
Kinetic expressions require growth-associated
and maintenance-associated production
rp  qp X
rp  Yp / xm  mp X
qp  Yp / xm  mp 
Growth assoc.
Non-growth assoc.
YP/X is the theoretical yield of product from biomass, mp is the
specific rate of product formation due to maintenance, and x is
biomass concentration.
'
p/x
Y
rp Yp/xμ  mp X
 
rx
μX
mp
'
Yp/x  Yp/x 
μ
Observed
Theoretical
Result = Y’p/x is higher than anticipated based on growth alone
Effect of incorporating
maintenance terms
• Gives observed yields rather than
theoretical yields
• Accounts for unusual behavior
– negative association with growth
Cell growth stages in a batch
culture
Limited by the depletion of a resource (nutrient, space, oxygen).
Product formation indirectly or not
coupled to energy metabolism
•
Product Formation Indirectly Coupled With Energy Metabolism
– Relationship between product formation and growth can be
complicated. Beyond the scope here.
•
Product Formation Not Coupled With Energy Metabolism
– Production not involving energy metabolism is difficult to relate to
growth because growth and product synthesis are dissociated.
– Rate of formation of non-growth-associated product can be directly
proportional to biomass concentration,
• constant qp
• qp = complex function of growth rate
– empirical equations derived from experiment.
Substrate uptake
• Used for:
– making biomass (x)
– making product (p)
– maintenance (ms)
rp  qp X
rs  qs X
Yp/s
Assumes substrate
used only to make
product (no x or ms)
rP qp
 
rs qs
rP
rs 
Yp/s
Substrate uptake
Cell growth
rs = qs X
Product
formation
rp
rx
rs 

 ms X
Yx / s Yp / s
Maintenance
 m

qp
rs  

 ms  X
Y

Y
x
/
s
p/s


Result = rs is higher than anticipated based on only growth and product formation
Lot's of parameters to estimate
• Need values for:
 m

qp
rs  

 ms  X
Y

Y
x
/
s
p/s


Yield of cells from substrate
'
x/s
Y
'
x/s
Y
rx mX
 
rs qs X
μ

 μ

qp




m
s
Y
Y
x/s
p/s


If there is no product generated (qp=0)
'
x/s
Y
rX

rS
'
x/s
Y

μ
 μ


 ms 
 Yx/s

1
1 ms


'
Yx/s Yx/s μ
Plot (1/Y’x/s) vs. 1/m – slope = ms
With production
'
x/s
Y
μ

 μ

qp




m
s
Y
Y
x/s
p/s


rp decreases Y’x/s

rp
Yp/xμ  mp X
Y  
rs  μ

qp




m
X
s
Y

Y
p/s
 x/s

'
p/s
Cancel out “X” ’s
'
p/s
Y

Y μ  m 


Y μm 

m 
p/x
 μ

Y
 x/s
p
p/x
Yp/s
p
s


Note
Yx/s * Yp/x = Yp/s
To determine the metabolic
parameters
• Need data on:
– substrate uptake with time
• with and without product formation
– product generation with time
• with and without cell growth
– cell growth with time
So, what do these yields yield?
• Basic estimation of nutritional requirements
• Targets for manipulation
– Growth rates
• Maintenance terms
– ms, mp
• Fudge factors to explain why Yp/s > Y’p/s
Maximize production
rp  Yp/xμ  mp X
Growth assoc.
Non-growth assoc.
How do we alter these parameters?
•
•
•
•
Control nutrient and oxygen supply
Cultivation methods – fed batch
Strain selection – high producers
Strain optimization
– Recombinant DNA techniques
– Metabolic engineering
"Growth, metabolic, and antibody production kinetics of hybridoma cell culture:
Effects of serum concentration, dissolved oxygen, and pH in a batch reactor."
The effects of serum, dissolved oxygen (DO) concentration, and medium pH on
hybridoma cell growth, viability, cell density, carbohydrate and amino acid
metabolism, respiration and energy production rates, and antibody production
rates were studied.
Cell growth was enhanced and cell death was decreased by increasing the serum
level. The growth rates followed a Monod-type model with serum being the
limiting component.
Specific glucose, glutamine, and oxygen uptake rates and specific lactate and
ammonia production rates did not change with serum concentrations. Amino
acid metabolism was slightly influenced by the serum level.
Oxidative phosphorylation accounted for about 60% of total energy production. This
contribution, however, increased at low pH values to 76%.
The specific antibody production rate was not growth associated and was
independent of serum and DO concentrations. A 2-fold increase in specific
antibody production rates was observed at pH values below 7.2.
Higher concentrations of antibody were obtained at high serum levels, between 20%
and 40% DO, and at pH 7.20 due to higher viable cell numbers obtained.
•Biotechnol Prog. 1991 Nov-Dec;7(6):481-94.
Ozturk SS, Palsson BO.
Example
• Yield example, modifying m, S
Impact of [S] on [P]
30
P (mu=.1)
P (mu=.2)
25
P (mu=.1) P (mu=.2)
10
0.53
0.93
20
1.04
2.05
50
2.28
6.08
75
2.99
9.83
100
3.51
13.96
150
4.2
21.54
200
4.63
27.3
20
P (g/L)
S
15
10
5
0
0
50
100
S (g/L)
150
200
250
Effects of parameters
↑ S,
↑ mmax,
↓ mmax,
↑Y'p/s,
↓Y'x/s,
↑P
↓P
↓P
↑P
↑P
Impact of Yx/s on product formation
30
P (Y'x/s=.25)
P (Y'x/s=.5)
P (Y'x/s=.75)
25
P [g/L]
20
15
10
5
0
0
30
60
90
S [g/L]
120
150