PKA has 2 catalytic subunits (Tpk) which are encoded by 3 genes: tpk1,tpk2 and tpk3. On binding cAMP, PKA is able to phosphorylate some proteins. However, in mutants like ours, it can be assumed that some of that proteins may not be phosphorylated.
PKA serves as a central regulator of the metabolic and transcriptional status of the yeast cell.
Characteristics of the kinase mutant TPK2 in bioreactors
1. TEAM 3
Characteristics of
the kinase mutant
TPK2 in
bioreactors
Beatriz Barrera
Borja Garnelo
Juan Carlos López
Elliott James Williams
Mr. Lobster
2. Strain TPK2
• YCK401 is a background strain which has the tpk2 gene deleted.
• We know that PKA has 2 catalytic subunits (Tpk) which are encoded by 3
genes: tpk1,tpk2 and tpk3. On binding cAMP, PKA is able to phosphorylate
some proteins. However, in mutants like ours, it can be assumed that some
of that proteins may not be phosphorylated. We’ll see it later.
4. PKA pathway
As we have said, PKA is a heterotetramer composed of two catalytic subunits
and two regulatory subunits. Tpk1, tpk2, tpk3 genes encode the catalytic
subunits and seems to be an important check point in protein phosphorylations.
The activation of PKA via Ras is in response to intracellular acidification, which
helps activating Cyr1 by phosphorylation. Cyr1 modifies ATP into cAMP, that is
going to bind the regulatory subunits, freeing Tpk.
Tpk participates in a negative feed-back. So, when we have high levels of Tpk, it
can activate Pde1,2 (transforms cAMP into an activated form) and inhibite Cyr1,
so free levels of PKA decreases.
Some of the well-characterized substrates for these kinase subunits include
proteins involved in metabolism of storage carbohydrates, enzymes in glycolysis
and gluconeogenesis, and transcription factors regulating stress response,
ribosomal biogenesis, and carbohydrate metabolism. So, PKA serves as a central
regulator of the metabolic and transcriptional status of the yeast cell.
5. VOLUME INOCULATED
We diluted 3 times,
0.33 x 1.5 = Volume x 4.24
so
Volume = 120 ml
10. CO2 Analysis
Variance of the CO2 respect time
Variance of the CO2 respect time
1.400
10
1.200
1.000
dCO2 (%)
1
0.800
dCO2 (%)
0 500 1000 1500 2000 2500 3000
0.600
0.1 0.400
0.200
0.000
0.01 0 500 1000 1500 2000 2500 3000
Time (min) Time (minutes)
Variance of CO2 normalised respect time
Variance of the CO2 normalised respect time
1.200
10
dO2 normalised (%)
dO2 normalised (%)
1.000
0.800
1
0 500 1000 1500 2000 2500 3000 3500 0.600
0.400
0,1
0.200
0.000
0,01
0 500 1000 1500 2000 2500 3000
Time (min)
Time (minutes)
11. Specific CO2 growth rate
Max specific growth rate
y = 0,1747e0,1945x
35
30
25
CO2 (g)
20
15
10
5
0
0,000 5,000 10,000 15,000 20,000 25,000 30,000
Tim e (h)
12. Correlation between O.D and DW
y = 0,545x + 0,2733
5
Dry Weight (g)
4
3
2
1
0
0 1 2 3 4 5 6 7 8
OD600
16. Yield Coefficients (Yse)
We calculate the Yse numerically: Yse on glucose
y = 0,5487x + 0,0351
10,0000
Yse = e / s 9,0000
Ethanol produced(g)
Yse = (e2 - e1) / (s2 - s1)
8,0000
7,0000
6,0000
5,0000
Ethanol (g) 4,0000
3,0000
2,0000
· Glucose (g)
1,0000
0,0000
Yse = 0.581 0,0000 2,0000 4,0000 6,0000 8,0000 10,0000 12,0000 14,0000 16,0000
Glucose used (g)
Yse on galactose
y = 0,4973x + 1,1397
10,0000
9,0000
Ethanol Produced (g)
Ethanol (g) 8,0000
7,0000
6,0000
· Galactose (g)
5,0000
4,0000
Yse = 0.58 3,0000
2,0000
1,0000
0,0000
0 2 4 6 8 10 12 14 16
Galactose Used (g)
17. Yield Coefficients (Ysc)
Ysc on glucose
y = 0,3795x - 0,2286
3
2,5
CO2 (g) 2
1,5
1
0,5
0
0,0000 1,0000 2,0000 3,0000 4,0000 5,0000 6,0000 7,0000
Glucose used (g)
We calculate Ysc numerically:
Ysc = c/s
Ycs = (c2-c1) / (s2-s1)
CO2 (g)
. Glucose
Ycs = 0,352
18. CO2 Analysis
Variance of the CO2 respect time
10
1
dCO2 (%)
0 500 1000 1500 2000 2500 3000
0,1
0,01
Time (min)
Variance of the CO2 normalised respect time
10
dO2 normalised (%)
1
0 500 1000 1500 2000 2500 3000 3500
0,1
0,01
Time (min)
19. TPK2 vs Wild Type
Variance of CO2 normalised
1.200
CO2 analysis
dO2 normalised (%)
1.000
0.800
0.600
0.400
0.200
0.000
0 500 1000 1500 2000 2500 3000
Time (minutes)
Varianc e of C O2 normalis ed (T E AM 1)
0,8
0,7
dC O2 norm alis ed (% )
0,6
0,5
0,4
0,3
0,2
0,1
0
0 5 10 15 20 25 30 35 40 45 50
T im e (h)
20. TPK2 vs Wild Type (Ysx)
Ysx on glucose Ysx on galactose
y = 0,2378x + 0,0141 y = 0,2084x + 0,0314
0,16 0,16
0,14 0,14
Biomass (Cmols)
Biomass (Cmols)
0,12 0,12
0,1 0,1
0,08 0,08
0,06 0,06
0,04 0,04
0,02 0,02
0 0
0,0000 0,0500 0,1000 0,1500 0,2000 0,2500 0,3000 0,3500 0,4000 0,4500 0,5000 0 0,1 0,2 0,3 0,4 0,5
Glucose used (Cmols) Galactose (Cmols)
Ysx on substrates (TEAM 1)
y = 0,1288x + 0,0682
0,12
0,1
Biomass (Cmol)
0,08
Glucose(Cmol)
0,06
Galactose(Cmol)
0,04
y = 0.3407x + 0.0008
0,02
0
0 0,05 0,1 0,15 0,2 0,25 0,3
Substrates used (Cmol)
21. TPK2 vs Wild Type
Yse on glucose
y = 0,5487x + 0,0351
10,0000
Yse on glucose
9,0000
Ethanol produced(g)
8,0000
(Ethanol produced
7,0000
6,0000
5,0000
(g)) 4,0000
3,0000
2,0000
1,0000
0,0000
0,0000 2,0000 4,0000 6,0000 8,0000 10,0000 12,0000 14,0000 16,0000
Glucose used (g)
Y s e on g lu c os e (T E AM 1)
y = 0.5599x + 0.0698
1,2
1,0
E thanol (g /l)
0,8
0,6
0,4
0,2
0,0
0 0,5 1 1,5 2
G luc ose use d (g /l)
22. TPK2 vs Wild Type
Yse on galactose
y = 0,4973x + 1,1397
10,0000
9,0000
Yse on galactose
Ethanol Produced (g)
8,0000
7,0000
(Ethanol produced 6,0000
5,0000
(g)) 4,0000
3,0000
2,0000
1,0000
0,0000
0 2 4 6 8 10 12 14 16
Galactose Used (g)
Y s e o n g alac to s e (T E AM 1)
y = 0.5292x + 0.529
7,0
6,0
5,0
E thanol (g /l)
4,0
3,0
2,0
1,0
0,0
0,0 2,0 4,0 6,0 8,0 10,0 12,0
G a la c tose use d (g /l)
23. TPK2 vs Wild Type
Ysc on glucose
y = 0,3795x - 0,2286
Ysc on glucose
3
(CO2 g)
2,5
2
CO2 (g)
1,5
1
0,5
0
0,0000 1,0000 2,0000 3,0000 4,0000 5,0000 6,0000 7,0000
Glucose used (g)
Ysc on substrates (TEAM 1)
0,35 40
0,3 35
C O 2 produc ed
y = 0.4589x + 0.1533
0,25 30
T ime (h)
(C mol)
25
0,2 G luc os e(C mol)
20
0,15
y = 0.478x - 0.0077 15
0,1 10
G alac tos e(C m
0,05 5 ol)
0 0
0 0,05 0,1 0,15 0,2 0,25 0,3 0,35 0,4 0,45 0,5
S ubs trates us ed (C mol)
24. TPK2 vs SNF1
Variance of CO2 normalised
1.200
dO2 normalised (%)
CO2 analysis
1.000
0.800
0.600
0.400
0.200
0.000
0 500 1000 1500 2000 2500 3000
Time (minutes)
Variance of CO2 normalised (TEAM 2)
10
9
8
7
CO2 (g)
6
5
4
3
2
1
0
0 10 20 30 40 50 60
Time (h)
30. Sample for transcription analysis
The sample we took for transcription analysis was the last one of the first
day, assigned as sample number G3.8. It was obtained in the ninth hour of
the fermentation process. It should be taken at this time because it’s when
all the cells are growing up in an ideal environment.
It is important to know because transcriptome analysis will show what mRNA
was present in the cell during that period of time. A cross comparison with
the dates shows what proteins were being used by the microorganism when
there was glucose in the media.
31. Other aspects
Crabtree effect. When the level of glucose goes beyond a critical
concentration, the ability of the yeast to oxide glucose is diminished and
the microorganism begins to express a mixed metabolism which includes a
respiration pathway (now limited) and a fermentation pathway too (which is
now very active). Nevertheless, there’s no evidence of the Crabtree effect
because of the glucose and ethanol levels (they don’t fit as we expected).
We can see glucose repression of growth on galactose. During the time that
there is glucose in the media, galactose is not used by the culture because
glucose inhibits it. However, when the concentration of glucose arrives to a
critical low level, it stops inhibiting galactose´s use and the culture starts
to grow up with it.
It may be gluconeogenesis because of the use of ethanol behind the
glucose/galactose one.
The strain was able to grow up with both substrates (galactose and ethanol).
This can be seen if you look at the decreasing levels of them.
The strain grew up fast because the levels of the different substrates
went down easily in comparison to the other strains.
39. References
Protein phosphorylation and dephosphorylation. Michael J.R. Starks
Online and in situ monitoring of biomass in submerged cultivations. Olsson,L.
and J.Nielsen.
How Saccharomyces responds to nutrients. Shania Zaman et al.