TEAM 3     Characteristics of     the kinase mutant          TPK2 in        bioreactors         Beatriz Barrera         Bo...
Strain TPK2•   YCK401 is a background strain which has the tpk2 gene deleted.•   We know that PKA has 2 catalytic subunits...
PKA pathway(Zaman S, et al., Annu. Rev. Genet., 2008)
PKA pathway   As we have said, PKA is a heterotetramer composed of two catalytic subunits    and two regulatory subunits....
VOLUME INOCULATED        We diluted 3 times,     0.33 x 1.5 = Volume x 4.24              so       Volume = 120 ml
Amount of substrate (g/l)                    10,0000                     0,0000                     1,0000                ...
Amount of substrate (g/l)                                                                                                 ...
Weight Of Filter Before                                Weight Of Filter After                    Calculated Weight      Av...
Amount of glucose (g/l)                                                                                                   ...
CO2 Analysis                                                                                                              ...
Specific CO2 growth rate                         Max specific growth rate                                y = 0,1747e0,1945...
Correlation between O.D and DW                                       y = 0,545x + 0,2733                   5  Dry Weight (...
OD600                                                                                                               0     ...
Yield Coefficients (Ysx)  We calculated the Ysx numerically:                                                   Ysx on gluc...
Yield Coefficients (Ysx)                                                                       Ysx on galactose           ...
Yield Coefficients (Yse) We calculate the Yse numerically:                                                                ...
Yield Coefficients (Ysc)                                           Ysc on glucose                                         ...
CO2 Analysis                            Variance of the CO2 respect time            10             1dCO2 (%)              ...
TPK2 vs Wild Type                                                                                                         ...
TPK2 vs Wild Type (Ysx)                                                       Ysx on glucose                              ...
TPK2 vs Wild Type                                                                                                        Y...
TPK2 vs Wild Type                                                                                                      Yse...
TPK2 vs Wild Type                                                                                                         ...
TPK2 vs SNF1                                                                       Variance of CO2 normalised             ...
TPK2 vs SNF1                                                                                                    Ysx on glu...
TPK2 vs SNF1                                                                                                     Yse on gl...
TPK2 vs SNF1                                                                                Ysc on glucose                ...
Comparison table                 Ysx on     Ysx on     Yse on     Yse on     Ysc on    Growth Rate   Growth Rate   Growth ...
Carbon balance           Glucose in      Galactose in    Biomass     Succinato     Accetate      Glycerol        Ethanol  ...
Sample for transcription analysis     The sample we took for transcription analysis was the last one of the first      da...
Other aspects    Crabtree effect. When the level of glucose goes beyond a critical     concentration, the ability of the ...
Snf1 mutation                Tpk2 mutation
Snf1 mutationTpk2 mutation
Tpk2 mutant
Snf1 mutant
References    Protein phosphorylation and dephosphorylation. Michael J.R. Starks    Online and in situ monitoring of bio...
So, we got it! Thank you guys!
Characteristics of the kinase mutant TPK2 in bioreactors
Characteristics of the kinase mutant TPK2 in bioreactors
Characteristics of the kinase mutant TPK2 in bioreactors
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Characteristics of the kinase mutant TPK2 in bioreactors

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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.

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Characteristics of the kinase mutant TPK2 in bioreactors

  1. 1. TEAM 3 Characteristics of the kinase mutant TPK2 in bioreactors Beatriz Barrera Borja Garnelo Juan Carlos López Elliott James Williams Mr. Lobster
  2. 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.
  3. 3. PKA pathway(Zaman S, et al., Annu. Rev. Genet., 2008)
  4. 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. 5. VOLUME INOCULATED We diluted 3 times, 0.33 x 1.5 = Volume x 4.24 so Volume = 120 ml
  6. 6. Amount of substrate (g/l) 10,0000 0,0000 1,0000 2,0000 3,0000 4,0000 5,0000 6,0000 7,0000 8,0000 9,0000 0, 00 2, 00 4, 00 6, 00 8, 0 10 0 ,0 12 0 ,0 14 0 ,0 16 0 ,0 18 0 ,0 20 0 ,0 22 0 ,0 24 0 ,0 26 0 ,0Time (h) 28 0 ,0 30 0 ,0 32 0 ,0 34 0 ,0 36 0 ,0 38 0 ,0 40 0 ,0 42 0 ,0 44 0 ,0 0 Substrate in fermenter as time goes by ethanol glucose galactose
  7. 7. Amount of substrate (g/l) 10,0000 0,0000 1,0000 2,0000 3,0000 4,0000 5,0000 6,0000 7,0000 8,0000 9,0000 0, 1,00 2,00 3,00 0 4, 0 10 120 2 4 6 8 5,00 6,00 7,00 0 8, 0 9,00 10 00 11,00 12,00 13,00 14,00 15,00 16,00 17,00 18,00 19,00 20,00 21,00 22,00 23,00 24,00 25,00 Time (h) 26,00 27,00 28,00 29,00 30,00 31,00 32,00 33,00 34,00 35,00 36,00 37,00 38,00 39,00 40,00 Accumulation of substrates in cells 41,00 42,00 43,00 44,00 45,00 Amount of substrate being used in Mr Lobster by the cells ,0 0 glucose ethanol galactose ethanol glucose galactose
  8. 8. Weight Of Filter Before Weight Of Filter After Calculated Weight Average Dry weightTime (h) Filter 1 Filter 2 Filter 1 Filter 2 Biomass (g) weight Filter 2 No weight weight Filter 2 No weight Filter 1 Filter 2 Weight (*) (g/l) Filter 1 No Filter 1 No 0.00 0.2810176 0.4215264 1.00 0.367483 0.5512245 2.00 0.2893735 0.43406025 3.00 0.3126247 0.46893705 4.00 7 0.0776 7 0.0806 0.003 0.3 0.3544042 0.5316063 5.00 2 0.0769 6 0.0776 2 0.0788 6 0.0806 0.0019 0.003 0.245 0.6297856 0.9446784 6.00 1 0.078 8 0.0784 1 0.0785 8 0.08 0.0005 0.0016 0.105 0.8187016 1.2280524 7.00 3 0.0772 9 0.0785 3 0.0782 9 0.0832 0.001 0.0047 0.285 0.995992 1.493988 8.00 19 0.0778 24 0.0779 19 0.0855 24 0.0788 0.0077 0.0009 0.43 1.3389472 2.0084208 22.50 12 0.0774 16 0.078 12 0.0992 16 0.0794 0.0218 0.0014 1.16 2.3213104 3.4819656 23.50 11 0.0774 10 0.0778 11 0.0943 10 0.0783 0.0169 0.0005 0.87 2.0074192 3.0111288 24.50 2.2399312 3.3598968 26.50 22 0.078 22 0.1011 0.0231 0.0231 2.31 2.2631824 3.3947736 27.50 25 0.078 26 0.078 25 0.0993 26 0.0996 0.0213 0.0216 2.145 2.3154976 3.4732464 45.50 23 0.0782 21 0.0781 23 0.1033 21 0.1022 0.0251 0.0241 2.46 2.7630832 4.1446248 4,5 4 Cell concentration (g) 3,5 3 2,5 2 1,5 1 0,5 0 0,00 5,00 10,00 15,00 20,00 25,00 30,00 35,00 40,00 45,00 50,00 Time (h)
  9. 9. Amount of glucose (g/l) 10,0000 0,0000 1,0000 2,0000 3,0000 4,0000 5,0000 6,0000 7,0000 8,0000 9,0000 0,00 1,00 2,00 3,00 4,00 5,00 6,00 7,00 8,00 9,00 10,00 11,00 12,00 13,00Time (h) 14,00 15,00 16,00 17,00 18,00 19,00 20,00 21,00 22,00 23,00 24,00 25,00 26,00 27,00 1 10 0,1 Dry weight (g/l) glucose Correlation between glucose and DW Average Dry Weight
  10. 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. 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. 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
  13. 13. OD600 0 1 2 3 4 5 6 7 8 0, 1, 00 2, 00 3, 00 4, 00 5, 00 6, 00 7, 00 8, 00 OD600 9 00 10 , 00 0.1 1 10 11 ,00 2 12 ,00 13 ,00 14 ,00 15 ,00 16 ,00 17 ,00 18 ,00 19 ,00 3 20 ,00 21 ,00 22 ,00 23 ,00 24 ,00 25 ,00 26 ,00 4 T ime (h) 27 ,00 28 ,00 29 ,00 30 ,00 31 ,00 32 ,00 33 ,00 5 34 ,00 35 ,00 36 ,00 37 ,00 38 ,00 39 ,00Time (h) 40 ,00 41 ,00 6 42 ,00 y = 0.1057e0.4407x 43 ,00 44 ,00 45 ,00 ,0 0 Cell density in the fermenter as time increases 0 1 2 3 7 0,5 1,5 2,5 Max Specific growth rate on glucose 8 Average Weight (*) R eal OD600 9
  14. 14. Yield Coefficients (Ysx) We calculated the Ysx numerically: Ysx on glucose y = 0,218x + 0,3879 Yxs = x / s 5 Yxs = (x2 - x1) / (s2 - s1) 4 Dry Weigh (g) 3 Dry Weight (g) 2 1 · Glucose (g) 0 0,0000 2,0000 4,0000 6,0000 8,0000 10,0000 12,0000 14,0000 16,0000 Yxs = 0.218 Glucose (g) Ysx on glucose Dry Weight (Cmols) y = 0,2378x + 0,0141 0,16 0,14 Biomass (Cmols) · Glucose (Cmol) 0,12 0,1 Yxs = 0.2378 0,08 0,06 0,04 0,02 0 0,0000 0,0500 0,1000 0,1500 0,2000 0,2500 0,3000 0,3500 0,4000 0,4500 0,5000 Glucose used (Cmols)
  15. 15. Yield Coefficients (Ysx) Ysx on galactose y = 0,1911x + 0,8633 Dry Weight (g) 5 4 · Galactose (g) DW (g) 3 Yxs = 0.2175 2 1 0 0 2 4 6 8 10 12 14 16 Galactose used (g) Ysx on galactose Dry Weight (Cmols) y = 0,2084x + 0,0314 0,16 0,14 Biomass (Cmols) · Galactose (Cmol) 0,12 0,1 Yxs = 0.2373 0,08 0,06 0,04 0,02 0 0 0,1 0,2 0,3 0,4 0,5 Galactose (Cmols)
  16. 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. 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. 18. CO2 Analysis Variance of the CO2 respect time 10 1dCO2 (%) 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. 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. 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. 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. 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. 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. 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)
  25. 25. TPK2 vs SNF1 Ysx on glucose y = 0,2378x + 0,0141 0,16 0,14 Biomass (Cmols) 0,12 Ysx on glucose 0,1 0,08 (Biomass Cmol) 0,06 0,04 0,02 0 0,0000 0,0500 0,1000 0,1500 0,2000 0,2500 0,3000 0,3500 0,4000 0,4500 0,5000 Glucose used (Cmols) Ysx on glucose (TEAM 2) y = 0.1347x + 0.0094 0.018 0.016 0.014 Biomass (c-mol) 0.012 0.01 0.008 0.006 0.004 0.002 0 0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 0.045 0.05 Glucose (c-mol)
  26. 26. TPK2 vs SNF1 Yse on glucose y = 0,5487x + 0,0351 10,0000 9,0000 Ethanol produced(g) 8,0000 7,0000 Yse on glucose 6,0000 5,0000 (Ethanol produced 4,0000 3,0000 g) 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) Yse on glucose (TEAM 2) y = 0.2116x + 0.2557 2.5 2 Ethanol (g) 1.5 1 0.5 0 0 1 2 3 4 5 6 7 8 9 10 Glucose (g)
  27. 27. TPK2 vs SNF1 Ysc on glucose y = 0,3795x - 0,2286 3 Ysc on glucose 2,5 (CO2 g) 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 glucose (TEAM 2) y = 0.5157x - 0.0888 0.9 0.8 0.7 0.6 CO2 (g) 0.5 0.4 0.3 0.2 0.1 0 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 Glucose (g)
  28. 28. Comparison table Ysx on Ysx on Yse on Yse on Ysc on Growth Rate Growth Rate Growth Rate Strain glucose galactose glucose galactose glucose glucose galactose Ethanol Biomass (gg-1) (gg-1) (gg-1) (gg-1) (gg-1) (h-1) (h-1) (h-1) (gl-1) WT - Team 1 0,296 0,112 0,55 n.a 0,66 0,44 0,045 0,07 2,66 WT - Team 4 0,124 0,376 0,312 0 0,758 0,328 0,057 0 2,8 SNF1 - Team 2 0,12 0 0,21 0 0,51 0,11 0 0 1,61 SNF1 - Team 5 0,12 0 0,24 0 0,23 0,13 0 0 1,2 TPK2 - Team 3 0,218 0,191 0,549 0,49 0,378 0,43 n.a n.a 2,76 TPK2 - Team 6 0,15 0,23 0,23 0,43 0,48 0,26 0,08 0,1 3,83
  29. 29. Carbon balance Glucose in Galactose in Biomass Succinato Accetate Glycerol Ethanol Ethanol CO2 CO2Time (h) ferm. (Cmol) ferm. (Cmols) (Cmols) (Cmols) (Cmols) (Cmols) produced (g) (Cmols) prod. (g) prod. (Cmol) 0,00 0,4756 0,469451327 0,01832823 0,0027 0,5003 0,0334 0 0,0000 1,00 0,459047551 0,459613822 0,02004453 0,0026 0,5356 0,0357 0,00079691 0,0000 2,00 0,452636162 0,461264404 0,01578401 0,0018 0,0026 0,0007 0,6397 0,0426 0,00103598 0,0000 3,00 0,440609389 0,461917886 0,01705226 0,0022 0,0026 0,0007 0,7592 0,0506 0,00127505 0,0000 4,00 0,424343979 0,462041649 0,01933114 0,0031 0,0025 0,9289 0,0619 0,00135475 0,0000 5,00 0,399134745 0,463599485 0,03435194 0,0039 0,0022 1,2067 0,0804 0,00135475 0,0000 6,00 0,366107147 0,463174676 0,04465645 0,0047 0,0021 1,5617 0,1041 0,0128568 0,0003 7,00 0,323906116 0,471833846 0,05432684 0,0060 0,0020 0,0016 2,0831 0,1389 0,01684134 0,0004 8,00 0,255707175 0,45674963 0,07303348 0,0072 0,0018 0,0021 2,7337 0,1822 0,02024149 0,0005 22,50 0 0,039912279 0,12661693 0,0342 0,0008 0,0115 9,1454 0,6097 0,01973678 0,0004 23,50 0 0,010723918 0,10949559 0,0357 0,0009 0,0119 9,3072 0,6205 0,01389278 0,0003 24,50 0 0,00927677 0,12217807 0,0349 0,0020 0,0124 9,1026 0,6068 0,00286887 0,0001 26,50 0 0,007590914 0,12344631 0,0350 0,0033 0,0147 8,5337 0,5689 0,00257667 0,0001 27,50 0 0,006428087 0,12629987 0,0344 0,0018 0,0168 8,0572 0,5371 0,00268293 0,0001 45,50 0 0,006743729 0,15071363 0,0300 0,0020 0,0221 3,6456 0,2430 0,00265636 0,0001 INPUT SUM Difference % error 0,9994 0,99939992 0,9770 0,02239906 2,23990569 0,99939992 0,9775 0,02192459 2,19245869 0,99939992 0,9758 0,02362163 2,36216317 0,99939992 0,9732 0,02621192 2,62119219 0,99939992 0,9836 0,01577527 1,57752747 0,99939992 0,9851 0,01426147 1,42614745 0,99939992 0,9989 0,00046984 0,04698416 0,99939992 0,9794 0,02003938 2,00393766 0,99939992 0,8232 0,17633321 17,6333212 0,99939992 0,7895 0,21001142 21,0011419 0,99939992 0,7877 0,2118361 21,1836104 0,99939992 0,7530 0,24658696 24,6586964 0,99939992 0,7229 0,27664874 27,6648736 0,99939992 0,4547 0,54501207 54,5012066
  30. 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. 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.
  32. 32. Snf1 mutation Tpk2 mutation
  33. 33. Snf1 mutationTpk2 mutation
  34. 34. Tpk2 mutant
  35. 35. Snf1 mutant
  36. 36. 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.
  37. 37. So, we got it! Thank you guys!

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