Quantitative determinants of aerobic glycolysis identify flux through
advertisement
Supplementary material and methods Kinetic mass-balance equations Intracellular metabolites: ππΊπΏπΆπ = π½ππ‘π − πβπ ππ‘ ππΊ6π ππ‘ ππΉ6π ππ‘ ππΉπ΅π ππ‘ = πβπ − ππππ − πππ π¦π − ππ6ππ + πππβππ = ππππ − ππππ = ππππ − ππππ ππΊπ΄3π = ππππ − πππππβ + ππ‘ππ ππ‘ ππ·π»π΄π ππ‘ π13π΅ππΊ ππ‘ π3ππΊ ππ‘ π2ππΊ ππ‘ πππΈπ ππ‘ ππππ ππ‘ ππΏπ΄πΆπ ππ‘ = ππππ − ππ‘ππ − πππππβ − ππππ = πππππβ − ππππ = ππππ − ππππ − ππππβ = ππππ − πππ = πππ − πππ = πππ − πππ₯πβππ − πππβ − ππππ‘ = πππβ − π½ππ‘π ππ΄ππ = −πβπ −ππππ +ππππ + πππ + πππ πππ₯πβππ − πππ‘πππ π + πππ − πππ + ππππ ππππ + ππππ ππππ ππ΄π·π = πβπ +ππππ −ππππ − πππ − πππ πππ₯πβππ + πππ‘πππ π − πππ + 2 ⋅ πππ − ππππ ππππ − ππ‘ ππππ ππππ ππ‘ πππ ππ‘ = −πππππβ + ππππβ − πππ πππ₯πβππ + πππ‘πππ π − ππππ ππππ + 2 ⋅ πππ π¦π −πππβππ πππ΄π·π» ππ‘ = πππππβ − πππβ + ππππβ − πππππβ − ππππ −ππππ πππΆπ ππ‘ ππ2π ππ‘ = −πππ = π½π2 − πππ₯ πππ₯πβππ ππΊπΏπΊ = πππ π¦π − πππβππ ππ‘ πππΈπ ππ‘ ππΊπΏπ ππ‘ = ππππβ − ππβππ‘ − ππ ππ‘ = ππβππ‘ − ππππ‘ ; Extracellular metabolites: ππΊπΏπΆπ ππ‘ ππΏπ΄πΆπ ππ‘ = 0 = πππ ⋅ π½ππ‘π Rate laws for each flux 1. Glucose transport π½ππ‘π = πΊπππ πΊπππ − ) πΎππππ πΎππππ πΊπππ πΊπππ 1+ + πΎππππ πΎππππ ππππ₯ π‘π ( 2. Glucose utilization πΊπΏπΆπ ∗π΄ππ πππ₯ πΊ6π∗π΄π·π −ππβπ πΎπβππ πΎπβππ πΊπΏπΆπ ∗π΄ππ πΊ6π∗π΄π·π 1+ + πΎπβππ πΎπβππ πππ₯ ππβπ πβπ = ( )∗ π πΎβπ ⁄ π (πΎβπ + πΊ6π) 3. Phosphoglucose isomerase activity a. ππππ = ( πΊ6π πππ₯ πΉ6π −πππππ πΎπππππ πΎπππππ πΊ6π πΉ6π 1+ + πΎπππππ πΎπππππ πππ₯ πππππ ) 4. Phosphofructokinase ππππ = ( + πΉ6π∗π΄ππ πππ₯ πΉ16π΅π∗π΄π·π∗π» −πππππ πΎπππππ πΎπππππ πΉ6π∗π΄ππ πΉ16π΅π∗π΄π·π∗π»+ 1+ + πΎπππππ πΎπππππ πππ₯ πππππ 5. Aldolase πππ = πΉ16π΅π πππ₯ πΊπ΄π∗π·π»π΄π −ππππ πΎππππ πΎππππ πΉ16π΅π πΊπ΄π∗π·π»π΄π 1+ + πΎππππ πΎππππ πππ₯ ππππ 6. Triosephosphate isomerase ) ∗ π΄ππ⁄ π (πΎπππ + π΄ππ) π·π»π΄π πππ₯ πΊπ΄π −πππ‘ππ πΎππ‘πππ πΎππ‘πππ π·π»π΄π πΊπ΄π 1+ + πΎππ‘πππ πΎππ‘πππ πππ₯ πππ‘ππ ππ‘ππ = 7. Glyceraldehyde phosphate dehydrogenase πππππβ = + πΊπ΄π∗ππ ∗ππ΄π·+ πππ₯ 13π΅ππΊ∗ππ΄π·π»∗π» −ππππππβ πΎπππππβπ πΎπππππβπ π πΊπ΄π ππ΄π·+ πΊπ΄π∗ππ ∗ππ΄π·+ 13π΅ππΊ ππ΄π·π» 13π΅ππΊ∗ππ΄π·π»∗π»+ 1+ ππππβ + π + ππππβ + + + ππππβ + πΎπππ πΎπππππβπ πΎππππ πΎπππππβπ πΎππππ πΎ πΎ ππππ ππππβ πππ₯ ππππππβ , 8. Phosphoglycerate kinase πππ₯ 13π΅ππΊ ∗ π΄π·π πππ₯ 3ππΊ ∗ π΄ππ πππππ − πππππ πΎπππππ πΎπππππ ππππ = 13π΅ππΊ ∗ π΄π·π 3ππΊ ∗ π΄ππ 1+ + πΎπππππ πΎπππππ 9. Phosphoglycerate mutase ππππ = 3ππΊ 2ππΊ πππ₯ −πππππ πΎπππππ πΎπππππ 3ππΊ 2ππΊ 1+ + πΎπππππ πΎπππππ πππ₯ πππππ 10. Enolase πππ = 2ππΊ πππ₯ ππΈπ −ππππ πΎππππ πΎππππ 2ππΊ ππΈπ 1+ + πΎππππ πΎππππ πππ₯ ππππ 11. Pyruvate kinase πππ₯ ππΈπ ∗ π΄π·π πππ₯ πππ ∗ π΄ππ ππππ − ππππ πΎππππ πΎππππ πππ = ( ) ∗ πΉ16π΅π⁄ π ππΈπ ∗ π΄π·π πππ ∗ π΄ππ (πΎππ + πΉ16π΅π) 1+ + πΎππππ πΎππππ 12. Lactate dehydrogenase πππβ = + πππ ∗ππ΄π·π» πππ₯ πΏπ΄πΆπ ∗ππ΄π· −ππππβ πΎπππβπ πΎπππβπ πππ ππ΄π·π» πππ ∗ππ΄π·π» πΏπ΄πΆπ ππ΄π·+ πΏπ΄πΆπ ∗ππ΄π·+ 1+ ππβ + ππβ + + ππβ + ππβ + πΎπππβπ πΎπππβπ πΎπππ¦π πΎππππβ πΎππππ πΎππππ πππ₯ ππππβ 13. Lactate Transport π½ππ‘π = πΏπ΄πΆπ πΏπ΄πΆπ − ) πΎππππ πΎππππ πΏπ΄πΆπ πΏπ΄πΆπ 1+ + πΎππππ πΎππππ πππ₯ πππ‘π ( 14. OxPhos πππ₯ = πππ πΎπππ¦πππ₯ πππ 1+ πΎπππ¦πππ₯ πππ₯ πππ₯ * π2π πΎππ2π π 1+ 2π πΎππ2π ∗ π΄π·π πΎππππππ₯ π΄π·π 1+ πΎππππππ₯ ; 15. Malate-Aspartate shuttle ππππ = πππ₯ = πππ πΎπππ¦πππ₯ πππ 1+ πΎπππ¦πππ₯ πππ₯ πππ₯ ∗ π2π πΎππ2π π 1+ 2π πΎππ2π ∗ π΄π·π πΎππππππ₯ π΄π·π 1+ πΎππππππ₯ 16. ATPase + π΄ππ πππ₯ π΄π·π∗ππ ∗π» −ππππ‘π πΎπππ‘ππ πΎπππ‘ππ π΄π·π∗ππ ∗π»+ π΄ππ 1+ + πΎπππ‘ππ πΎπππ‘ππ πππ₯ ππππ‘π πππ‘πππ π = 17. Creatine kinase πππ = ππΆπ ∗π΄π·π πππ₯ πΆπ ∗π΄ππ −ππππ πΎππππ πΎππππ ππΆπ ∗π΄π·π πΆπ ∗π΄ππ 1+ + πΎππππ πΎππππ πππ₯ ππππ 18. Adenylate kinase πππ = 2 π΄ππ∗π΄ππ πππ₯ π΄π·π −ππππ πΎππππ πΎππππ π΄ππ∗π΄ππ π΄π·π2 1+ + πΎππππ πΎππππ πππ₯ ππππ 19. Oxygen transport to the cell π½ππ‘π2 = ππ2 (πΆπ2π − πΆπ2π ) 20. De novo synthesis of Serine through 3-phosphoglycerate dehydrogenase (PHGDH). This involves a lumping of 3 reactions 3PG + NAD+ ↔ p-hPYR + NADH+H+, p-hPYR↔pSER, pSER↔SER ππβππβ 3ππΊ ∗ ππ΄π· + ππΈπ ∗ ππ΄π·π» ∗ π» + πππ₯ − πππβππβ πΎππβππβπ πΎππβππβπ = 3ππΊ ππ΄π· + 3ππΊ ∗ ππ΄π· + ππΈπ ππ΄π·π» ππΈπ ∗ ππ΄π·π» ∗ π» + 1 + πβππβ + πβππβ + + πβππβ + πβππβ + πΎππβππβπ πΎ πΎππβππβπ πΎ πΎ πΎ πππ₯ πππβππβ π3ππ ππππ ππ ππ ππππβ 21. De novo GLY synthesis through glycine hydroxymethyltransferase (GHMT, 2.1.2.1). SER↔GLY ππβππ‘ = ππΈπ πΊπΏπ πππ₯ −πππβππ‘ πΎππβππ‘π πΎππβππ‘π ππΈπ πΊπΏπ 1+ + πΎππβππ‘π πΎππβππ‘π πππ₯ πππβππ‘ Parameters The parameters used in the equations and the justifications for their starting points are shown below. Steady state concentrations Starting values of model concentrations were taken from a total of several references with values below(Buxton and Frank 1997; Ercan-Fang, Gannon et al. 2002; Konig, Bulik et al. 2012). Steady State Species concentrations Species Conc., Conc range, mM mM 2.5 3.5-6.9 GLC 0.25 0.05-0.32 G6P 7.73E-02 0.01-0.1 F6P 1.55E-01 0.016-0.030 F16BP 2.00E-03 0.001-0.28 GA3P 4.14E-02 0.01-0.1 DHAP 1.00E-01 13BPG* 0.5 0.05-0.41 3PG 3.00E-02 0.007-0.05 2PG 0.15 0.012-0.27 PEP 5.00E-01 0.02-0.27 PYR 5 0.1-2.5 LAC 3.00E+00 0.5-3.5 ATP 1.18E-02 0.5-1.4 ADP 4.62E-05 0.04 AMP 4.00E+00 3.6-5.7 Pi 1.00E-03 0.03-0.05 NADH 5.49E-01 0.45 NAD+ 1.00E+01 10.0-21.0 PCr 0.04 0.026-0.034 (25mmHg) O2i** 3.00E-01 SER 1.30E-01 GLY 3.00E-01 pSER 7.00E+00 pH Extracellular concentrations 5.00E+00 GLCe 5.00E-01 LACe 3.00E-01 SERe 1.30E-01 GLYe * estimated based on Thermodynamics ** calculated based on Henry's law of solubility of O2 in water at 37°C Rate constants Starting rate constants are shown below. The Km values for substrates in glycolysis are set equal to the steady state substrate concentrations in single-substrate reactions and equal to the product of substrate concentrations in multisubstrate reactions. Km values are reported in units of mM. Vmax values are reported in units of mM/hr. Enzyme GLUT Parameter/value Vmaxtr Kmglc 100 2.1 Vmaxf Kmf 176 7.5 Vmaxf Kmf 858 0.25 Vmaxf Kmf 1769 0.23 Kmr 2.94E-10 Kmr 7.73E-02 Kmr 1.82E-10 Vmaxf 321 Vmaxf 859 Vmaxf 781 Kmf 0.16 Kmf 0.04 Kmnad 0.55 Kmr 8.29E-05 Kmr 0.002 Kmnadh 0.001 PGK Vmaxf 221 Kmr 1.5 PGM Vmaxf 527.895 Vmaxf 1340.08 9 Vmaxf 211.525 Kmf 1.18E03 Kmf 0.5 Kmf 0.03 Kmf 1.77E03 Kmnadh 0.001 Kmlac 3 Kmpyr 0.001 Kmf 3 Kmf 5 Kmf 5 Kmr 0.15 Ka 0.5 Kmnad 0.549 Kmpyr 0.5 Kmo2 0.005 Kmr 4.71E-09 Kmr 2 Kmr 2 Kmadp 0.005 HK PGI PFK ALD TPI GAPDH ENO PK LDH MCT OxPhos ATPase CKase AKase O2transp Vmaxf 434 Vmaxtr 60 Vmax 8.4 Vmaxf 390 Vmaxf 1000 Vmaxf 2000 ko2 164 Ki 0.2 Ka 0.001 Kmgap 2.00E-03 Kmpi 4 Kmbpg 1.00E-01 Kmf 4.392e-3 Kmlac 5 Kmf 5.00E-04 Kmr 2.745 Kmr 0.03 Kmr 0.15 Kmr 1.00E -11 PHGDH GHMT Other parameters Vmaxf Km3pg Kmnad Kmser 0 0.5 0.5 0.1 Vmaxf 0 nop Kmf 1.5 nfad Kmr 0.5 nnad nox 12.5 1.5 2.5 3 Kmnad h 0.01 Kmf Kmr 0.25 1.00E10 Cell uptake and release fluxes Typical uptake and release fluxes were considered(Shestov, Mancuso et al. 2013). Cell Uptake-Release Fluxes mM/h Fglc Fmpc Ftca Fldh Fltr CMRO2 Fatp(cyt) Fatp(mit) WE 80 8.8 10.7 150 150 34 150 174 14.6 Thermodynamics Standard Gibbs Free Energies (dG) were used to constrain fluxes based on Haldane relationships(Goldberg, Tewari et al. 2004; Li, Wu et al. 2011). Reaction HK PGI PFK ALD TPI GAPDH PGK PGM ENO PK LDH CK dG, kJ/mol -19.22 2.78 -15.62 24.64 7.57 2.6 -21.6 6.35 -4.47 -27.18 -23.9 -12.5 AK ATPase 0 -32.42 Supplementary References to Materials and Methods Buxton, R. B. and L. R. Frank (1997). "A model for the coupling between cerebral blood flow and oxygen metabolism during neural stimulation." J Cereb Blood Flow Metab 17(1): 64-72. Ercan-Fang, N., M. C. Gannon, et al. (2002). "Integrated effects of multiple modulators on human liver glycogen phosphorylase a." Am J Physiol Endocrinol Metab 283(1): E29-37. Goldberg, R. N., Y. B. Tewari, et al. (2004). "Thermodynamics of enzyme-catalyzed reactions--a database for quantitative biochemistry." Bioinformatics 20(16): 28742877. Konig, M., S. Bulik, et al. (2012). "Quantifying the contribution of the liver to glucose homeostasis: a detailed kinetic model of human hepatic glucose metabolism." PLoS Comput Biol 8(6): e1002577. Li, X., F. Wu, et al. (2011). "A database of thermodynamic properties of the reactions of glycolysis, the tricarboxylic acid cycle, and the pentose phosphate pathway." Database (Oxford) 2011: bar005. Shestov, A. A., A. Mancuso, et al. (2013). "Metabolic network analysis of DB1 melanoma cells: how much energy is derived from aerobic glycolysis?" Adv Exp Med Biol 765: 265-271.
![lxdfn kmf]6f]klqsf](http://s2.studylib.net/store/data/018554002_1-ad1a1817529e517aa00724ffda1d0f8d-300x300.png)
