Lecture #21. Exploring Network Func7ons

Size: px
Start display at page:

Download "Lecture #21. Exploring Network Func7ons"

Transcription

1 Lecture #1 Exploring Network Func7ons

2 Outline Parsing te overall network Many simultaneous metabolic func7ons Core E. coli Model Op7mal ATP produc7on Op7mal NAD(P)H produc7on Op7mal syntesis of biosynte7c precursors Func7onal tes7ng sets

3 Wat to explore PARSING NETWORK FUNCTIONS

4 Four overall func7ons of cellular metabolism J. Teoret. Biol.165: (1993)

5 Core E. coli Metabolism

6 Consumption of ATP is represented troug a demand reaction: ATP + H O v ATPM! ADP + P i + H + (1) Te objective function for linear optimization is: Z = v ATPM () OPTIMAL ATP PRODUCTION

7 Op7mal aerobic ATP produc7on: core E. coli Flux map GLCpts (1) EX_glc(e) (-1) glc-d[e] EX_mal-L(e) (0) MALt_ (0) FUMt_ (0) fum[e] [e] mal-l[e] EX_fum(e) (0) [e] [e] THD (0) Te Objecve ATPS4r (13.5) PGK () ATPM (17.5) FRUpts (0) fru[e] EX_fru(e) (0) pep pyr p p o pyr g6p 6pgl G6PDHr (0) PGL (0) PGI (1) pep f6p FBP (0) PFK (1) TKT (0) o fdp FBA (1) dap g3p p co p 6pgc ru5p-d GND (0) RPI (0) RPE (0) xu5p-d r5p TKT1 (0) s7p g3p TALA (0) p NADTRHD () p o amp o ADK1 (0) ATPM (17.5) 0.5 o o q8 q8 ATPS4r (13.5) 4 [e] Ot (6) o[e] EX_o(e) (-6) CYTBD (1) [e] EX_(e) (0) PYK (1) SUCOAS () ATPM (17.5) Node Maps PFK (1) TPI (1) e4p f6p [e] GAPD () NADH16 (10) 13dpg FRD7 (0) 4 3 [e] PGK (-) q8 q8 EX_succ(e) (0) 3pg fum SUCDi () o SUCCt3 (0) succ [e] succ[e] SUCOAS (-) PGM (-) SUCCt_ (0) FUM () pg [e] mal-l AKGtr (0) EX_akg(e) (0) ENO () suc co ME1 (0) co akg[e] o pep o p MALS (0) [e] ac co MDH () AKGDH () PPC (0) ME (0) o co p amp p o co p glx EX_glu-L(e) (0) PPCK (0) n4 glu-l glu-l[e] akg PPS (0) p GLUDy (0) GLUtr (0) oaa co PYK (1) [e] p o co n4 ICL (0) n4 o GLUN (0) EX_pyr(e) (0) acald GLNS (0) PDH () ICDHyr () CS () acon-c icit p ac o pyr[e] pyr ACALD (0) PYRtr (0) PFL (0) cit [e] PTAr (0) for ACONTa () ACONTb () p GLNabc (0) EX_gln-L(e) (0) o GLUSy (0) gln-l LDH_D (0) actp eto ALCDx (0) gln-l[e] ACKr (0) o lac-d ac o co n4 ACtr (0) ATPS4r (3 x 13.5) CS () GAPD () MDH () PFK (1) ATPase leung protons in CYTBD ( x 1) NADH16 (4 x 10) PYK (1) Pumng protons out D-LACt (0) [e] lac-d[e] EX_lac-D(e) (0) FORt (0) FORti (0) o[e] [e] [e] [e] ACALDt (0) ETOHtr (0) HOt (-6) COt (-6) co[e] NH4t (0) n4[e] PItr (0) for[e] [e] acald[e] eto[e] ac[e] [e] EX_eto(e) (0) EX_for(e) (0) EX_ac(e) (0) EX_co(e) (6) EX_acald(e) (0) EX_o(e) (6) EX_n4(e) (0) EX_(e) (0) CYTBD ( x 1) NADH16 (3 x 10) [e] ATPS4r (4 x 13.5)

8 Te op7mal solu7on: te flux values, te reduced costs, and te sadow prices # Reaction Flux Reduced # Reaction Flux Reduced # Reaction Flux Reduced # Metabolite Sadow # Metabolite Sadow Name Value Cost Name Value Cost Name Value Cost Name Price Name Price 1 ACALD EX_lac_D(e) ME dpg[c] 9 37 gln-l[e] 11.5 ACALDt EX_mal_L(e) ME 0 0 pg[c] 8 38 glu-l[c] ACKr EX_n4(e) NADH pg[c] 8 39 glu-l[e] 1 4 ACONTa 0 36 EX_o(e) NADTRHD 0 4 6pgc[c] glx[c] ACONTb 0 37 EX_(e) NH4t pgl[c] o[c] 0 6 ACtr EX_pyr(e) Ot ac[c] o[e] 0 7 ADK EX_succ(e) PDH 0 7 ac[e] [c] AKGDH 0 40 FBA PFK acald[c] [e] 0 9 AKGtr FBP PFL acald[e] icit[c] ALCDx FORt PGI ac[c] lac-d[c] 8 11 ATPM FORti PGK acon-c[c] lac-d[e] ATPS4r FRD PGL actp[c] mal-l[c] Biomass FRUpts PGM [c] mal-l[e] COt FUM 0 78 PItr akg[c] [c] CS 0 47 FUMt_ PPC akg[e] [c] 0 16 CYTBD G6PDHr PPCK amp[c] - 5 p[c] D_LACt GAPD 0 81 PPS [c] 0 53 p[c] 0 18 ENO 0 50 GLCpts PTAr cit[c] n4[c] 0 19 ETOHtr GLNS PYK co[c] 0 55 n4[e] 0 0 EX_ac(e) GLNabc PYRtr co[e] 0 56 o[c] 0 1 EX_acald(e) GLUDy RPE [c] 0 57 o[e] 0 EX_akg(e) GLUN RPI 0 0 dap[c] oaa[c] 7 3 EX_co(e) GLUSy SUCCt_ e4p[c] pep[c] 8 4 EX_eto(e) GLUtr SUCCt eto[c] [c] EX_for(e) GND SUCDi 0 5 eto[e] [e] 0 6 EX_fru(e) HOt SUCOAS f6p[c] pyr[c] EX_fum(e) ICDHyr 0 91 TALA fdp[c] 0 63 pyr[e] EX_glc(e) ICL THD for[c] 0 64 q8[c] 0 9 EX_gln_L(e) LDH_D TKT for[e] 0 65 q8[c] EX_glu_L(e) MALS TKT fru[e] r5p[c] EX_(e) MALt_ TPI fum[c] ru5p-d[c] EX_o(e) MDH 0 3 fum[e] s7p[c] g3p[c] succ[c] g6p[c] succ[e] glc-d[e] suc[c] gln-l[c] xu5p-d[c]

9 Op7mal aerobic ATP produc7on: some caracteris7cs 13.5 ATP made by ATP syntase, 4 net made by substrate level posporyla7on for a total of 17.5 P/O ra7o is 5/4, 5 protons pumped out for eac electron pair, 4 protons pumped in for eac ATP made Proton transmembrane balancing determines ATP yield ATPS4r (13.5) PGK () PYK (1) SUCOAS () ATPM (17.5) PS4r (3 x 13.5) CS () GAPD () MDH () ATPM (17.5) PFK (1) CYTBD ( x 1) NADH16 (4 x 10) PYK (1) 4 protons needed to make 1 ATP, so [c] sadow price is PFK (1) CYTBD ( x 1) ATPS4r (4 x 13.5) ADH16 (3 x 10) [e]

10 Op7mal aerobic ATP produc7on: Sadow prices for te intermediates correspond to te ATP yield on tem Oter sadow prices demonstrate importance of protons: succ[c] SP = 8.75, succ[e] = 8.5, two protons pumped in wit every succinate Water is made some caracteris7cs Cells can produce about pw/µ 3 Te yield of 38 ATP/glucose seen in text books assumes a P/O ra7o of 3 and no systemic network constraints see analysis in yeast, PNAS 100: (003)

11 Te op7mal solu7on: some observa7ons # Reaction Flux Reduced # Reaction Flux Reduced # Reaction Flux Reduced # Metabolite Sadow # Metabolite Sadow Name Value Cost Name Value Cost Name Value Cost Name Price Name Price 1 ACALD EX_lac_D(e) ME dpg[c] 9 37 gln-l[e] 11.5 ACALDt EX_mal_L(e) ME 0 0 pg[c] 8 38 glu-l[c] ACKr EX_n4(e) NADH pg[c] 8 39 glu-l[e] 1 4 ACONTa 0 36 EX_o(e) NADTRHD 0 4 6pgc[c] glx[c] ACONTb 0 37 EX_(e) NH4t pgl[c] o[c] 0 6 ACtr EX_pyr(e) Ot ac[c] o[e] 0 7 ADK EX_succ(e) PDH 0 7 ac[e] [c] AKGDH 0 40 FBA PFK acald[c] [e] 0 9 AKGtr FBP PFL acald[e] icit[c] ALCDx FORt PGI ac[c] lac-d[c] 8 11 ATPM FORti PGK acon-c[c] lac-d[e] ATPS4r FRD PGL actp[c] mal-l[c] Biomass FRUpts PGM [c] mal-l[e] COt FUM 0 78 PItr akg[c] [c] CS 0 47 FUMt_ PPC akg[e] [c] 0 16 CYTBD G6PDHr PPCK amp[c] - 5 p[c] D_LACt GAPD 0 81 PPS [c] 0 53 p[c] 0 18 ENO 0 50 GLCpts PTAr cit[c] n4[c] 0 19 ETOHtr GLNS PYK co[c] 0 55 n4[e] 0 0 EX_ac(e) GLNabc PYRtr co[e] 0 56 o[c] 0 1 EX_acald(e) GLUDy RPE [c] 0 57 o[e] 0 EX_akg(e) GLUN RPI 0 0 dap[c] oaa[c] 7 3 EX_co(e) GLUSy SUCCt_ e4p[c] pep[c] 8 4 EX_eto(e) GLUtr SUCCt eto[c] [c] EX_for(e) GND SUCDi 0 5 eto[e] [e] 0 6 EX_fru(e) HOt SUCOAS f6p[c] pyr[c] EX_fum(e) ICDHyr 0 91 TALA fdp[c] 0 63 pyr[e] EX_glc(e) ICL THD for[c] 0 64 q8[c] 0 9 EX_gln_L(e) LDH_D TKT for[e] 0 65 q8[c] EX_glu_L(e) MALS TKT fru[e] r5p[c] EX_(e) MALt_ TPI fum[c] ru5p-d[c] EX_o(e) MDH 0 3 fum[e] s7p[c] g3p[c] succ[c] g6p[c] succ[e] glc-d[e] suc[c] gln-l[c] xu5p-d[c]

12 Systemic P/O in Yeast Results Te in silico model can be used to assess network properties suc as te P O ratioandenergymaintenancecostsandtocompute wole-cell functions. Te efficiency of aerobic resration is measured by te P O ratio.experimentalstudiesofisolated mitocondria ave sown tat S. cerevisiae lacks site I proton translocation (8). Consequently, estimation of te maximum teoretical or mecanistic yield of te ETS alone gives a P O ratio of 1.5 for oxidation of NADH in S. cerevisiae grown on glucose (8). However, based on experimental measurements, it as been determined tat te net in vivo P Oratiois 0.95 (8). Tis difference is generally attributed to te use of te mitocondrial transmembrane proton gradient needed to drive metabolite excange (suc as te proton-coupled translocation of pyruvate) across te inner mitocondrial membrane. In te reconstructed network, wic contains no proton leakage, 1.5 molecules of ATP are generated via te ETS. As complete oxidation of glucose leads to donation of 1 electron pairs (10 NADH and FADH )toteelectrontransportcain,tein silico P O ratiois1.04foroxidationofnadhandfadh during growt on glucose, i.e., , agreeing well wit te measured value witout including any proton leakage. Te network-based computation systemically accounts for all te steps required to import and export compounds from te mitocondria, computing a net overall P O ratio. Cells require energy for bot growt- and non-growtassociated activities (9). Te energy requirement for te formation of biomass as been measured experimentally for S. cerevisiae, andreportedvaluesrangefrom6.5to71.4mmolof ATP gdw (9, 30). A network-based calculation procedure of te growt-associated energy requirement as been developed (31), and wen applied to te reconstructed S. cerevisiae network, a value of 69. mmol of ATP gdw was computed (see Metods), wic falls in te range of experimentally determined values. Energy required for precursor metabolite formation and macromolecule polymerization can be calculated from te biosyntetic composition of te cell. Te model-based ATP requirement is entirely network-dependent and was derived from te in silico calculations. Te reconstructed metabolic network of S. cerevisiae can be PNAS 100: (003)

13 Op7mal anaerobic ATP produc7on: core E. coli ACKr (1) ATPM (.75) Flux map Te Objec7ve PGK () ATPS4r (0.5) GLCpts (1) EX_glc(e) (-1) glc-d[e] EX_mal-L(e) (0) EX_fum(e) (0) mal-l[e] MALt_ (0) FUMt_ (0) fum[e] [e] [e] [e] THD (0) PYK (1) PFK (1) A o amp pep pyr p p o p ATPS4r (-0.5) p co o 4 pyr [e] g6p 6pgl 6pgc ru5p-d ADK1 (0) ATPM (.75) FRUpts (0) G6PDHr (0) PGL (0) GND (0) p NADTRHD (0) p fru[e] PGI (1) RPI (0) EX_fru(e) (0) RPE (0) pep f6p xu5p-d r5p Ot (0) 0.5 TKT1 (0) FBP (0) o o[e] PFK (1) o EX_o(e) (0) TKT (0) o CYTBD (0) g3p fdp s7p [e] FBA (1) TALA (0) q8 q8 EX_(e) (3) dap g3p e4p f6p TPI (1) [e] GAPD () NADH16 (0) 13dpg FRD7 (0) 4 3 [e] PGK (-) q8 q8 EX_succ(e) (0) 3pg fum SUCDi (0) o SUCCt3 (0) succ [e] succ[e] SUCOAS (0) PGM (-) SUCCt_ (0) FUM (0) pg [e] mal-l AKGtr (0) EX_akg(e) (0) ENO () suc co co ME1 (0) akg[e] o pep o p MALS (0) [e] ac co MDH (0) AKGDH (0) PPC (0) ME (0) o co p amp p o co p glx EX_glu-L(e) (0) PPCK (0) n4 glu-l glu-l[e] akg PPS (0) p GLUDy (0) GLUtr (0) oaa co PYK (1) [e] p o co n4 n4 o ICL (0) GLUN (0) EX_pyr(e) (0) acald PDH (0) ICDHyr (0) GLNS (0) CS (0) acon-c icit p ac o pyr[e] pyr ACALD (-1) PYRtr (0) PFL () cit [e] PTAr (1) for ACONTa (0) ACONTb (0) p GLNabc (0) EX_gln-L(e) (0) o GLUSy (0) gln-l LDH_D (0) actp eto gln-l[e] ALCDx (-1) ACKr (-1) o lac-d ac o co n4 ACtr (-1) B ATPM (.75) GAPD () PFK (1) Node Maps ACALD (1) ACtr (1) ALCDx (1) ATPS4r (3 x 0.5) ETOHtr (1) PYK (1) D-LACt (0) FORt (0) FORti () [e] lac-d[e] EX_lac-D(e) (0) o[e] [e] [e] ACALDt (0) ETOHtr (-1) [e] HOt (1) COt (0) co[e] NH4t (0) n4[e] PItr (0) for[e] [e] acald[e] eto[e] ac[e] [e] EX_eto(e) (1) EX_for(e) () EX_ac(e) (1) EX_co(e) (0) EX_acald(e) (0) EX_o(e) (-1) EX_n4(e) (0) EX_(e) (0) ACtr (1) ATPS4r (4 x 0.5) [e] EX_(e) (3) ETOHtr (1)

14 Op7mal anaerobic ATP produc7on: some caracteris7cs.75 net ATP produced, all by substrate level posporyla7on net ATP produced in glycolysis, 1 by acetate kinase 4.75 net protons are produced 4 are secreted by etanol and acetate transporters 0.75 protons must be pumped out by ATP syntase, consuming 0.5 ATP

15 ATP produc7on from oter substrates: summary of te network s energy genera7on ability Metabolite Abbrev. Maximum Maximum Aerobic Yield Anaerobic Yield Glycolysis Glucose glc Fructose fru Pyruvate pyr Lactate lac-d Fermentation Etanol eto Acetaldeyde acald Acetate ac Amino acids Glutamine gln-l Glutamate glu-l TCA a-ketoglutarate akg Succinate succ Fumarate fum Malate mal -L

16 fru[e] pyr[e] [e] fru[e] pyr[e] [e] pyr o amp pep o pyr amp o pep o dap dap pep o [e] fdp pyr lac-d[e] pep o [e] fdp pyr lac-d[e] glc-d[e] g6p f6p g3p 3pg pyr 13dpg pg pep lac-d co [e] glc-d[e] g6p f6p g3p pyr 13dpg 3pg pg pep lac-d p co [e] co co o p o for p for 6pgl for[e] p 6pgl o co ac[e] ac o co for[e] ac[e] ac actp ac 6pgc actp ac [e] 6pgc p xu5p-d [e] s7p e4p p co co xu5p-d s7p e4p co co p ru5p-d p acald ru5p-d co p acald[e] acald co p acald[e] r5p g3p f6p [e] p r5p g3p f6p mal-l o eto eto[e] [e] p mal-l o eto mal-l[e] o [e] eto[e] oaa fum[e] fum mal-l[e] o [e] oaa [e] fum[e] fum [e] [e] [e] cit [e] [e] cit q8 q8 ac glx q8 o acon-c o ac glx q8 o acon-c o p o succ icit o[e] p o succ icit o[e] [e] p p p co [e] suc p co akg co co[e] suc p akg co co[e] p n4 co p n4 amp p p co p n4 n4[e] amp p p n4 n4[e] p n4 o p o glu-l gln-l n4 o o o glu-l gln-l o o o o o n4 o o o n4 o q8 q8 q8 q8 o[e] [e] [e] [e] [e] [e] [e] [e] [e] akg[e] glu-l[e] gln-l[e] o[e] [e] [e] [e] [e] [e] [e] [e] [e] glu-l[e] succ[e] akg[e] gln-l[e] succ[e] fru[e] pyr[e] fru[e] pyr[e] [e] [e] pyr amp o pep o pyr amp o pep o dap dap pep o [e] pep o fdp pyr lac-d[e] [e] fdp pyr lac-d[e] glc-d[e] g6p f6p g3p pyr 13dpg 3pg pg pep lac-d glc-d[e] g6p f6p g3p pyr 13dpg 3pg pg pep lac-d co [e] co [e] p co p co o o for for p 6pgl p 6pgl for[e] o co o co for[e] ac[e] ac ac[e] ac actp ac actp ac 6pgc 6pgc [e] [e] p xu5p-d p s7p e4p xu5p-d s7p e4p co co co co p ru5p-d p ru5p-d acald acald co p acald[e] co p acald[e] r5p g3p f6p r5p g3p f6p [e] p [e] mal-l p o eto eto[e] mal-l o eto eto[e] mal-l[e] o [e] oaa mal-l[e] o [e] fum[e] fum oaa fum[e] fum [e] [e] [e] [e] [e] [e] cit cit q8 q8 ac glx q8 o acon-c o ac glx q8 o acon-c o p o succ icit o[e] p o succ icit o[e] [e] p [e] p p co p co suc akg co suc co[e] akg co co[e] p p n4 n4 co co p amp p p amp p p p n4 n4[e] n4 n4[e] p p n4 o n4 o o glu-l gln-l o glu-l gln-l o o o o o o n4 o o o n4 o q8 q8 q8 q8 o[e] [e] [e] [e] [e] [e] [e] [e] [e] akg[e] glu-l[e] gln-l[e] o[e] [e] [e] [e] [e] [e] [e] [e] [e] akg[e] glu-l[e] gln-l[e] succ[e] succ[e] Lactate Malate EX_glc(e) (0) EX_mal-L(e) (0) EX_fum(e) (0) EX_glc(e) (0) EX_mal-L(e) (-1) EX_fum(e) (0) GLCpts (0) MALt_ (0) FUMt_ (0) THD (0) GLCpts (0) MALt_ (1) FUMt_ (0) THD (0) FRUpts (0) EX_fru(e) (0) FBP (0) PGI (0) PFK (0) G6PDHr (0) PGL (0) GND (0) RPE (0) TKT1 (0) TKT (0) FBA (0) TALA (0) RPI (0) NADTRHD (1) ADK1 (0) ATPM (7.75) 0.5 ATPS4r (6.75) 4 Ot (3) EX_o(e) (-3) CYTBD (6) FRUpts (0) EX_fru(e) (0) FBP (0) PGI (0) PFK (0) FBA (0) G6PDHr (0) PGL (0) TKT (0) GND (0) RPE (0) TKT1 (0) TALA (0) RPI (0) NADTRHD (1) ADK1 (0) ATPM (7.75) 0.5 ATPS4r (6.75) 4 Ot (3) EX_o(e) (-3) CYTBD (6) Aerobic EX_pyr(e) (0) PYRtr (0) PPS (0) TPI (0) GAPD (0) PGK (0) PGM (0) FUM (1) ENO (0) LDH_D (1) PYK (0) PPCK (0) PFL (0) PPC (0) PDH (1) PTAr (0) ACKr (0) ACtr (0) ME1 (0) ME (0) ACALD (0) ALCDx (0) MDH (1) CS (1) MALS (0) FRD7 (0) 4 SUCDi (1) ACONTa (1) ACONTb (1) ICL (0) ICDHyr (1) SUCCt3 (0) SUCOAS (-1) AKGDH (1) GLUSy (0) GLUDy (0) GLUN (0) GLNS (0) GLNabc (0) SUCCt_ (0) GLUtr (0) EX_(e) (-1) NADH16 (5) 3 EX_succ(e) (0) AKGtr (0) EX_akg(e) (0) EX_glu-L(e) (0) EX_gln-L(e) (0) EX_pyr(e) (0) PYRtr (0) PPS (0) TPI (0) GAPD (0) PGK (0) PGM (0) FUM (1) ENO (0) LDH_D (0) PYK (0) PPCK (0) PFL (0) PPC (0) PDH (1) PTAr (0) ACKr (0) ACtr (0) ME1 (1) ME (0) ACALD (0) ALCDx (0) MDH (1) CS (1) MALS (0) FRD7 (0) 4 SUCDi (1) ACONTa (1) ACONTb (1) ICL (0) ICDHyr (1) SUCCt3 (0) SUCOAS (-1) AKGDH (1) GLUSy (0) GLUDy (0) GLUN (0) GLNS (0) GLNabc (0) SUCCt_ (0) GLUtr (0) EX_(e) (-) NADH16 (5) 3 EX_succ(e) (0) AKGtr (0) EX_akg(e) (0) EX_glu-L(e) (0) EX_gln-L(e) (0) D-LACt (1) EX_lac-D(e) (-1) FORt (0) FORti (0) EX_for(e) (0) EX_ac(e) (0) ACALDt (0) ETOHtr (0) EX_eto(e) (0) EX_acald(e) (0) EX_(e) (0) HOt (-3) PItr (0) COt (-3) NH4t (0) EX_o(e) (3) EX_co(e) (3) EX_n4(e) (0) D-LACt (0) EX_lac-D(e) (0) FORt (0) FORti (0) EX_for(e) (0) EX_ac(e) (0) ACALDt (0) ETOHtr (0) EX_eto(e) (0) EX_acald(e) (0) EX_(e) (0) HOt (-3) PItr (0) COt (-4) NH4t (0) EX_o(e) (3) EX_co(e) (4) EX_n4(e) (0) GLCpts (0) EX_glc(e) (0) EX_mal-L(e) (0) EX_fum(e) (0) MALt_ (0) FUMt_ (0) THD (0) GLCpts (0) EX_glc(e) (0) EX_mal-L(e) (-1) EX_fum(e) (0) MALt_ (1) FUMt_ (0) THD (0) FRUpts (0) EX_fru(e) (0) FBP (0) PGI (0) PFK (0) G6PDHr (0) PGL (0) GND (0) RPE (0) TKT1 (0) TKT (0) FBA (0) TALA (0) RPI (0) NADTRHD (0) ADK1 (0) ATPM (0.375) 0.5 ATPS4r (-0.15) 4 Ot (0) EX_o(e) (0) CYTBD (0) FRUpts (0) EX_fru(e) (0) FBP (0) PGI (0) PFK (0) G6PDHr (0) PGL (0) GND (0) RPE (0) TKT1 (0) TKT (0) FBA (0) TALA (0) RPI (0) NADTRHD (0) ADK1 (0) ATPM (0.375) 0.5 ATPS4r (-0.15) 4 Ot (0) EX_o(e) (0) CYTBD (0) Anaerobic EX_pyr(e) (0) PYRtr (0) PPS (0) TPI (0) GAPD (0) PGK (0) PGM (0) FUM (0) ENO (0) LDH_D (1) PYK (0) PPCK (0) PFL (1) PPC (0) PDH (0) PTAr (0.5) ACKr (-0.5) ACtr (-0.5) ACALD (-0.5) ME1 (0) ME (0) ALCDx (-0.5) MDH (0) CS (0) MALS (0) FRD7 (0) 4 SUCDi (0) ACONTa (0) ACONTb (0) ICL (0) ICDHyr (0) SUCCt3 (0) SUCOAS (0) AKGDH (0) GLUSy (0) GLUDy (0) GLUN (0) GLNS (0) GLNabc (0) SUCCt_ (0) GLUtr (0) EX_(e) (0.5) NADH16 (0) 3 EX_succ(e) (0) AKGtr (0) EX_akg(e) (0) EX_glu-L(e) (0) EX_gln-L(e) (0) EX_pyr(e) (0) PYRtr (0) PPS (0) TPI (0) GAPD (0) PGK (0) PGM (0) FUM (0) ENO (0) LDH_D (0) PYK (0) PPCK (0) PFL (1) PPC (0) PDH (0) PTAr (0.5) ACKr (-0.5) ACtr (-0.5) ACALD (-0.5) ME1 (1) ME (0) ALCDx (-0.5) MDH (0) CS (0) MALS (0) FRD7 (0) 4 SUCDi (0) ACONTa (0) ACONTb (0) ICL (0) ICDHyr (0) SUCCt3 (0) SUCOAS (0) AKGDH (0) GLUSy (0) GLUDy (0) GLUN (0) GLNS (0) GLNabc (0) SUCCt_ (0) GLUtr (0) EX_(e) (-0.5) NADH16 (0) 3 EX_succ(e) (0) AKGtr (0) EX_akg(e) (0) EX_glu-L(e) (0) EX_gln-L(e) (0) D-LACt (1) EX_lac-D(e) (-1) FORt (0) FORti (1) EX_for(e) (1) EX_ac(e) (0.5) ACALDt (0) ETOHtr (-0.5) EX_eto(e) (0.5) EX_acald(e) (0) EX_(e) (0) HOt (0.5) PItr (0) COt (0) NH4t (0) EX_o(e) (-0.5) EX_co(e) (0) EX_n4(e) (0) D-LACt (0) EX_lac-D(e) (0) FORt (0) FORti (1) EX_for(e) (1) EX_ac(e) (0.5) ACALDt (0) ETOHtr (-0.5) EX_eto(e) (0.5) EX_acald(e) (0) EX_(e) (0) HOt (0.5) PItr (0) COt (-1) NH4t (0) EX_o(e) (-0.5) EX_co(e) (1) EX_n4(e) (0)

17 Consumption of redox potential (NADH or NADPH) is troug a demand reaction: NAD(P)H v NAD(P)H! NAD(P) + + H + + e (1) Te objective function ten becomes: Z = v NAD(P)H () representing a demand (DM) function on redox potential. OPTIMAL REDOX PRODUCTION

18 fru[e] pyr[e] [e] pyr pep amp o o dap pep o [e] fdp pyr lac-d[e] glc-d[e] g6p f6p g3p 13dpg 3pg pg pep pyr lac-d co [e] p co o for p 6pgl for[e] o co ac ac[e] actp ac 6pgc [e] p xu5p-d s7p e4p co co p ru5p-d acald co p acald[e] g3p f6p r5p [e] p mal-l o eto eto[e] mal-l[e] o [e] oaa fum[e] fum [e] [e] [e] cit q8 ac glx q8 o acon-c o p o succ icit o[e] [e] p p co suc akg co co[e] p co n4 p p p amp n4 n4[e] p n4 o o glu-l gln-l o o o o n4 o q8 q8 o[e] [e] [e] [e] [e] [e] [e] [e] [e] akg[e] glu-l[e] gln-l[e] succ[e] Op7mal aerobic NADH produc7on EX_glc(e) (-1) EX_mal-L(e) (0) EX_fum(e) (0) GLCpts (1) MALt_ (0) FUMt_ (0) THD (0) FRUpts (0) EX_fru(e) (0) PGI (1) G6PDHr (0) PGL (0) GND (0) RPE (0) RPI (0) NADTRHD () ADK1 (0) ATPM (0) ATPS4r (-4) 4 FBP (0) PFK (1) FBA (1) TKT (0) TKT1 (0) TALA (0) 0.5 Ot (1) EX_o(e) (-1) CYTBD () A EX_pyr(e) (0) PYRtr (0) PPS (0) TPI (1) GAPD () PGK (-) PGM (-) ENO () LDH_D (0) PYK (1) PPCK (0) PFL (0) PPC (0) ME1 (0) ME (0) FRD7 (0) 4 SUCDi () AKGDH () ICL (0) PDH () ICDHyr () CS () PTAr (0) ACKr (0) ACtr (0) DM_ (10) ACALD (0) ALCDx (0) MDH () FUM () MALS (0) ACONTa () ACONTb () SUCCt3 (0) SUCOAS (-) SUCCt_ (0) GLUSy (0) GLUDy (0) GLUN (0) AKGtr (0) GLNS (0) GLNabc (0) GLUtr (0) NADH16 (0) 3 EX_(e) (0) EX_succ(e) (0) EX_akg(e) (0) EX_glu-L(e) (0) EX_gln-L(e) (0) Te Objec7ve D-LACt (0) EX_lac-D(e) (0) FORt (0) FORti (0) EX_for(e) (0) EX_ac(e) (0) ACALDt (0) ETOHtr (0) EX_eto(e) (0) EX_acald(e) (0) EX_(e) (0) HOt (4) PItr (0) COt (-6) NH4t (0) EX_o(e) (-4) EX_co(e) (6) EX_n4(e) (0) AKGDH () GAPD () PGK () ATPS4r (4) MDH () DM_ (10) PYK (1) PFK (1) NADTRHD () SUCOAS () B PDH () CS () DM_ (10) ATPS4r (3 x 4) ATPS4r (4 x 4) GAPD () MDH () CYTBD ( x ) PYK (1) CYTBD ( x ) [e] EX_(e) (0) PFK (1)

19 Interpreta7on of te op7mal solu7on for aerobic NADH produc7on NADH yield is limited by proton transmembrane balancing and stoiciometry Transmembrane gradients are - 0 mv/ 7nm=300,000 V/cm Protons produced in metabolism must be pumped out by te ATP syntase, requiring ATP Glycolysis and te TCA cycle must be used to generate ATP, but some reducing power is used to reduce q8 by SUCDi If ATP is supplied ar7ficially, te flux distribu7on canges

20 Op7mal aerobic NADH produc7on: remove ATP constraints EX_glc(e) (-1) EX_mal-L(e) (0) EX_fum(e) (0) GLCpts (1) glc-d[e] MALt_ (0) [e] mal-l[e] fum[e] FUMt_ (0) [e] [e] THD (0) Te Objec7ve FRUpts (0) fru[e] EX_fru(e) (0) pep pyr p p o pyr g6p 6pgl G6PDHr (6) PGL (6) PGI (-5) pep f6p FBP (1) PFK (0) TKT () o fdp FBA (-1) p co p 6pgc ru5p-d GND (6) RPI (-) RPE (4) xu5p-d r5p TKT1 () s7p g3p TALA () p NADTRHD (1) p o amp o ATPM (-8) ADK1 (1) 0.5 o o ATPS4r (-6) 4 [e] Ot (0) o[e] EX_o(e) (0) CYTBD (0) [e] q8 A q8 dap g3p EX_(e) (4) e4p f6p TPI (-1) [e] GAPD (0) NADH16 (0) 13dpg FRD7 (0) 4 3 [e] PGK (0) q8 q8 DM_ (1) EX_succ(e) (0) 3pg fum SUCDi (0) o SUCCt3 (0) succ [e] succ[e] SUCOAS (0) PGM (0) SUCCt_ (0) FUM (0) pg [e] mal-l EX_akg(e) (0) AKGtr (0) ENO (0) suc co ME1 (0) akg[e] o pep co p MALS (0) [e] o ac PPC (0) co MDH (0) AKGDH (0) ME (0) o amp co p p o co p glx EX_glu-L(e) (0) glu-l glu-l[e] PPCK (0) akg n4 PPS (1) p GLUDy (0) GLUtr (0) oaa co PYK (0) p [e] o n4 co n4 o ICL (0) GLUN (0) EX_pyr(e) (0) acald GLNS (0) PDH (0) ICDHyr (0) CS (0) acon-c icit p pyr[e] pyr ac o PYRtr (0) ACALD (0) PFL (0) cit [e] PTAr (0) ACONTa (0) ACONTb (0) for p GLNabc (0) EX_gln-L(e) (0) o GLUSy (0) gln-l LDH_D (0) actp eto ALCDx (0) gln-l[e] ACKr (0) o lac-d ac o co n4 ACtr (0) D-LACt (0) [e] lac-d[e] EX_lac-D(e) (0) FORt (0) FORti (0) [e] for[e] ac[e] EX_for(e) (0) o[e] [e] ACALDt (0) ETOHtr (0) [e] HOt (6) COt (-6) co[e] NH4t (0) n4[e] PItr (0) [e] acald[e] eto[e] [e] EX_eto(e) (0) EX_ac(e) (0) EX_co(e) (6) EX_acald(e) (0) EX_o(e) (-6) EX_n4(e) (0) EX_(e) (0) ADK1 (1) NADTRHD (1) DM_ (1) ATPM (8) ATPS4r (6) PPS (1) B DM_ (1) Wat you see in textbooks!! G6PDHr (6) PGL (6) ATPM (8) ATPS4r (3 x 6) ATPS4r (4 x 6) EX_(e) (4) [e] PPS ( x 1)

21 Op7mal anaerobic NADH produc7on: EX_glc(e) (-1) EX_mal-L(e) (0) EX_fum(e) (0) GLCpts (1) glc-d[e] MALt_ (0) [e] mal-l[e] fum[e] FUMt_ (0) [e] [e] THD (0) FRUpts (0) fru[e] EX_fru(e) (0) pyr pep pep pyr p p o g6p 6pgl G6PDHr (1.5) PGL (1.5) PGI (-0.5) f6p p co p 6pgc ru5p-d GND (1.5) RPE (1) RPI (-0.5) p NADTRHD (3) p o amp o ATPM (0) ADK1 (0) ATPS4r (-3) 4 [e] FBP (0) PFK (0.5) o fdp FBA (0.5) TKT (0.5) xu5p-d s7p r5p TKT1 (0.5) g3p TALA (0.5) 0.5 o o Ot (0) o[e] EX_o(e) (0) CYTBD (0) [e] q8 Te Objec7ve A dap g3p e4p f6p TPI (0.5) GAPD (1.5) 13dpg FRD7 (0) 4 q8 EX_(e) (13.5) [e] PGK (-1.5) q8 q8 DM_ (6) EX_succ(e) (0) 3pg fum SUCDi (0) SUCCt3 (0) o succ [e] succ[e] SUCOAS (0) PGM (-1.5) SUCCt_ (0) FUM (0) pg [e] mal-l EX_akg(e) (0) AKGtr (0) ENO (1.5) suc co ME1 (0) akg[e] o pep co p MALS (0) [e] o ac PPC (0) co MDH (0) AKGDH (0) ME (0) o amp co p p o co p glx EX_glu-L(e) (0) glu-l glu-l[e] PPCK (0) akg n4 PPS (0) p GLUDy (0) GLUtr (0) oaa co PYK (0.5) p [e] o n4 co n4 PDH (1.5) o ICL (0) GLUN (0) EX_pyr(e) (0) acald ICDHyr (0) GLNS (0) CS (0) acon-c icit p pyr[e] pyr ac o PYRtr (0) ACALD (0) PFL (0) cit [e] PTAr (1.5) ACONTa (0) ACONTb (0) for p GLNabc (0) EX_gln-L(e) (0) o GLUSy (0) gln-l LDH_D (0) actp eto gln-l[e] ALCDx (0) ACKr (-1.5) o lac-d ac o co n4 ACtr (-1.5) NADH16 (0) 3 [e] D-LACt (0) [e] lac-d[e] EX_lac-D(e) (0) FORt (0) FORti (0) [e] for[e] ac[e] EX_for(e) (0) o[e] [e] ACALDt (0) ETOHtr (0) [e] HOt (3) COt (-3) co[e] NH4t (0) n4[e] PItr (0) [e] acald[e] eto[e] [e] EX_eto(e) (0) EX_ac(e) (1.5) EX_co(e) (3) EX_acald(e) (0) EX_o(e) (-3) EX_n4(e) (0) EX_(e) (0) GAPD (1.5) ACKr (1.5) ATPS4r (3) NADTRHD (3) PDH (1.5) DM_ (6) PGK (1.5) PYK (0.5) PFK (0.5) B DM_ (6) G6PDHr (1.5) ACtr (1.5) ACtr (1.5) GAPD (1.5) ATPS4r (3 x 3) EX_(e) (13.5) ATPS4r (4 x 3) [e] PFK (0.5) PYK (0.5) PGL (1.5)

22 Interpreta7on of te op7mal solu7on for anaerobic NADH produc7on Can not use te TCA cycle witout oxygen, so a different strategy is used Splits flux evenly between glycolysis and pentose pospate patway Generates 3 NADPH in PPP, ten converts tem to NADH wit te transydrogenase. Also makes 1.5 NADH in glycolysis and 1.5 by pyruvate deydrogenase. Needs ATP to pump out 9 protons. PPP doesn t produce ATP, so glycolysis must also be used even toug it doesn t yield as muc NADH

23 Cofactor Produc7on Rates Cofactor Yield PPS ATP sadow Constraint price Aerobic ATP % 0 Internal proton NADH % Energy and Stoiciometry NADPH % Energy and Stoiciometry Anaerobic ATP.750 0% 0 Internal proton NADH % Energy and Stoiciometry NADPH % Energy and Stoiciometry

24 Prelude to simula7ng growt BIOSYNTHETIC PRECURSORS

25 GROWTH REQUIREMENTS: Genome- scale A Cell wall Lids Purines Nucleosides Amino acids Pyrimidines Heme versus core αkg G6P, F6P models B OAA R5P, E4P AcCoA T3P, 3PG PEP, PYR 1 biosynte7c precursors

26 Aerobic Metabolite Yield Carbon ATP sadow Constraint conversion price 3PG 100% 0 PEP 100% 0 Pyr 100% 0 OA % 0 G6P % Energy F6P % Energy R5P % Energy E4P % Energy G3P % Energy AcCoA 66.67% 0 Stoiciometry akg % 0 Stoiciometry SuccCoA % 0

27 Anaerobic Metabolite Yield Carbon ATP sadow Constraint conversion price 3PG 1 50% 0 Stoiciometry PEP 1 50% 0 Stoiciometry Pyr 1 50% 0 Stoiciometry OA % 0 Stoiciometry G6P % Energy F6P % Energy R5P % 0.19 Energy E4P % 0.64 Energy G3P % Energy AcCoA % 0 Stoiciometry akg % 0 Stoiciometry SuccCoA % 0 Stoiciometry

28 Use of tests TO DEBUG AND VALIDATE NETWORKS

29 Network valida7on: te Tiele tests Test if network is mass- and carge balanced. Gap filling. Test for stoiciometrically balanced cycles. Test if biomass precursors can be produced in standard medium. Test if biomass precursors can be produced in oter growt media. Test if model can produce known secre7on products. Ceck for blocked reac7ons. Compute single gene dele7on penotypes. Test for known incapabilites of te organism. Compare predicted pysiological proper7es wit known proper7es. Test if te model can grow fast enoug. Test if te model grows too fast.

30 Network Valida7on: te Recon 1 tests 88 dis7nct uman metabolic func7ons were defined and simulated wit FBA to assess func7onality of Recon 1 Many are simple: melatonin trp- L

31 88 recon 1 tests

32 Gap- filling wen valida7on fails: see Biotecnol & Bioeng, 15;107:403-1 (010).

33 Summary Te capabili7es and caracteris7cs of networks can be explored using LP Objec7ve func7ons can be used to represent par7cular network proper7es of interest Sadow prices/reduced costs can be useful in interpre7ng te solu7on and governing constraints ATP and NADH yields can be studied in details Ability to make biosynte7c precursors can precede te study of growt Various substrates can easily be studied Explora7on can be in te form of func7onal and valida7on tests

34 THE END

35 SOME INTERESTING LITERATURE

36 Amino acid Yield Calcula7ons: defini7on of constraints

37 Amino acid Yield Calcula7ons:

38 Systemic P/O in Yeast Results Te in silico model can be used to assess network properties suc as te P O ratioandenergymaintenancecostsandtocompute wole-cell functions. Te efficiency of aerobic resration is measured by te P O ratio.experimentalstudiesofisolated mitocondria ave sown tat S. cerevisiae lacks site I proton translocation (8). Consequently, estimation of te maximum teoretical or mecanistic yield of te ETS alone gives a P O ratio of 1.5 for oxidation of NADH in S. cerevisiae grown on glucose (8). However, based on experimental measurements, it as been determined tat te net in vivo P Oratiois 0.95 (8). Tis difference is generally attributed to te use of te mitocondrial transmembrane proton gradient needed to drive metabolite excange (suc as te proton-coupled translocation of pyruvate) across te inner mitocondrial membrane. In te reconstructed network, wic contains no proton leakage, 1.5 molecules of ATP are generated via te ETS. As complete oxidation of glucose leads to donation of 1 electron pairs (10 NADH and FADH )toteelectrontransportcain,tein silico P O ratiois1.04foroxidationofnadhandfadh during growt on glucose, i.e., , agreeing well wit te measured value witout including any proton leakage. Te network-based computation systemically accounts for all te steps required to import and export compounds from te mitocondria, computing a net overall P O ratio. Cells require energy for bot growt- and non-growtassociated activities (9). Te energy requirement for te formation of biomass as been measured experimentally for S. cerevisiae, andreportedvaluesrangefrom6.5to71.4mmolof ATP gdw (9, 30). A network-based calculation procedure of te growt-associated energy requirement as been developed (31), and wen applied to te reconstructed S. cerevisiae network, a value of 69. mmol of ATP gdw was computed (see Metods), wic falls in te range of experimentally determined values. Energy required for precursor metabolite formation and macromolecule polymerization can be calculated from te biosyntetic composition of te cell. Te model-based ATP requirement is entirely network-dependent and was derived from te in silico calculations. Te reconstructed metabolic network of S. cerevisiae can be PNAS 100: (003)

39 Yields from iaf160 Substrate Glucose Xylose Glycerol Glucose Xylose Glycerol Aerobicit Anaerobic Anaerobic Anaerobic Aerobic Aerobic Aerobic product no. yof carbons Y p/s Y p/s Y p/s Y p/s Y p/s Y p/s Etanol 49%* 49%* 49% 49% 49% 54% D- Lactate 3 95%* 95%* 13% 95% 95% 97% Glycerol 3 37% 7% 75% 74% L- Alanine 3 95%* 76% 13% 95% 93% 96% L- Serine 3 47% 35% 6% 115% 114% 116% Pyruvate 3 71% 60% 6% 100% 99% 100% Fumarate 4 54% 40% 5% 110% 108% 117% L- Malate 4 63% 46% 5% 17% 15% 135% Succinate 4 93% 81% 1% 104% 101% 111% - Oxoglutarate 5 40% 3% 3% 98% 96% 101% L- Glutamate 5 44% 36% 3% 9% 90% 97%

40 APPENDIX: Old Core E. coli model Historical case: simpler maps, easier to interpret, from

41

42

43

44

45

46

47

48

49

50

51 First report of equivalent op7mal solu7ons

52 Te end

Constraint-based Metabolic Reconstructions & Analysis H. Scott Hinton, Lesson: Flux Variability Analysis & Parsimonious Flux Balance Analysis

Constraint-based Metabolic Reconstructions & Analysis H. Scott Hinton, Lesson: Flux Variability Analysis & Parsimonious Flux Balance Analysis -1- Flux Variability Analysis & Parsimonious Flux Balance Analysis -2- Learning Objectives Explain alternate optimal solutions, Explain flux variability analysis, Explain parsimonious flux balance analysis.

More information

Introduction to constraint-based modeling in metabolism

Introduction to constraint-based modeling in metabolism 2 2 2 2 4 2 3 2 2.5 2 2 2 4 atp 3pg 13dpg adp nadp 6pgc co2 nadp ru5p-d o2 o2 nadp nad nadp nad 2o fum mal-l icit nadp nadp co2 akg nad pyr coa co2 accoa nad 2o pep co2 pi oaa 2pg 2o g6p f6p 2o fdp pi

More information

Randomized Sampling and Adaptive Laboratory Evolution

Randomized Sampling and Adaptive Laboratory Evolution 1 Randomized Sampling and Adaptive Laboratory Evolution 2 LEARNING OBJECTIVES Each student should be able to: Explain randomized sampling Explain the Method of Minimization of Metabolic Adjustment (MOMA)

More information

Constraint-based Metabolic Reconstructions & Analysis H. Scott Hinton. The Cobra Toolbox. Lesson: Cobra Toolbox

Constraint-based Metabolic Reconstructions & Analysis H. Scott Hinton. The Cobra Toolbox. Lesson: Cobra Toolbox 1 The Cobra Toolbox 2 Learning Objectives Each student should be able to: Explain the purpose of the Cobra Toolbox, Demonstrate basic operation of the Cobra Toolbox, Explain the BIGG Database, Explain

More information

FLUX BALANCE ANALYSIS OVERVIEW

FLUX BALANCE ANALYSIS OVERVIEW FLUX BALANCE ANALYSIS OVERVIEW Learning Objectives Each student should be able to: Explain flux balance analysis (FBA). Explain the stoichiometric reactions and metabolites. Explain mass balanced linear

More information

Flux Balance Analysis Overview

Flux Balance Analysis Overview 1 Flux Balance Analysis Overview 2 Learning Objectives Each student should be able to: Explain flux balance analysis (FBA). Explain reactions, metabolites, & pathways. Explain mass balanced linear equations.

More information

Supplementary material III: metabolic pathway analysis

Supplementary material III: metabolic pathway analysis Supplementary material III: metabolic pathway analysis Elementary mode analysis We used elementary mode analysis (1)to systematically identify all circulations and futile cycle in the model. For this,

More information

13. PG3 + ATP + NADH => GA3P + ADP + Pi + NAD +

13. PG3 + ATP + NADH => GA3P + ADP + Pi + NAD + Additional file 2. 1.1 Stochiometric model for P. pastoris containing some additional reactions from the 13 C model (section 1.2) Methanol metabolism 1. Metoh => Form 2. Form => FOR + NADH 3. FOR + NAD

More information

Reconstruction and Analysis of Metabolic Networks

Reconstruction and Analysis of Metabolic Networks 1 Reconstruction and Analysis of Metabolic Networks 2 Outline What is a Reconstruction? Data Collection Interactions Between Network Components Special Considerations Applications Genome-scale Metabolic

More information

Lecture 10. Proton Gradient-dependent ATP Synthesis. Oxidative. Photo-Phosphorylation

Lecture 10. Proton Gradient-dependent ATP Synthesis. Oxidative. Photo-Phosphorylation Lecture 10 Proton Gradient-dependent ATP Synthesis Oxidative Phosphorylation Photo-Phosphorylation Model of the Electron Transport Chain (ETC) Glycerol-3-P Shuttle Outer Mitochondrial Membrane G3P DHAP

More information

Change to Office Hours this Friday and next Monday. Tomorrow (Abel): 8:30 10:30 am. Monday (Katrina): Cancelled (05/04)

Change to Office Hours this Friday and next Monday. Tomorrow (Abel): 8:30 10:30 am. Monday (Katrina): Cancelled (05/04) Change to Office Hours this Friday and next Monday Tomorrow (Abel): 8:30 10:30 am Monday (Katrina): Cancelled (05/04) Lecture 10 Proton Gradient-dependent ATP Synthesis Oxidative Phosphorylation Photo-Phosphorylation

More information

Description of the algorithm for computing elementary flux modes

Description of the algorithm for computing elementary flux modes Description of the algorithm for computing elementary flux modes by Stefan Schuster, Thomas Dandekar,, and David Fell Department of Bioinformatics, Max Delbrück Centre for Molecular Medicine D-9 Berlin-Buch,

More information

Dynamic Flux Balance Analysis

Dynamic Flux Balance Analysis 1 Dynamic Flux Balance Analysis 2 LEARNING OBJECTIVES Each student should be able to: Explain dynamic flux balance analysis. Describe the strengths and limitations of dynamic flux balance analysis. Describe

More information

Chapter 7: Metabolic Networks

Chapter 7: Metabolic Networks Chapter 7: Metabolic Networks 7.1 Introduction Prof. Yechiam Yemini (YY) Computer Science epartment Columbia University Introduction Metabolic flux analysis Applications Overview 2 1 Introduction 3 Metabolism:

More information

Transcriptional Regulatory Networks

Transcriptional Regulatory Networks 1 Transcriptional Regulatory Networks 2 LEARNING OBJECTIVES Each student should be able to: Explain the purpose of a transcriptional regulatory network. Explain the role of a transcription factor. Explain

More information

Extreme Pathways in the Post-Genome Era

Extreme Pathways in the Post-Genome Era Extreme Pathways in the Post-Genome Era Bernhard Palsson Lecture #8 September 6, 003 ) Overview of extreme pathways Outline ) Extreme pathways of human red blood cell metabolism 3) Extreme pathway analysis

More information

Constraint-Based Workshops

Constraint-Based Workshops Constraint-Based Workshops 2. Reconstruction Databases November 29 th, 2007 Defining Metabolic Reactions ydbh hslj ldha 1st level: Primary metabolites LAC 2nd level: Neutral Formulas C 3 H 6 O 3 Charged

More information

Escherichia coli Core Metabolism Model in LIM

Escherichia coli Core Metabolism Model in LIM Escherichia coli Core Metabolism Model in LIM Karline Soetaert Royal Netherlands Institute of Sea Research Yerseke The Netherlands Abstract R package LIM (Soetaert and van Oevelen 2009a) is designed for

More information

Towards integrated models of regulatory networks: the MetaGenoReg project

Towards integrated models of regulatory networks: the MetaGenoReg project Towards integrated models of regulatory networks: the MetaGenoReg project Hidde de Jong and Daniel Kahn INRIA Grenoble - Rhône-Alpes Hidde.de-Jong@inria.fr http://ibis.inrialpes.fr LBBE, Université de

More information

Metabolism. Fermentation vs. Respiration. End products of fermentations are waste products and not fully.

Metabolism. Fermentation vs. Respiration. End products of fermentations are waste products and not fully. Outline: Metabolism Part I: Fermentations Part II: Respiration Part III: Metabolic Diversity Learning objectives are: Learn about respiratory metabolism, ATP generation by respiration linked (oxidative)

More information

Winter School in Mathematical & Computational Biology

Winter School in Mathematical & Computational Biology 1 Network reconstruction, topology and feasible solution space From component to systems biology Component biology Systems biology Component view Systems view Needed homeostasis Function S+E X E+P Reaction

More information

Systems Biology Lecture 1 history, introduction and definitions. Pawan Dhar

Systems Biology Lecture 1 history, introduction and definitions. Pawan Dhar Systems Biology Lecture 1 history, introduction and definitions Pawan Dhar Historical context 1900 1950 2000 Dominant approach Physiology Molecular biology Focus of study Paradigmatic discovery Functioning

More information

Bioinformatics: Network Analysis

Bioinformatics: Network Analysis Bioinformatics: Network Analysis Flux Balance Analysis and Metabolic Control Analysis COMP 572 (BIOS 572 / BIOE 564) - Fall 2013 Luay Nakhleh, Rice University 1 Flux Balance Analysis (FBA) Flux balance

More information

QUALITATIVE PATH ANALYSIS OF METABOLIC PATHWAYS USING PETRI NETS FOR GENERIC MODELLING

QUALITATIVE PATH ANALYSIS OF METABOLIC PATHWAYS USING PETRI NETS FOR GENERIC MODELLING BRANDENBURG UNIVERSITY OF TECHNOLOGY AT COTTBUS Faculty of Mathematics, Natural Sciences and Computer Science Institute of Computer Science COMPUTER SCIENCE REPORTS Report 03/04 August 2004 QUALITATIVE

More information

Paint4Net: visualisation toolbox for COBRA

Paint4Net: visualisation toolbox for COBRA Paint4Net: visualisation toolbox for COBRA Author(s): Andrejs Kostromins, Biosystems Group, Department of Computer Systems, Latvia University of Agriculture, Liela iela 2, LV-3001 Jelgava, Latvia. Egils

More information

Oxidative Phosphorylation versus. Photophosphorylation

Oxidative Phosphorylation versus. Photophosphorylation Photosynthesis Oxidative Phosphorylation versus Photophosphorylation Oxidative Phosphorylation Electrons from the reduced cofactors NADH and FADH 2 are passed to proteins in the respiratory chain. In eukaryotes,

More information

Lecture Series 9 Cellular Pathways That Harvest Chemical Energy

Lecture Series 9 Cellular Pathways That Harvest Chemical Energy Lecture Series 9 Cellular Pathways That Harvest Chemical Energy Reading Assignments Review Chapter 3 Energy, Catalysis, & Biosynthesis Read Chapter 13 How Cells obtain Energy from Food Read Chapter 14

More information

Bio102 Problems Photosynthesis

Bio102 Problems Photosynthesis Bio102 Problems Photosynthesis 1. Why is it advantageous for chloroplasts to have a very large (in surface area) thylakoid membrane contained within the inner membrane? A. This limits the amount of stroma

More information

Photosynthesis and Cellular Respiration Note-taking Guide

Photosynthesis and Cellular Respiration Note-taking Guide Photosynthesis and Cellular Respiration Note-taking Guide Preview to Photosynthesis glucose, reectlons, light-dependent, Calvin cycle, thylakoid, oxygen, light-harvesting, two, chloroplasts, photosynthesis,

More information

Genome Evolution Greg Lang, Department of Biological Sciences

Genome Evolution Greg Lang, Department of Biological Sciences Genome Evolution Greg Lang, Department of Biological Sciences BioS 010: Bioscience in the 21st Century Mechanisms of genome evolution Gene Duplication Genome Rearrangement Whole Genome Duplication Gene

More information

Genome-scale Models: Lessons Learned

Genome-scale Models: Lessons Learned Genome-scale Models: Lessons Learned Bernhard Palsson Lecture #7 September 15, 2003 1 Outline 1) Status of reconstruction 2) Genome-scale in silico models of E. coli 3) A Genome-Scale in silico Model of

More information

Transformation of Energy! Energy is the ability to do work.! Thermodynamics is the study of the flow and transformation of energy in the universe.

Transformation of Energy! Energy is the ability to do work.! Thermodynamics is the study of the flow and transformation of energy in the universe. Section 1 How Organisms Obtain Energy Transformation of Energy! Energy is the ability to do work.! Thermodynamics is the study of the flow and transformation of energy in the universe. Section 1 How Organisms

More information

Photosynthesis and Cellular Respiration Note-taking Guide

Photosynthesis and Cellular Respiration Note-taking Guide Photosynthesis and Cellular Respiration Note-taking Guide Preview to Photosynthesis glucose, reactions, light-dependent, Calvin cycle, thylakoid, photosystem II, oxygen, light-harvesting, two, chloroplasts,

More information

Cellular Respiration. The mechanism of creating cellular energy. Thursday, 11 October, 12

Cellular Respiration. The mechanism of creating cellular energy. Thursday, 11 October, 12 Cellular Respiration The mechanism of creating cellular energy What do we know?? What do we know?? Grade 5 - Food --> Energy What do we know?? Grade 5 - Food --> Energy Grade 10 - glu. + O2 --> CO2 + H20

More information

arxiv: v1 [q-bio.mn] 23 Oct 2014

arxiv: v1 [q-bio.mn] 23 Oct 2014 Inferring metabolic phenotypes from the exometabolome through a thermodynamic variational principle Daniele De Martino, Fabrizio Capuani, 2, 3 2, 3, and Andrea De Martino Center for Life Nano Science@Sapienza,

More information

Unit 3: Cell Energy Guided Notes

Unit 3: Cell Energy Guided Notes Enzymes Unit 3: Cell Energy Guided Notes 1 We get energy from the food we eat by breaking apart the chemical bonds where food is stored. energy is in the bonds, energy is the energy we use to do things.

More information

Metabolism Review. A. Top 10

Metabolism Review. A. Top 10 A. Top 10 Metabolism Review 1. Energy production through chemiosmosis a. pumping of H+ ions onto one side of a membrane through protein pumps in an Electron Transport Chain (ETC) b. flow of H+ ions across

More information

Photosynthesis and Cellular Respiration Practice Test Name

Photosynthesis and Cellular Respiration Practice Test Name Photosynthesis and Cellular Respiration Practice Test Name MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. 1) Which H+ has just passed through the

More information

Predicting rice (Oryza sativa) metabolism

Predicting rice (Oryza sativa) metabolism Predicting rice (Oryza sativa) metabolism Sudip Kundu Department of Biophysics, Molecular Biology & Bioinformatics, University of Calcutta, WB, India. skbmbg@caluniv.ac.in Collaborators: Mark G Poolman

More information

Biochemical Pathways

Biochemical Pathways Biochemical Pathways Living organisms can be divided into two large groups according to the chemical form in which they obtain carbon from the environment. Autotrophs can use carbon dioxide from the atmosphere

More information

Omic data from evolved E. coli are consistent with computed optimal growth from genome-scale models

Omic data from evolved E. coli are consistent with computed optimal growth from genome-scale models Molecular Systems Biology 6; Article number 39; doi:1.138/msb.21.47 itation: Molecular Systems Biology 6:39 & 21 EMBO and Macmillan Publisers Limited All rigts reserved 1744-4292/1 www.molecularsystemsbiology.com

More information

Cell Energy Notes ATP THE ENDOSYMBIOTIC THEORY. CELL ENERGY Cells usable source of is called ATP stands for. Name Per

Cell Energy Notes ATP THE ENDOSYMBIOTIC THEORY. CELL ENERGY Cells usable source of is called ATP stands for. Name Per Cell Energy Notes Name Per THE ENDOSYMBIOTIC THEORY The Endosymbiotic theory is the idea that a long time ago, engulfed other prokaryotic cells by. This resulted in the first First proposed by Explains

More information

BBS2710 Microbial Physiology. Module 5 - Energy and Metabolism

BBS2710 Microbial Physiology. Module 5 - Energy and Metabolism BBS2710 Microbial Physiology Module 5 - Energy and Metabolism Topics Energy production - an overview Fermentation Aerobic respiration Alternative approaches to respiration Photosynthesis Summary Introduction

More information

Photosynthesis and cellular respirations

Photosynthesis and cellular respirations The Introduction of Biology Defining of life Basic chemistry, the chemistry of organic molecules Classification of living things History of cells and Cells structures and functions Photosynthesis and cellular

More information

Electron Transport Chain (Respiratory Chain) - exercise - Vladimíra Kvasnicová

Electron Transport Chain (Respiratory Chain) - exercise - Vladimíra Kvasnicová Electron Transport Chain (Respiratory Chain) - exercise - Vladimíra Kvasnicová Respiratory chain (RCH) a) is found in all cells b) is located in a mitochondrion c) includes enzymes integrated in the inner

More information

The Proton Motive Force. Overview. Compartmentalization 11/6/2015. Chapter 21 Stryer Short Course. ATP synthesis Shuttles

The Proton Motive Force. Overview. Compartmentalization 11/6/2015. Chapter 21 Stryer Short Course. ATP synthesis Shuttles The Proton Motive Force Chapter 21 Stryer Short Course Redox reactions Electron transport chain Proton gradient Overview ATP synthesis Shuttles Analogy: How does burning coal put flour in the grocery store?

More information

Integrated Knowledge-based Reverse Engineering of Metabolic Pathways

Integrated Knowledge-based Reverse Engineering of Metabolic Pathways Integrated Knowledge-based Reverse Engineering of Metabolic Pathways Shuo-Huan Hsu, Priyan R. Patkar, Santhoi Katare, John A. Morgan and Venkat Venkatasubramanian School of Chemical Engineering, Purdue

More information

Sampling with poling-based flux balance analysis: optimal versus sub-optimal flux space analysis of Actinobacillus succinogenes

Sampling with poling-based flux balance analysis: optimal versus sub-optimal flux space analysis of Actinobacillus succinogenes Binns et al. BMC Bioinformatics (2015) 16:49 DOI 10.1186/s12859-015-0476-5 ESEACH ATICLE Open Access Sampling with poling-based flux balance analysis: optimal versus sub-optimal flux space analysis of

More information

Giving you the energy you need!

Giving you the energy you need! Giving you the energy you need! Use your dominant hand Open and close the pin (with your thumb and forefinger) as many times as you can for 20 seconds while holding the other fingers straight out! Repeat

More information

V15 Flux Balance Analysis Extreme Pathways

V15 Flux Balance Analysis Extreme Pathways V15 Flux Balance Analysis Extreme Pathways Stoichiometric matrix S: m n matrix with stochiometries of the n reactions as columns and participations of m metabolites as rows. The stochiometric matrix is

More information

2015 AP Biology PRETEST Unit 3: Cellular Energetics Week of October

2015 AP Biology PRETEST Unit 3: Cellular Energetics Week of October Name: Class: _ Date: _ 2015 AP Biology PRETEST Unit 3: Cellular Energetics Week of 19-23 October Multiple Choice Identify the choice that best completes the statement or answers the question. 1) Which

More information

A. Structures of PS. Site of PS in plants: mostly in leaves in chloroplasts. Leaf cross section. Vein. Mesophyll CO 2 O 2. Stomata

A. Structures of PS. Site of PS in plants: mostly in leaves in chloroplasts. Leaf cross section. Vein. Mesophyll CO 2 O 2. Stomata PS Lecture Outline I. Introduction A. Structures B. Net Reaction II. Overview of PS A. Rxns in the chloroplast B. pigments III. Closer looks A. LD Rxns B. LI Rxns 1. non-cyclic e- flow 2. cyclic e- flow

More information

RESPIRATION AND FERMENTATION: AEROBIC AND ANAEROBIC OXIDATION OF ORGANIC MOLECULES. Bio 107 Week 6

RESPIRATION AND FERMENTATION: AEROBIC AND ANAEROBIC OXIDATION OF ORGANIC MOLECULES. Bio 107 Week 6 RESPIRATION AND FERMENTATION: AEROBIC AND ANAEROBIC OXIDATION OF ORGANIC MOLECULES Bio 107 Week 6 Procedure 7.2 Label test tubes well, including group name 1) Add solutions listed to small test tubes 2)

More information

State state describe

State state describe Warm-Up State the products of the light-dependent reaction of photosynthesis, state which product has chemical energy, and describe how that product is made. KREBS ETC FADH 2 Glucose Pyruvate H 2 O NADH

More information

Cellular Respiration. Mitochondria Rule! Mr. Kurt Kristensen

Cellular Respiration. Mitochondria Rule! Mr. Kurt Kristensen Cellular Respiration Mitochondria Rule! Mr. Kurt Kristensen Harvard Biovisions Mitochondria Summer Session Week 1: Cellular Respiration Students should. 1) Understand the locations, and functions of the

More information

Cell Energy: The Big Picture. So, What Exactly is ATP. Adenosine Triphosphate. Your turn to Practice converting ATP to ADP:

Cell Energy: The Big Picture. So, What Exactly is ATP. Adenosine Triphosphate. Your turn to Practice converting ATP to ADP: Understanding How Living Things Obtain and Use Energy. Cell Energy: The Big Picture Most Autotrophs produce food (sugar) using light energy during Photosynthesis. Then, both Autotrophs and Heterotroph

More information

Respiration and Photosynthesis

Respiration and Photosynthesis Respiration and Photosynthesis Cellular Respiration Glycolysis The Krebs Cycle Electron Transport Chains Anabolic Pathway Photosynthesis Calvin Cycle Flow of Energy Energy is needed to support all forms

More information

TCA Cycle. Voet Biochemistry 3e John Wiley & Sons, Inc.

TCA Cycle. Voet Biochemistry 3e John Wiley & Sons, Inc. TCA Cycle Voet Biochemistry 3e Voet Biochemistry 3e The Electron Transport System (ETS) and Oxidative Phosphorylation (OxPhos) We have seen that glycolysis, the linking step, and TCA generate a large number

More information

Supplementary Information

Supplementary Information 1 Steady State Analysis of Genetic Regulatory Network incorporating underlying Molecular Mechanisms for Anaerobic Metabolism in Escherichia coli Sumana Srinivasan and K. V. Venkatesh Department of Chemical

More information

A + B = C C + D = E E + F = A

A + B = C C + D = E E + F = A Photosynthesis - Plants obtain energy directly from the sun - Organisms that do this are autotrophs (make their own food from inorganic forms) - Photosynthesis is a series of chemical reactions where the

More information

Cellular Energy. How Organisms Obtain Energy Section 2: Photosynthesis Section 3: Cellular Respiration. Click on a lesson name to select.

Cellular Energy. How Organisms Obtain Energy Section 2: Photosynthesis Section 3: Cellular Respiration. Click on a lesson name to select. Section 1: How Organisms Obtain Energy Section 2: Photosynthesis Section 3: Cellular Respiration Click on a lesson name to select. Section 1 How Organisms Obtain Energy Transformation of Energy Energy

More information

Energy Transformation. Metabolism = total chemical reactions in cells.

Energy Transformation. Metabolism = total chemical reactions in cells. Energy Transformation Metabolism = total chemical reactions in cells. metabole = change Metabolism is concerned with managing the material and energy resources of the cell -Catabolism -Anabolism -Catabolism

More information

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. AP Exam Chapters 9 and 10; Photosynthesis and Respiration Name MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. 1) Carbon dioxide (CO2) is released

More information

Name Date Class. Photosynthesis and Respiration

Name Date Class. Photosynthesis and Respiration Concept Mapping Photosynthesis and Respiration Complete the Venn diagram about photosynthesis and respiration. These terms may be used more than once: absorbs, Calvin cycle, chlorophyll, CO 2, H 2 O, Krebs

More information

Copyright The McGraw-Hill Companies, Inc. Permission required for reproduction or display. Outer Glycolysis mitochondrial membrane Glucose ATP

Copyright The McGraw-Hill Companies, Inc. Permission required for reproduction or display. Outer Glycolysis mitochondrial membrane Glucose ATP Fig. 7.5 uter Glycolysis mitochondrial membrane Glucose Intermembrane space xidation Mitochondrial matrix Acetyl-oA Krebs FAD e NAD + FAD Inner mitochondrial membrane e Electron e Transport hain hemiosmosis

More information

Cellular Energetics. Photosynthesis, Cellular Respiration and Fermentation

Cellular Energetics. Photosynthesis, Cellular Respiration and Fermentation Cellular Energetics Photosynthesis, Cellular Respiration and Fermentation TEKS B.4 Science concepts. The student knows that cells are the basic structures of all living things with specialized parts that

More information

Systems Engineering Challenges and Opportunities in Computational Biology

Systems Engineering Challenges and Opportunities in Computational Biology Systems Engineering Challenges and Opportunities in Computational Biology Costas D. Maranas Penn State University University Park, PA 16802 E-mail: costas@psu.edu Web page: fenske.che.psu.edu/faculty/cmaranas

More information

THIS IS. In photosynthesis A) Carbon gets oxidized B) Carbon gets reduced C) Carbon gets metabolized D) Carbon gets digested

THIS IS. In photosynthesis A) Carbon gets oxidized B) Carbon gets reduced C) Carbon gets metabolized D) Carbon gets digested THIS IS With Your Host... table Column A Column B Column C Column D Column E Column F 100 100 100 100 100 100 200 200 200 200 200 200 300 300 300 300 300 300 400 400 400 400 400 400 In photosynthesis A)

More information

Energy Exchanges Exam: What to Study

Energy Exchanges Exam: What to Study Energy Exchanges Exam: What to Study Here s what you will need to make sure you understand in order to prepare for our exam: Free Energy Conceptual understanding of free energy as available energy in a

More information

AP Biology Cellular Respiration

AP Biology Cellular Respiration AP Biology Cellular Respiration The bonds between H and C represents a shared pair of electrons These are high-energy electrons This represents chemical potential energy Hydro-carbons posses a lot of chemical

More information

CHAPTER 15 Metabolism: Basic Concepts and Design

CHAPTER 15 Metabolism: Basic Concepts and Design CHAPTER 15 Metabolism: Basic Concepts and Design Chapter 15 An overview of Metabolism Metabolism is the sum of cellular reactions - Metabolism the entire network of chemical reactions carried out by living

More information

Center for Academic Services & Advising

Center for Academic Services & Advising March 2, 2017 Biology I CSI Worksheet 6 1. List the four components of cellular respiration, where it occurs in the cell, and list major products consumed and produced in each step. i. Hint: Think about

More information

CHLOROPLASTS, CALVIN CYCLE, PHOTOSYNTHETIC ELECTRON TRANSFER AND PHOTOPHOSPHORYLATION (based on Chapter 19 and 20 of Stryer )

CHLOROPLASTS, CALVIN CYCLE, PHOTOSYNTHETIC ELECTRON TRANSFER AND PHOTOPHOSPHORYLATION (based on Chapter 19 and 20 of Stryer ) CHLOROPLASTS, CALVIN CYCLE, PHOTOSYNTHETIC ELECTRON TRANSFER AND PHOTOPHOSPHORYLATION (based on Chapter 19 and 20 of Stryer ) Photosynthesis Photosynthesis Light driven transfer of electron across a membrane

More information

Cellular Respiration: Harvesting Chemical Energy. 9.1 Catabolic pathways yield energy by oxidizing organic fuels

Cellular Respiration: Harvesting Chemical Energy. 9.1 Catabolic pathways yield energy by oxidizing organic fuels Cellular Respiration: Harvesting Chemical Energy 9.1 Catabolic pathways yield energy by oxidizing organic fuels 9.2 Glycolysis harvests chemical energy by oxidizing glucose to pyruvate 9.3 The citric acid

More information

Glycolysis and Fermentation. Chapter 8

Glycolysis and Fermentation. Chapter 8 Glycolysis and Fermentation Chapter 8 Cellular Respiration and Photosynthesis 0 Things to know in these chapters 0 Names and order of the processes 0 Reactants and products of each process 0 How do they

More information

MITOCW watch?v=0xajihttcns

MITOCW watch?v=0xajihttcns MITOCW watch?v=0xajihttcns The following content is provided under a Creative Commons license. Your support will help MIT OpenCourseWare continue to offer high quality educational resources for free. To

More information

Biology Chapter 8 Test: Cellular Energy

Biology Chapter 8 Test: Cellular Energy Class: Date: Biology Chapter 8 Test: Cellular Energy True/False Indicate whether the statement is true or false. 1. During the light-independent reactions of photosynthesis, light energy is used to split

More information

6CO 2 + 6H 2 O C 6 H 12 O 6 + 6O 2. sun. Occurs in chloroplasts ATP. enzymes CO 2 O 2 H 2 O. sugars

6CO 2 + 6H 2 O C 6 H 12 O 6 + 6O 2. sun. Occurs in chloroplasts ATP. enzymes CO 2 O 2 H 2 O. sugars 4.2 8.2 Overview Photosynthesis: of Photosynthesis An Overview Photosynthesis process by which plants make food using energy from the sun Plants are autotrophs that make their own source of chemical energy.

More information

Review Questions - Lecture 5: Metabolism, Part 1

Review Questions - Lecture 5: Metabolism, Part 1 Review Questions - Lecture 5: Metabolism, Part 1 Questions: 1. What is metabolism? 2. What does it mean to say that a cell has emergent properties? 3. Define metabolic pathway. 4. What is the difference

More information

1. Why do you have to breath in

1. Why do you have to breath in 1. Why do you have to breath in O2? 2.Why is hyperventilating bad? 3.Why is it hard to breath on top of a mountain? 4.Why does being at high altitude make you tired? Unit 4 Assessment is on Tuesday December

More information

Chapter 15 part 2. Biochemistry I Introduction to Metabolism Bioenergetics: Thermodynamics in Biochemistry. ATP 4- + H 2 O ADP 3- + P i + H +

Chapter 15 part 2. Biochemistry I Introduction to Metabolism Bioenergetics: Thermodynamics in Biochemistry. ATP 4- + H 2 O ADP 3- + P i + H + Biochemistry I Introduction to Metabolism Bioenergetics: Thermodynamics in Biochemistry ATP 4- + 2 ADP 3- + P i 2- + + Chapter 15 part 2 Dr. Ray 1 Energy flow in biological systems: Energy Transformations

More information

Bioenergetics and high-energy compounds

Bioenergetics and high-energy compounds Bioenergetics and high-energy compounds Tomáš Kučera tomas.kucera@lfmotol.cuni.cz Department of Medical Chemistry and Clinical Biochemistry 2nd Faculty of Medicine, Charles University in Prague and Motol

More information

All organisms require a constant expenditure of energy to maintain the living state - "LIFE".

All organisms require a constant expenditure of energy to maintain the living state - LIFE. CELLULAR RESPIRATION All organisms require a constant expenditure of energy to maintain the living state - "LIFE". Where does the energy come from and how is it made available for life? With rare exception,

More information

AP Bio-Ms.Bell Unit#3 Cellular Energies Name

AP Bio-Ms.Bell Unit#3 Cellular Energies Name AP Bio-Ms.Bell Unit#3 Cellular Energies Name 1. Base your answer to the following question on the image below. 7. Base your answer to the following question on Which of the following choices correctly

More information

REVIEW 3: METABOLISM UNIT RESPIRATION & PHOTOSYNTHESIS. A. Top 10 If you learned anything from this unit, you should have learned:

REVIEW 3: METABOLISM UNIT RESPIRATION & PHOTOSYNTHESIS. A. Top 10 If you learned anything from this unit, you should have learned: Period Date REVIEW 3: METABOLISM UNIT RESPIRATION & PHOTOSYNTHESIS A. Top 10 If you learned anything from this unit, you should have learned: 1. Energy production through chemiosmosis a. pumping of H+

More information

Lectures by Kathleen Fitzpatrick

Lectures by Kathleen Fitzpatrick Chapter 10 Chemotrophic Energy Metabolism: Aerobic Respiration Lectures by Kathleen Fitzpatrick Simon Fraser University Figure 10-1 Figure 10-6 Conversion of pyruvate The conversion of pyruvate to acetyl

More information

Chapter 5. Table of Contents. Section 1 Energy and Living Things. Section 2 Photosynthesis. Section 3 Cellular Respiration

Chapter 5. Table of Contents. Section 1 Energy and Living Things. Section 2 Photosynthesis. Section 3 Cellular Respiration Photosynthesis and Cellular Respiration Table of Contents Section 1 Energy and Living Things Section 2 Photosynthesis Section 3 Cellular Respiration Section 1 Energy and Living Things Objectives Analyze

More information

Energy Metabolism exergonic reaction endergonic reaction Energy of activation

Energy Metabolism exergonic reaction endergonic reaction Energy of activation Metabolism Energy Living things require energy to grow and reproduce Most energy used originates from the sun Plants capture 2% of solar energy Some captured energy is lost as metabolic heat All energy

More information

Edexcel (B) Biology A-level

Edexcel (B) Biology A-level Edexcel (B) Biology A-level Topic 5: Energy for Biological Processes Notes Aerobic Respiration Aerobic respiration as splitting of the respiratory substrate, to release carbon dioxide as a waste product

More information

Photosynthesis. Chapter 10. Active Lecture Questions for use with Classroom Response Systems Biology, Seventh Edition Neil Campbell and Jane Reece

Photosynthesis. Chapter 10. Active Lecture Questions for use with Classroom Response Systems Biology, Seventh Edition Neil Campbell and Jane Reece Chapter 10 Photosynthesis Active Lecture Questions for use with Classroom Response Systems Biology, Seventh Edition Neil Campbell and Jane Reece Edited by William Wischusen, Louisiana State University

More information

Biology Reading Assignment: Chapter 9 in textbook

Biology Reading Assignment: Chapter 9 in textbook Biology 205 5.10.06 Reading Assignment: Chapter 9 in textbook HTTP://WUNMR.WUSTL.EDU/EDUDEV/LABTUTORIALS/CYTOCHROMES/CYTOCHROMES.HTML What does a cell need to do? propagate itself (and its genetic program)

More information

Photosynthesis and Cellular Respiration

Photosynthesis and Cellular Respiration Photosynthesis and Cellular Respiration What you will learn: GPS Standard SB3a Explain the cycling of energy through the processes of photosynthesis and respiration. IN OTHER WORDS Photosynthesis and Cellular

More information

arxiv: v1 [q-bio.mn] 12 Jul 2011

arxiv: v1 [q-bio.mn] 12 Jul 2011 Computing fluxes and chemical potential distributions in biochemical networks: energy balance analysis of the human red blood cell Daniele De Martino, Matteo Figliuzzi, Andrea De Martino, and Enzo Marinari

More information

Cell Respiration: Energy for Plant Metabolism

Cell Respiration: Energy for Plant Metabolism Cell Respiration: Energy for Plant Metabolism Glucose is the originating molecule for respiration Production and consumption of ATP Coupled reactions: Endergonic reactions are coupled to exergonic ones

More information

Numerical Differentiation

Numerical Differentiation Numerical Differentiation Finite Difference Formulas for te first derivative (Using Taylor Expansion tecnique) (section 8.3.) Suppose tat f() = g() is a function of te variable, and tat as 0 te function

More information

Characterization of the Metabolic Requirements in Yeast Meiosis

Characterization of the Metabolic Requirements in Yeast Meiosis Characterization of the Metabolic Requirements in Yeast Meiosis Debjit Ray 1,2, Ping Ye 1,3 * 1 School of Molecular Biosciences, Washington State University, Pullman, Washington, United States of America,

More information

Unit 1C Practice Exam (v.2: KEY)

Unit 1C Practice Exam (v.2: KEY) Unit 1C Practice Exam (v.2: KEY) 1. Which of the following statements concerning photosynthetic pigments (chlorophylls a and b, carotenes, and xanthophylls) is correct? (PT1-12) a. The R f values obtained

More information

MATH1131/1141 Calculus Test S1 v8a

MATH1131/1141 Calculus Test S1 v8a MATH/ Calculus Test 8 S v8a October, 7 Tese solutions were written by Joann Blanco, typed by Brendan Trin and edited by Mattew Yan and Henderson Ko Please be etical wit tis resource It is for te use of

More information

Energy for Life 12/11/14. Light Absorption in Chloroplasts

Energy for Life 12/11/14. Light Absorption in Chloroplasts Energy for Life Biochemical pathways A series of reactions where the products of one reaction is used in the next reaction Light Absorption in Chloroplasts Chloroplasts Two membranes Grana- layered stacks

More information

V19 Metabolic Networks - Overview

V19 Metabolic Networks - Overview V19 Metabolic Networks - Overview There exist different levels of computational methods for describing metabolic networks: - stoichiometry/kinetics of classical biochemical pathways (glycolysis, TCA cycle,...

More information