Lecture #19

Growth states of cells

Outline

• Objective functions• The BOF• The core E. coli model• The genome-scale E. coli

model• Using BOF

OBJECTIVE FUNCTIONSThree basic types

Types of objective functions

• For basic exploration and probing of solution space – lecture #20

• To represent likely physiological objectives – this lecture

• To represent bioengineering design objectives – lecture #31

Inferring the objective function

• Back calculate it from a known functional state– Burgard AP, Maranas CD. Biotechnol Bioeng. 2003

Jun 20;82(6):670-7. • Guess at multiple objectives and find the one

that fits best– Savinell JM, Palsson BO. J Theor Biol. 1992 Mar

21;155(2):215-42.– Schuetz R, Kuepfer L, Sauer U. Mol Syst Biol.

2007;3:119.

Identifying Candidate Cellular ObjectivesCalculating the cone of possible objective functions

Def

ined

Cel

lula

r Obj

ectiv

e

Mathematics

Biological Significance: Given an experimentally measured cell state, calculates range of possible objectives for which the cell could be optimizing

Example: Calculating potential objectives for Escherichia coli led to showed that optimal growth was a candidate objective function [Burgard and Maranas]

References

Burgard AP, Maranas CD. Biotechnol Bioeng. 2003 Jun 20;82(6):670-7.

Cone of possible objective functions

Measured cellular operating state

Objective Functions: fit to data

Schuetz R, Kuepfer L, Sauer U. Mol Syst Biol. 2007;3:119.

THE BIOMASS OBJECTIVE FUNCTION (BOF)

Cell growth

Properties of the BOF• Quantifiable

– Simultaneous demands on the metabolic network– Measurements needed:

• Dry Cell Weight Composition– Obtainable through standard assays

• Macromolecular breakdown– Drill-drown biochemical assays– Moving towards High-throughput measurements

• Can select for cells which display an optimal biomass formation– Adaptive Evolution enables experimental selection of cells with

optimal biomass formation (max vBOF)

Conceptual Basis: The Biomass Objective Function

Quantifying Macromolecular Content of a cell

Quantifying Building Blocks of Macromolecules

CORE E. COLI MODELStart on a small scale

Example: core E. coli growth on glucose

Compound Stoichiometry3pg -1.496

accoa -3.7478adp 59.81akg 4.1182atp -59.81coa 3.7478e4p -0.361f6p -0.0709g3p -0.129g6p -0.205

gln-L -0.2557glu-L -4.9414

h 59.81h2o -59.81nad -3.547

nadh 3.547nadp 13.0279

nadph -13.0279oaa -1.7867pep -0.5191pi 59.81

pyr -2.8328r5p -0.8977

BOF: core model

Metabolic requirements to produce 1 g cells

GlcZ

MZ

GlcM

Scaled shadow prices (σ) of metabolites

GlcM

MZ

GlcZ

Yield of metabolite

Growth yield

Shadow price of metabolite

Scaled shadow price:a dimensionless measure of the relative importance of a metabolite for producing biomass

Aerobic growth with no ATP maintenance

Biomass yield: 0.0917 gDW/g Glc

Sensitivity of Biomass Yield

0 10 20 30 40 50 60 70 80 90 10098.5

99

99.5

100

% PPS

% M

axim

al y

ield

Effect of varying flux through the pentose phosphate shunt on biomass yield

P/O ratio• Can vary the P/O ratio by altering the NADH dehydrogenase (NADH16) or

ATP synthase (ATPS4r)• Standard P/O ratio in core model: 1.25

•Set NADH16 to export 0 protons, P/O ratio = 0.5•Set ATPS4r to import 10 protons per ATP, P/O ratio = 0.5•Set ATPS4r to import 2.5 protons per ATP, P/O ratio = 2.0

Effects of Altering P/O Ratio

0.5 1 1.5 2

0.075

0.08

0.085

0.09

0.095

0.1

0.105

P/O ratio

Bio

mas

s Y

ield

(gD

W g

-1)

NADH16ATPS4r

0.5 1 1.5 20.92

0.93

0.94

0.95

0.96

0.97

0.98

P/O ratio

ATP

sca

led

shad

ow p

rice,

NADH16ATPS4r

The biomass yield is slightly more sensitive to changes in NADH transhydrogenase than in ATP synthase

The scaled shadow price of ATP is lower when the P/O ratio is lower

BOF Maintenance Parameters:Quantifying non-metabolic activity

0

8.39

59.81mmol ATP gDW-1 hr-1

ATP Maintenance Requirements• Set nonzero lower bounds on ATPM

reaction to simulate non-growth associated consumption of ATP

• Effects of maintenance requirement on use of pentose phosphate shunt:

0 10 20 30 40 50 60 70 80 90 10096

96.5

97

97.5

98

98.5

99

99.5

100

100.5

% PPS

% M

axim

al y

ield

0 ATP4 ATP6 ATP

0 2 4 6 8 10 12 14 16 180

10

20

30

40

50

60

ATP maintenance/Glc (mol mol-1)

% P

PS

0 2 4 6 8 10 12 14 16 180

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

ATP maintenance/Glc (mol mol-1)

Bio

mas

s Y

ield

(gD

W g

-1)

Yield sensitivity at 3 different ATPM req.

Optimal PPS flux vs. ATPM req.

Max biomass vs. ATPM req.

Max ATP yield = 17.5

ATP Maintenance Requirements

0 2 4 6 8 10 12 14 16 180

1

2

3

4

5

6

7

8

9

ATP maintenance/Glc (mol mol-1)

NA

DP

H y

ield

(mol

mol

-1

0 2 4 6 8 10 12 14 16 187.8

8

8.2

8.4

8.6

8.8

9

9.2x 10

-3

ATP maintenance/Glc (mol mol-1)

NA

DP

H s

hado

w p

rice

(gD

W m

mol

-1)

0 2 4 6 8 10 12 14 16 180.78

0.79

0.8

0.81

0.82

0.83

0.84

0.85

0.86

0.87

0.88

ATP maintenance/Glc (mol mol-1)

NA

DP

H s

cale

d sh

adow

pric

e,

•Effects of ATPM on NADPH yield and shadow price•The discontinuity occurs because optimal pathway use for production of biomass shifts

NADPH shadow price

NADPH yield

NADPH scaled shadow price

Effect of Precursor Drain

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

PEP drain (mol mol-1 Glc)

Bio

mas

s Y

ield

(gD

W g

-1)

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

0.2

0.4

0.6

0.8

1

1.2

1.4

PEP drain (mol mol-1 Glc)

scal

ed s

hado

w p

rice,

ATPNADPHPEPE4P

•Drain PEP from the system and maximize biomass•Several discontinuities occur, each at a change in the flux distribution•At a PEP drain of above 1.9, excess ATP and NADPH are produced, so their shadow prices are 0

Growth on other substrates

Substrate

Growth Rate (UR = -10) Growth Rate (UR = -20) Growth Rate (UR = -30)

Aerobic Anaerobic Aerobic Anaerobic Aerobic Anaerobic

acetate 0.1733 0 0.3893 0 0.6053 0

acetaldehyde 0.2842 0 0.6073 0 0.9303 0

α-ketoglutarate 0.5287 0 1.0982 0 1.6676 0

ethanol 0.3304 0 0.6696 0 1.0687 0

fructose 0.8739 0.2116 1.7906 0.5163 2.7072 0.8208

fumarate 0.3707 0 0.7865 0 1.2022 0.0358

glucose 0.8739 0.2116 1.7906 0.5163 2.7072 0.8208

L-glutamine 0.5592 0 1.1636 0 1.7679 0

L-glutamate 0.5987 0 1.2425 0 1.8862 0

D-lactate 0.3503 0 0.7403 0 1.1303 0.0289

L-malate 0.3707 0 0.7865 0 1.2022 0.0358

pyruvate 0.2912 0 0.6221 0.0655 0.953 0.1399

succinate 0.3975 0 0.8401 0 1.2827 0

•Simulated growth on all 13 biomass producing substrates at different uptake rates, aerobically and anaerobically, with ATPM = 8.39

Example: Growth on acetate, aerobic

Acetate uptake rate = 10 mmol gDW-1 hr-1

Growth rate = 0.1733 hr-1

GENOME-SCALE E. COLI MODEL

The Biomass Objective Function:Genome-scale

Quantifying Macromolecular Content of a cell

Quantifying Building Blocks of Macromolecules

Procedure to Generate a Detailed Biomass Objective Function

2 3BOFWT BOFCORE

BOF: Average and Essential Cellular Composition

• Define components of average cell• Analysis of essential biomass components

– Biomass objective function• Core• Upgrades

BOFWT = Core + Upgrades

BOFCORE= Core

• Non-metabolic costs for cellular activity exist– Protein Synthesis and Breakdown– RNA/DNA polymerization– Membrane Leakage

• Non-metabolic costs– Approximated through ATP usage– Experimental growth data necessary to quantify– Two types: Growth and Non-Growth Associated

BOF Maintenance Parameters:Accounting for non-metabolic activity

Energy Cost: ATP + H2O ADP + H + Pi

BOF Maintenance Parameters:Quantifying non-metabolic activity

0

8.39

59.81mmol ATP gDW-1 hr-1

Typical 'wild type' compositionProtein (55.0%) Lipid (9.1%)L-alanine L-arginine L-asparagine structureL-aspartate L-cysteine L-glutamine phosphatidylethanolamineL-glutamate glycine L-histidine phosphatidylglycerol #

cardiolipinL-isoleucine L-leucine L-lysine acyl chain length : number of unsaurated bondsL-methionine L-phenylalanine 16:0 16:1 18:1

L-proline L-serine L-threonine LPS (3.4%)L-tryptophan L-tyrosine L-valine inner/outer core KDO 2 lipid A

RNA (20.5%) Cofactors, Prosthetic Groups and Other (<2.9%)ATP CTP GTP S-adenosylmethionine FAD coenzyme A NAD(P)UTP thiamine diphosphate riboflavin undecaprenyl pyrophosphate

DNA (3.1%) pyridoxal 5'-phosphate * folates quinones hemes dATP dCTP dGTP chorismate enterobactin glutathione putrescinedTTP spermidine vitamin B12

Inorganic ions (1.0%) Murein (2.5%)ammonium calcium chlorine structurecobalt copper iron murein disaccharidemagnesium manganese molybdate peptide chain lengthphosphorous potassium sulfate pentapeptide tetrapeptide tripeptide

zinc Glycogen (2.5%)glycogen

'Core' biomass composition substritutesinner/outer core KDO 2 lipid A : substituted with KDO 2 lipid (IV) Aquinones : substituted with 2-octaprenyl-6-hydroxyphenolhemes : protoheme; siroheme includedfolates : tetrahydrofolate; 10-formyltetrahydrofolate; 5,10-Methylenetetrahydrofolate included

Biomass Objective Function of E. coli

Black – always essential Blue – have minimal component(s) Red – non-essentialBOFwt = All BOFcore = Black + Blue

E. coli Reconstruction – iAF1261

Calculation and

organization of data:

Equation should be

easily adjustable

Ecoli Biomass

Macromolecule overall wt% composition

(molar fraction)mmol/gDW

(Calc.) metabolite location type formula C H N

[1] pg. 96 Protein 0.55 0.096 0.487624 ala-L cytoplasm AA C3H7NO2 3 7 1[1] pg. 96 0.055 0.280783 arg-L cytoplasm AA C6H15N4O2 6 15 4[1] pg. 96 0.045 0.228823 asn-L cytoplasm AA C4H8N2O3 4 8 2[1] pg. 96 0.045 0.228823 asp-L cytoplasm AA C4H6NO4 4 6 1[1] pg. 96 0.017 0.086933 cys-L cytoplasm AA C3H7NO2S 3 7 1[1] pg. 96 0.049 0.249807 gln-L cytoplasm AA C5H10N2O3 5 10 2[1] pg. 96 0.049 0.249807 glu-L cytoplasm AA C5H8NO4 5 8 1[1] pg. 96 0.115 0.581551 gly cytoplasm AA C2H5NO2 2 5 1[1] pg. 96 0.018 0.089931 his-L cytoplasm AA C6H9N3O2 6 9 3[1] pg. 96 0.054 0.275787 ile-L cytoplasm AA C6H13NO2 6 13 1[1] pg. 96 0.084 0.427670 leu-L cytoplasm AA C6H13NO2 6 13 1[1] pg. 96 0.064 0.325748 lys-L cytoplasm AA C6H15N2O2 6 15 2[1] pg. 96 0.029 0.145887 met-L cytoplasm AA C5H11NO2S 5 11 1[1] pg. 96 0.035 0.175864 phe-L cytoplasm AA C9H11NO2 9 11 1[1] pg. 96 0.041 0.209838 pro-L cytoplasm AA C5H9NO2 5 9 1[1] pg. 96 0.040 0.204842 ser-L cytoplasm AA C3H7NO3 3 7 1[1] pg. 96 0.047 0.240814 thr-L cytoplasm AA C4H9NO3 4 9 1[1] pg. 96 0.011 0.053958 trp-L cytoplasm AA C11H12N2O2 11 12 2[1] pg. 96 0.026 0.130899 tyr-L cytoplasm AA C9H11NO3 9 11 1[1] pg. 96 0.079 0.401690 val-L cytoplasm AA C5H11NO2 5 11 1

GC content for E. coli K-12mg1655 (50.8%) DNA 0.031 0.246 0.024805 datp cytoplasm DNA C10H12N5O12P3 10 12 5GC content for E. coli K-12mg1655 (50.8%) 0.254 0.025612 dctp cytoplasm DNA C9H12N3O13P3 9 10 3GC content for E. coli K-12mg1655 (50.8%) 0.254 0.025612 dgtp cytoplasm DNA C10H12N5O13P3 10 12 5GC content for E. coli K-12mg1655 (50.8%) 0.246 0.024805 dttp cytoplasm DNA C10H13N2O14P3 10 13 2

[1] pg. 98 RNA 0.205 0.200 0.126709 ctp cytoplasm RNA C9H12N3O14P3 9 12 3[1] pg. 98 0.322 0.204142 gtp cytoplasm RNA C10H12N5O14P3 10 12 5[1] pg. 98 0.216 0.136765 utp cytoplasm RNA C9H11N2O15P3 9 11 2[1] pg. 98 0.262 0.165928 atp** cytoplasm RNA C10H12N5O13P3 10 12 5[1] pg. 4 glycogen 0.025 1 0.154187 glycogen cytoplasm carbohydrate C6H10O5 6 10 0

[1] pg. 4, see 'murein' worksheet murein 0.025 0.4 0.005381 murein4p4p periplasm murein C74H114N14O40 74 114 14[1] pg. 4, see 'murein' worksheet 0.1 0.001345 murein3p3p periplasm murein C68H104N12O38 68 104 12[1] pg. 4, see 'murein' worksheet 0.405 0.005448 murein4px4p periplasm murein C74H112N14O39 74 112 14[1] pg. 4, see 'murein' worksheet 0.045 0.000605 murein3px4p periplasm murein C71H107N13O38 71 107 13[1] pg. 4, see 'murein' worksheet 0.05 0.000673 murein4px4px4p periplasm murein C111H167N21O58 111 167 21

[1] pg. 4, and NH pg 1041 (essentially all laboratory strains of E. coli K-12 lack O-antigen, a rough phenotype), pg 15 NH in table LPS 0.034 1 0.008151 colipa extra-cellular face LPS C176H303N2O100P4 176 303 2[1] pg. 4, see 'lipid' worksheet lipid 0.091 0.3513 0.043215 pe160 cytoplasm / periplasm lipid C37H74N1O8P1 37 74 1[1] pg. 4, see 'lipid' worksheet 0.2732 0.033611 pe161 cytoplasm / periplasm lipid C37H70N1O8P1 37 70 1[1] pg. 4, see 'lipid' worksheet 0.1408 0.017324 pe181 cytoplasm / periplasm lipid C41H78N1O8P1 41 78 1[1] pg. 4, see 'lipid' worksheet 0.0843 0.010371 pg160 cytoplasm / periplasm lipid C38H74O10P1 38 74 0[1] pg. 4, see 'lipid' worksheet 0.0656 0.008067 pg161 cytoplasm / periplasm lipid C38H70O10P1 38 70 0[1] pg. 4, see 'lipid' worksheet 0.0338 0.004158 pg181 cytoplasm / periplasm lipid C42H78O10P1 42 78 0[1] pg. 4, see 'lipid' worksheet 0.0234 0.002881 clpn160 periplasm lipid C73H140O17P2 73 140 0[1] pg. 4, see 'lipid' worksheet 0.0182 0.002241 clpn161 periplasm lipid C73H132O17P2 73 132 0[1] pg. 4, see 'lipid' worksheet 0.0094 0.001155 clpn181 periplasm lipid C81H148O17P2 81 148 0

[1] pg. 21 for type and breakdown is an estimation inorganic ions 0.01 0.7143 0.169185 k cytoplasm inorganic ions K[1] pg. 21 for type and breakdown is an estimation 0.0476 0.011279 nh4 cytoplasm inorganic ions H4N 0 4 1[1] pg. 21 for type and breakdown is an estimation 0.0317 0.007519 mg2 cytoplasm inorganic ions Mg[1] pg. 21 for type and breakdown is an estimation 0.0190 0.004512 ca2 cytoplasm inorganic ions Ca[1] pg. 21 for type and breakdown is an estimation 0.0286 0.006767 fe2 cytoplasm inorganic ions Fe[1] pg. 21 for type and breakdown is an estimation 0.0286 0.006767 fe3 cytoplasm inorganic ions Fe[1] pg. 21 for type and breakdown is an estimation 0.0127 0.003008 cu2 cytoplasm inorganic ions Cu[1] pg. 21 for type and breakdown is an estimation 0.0127 0.003008 mn2 cytoplasm inorganic ions Mn[1] pg. 21 for type and breakdown is an estimation 0.0127 0.003008 mobd cytoplasm inorganic ions MoO4[1] pg. 21 for type and breakdown is an estimation 0.0127 0.003008 cobalt2 cytoplasm inorganic ions Co[1] pg. 21 for type and breakdown is an estimation 0.0127 0.003008 zn2 cytoplasm inorganic ions Zn[1] pg. 21 for type and breakdown is an estimation 0.0190 0.004512 cl cytoplasm inorganic ions Cl[1] pg. 21 for type and breakdown is an estimation 0.0159 0.003760 so4 cytoplasm inorganic ions O4S 0 0 0[1] pg. 21 for type and breakdown is an estimation 0.0159 0.003760 pi** cytoplasm inorganic ions HO4P 0 1 0

soluble pool 0.029 0.033270 ptrc cytoplasm polyamine C4H14N2 4 14 20.006744 spmd cytoplasm polyamine C7H22N3 7 22 3

UTILIZATION OF THE BIOMASS OBJECTIVE FUNCTION

Reconstruction to Predictive Model: How the BOF gets used (Panels D & E)

• Key biological factors to consider when using a reconstruction as a predictive model (A – D)

• Prediction of physiological behavior (E)

Which Parameters Matter?:Sensitivity Analysis on BOF Components

• Examining the key parameters associated with optimal growth predictions

– Protein, RNA, Lipid content– P/O ratio– Maintenance parameters

• NGAM – non-growth associated maintenance

• GAM - non-growth associated maintenance

• Condition specific ?– Substrate conditions– Evolutionarily stable

50–80% 10–25%

7–15% 1.0–2.7

50% 50%

Reaction Essentiality

in Generating

Biomass Precursors

Biomass Yield Precursor Yields (mmol precusor/mmol glucose)Reaction Deleted (g DW/mmol glucose) 3pg accoa akg e4p f6p g3p g6p oaa pep pyr r5pACKr 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05ACONT 0 2.00 2.00 0 1.22 0.83 1.57 0.83 1.50 2.00 2.00 1.00ACt2r 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05ADHEr 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05ADK1 0.09 1.50 2.00 1.00 1.13 0.75 1.50 0.75 1.50 1.50 2.00 0.90AKGt2r 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05ATPS4r 0.04 1.67 2.00 1.00 1.00 0.71 1.25 0.71 1.50 1.67 2.00 0.83CO2t 0.05 2.00 2.00 1.00 1.08 0.76 1.37 0.76 1.50 2.00 2.00 0.90CS 0 2.00 2.00 0 1.22 0.83 1.57 0.83 1.50 2.00 2.00 1.00CYTBD 0.02 1.00 1.00 0.40 0.90 0.65 1.11 0.65 0.67 1.00 1.00 0.76D-LACt2 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05ENO 0 2.00 0 0 1.22 0.83 1.57 0.83 0 0 0 1.00ETOHt2r 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05FBA 0.07 1.00 1.00 0.50 1.00 0.87 1.00 0.87 1.00 1.00 1.00 1.00FBP 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05FORt 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05FRD 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05FUM 0.08 2.00 2.00 1.00 1.22 0.83 1.57 0.83 1.50 2.00 2.00 1.00FUMt2_2 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05G6PDH2r 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05GAPD 0 0 0 0 1.22 0.83 1.57 0.83 0 0 0 1.00GLCpts 0 0 0 0 0 0 0 0 0 0 0 0GND 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05H2Ot 0.04 1.00 1.00 0.50 0.60 0.50 0.67 0.50 0.67 0.50 1.00 0.55ICDHyr 0 2.00 2.00 0 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05ICL 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05LDH_D 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05MALS 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05MDH 0.08 2.00 2.00 1.00 1.24 0.86 1.60 0.86 1.50 2.00 2.00 1.01ME1 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05ME2 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05NADH11 0.02 1.00 1.00 0.40 0.90 0.65 1.11 0.65 0.67 1.00 1.00 0.76O2t 0.02 1.00 1.00 0.40 0.90 0.65 1.11 0.65 0.67 1.00 1.00 0.76PDH 0.08 2.00 2.00 1.00 1.27 0.87 1.64 0.87 1.50 2.00 2.00 1.03PFK 0.07 1.00 1.00 0.50 1.00 0.87 1.00 0.87 1.00 1.00 1.00 1.00PFL 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05PGI 0.08 1.67 1.67 0.83 1.23 0.83 1.60 0.88 1.50 1.67 1.67 1.00PGK 0 0 0 0 1.22 0.83 1.57 0.83 0 0 0 1.00PGL 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05PGM 0 2.00 0 0 1.22 0.83 1.57 0.83 0 0 0 1.00PIt 0 0 2.00 1.00 0 0 0 0 1.50 0 2.00 0PPC 0.09 2.00 2.00 0.67 1.30 0.89 1.68 0.89 1.00 2.00 2.00 1.05PPCK 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05PPS 0.09 1.50 2.00 1.00 1.13 0.75 1.50 0.75 1.50 1.50 2.00 0.90PTAr 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05PYK 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05PYRt2r 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05RPE 0.09 2.00 2.00 1.00 1.25 0.89 1.68 0.89 1.50 2.00 2.00 1.00RPI 0 2.00 2.00 1.00 0 0.89 1.68 0.89 1.50 2.00 2.00 0SUCCt2_2 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05SUCCt2b 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05SUCD1i 0.08 2.00 2.00 1.00 1.22 0.83 1.57 0.83 1.50 2.00 2.00 1.00SUCD4 0.08 2.00 2.00 1.00 1.22 0.83 1.57 0.83 1.50 2.00 2.00 1.00SUCOAS 0.08 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05TALA 0.09 2.00 2.00 1.00 0 0.89 1.68 0.89 1.50 2.00 2.00 1.00TEST_AKGDH 0.08 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05TEST_NADTRHD 0.09 2.00 2.00 0 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05THD2 0.09 2.00 2.00 1.00 1.30 0.89 1.68 0.89 1.50 2.00 2.00 1.05TKT1 0.09 2.00 2.00 1.00 0 0.89 1.68 0.89 1.50 2.00 2.00 1.00TKT2 0.09 2.00 2.00 1.00 1.00 0.89 1.68 0.89 1.50 2.00 2.00 1.00TPI 0.07 1.00 1.00 0.50 1.00 0.87 1.00 0.87 1.00 1.00 1.00 1.00

Black - EssentialGray - Nonessential but InfluentialWhite – No Affect

ALA

AR

G

ASN

ASP

CY

S

GLU

GLN

GLY

HIS

ILE

LEU

LYS

MET

PHE

PRO

SER

THR

TRP

TYR

VAL

ATP

GTP

CTP

UTP

DAT

P

DG

TP

DC

TP

DTT

P

PS PE PG PEPT

IDO

LPS

PTR

C

SPM

D

OPP

UD

PP

NA

D

NA

DP

FAD

CO

A

AC

P

HO

THIA

MIN

MTH

F

MK

DM

K

GLY

CO

GEN

pgifbafbptpiAgapApgkgpmAenorpiAtktAprsAppc

ALA

AR

G

ASN

ASP

CY

S

GLU

GLN

GLY

HIS

ILE

LEU

LYS

MET

PHE

PRO

SER

THR

TRP

TYR

VAL

ATP

GTP

CTP

UTP

DAT

P

DG

TP

DC

TP

DTT

P

PS PE PG PEPT

IDO

LPS

PTR

C

SPM

D

OPP

UD

PP

NA

D

NA

DP

FAD

CO

A

AC

P

HO

THIA

MIN

MTH

F

MK

DM

K

GLY

CO

GEN

pgifbafbptpiAgapApgkgpmAenorpiAtktAprsAppc

Application: Gene Deletions & Production Deficiencies

H. Influenzae Central Metabolism50 Biomass Requirements

Genes of Central Metabolism

Minimal Substrate Conditions

(fructose)

Carbon-supplementedConditions

(fructose, glucose, glycerol, galactose, fucose, ribose, and sialic acid)

Production Capabilities Under Two Environmental Conditions:Production Capabilities Under Two Environmental Conditions: 1. 1. ““in vitroin vitro”” Minimal Media (fructose) Minimal Media (fructose) 2. 2. ““in vivoin vivo”” Complete Conditions (multiple carbon sources) Complete Conditions (multiple carbon sources)

Analysis of alternate growth conditions: BOF enabled prediction of phenotypes

experimental

sourcepotential

substratessupport growth

potential sub. matches growth none % e=none

c=yese=growth

c=no %

carbon 262 174 87 54 11 75% 22 0 25%nitrogen 162 79 51 28 8 71% 8 7 29%phosphorous 63 49 20 20 0 100% 0 0 0%sulfur 25 11 5 4 0 80% 0 1 20%

computational agreement disagreement

• Examined all 300 different exchange reactions for their ability to support growth

• Compared results to Biolog ® Data for E. coli

validation• regulation• errors

• discovery targets

parallelconcept

Summary• Growth is enabled by the balanced production of all the

compounds necessary for growth• For a core metabolic model, growth can be represented by

the balanced production of the 12 biosynthetic precursors• Maintenance parameters are needed for metabolic demands

other than the stoichiometric requirement for growth• Model can be interrogated for many parameters: the

glycolysis/ppp split, the P/O ratio, maintenance parameters, substrates, etc

• At the genome-scale several complicating factors appear: BOF=core + upgrades, variable P/O, etc

The end