Quantitative Studies of Nitrogen Assimilation in E. coli · Nitrogen assimilation •GDH-GS...

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Quantitative Studies ofNitrogen Assimilation in E. coli

Peter Lenz

Collaboration with T. Hwa, S. Kustu, Y. Wang and D. Yan

Bacterium able to produce exact copy of itselfdoubling time: T=20-200min (depending onenvironment/media)

The life of a bacterium

life of a bacterium:matter + energy → biomass

E. coli (minimal medium):glucose + NH3 → biomass

Only produced what'snot available→bacteria can sense the

environment and adjustits “growth program”according to nutrientsprovided by the medium

Bacterium able to produce exact copy of itselfdoubling time: T=20-200min (depending onenvironment/media)

The life of a bacterium

life of a bacterium:matter + energy → biomass

E. coli (minimal medium):glucose + NH3 → biomass

DNA-replication:

T<60min: several replication forks

DNA for grand-children is replicated

Bacterium able to produce exact copy of itselfdoubling time: T=20-200min (depending onenvironment/media)

The life of a bacterium

life of a bacterium:matter + energy → biomass

E. coli (minimal medium):glucose + NH3 → biomass

→bacteria can sense theenvironment and adjustits “growth program”according to nutrientsprovided by the medium

Adjustment of growth program:

Faster growing bacteria

•have more ribosomes

•have more DNA

•are bigger

Optimal growth

Central questions:• What’s the optimal way of partitioning the cell’s activity in producing

ribosomes, proteins, DNA ...→What's the optimal way for setting up a bacterium?

• What sets/determines growth rate?• Which regulation guarantees optimal growth under varying conditions?

Bacteria need to optimize their growth rate:evolutionary pressure

97%50%%bacteria with µ=60min3%50%%bacteria with µ=66min

t=48ht=0

Molecular view of growth: Metabolism

‘Modules’=production units.

E.coli metabolic network:

~250 pathways

~1500 enzymes

~2000 reactions

~1200 compounds

Molecular view of growth: Metabolism

Nitrogen assimilation ‘module’

Coupled to carbon, energyand amino acids ‘modules’

Nitrogen assimilation

•GDH-GS pathway: high ammonia

energetically preferred, but GDH has low affinity for NH3 (large KM)

•GS-GOGAT pathway: dominant for energy rich conditions at low [NH3]

Well defined module: 3 enzymes, 3 metabolites

Common view:

Coupling to growth

High AmmoniaLow Ammonia

Coupling to growth

High AmmoniaLow Ammonia

transaminase current

Coupling to growth

High AmmoniaLow Ammonia

Precursor Amino acid

Proteins

Coupling to growth

High Ammonia

N-Demand: Gln,Glu→amino acids

Balance of currents Cycles run 109 times/doubling time!

Low Ammonia

N-demand:transaminase current

N-supply

Coupling to carbon

JaKG

aKG is gatekeeper

Energy-production: dependson carbon source

Sugar from medium

aKG regulates fluxinto bypass

Coupling to carbon

Optimal growth: balance of all components (N, C, Energy) Centrale role: aKG

JaKG

Allosteric and transcriptional regulation of GS

high Gln/aKG ratio deactivates GS, low Gln/akG activates GS

12 active sitesturned on/off

transcription on

transcription off

GS-activity can be fine-tuned over several orders of magnitude!

bifunctionalprotein

Allosteric and transcriptional regulation of GS

high Gln/aKG ratio deactivates GS, low Gln/akG activates GS

transcription on

transcription off

GS-activity can be fine-tuned over several orders of magnitude!

GlnAp1: σ70

+ : CRP

- : NtrC-P

GlnAp2: σ54

+ : NtrC-P

- : CRP

Allosteric and transcriptional regulation of GS

high Gln/aKG ratio deactivates GS, low Gln/akG activates GS

transcription on

transcription off

GS-activity can be fine-tuned over several orders of magnitude!

Why? What’s theadvantage of thisregulation?

Steady state analysis

Steady state analysis

measured dependence of #a.aper cell, cell mass on DT[Bremer & Dennis, 1996]

Steady state analysis

parameters known from invitro assays

First model: only transcriptional regulation of GS taken into account:

CS, GDH, GG: constant #/cell

Only free parameters

Steady state analysis

Feedback regulation of JaKG

CS and aKGDH-levels depend oncarbon source and energy status.For fixed carbon source, [aKG]directly depends on growth rate andis independent of the details of theGS/GG/GDH system

Steady state analysis

3 equations for 4 unknowns([aKG],[Glu],[Gln],JAA)

want to solve for varying [NH3]

A Physiological constraint

High glutamate level crucial for growth

NH4 upshift Glu is main counterion for K+

[K+] can be changed by osmolarity ofmedium later

Yan & Kustu (1996)

1st attempt: GS-GG cycle (low NH3)

•no GDH

•assume that Glu-level is set externally

3 equations for 3 unknowns([aKG],[Gln],JAA)

Steady state: nosignificant differencesbetween different GS-regulation strategies

Back to full model

3 equations for 4 unknowns([aKG],[Glu],[Gln],JAA)

want to solve for varying [NH3]

GOGAT-

070927 WT (FG1047) & GOGAT- (FG1195)

0 50 100 150 200 250 300 350 400

0.1

1

WT_10mM NH4+

GG-_10mM NH4+

GG-_8mM NH4+

GG-_6mM NH4+

GG-_4mM NH4+

GG-_2mM NH4+

Time (min)

OD600

WT: maintains exponential growthuntil hardly any NH4 left

GG: slows down as NH4 used up

GOGAT-: Linear Pathway: aKG Glu GlnGDH GS

GOGAT-

Dalai Yan, PNAS 2007

Change in osmolarity leads tochange in Glu-level

WT and suppressor mutants

⇒GOGAT-: direct correlation between growth rate and Glu-level

Theoretical proposition

Ribosomal activity =

Propose: relation from the control of a.a. level on growth rate

Mediated via stringentresponse (ppGpp)

Stringent responsedue to uncharging oftRNA-Gln

hypothesizeddependence ofribosome activiy onthe Glu (or K+) level

depends on osmolarity(1 more free parameter)

Full model: steady state

3 equations for 3 unknowns([aKG],[Glu],[Gln])

Full model: steady state

GDH sets growth rate

Comparison with experimental data: GG-

key parameters:KNH3 =1.1mMk+ = 825/sec (>> k-)[Sakamoto et al(1975)]

Best fit: 350 GDH/cell

Only weak influence

Growth rate setby N-supplyfrom GDH

suggests constant GDH level

• best-fit: 560 CS, 30 aKGDH• measurement: 600 CS (Robinson et al, 1983) 70 aKGDH (Waskiewica & Hammes,1984)

Comparison with experimental data: GG-

Comparison with experimental data: GG-

Gln produced by GS: supply>demand → minimal supply: basal GS activity

basal GS activity

Comparison with experimental data: GG-

Gln produced by GS: supply>demand → minimal supply: basal GS activity

basal GS activity basal GS activity + Gln leakage/ degradation

best fit: ~150 GS/cell+ 30% Gln/hr leakage

Comparison with experimental data: GG-

Gln produced by GS: supply>demand → minimal supply: basal GS activity

basal GS activity basal GS activity + Gln leakage/ degradation

best fit: ~150 GS/cell+ 30% Gln/hr leakage

Glutaminase B?

Comparison with experimental data: GG-

Glu produced by GDH

Result of ‘ribosome model’: single fit parameter J0 works for GG- and WT

Comparison with experimental data: GG-

Glu produced by GDH

High osmolarity: lower J0

Comparison with experimental data: GG-

Comparison with experimental data: GG- (high osm.)

Increase in Glu-pool → increased Gln-pool?

Comparison with experimental data: GG- (high osm.)

aKG pool: data describedby the same model

originalGDH model

with Gln-inhibition(Sakamoto)

Best fit: 40% reduction inGDH-level

Theoretical predictions: mutants

Other mutants: glnE, inducible GSmin, inducible CS

GDH kinetic parameters

Km depend ontemperature, salt…

⇒wrong Km used!

KNH4=8.3 mM and notKNH4=1.1 mM

GDH assay: direct measurement ofGDH activity

GG- data converted in GDH activity(with theoretical model)

GDH kinetic parameters

Km depend ontemperature, salt…

⇒wrong Km used!

KNH4=8.3 mM and notKNH4=1.1 mM

→ GDH isreversible

GDH kinetic parameters

Km depend ontemperature, salt…

⇒wrong Km used!

KNH4=8.3 mM and notKNH4=1.1 mM

constantGDH level

increase in GDH levelwith decrease in N

Reversible GDH reaction

New parameters not compatible with constant GDH level

Reversible GDH reaction

New parameters not compatible with constant GDH level

Single cell: volume doubles during growth

Test new GDH parameters in vivo

gdhrbs

gdhrbs

Pgdh

Ptet

Construct strain (NQ5) with weak constitutive gdh expression in GG- background removes possible regulation

• qualitatively consistent with large KNH4• cannot directly fit GDH kinetics because poolsand GDH amount all depend on growth rate

Ensemble measurements

Measurements per OD (~cell mass):

•GDH amount (from quantitativeWestern)

•Pool sizes

NH4 consumption ~ 3mM per OD600Compulsory binding:

! =[NADP]

KNADP

[NADPH ]

KNADPH

Unknown parameter:

(E. coli in glucose: η≈0.3)

Ensemble measurements

Measurements per OD (~cell mass):

•GDH amount (from quantitativeWestern)

•Pool sizes

NH4 consumption ~ 3mM per OD600Compulsory binding:

! =[NADP]

KNADP

[NADPH ]

KNADPH

Unknown parameter:

(E. coli in glucose: η≈0.3)

Test: in vitro

Ensemble measurements

NH4 consumption ~ 3mM per OD600Compulsory binding:

! =[NADP]

KNADP

[NADPH ]

KNADPH

Unknown parameter:

(E. coli in glucose: η≈0.3)

Ultimate test in WT: GDH runs in reverse for NH4<2mM: stronglyoverexpressed GDH should lead to growth defect

Key findings and outlook

Microscopic analysis of cell growth

Theoretical model based on•biochemical characterization of enzymes

•coupling to transamination current

Comparison with exp. measured pool sizes/enzyme levels•Gln leakage/degradation

•Gln-inhibition of GDH

•reversible GDH reaction

•GS basal level

General lessons•mutants elucidate specific aspects of regulation

•every detail matters!

•single cell vs. ensemble measurement

Outlook:•WT: aKG/Gln regulation of GS