Download Venice, Sep 2010 - Theoretical Biochemistry Group

Towards Quantitative Models of
Photosynthetic Growth
Rainer Machné
joint work with
Douglas B. Murray, Christoph Flamm,
Stefan Müller, James Lu, Clemens Zarzer, Philipp Kügler
Ladislav Nedbal, Jan Červený, Martin Trtílek
Institute for Theoretical Chemistry, University of Vienna, Austria
IAB Tsuruoka, Keio University, Japan
RICAM Sys.Bio. Group, Austrian Academy of Sciences, Austria
PSI - Photon System Instruments, Czech Republic
Harvest Meeting, Venice 2010
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Continuous Culture: Stable Growth Conditions
MONOD 1941ff. - CELL GROWTH IN CONTINUOUS CULTURE
Dilution rate
Substrate S
Biomass B ( or cell number C)
Average growth rate
Steady State @ Ḃ = 0
average cell doubling time
Eigen & Schuster 1979:
RNA World/Hypercycle/Quasispecies
LIFE AS AN
AUTO-CATALYTIC ENZYME
φ
Ṡ = −v µB + φ(Sin − S)
Ḃ = µB − φB
µ = µmax K S
+S
µ=φ
T2 =
ln(2)
µ
Monod, J: La technique de culture continue, théorie et applications.
Ann Inst Pasteur 1950
⇒ QUANTITATIVE BIOLOGY ⇐
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Continuous Culture: Stable Growth Conditions
Dougie-sensei, IAB Tsuruoka
Yeast Respiratory Cycles
Lada Nedbal, Jan Červený, Martin Trtílek, Photon System Instruments
Algal Growth under Varying Light Conditions
Saccharomyces cerevisiae
Cyanobacteria: Synechocystis sp. pcc6803, Synechococcus elongatus pcc7942,
Cyanothece sp. ATCC 51142, ...
⇒ QUANTITATIVE BIOLOGY ⇐
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Continuous Culture: Growth , Yeast
Total Mass Flow Measured
◮ BIOMASS YIELD
Y = [DCW ] ∗ VL ∗ φ ∗ t [g]
YC = Y ∗ cCc [C-mol]
◮
Total O2 exchanged
R
dO2 = 0t ([O2 ] ∗ A)dt [mol]
◮
Total CO2 exchanged
R
dCO2 = 0t ([CO2 ] ∗ A)dt [mol]
Catabolic & Anabolic
Stoichiometries Calculated
1. Yield per O2
YO = YC /dO2 [C-mol/mol]
2
1. Set
dilution rate φ [/h] and aeration rate [l/h] A
2. Measure
- dry cell weight: DCW [g/l]
- cell carbon content: cCc [C-mol/g]
- offgas: O2 , CO2 [mol/l]
3. Add Knowledge - e.g. ∆G intermediates
- substrate-specific stoichiometries of TCA
- C/O ratio: CO2 produced per O2 consumed
- P/O ratio: ATP produced per O2 consumed
2. Anabolic CO2
dCO2 cd = dO2 ∗ (C/O) [mol]
dCO2 ab = dCO2 − dCO2 cd [mol]
3. Yield per ATP
YATP = YO /(P/O) [C-mol/mol]
2
⇒ only valid on
non-fermentable substrates! ⇐
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Continuous Culture: Growth , Yeast
Total Mass Flow Measured
◮ BIOMASS YIELD
Y = [DCW ] ∗ VL ∗ φ ∗ t [g]
YC = Y ∗ cCc [C-mol]
◮
Total O2 exchanged
R
dO2 = 0t ([O2 ] ∗ A)dt [mol]
◮
Total CO2 exchanged
R
dCO2 = 0t ([CO2 ] ∗ A)dt [mol]
Catabolic & Anabolic
Stoichiometries Calculated
1. Yield per O2
YO = YC /dO2 [C-mol/mol]
2
1. Set
dilution rate φ [/h] and aeration rate [l/h] A
2. Measure
- dry cell weight: DCW [g/l]
- cell carbon content: cCc [C-mol/g]
- offgas: O2 , CO2 [mol/l]
3. Add Knowledge - e.g. ∆G intermediates
- substrate-specific stoichiometries of TCA
- C/O ratio: CO2 produced per O2 consumed
- P/O ratio: ATP produced per O2 consumed
2. Anabolic CO2
dCO2 cd = dO2 ∗ (C/O) [mol]
dCO2 ab = dCO2 − dCO2 cd [mol]
3. Yield per ATP
YATP = YO /(P/O) [C-mol/mol]
2
⇒ only valid on
non-fermentable substrates! ⇐
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Continuous Culture: Growth , Yeast
Total Mass Flow Measured
◮ BIOMASS YIELD
Y = [DCW ] ∗ VL ∗ φ ∗ t [g]
YC = Y ∗ cCc [C-mol]
◮
Total O2 exchanged
R
dO2 = 0t ([O2 ] ∗ A)dt [mol]
◮
Total CO2 exchanged
R
dCO2 = 0t ([CO2 ] ∗ A)dt [mol]
Catabolic & Anabolic
Stoichiometries Calculated
1. Yield per O2
YO = YC /dO2 [C-mol/mol]
2
1. Set
dilution rate φ [/h] and aeration rate [l/h] A
2. Measure
- dry cell weight: DCW [g/l]
- cell carbon content: cCc [C-mol/g]
- offgas: O2 , CO2 [mol/l]
3. Add Knowledge - e.g. ∆G intermediates
- substrate-specific stoichiometries of TCA
- C/O ratio: CO2 produced per O2 consumed
- P/O ratio: ATP produced per O2 consumed
2. Anabolic CO2
dCO2 cd = dO2 ∗ (C/O) [mol]
dCO2 ab = dCO2 − dCO2 cd [mol]
3. Yield per ATP
YATP = YO /(P/O) [C-mol/mol]
2
⇒ only valid on
non-fermentable substrates! ⇐
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Continuous Culture: Growth , Cyanobacteria
Carbon Mass & Free Energy
Conversions
∆GP ∆Gox
Yeast
Glycolysis/TCA +ATP +NADH
Fermentation
-NADH
Resp. e-chain +ATP -NADH
+H2 O2
PPP/ALD.ACS
+NADPH
...
Maintenance -ATP -NADPH
Synthesis
-ATP -NADPH
+ photosynthesis:
CO2 & hν ⇒ (COH)n
ADP & hν ⇒ ATP
sounds interesting / boring / totally wrong
... but ... WHY?
Cyanos
Linear e-chain
Calvin Cycle
Cyclic e-chain
Photoresp.
mass
+CO2
+COHex
-O2
(+CO2 )
-COH, -CO2 ,
+ BM
+ATP +NADPH +O2
-ATP -NADPH +COH
+ATP
-ATP -NADPH -O2
+H2 O2
...
⇒ keep track of assumptions:
dimensionality checks,
self-consistency checks, ... ⇐
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−1.0
−2.0
Nucl.Lee
0.0
Continuous Culture: Dynamics , Yeast
−500
0
500
0.55
0.45
R freq.
distance from TSS
von Meyenburg 1969, Strässle et al. 1988, Satroudinov et al. 1992,
Klevecz et al. 2004 PNAS, Murray DB et al. 2007 PNAS,
Machné & Murray: unpublished aka almost done ...
- Tightly interlinked with the cell division cycle (S-phase gating)
- Oscillation of large parts of metabolome and transcriptome
- Separation of Anabolic and Catabolic Activity!
0
500
0.40
0.35
S freq.
0.45
distance from TSS
0.30
OSCILLATIONS OF CELLULAR REDOX STATE
−500
−500
0
500
distance from TSS
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Continuous Culture: Dynamics , Cyanobacteria
A (too) simple first picture emerges:
CATABOLISM
ATP
ANABOLISM
Levels of Cellular Regulation
Wijker et al. 1995 Biophys Chem: Energy,
control and DNA structure in the living cell.
∆Gox ⇔ ∆µ̃H + ⇔ ∆GP
Vijayan et al. 2009 PNAS: Oscillations in supercoiling drive circadian
gene expression in cyanobacteria.
carried by (adenosine-based) currency
metabolites: ATP, NAD(P)H, CoA, SAM, ...
Functional analysis of co-expressed clusters shows remarkable
overlap with yeast redox clusters!
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Continuous Culture: Dynamics , Yeast
A (too) simple first picture emerges:
CATABOLISM
Direct feedback between energetic state and
expression of broad cellular functionality!
◮
∆Gox : redox potential (e-chain)
e.g. ATP → nucleosome remodelling
◮
∆GP : phosphorylation potential
e.g. NAD+ → Sirtuin histone deacetylation
◮
ATP
ANABOLISM
Levels of Cellular Regulation
Wijker et al. 1995 Biophys Chem: Energy,
control and DNA structure in the living cell.
∆Gox ⇔ ∆µ̃H + ⇔ ∆GP
carried by (adenosine-based) currency
metabolites: ATP, NAD(P)H, CoA, SAM, ...
+
∆µ̃H : electrochemical potential
e.g. proton gradient → DNA membrane attachment
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Continuous Culture: Dynamics , Cyanobacteria
e-PHOTOSYNTHESIS work groups
- A QUANTITATIVE Framework
- SBML-based (many tools available)
- EXTENSIBLE
TODO & WISH LIST
1. Reactor basics
gas ⇔ liquid ⇔ cell phases
2. Decide on organism, set-up culture
and measure overall mass flow
3. What can we learn & calculate from
e-chain fluorescence?
◮ Energy Dissipation?
∆Gcurrency =
∆hνabsorbed −∆hνfluor +∆Q
4. APPLY, ask specific questions
◮ KaiC ⇔ DNA ⇔ ∆Gcurrency
◮ Photosynthetic Yields
Optimization (yield vs. rate)
Photoinhibition/Photoprotection
◮ CO2 ⇔ HCO − + H +
3
◮ N2 vs. O2
◮ Map to metabolic models
◮ Map to e-chain models
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Continuous Culture: Dynamics , Cyanobacteria
e-PHOTOSYNTHESIS work groups
- A QUANTITATIVE Framework
- SBML-based (many tools available)
- EXTENSIBLE
TODO & WISH LIST
1. Reactor basics
gas ⇔ liquid ⇔ cell phases
2. Decide on organism, set-up culture
and measure overall mass flow
3. What can we learn & calculate from
e-chain fluorescence?
◮ Energy Dissipation?
∆Gcurrency =
∆hνabsorbed −∆hνfluor +∆Q
4. APPLY, ask specific questions
◮ KaiC ⇔ DNA ⇔ ∆Gcurrency
◮ Photosynthetic Yields
Optimization (yield vs. rate)
Photoinhibition/Photoprotection
◮ CO2 ⇔ HCO − + H +
3
◮ N2 vs. O2
◮ Map to metabolic models
◮ Map to e-chain models
12 / 17
Continuous Culture: Dynamics , Cyanobacteria
e-PHOTOSYNTHESIS work groups
- A QUANTITATIVE Framework
- SBML-based (many tools available)
- EXTENSIBLE
TODO & WISH LIST
1. Reactor basics
gas ⇔ liquid ⇔ cell phases
2. Decide on organism, set-up culture
and measure overall mass flow
3. What can we learn & calculate from
e-chain fluorescence?
◮ Energy Dissipation?
∆Gcurrency =
∆hνabsorbed −∆hνfluor +∆Q
4. APPLY, ask specific questions
◮ KaiC ⇔ DNA ⇔ ∆Gcurrency
◮ Photosynthetic Yields
Optimization (yield vs. rate)
Photoinhibition/Photoprotection
◮ CO2 ⇔ HCO − + H +
3
◮ N2 vs. O2
◮ Map to metabolic models
◮ Map to e-chain models
13 / 17
Continuous Culture: Dynamics , Cyanobacteria
e-PHOTOSYNTHESIS work groups
- A QUANTITATIVE Framework
- SBML-based (many tools available)
- EXTENSIBLE
TODO & WISH LIST
1. Reactor basics
gas ⇔ liquid ⇔ cell phases
2. Decide on organism, set-up culture
and measure overall mass flow
3. What can we learn & calculate from
e-chain fluorescence?
◮ Energy Dissipation?
∆Gcurrency =
∆hνabsorbed −∆hνfluor +∆Q
4. APPLY, ask specific questions
Anabolism & Cell Division Cycle
Energetics + Cell Biology + Genetics
feedback & feedforward relations
at every level
◮ KaiC ⇔ DNA ⇔ ∆Gcurrency
◮ Photosynthetic Yields
Optimization (yield vs. rate)
Photoinhibition/Photoprotection
◮ CO2 ⇔ HCO − + H +
3
◮ N2 vs. O2
◮ Map to metabolic models
◮ Map to e-chain models
14 / 17
Continuous Culture: Dynamics , Cyanobacteria
e-PHOTOSYNTHESIS work groups
- A QUANTITATIVE Framework
- SBML-based (many tools available)
- EXTENSIBLE
TODO & WISH LIST
1. Reactor basics
gas ⇔ liquid ⇔ cell phases
2. Decide on organism, set-up culture
and measure overall mass flow
3. What can we learn & calculate from
e-chain fluorescence?
◮ Energy Dissipation?
∆Gcurrency =
∆hνabsorbed −∆hνfluor +∆Q
4. APPLY, ask specific questions
Catabolism & Photosynthesis
◮ KaiC ⇔ DNA ⇔ ∆Gcurrency
◮ Photosynthetic Yields
Optimization (yield vs. rate)
Photoinhibition/Photoprotection
◮ CO2 ⇔ HCO − + H +
3
◮ N2 vs. O2
◮ Map to metabolic models
◮ Map to e-chain models
15 / 17
Continuous Culture: Dynamics , Cyanobacteria
e-PHOTOSYNTHESIS work groups
- A QUANTITATIVE Framework
- SBML-based (many tools available)
- EXTENSIBLE
TODO & WISH LIST
1. Reactor basics
gas ⇔ liquid ⇔ cell phases
2. Decide on organism, set-up culture
and measure overall mass flow
3. What can we learn & calculate from
e-chain fluorescence?
◮ Energy Dissipation?
∆Gcurrency =
∆hνabsorbed −∆hνfluor +∆Q
4. APPLY, ask specific questions
◮ KaiC ⇔ DNA ⇔ ∆Gcurrency
◮ Photosynthetic Yields
Optimization (yield vs. rate)
Photoinhibition/Photoprotection
◮ CO2 ⇔ HCO − + H +
3
◮ N2 vs. O2
◮ Map to metabolic models
◮ Map to e-chain models
16 / 17
Acknowledgements
Institutions:
ITC/TBI, University of Vienna
Christoph Flamm
RICAM Systems Biology Group
Austrian Academy of Sciences
Stefan Müller
James Lu
Clemens Zarzer
Philipp Kügler
IAB Tsuruoka, Keio University
Douglas B. Murray
Cornelia Amariai
Kalesh Sasidharan
PSI - Photon System
Instruments
Ladislav Nedbal
Jan Červený
Martin Trtílek
Funding:
http://xkcd.com/793/
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