Post on 29-Jan-2016
A Fermentation Strategy for Industrial Application of Purple Bacteria, based
on Computational ModelingHartmut Grammel,
Hochschule Biberach, Biberach University of Applied SciencesMax Planck Institute for Dynamics of Complex Technical Systems, Magdeburg
3rd International Conference on Bioprocess and Biosystems Engineering September 14, 2015, Baltimore
Fermentation Technology, Bioprocess and cell culture
• Phototrophic vs. Dark Fermentation• Aerobic – Anaerobic – Microaerobic• online-Spectroscopy Monitoring and Control• Computational Modeling (Stoichiometric,
Kinetic, Process Models)• Continuous Cultivation (Cytostat)
Algae and Cyanobacteria
Photosynthetic Metabolism as a Source for Chemical Products
Photo taken from http://biology.ucsd.edu/
Purple Bacteria (Rhodospirillaceae)- facultative photosynthetic, anoxygenic
Biofuels- Biodiesel- Biohydrogen- Bioethanol- Lipidsetc
- Single cell protein- Vitamins- Coenzyme Q10- Biopesticides- Biopolyesters- Biofertilizersetc.
Photosynthetic Products of Purple Non-Sulfur Bacteria
Species
Rc. gelatinosusRb. sphaeroidesRb. capsulatusR. tenueR. rubrumRps. palustrisR. molichianumRps. viridis...
Feedstock
Wheat branWheyCassava starchSoybean wasteBiogas plant slurryWastewaterWaste sulfite liquor from wood...
Product/ApplicationSCP, animal feedCholesterol-lowering food supplementVitamin B2Vitamin EVitamin B12CarotenoidsPorphyrinesCoenzyme Q10EnzymesWaste treatmentBiopolymersBiopesticides (5-ALA)Biohydrogenrecombinant membrane proteins...
http://www.bio-pro.de/de/region/freiburg/magazin/04647/index.html
SCIENCE VOL 329 13 AUGUST 2010
Phototrophic Cultivation Systems...
Greenovation Biotech GmbH, Flatpane-Airlift Reactor, IGB Stuttgart
+ O2: aerobic respration
- O2: anaerobic respiration, fermentation
+ O2
Photosynthetic gene expression repressed
Photosynthesis,
Formation of Intracytoplasmic membranes
- O2
pfla'ack pta cbiD137
411 481 L H I J K cupBcdpA C D E F C X Y Z WBAL M
Expression of photosynthetic genes
Induction of Photosynthetic Membranes by Environmental Factors, Oxygen and Light
Expression of Photosynthetic Membranes in Purple Bacteria
• Intracytoplasmic photosynthetic membranes in Rhodospirillum rubrum
•Cyclic photophosphorylation in photosynthetic membranes
High Level Expression of Photosynthetic Membranes as Model System for Redox Signaling and Control
Semiaerobic cultivation of R. rubrum in the dark with different carbon substrates
SuccinateSuccinate
Fructose Succinate Fructose/ SuccinateFructose Succinate Fructose/ Succinate
pfla' ack pta cbiD137
411 481 L H I J K cupBcdpA C D E F C Xpfla' ack pta cbiD137
411 481 L H I J K cupBcdpA C D E F C XcdpA C D E F C X Y Z WBAL M
O2
Photosynthetic gene expression
?
LIGHT
CARBON SOURCE
Redox signalling
?
?
?
Ghosh et al. 1994. Appl. Env. Microbiol. 60(5):1698
Grammel, H. and R. Ghosh . 2008, J. Bacteriol. 190 (14):4912-4921
Fructose Succinate Fructose/SuccinateFructose Succinate Fructose/Succinate
Semiaerobic cultivation of R. rubrum in the dark with different carbon substrates
High Level Expression of Photosynthetic Membranes as Model System for Redox Signaling and Control
Kinetic modeling of electron transfer
chains and redox signaling
Kinetic modeling of electron transfer
chains and redox signaling
Drivingforce: redoxpotential difference E
]2][[
]][[ln
27,0 QHNAD
QNADH
F
RTEE pH
mVEmVE QHQpH
NADHNADpH 90;320 2/
7,0/7,0
Thermodynamic span: ts
)4(2 pmfEFGts
Flux rNADH-DH through NADH-DH:
rNADH-DH= kNADH-DH[NADH-DH] ts
Drivingforce: redoxpotential difference EDrivingforce: redoxpotential difference E
]2][[
]][[ln
27,0 QHNAD
QNADH
F
RTEE pH
mVEmVE QHQpH
NADHNADpH 90;320 2/
7,0/7,0
Thermodynamic span: ts
)4(2 pmfEFGts
Flux rNADH-DH through NADH-DH:
rNADH-DH= kNADH-DH[NADH-DH] ts
Drivingforce: redoxpotential difference E
]2][[
]][[ln
27,0 QHNAD
QNADH
F
RTEE pH
mVEmVE QHQpH
NADHNADpH 90;320 2/
7,0/7,0
Thermodynamic span: ts
)4(2 pmfEFGts
Flux rNADH-DH through NADH-DH:
rNADH-DH= kNADH-DH[NADH-DH] ts
Drivingforce: redoxpotential difference EDrivingforce: redoxpotential difference E
]2][[
]][[ln
27,0 QHNAD
QNADH
F
RTEE pH
mVEmVE QHQpH
NADHNADpH 90;320 2/
7,0/7,0
Thermodynamic span: ts
)4(2 pmfEFGts
Flux rNADH-DH through NADH-DH:
rNADH-DH= kNADH-DH[NADH-DH] ts
Drivingforce: redoxpotential difference E
]2][[
]][[ln
27,0 QHNAD
QNADH
F
RTEE pH
mVEmVE QHQpH
NADHNADpH 90;320 2/
7,0/7,0
Thermodynamic span: ts
)4(2 pmfEFGts
Flux rNADH-DH through NADH-DH:
rNADH-DH= kNADH-DH[NADH-DH] ts
Drivingforce: redoxpotential difference EDrivingforce: redoxpotential difference E
]2][[
]][[ln
27,0 QHNAD
QNADH
F
RTEE pH
mVEmVE QHQpH
NADHNADpH 90;320 2/
7,0/7,0
Thermodynamic span: ts
)4(2 pmfEFGts
Flux rNADH-DH through NADH-DH:
rNADH-DH= kNADH-DH[NADH-DH] ts
Drivingforce: redoxpotential difference E
]2][[
]][[ln
27,0 QHNAD
QNADH
F
RTEE pH
mVEmVE QHQpH
NADHNADpH 90;320 2/
7,0/7,0
Thermodynamic span: ts
)4(2 pmfEFGts
Flux rNADH-DH through NADH-DH:
rNADH-DH= kNADH-DH[NADH-DH] ts
Drivingforce: redoxpotential difference EDrivingforce: redoxpotential difference E
]2][[
]][[ln
27,0 QHNAD
QNADH
F
RTEE pH
mVEmVE QHQpH
NADHNADpH 90;320 2/
7,0/7,0
Thermodynamic span: ts
)4(2 pmfEFGts
Flux rNADH-DH through NADH-DH:
rNADH-DH= kNADH-DH[NADH-DH] ts
Metabolic network analysis Metabolic network analysis
Process modeling,
model-based control
Process modeling,
model-based control
Cybernetics models Cybernetics models In vivo online spectroscopy
In vivo online spectroscopy
Enzyme activities Enzyme activities
Metabolomics13C isotope metabolic flux
analysis
Metabolomics13C isotope metabolic flux
analysis
Gene expression profiling Gene expression profiling
Theoretical AnalysisComputational Modeling
Experimental AnalysisBioreactor Cultivations
Development of Rhodospirillum rubrum for Applications in Biotechnology
- A Systems Biology Approach
(Hädicke, O., H. Grammel, and S. Klamt. 2011. Metabolic network modeling of redox balancing and biohydrogen production in purple nonsulfur bacteria. BMC Syst. Biol. 5:150. )
Stoichiometric Modeling and Metabolic Network Analysis
www.mpi-magdeburg.mpg.de/projects/cna/cna.html
Software Tool: CellNetAnalyzer
Nrdt
dc0
- stoichiometric model of central metabolic pathways in purple non-sulfur bacteria.
- 119 metabolites- 142 enzymatic reactions- MFA and FBA and FVA analysis with measured extracellular rates
N : stoichiometric matrix (rows: metabolites; columns: reactions with stoichmiometric coefficients)r: vector of reaction rates, (mmol/g h)
Linear metabolite balancing equation:
• MATLAB toolbox with graphical user interface
• comprehensive toolbox with algorithms for biological network analysis: - metabolic networks - signal transduction and regulatory networks
• Application for optimization of the metabolic network (target reactions for gene overexpression of knock-outs)
BioMicroWorld2011
Software Tool: CellNetAnalyzer
(Hädicke, O., H. Grammel, and S. Klamt. 2011. Metabolic network modeling of redox balancing and biohydrogen production in purple nonsulfur bacteria. BMC Syst. Biol. 5:150. )
www.mpi-magdeburg.mpg.de/projects/cna/cna.htmlKlamt et al., 2007, BMC Systems Biology 1:2
Stoichiometric Modeling and Metabolic Network Analysis
Fructose Succinate Fructose/SuccinateFructose Succinate Fructose/Succinate…independent of light at microaerobic conditions and at high cell densities !
Porphyrins
Biopolymers
Biohydrogen Energy carrier
Photodynamic Tumor Therapy
Production of:
Poly-b-hydroxyalkanoates
Carotenoids
Food industry Vitamins, Coenzymes B12, Q10
Membrane proteins Vaccines …
Food supplement
Biotechnological Potential of Purple Non-Sulfur Bacteria
• Photodynamic tumor therapy using bacteriochlorophyll derivatives
Development of Rhodospirillum rubrum for Applications in Biotechnology
Background image from http://www.photofrin.com
Bacteriochlorophyll a
Laser light
1O2
- Bacteriopheophorbide
m/z 611.2 [M+H+]+,
lmax (nm) 358, 524, 748
Biotechnological Applications of Photosynthetic Bacteria
Biohydrogen
(Hädicke, O., H. Grammel, and S. Klamt. 2011. Metabolic network modeling of redox balancing and biohydrogen production in purple nonsulfur bacteria. BMC Syst. Biol. 5:150. )
0
500
1000
1500
2000
2500
3000
0,0
0,5
1,0
1,5
2,0
2,5
3,0
3,5
4,0
0 10 20 30 40 50 60 70 80
H2[p
pm]
Cel
lgro
wth
[A66
0]
t [h]
H2cell growth
Development of Rhodospirillum rubrum , for High-Level
Expression of Industrially Relevant Carotenoids
Center Systems Biology, University of Stuttgart, MaCS, Magdeburg Centre For Systems Biology,
crtW-mediated
crtZ
Microaerobic Microbial Phenomena
Microaerobic conditions were shown to be important not only for…
• Photosynthetic Products in R. rubrum without light (Rudolf et al., Zeiger and Grammel, 2010; Grammel and Ghosh, Grammel et al.,)
but also for….• bacterial pathogenicity
(Park et al., 2011; Schueller and Phillips, 2010)
• industrial waste water treatment (Zheng and Cui, 2012)
• industrial production of cellulosic ethanol(Agbogbo and Coward-Kelly, 2008)
• …and many others
• Microaerobic expression of photosynthetic membranes is induced below 0.5 % DO
• Respiratory growth in E. coli was shown to occur at ≤ 3 nM (Stolper et al., 2010. PNAS, 107:18755) )
•…well below the measurement range of conventional oxygen probes!
Fructose Succinate Fructose/SuccinateFructose Succinate Fructose/Succinate
How much Oxygen is Microaerobic?
Microaerobic Process Control
How to achieve microaerobic conditions in a bioreactor?
• pH-stat photosynthetic products in R. rubrum• Respiratory quotient 2,3 butanediol in Enterobacter
aerogenes (Zeng et al., 1994)• Culture redox potential (CRP) as controlled variable
– many industrial and environmental processes
Grammel, H., Gilles, E.D., and Ghosh, R. (2003) Appl Env Microbiol 69, 6577-6586
photosynthetic membrane
cell growth
Expression of Photosynthetic Membranes in Bioreactor Cultivations of Rhodospirillum rubrum under Microaerobic Dark Conditions
photosynthetic membrane
fructose
H+
succinateOH-
Fructose consumption pH decrease
air supply
pO2 increase
Succinateconsumption
+
--
in vivo Whole Cell UV/Vis/NIR Absorption Spectroscopy of R. rubrum
Fructose Succinate Fructose/SuccinateFructose Succinate Fructose/Succinate
300 400 500 600 700 800 900
AU
nm
LH1, RC
carotenoids,cytochrome c
LH1
LH1, RC RC
Photosynthetic membrane expression as cellular redox indicator
Bioreactor
Fibre optics
Fluorescence spectrometer
CCD spectrometers
Online Spectroscopical Process Monitoring – Technical Equipment
online Biomass and PM
spectroscopicdata
Model-based Control of Microaerobic Steady-States
• model-based. CRP-dependent 2DOF controller
Dilution rate
Model trajectory
outputtrajectory
Unstructured process modelrb(CRP,xs, xf) (specific growth rate)
• model-based. CRP-dependent 2DOF controller
CRP – 50 mV CRP – 100 mV
model-based 2 DOF control and online spectroscopy allows switch from – 50 mV to -100 mV without disturance or oscillations.
New dilution rate adjusted to reach the desired steady state
Model-based Control of Microaerobic Steady-States
Fructose Succinate Fructose/SuccinateFructose Succinate Fructose/Succinate…independent of light; at high cell densities ?
Porphyrins
Biopolymers
Biohydrogen Energy carrier
Photodynamic Tumor Therapy
Production of:
Poly-b-hydroxyalkanoates
Carotenoids
Food industry Vitamins, Coenzymes B12, Q10
Membrane proteins Vaccines …
Food supplement
Biotechnological Potential of Purple Non-Sulfur Bacteria
High Cell Density Cultivation of Rhodospirillum rubrum
A660 nm
Fructose
Ammonium
Succinate, Phosphate
~ 60 g/l cell dry weight(Zeiger and Grammel, 2010. Biotechnol. Bioeng.105(4):729-39.)
Model-based high cell density cultivation:
)tμset(t
S,Feed
FFS
X/S
setSS e
C
))X(tV(tm
Y
μρ(t)M 0
Partners• Biberach University of Applied Science• Max Planck Institute for Dynamics of
Complex Technical Systems, Magdeburg• University Stuttgart• Center for Systems Biology, Stuttgart• FZ Jülich• NMI Reutlingen• Philipps-University Marburg, Loewe
Center for Synthetic Microbiology
Thank you for the attention!
Acknowledgements
)00001.0
)(00001.0
)(1
)((
4
4
4
4
21
212max,
PO
PO
NH
NH
FruSucSFM C
C
C
C
kkkk
++++= mmmm )
00001.0)(
00001.0)(
1)((
4
4
4
4
21
212max,
PO
PO
NH
NH
FruSucSFM C
C
C
C
kkkk
++++= mmmm )
00001.0)(
00001.0)(
1)((
4
4
4
4
21
212max,
PO
PO
NH
NH
FruSucSFM C
C
C
C
kkkk
++++= mmmm
)(,
2,max,
Suci
SucSucSuc
SucSucsimSuc
K
CCK
C
++
=mm
)(,
2,max,
Suci
SucSucSuc
SucSucsimSuc
K
CCK
C
++
=mm
)(,
2,max,
Suci
SucSucSuc
SucSucsimSuc
K
CCK
C
++
=mm
)(,max,
FruFru
FruFrusimFru CK
C+
=mm)(,max,
FruFru
FruFrusimFru CK
C+
=mm)(,max,
FruFru
FruFrusimFru CK
C+
=mm
44exp4,44,,
44 )()(
NHC
NHNHFeedC
NHNHFeedPN
NHNH C
V
FCC
V
FCC
V
FCxq
dt
dC --+-´+-=44exp4,44,
,4
4 )()(NH
CNHNHFeed
CNHNHFeed
PNNH
NH CV
FCC
V
FCC
V
FCxq
dt
dC --+-´+-=44exp4,44,
,4
4 )()(NH
CNHNHFeed
CNHNHFeed
PNNH
NH CV
FCC
V
FCC
V
FCxq
dt
dC --+-´+-=
444,,
44 )(
POC
POPOFeedPN
POPO C
V
FCC
V
FCxq
dt
dC --+-=444,
,4
4 )(PO
CPOPOFeed
PNPO
PO CV
FCC
V
FCxq
dt
dC --+-=444,
,4
4 )(PO
CPOPOFeed
PNPO
PO CV
FCC
V
FCxq
dt
dC --+-=
FruPN
FruFruFeedC
FruFruFru C
V
FCC
V
FCxmCxq
dt
dC,
,)( --+--=
FruPN
FruFruFeedC
FruFruFru C
V
FCC
V
FCxmCxq
dt
dC,
,)( --+--=
FruPN
FruFruFeedC
FruFruFru C
V
FCC
V
FCxmCxq
dt
dC,
,)( --+--=
SucPN
SucSucFeedC
SucSucSuc C
V
FCC
V
FCxmCxq
dt
dC ,,
)( --+--=Suc
PNSucSucFeed
CSucSuc
Suc CV
FCC
V
FCxmCxq
dt
dC ,,
)( --+--=Suc
PNSucSucFeed
CSucSuc
Suc CV
FCC
V
FCxmCxq
dt
dC ,,
)( --+--=
CxV
FFCx
dt
dCx CPN)(
,+
-=m CxV
FFCx
dt
dCx CPN)(
,+
-=m CxV
FFCx
dt
dCx CPN)(
,+
-=m
Mass and volume balances
0 10 20 30 40 50 60 70 80 90 1000
20
40
60
80
CD
W (
g/l)
Fruc
tose
, Suc
cina
te (
mM
)
t (h)
0.0
1.0
2.0
3.0
4.0
0 10 20 30 40 50 600
5
10
15
20
25
30
35
40
45
CD
W (g/
l)
Fru
ctos
e, S
ucci
nate
(m
M)
t (h)
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
Mixed-substrate kinetics for fed-batch cultivation with succinate/fructose
Process Model for R. rubrum
Single substrates
Mixed-substrate (M2SF)
Zeiger and Grammel, 2010. Biotechnol. Bioeng.105(4):729-39.
*, calculated after d´Anjou and Daugulis corresponding to the used succinate to fructose ratio. abatch phase, succinate/fructose ratio as in M2SF medium; bfed-batch, 0.85 M succinate to 1.66 M fructose.
Parameter Description Value
µmax, Suc maximum specific growth rate, succinate 0.124 (1/h) µmax, Fru maximum specific growth rate, fructose 0.123 (1/h) µmax, M2SF maximum specific growth rate, M2SF 0.128 (1/h) YX/S,Suc biomass/succinate yield coefficient 56.32 1.06 (g/mol) YX/S,Fru biomass/fructose yield coefficient 100.54 5.54 (g/mol) YX/S,M2SF biomass/substrate yield coefficient, M2SF 68.0 (g/mol) qSuc succinate uptake rate 2.20 0.02 (mmol/g h) qFru fructose uptake rate 1.22 0.02 (mmol/g h) qSuc,M2SF succinate, mixed substrate uptake rate 1.02 (mmol/g h) qFru,M2SF fructose, mixed substrate uptake rate 0.42 (mmol/g h) qNH4 ammonium uptake rate 0.63 0.1 (mM/ g h) qPO4 phosphate uptake rate 0.0125 0.003 (mM/ g h)
µmax,sim,Suc theoretical maximum specific growth rate, succinate 0.22 (1/h) µmax,sim,Fru theoretical maximum specific growth rate, fructose 0.12 (1/h) µmax,sim,mix theoretical maximum specific growth rate, mixed-substrate 1.6 (1/h) YX/S,mix,Suc biomass/succinate yield coefficient 39a /19b (g/mol) YX/S,mix,Fru biomass/fructose yield coefficient 31a /69b (g/mol) YX/S,mix * biomass/substrate yield coefficient, mixed-substrate 68a / 87b (g/mol) mSuc maintenance coefficient, succinate 8.3 (µmol/g h) mFru maintenance coefficient, fructose 16.3 (µmol/g h) mS maintenance coefficient, mixed-substrate 25.0 (µmol/g h) KSuc Monod saturation constant, succinate 8.7 (mM) KFru Monod saturation constant, fructose 7.0 (mM) Ki, Suc Monod inhibition constant, succinate 42.0 (mM) k1 kinetic constant (Eq. [10]) 0.46 k2 kinetic constant (Eq. [10]) 1.85 k3 kinetic constant 9 k4 kinetic constant 15
)(
,
2,max,
Suci
Suc
SucSuc
Suc
SucsimSuc
K
CCK
C
++
=mm
)(,max,
FruFru
Fru
FrusimFru CK
C
+=mm
Succinate
Fructose
Fed-Batch Cultivation of R. rubrum: Basic Growth Parameters
Zeiger and Grammel, 2010. Biotechnol. Bioeng.105(4):729-39.
Fructose Succinate Fructose/ SuccinateFructose Succinate Fructose/ Succinate
pfla' ack pta cbiD137
411 481 L H I J K cupBcdpA C D E F C Xpfla' ack pta cbiD137
411 481 L H I J K cupBcdpA C D E F C XcdpA C D E F C X Y Z WBAL M
O2
Photosynthetic gene expression
?
LIGHT
CARBON SOURCE
Redox signalling
?
?
?
Ghosh et al. 1994. Appl. Env. Microbiol. 60(5):1698
Grammel, H. and R. Ghosh . 2008, J. Bacteriol. 190 (14):4912-4921
Fructose Succinate Fructose/SuccinateFructose Succinate Fructose/Succinate
Semiaerobic cultivation of R. rubrum in the dark with different carbon substrates
Ubiquinone (Coenzyme Q10); A metabolic signal in gene regulation ?
High Level Expression of Photosynthetic Membranes as Model System for Redox Signaling and Control
aerobic (respiration)
anaerobic in light(photosynthesis)
respiration + photosynthesisIssues:
-Stoichiometric model
(elementary modes, etc.)
- Kinetic model (rate laws of
electron transfer reactions based
on redox potentials
-QH2 (Ubiquinone-10) as major
regulatory signal
Modeling the Electron Transport Chain (ETC) of Rhodospirillaceae
Klamt, S., H. Grammel, R. Straube, R. Ghosh, and E.D. Gilles. 2008. Mol. Syst. Biol. 4:156.
mVEmVE QHQpH
NADHNADpH 90;320 2/
7,0/
7,0
EDriving force: redox potential difference
]2][[
]][[ln
27,0 QHNAD
QNADH
F
RTEE DHNADH
pHDHNADH
Reaction rate rNADH-DH :
rNADH-DH= kNADH-DH tsNADH-DH
Thermodynamic span: ts
tsNADH-DH = – ΔG= F(2ΔENADH-DH – 4 pmf)
Kinetic description of the electron transfer processes in the ETC based on the driving forces: redox potential differences
Kinetic Model of the Electron Transport Chain
Klamt, S., H. Grammel, R. Straube, R. Ghosh, and E.D. Gilles. 2008. Mol. Syst. Biol. 4:156.
Simulation studies: Steady-state response curves of selected model variables under different environmental conditions
Kinetic Model of the Electron Transport Chain
NAD(P)H
Protein
FMN, FAD
In vivo Spectroscopy of Cellular Redox Dynamics
NAD(P)H-fluorescence during aerobic-anaerobic switch
2D fluorescence scan of bioreactor cultivation of R. rubrum