3rd International Conference on Bioprocess and Biosystems Engineering September 14, 2015, Baltimore

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



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


)4(2 pmfEFGts




]2][[

]][[ln

27,0 QHNAD

QNADH

F

RTEE pH

mVEmVE QHQpH

NADHNADpH 90;320 2/

7,0/7,0


)4(2 pmfEFGts




]2][[

]][[ln

27,0 QHNAD

QNADH

F

RTEE pH

mVEmVE QHQpH

NADHNADpH 90;320 2/

7,0/7,0


)4(2 pmfEFGts




]2][[

]][[ln

27,0 QHNAD

QNADH

F

RTEE pH

mVEmVE QHQpH

NADHNADpH 90;320 2/

7,0/7,0


)4(2 pmfEFGts




]2][[

]][[ln

27,0 QHNAD

QNADH

F

RTEE pH

mVEmVE QHQpH

NADHNADpH 90;320 2/

7,0/7,0


)4(2 pmfEFGts




]2][[

]][[ln

27,0 QHNAD

QNADH

F

RTEE pH

mVEmVE QHQpH

NADHNADpH 90;320 2/

7,0/7,0


)4(2 pmfEFGts




]2][[

]][[ln

27,0 QHNAD

QNADH

F

RTEE pH

mVEmVE QHQpH

NADHNADpH 90;320 2/

7,0/7,0


)4(2 pmfEFGts



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


www.mpi-magdeburg.mpg.de/projects/cna/cna.htmlKlamt et al., 2007, BMC Systems Biology 1:2

Stoichiometric Modeling and Metabolic Network Analysis

http://www.mpi-magdeburg.mpg.de/projects/cna/cna.html

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


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!


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


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



Ubiquinone (Coenzyme Q10); A metabolic signal in gene regulation ?


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


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

Documents

3rd International Conference on Bioprocess and Biosystems Engineering September 14, 2015, Baltimore