microbial and biocatalytic production of advanced ... · microbial and biocatalytic production of...

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Microbial and Biocatalytic Productionof Advanced Functional Polymers

Costas Kiparissides Department of Chemical Engineering, Aristotle University of

Thessaloniki, and Chemical Process Engineering Research Institute, Centre for Research and Technology Hellas

Thessaloniki, Greece

Biorefinica: International Symposium Biobased Products and Biorefineries,

Osnabruck, Germany, January 27-28, 2009

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Bioproduction Objectives

• Development of an industrial R&D platform in sustainable productionof functional biopolymers , chemical building blocks and biosurfactants.

• Use of renewable agricultural sources (e.g., corn, wheat, sugar beets) and wastes as raw materials and biological processes (fermentation, biocatalysis).

• Development of novel biocatalysts (enzymes) for higher product efficiency, improved stability, reduction of the number of conversion steps and replacement of difficult syntheses by simpler processes.

• Application of advanced modeling, on-line monitoring and controlmethodologies to bioprocesses (Digital Bioprobuction).

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Industries & SMEs - 11• KitoZyme SA (KitoZyme) – BELGIUM

• Procter & Gamble (P&G) – BELGIUM

• Tate and Lyle – FINLAND

• Artes Biotechnology GmbH (ARTES) – GERMANY

• FMC Biopolymer AS/Nova Matrix (FMC Biopolymer) – NORWAY

• Companhia Petroquímica do Barreiro S.A. (CPB) – PORTUGAL

• BIOMEDAL S.L. (BIOMEDAL) – SPAIN

• BIOPOLIS S.L. (BIOPOLIS) – SPAIN

• IMEnz Bioengineering BV (IMEnz) – THE NETHERLANDS

• Ciba Specialty Chemicals PLC (CIBA) – UK

• The Centre for Process Innovation (CPI) – UK

List of Partners

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Research Institutions - 6• Centre for Research and Technology Hellas / Chemical Process

Engineering Research Institute (CERTH/CPERI) – GREECE

• DWI an der RWTH Aachen (DWI/RWTH) – GERMANY

• Instituto di Ricerca Protos (PROTOS) – ITALY

• Consejo Superior De Investigaciones Científicas -Centro De Investigaciones Biológicas (CSIC-CIB) – SPAIN

• Instituto de Ciencia e Tecnologia de Polimeros (ICTPOL) – PORTUGAL

• Agrotechnology and Food Innovations (A&F) – THE NETHERLANDS

List of Partners (cont’d)

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Universities - 8• Institute of Chemical Technology Prague (ICT Prague) – CZECH REPUBLIC

• Technical University of Denmark (DTU) – DENMARK

• Université Louis Pasteur (ULP) – FRANCE

• University of Stuttgart (UST) – GERMANY

• Universidad del Pais Vasco (UPV/EHU) – SPAIN

• Royal Institute of Technology (Kungliga Tekniska Högskolan) (KTH) –SWEDEN

• University of Newcastle, Newcastle upon Tyne (UNEW) – UK

• University of Liege, (ULg) – BELGIUM

List of Partners (cont’d)

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European Dimension of Partnership

CERTH/CPERI

BiomedalBiomedal

IMEnzBioengineering

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From Microorgnisms to Functional Biomaterials

• Epimerases• Alginate C-5 epimerases• Proteases• Lipases & esterases• C. antarctica lipase B• PHA depolymerases, hydrolases • C-LYTAG-tagged PHA

depolymerases• Immobilised-encapsulated C-

LYTAG-tagged PHA depolymerases

• Chitinases, chitin deacetylases• Glycerol-dehydratases• Alcohol dehydrogenases,

carboxydrate oxidases and laccases

WP 2

• PLA• PHAs

Particles coated with BioF-protein fusionsAmorphous & semi-crystalline PHAPHA with unsaturated monomers and with monomers with carboxylic groupsPHB, P(3HB-co-3HV)Polyhydroxypropionate

• AlginatesAlginate biopolymers with tailored functionalityAlginate based wound care formats

• Chitin-glucan-chitosan biopolymers• Polyuronic acids• Polypeptides & proteins• Polycaprolactones• Antimicrobial, adhesive, repellent

FUNCTIONAL BIOPOLYMERSFUNCTIONAL BIOPOLYMERS

• Hansenula yeast strains (Staphylococcus, Arxula, Sordaria)

• Hansenula Polymorpha • E-coli• Ralstonia eutropha• Pseudomonas fluorescens mutants-

GK13• Pseudomonas & Rhodococcus species• Pseudomonas putida KT2442• Bacterial plasmid vectors• Bacillus, Lactococcus, Lactobacillus• Streptomyces exfoliatus &

hygroscopius• Streptomyces lavendulae • Actinoplanes utahensis• Candida antarctica

ENZYMESENZYMES--BIOCATALYSTSBIOCATALYSTS

STARTING MATERIALSSTARTING MATERIALS•Fungal biomass•Fructose, surcose,

lactose•Glucose/methanol•Hexoses and

pentoses•Glucerol, corn step,

molasses, oils•Recycled paper

sludge

MICROORGANISMSMICROORGANISMS--NEW STRAINSNEW STRAINS

WP 1

WP 3,5

BUILDING BLOCKSBUILDING BLOCKS• Alginate substrates• Hydroxy acid-lactic acid

(succinic acid, butanediol, pentaerythritol)

• (R)-3-hydroxyalckanoic acids• Carbohydrate-based building

blocks: homo- and hetero-monomers for polyester and polyamide synthesis (dehydrohexitols)

WP 4

BIOSURFACTANTSBIOSURFACTANTS

• Sugar Fatty Acid Esters (SFAEs) (peptide surfactants)

• Functional cross-linked polysaccharides

• Epimerases• Alginate C-5 epimerases• Proteases• Lipases & esterases• C. antarctica lipase B• PHA depolymerases, hydrolases • C-LYTAG-tagged PHA

depolymerases• Immobilised-encapsulated C-

LYTAG-tagged PHA depolymerases

• Chitinases, chitin deacetylases• Glycerol-dehydratases• Alcohol dehydrogenases,

carboxydrate oxidases and laccases

WP 2WP 2

• PLA• PHAs




FUNCTIONAL BIOPOLYMERSFUNCTIONAL BIOPOLYMERS

• PLA• PHAs




• PLA• PHAs




FUNCTIONAL BIOPOLYMERSFUNCTIONAL BIOPOLYMERSFUNCTIONAL BIOPOLYMERSFUNCTIONAL BIOPOLYMERS

• Hansenula yeast strains (Staphylococcus, Arxula, Sordaria)

• Hansenula Polymorpha • E-coli• Ralstonia eutropha• Pseudomonas fluorescens mutants-

GK13• Pseudomonas & Rhodococcus species• Pseudomonas putida KT2442• Bacterial plasmid vectors• Bacillus, Lactococcus, Lactobacillus• Streptomyces exfoliatus &

hygroscopius• Streptomyces lavendulae • Actinoplanes utahensis• Candida antarctica

ENZYMESENZYMES--BIOCATALYSTSBIOCATALYSTSENZYMESENZYMES--BIOCATALYSTSBIOCATALYSTS

STARTING MATERIALSSTARTING MATERIALSSTARTING MATERIALSSTARTING MATERIALS•Fungal biomass•Fructose, surcose,

lactose•Glucose/methanol•Hexoses and

pentoses•Glucerol, corn step,

molasses, oils•Recycled paper

sludge

MICROORGANISMSMICROORGANISMS--NEW STRAINSNEW STRAINSMICROORGANISMSMICROORGANISMS--NEW STRAINSNEW STRAINS

WP 1

WP 3,5

BUILDING BLOCKSBUILDING BLOCKSBUILDING BLOCKSBUILDING BLOCKS• Alginate substrates• Hydroxy acid-lactic acid

(succinic acid, butanediol, pentaerythritol)

• (R)-3-hydroxyalckanoic acids• Carbohydrate-based building

blocks: homo- and hetero-monomers for polyester and polyamide synthesis (dehydrohexitols)

WP 4

BIOSURFACTANTSBIOSURFACTANTSBIOSURFACTANTSBIOSURFACTANTS

• Sugar Fatty Acid Esters (SFAEs) (peptide surfactants)

• Functional cross-linked polysaccharides

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Microorganisms-Biocatalysts

ObjectivesSelection of high yield microorganisms and enzymesMutation of bacteria strains for improved productivity of new compounds and/or enzyme generation with improved propertiesImmobilization of enzymes and microorganisms for increased operational stability, catalytic activity and efficient product separation/purificationAlternative Media of high compatibility with substrates and product for maximum enzymic reaction routesProduction of Biocatalysts

Microorganisms & Enzyme libraries

Selection

Modification

Purification

TestingTechnologies

Recombinant bacteria, Enzymes, Vectors, Gene expression

techniques

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Production, purification and characterization of prototype P(3HO) depolymerase from P. fluorescens GK13Production

-1

-0,5

0

0,5

0 30 60 90Time (h)

Log

(A60

0)

1

2

34 5

Cel

lgro

wth

(Log

A60

0 nm

)

Culture time (h)

Growth assessment

Biostat A Fermentor

P(3HO) depolymerase activity assay

SDS-PAGE analysis

25

5037

15

75

1 2 3 4 5kDa

1 2 3 4 5•Step 1: Hydrophobic interaction chromatographyThe enzyme was adsorbed on Accurel MP1000 andeluted by 80% (v/v) isopropanol•Step 2: Size-exclusion chromatographySephacryl S-200 (30 x 1.5 cm) equilibrated in 50 mMglycine-NaOH (pH 9.5) 0.15 M KCl in an ÄKTA equipment

Purification

1. MW Markers2. Coomassie Blue stain3. Silver stain

25

5037

75

150kDa

15

25

5037

75

150

15 1 2 3

2 mg of pure enzyme was obtained from 1 liter of

fermentation broth

Production of Enzymes

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Extracellular and Intracellular Production of Lipase from Thermus Thermophilus

Production of Enzymes

0

0.5

1

1.5

2

2.5

3

3.5

4

0 20 40 60 80 100

Time (h)

O.D

. 600

nm

0.8

1

1.2

1.4

1.6

1.8

2

Bio

mas

s (g

/l cu

lture

)

O.D. 600 nmBiomass

0

50100

150200

250

300350

400450

500

0 20 40 60 80 100Time (h)

Intra

cellu

lar A

ctiv

ity U

/lt

0

2

4

6

8

10

12

14

16

Extra

cellu

lar A

ctiv

ity U

/lt c

ultu

re

IntracellularExtracellular

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Molecular Modelling

Force Field Description (Potential Energy Function)

Thermodynamic Properties & Parameters

Enzyme Activity

Enzyme Selectivity

Free-Energy Profiles

Objectives• Determination of information concerning

structural and dynamic properties of biomolecules.

• Prediction of enzyme’s selectivity and substrate specificity.

• Assessment of theoretical tools as replacement of costly and time consuming experiments.

MD Software Tools•ABINIT (Density functional

theory)•AMBER (Molecular Mechanics)•CASTEP (ab-initio)•Car-Parrinello MD (Density

functional theory)•CHARMM (Molecular

Mechanics)

Enzyme Activity/Selectivity

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Enzyme Immobilization Strategies

Improving catalyst efficiency, stability and recovery by immobilization.

Enzyme

S

P

S

P

SP

S P

S

P

S

PMonolithic reactor

Affinity binding tomulti-well plate

Entrapment within polymer, scaffold engineering

Encapsulation in micro/nano particles

Encapsulation/ immobilization in magnetic particle

S

P

N S

Covalent attachment on activated supports

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H2O

EnzymeSP

EnzymeS

PH2O

Organic

Organic

EnzymeS

P

Enzymes in Non-conventional Media

H2O

EnzymeS

ºCDeamidationPeptide hydrolysisCysteindecomposition

● Solvent property screening tools.

● Atomistic models to predict enzyme and substrate stabilityin new solvent environment (composition, pH, ionic strength, temperature, etc.).

● Other solvent aspects (mass transfer limitations, surface tension, toxicity, flammability, waste disposal, cost, etc.).

Medium engineering

Improving catalyst efficiency and stability by modifying its molecular environment.

Organic, reversed micelles, nanoemulsions.

S

PEnzyme

Enzyme instability/poor performance in aqueous media.

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Production & Separation Systems

ObjectivesCost effective in-vivo production, separation and purification of biopolymers.

In-vitro or in-vivo production of intermediates from renewable sources.

Emphasis on process intensification, scaling-up, optimization of the production procedure and product end-use properties

Specifications of Bioproducts

Microorganisms & Biocatalysts

Process Development

Product Characterization

SeparationProcess scale-up

Strategies for optimal and economically efficient production

of bioproducts with desired properties

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Bioproduction IP

Optimization of fermentation conditions for production of intermediates or end products.

Validation of nutrient sources.

Improved recombinant strains for PHA production and other products

Microbial Polymer Production

Optimization of PHA downstream polymer separation

• Bioreactor configuration• Feeding regimes• Process integration

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PHA granule

Polymerases PhasinsDepolymerases

PHA

Regulators

Phospholipidmonolayer

0.5 μ

Pseudomonas Putida Producing PHA Granules

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End-use Properties `̀̀

Nutrients-Substrates

NutrientsSubstrates

Raw Materials

Bioreactor

Preculture

Cell Population

Single Cell

PHB Polymer

Applications

Bacteria Stock

Production Process-Flowchart

Extraction Techniques

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Production of chiral hydroxyalkanoic acids from PHA

OH

O

CH2CH C

(CH2)5

OH

PHA

metabolism

PHA

PhaZ

In vitro

In vivo

Building Blocks

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Recycled Paper Sludge conversion process

RPS(raw material)

BioproductEthanol

orLactic Acid

SSF(Enzymes + Microorganism)

Fermentation on SHF(Microorganism)

Saccharification(Enzymes)

Hydrolysis and downstream fermentation

Enzymatic hydrolysis of Cellulose + XylanFermentation of C5 (xylose) and C6 (glucose)

sugars

SHF, Separate Hydrolysis and Fermentation

SSF, Simultaneous Saccharification and (co-)Fermentation

Production of Lactic Acid

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Advanced Functional Biomaterials

ObjectivesAdvanced functional biopolymers with specific properties for selected applications

Production of biosurfactants-SFAEs

Raw Materials

Synthesis Routes

Product Characterization

SeparationCommercial application screening

Advanced applications

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ObjectivesSFAE that can be used as emulsifiers & surfactants

Tailored properties via variation of hydrophilic moieties

(carbohydrates, polysaccharides, ..) and hydrophobic chains

Acceptable colour/odour profiles for use in consumer

products

Sugar Fatty Acid Esters

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Objectives Development of processes to produce novel lactic acid based copolymers with improved properties utilising biobased raw materials generated in the projectTesting and characterisation of the produced materialsModeling/simulation of PLA formation

Novel functional copolymers containing lactic acid

Improved properties compared to standard PLAComparable properties with traditional plastics for e.g. packaging applicationsMaterials with new properties for novel applications

Lactic Acid Based Copolymers

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The main goals in the alginate part of the project are:• Make alginate based products for wound care applications and evaluate

the release of bioactive alginates and response to cellular biomarkers relevant to wound healing

• Production of alginate substrates by fermentation with available alginate over-producing Pseudomonas fluorescens strains.

• Find new mannuronan C-5 epimerases with tailored functionality by high throughput screening of an epimerase library generated by gene shuffling and error prone PCR

• Generation of yeast and bacterial strains that efficiently produces natural or engineered mannuronan C-5 epimerases in amounts sufficient to enable industrial epimerase production

• Develop an efficient and scalable fermentation and purification process for production of epimerases. Test novel reactor technology and “model assisted”optimization of the epimerase production in high cell density fermentations

• Produce test quantities of epimerases and use these for in vitroepimerization of alginate substrates to yield alginates possessing bioactivity

Alginate Based ProductsAlginate Based Products

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ObjectivesIdentify new functionalities to be added to fungal biopolymers

Select chemical, enzymatic or blend modifications routes that follow the “non-polluting” process: industrial viability, vegetal based ingredients, avoid organic solvents, single step process.

Three functionalities were selected according to marketneeds:Water-soluble chitosanHydrophobic chitosanProcessable chitosan

Fungal Biopolymers

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Microbial Production Microbial Production of PHAsof PHAs

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• Microbial Production of PHAsDevelopment of high productivity processes for 3HB homo-polymers and co-polymers with tailored molecular/mechanical properties from wild and modified strains using as carbon sources renewable and waste materialsDevelopment and assessment of strategies for product separation/purification

• Digital BioprocessesDevelopment of integrated metabolic/polymerization modelsAlgorithms for on-line adaptive metabolic flux analysis for biological systems with dynamic metabolic networksDevelopment of segregated population models for microbial cultures combined with multi-objective optimisation algorithmsScaling-up of selected bioprocesses

Production of Biopolymers

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•Pure substrates– Glycerol– Lactose– Sucrose– Octanoic acid

•Wastes/Surplus– Glycerol from

Biodiesel– Fermented

molasses– Cheese Whey

Raw Materials

•mcl-PHAs–P(3HHx)–Other

•scl- PHAs–PHB–P(3HB-co-3HV)–P(3HB-co-4HB)

Products

•Genetically modified– E.coli– P. putida KTfadB

•Wild Strains-P. putida KT2442-C. necator DSM545-H. Meditarranei-A. latus

•Mixed Cultures

Microorganisms

Microrganisms/Raw Materials/Products

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Polyhydroxyalkanoates (PHAs)

• Polyhydroxyalkanoates (PHAs) are completely biodegradable polyesters of hydroxyalkanoatesthat are synthesized by many bacteria. The molecular weight of these polymers is in the range of 200,000 – 3,000,000 Da and they are accumulated in the cells in the form of discrete granules as a carbon and energy storagematerial.

• Polyhydroxybutyrate (PHB) was the first PHA to be discovered and is also the most widely studied and best characterized. It has mechanical properties very similar to conventional plastics, like propylene.

O

R O

100-30000n

O

O

n

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FERMENTATIONRECOVERY

PURIFICATION

PRODUCT CHARACTERIZATION

PHA PRODUCTION

CULTURE MEDIUMCARBON SOURCEPs. putida KT2442

• Operation mode: continuous, fed-batch

• Culture medium• Limiting nutrient/nutrients: • C limitation/C/N limitation• Ambient variables: • Oxygen concentration, temperature• Fermentation time

• Disruption method: mechanicallysis, solvent extraction

• Solvent extraction: type of solvent, length, temperature

• Precipation method:Liquid/liquid, temperature

• Composition• Chain length distribution• Mechanical properties• Thermal properties

YieldProductivity Yield

Productivity

CostMonitoring

Research Objectives

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Tailor-made PHAs by fermentation technology:The variability of bacterial PHAs produced by fermentation is exThe variability of bacterial PHAs produced by fermentation is extraordinary traordinary large (150 different monomers). large (150 different monomers).

PHA production processes:

• Single, continuous or fed-batch mode or in two-stage fed-batch mode with usual productivities ranging between 0.5 and 5 g PHA/L•h depending on strain and specifications of the productive procedure.

• Oxygen transfer rate becomes limiting at high cell densities and special reactor configurations are required.

4.9498.7111.7PHBA. latus

4.6141194PHBRecombinant E. coli

PHB

mcl-PHA

Product

3.14232281C. necator

1.9072141 P. putidaKT2442

Overall productivityg/L·h

PHA concentrationg/L

Cell concentrationg/L

Strain

Tailor-made PHAs

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P(3HB-co-3HV) copolymers – Microstructure Analysis

Batch experiments with alternated pulses of acetate and propionate and mixtures of acetate and propionate were performed.

• A copolymer P(3HB-co-3HV) was obtained and the 3HV fraction ranged from 34% to 78%, depending on the type and frequency of the substrate supplied.

• Monomers of 3HB produced with acetate pulses while production of 3HV was almost constant, the opposite was observed with propionate pulses.

• SEC analysis showed chromatograms with unimodal behaviour- copolymer;• The molecular weights were in the range 0.4-1.6×106;• One peak of Tg and Tm for the P(HB/HV) analysed ⇒ true copolymers obtained; • Tm between 88.5ºC and 93.8ºC and Tg between -14.3ºC and -5.4ºC which are in

accordance with the range of the HV proportion.

PHAsPHAs--Mixed culturesMixed cultures

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Bioproduction IP6 8 10 12 14 16 18 20

1.0x105

1.0x106

2

3

4

5

Mol

ecul

ar W

eigh

t (g/

mol

)

C/N ratio (g/g)

Mw

Mn

PDI

Pol

ydis

pers

ity In

dex

6 8 10 12 14 16 18 200.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

20

25

30

35

40

45

50

55

PHB

Conc

entra

tion

(g/l)

C/N ratio (g/g)

PHB Concentration (g/l) PHB Content (% g/g)

% P

HB

Cont

ent (

g/g

DCW

)

Same initial sucrose concentration (20 g/l) and different ammonium sulphate initial loadings (from 1 to 3 g/l).

Cultivation up to the stationary phase.

Molecular Weights

Molecular WeightDistributions

PHB Production

PHB-Medium CompositionStudy of the influence of the initial C/N ratio on the PHB production by Alcaligenes Latus

Batch Experiments

3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.50.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

Wf/[

dlog

MW

]

Log[MW]

C/N = 20 C/N = 13.3 C/N = 10 C/N = 8 C/N = 6.6

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Molecular PropertiesMw = 1,073,000 DaMn = 373,000 DaPD = 2.87Thermal PropertiesDegree of Crystallinity = 66%Tm = 176 oC

0 2 4 6 8 100.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75

2.00

O.D

. @ 6

00 n

m

Time (h)

Optical Density Dry Cell Weight

DCW

(g/l)

0 2 4 6 8 10

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

0

5

10

15

20

25

30

35

40

45

50

PHB

Conc

entra

tion

(g/l)

Time (h)

PHB Concentration (g/l) PHB Content (% g/g)

% P

HB C

onte

nt (g

/g D

CW)

0 2 4 6 8 10

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

6.5

7.0

7.5

8.0

8.5

9.0

9.5

10.0

10.5

11.0

11.5

12.0

12.5

Amm

oniu

m C

once

ntra

tion

(g/l)

Time (h)

Phosphorous Ammonium Ph

osph

orou

s C

once

ntra

tion

(g/l)

Growth Curve

Nutrients Consumption

PHB Production

PHB-Kinetic StudiesMicrobial PHB production by Alcaligenes Latus in a 2 lt. Flask

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Bioproduction IP

0 5 10 15 20 25 30 35 40 450

10

20

30

40

50

60

70

80 PHB Content PHB Concentration Residual Biomass Concentration

Cultivation Time (h)

PHB

Con

tent

% (g

/g D

CW

)

0

1

2

3

4

5

6

7

8

9

10

PHB

Con

cent

ratio

n (g

/l) &

Res

idua

l Bio

mas

s C

once

ntra

tion

(g/l)

0 5 10 15 20 25 30 35 40 450

1

2

3

4

5

6

7

8

9

10

11

12

Dry Cell Weight Phosphates Conc. (NH4)2SO4 Conc.

Cultivation Time (h)

Dry

Cel

l Wei

ght (

g/l)

&Ph

osph

ates

Con

cent

ratio

n (g

/l)

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75

2.00

(NH

4) 2SO

4 Con

cent

ratio

n (g

/l)

0 5 10 15 20 25 30 35 40 450

4

8

12

16

20

24

28

32

36

40

44

Optical Density Sucrose Concentration

Cultivation Time [h]

Opt

ical

Den

sity

@ 6

00 n

m

0

2

4

6

8

10

12

14

16

18

20

Sucr

ose

Con

cent

ratio

n (g

/l)

Molecular PropertiesMw = 436,300 DaMn = 199,100 DaPD = 2.19Thermal PropertiesDegree of Crystallinity = 63.24%Tm = 175.71 oC

Nutrients Consumption

PHB Production 80% wt. of DCW

PHB Kinetic Studies - Fed-BatchMicrobial PHB production by A. Latus in a 2 lt. Flask Fed-Batch

Substrate feeding

Substrate feeding

Substrate feeding

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Bioproduction IP2,210,0000.7748.0537.01

745,0000.5129.7015.00

595,8000.5428.3015.40

2,576,0000.7920.2016.10

860,0000.5037.5818.88

1,213,0000.6136.6722.37

1,576,1000.6638.1025.30

365,300

177,000

1,710,000

Molecular Weight of Recovered Polymer (g/mol)

0.45

0.41

0.63

Efficiency of the Recovery Method

32.8814.73

31.4613.03

11.687.35

PHB Content Determined by GC-MS/FT-IR Analysis (%)

Content of Precipitated PHB (%)

• Fermentation of A. latus in flasks and bioreactors

• Recovery Method: Cell disruption with sonication-CHCl3-based PHB extraction

• MW is the weight average molecular weight and [EF] the extraction efficiency ratio 0.40 0.45 0.50 0.55 0.60 0.65 0.70 0.75 0.80 0.85

1x105

2x105

4x105

6x105

8x1051x106

2x106

4x106

MW = 5.970x106*[EF] - 2.305x106

R2 = 0.9584

Experimental Data Linear Fit

Mol

ecul

ar W

eigh

t (g/

mol

)

Extraction Efficiency

Study of the efficiency of the product recovery method depending on polymer Mw

PHB Processing

PRODUCTIONbio

Bioproduction IP

(a)(b)

(a)

3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.50.0

0.2

0.4

0.6

0.8

1.0

Wf/[

dlog

MW

]

Log[MW]

(a)(b)

(c)

(a) Sonication:40% amplitude 30 minMw = 1.8·106

(b) Sonication:50% amplitude 30 minMw = 1.2·106

(d) Reflux:65 oC 20 hrMw = 2.0·106

(e) Reflux:65 oC 40 hrMw = 1.0·106

(c) Sonication:50% amplitude 40 minMw = 0.5·106

(a)(b)

(c)

(d)

(a)(b)

(c)

(d)

(e)

Effect of the product recovery method on the polymer MWD

PHB-Downstream Processing

19

PRODUCTIONbio

Bioproduction IP

Digital BioprocessesDigital Bioprocesses

Model Developments Hardware Sensors

Software Sensors

1800,0 1700 1600 1500 1400 1300 1200 1100 1000,0Wavenumber, cm-1

A

z-v

z-v

OutputsNew Inputs

Optimization & Control

Model Developments Hardware Sensors

Software Sensors

1800,0 1700 1600 1500 1400 1300 1200 1100 1000,0Wavenumber, cm-1

A

1800,0 1700 1600 1500 1400 1300 1200 1100 1000,0Wavenumber, cm-1

A

z-v

z-v

OutputsNew Inputs

Optimization & Control

PRODUCTIONbio

Bioproduction IP

Multi-Scale Modeling Framework

MetabolicModels

• Unstructured• Structured• MFA

• Moment Methods• Distribution Methods

Reactor Models

PopulationModels

Polymerization Models

• Population Ensemble• Cell Ensemble• PBEs

• Ideal Mixing• Multizonal• CFD/Multizonal• Full CFD

Time Scale

Length Scale

PolymerizationModelling


Metabolic ModellingMetabolic Modelling

Population Modeling

Population Modeling

ReactorModelingReactor

Modeling

Time Scale

Length Scale




Population Modeling

Population Modeling


Modeling

Initiation

(Monomer Unit) (Synthase Dimer)

+ +(Coenzyme A)

Propagation

+

(Active [n]mer)

(Active [n+1]mer)

Coenzyme A

Chain Transferto Water H2O

Depolymerization

(Depolymerase)

(Inactive [n]mer)

(Inactive Monomer)

+

+

(Active Monomer)

Synthase Dimer

(Inactive [n+1]mer)

H2O

Depolymerase

Initiation


+ +(Coenzyme A)

Propagation

+

(Active [n]mer)

(Active [n+1]mer)

Coenzyme A


Depolymerization

(Depolymerase)

(Inactive [n]mer)

(Inactive Monomer)

+

+

(Active Monomer)

Synthase Dimer

(Inactive [n+1]mer)

H2O

Depolymerase

P(3HB)n

Substrate

AcCoA

Ac-AcCoA

3-HB

Biomass

3-HBCoA

KrebsCycle

KrebsCycleCO2

O2NADHATP

Nitrogen

ATP

PhaA

PhaB

PhaC

PhaZ

Entner-Doudoroff Pathway

P(3HB)nP(3HB)n

SubstrateSubstrate

AcCoAAcCoA

Ac-AcCoAAc-AcCoA

3-HB3-HB

BiomassBiomass

3-HBCoA3-HBCoA

KrebsCycle

KrebsCycleCO2CO2

O2O2NADHNADHATPATP

NitrogenNitrogen

ATPATP

PhaA

PhaB

PhaC

PhaZ


20

PRODUCTIONbio

Bioproduction IP

Reactor Models

PopulationModels

• Population Ensemble• Cell Ensemble• PBEs

• Ideal Mixing• Multizonal• CFD/Multizonal• Full CFD

•••Nutrients•••Substrates

•••Substrates•••Nutrients

•••Nutrients•••Substrates

•••Substrates•••Nutrients

MetabolicModels

• Unstructured• Structured• MFA

• Moment Methods• Distribution Methods

Polymerization Models

Time Scale

Length Scale




Population Modeling

Population Modeling


Modeling

Time Scale

Length Scale




Population Modeling

Population Modeling


Modeling

Multi-Scale Modeling Framework

PRODUCTIONbio

Bioproduction IP

Cell-Level: Metabolic Flux AnalysisComplete metabolic pathway of biomass growth and PHB accumulation in A. latus

“Bacteria Fermentation Culture for Synthesis of PHA Biopolymers as

Intracellular Product”Sucrose

glucose fructose

G6P

F6P

GAP

PEP

PYR

AcCoA

ICT

KG

OAA

SUC

AcAcCoA HBCoA PHB

Biomass

CO2,int CO2,ext

FADH 2 ATP

NADH 3 ATP

ATP energyNADH

ATP

ATP

ATP

ATP

NADHCO2

CO2

NADH

NADHCO2

NADHATP

CO2

NADHFADH

NADH

AcCoA

Jsuc1 Jsuc2

Jglu

Jg6p

Jgap

Jpep

Jpyr

Jacc Jaca Jhbc

Jfru

Joaa

Jict

Jkg

Jsuc

Jbio

Jco2

Jatp

Jnad

Jfad

Jppc

Jglx

Jf6p

Metabolism of sucrose towards the accumulation of PHB through Glucolysis as energy carbon storage and biomass growth through Krebs Cycle

The PHB production rate and the biomass growth rate are functions of sucrose diffusion from the culture medium through the cell membrane and its assimilation rate inside the cell.

Monomer unit

Metabolic Flux Analysis reveals that the PHB production rate is most sensitive to the manipulation of the F6P flux.

21

PRODUCTIONbio

Bioproduction IP

Intracellular PHB Accumulation in A. Latus

“Bacteria Fermentation Culture for Synthesis of PHA Biopolymers as

Intracellular Product”

`̀̀

Polymer GranulesPolymer GranulesPolymer Chains Below Critical LengthPolymer Chains Below Critical Length

PHB accumulation in Alcaligenes latus’ cytoplasm:Two-Phase Emulsion-Like Polymerization MechanismPHB accumulation in Alcaligenes latus’ cytoplasm:

Two-Phase Emulsion-Like Polymerization Mechanism

CytoplasmCytoplasm

Microbial CultureMicrobial Culture

Poly(3-hydroxybutyrate) PHB

Poly(3-hydroxybutyrate) PHB

PRODUCTIONbio

Bioproduction IP

Metabolic pathway of synthesis and degradation of P(3HB).

P(3HB)n

Substrate

AcCoA

Ac-AcCoA

3-HB

Biomass

3-HBCoA

KrebsCycle

KrebsCycleCO2

O2NADHATP

Nitrogen

ATP

PhaA

PhaB

PhaC

PhaZ


Model Integration at the Cell Level

The activated monomer 3-HBCoA constitutes the link between the two models.

22

PRODUCTIONbio

Bioproduction IP

Initiation


+ +(Coenzyme A)

Propagation

+

(Active [n]mer)

(Active [n+1]mer)

Coenzyme A


Depolymerization

(Depolymerase)

(Inactive [n]mer)

(Inactive Monomer)

+

+

(Active Monomer)

Synthase Dimer

(Inactive [n+1]mer)

H2O

Depolymerase

Polymerization MechanismPolymerization Model

1m ik kE SH M SCoA ESH M P ES SH CoA− + − ⎯⎯→ − ⎯⎯→ − + −

1pm kk

n n nP ES M SCoA P ES M P ES SH CoA+− + − ⎯⎯→ − − ⎯⎯→ − + −

2tk

n nP ES H O D E SH− + ⎯⎯→ + −

Initiation

Depolymerization

Propagation

Termination with H2O

1 1dk

n nD E OH D D E OH−+ − ⎯⎯→ + + −

Assumptions• Polymerase (PhaC), depolymerase (PhaZ) and

water concentrations are constant throughout the course of polymerization.

• Cell death occurring after a certain period of time (i.e. 30h) causes polymer degradation to gradually decrease.

• Kinetic rate constants are independent of chain length.

PRODUCTIONbio

Bioproduction IP

Formulation of Differential Equations

Polymerization Model

Metabolic Model

Live polymer chains of length n

[ ] [ ] [ ][ ] [ ][ ]ni m n p n-1 t n 2

d P * = k E-SH-M δ(n-1) - k P M + k P (n-1) - k P H Odt

⎡ ⎤⎢ ⎥⎣ ⎦

H

[ ][ ]*n *

m n p n

d P= k P M - k P

dt

⎡ ⎤⎣ ⎦ ⎡ ⎤⎣ ⎦

[ ] [ ][ ] [ ] [ ]n * * *t n 2 d n d n d n+1

n=2

d D = k P H O - k D (n-1) + k D δ(n-1) + k D

dt∞

∑H

[ ] ( ) [ ] [ ] [ ]*m m n

n=1

d M= - k M - k M P

dt MJ t∞

∑

[ ] [ ] [ ]*m i

d E-SH-M= k M - k E-SH-M

dt

Intermediate polymer chains of length n

Dead polymer chains of length n

Monomer

Monomer-Synthase Complex

( ) ( )MJ t g , , , , tk Y C J=

23

PRODUCTIONbio

Bioproduction IP

Model Tuning (Fructose 5 g/l)

• The polymerization model was solved with two different numerical methods. • Parameters are estimated using the General Regression Software (GREG).• The model is able to predict the evolution of Mn and polymer yield.• There is a very good agreement between numerical methods.

0.00.51.01.52.02.53.03.54.04.55.0

0 10 20 30 40 50

Time (h)

PHB

(gr/

lt)

ExperimentalPHB - MOMPHB - Fixed Pivot

0.0E+001.0E+052.0E+053.0E+054.0E+055.0E+056.0E+057.0E+058.0E+059.0E+051.0E+06

0 10 20 30 40 50

Time (h)

Mn

ExperimentalM n - M OMM n - Fixed Pivot

PRODUCTIONbio

Bioproduction IP

Model Validation (Fructose 10 g/l)

• The model is able to predict the evolution of Mn and polymer yield.• There is a very good agreement between numerical methods.• In batch cultures a maximum Mn and polymer yield are achieved and

subsequently there is a decrease to a steady-state value.

0.0E+005.0E-01

1.0E+001.5E+002.0E+002.5E+003.0E+003.5E+004.0E+004.5E+005.0E+00

0 10 20 30 40 50

Time (h)

PHB

(gr/

lt)

ExperimentalPHB - MOMPHB - Fixed Pivot

0.0E+001.0E+052.0E+053.0E+054.0E+055.0E+056.0E+057.0E+058.0E+059.0E+051.0E+06

0 10 20 30 40 50

Time (h)

Mn

ExperimentalMn - MOMMn - Fixed Pivot

24

PRODUCTIONbio

Bioproduction IP

1.0E-20

2.0E-08

4.0E-08

6.0E-08

8.0E-08

1.0E-07

1.2E-07

1.4E-07

1.6E-07

1.8E-07

2.0E-07

1.E+02 1.E+03 1.E+04 1.E+05

Chain Length

Con

cent

ratio

n (m

ol lt-1

)

t=2ht=10ht=20ht=30ht=50h

0.0E+00

2.0E-08

4.0E-08

6.0E-08

8.0E-08

1.0E-07

1.2E-07

1.4E-07

1.6E-07

1.8E-07

2.0E-07

1.E+02 1.E+03 1.E+04 1.E+05

Chain Length

Con

cent

ratio

n (m

ol lt-1

)

t=2ht=10h

t=20ht=50h

Fructose 5 g/l Batch Fructose 5 g/l Fed-batch

• Chain length distributions reflect the behavior of Mn and polymer yield.

Investigation of MWD Evolution

PRODUCTIONbio

Bioproduction IP

The evolution of the cell mass distribution under the combined action of cell growth and division is described by the following equation:

( ) ( ) ( ) ( ) ( ) ( ) ( ) ( )m

n m,tG m,S n m,t 2 Γ m ,S P m,m n m ,t dm Γ m,S n m,t

t m

∞∂ ∂ ′ ′ ′ ′+ = −⎡ ⎤⎣ ⎦∂ ∂ ∫

The PBE is coupled to the mass balance for the substrate concentration.

( ) ( )0

dS 1 G m,s n m, t dmdt Y

∞

= ∫

The Population Balance Equation (PBE)

( )n m t, : number of cells with mass between [ ], +m m dm per unit biovolume at time t, 1 3− −⋅g m .

( )G m,S : growth of cells with mass m, g/s.

( ),Γ m S : division rate (intensity) of cells with mass m, 1−s .

( )′P m m, : partitioning function, i.e., probability that a mother cell with mass ′m will give birth to a daughter cell with mass m, 3−m .

Y: yield coefficient(g substrate/g biomass)

25

PRODUCTIONbio

Bioproduction IP

Case I: Linear Growth - Equal partitioning

1020

30

0

0.5

1

0

1

2

3

4

5

Time (h)

Cell Mass (m/m0 )

n(m

,t)

Case II: Linear Growth – Unequal Partitioning

1020

30

0

0.5

1

0

1

2

3

4

5

Time (h)

Cell Mass (m/m 0 )

n(m

,t)

Constant Substrate Concentration

For linear cell growth rate and equal partitioning the cell mass distribution exhibits a periodic behavior with a frequency equal to the cell doubling time Td=5h. For linear cell growth rate and unequal partitioning a state of balanced growth is gradually achieved.

PRODUCTIONbio

Bioproduction IP

Reactor level

Modelling Challenges

Ideal Mixing

Full CFD Model

Multizonal Model

CFD/Multizonal Model

Distributed SegregatedCell population level

Single-cell level

• Define the level of the model complexity.

• Detailed mathematical descriptions are of great value for the design of bioprocesses, usually lead to computationally intractable models.

UnstructuredStructured

Reactor level

26

PRODUCTIONbio

Bioproduction IP

Conclusions

• The microbial PHA production process is a multi-parametric system

• The physiological state of the culture is determinant for both the quality and the quantity of the produced biopolymers

• Exhaustive investigation and mapping of the influence of all the operating parameters on both the physiological state of the culture and the productivity and quality of the biopolymers is necessary

• A model-based optimization of these production processes and simulation of the biopolymer molecular properties will enhance their competitiveness and will assist their economic viability.

• Operating profiles, product recovery techniques, and reactor configuration were explored through an experimental- and a model-based approach

• The conceptual framework for the development of integrated metabolic, polymerization and population models at a reactor level accounting for heat and mass transfer phenomena was presented

• An integrated metabolic/polymerization model was developed based on experimental data from fermentation of Alcaligenes species.

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