bacterial consortia for the improvement of consolidated bioprocessing...

Bacterial Consortia for the Improvement of

Consolidated Bioprocessing Techniques

1

Outline

Consolidated Bioprocessing

Designing our system

Implementation Details

• Cellulose as substrate

• Monocultures• Co-cultures• Bacteria choice

for CBP

• Modeling• Naïve co-culture• Measurement• Circuit design

• C. Hutchinsoniias a new chassis

• Biodiesel

2

$$$

• 120 million tons of stover

• Cheap• Not a food source

…. but difficult to process

Corn Stover, Agriculture and Agri-food Canada, 2008.

Enzymes

Energy

Cellulose is lying around in abundance

3

CBP uses a single reactor for all production steps.

The CBP State of the Art relies on monoculture-based processing, which isn’t reliable

Consolidated BioProcessing will be our

vehicle

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State of the art of Consolidated

Bioprocessing

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Co-cultures are better than monocultures

Co-cultures allow for specialty, robustness, and are inspired by nature.6


Cellulose Degrading Bacteria



Cellulose Degrading Bacteria

E. coli

extractionProduct

Simple sugars


CBP with communicating Co-Culture

Cytophaga hutchinsonii:

degrades cellulose, aerobic,

sequenced genome

and transformable

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CBP with communicating Co-Culture

E. coli:

well characterized and produce a variety of products

Our product: biofuel

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0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50

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Time

Po

pula

tion

Bacteria 1

Bacteria 2

Herbert H.P. Fang, Heguang Zhu, Tong Zhang, Phototrophic hydrogen production from glucose by pure and co-cultures of Clostridium butyricum and Rhodobacter sphaeroides,

International Journal of Hydrogen Energy, Volume 31, Issue 15, December 2006, Pages 2223-2230, ISSN 0360-3199

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50

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Time

Po

pula

tion

Bacteria 1

Bacteria 2

Preliminary Modeling Suggests that Co-Culture can

be Improved with Communication

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http://library.mit.edu/F?func=find-b&sourceid=libxmit&local_base=mit01pub&find_code=WRD&request=issn:(2223-2230)+OR+eissn:(2223-2230)

http://library.mit.edu/F?func=find-b&sourceid=libxmit&local_base=mit01pub&find_code=WRD&request=issn:(0360-3199)+OR+eissn:(0360-3199)

Outline






for CBP

• Modeling• Naïve co-culture• Measurement• Circuit design


• Biodiesel

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Time

Co

nce

ntr

atio

n

Population 1

Product

Substrate Population 2

Modeling to Predict Co-Culture

Dynamics

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Time

Co

nce

ntr

atio

n

Population 1

Product

Substrate Population 2

Modeling to Tune Populations –

Forward Design

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Modeling Methods: Dynamic Flux

Balance Analysis

Start with the Flux Balance Analysis

Source: BiGG database, Orth et al. 2011

Av=0

Steady state

v

Maxμ=wTv

A

Stoichiometric Matrix

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Then consider extracellular dynamics

Flux Balance Model

Extracellular dynamic mass

balances

Uptake/secretion kinetics

Modeling Methods: Dynamic Flux Balance

Analysis


Balance AnalysisThen consider extracellular dynamics

Flux Balance Model

Max μ=wTvs.t.: Av=0lb < v < ub Extracellular Mass Balances

dX

dt= μX

𝑑𝑆,𝑃

𝑑𝑡= v

siX

Uptake/Secretion Kinetics

vs = fs(S,P)

S, P

vs

μ, vp


Balance Analysis


Flux Balance Model


dX

dt= μX

𝑑𝑆,𝑃

𝑑𝑡= v

siX


vs = fs(S,P)

S, P

vs

μ, vp

16


Flux Balance Model

Extracellular dynamic mass

balances

Uptake/secretion kinetics

Modeling Methods: Dynamic Flux Balance

Analysis


Balance AnalysisThen consider extracellular dynamics

Flux Balance Model


dX

dt= μX

𝑑𝑆,𝑃

𝑑𝑡= v

siX


vs = fs(S,P)

S, P

vs

μ, vp

We Overcame Many Significant Challenges in Implementing Our Models

Gomez, J.A., Höffner, K. and Barton, P. I.: DFBAlab: A fast and reliable MATLAB code for Dynamic Flux Balance Analysis. BMC Bioinformatics 15(1) (2014).

Valid metabolic networks

Kinetic parameters Computationally

feasible

Non-native pathways

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Outline






for CBP

• Modeling• Naïve co-culture

• Grow E. coli and C. hutchinsoniitogether

• Separate populations

• Analyze carbohydrates

• Circuit design


• Biodiesel

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Naïve Co-Culture to tell us what to improve

E. coli

Salts

Filter paper C. hutchinsonii

humboldtmfg.com

drpinna.com

lbc.msu.eduStandardsingenomics.org

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Outline






for CBP

• Modeling• Naïve co-culture

• Growing E. coli and C. hutchinsoniitogether

• Measurement

• Circuit design


• Biodiesel

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http://femsle.oxfordjournals.org/content/362/14/fnv095.full

We developed a method of distinguishing

cells by shape

C. Hutchinsonii E. Coli

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http://ucflow.blogspot.com/ Time

Voltage

Scatter height

Scatter width


cells by shape

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cells by shape

Forward scatter height

C. Hutchinsonii cells

E. Coli cells

debris

Forward scatter width

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Carbohydrate Analysis: Sulfuric Acid-

Phenol Method

+

y = 1.2971x - 0.0472R² = 0.9872

-0.2

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1.4

0.00 0.20 0.40 0.60 0.80 1.00 1.20

Ab

sorb

ance

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0 n

m

concentration (%wt/v)

round 1

round 2

round 3

average

linear regression

StandardsNaïve Co-culture Data

0 20 40 60 80 100 1203

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Time [h]

Co

nce

ntr

atio

n [g

/L]

Total Cabohyrates Data

Total Carbohyrates Fitted Data

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Modeling Predicts Naïve Co-Culture

Data

Data Model

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10

Time [h]

Co

nce

ntr

ation

[g

/L]

Biomass C. hutchinsonii

Biomass E. coli

Filter paper

Glucose

Xylose

Cellodextrins (2-7)

Xylo-oligosaccharides (2-7)

Outline






for CBP

• Modeling• Naïve co-culture• Circuit design


• Biodiesel

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Pros of Continuous Culture

• Higher productivity

• No turnover time

Cons of Continuous Culture

• Susceptible to genetic instability

• Susceptible to contamination

• Impractical in industry

Changing Focus from Continuous to Batch

Culture

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We used a toxin and antitoxin system to modulate C.

hutchinsonii population size

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Any Gene Expression!

AHL

We used the Lux quorum sensing system for inter-

bacteria communication

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C. hutchinsonii E. Coli

AHL

Simple sugars

Circuit design tethers C. Hutchinsonii growth to E. Coli

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Modeling predicts circuit failure and success

modes

Not enough starting AHL

Threshold level of E. coli too high

AHL

Simple sugars

Success: C. Hutchinsonii to E. Coli ratio improved

Success: C. Hutchinsonii to E. Coli ratio increased

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Outline






for CBP



• Biodiesel

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Engineering C. hutchinsonii Requires Plasmids

Basic

Plasmid

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Origin of Replication Part Design

• PCR amplified chromosomal origin of replication (oriC)

• BioBrick and MoClo compatible

• Part# Bba_K1705010

C. hutchinsonii Genome

Cloning Site

oriC

pSB1C3

oriC

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Testing Selection Markers

• Inserted oriC in both CmR and KanR backbones

• Cm resistance to 10 ug/mL

• Kan resistance at 30 ug/mL

Wild-Type Transformed

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C. hutchinsonii Accomplishments

• Opened new, interesting chassis• Culture and transformation methods

• Modularized origin of replication (Bba_K1705010)

• Selection with Kan and Chlor

• Future directions • Native constitutive promoter (Bba_K1705012)

• Native RBS (Bba_K1705011)

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Outline






for CBP



• Biodiesel

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SugarspdcadhB (BBa_K1705000)

Ethanol

‘tesA (BBa_K1705002) FadD (BBa_K1705003)

atfA(BBa_K1705001)

Producing biodiesel with E. coli

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-10

0

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0 5 10 15 20 25 30

Val

ue(

mA

U)

Time(min)

90% Methanol Standards

Methanol Ethyl Palmitate Standard Palmitic Acid Standard 1:1 Ethyl Palmitate:Palmitic Acid

Ethyl Palmitate

Palmitic Acid

Developed a Method to Detect Biodiesel

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Experimental Samples with 90% Methanol

Not Induced Induced

Fatty Acid Ethyl Esters(FAEEs)

We developed a method to separate a fatty acid

from its ethyl ester

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Outline






for CBP



• Biodiesel

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• Characterized co-culture

What have we achieved?

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• Designed population control system


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• Progress toward implementation


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1.2

BBa_J23100 BBa_J23102 BBa_J23107 BBa_J23106

Stre

ngt

h

Anderson Promoter Strengths

Part BioBrick #

C. hutchinsonii Origin of Replication

BBa_K1705010

C. hutchinsonii RBS BBa_K1705011

C. hutchinsonii promoter BBa_K1705012

alcohol dehydrogenase (adhB) BBa_K1705000

Acyl-CoA diacylglycerolacyltransferase (aftA)

BBa_K1705001

Leaderless thioesterase (‘tesA) BBa_K1705002

Acyl-CoA synthetase (fadD) BBa_K1705003

pLux BBa_K1705006

luxR BBa_K1705007

luxI BBa_K1705008

luxI LVA BBa_K1705009

RelE BBa_K1705004

RelB BBa_K1705005


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• Collaboration


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• Addresses issue of population instability

• Modular system

• New use of cellulosic waste

• Future challenges:

• Scalability

• Genetic instability

Broader Context

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Acknowledgements

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Questions

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Separating Populations

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E. coli Growth on Dead C. hutchinsonii

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Naïve Co-Culture data

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Naïve Co-Culture data

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