PosterPDF Available

Systems-level flux analysis of Clostridium phytofermentans for metabolically engineered optimal production of biofuels

Authors:

Abstract

Catabolite repression is a significant impediment to industrial scale generation of biofuels using microbial metabolism of plant biomass. In order to overcome this limitation, we aim to generate a bacterial co-culture composed of a number of engineered organisms that have the capability to consume only select sugars. The base organism for our effort is Clostridium phytofermentans (Cphy), a gene5cally tractable model bacterium that can directly convert a broad range of biomass sources into ethanol and hydrogen gas. One of the most attractive characteristics of this organism is that Cphy can produce biofuels without the need for expensive thermochemical pretreatment and enzyme additions. Here we report the latest results of our engineering effort. Better understanding of Cphy can provide bioengineering solutions to simultaneously utilize all forms of pentose and hexose sugars present in the plant waste. Using our genome-scale flux balance analysis (FBA) model of metabolism in Cphy, constrained by our experimental data, we search for solution for optimal degradation of plant material, and production of biofuels in Cphy.
Systems-level*flux*analysis*of*Clostridium+phytofermentans*for*
metabolically*engineered*op9mal*produc9on*of*biofuels*
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System-level*Analysis*of*Cphy*metabolism*
Abstract*
References:*
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>3)# (f4()*1(';%E# C%;%,# <(# +(%)/7# U>)# +>E35>'# U>)# >451%E# C(?)%C%5>'# >U# 4E%';# 1%;()*%E,# %'C#
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Experimental*data*
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##
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2(/>'C%)&#1(;%J>E*;(+,#(;7%'>E#%'C#%/(;%;(,#%)(#4)>C3/(C#%'C#/%'#*'7*J*;#?)><;7"+
Our*bioengineering*gene*knockout*tools:*
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Procedure*for*obtaining*curated*FBA*model6-7*
1.DraI*reconstruc9on**
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3.*Conversion*of*reconstruc9on*into*computable*format*
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;>#*C('5U&#%44)>4)*%;(#J*>('?*'(()*'?#;%)?(;+"#
Single Sugar Growth Curves
020 40 60 80
0.0
0.5
1.0
1.5
2.0
2.5 Galactose
Glucose
Xylose
Cellobiose
Time (Hours)
OD600
Sugar Combination Growth Curves
010 20 30 40
0.0
0.5
1.0
1.5
2.0 Glucose/Galactose
Xylose/Cellobiose
Xylose/Glucose
Xylose/Galactose
Time (Hours)
OD600
Glucose + Xylose H Column
010 20 30 40
0
5
10
15
20
25 mM Glucose
mM Xylose
mM Acetate
mM Ethanol
Time (hours)
mM Metabolite
Cellobiose + Xylose H Column
0 10 20 30 40
0
5
10
15
20
25 mM Cellobiose
mM Xylose
mM Acetate
mM Ethanol
Time (hours)
mM Metabolite
Galactose + Xylose
010 20 30 40
0
5
10
15
20 mM Galactose
mM Xylose
mM Acetate
mM Ethanol
Time (hours)
mM Metabolite
Glucose + Galactose H Column
0 10 20 30 40
0
5
10
15
20
25 mM Glucose
mM Galactose
mM Acetate
mM Ethanol
Time (hours)
mM Metabolite
K>1J*'%5>'#+3?%)#/>'+3145>'#%'C#1(;%J>E*;(#C%;%W#
Cellobiose H Column
0 10 20 30 40
0
5
10
15
20
25 mM Cellobiose
mM Acetate
mM Ethanol
Time (hours)
mM Metabolite
Xylose H Column
0 20 40 60 80 100
0
5
10
15
20
25 mM Xylose
mM Acetate
mM Ethanol
Time (hours)
mM Metabolite
Glucose H Column
010 20 30 40
0
5
10
15
20
25 mM Glucose
mM Acetate
mM Ethanol
Time (hours)
mM Metabolite
2*'?E(#+3?%)#/>'+3145>'#%'C#1(;%J>E*;(#C%;%W#
Visualiza9on*of*gene*knockout*targets*=*****and*fermenta9on*pathway*
Number*of*Genes+aTY#
Number*reac9ons*-9[Y#
Number*compounds*-FF9#
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mM*Metabolite* mM*Metabolite*
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Flux*Balance*Analysis*(FBA)*
Theore9cal*Robustness*Analysis*
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Network reconstructions are a common denominator in systems biology. Bottom-up metabolic network reconstructions have been developed over the last 10 years. These reconstructions represent structured knowledge bases that abstract pertinent information on the biochemical transformations taking place within specific target organisms. The conversion of a reconstruction into a mathematical format facilitates a myriad of computational biological studies, including evaluation of network content, hypothesis testing and generation, analysis of phenotypic characteristics and metabolic engineering. To date, genome-scale metabolic reconstructions for more than 30 organisms have been published and this number is expected to increase rapidly. However, these reconstructions differ in quality and coverage that may minimize their predictive potential and use as knowledge bases. Here we present a comprehensive protocol describing each step necessary to build a high-quality genome-scale metabolic reconstruction, as well as the common trials and tribulations. Therefore, this protocol provides a helpful manual for all stages of the reconstruction process.
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Systems biology is the study of interactions between assorted components of biological systems with the aim of acquiring new insights into how organisms function and respond to different stimuli. Although more and more efforts are being directed toward examining systems biology in complex multi-cellular organisms, the bulk of system-level analyses conducted to date have focused on the biology of microbes. In, Microbial Systems Biology: Methods and Protocols expert researchers in the field describe the utility and attributes of different tools (both experimental and computational) that are used for studying microbial systems. Written in the highly successful Methods in Molecular Biology™ series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Microbial Systems Biology: Methods and Protocols introduces and aids scientists in using the various tools that are currently available for analysis, modification and utilization of microbial organisms.
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  • T A Warnick
Warnick TA. 2002. Interna5onal journal of systema5c and evolu5onary microbiology 52:1155-1160.
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  • A C Tolonen
Tolonen AC. 2013. Biological conversion of biomass for fuels and chemicals:114-139.
  • A C Tolonen
Tolonen AC. 2009. Molecular Microbiology 74:1300-1313.
  • T R Zuroff
Zuroff TR. 2014. Microbiology 160:1134-1143.