In silico feasibility of novel biodegradation pathways for 1,2,4-trichlorobenzene
BMC Systems Biology
In silico feasibility of novel biodegradation pathways for 1,2,4-trichlorobenzene
Stacey D Finley 2
Linda J Broadbelt 2
Vassily Hatzimanikatis 0 1
0 Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Federale de Lausanne (EPFL) and Swiss Institute of Bioinformatics (SIB) , CH H4 625, Station 6, CH-1015 Lausanne , Switzerland
1 Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Federale de Lausanne (EPFL) and Swiss Institute of Bioinformatics (SIB) , CH H4 625, Station 6, CH-1015 Lausanne , Switzerland
2 Department of Chemical and Biological Engineering, McCormick School of Engineering and Applied Sciences, Northwestern University , 2145 Sheridan Road, Evanston, IL 60208 , USA
Background: Bioremediation offers a promising pollution treatment method in the reduction and elimination of man-made compounds in the environment. Computational tools to predict novel biodegradation pathways for pollutants allow one to explore the capabilities of microorganisms in cleaning up the environment. However, given the wealth of novel pathways obtained using these prediction methods, it is necessary to evaluate their relative feasibility, particularly within the context of the cellular environment. Results: We have utilized a computational framework called BNICE to generate novel biodegradation routes for 1,2,4-trichlorobenzene (1,2,4-TCB) and incorporated the pathways into a metabolic model for Pseudomonas putida. We studied the cellular feasibility of the pathways by applying metabolic flux analysis (MFA) and thermodynamic constraints. We found that the novel pathways generated by BNICE enabled the cell to produce more biomass than the known pathway. Evaluation of the flux distribution profiles revealed that several properties influenced biomass production: 1) reducing power required, 2) reactions required to generate biomass precursors, 3) oxygen utilization, and 4) thermodynamic topology of the pathway. Based on pathway analysis, MFA, and thermodynamic properties, we identified several promising pathways that can be engineered into a host organism to accomplish bioremediation. Conclusions: This work was aimed at understanding how novel biodegradation pathways influence the existing metabolism of a host organism. We have identified attractive targets for metabolic engineers interested in constructing a microorganism that can be used for bioremediation. Through this work, computational tools are shown to be useful in the design and evaluation of novel xenobiotic biodegradation pathways, identifying cellularly feasible degradation routes.
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Background
The prevalence and widespread use of man-made
chemicals ("xenobiotics) has led to a focused effort to
establish new technologies to reduce or eliminate these
contaminants from the environment. Commonly used
pollution treatment methods such as incineration,
landfilling, and air stripping also have an adverse effect on
the environment [1,2]. Additionally, these methods are
costly and sometimes inefficient. Therefore, it is
important to develop alternative methods of biodegradation
that are effective, minimally hazardous, and economical.
One promising treatment method is to exploit the
ability of microorganisms to use these foreign substances
for maintenance and growth, a process known as
bioremediation [3].
Microorganisms provide a wealth of potential in
biodegradation. It has been proposed that the ability of
these organisms to reduce the concentration of
xenobiotics is closely linked to their long-term adaptation to
environments where these compounds exist [4-6].
Genetic engineering may be used to enhance the
performance of the microorganisms such that they have the
desired properties needed for biodegradation.
Genetically engineered microorganisms (GEMs) have new
metabolic pathways, more stable catabolic activity, and
expanded substrate ranges relative to existing organisms
[7]. For example, genetic engineering has been employed
to design specific pathways [8] or a microbial
consortium [9] for the biodegradation of an organophosphorus
insecticide. Whole-genome sequencing has also proved
helpful in understanding and enhancing microorganisms
for bioremediation [10].
In order to fully explore the capabilities of
microorganisms in cleaning up the environment, the use of
computational tools to predict novel biodegradation pathways for
pollutants and gain a better understanding of the fate of
these compounds in the environment would be valuable
[11]. Prediction methods such as the Pathway Prediction
System (PPS) [12], META [13], and others [14-18] rely on
databases of rules describing biotransformations that
occur in cellular and environmental processes. An
alternative method is the Biochemical Network Integrated
Computational Explorer (BNICE), a framework developed for
the discovery of novel biochemical reactions [19-21].
BNICE has been shown to be a pathway prediction
method that generates feasible biodegradation routes [22].
BNICE utilizes reaction rules derived from the Enzyme
Commission (EC) classification system, which provide a
compact way to describe biochemical reactions and can be
used to link the degradation of xenobiotic compounds to
small molecule metabolism.
Given the wealth of novel biodegradation pathways
obtained using computational prediction methods, it is
necessary to evaluate their relative feasibility.
Thermodynamic feasibility is a useful metric to evaluate potential
biodegradation pathways. In the absence of experimental
data for the Gibbs free energies of formation and
reaction, group contribution provides an estimate of the
thermodynamic properties of compounds and reactions
[23] and is an effective tool in the evaluation [24,25]
and reconstruction [26,27] of genome-scale models.
Additionally, metabolic flux analysis (MFA) provides a
means of investigating the cellular feasibility of novel
pathways; that is, how implementation of the pathway
influences the existing metabolism of an organism and
gives rise to competition for cellular resources. MFA
can be augmented with thermodynamic constraints, a
methodology called thermodynamics-based metabolic
flux analysis (TMFA) [24], in order to generate
thermodynamically feasible flux profiles and predict cellular
behavior. These tools provide a systematic evaluation of
the feasibility of novel pathways within the context of
the cellular environment.
In this work, we describe the evaluation of novel
pathways to degrade 1,2,4-trichlorobenzene (1,2,4-TCB) in
the context of the cellular metabolism of Pseudomonas
putida, a pollutant-degrading organism. 1,2,4-TCB is
one of the most widely used chlorobenzenes [28] and
has many industrial uses. Chlorobenzenes have toxic
effects in humans and animals [29,30], and 1,2,4-TCB in
particular is included on the list of Priority Chemicals,
as designated by the Environmental Protection Agency
(EPA) http://www.epa.gov/epawaste/hazard/wastemin/
priority.htm. A biodegradati (...truncated)