development of microorganisms with improved bioremediation properties (Dua
et al. 2002). A psychrotolerant nonpathogenic Pseudomonas fluorescens strain that
was genetically engineered for degradation of 2,4-dinitrotoluene was studied by
transferring the Burkholderia sp. strain DNT pJS1 mega plasmid containing the dnt
genes (Monti et al. 2005). Thus, a stable 2,4-dinitrotoluene-degrading phenotype
was first achieved by integrating the dnt genes into the P. fluorescens chromosome.
Haro and Lorenzo (2001) combined two catabolic segments from the toluene
(TOL) and toluene dioxygenase (TOD) pathways of Pseudomonas putida to create
an upper hybrid pathway for bioconversion of 2-chlorotoluene into
2-chlorobenzoate. This pathway was integrated into the pathway of two
2-chlorobenzoate-degrading Pseudomonas strains, expecting to provide complete
degradation of 2-chlorotoluene. The two strains were able to co-metabolize
2-chlorotoluene to 2-chlorobenzoate with citrate as co-substrate but failed to grow
on 2-chlorotoluene alone. Analysis of the cultures with gas chromatography–mass
spectroscopy (GC-MS) showed that citrate-grown cells accumulated
2-chlorobenzoate and other intermediates in the upper pathway during exposure of
2-chlorotoluene. However, no reason was found for the lack of degradation of
2-chlorobenzoate. This study clearly emphasizes that an unbiased and nontarget
analysis of the performance and physiology of the biological model system via
metabolomics is necessary.
Metabolomics and other genome-wide methodologies as transcriptomics, proteomics, interactomics, and fluxomics have became important tools for describing how
a phenotype is generated from its genotype and the environmental conditions. These
technologies became important for both metabolic engineering and system biology
because the focus is on integrated networks of metabolic pathways and not on
individual isolated reactions (Friboulet and Thomas 2005). The strategy of inverse
metabolic engineering is through comparisons between mutated strains and reference strains to gain insight into the metabolism (Bro and Nielsen 2004). In bioremediation, this approach is also relevant (e.g., comparison of reference strains with
recombinant strains modified with a new degradation pathway). Also important is
the exploration of the response of the microorganisms to pollutant exposure. A
metabolome analysis can supply information regarding which pathways are activated under expression of the new heterologous pathway and under pollutantexposure conditions. The strength of metabolome analysis is that it points out the
pathways that need to be targeted by metabolic engineering (Trethewey 2001).
Because the other OMICS-related approaches provide invaluable complementary
information, the future of metabolic engineering is to integrate the different sets of
data to develop optimal strains for use in both bioprocessing and bioremediation
(Park et al. 2005). Lee et al. (2006) used a quantitative proteomics approach to
provide important insights into the metabolic and physiological changes that occur
upon cis-dichloroethylene degradation by engineered Escherichia coli strains.
Because the number of identified central proteins in the degradation pathways was
less than the number of genes, a transcriptome analysis may complement the
proteomics approach as would the metabolomics and fluxomics analyses on the
physiological characterization.
462
S. K. Shekhar et al.
et al. 2002). A psychrotolerant nonpathogenic Pseudomonas fluorescens strain that
was genetically engineered for degradation of 2,4-dinitrotoluene was studied by
transferring the Burkholderia sp. strain DNT pJS1 mega plasmid containing the dnt
genes (Monti et al. 2005). Thus, a stable 2,4-dinitrotoluene-degrading phenotype
was first achieved by integrating the dnt genes into the P. fluorescens chromosome.
Haro and Lorenzo (2001) combined two catabolic segments from the toluene
(TOL) and toluene dioxygenase (TOD) pathways of Pseudomonas putida to create
an upper hybrid pathway for bioconversion of 2-chlorotoluene into
2-chlorobenzoate. This pathway was integrated into the pathway of two
2-chlorobenzoate-degrading Pseudomonas strains, expecting to provide complete
degradation of 2-chlorotoluene. The two strains were able to co-metabolize
2-chlorotoluene to 2-chlorobenzoate with citrate as co-substrate but failed to grow
on 2-chlorotoluene alone. Analysis of the cultures with gas chromatography–mass
spectroscopy (GC-MS) showed that citrate-grown cells accumulated
2-chlorobenzoate and other intermediates in the upper pathway during exposure of
2-chlorotoluene. However, no reason was found for the lack of degradation of
2-chlorobenzoate. This study clearly emphasizes that an unbiased and nontarget
analysis of the performance and physiology of the biological model system via
metabolomics is necessary.
Metabolomics and other genome-wide methodologies as transcriptomics, proteomics, interactomics, and fluxomics have became important tools for describing how
a phenotype is generated from its genotype and the environmental conditions. These
technologies became important for both metabolic engineering and system biology
because the focus is on integrated networks of metabolic pathways and not on
individual isolated reactions (Friboulet and Thomas 2005). The strategy of inverse
metabolic engineering is through comparisons between mutated strains and reference strains to gain insight into the metabolism (Bro and Nielsen 2004). In bioremediation, this approach is also relevant (e.g., comparison of reference strains with
recombinant strains modified with a new degradation pathway). Also important is
the exploration of the response of the microorganisms to pollutant exposure. A
metabolome analysis can supply information regarding which pathways are activated under expression of the new heterologous pathway and under pollutantexposure conditions. The strength of metabolome analysis is that it points out the
pathways that need to be targeted by metabolic engineering (Trethewey 2001).
Because the other OMICS-related approaches provide invaluable complementary
information, the future of metabolic engineering is to integrate the different sets of
data to develop optimal strains for use in both bioprocessing and bioremediation
(Park et al. 2005). Lee et al. (2006) used a quantitative proteomics approach to
provide important insights into the metabolic and physiological changes that occur
upon cis-dichloroethylene degradation by engineered Escherichia coli strains.
Because the number of identified central proteins in the degradation pathways was
less than the number of genes, a transcriptome analysis may complement the
proteomics approach as would the metabolomics and fluxomics analyses on the
physiological characterization.
462
S. K. Shekhar et al.