Cong T. Trinh:Research

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Recent advances in the sequencing technology have generated an increasingly large database of genetic codes for many different organisms (1). Such genetic information has been providing a good resource for researchers to search and predict functional genes of interested organisms through the comparative genomics approach (2-3). However, knowledge of a genetic sequence encoding a functional gene is only an initial step to understand how a cell works at the molecular level since the cellular operation such as cellular metabolism highly depends on many intricate layers of regulation and interaction from gene expression, protein synthesis, and metabolite production. Our research group seeks to fundamentally understand and engineer cellular metabolism with the ultimate goal to design, construct, and characterize cells with optimized metabolic functionalities. These engineered cells are utilized as efficient and robust whole-cell biocatalysts exhibiting only desirable properties specifically tailored for biotechnological applications related to health, bioenergy, and environment. To pursue the goal, our research group is interested in applying and developing both theoretical and experimental tools in interdisciplinary fields of systems and synthetic biology together with metabolic and biochemical engineering. Below is a list of research topics that we are currently pursuing in our research group.

Contents

1. Engineering cells with optimized metabolic functionalities

Powerful approach to design cells with optimized metabolic functionalities is to apply the metabolic pathway analysis tool to analyze cellular metabolism and elucidate interaction of cell genotype and phenotype as outlined in the recent review (4). A metabolic network describing a cellular metabolism typically contains hundreds to thousands of reactions catalyzed by functional enzymes to convert feed substrates into precursor metabolites used to synthesize cell components for growth or other metabolites secreted to extracellular environments. These functional enzymes are directly encoded by functional genes that determine cell phenotypes.

By using elementary mode analysis as the metabolic pathway analysis tool, a metabolic network can be decomposed into unique pathways, each of which contains a minimal set of enzymatic reactions supporting cell functions (5). Each of these independent pathways can represent a physiological state of cell operation. The knowledge of these pathways allows the selection of cell phenotypes of interest, which establishes a basis for designing cells with optimized metabolic functionalities. The engineered cells are particularly designed to function only according to the efficient pathways to produce the target metabolite by eliminating the inefficient pathways. In addition, the operation of these pathways is always enforced by coupling both the cell growth and production of the target metabolite. Through genetic engineering, cells exhibiting the phenotypes of interest are constructed and characterized.

From the past successful demonstration of this approach to develop Escherichia coli cells optimized for efficient biomass production (6) and ethanol synthesis from mixed sugars (7) and biodiesel waste, glycerol (8), we are interested in applying this powerful approach to design, construct, and characterize a wide spectrum of different efficient cells to produce advanced biofuels and biochemicals from lignocellulosic biomass and high-valued products such amino acid, secondary metabolites, and proteins/enzymes.

2. Engineering cells tolerant to chemical inhibitors

One of the challenging tasks to convert lignocellulosic biomass into biofuels is to develop robust solventogenic microorganisms that can tolerate chemical inhibitors present in the fermentation broth (9). These inhibitors are produced during pretreatment and fermentation. Depending on the biofuel process, the inhibitors can contain weak organic acids (e.g., succinic acid, lactic acid, acetic acid, formic acid), furan derivatives (e.g., furfural, hydroxyl methyl furfural), phenolic compounds derived from lignin, and organic solvents synthesized by microorganisms as fermentative products (e.g., ethanol and butanol) (10-11). These inhibitors cause detrimental effect on biocatalyst performance by decreasing both cell growth and solvent production. It is difficult to metabolically engineer microorganisms resistant to these chemical inhibitors because the genotype and phenotype link resulting in chemical resistance in microorganisms is very often unknown.


To approach this problem, we pursue the genomics approach by applying the gene swapping and amplification technique. This approach is designed to transfer novel phenotypes from not-well-characterized microorganisms exhibiting high resistance to chemical inhibitors to an engineered host. We are also interested in investigating mechanisms of chemical toxicity that affects cell growth and solvent production by analyzing response of cellular metabolism through systems biology approach. Discovering the mode of chemical toxicity can provide metabolic engineering strategy to improve the microorganism performance. For instance, we have recently demonstrated that the glycolytic flux of the recombinant ethanologenic strain KO11 controlled the mixed acid fermentation (12). The ethanol production was suboptimal because the high glycolytic flux could not be completely channeled to the ethanol pathway. A simple metabolic engineering strategy of increasing the ethanol flux by increasing the copy number of the ethanol-producing genes resulted in significant improvement of the ethanol titer, productivity, and yield.

3. Optimizing expression of multiple heterologous genes in a synthetic pathway

Developing an efficient and robust whole-cell biocatalyst to produce a target chemical often requires the recruitment of heterologous genes to constitute a synthetic pathway in the microorganism. Even though advances in the recombinant DNA technology have resulted in powerful and convenient molecular biology tools to transfer genes among species, it is still a challenging task to optimize the operation of a synthetic pathway in the microorganism due to imbalanced metabolic fluxes not only in the synthetic pathway but also in other associated pathways. This imbalance results in the accumulation of intermediates that are toxic to cells, which inhibits cell growth and decreases production of a target metabolite.


We are interested in developing a rational approach to optimize the performance of the synthetic operons constituting a synthetic pathway in an engineered host by satisfying two design criteria: (1) balancing metabolic fluxes existing in the synthetic pathway and (2) controlling the flux directed to the synthetic pathway to avoid inhibition effect on other associated pathways.

4. Molecular pathway evolution

An optimized cell designed to couple cell growth and operation of a target pathway can be utilized as an useful host to conduct the in vivo molecular pathway evolution because cell growth is inhibited without the functioning of the target pathway. The selection basis for the molecular pathway evolution is growth phenotype which is easy to implement. In the recent studies, we successfully demonstrated this approach by developing optimized E. coli cells that can convert mixed sugars and biodiesel waste, glycerol into bioethanol (7-8).


We are exploring this approach in different optimized cells to improve titers, yields, and productivities for production of biofuels, biochemicals, and secondary metabolites. With this approach, the molecular pathway evolution can also be implemented by replacing the enzyme of a reaction within the target pathway with a potential candidate from a library of mutated enzymes or from different microorganisms that have similar or related functions. Only cells containing complementary enzymes can support cell growth. The candidate can be selected by using advanced cell-culturing techniques such as a cytostat, turbidostat, and/or CO2-stat. With these selection methods, only host cells containing enzymes with high activities are enriched in the bioreactor while others are washed out. We anticipate that the molecular pathway evolution is complementary to the rational approach to optimize the performance of a synthetic metabolic pathway. Toward this end, we are interested in better understanding the fundamental mechanism of the molecular pathway evolution resulting in desirable phenotypes by using systems-biology tools and hence discovering novel genotype-phenotype links to implement inverse metabolic engineering.


References

1. R. Overbeek et al., Nucleic acids research 33, 5691 (2005).

2. A. Osterman, R. Overbeek, Current opinion in chemical biology 7, 238 (2003).

3. V. de Crecy-Lagard, A. D. Hanson, Trends in microbiology 15, 563 (2007).

4. C. Trinh, A. Wlaschin, F. Srienc, Applied Microbiology and Biotechnology 81, 813 (2009).

5. S. Schuster, D. A. Fell, T. Dandekar, Nat Biotechnol 18, 326 (2000).

6. C. T. Trinh, R. Carlson, A. Wlaschin, F. Srienc, Metabolic engineering 8, 628 (2006).

7. C. T. Trinh, P. Unrean, F. Srienc, Applied and Environmental Microbiology 74, 3634 (2008).

8. C. T. Trinh, F. Srienc, Applied and Environmental Microbiology 75, 6696 (2009).

9. H. W. Blanch et al., ACS chemical biology 3, 17 (2008).

10. E. Palmqvist, B. Hahn-H├Ągerdal, Bioresource technology 74, 17 (2000).

11. E. Palmqvist, B. Hahn-H├Ągerdal, Bioresource technology 74, 25 (2000).

12. C. T. Trinh, S. Huffer, M. E. Clark, H. W. Blanch, D. S. Clark, Biotechnology and Bioengineering 106, 721 (2010).



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Updated 13 July 2011 MW

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