A metabolic network describing a cellular metabolism typically contains hundreds to thousands of reactions catalyzed by functional enzymes to convert substrates into precursor metabolites used for cell synthesis and other metabolites secreted to extracellular environments. These functional enzymes are directly encoded by functional and regulatory genes that determine cell phenotypes. Through metabolic network modeling, we can decompose a complex metabolic network into unique pathways, each of which contains a minimal set of enzymatic reactions supporting cell functions.  Each of these independent pathways can represent physiological states of cell operation. Complete 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 can be rationally designed, constructed, and validated to function only according to the most efficient pathways to produce target products (e.g., chemicals, fuels, and materials).

Trinh lab is particularly focused on understanding and harnessing modularity of complex biological systems for industrial biocatalysis (Figure 1). We are developing the MODCELL technology that enables rapid development of optimal production strains in a plug-and-play fashion to produce a large space of biomolecules, e.g., advanced biofuels, biochemicals, and biomaterials from renewable feedstocks or wastes (e.g., mixed plastics wastes, CO2) as well as high-valued products such as fine chemicals, secondary metabolites, and enzymes. These production strains are assembled from a universal modular (chassis) cell and different production modules based on modular cell design principles.

Figure 1: Blueprint of Modular Cell Design

We are developing the following computational tools:

(1) ModCell (Modular Cell): This tool designs optimal modular cells that can couple with exchangeable production modules to build modular microbial cell factories in a plug-and-play fashion for efficient production of desirable molecules.

(2) MMF (Minimal Metabolic Functionality): This tool identifies a minimal set of gene deletions to achieve high production of target molecules.

(3) SMET (Systematic Multiple Enzyme Targeting): This tool combines both structural and dynamic modeling to systematically identify target enzymes and their levels of up/down expression to enhance production of target molecules.

We are applying these tools to construct and characterize several different microbial biotransformation platforms including bacteria (Escherichia coli, Clostridium thermocellum, Bacillus coagulans) and yeasts (Saccharomyces cerevisiae, and Yarrowia lipolytica) for combinatorial biosynthesis of esters that can be used as flavors, fragrances, solvents, and biofuels.

Funding sources: The U.S. National Science Foundation; The U.S. Department of Energy.

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.   These inhibitors can be unwantedly generated during pretreatment, enzymatic hydrolysis, and fermentation.  Depending on the biofuel process, inhibitors can be 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, organic solvents derived from pretreatments (e.g., ionic liquids), and/or fermentative products synthesized by microorganisms (e.g., ethanol, (iso)butanol, esters).   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 links resulting in chemical resistance in microorganisms are complex and very often unknown.

Figure 2: Pipeline of adaptive laboratory evolution and genome-wide analysis to understand and optimze cellular robustness

To engineer cellular robustness, Trinh lab has applied and developed various genome engineering tools. One developed tool is the gene swapping and amplification that is designed to transfer novel phenotypes from not-well-characterized microorganisms exhibiting high resistance to chemical inhibitors to an engineered host. The other approach is based on the classical but effective adaptive laboratory evolution (Figure 2). In parallel to the engineering efforts, Trinh lab is also interested in developing and applying novel omics tools to elucidate the genetics and underlying mechanisms enable cellular robustness through systems-wide analysis. 

Funding sources: The U.S. National Science Foundation; The U.S. Department of Energy.

Developing an efficient and robust whole-cell biocatalyst to produce a target chemical requires the recruitment of heterologous genes to constitute a synthetic metabolic pathway in the microorganism.   Even though advances in the recombinant DNA technology have developed powerful and convenient molecular biology tools to transfer genes among species, it is still a challenging task to optimize the operation of synthetic metabolic pathways in a microorganism due to imbalanced metabolic fluxes not only in the synthetic metabolic 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.  

Trinh lab is interested in developing novel prototypes to efficiently and rapidly design and optimize the performance of synthetic operons that can dynamically control fluxes of synthetic and native metabolic pathways for enhanced product formation in engineered cells. We are currently exploring a large space of novel pathways for combinatorial microbial biosynthesis of esters that can be used as flavors, fragrances, solvents, and biofuels (Figure 3).

Figure 3: Metabolic pathway platform for biosynthesis of butyrate esters

Funding sources: The U.S. National Science Foundation; The U.S. Department of Energy.

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 metabolic 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. 

Figure 4: Directed metabolic pathway evolution using ModCell design

We are exploring this approach using our MODCELL technology to improve titers, yields, and productivities for microbial production of biofuels, biochemicals, secondary metabolites, and enzymes.  With this approach, the metabolic pathway evolution can 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 (Figure 4).  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 parallel, we are highly interested in better understanding the underlying mechanisms of the molecular pathway evolution resulting in desirable phenotypes by using systems-biology tools and hence discovering novel genotype-phenotype links to guide the inverse metabolic engineering.

Funding sources: The U.S. National Science Foundation; The U.S. Department of Energy.

In the war against virulent pathogens, defensive measures must be developed quickly and be readily modifiable to counter rapid and unpredictable evolution of resistance.  The current paradigm relies on small molecule discovery technologies that are unable to scale to production fast enough to counter pathogens that can rapidly adapt to neutralize existing treatments. To address the challenge, we seek to develop the ViPaRe (Virulent Pathogen Resistance) technology capable of inactivating rapidly evolving and resistant infectious pathogens (e.g, Staphylococcus aureus, Candida albicans, Candida auris, Escherichia coli ) in their microbiomes using the CRISPR-based gene editing technology (Figure 5).

Figure 5: ViPaRe technology

We are developing the following computational tools:

CASPER (CRISPR Associated Software for Pathway Engineering and Research): This tool enables gRNA designs for any organisms and Cas enzymes of interest. It also contains novel features for analyzing multiplexing, multitargeting, multipopulation, and PAMs.

Funding sources: The U.S. Department of Defense.