Graduate Students
Rohit Jaini
A significant proportion of photosynthetic product in plants is channeled towards the amino acid phenylalanine (Phe) and in turn to lignin, a phenolic heteropolymer that confers structural support to plants but at the same time renders it resistant to degradation for biofuel production. Significant efforts have been made to manipulate lignin biosynthesis mainly focusing on down regulating individual steps of the phenylpropanoid pathway. The choice of the enzyme for down-regulation has been based solely on the enzyme identity and assumed role in lignin synthesis, thereby limiting a mechanistic understanding of the flux regulation in the lignin synthesis pathway. Kinetic modeling of metabolic networks has been gaining attention for its ability to quantitatively predict the dynamic and steady state fluxes in a biochemical pathway, at the same time capturing the effects of modified enzyme activities.

My research is focused in the following areas:
  • Developing a method for identifying and quantifying phenylpropanoid pathway intermediates
  • Conducting nonaqueous fractionation on Arabidopsis thaliana stem tissue and quantifying metabolites in the pathway using data from isotopic labeling experiments
Longyun Guo
As the knowledge of detailed biochemical mechanisms grows, along with the fast development of high-throughput technologies which enable the quantification of metabolites, proteins and transcripts, it is now possible to integrate different sets of data using a systems biology approach to mechanistically understand a biological system. A mathematical model is a quantitative way to hypothesize a potential set of mechanisms to interpret the experimental observations. And once the model is proposed and validated, systematical aspects of the bio-network can be inferred, which is not easily measurable with experiments. Lignin biosynthesis in Arabidopsis is a perfect model system as each enzymatic step is well characterized, and lignin content is always an engineering target since its negative effect towards saccharification. A kinetic model of lignin biosynthesis will contribute to deeper understanding of underlying regulatory mechanisms, and help to provide a rational design for lignin biosynthesis manipulation.

My research is focused in the following areas:
  • Constructing a kinetic model of lignin biosynthesis in Arabidopsis to help understand the dynamic structure of the pathway.
  • Integrate RNA-seq data into the kinetic model to derive potential hierarchical regulations controlling the monolignol composition.
Shaunak (Rick) Ray
The phenylpropanoid pathway plays a major role in the biosynthesis of lignin and numerous secondary metabolites imperative to plant survival and vitality. Lignin biosynthesis, however, impedes the production of biofuel from lignocellulosic biomass. 2-phenylethanol is a highly used fragrance chemical that is naturally synthesized from the aromatic amino acid, L-phenylalanine which also serves as the primary substrate for lignin biosynthesis. It serves as an interesting concept of metabolic engineering of plants to be able to modulate the phenylpropanoid pathway in a way that lignin biosynthesis is reduced and 2-phenylethanol biosynthesis is increased allowing for higher yields of both biofuel and commodity chemicals. The use of kinetic modeling of the enzymatic reactions of the pathway serve as the basis for the prediction of fluxes and building a deeper understanding of the pathway control mechanisms.

My research is focused in the following areas:
  • Using analytical techniques based on chromatography and mass spectrometry for the detection of key metabolites in the biosynthesis of 2-phenylethanol
  • Generating a kinetic model using estimated parameters based on experimental data obtained from [13C6]-phenylalanine labeling studies in Arabidopsis
Jeremiah Vue
The amino acid phenylalanine is a precursor for the artificial sweetener aspartame and is an additive for feed and pharmaceuticals. Phenylalanine is currently produced with fermentative microorganisms such as E. coli as feed through metabolic engineering of the aromatic amino acid pathway. The sugars required for fermentation add production cost and rely on technologies to extract sugars from biomass. An alternative approach is to engineer photosynthetic cyanobacteria using minimal nutrients, solar energy, and carbon dioxide as inputs to produce significant quantities of phenylalanine.

My research is focused in the following areas:
  • Applying random mutagenesis and appropriate selection pressures to discover a strain that overproduces phenylalanine
  • Modifying the aromatic amino acid pathway for production of phenylalanine
Nathaphon (Joel) Yu King Hing
The Calvin cycle, which is responsible for the fixation of carbon dioxide from the atmosphere, is an essential metabolic process common to all photosynthetic organisms. A kinetic model of the Calvin cycle can further improve our understanding of regulatory processes that occur within the cycle, help identify targets for metabolic engineering, and be used to optimize the rate of growth of photosynthetic organisms. Dynamic changes in Calvin cycle behavior caused by changes in light availability could be integrated into the kinetic model to predict steady states in a variety of light conditions.

My research is focused in the following areas:
  • Developing a kinetic model for the Calvin cycle in the cyanobacteria Synechocystis sp. PCC6803 that incorporates metabolic regulation by light
  • Analyzing metabolite profiles of cyanobacteria in different growth conditions using LC/MS and other techniques

Undergraduate Students

  • Nuttanit (Natalie) Pramounmat
Exchange Students

  • Juliana Carrizosa
  Group Social

  • Spring 2016


Han Xiao Jiang (PhD): Amyris Biotechnologies

Hao Chen (PhD): Merck Inc.

Avantika Shastri (PhD): Sabic Innovative Plastics

Nannette Boyle (PhD): Assistant Professor, Colorado School of Mines

Sean Werner (PhD): Exxon Mobil

Neelanjan Sengupta (PhD): Becton Dickinson

Cameron Hill (MS): CalEnergy

John O'Grady (PhD): Perfinity Biosciences

Mattia R. Rastochak (BS): Exxon Mobil

Robin Wheeler (MS)