Stephen S. Fong, Ph.D.

Professor, Department of Chemical and Life Science Engineering

  • Engineering West Hall, Room 422, Richmond VA UNITED STATES
ssfong@vcu.edu

Bioengineer who modifies micro-organisms to produce chemicals (e.g. from beer to fuel).

Contact

Industry Expertise

Education/Learning

Areas of Expertise

Systems Biology
Synthetic Biology
Evolutionary Biology
Metabolic Engineering
Molecular engineering
Molecular Evolution
Computational Modeling
Computational metabolic modeling
Biorefineries

Education

University of California, San Diego

Ph.D.

Bioengineering

2004

University of California, San Diego

M.S.

Bioengineering

2001

Worcester Polytechnic Institute

B.S.

Chemical Engineering

1998

Media Appearances

Historic Jamestowne, Hardywood Park Craft Brewery to debut historic brew in Richmond

The Virginia Gazette  online

2019-10-15

Jamestown archaeologists worked with professors Stephen Fong, Grace Lim-Fong and Hardywood brewers to harvest a strain of yeast from the island which was then used to recreate the beer, Givens said.

View More

Beer Fundamentals

Richmond Magazine  online

2019-09-04

Stephen Fong, a VCU engineering professor who lectures on quality assurance and process, is part of an interdisciplinary faculty team aiming to grow the program through the addition of laboratory equipment. The goal is to “bring participants through the entire brewing process from raw materials to the chemical analysis of finished products,” Fong says.

View More

All-day “hackathon” engages students in environmental problem-solving

The Commonwealth Times  print

2019-01-23

“[We] wanted to provide an avenue for people to be able to do something,” said Stephen Fong, VCU associate professor and EarthHacks mentor. “And by doing something, I mean thinking about it more deeply, diving into it, and saying, ‘I want to learn more about this … is there some solution we can think about?’”

“And it doesn’t have to be an overly complicated solution. Sometimes the solutions are simple,” Fong said. “There are small adjustments we could get people to make right now that could alter the long-term results.”

“The way we go about our daily lives sometimes isn’t really in the best interest of human well-being,” Fong said. “Extrapolating long-term … short-term maybe it doesn’t make that big a difference, but after a while, there’s a cumulative effect.”

View More

Show All +

Event Appearances

Tinkering with (Bio)Engineering Education

TEDxRVA  Richmond, Virginia

2013-07-19

Selected Articles

Synthetic biology: A foundation for multi-scale molecular biology

Bioengineered Bugs

2010

The field of synthetic biology has made rapid progress in a number of areas including method development, novel applications, and community building. In seeking to make biology “engineerable,” synthetic biology is increasing the accessibility of biological research to researchers of all experience levels and backgrounds. One of the underlying strengths of synthetic biology is that it may establish the framework for a rigorous bottom-up approach to studying biology starting at the DNA level. Building upon the existing framework established largely by the Registry of Standard Biological Parts, careful consideration of future goals may lead to integrated multi-scale approaches to biology. Here we describe some of the current challenges that need to be addressed or considered in detail to continue the development of synthetic biology. Specifically, discussion on the areas of elucidating biological principles, computational methods, and experimental construction methodologies are presented.

View more

Genome-scale metabolic model integrated with RNAseq data to identify metabolic states of Clostridium thermocellum

Biotechnology Journal

2010

Constraint-based genome-scale metabolic models are becoming an established tool for using genomic and biochemical information to predict cellular phenotypes. While these models provide quantitative predictions for individual reactions and are readily scalable for any biological system, they have inherent limitations. Using current methods, it is difficult to computationally elucidate a specific network state that directly depicts an in vivo state, especially in the instances where the organism might be functionally in a suboptimal state. In this study, we generated RNA sequencing data to characterize the transcriptional state of the cellulolytic anaerobe, Clostridium thermocellum, and algorithmically integrated these data with a genome-scale metabolic model. The phenotypes of each calculated metabolic flux state were compared to 13 experimentally determined physiological parameters to identify the flux mapping that best matched the in vitro growth of C. thermocellum. By this approach we found predicted fluxes for 88 reactions to be changed between the best solely computational prediction (flux balance analysis) and the best experimentally derived prediction. The alteration of these 88 reaction fluxes led to a detailed network-wide flux mapping that was able to capture the suboptimal cellular state of C. thermocellum.

View more

Exploring biodiversity for cellulosic biofuel production

Chemistry & Biodiversity

2010

Industrial production of solvents such as EtOH and BuOH from cellulosic biomass has the potential to provide a sustainable energy source that is relatively cheap, abundant, and environmentally sound, but currently production costs are driven up by expensive enzymes, which are necessary to degrade cellulose into fermentable sugars. These costs could be significantly reduced if a microorganism could be engineered to efficiently and quickly convert cellulosic biomass directly to product in a one-step process. There is a large amount of biodiversity in the number of existing microorganisms that naturally possess the enzymes necessary to convert cellulose to usable sugars, and many of these microorganisms can directly ferment sugars to EtOH or other solvents. Currently, the vast majority of cellulolytic organisms are poorly understood and have complex metabolic networks. In this review, we survey the current state of knowledge on different cellulases and metabolic capabilities found in various cellulolytic microorganisms. We also propose that the use of large-scale metabolic models (and associated analyses) is potentially an ideal means for improving our understanding of basic metabolic network function and directing metabolic engineering efforts for cellulolytic microorganisms.

View more