Ph.D., Energy, Environmental & Chemical Engineering, Washington University in St. Louis, 2012
B.S., Biology, Wuhan University, 2008
B.S., Environmental Engineering, Huazhong University of Science & Technology, 2008
August 2014 - present – Assistant Professor, Department of Biological Systems Engineering, Virginia Tech
March 2012 - May 2014 – Postdoctoral Fellow, Energy Biosciences Institute – Illinois, University of Illinois at Urbana-Champaign
Selected Major Awards
- 2016 - Junior Faculty Award, Institute of Critical Technology and Applied Science (ICTAS), Virginia Tech
- 2013 - Shen Postdoctoral Fellow, Dept. of Chemical & Biomolecular Engineering, University of Illinois at Urbana-Champaign
- 2011 - Doctoral Student Research Award, Dept. of Energy, Environmental & Chemical Engineering, Washington University in St. Louis
- 2010 - Student Travel Grant, the 110th General Meeting of the American Society for Microbiology
Courses taught for last five years:
- BSE 3534 - Bioprocess Engineering
- BSE 4564 - Metabolic Engineering
- BSE 5964 - Advanced Metabolic Engineering
- SYSB 2025: Introduction to Systems Biology (FL2015/FL2016)
- CEE 5984: Engineering Solutions for Environmental Sustainability (SP2015)
- GBCB 5874: Problem Solving in Genetics, Bioinformatics, and Computational Biology (SP2015)
- BSE 2004: Introduction to Biological Systems Engineering (SP2015/FL2015/FL2016)
- SYSB 3115: Network Dynamics & Cell Physiology (FL2016)
I have mentored 17 undergraduate students in my research laboratory in the past two years. I also mentor 1-2 senior design teams each academic year.
My research program concentrates on the following areas:
Area 1: Develop noval methods in systems biology to uncover the cell-wide regulations of cell metabolism. We will develop a high-throughput 13C-MFA approaches to take "snapshot" of intracellular differences of cell metabolism (i.e., phenotype), and apply multi-omics analysis to profil the corresponding transcriptome, proteome and metabolome changes (i.e., genotype). The phenotype and genotype of cell metabolism will then be linked to reveal the cell-wide regulation using state-of-art machine learning approaches.
- Cross-omics analysis (CROSSOM). We are developing a noval platform to connect multi-omics data with flux balance analysis to achieve accurate phenotype prediction. Our method is innovative since it does not require a priori knowledge of either objective function for cell metabolism or the interactions among cell components (e.g., genese and proteins).
- Integrated Genotype and Phenotype (iGAP) Database. We are collecting the paired dataset of gene expression, protein abundance, metabolite concentration and cell pheotype for model orgamisms such as E. coli and S. cerevisiae, from research publications in NCBI and public gene expression database such as GEO. We will normalize gene/protein/metabolite expression datasets (with fold change and p-value) to make the data generated by different laboratories and researchers more comparable, and integrate them with cell phenotype (e.g., growth rate, byproduct yield), cell cultivation conditions and the stress factors, to an organized "open-source" mega-dataset.
Area 2: Design novel methods in synthetic biology to rewire the cell metabolism. We will design a synthetic regulatory network to control the fate of cell metabolism. We will also develop molecular tools to edit the genome of eukaryotic cells and achieve novel cell functions.
- dCas9-based genome editing. We are developing an innovative, rule-based genome editing tools for yeast and other eukaryotic organisms using dCas9/CRISPR. It can target on multiple genetic targets (i.e., multiplexed) and simultaneously achieve gene activation and repression for different genes (i.e., programmable). We will apply the dCas9-based genome-editing tool for studying key regulatory pathways in protein synthesis and optimizing biochemical productions.
- Incorporating unnatural amino acids into proteins. We are synergizing synthetic biology and metabolic engineering to engineer S. cerevisiae for in vivo synthesis of unnatural amino acids and incorporation of unnatural amino acids into target proteins simultaneously. This technology will scale up the research on unnatural amino acids from shaker flasks to pilot fermenters, and will be applied in various areas such as development of novel drug delivery methods.
Area 3: Systems metabolic engineering of microbes to produce biochemicals. We will integrate the systems biology approaches and metabolic engineering approaches to make S. cerevisiae produce both bulk chemicals (such as fatty alcohols) and value-added chemicals (such as drugs) from renewable feedstock (such as xylose and arabinose).
- Fatty alcohols. We are engineering S. cerevisiae to produce medium chain (C8~C12) and long chain (C14~C20) fatty alcohols from renewable feedstocks. To this end, we will develop a "design-build-test-improve" cycle by applying RNAseq and metabolic modeling approaches to "design" the best mutants for fatty alcohol production, using promoter engineering and dCas9-based genome editing tools to "build" the target mutants, running HPLC and GC-MS to "test" the fatty alcohol production of the mutants, and interrogating the yeast metabolism via 13C-MFA to "improve" the mutant design.
- Therapeutic proteins. We are engineering S. cerevisiae to produce HBV vaccines in a more affordable way by identifying the key genes involved in protein degradation, protein folding, protein trafficking and protein secretion. Once the key genes are identified, we will apply the similar "design-build-test-improve" cycle to improve vaccine production in yeast.
Selected Recent Publications
(*undergraduate student, **graduate student, *** post-doc)
Guo W**, Chen Y, Wei N, Feng X. “Investigate the metabolic reprogramming of Saccharomyces cerevisiae for enhanced resistance to mixed fermentation inhibitors via 13C metabolic flux analysis” PLoS One. 2016, 11(8):e0161448.
Suastegui M, Guo W**, Feng X, Shao Z. “Investigating strain dependency in the production of aromatic compounds in Saccharomyces cerevisiae.” Biotechnol Bioeng. 2016, 113(12):2676-2685.
Sheng J***, Stevens J*, Feng X. “Pathway compartmentalization in peroxisome of Saccharomyces cerevisiae to produce versatile medium chain fatty alcohols” Sci Rep. 2016, 6: 26884.
Quarterman J, Skerker JM, Feng X, Liu IY, Zhao H, Arkin AP, Jin YS. “Rapid and efficient galactose fermentation by engineered Saccharomyces cerevisiae” J Biotechnol. 2016, 229:13-21.
Guo W**, Feng X. “OM-FBA: Integrate transcriptomics data with flux balance analysis to decipher the cell metabolism” PLoS One. 2016, 11(4):e0154188.
Zhang J***, Wu C**, Sheng J***, Feng X. “Molecular basis of 5-hydroxytryptophan synthesis in Saccharomyces cerevisiae” Mol BioSyst. 2016, 12: 1432-1435.
Huttanus H**, Sheng J***, Feng X. “Metabolic engineering for production of small molecule drugs: challenges and solutions” Fermentation. 2016, 2(1): 4.
Guo W**, Sheng J***, Zhao H, Feng X. “Metabolic engineering of Saccharomyces cerevisiae to produce 1-hexadecanol from xylose” Microb Cell Fact. 2016, 15: 24.
Luo S, Guo W**, Nealson K, Feng X, He Z. “13C pathway analysis for the role of formate in electricity generation by Shewanella oneidensis MR-1 using lactate in microbial fuel cells” Sci Rep. 2016, 6: 20941.
- Virginia Tech - "Researchers discover a royal flush in powering fuel cells with wastewater"
- WVTF (89.1 FM) - "Keeping Energy from Going Down the Drain"
- CityLab - "A Better Way to Turn Poop Into Energy"
- Science Daily - "Scientists unlock key to turning wastewater and sewage into power"
Guo W**, Sheng J***, Feng X. “13C-Metabolic flux analysis: an accurate approach to demystify microbial metabolism for biochemical production” Bioengineering. 2016, 3,3.
Chen Y, Sheng J***, Jiang T, Stevens J*, Feng X, Wei N. “Transcriptional profiling reveals molecular basis and novel genetic targets for improved resistance to multiple fermentation inhibitors in Saccharomyces cerevisiae” Biotechnol Biofuels. 2016, 9:9.
- "Top three most cited articles of 2016" from Biotechnology for Biofuels.
Sundararaman N, Ash C*, Guo W**, Button R, Singh J*, Feng X. “iTAP: Integrated transcriptomics and phenotype database for stress response of Escherichia coli and Saccharomyces cerevisiae” BMC Res Notes. 2015, 8: 771.
Zhuang L, Guo W**, Yoshida M, Feng X, Goodell B. “Investigating oxalate biosynthesis in wood-decaying fungus Gloeophyllum trabeum using 13C metabolic flux analysis” RSC Adv. 2015, 5: 104043-104047.
Kim M, Le HM, Xie X, Feng X, Tang YJ, Mouttaki H, McInerney MJ, Buckel W. “Two pathways for glutamate biosynthesis in the syntrophic bacterium, Syntrophus aciditrophicus” Appl Environ Microbiol. 2015, 81(24):8434-8444.
Sheng J*** and Feng X. “Metabolic engineering of yeast to produce fatty acid-derived biofuels: bottlenecks and solutions” Front. Microbiol. 2015, 6:554.
Guo W**, Luo S, He Z, Feng X. “13C pathway analysis of biofilm metabolism of Shewanella oneidensis MR-1” RSC Adv. 2015, 5: 39840-39843.
Feng X, Lian J, Zhao H. “Metabolic engineering of Saccharomyces cerevisiae to improve 1-hexadecanol production” Metab Eng. 2015, 27: 10-1
- “CFPS-On-A-Chip: Development of a microfluidic platform for engineered therapeutic proteins”, PIs Feng X, Lu C, ICTAS, $120,000, 7/16-7/18.
- “On-Chip Manufacturing of Synthetic Proteins for Point-of-Care Therapeutics”, PIs Feng X, Lu C, Li L, ICTAS, $20,000, 1/17-6/17.