(2fd) Quantitative Metabolism in Microbes and Microbial Communities

Microorganisms enable the conversion of plant feedstock to fuels and value-added chemicals, demonstrating great potential to meet increasing societal demand for clean energy, biomass conversion, and carbon sequestration. They also form microbial communities that are crucial metabolic players in human health and geochemical cycle. Systems level knowledge of their metabolism is the key to our ability to adapt, exploit, and extend what nature has accomplished. My goal as an independent investigator is to elucidate the metabolism and metabolic control principles in diverse microorganisms and microbial communities, and develop tools to enable rapid iterative design.

My research program will focus on three major themes:

Develop high throughput imaging tools for pathway activity-based selection. Accompanying genome-wide engineering capability is the need for rapid testing, in specific, measuring the flux through the engineered pathway. In addition, individual-to-individual variability within a population of cells is also a limiting factor in scale-up. My research aims to develop chemical imaging to allow rapid screening of genetic variants or culture conditions, thereby accelerating the design-build-test-learn (DBTL) cycle.

Diagnose and overcome metabolic bottlenecks in carbon source co-utilization. Versatile carbon source co-utilization in microorganisms allows upgrading products derived from photochemical conversion of CO2, but has been proved difficult. My research aims to use systems approach to diagnose bottleneck therein, and understand the molecular mechanism to overcome the bottleneck during adapted lab evolution.

Quantitate fluxes in synthetic and natural microbial communities and build predictive models for environmental response. Microbial communities maintain their chemical environment through coordinated metabolism, which produces molecular signals to be sensed by the host (mammalian gut or plant root). Genome information reveals metabolic capability of community members, without knowledge on how much of the capacity is realized. My research aims to quantitatively map fluxes within the microbial community by means of absolute exometabolomics and flux analysis, and elucidate the dynamic response to environmental changes.

Research Experience

Doctoral training with Wei Min, Chemistry, Columbia University

I had a huge interest in developing microscopic tools that allow mapping biological activity in live cells. Fluorescence microscope has transformed biology, yet it was challenging to track small molecules such as metabolites. Therefore, my doctoral study focuses on developing stimulated Raman scattering (SRS) microscopy to image metabolic activity. SRS allows rapid and quantitative visualization of chemical bonds at sub-micron resolution. Tracking of the molecule is achieved with a vibrational tag, a minimal Raman-active chemical moiety such as a carbon-deuterium bond. I developed imaging tools to measure protein turnover rate within a cell. Applying the technique to track fatty acid metabolism, I found that it not only quantitatively aligned with lipidomics, but also revealed micron-scale phase separation of lipid metabolites, which have profound structural impact on intracellular membrane systems. Bring in the spectral information to decode chemical specificity, I also co-developed spectral tracing of glucose in animals, which allows product specific mapping of glucose anabolism. Overall, my doctoral training has cultivated my belief that technology transforms how we perceive the world.

Postdoctoral training with Joshua Rabinowitz, Chemistry and Genomics, Princeton University

My current research aims to gain systems level understanding of metabolic control. In bioenergy applications, engineering of microorganisms has benefited from thorough knowledge of their native metabolism. This goes beyond genome, and is rather how that genetic information is executed. In addition to a model yeast, of which systems level measurement has accumulated over the years, I also work on non-model yeasts with greater engineering potential. To assess metabolic control in these yeasts, I took a systems approach, integrating proteomics, metabolomics and metabolic flux analysis. I showed that the flexibility of metabolic network is conferred by how much enzyme is used rather than enzyme expression. More importantly, energy metabolism is a cost-benefit choice between achieving maximal proteome efficiency and maintaining spare capacity for hedging against unpredictable environment. My postdoc training also exposes me to many collaborative efforts in bioenergy research center, and build teamwork into my research philosophy.

Teaching Interests

I have served as teaching assistant in general chemistry lab and physical chemistry I and II recitation, and mentored 2 graduate students and 3 undergraduate students. With my teaching experience as well as my own research experience, I think I will be well suited to teach both general or advanced courses, including physical chemistry, thermodynamics, optical imaging and spectroscopy, biochemistry, and omics techniques. My goal of teaching is to engage students in active learning, and support them in pursuit of their own career goals.

Selected publications

Y. Shen, F. Xu, L. Wei, F. Hu, W. Min. ‘Live-cell quantitative imaging of proteome degradation by stimulated Raman scattering.’ Angew. Chem. 2014, 53, 5596.

Y. Shen, Z. Zhao, L. Zhang, L. Shi, S. Shahriar, R. B. Chan, G. Di Paolo & W. Min. ‘Metabolic activity induces membrane phase separation in endoplasmic reticulum’, Proc. Natl. Acad. Sci, 2017, 114 (51), 13394.

L. Zhang*, L. Shi*, Y. Shen*, Y. Miao, M. Wei, N. Qian, Y. Liu & W. Min. ‘Spectral tracing of deuterium for imaging glucose metabolism’, Nat. Biomed. Eng. 2019, 3 (5), 402 (* equal contribution)

Y. Shen*†, Z. Zhao*, L. Shi, C. Petzold, F. Liang & W. Min †. ‘Advanced imaging reveals relay of phase separation from lipid to protein in response to saturated fatty acid’, 2022, under revision. († co-corresponding, * co-first)

Y. Shen, H. V. Dinh, E. Cruz, C. M. Call, H. Baron, R. P. Ryseck, J. Pratas, A. Subramanian, Z. Fatma, D. Weilandt, S. Dwaraknath, T. Xiao, J. I. Hendry, V. Tran, L. Yang, Y. Yoshikuni, H. Zhao, C. D. Maranas, M. Wühr †, J. D. Rabinowitz †. ‘Proteome capacity constraints favor respiratory ATP generation’. 2022, submitted (†co-corresponding)