Biomedical Engineering

Cheemeng Tan

Tan Assistant Professor

530-752-7849

cmtan@ucdavis.edu

Office: 3009 Ghausi

Tan Lab

Personal Education
Ph.D. Biomedical Engineering , 2010, Duke University
M.S. in High Performance Computation for Engineered Systems, 2002, Singapore-MIT Alliance
B.E. (First Class Honor), 2001, National University of Singapore

Research Interests
The engineering of artificial cellular systems

Artificial cellular systems have tremendous potential for applications in biosensors, drug delivery, and synthetic biological studies. We have established a multi-scale approach that consists of single molecule experiments, cell-free expression systems, and artificial cells. Single molecule experiments could unravel the heterogeneity in molecular interactions, which could impact dynamics of synthetic biological systems. Based on the framework, we are interested in constructing artificial cellular systems for novel biotechnological applications. Furthermore, we are interested in unveiling new insights into gene regulation by exploiting the multiscale framework.

Novel strategies of antibiotic treatment

Traditional approaches towards antibacterial treatment are failing and there is a critical need to design better treatment strategies. On the one hand, this strategy is becoming inevitable due to the lack of new antibiotics. On the other hand, proper dosing of antibiotics could gradually reduce the frequency of resistant bacteria by exploiting the slight growth disadvantage of resistant bacteria in the absence of antibiotic treatment. We are interested in designing new synthetic biological strategies to combat bacterial resistance.

Underlying mechanisms of cellular heterogeneity

Classical therapeutic treatment generally does not take into account of heterogeneity in the targeted cellular population. However, it is known that cellular heterogeneity can diminish the efficacy of drug targeting and treatment. We are interested in the fundamental understanding of how cellular populations generate heterogeneous phenotype, which could be exploited to improve new treatment strategies. We address the question using a combination of quantitative modeling, molecular biology, and imaging methods.

Selected Publications

Shaping gene expression in artificial cellular systems by cell-inspired molecular crowding.

C. Tan, S. Saurabh, M. Bruchez, R. Schwartz, and P. LeDuc.

Nature Nanotechnology, 2013.

The inoculum effect and band-pass bacterial response to periodic antibiotic treatment.

C. Tan*, R. Smith*, J. Srimani, K. Riccione, S. Prasada, M. Kuehn, and L. You. (*Equal contribution).

Molecular Systems Biology, 2012

Frontiers of optofluidics in synthetic biology.

C. Tan, S. Lo, P. LeDuc, and CM. Cheng.

Lab on a Chip, 2012

Emergent bistability by a growth-modulating positive feedback circuit.

C. Tan, P. Marguet, and L. You.

Nature Chemical Biology, 2009.

A synthetic biology challenge: making cells compute.

C. Tan, H. Song, J. Niemi, and L. You.

Molecular BioSystems, 2007.

 

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