Anushree Chatterjee

Anushree ChatterjeeAssistant Professor
(303) 735-6586
Curriculum Vitae
Google Scholar Profile
Chatterjee Research Group


Ph.D., University of Minnesota (2011)
M.S., Indian Institute of Technology Delhi (2006)
B.S., Indian Institute of Technology Delhi, Chemical Engineering (2006)


  • New Inventor of the Year by University of Colorado Technology Transfer Office, 2014
  • Center for Nonlinear Studies Postdoctoral Fellow, Los Alamos National Laboratory, 2011-2012
  • Doctoral Dissertation Fellowship, University of Minnesota, 2010-2011
  • Microbial and Plant Genomics Institute Grant award, University of Minnesota, 2009
  • Usha Kumar Fellowship, University of Minnesota, 2006
  • Suman-Upma Gupta Memorial Gold medal, Indian Institute of Technology Delhi, 2006

Selected Publications

  • Anushree Chatterjee, Laura C. Cook, Che-Chi Shu, Yuching Chen, Dawn Manias, Doraiswami Ramkrishna, Gary M. Dunny and Wei-Shou Hu (2013), “Antagonistic self-sensing and mate-sensing signaling controls antibiotic-resistance transfer.” Proceedings of National Academy of Sciences, 110(17), 7086-7090.
  • Anushree Chatterjee, Christopher M. Johnson, Che-Chi Shu, Yiannis N. Kaznessis, Doraiswami Ramkrishna, Gary M. Dunny and Wei-Shou Hu (2011). “Convergent transcription confers a bistable switch in Enterococcus faecalis conjugation.” Proceedings of the National Academy of Sciences, 108: 9721-9726.
  • Anushree Chatterjee, Laurie Drews, Sarika Mehra, Eriko Takano, Yiannis N. Kaznessis and Wei-Shou Hu (2011), “Convergent transcription in the butyrolactone regulon in Streptomyces coelicolor confers a bistable genetic switch for antibiotic biosynthesis.” PLoS ONE, 6:e21974.
  • Che-Chi Shu, Anushree Chatterjee, Gary M. Dunny, Wei-Shou Hu and Doraiswami Ramkrishna (2011), “Bistability versus Bimodal Distributions in Gene Regulatory Processes from Population Balance Model.” PLoS Computational Biology 7(8):e1002140.
  • Laura CC Cook, Anushree Chatterjee, Aaron Barnes, Jeremy Yarwood, Wei-Shou Hu and Gary M. Dunny (2011), “Biofilm growth alters regulation of conjugation by a bacterial pheromone.” Molecular Microbiology, 81(6): 1499-1510.
  • Christopher M Johnson, Heather Haeming, Anushree Chatterjee, Wei-Shou Hu, Keith E. Weaver, and Gary M. Dunny (2011), “RNA-mediated reciprocal regulation between two bacterial operons is RNAse III dependent” mBio, 2(5): e00189-11.
  • Anushree Chatterjee, Patrick F. Smith and Alan S. Perelson (2012), “Hepatitis C viral kinetics: the past, present and future.” Clinics in Liver Disease, doi:10.1016/j.cld.2012.09.003 (in press).

Research Interests

Our research group uses a combination of interdisciplinary approaches including chemical engineering, synthetic biology, systems biology, molecular biology, microbiology, metabolic engineering and computational biology to address key global challenges including medical and energy needs. We are interested in adopting an integrated mathematical modeling and experimental approach to investigate fundamental and medically relevant issues such as understanding the molecular mechanisms responsible for antibiotic and antiviral resistance, and for developing “next-generation smart antimicrobials” by rationally engineering novel therapeutics that target essential bacterial/viral genes in a potentially resistance-free manner. We study genetic regulatory networks that control propagation of infectious diseases such as Hepatitis C, with the goal of discovering novel drug targets for therapy. Using synthetic biology tools we design, construct and engineer modular synthetic genetic devices that can achieve higher-order biological computation, for variety of biotechnological and bioenergy applications. To this end, we engineer biological parts such as transcription factors, promoter sequences, receptors, feedback loops, and regulatory RNA to build complex genetic networks that can be used to optimize cellular machinery for production of bio-fuels and pharmaceuticals, and for gene therapy applications. Using these genetic devices, we apply systems biology approaches to understand functioning of complex genetic networks and to build rules to manipulate such networks.