SCS Faculty Candidate

  • Research Fellow
  • Department of Systems Biology
  • Harvard Medical School

Gene Regulation and Dynamical Efficacy in Antibiotic Responses

Our conventional understanding of antibiotic resistance is based almost entirely on the notion of a bacterial population’s ability to maintain growth under steady-state drug conditions. Yet, it is becoming increasingly apparent that the outcome of drug treatments depends on highly dynamic responses that show great variation at the single-cell level. The effectiveness of a resistance mechanism depends not only on fine-tuning expression of resistance genes, but also on coping with transient fast-changing conditions. The study of such systems requires a quantitative understanding of the regulation of resistance genes at multiple levels, ranging from its molecular basis to networks controlling cell responses. Focusing on the tet operon, I show that, somewhat counterintuitively, prompt expression of TetR, the repressor of TetA efflux pump, is key for cellular survival upon abrupt exposure to tetracycline. Tracking individual cells upon exposure shows that differences in the rate of TetR elevation result in three distinct cell fates: recovery (high rate), death from excess of TetA (intermediate rate) and death from the drug (low rate). Early TetR expression is essential to increase the responsiveness of the tet system, showing how regulatory circuits of resistance genes have evolved for optimized dynamics.


Daniel Schultz is a Research Fellow at the Department of Systems Biology at the Harvard Medical School and a Visiting Scientist at the Department of Biology at the Technion, Israel. He has a background in electrical engineering from the Technological Institute of Aeronautics, in Brazil, and started his academic career investigating the stability of small carbon nanoparticles. He then obtained his Ph.D. in Chemistry and Biochemistry from UC San Diego, working at the Center for Theoretical Biological Physics, using stochastic models of gene regulation to study the role of noise in bacterial networks performing cell decisions.

In his postdoctoral work, Dr. Schultz has developed quantitative approaches to study the emergence, operation and optimization of gene networks, focusing on the dynamics of antibiotic resistance mechanisms in bacteria. His research program employs both theoretical and experimental methods to uncover the selective pressures that shape the evolution of bacterial responses and ultimately guide innovation in clinical therapies.

Faculty Host: Christopher Langmead
Computational Biology

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