Research

Research opportunities: The Lambert Lab is seeking highly motivated graduate students and postdocs.

For more information, please email me () or visit the contact page.

The Lambert Lab pursues interdisciplinary research at the intersection of Physics and Quantitative Biology. Our research is motivated by the notion that complex behaviors in bacteria (e.g. pathogenicity, antibiotic resistance, gene regulation and cell-fate decisions, etc.) often arise from cell-to-cell variability, transient cellular dynamics, or heterogeneous phenotypic responses before spreading within a population. Consequently, to gain sufficient insight into active biological processes, information about microorganisms must be gathered at the single-cell level and in real time.

To this end, we combine tools from Physics, Bioengineering, and Synthetic Biology to monitor the response of individual bacteria subjected to environmental fluctuations. We believe that the study of naturally-occurring regulatory systems can lead to the discovery of physical and biological principles broadly applicable to the development of biomedical and diagnostics applications. Ongoing research projects include: 1) the study of the survival strategies used by bacteria in response to toxic environments, 2) a quantitative description of synthetic transcription factors and their robustness to perturbations, and 3) the basis of extracellular information processing in microorganisms.


Antibiotic resistance

Emergence, population dynamics, evolution

The discovery of antibiotics has greatly improved the quality of human life in both health and disease. Increasingly, however, bacterial populations have developed the ability to evolve resistance to antibiotics most commonly used in clinical settings. Can a fundamental understanding of the selective pressures guiding the evolution of antibiotic resistance help the development of new and more efficient antimicrobials?

While obtaining a direct measurement of the selective pressures guiding the evolution of resistance requires monitoring every birth, death or other life event for extended periods of time (a challenging task for many biological systems), our work has recently used a novel mathematical framework --the optimal lineage principle-- to very efficiently characterize these selective pressures. Indeed, using the optimal lineage principle, our analysis shows that complete information about evolutionary pressures can be obtained by simply analyzing the lineage properties of a single individual within a population. Our framework is very powerful, in that it can be generalized to detect signatures of trait-specific selection in other biological systems, including multicellular organisms and even human populations. In the future, the Lambert lab will exploit this powerful approach to characterize the strategies used by bacteria to survive and evolve resistance to antibiotic treatments.

Relevant publications: Physical Review X 5, 011016 [pdf]. News: [Physics spotlight]


Synthetic Biology

Engineered genetic circuits in bacteria

Microorganisms are able to sense single molecules, interpret extracellular signals despite molecular noise and accurately transmit information across time and space using a sophisticated molecular machinery that results from millions of years of evolution. One of the goals of the nascent field of synthetic biology is to harness the complexity of living systems in order to create active biological circuits for tailored applications. However, one of the problems that hinders current progress in synthetic biology is the limited number of orthogonal parts available, which in turn severely limits the interoperability, complexity, and modularity of synthetic gene networks.

Recently, technological advances in engineered synthetic biology have helped resolve some of the inherent constraints associated with the limited set of genetic components currently available. For instance, hundreds of independent regulatory elements with very high on/off ratios (up to 600) have been generated using toehold RNA riboswitches: crucially, this means that a large number of independent logic elements can coexist inside a cell. Similarly, binding of DNA by a deactivated CRISPR associated RNA-protein complex can lead to efficient and programmable interactions between genetic regulatory elements. The goal of the Lambert Lab is to develop engineered synthetic computational elements and characterize their stability, robustness and responsiveness at the single-cell level.

Relevant publication: Cell 165 (5), 1255–1266 [pdf]. News: [Wyss Institute]


Applied Biophysics and Systems Biology

Optimality in gene networks

Environmental noise is an important source of variation in gene expression in microorganisms. Regulatory networks must robustly sense, decode, and transmit information at the molecular level in order to efficiently respond to changing environments. An efficient response typically necessitates the coordination of many regulatory elements. It has been shown that microorganisms can utilize molecular noise to regulate gene expression and facilitate decision-making; are bacteria also capable of similarly exploiting temporal fluctuations to optimize genetic regulation? Moreover, despite recent efforts to quantify absolute expression levels under stable environmental conditions, it is currently unknown which physical principles help maintain robustness in regulatory networks under environmental perturbations. Can we learn more about phenotypic adaptation by investigating the expression dynamics of sensing networks in response to temporal variations?

Broadly, the Lambert lab wants to understand why organisms utilize a particular regulatory architecture to sense extracellular environments. For instance, many metabolic operons utilize different regulatory architectures to achieve a similar role –eg. induction in the lac, trp, ara, and gal operons all involve a different combination of positive and negative control of expression. By monitoring the single-cell response of bacteria to fluctuating environments, we examine whether each mode of regulation is optimized for specific fluctuation regimes in order to gain better insight into the mechanisms driving bacterial adaptations to extracellular stress.

Relevant publication: PLoS genetics 10 (9), e1004556 [pdf], Biophysical Journal 111 (4), 883–891 [pdf]