Interest and Focus
Traditionally, biological questions have been investigated with qualitative techniques that allow for interpretation classically in the context of evolution. This qualitative approach, however, struggles to adequately describe the dynamic nature of most of the essential biological processes upon which evolution is acting. Recent advances in molecular biology, optical microscopy, nanoscopic physics and computer science have opened up new avenues for interpreting biological phenomena, combining high-precision measurement of biological processes with theoretical predictions and models that are bound by physical principles and formulated in mathematical language. This allows for models to be numerically tested and validated by experiments and, conversely, for experiments to be designed and guided by theoretical models. My laboratory uses such an approach to understand a biological system holistically, within a framework of fundamental physical principles that dictate and constrain biological phenomena.
Methods and Models
Research in the lab is highly interdisciplinary. The interests and expertise of the lab's members range from physics to biology to computer science to engineering; we use a combination of computational and experimental approaches. We build microscopes and microfluidic devices to measure the concentrations dynamics of proteins and signaling molecules; we use tools from molecular biology and genetics to manipulate the organisms we study; and we use image analysis and modeling to analyze our data. Researchers are encouraged to move freely between the different disciplines and to learn a variety of techniques according to their specific needs and interests. We primarily address questions concerning the development of fruit fly embryos and emergent collective behavior via cell signaling in amoeba populations, but we are open to new ideas and collaborations addressing questions in other model systems.
Specific example research projects
Signaling and emergent collective behavior in cell populations
Cells often communicate via concentration oscillations of small molecules, such as ions in neurons or cAMP in stressed (starved) cells of the social amoeba Dictyostelium. However, the "code'' or the language that these cells use to change their behavior is largely unknown. Optical concentration measurements of the relevant oscillating constituents will be used to measure the spatiotemporal communication dynamics among a few Dictyostelium cells. Simultaneously, a combination of electro-physiological and optical measurements will be used to measure similar dynamics in a developing network of cultured neurons. In both cases, communication among cells via oscillations affects the resulting behavior, i.e., aggregation for amoebae, network rewiring for neurons. The goal is to seek common strategies and mechanisms these cells use to change their behavior to form an organism, ultimately revealing unifying principles of communication in different systems.
Spatio-temporal patterning and differentiation during early development
In utero imaging of early mammalian development
Beyond D'Arcy Thompson: Future challenges for quantitative biology. Mech Dev. 2017 ;. .
Only accessible information is useful: insights from gradient-mediated patterning. R Soc Open Sci. 2015 ;2(11):150486. .
Modeling oscillations and spiral waves in Dictyostelium populations. Phys Rev E Stat Nonlin Soft Matter Phys. 2015 ;91(6):062711. .
From intracellular signaling to population oscillations: bridging size- and time-scales in collective behavior. Mol Syst Biol. 2015 ;11(1):779. .
Positional information, positional error, and readout precision in morphogenesis: a mathematical framework. Genetics. 2015 ;199(1):39-59. .
Dynamic regulation of eve stripe 2 expression reveals transcriptional bursts in living Drosophila embryos. Proc Natl Acad Sci U S A. 2014 ;111(29):10598-603. .