Keynote - Bragg Lecturer: Naama Barkai Weizmann Institute, Israel
How Transcription Factor Locate Their Binding Sites In Large Genomes: A Role For Intrinsically Disordered Regions Cells are constantly "making decisions" - monitoring their environment, modulating their metabolism and 'deciding' whether to divide, differentiate or die. For this, they use biochemical circuits composed of interacting genes and proteins. Advances over the past decades have mapped many of these circuits. Still, can we infer the underlying logic from the detailed circuit structure? Can we deduce the selection forces that shaped these circuits during evolution? What are the principles that govern the design and function of these circuits and how similar or different are they from principles that guide the design of man-made machines? The interplay between variability and robustness is a hallmark of biological computation: Biological systems are inherently noisy, yet control their behavior precisely. Research projects in our lab quantify biological variability and identify its genetic origins, examine how variability is buffered by molecular circuits and investigate whether variability can in fact be employed to improve cellular computation. We encourage a multi-disciplinary approach, combining wet-lab experiments, dynamic-system theory and computational data analysis. This is achieved through fruitful interactions between students with backgrounds in physics, biology, computer science, mathematics and chemistry.
Sticking together: How bacterial collectives use chemical cues to (re)shape themselves Sujit Datta is an Associate Professor and Director of Graduate Studies of Chemical and Biological Engineering at Princeton University. He earned a BA in Mathematics and Physics and an MS in Physics in 2008 from the University of Pennsylvania, and then a PhD in Physics in 2013 from Harvard, where he studied fluid dynamics and instabilities in soft and disordered media with Dave Weitz. His postdoctoral training was in Chemical Engineering at Caltech, where he studied the biophysics of the gut with Rustem Ismagilov.
Datta joined Princeton in 2017, where his lab studies the dynamics, self-organization, and applications of complex, soft (“squishy”), and living systems. Datta’s research has revealed and shed new light on the fascinating behaviors manifested by complex fluids and bacterial populations in complex environments, guiding the development of new approaches to environmental remediation, energy production, agriculture, water security, and biotechnology. He also actively leads outreach efforts in STEM to bring together diverse perspectives and provide access to researchers from traditionally under-represented groups in studies of soft and living systems.
Datta’s scholarship has been recognized by awards from a broad range of different communities, reflecting its multidisciplinary nature, including through the AIChE 35 Under 35 Award, ACS Unilever Award, Camille Dreyfus Teacher-Scholar Award, three awards from the APS (Early Career Award in Biological Physics, Andreas Acrivos Award in Fluid Dynamics, and the Apker Award), the Arthur Metzner of the Society of Rheology, Pew Biomedical Scholar Award, NSF CAREER Award, and multiple commendations for teaching.
It’s getting hot in here The impact of temperature on growth is typically considered only under heat- or cold-shock conditions that elicit specific regulation. Over intermediate temperatures, the growth rate of all cells varies according to the Arrhenius law of thermodynamics; growth rate dynamics during transitions between temperatures remain mostly unstudied. How this behavior arises and what determines temperature sensitivity are largely unknown. Using a device that enables single-cell tracking during switches across a wide range of temperatures (0 °C to 47 °C), we show that many bacteria respond to temperatures upshifts on a characteristic time scale of ~1.6 doublings at the higher temperature, regardless of initial/final temperature or nutrient source. We rule out transcriptional, translational, and membrane reconfiguration as potential mechanisms, and instead discover that an autocatalytic enzyme network incorporating temperature-sensitive Michaelis-Menten kinetics recapitulates all temperature-shift dynamics and successfully predicts the altered temperature responses observed under simple-sugar and low-nutrient growth conditions. These findings suggest that the temperature sensitivity of metabolite flux dictates responses to temperature fluctuations.
Growth Control Across Scales Rita Mateus is a joint group leader at the Max Planck Institute of Molecular Cell Biology and Genetics and the Cluster of Excellence Physics of Life (TUD) in Dresden, Germany. She has always been interested in understanding how cells coordinate precise growth and form of tissues, allowing them to become fully functional. To this end, Rita did her PhD in Prof. Antonio Jacinto's laboratory in Portugal, where she investigated how, upon injury, the zebrafish caudal fin precisely regenerates its shape and size, over and over, error-free. During her postdoc in the group of Prof. Marcos Gonzalez-Gaitán in Switzerland, Rita turned to development to investigate how morphogens control organ growth, using the zebrafish pectoral fin as a model. In parallel, she became more and more interested in understanding size and shape at the subcellular level, in particular to try to understand the physics and cell biology underlying structural colors, that require the formation of specific organelles with particular morphologies. Now, in her laboratory, Rita is pursuing these two research avenues to explore the biophysical properties involved in controlling growth across these very different length scales.
Optimization and historical contingency in protein sequences In biological evolution, populations are pushed to optimality, but may also be shaped by the contingency of their evolutionary history. The recent major growth of sequence data gives us access to the outcomes of molecular evolution. In this exciting context, my group studies the importance of optimization and contingency at the molecular scale and at the scale of microorganism populations. We perform physics-inspired mathematical modeling, numerical simulations and data analysis. To analyze protein sequence data, we employ both statistical physics-based inference methods and deep learning methods.
Pattern formation by living droplets The primary interest of my laboratory is to understand how cells make decisions about their identity during development. To allow a deeper understanding of cell decision making, and the generation of more useful conceptual frameworks, we have developed and implemented a range of imaging technologies- with the view that to understand the decision of cell requires monitoring a broad range of regulatory features of single cells, as they differentiate. In particular, we use imaging to directly observe the bursts of activity of individual genes in living cells in parallel with direct measurements of different signalling inputs.
Peter Swain University of Edinburgh, UK - Cancelled -
