Seminar Colour Guide:              
EMBL Distinguished Visitor Lecture
Thursday, 21 November 2019, 11:00Add to calendarThe bacterial pathogen Listeria monocytogenes: from classical cell biology to genomics and microbiotologyPascale Cossart, Pasteur Institute, FranceHost: Nassos TypasLarge Operon, EMBL Heidelberg
External Faculty Speaker
Thursday, 21 November 2019, 15:00Add to calendarMUSICAL live cell friendly computational nanoscopy Krishna Agarwal, Artic University of Norway, Tromsø, NorwayHost: Rainer PepperkokSmall Operon, EMBL Heidelberg
Abstract: Single-molecule localization techniques are restricted by long acquisition and computational times, or the need of special fluorophores or biologically toxic photochemical environments. Here we propose a statistical super-resolution technique of wide-field fluorescence microscopy we call the multiple signal classification algorithm which has several advantages. It provides resolution down to at least 50 nm, requires fewer frames and lower excitation power and works even at high fluorophore concentrations. Further, it works with any fluorophore that exhibits blinking on the timescale of the recording. The multiple signal classification algorithm shows comparable or better performance in comparison with single-molecule localization techniques and four contemporary statistical super-resolution methods for experiments of in vitro actin filaments and other independently acquired experimental data sets. We also demonstrate super-resolution at timescales of 245 ms (using 49 frames acquired at 200 frames per second) in samples of live-cell microtubules and live-cell actin filaments imaged without imaging buffers.Tags: Cell Biology, Imaging and Image Analysis, Biophysics, Structural Biology
External Faculty Speaker
Tuesday, 26 November 2019, 11:00Add to calendarCryptic variation and evolvability in a simple molecular systemAndreas Wagner, Dept. of Evolutionary Biology, & Environmental Studies, University of Zurich, SwitzerlandHost: Justin CrockerSmall Operon, EMBL Heidelberg
Abstract: Cryptic variation is genetic variation that does not normally contribute to phenotypic variation, but that can bring forth such phenotypic variation after environmental change or genetic perturbation. This phenotypic variation can facilitate adaptive evolution through mechanisms that are still poorly understood. To identify these mechanisms, we used directed evolution to accumulate such variation in populations of yellow fluorescent proteins, and subsequently evolved these proteins towards the new phenotype of green fluorescence. Populations with cryptic variation evolved to a greater intensity of green fluorescence, and did so more rapidly than populations without cryptic variation. High-throughput sequencing and mutant engineering showed that different populations with cryptic variation evolved adaptive genotypes that are both more diverse and have higher fluorescence than populations without cryptic variation, which converge on similar genotypes. Populations with cryptic variation accumulated neutral or deleterious mutations that help traverse unfavorable evolutionary paths by breaking the constraints that epistasis imposes on the order in which adaptive mutations arise. In doing so, cryptic variation opens paths to new and highly adaptive genotypes, creates historical contingency, and reduces the predictability of evolution by allowing different replicate populations to climb different adaptive peaks. By opening pathways to new peaks, cryptic variation also helps explore otherwise inaccessible regions of an adaptive landscape.