Future Seminars
Seminar Colour Guide:
| EMBL Distinguished Visitor Lecture | |
| External Faculty Speaker | Thursday, 21 November 2019, 15:00MUSICAL 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 50ânm, 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 245âms (using 49 frames acquired at 200 frames per second) in samples of live-cell microtubules and live-cell actin filaments imaged without imaging buffers. |
| External Faculty Speaker | Tuesday, 26 November 2019, 11:00Cryptic 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. |