The emerging field of compartmentalized in vitro evolution, where selection is carried out by differential reproduction in each compartment, is a promising new approach to protein engineering. From practical point of view, it is important to know the effect of the increase in the average number of genotype bearing agents per compartment. This effect is also interesting on its own in the context of primordial evolution in the hypothetical RNA world. The question is important as genotypes with different phenotypes in the same compartment share their fitness (the number of produced copies) rendering the selection frequency-dependent. I will show the results of a theoretical investigation of this problem in the context of selection dynamics for a simple model with an infinite population that is periodically redistributed among infinite number of identical compartments, inside which all molecules are copied without distinction with the success rate as a function of the total genomic composition…

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In this talk I will present some of the current knowledge regarding the cnidarian endogenous biological clock.  During the last few years our team has examined the evidence from behavioral, physiological, molecular, and evolutionary perspectives regarding the role of the clock machinery in some key cnidarians such as symbiotic corals, Aiptasia and Nematosella vectensis, an emerging model organism.  Our research is mainly focused on symbiotic corals. They are an interesting model to study the complexities and evolution of the metazoan biological clock.   A deeper understanding of this complex issue can help explain coral mass spawning, and how symbiotic organisms measure time and synchronize themselves to their environmental conditions.  Our main goal is understanding how two pacemakers, the host and the symbiont, function together in one organism and what is the cross-talk in this holobiont system. 

According to the endosymbiont theory of organelle evolution, a β cyanobacterium that was engulfed by a unicellular protist (primary endosymbiosis) evolved into the chloroplasts that are currently present in algae and plants. This successful evolutionary event was thought to have occurred once (monophyletic), about a billion years ago. The long time span separating the initial acquisition of the endosymbiont by its host and its current state as a photosynthetic organelle makes it difficult to reconstruct the evolutionary history of primary plastids. However, recently it was shown that the thecate protist Paulinella chromatophora has a photosynthetic organelle called a chromatophore that was acquired approximately 100 million years ago. Analyses of this organelle are providing us with the opportunity to deduce events that occur during early stages in organellogenesis. Overall, our studies have demonstrated that the chromatophore is a bona fide photosynthetic organelle with a reduced genome size relative to the initial endosymbiont, and it contains numerous proteins…

The spatial organization of chromosomes in eukaryotic cell nuclei has important implications for gene expression and genome stability, but has not been charted in detail and its underlying principles remain poorly known. Our lab develops imaging methods and computational models to better understand how chromatin fibers are organized and move in 3D. In this talk, I will review the methods that we developed over the years to map chromosome architecture in yeast and understand its mechanistic basis. In particular, I will show how a simple polymer model can recapitulate a host of experimental observations, and how this model can be used to infer key properties of the chromatin fiber. I will also present collaborative work addressing how chromosome architecture constrains DNA repair by homologous recombination, and how DNA damage increases chromatin mobility. Finally, I will briefly discuss an ongoing project on high-resolution imaging and modeling of human chromosomes.

Proteins are the workhorses of the cell and, over billions of years, they have evolved an amazing plethora of extremely diverse and versatile structures with equally diverse functions.Therefore, protein evolution echoes the evolution of all forms of life.While it was previously assumed that all proteins result from old ones and that evolutionary emergence of new proteins and transitions between existing ones are rare or even impossible, recent advances in comparative genomics have repeatedly called some 10%-30% of all genes without any detectable similarity to existing proteins.Even after careful scrutiny, some of those "orphan" genes contain protein coding reading frames with detectable transcription and translation but lack a homolog at the DNA level in outgroups.Accordingly, some proteins seem to have emerged from previously non-coding 'dark genomic matter'.Computational studies indicate that these 'de novo' proteins are disordered, fast evolving, weakly expressed and rapidly assuming novel and physiologically important functions.They are therefore interesting to understand…

The field of Artificial Intelligence has made significant progress over the past 5 years by making use of Deep Neural Networks. The ability of Deep Neural Networks to carry out complex mappings in high dimensional spaces makes them extremely interesting for biological applications, e.g. for relating genotypes to (molecular) phenotypes. This talk gives an easy to understand introduction into Deep Learning concepts that are interesting for Life Sciences. State of the art results are presented by using Deep Neural networks for predicting DNA binding motifs and RNA secondary structures.