Alexandre Dawid

DNA mechanics as a tool to probe helicase and translocase activity

Helicases and translocases are proteins that use the energy derived from ATP hydrolysis to move along or pump nucleic acid substrates. Single molecule manipulation has proved to be a powerful tool to investigate the mechanochemistry of these motors. Here we first describe the basic mechanical properties of DNA unraveled by single molecule manipulation techniques. Then we demonstrate how the knowledge of these properties has been used to design single molecule assays to address the enzymatic mechanisms of different translocases. We report on four single molecule manipulation systems addressing the mechanism of different helicases using specifically designed DNA substrates: UvrD enzyme activity detection on a stretched nicked DNA molecule, HCV NS3 helicase unwinding of a RNA hairpin under tension, the observation of RecBCD helicase/nuclease forward and backward motion, and T7 gp4 helicase mediated opening of a synthetic DNA replication fork. We then discuss experiments on two dsDNA translocases: the RuvAB motor studied on its natural substrate, the Holliday junction, and the chromosome-segregation motor FtsK, showing its unusual coupling to DNA supercoiling.

Quantitative Prediction of the Phase Diagram of DNA-Functionalized Nanosized Colloids

We present a coarse-grained model of DNA-functionalized colloids that is computationally tractable. Importantly, the model parameters are solely based on experimental data. Using this highly simplified model, we can predict the phase behavior of DNA-functionalized nanocolloids without assuming pairwise additivity of the intercolloidal interactions. Our simulations show that, for nanocolloids, the assumption of pairwise additivity leads to substantial errors in the estimate of the free energy of the crystal phase. We compare our results with available experimental data and find that the simulations predict the correct structure of the solid phase and yield a very good estimate of the melting temperature. Current experimental estimates for the contour length and persistence length of single-stranded (ss) DNA sequences are subject to relatively large uncertainties. Using the best available estimates, we obtain predictions for the crystal lattice constants that are off by a few percent: this indicates that more accurate experimental data on ssDNA are needed to exploit the full power of our coarse-grained approach.

Multiple peaks and reciprocal sign epistasis in an empirically determined genotype-phenotype landscape

Insight into the ruggedness of adaptive landscapes is central to understanding the mechanisms and constraints that shape the course of evolution. While empirical data on adaptive landscapes remain scarce, a handful of recent investigations have revealed genotype-phenotype and genotype-fitness landscapes that appeared smooth and single peaked. Here, we used existing in vivo measurements on lac repressor and operator mutants in Escherichia coli to reconstruct the genotype-phenotype map that details the repression value of this regulatory system as a function of two key repressor residues and four key operator base pairs. We found that this landscape is multipeaked, harboring in total 19 distinct optima. Analysis showed that all direct evolutionary pathways between peaks involve significant dips in the repression value. Consistent with earlier predictions, we found reciprocal sign epistatic interactions at the repression minimum of the most favorable paths between two peaks. These results suggest that the occurrence of multiple peaks and reciprocal epistatic interactions may be a general feature in coevolving systems like the repressor-operator pair studied here.

A Nanostructure Made of a Bacterial Noncoding RNA

Natural RNAs, unlike many proteins, have never been reported to form extended nanostructures, despite their wide variety of cellular functions. This is all the more striking, as synthetic DNA and RNA forming large nanostructures have long been successfully designed. Here, we show that DsrA, a 87-nt noncoding RNA of Escherichia coli, self-assembles into a hierarchy of nanostructures through antisense interactions of three contiguous self-complementary regions. Yet, the extended nanostructures, observed using atomic force microscopy (AFM) and fluorescence microscopy, are easily disrupted into >100 nm long helical bundles of DsrA filaments, including hundreds of DsrA monomers, and are surprisingly resistant to heat and urea denaturation. Molecular modeling demonstrates that this structural switch of DsrA nanostructures into filament bundles results from the relaxation of stored torsional constraints and suggests possible implications for DsrA regulatory function.

Breaking evolutionary constraint with a tradeoff ratchet

Significance Suboptimal fitness peaks are generally recognized as causing evolutionary stasis. Here, we show that these constraints can be overcome in an adaptive manner by reconstructing mutational trajectories for a transcription factor and its DNA binding site in variable environments. Cross-environmental tradeoffs, typically associated with evolutionary limitations, are an essential enabling component of this evolutionary mechanism. Our results underscore the importance of characterizing environmental dependencies when studying genetic interactions and provide the clearest indication so far that environmental variability can accelerate evolution hampered by stasis in constant conditions. Given that environmental variations and tradeoffs are ubiquitous, this evolutionary mechanism may be relevant to a wide range of genetically constrained phenotypes and major evolutionary transitions. Epistatic interactions can frustrate and shape evolutionary change. Indeed, phenotypes may fail to evolve when essential mutations are only accessible through positive selection if they are fixed simultaneously. How environmental variability affects such constraints is poorly understood. Here, we studied genetic constraints in fixed and fluctuating environments using the Escherichia coli lac operon as a model system for genotype–environment interactions. We found that, in different fixed environments, all trajectories that were reconstructed by applying point mutations within the transcription factor–operator interface became trapped at suboptima, where no additional improvements were possible. Paradoxically, repeated switching between these same environments allows unconstrained adaptation by continuous improvements. This evolutionary mode is explained by pervasive cross-environmental tradeoffs that reposition the peaks in such a way that trapped genotypes can repeatedly climb ascending slopes and hence, escape adaptive stasis. Using a Markov approach, we developed a mathematical framework to quantify the landscape-crossing rates and show that this ratchet-like adaptive mechanism is robust in a wide spectrum of fluctuating environments. Overall, this study shows that genetic constraints can be overcome by environmental change and that cross-environmental tradeoffs do not necessarily impede but also, can facilitate adaptive evolution. Because tradeoffs and environmental variability are ubiquitous in nature, we speculate this evolutionary mode to be of general relevance.