Homologous Recombination under the Single-Molecule Fluorescence Microscope

Homologous recombination (HR) is a complex biological process and is central to meiosis and for repair of DNA double-strand breaks. Although the HR process has been the subject of intensive study for more than three decades, the complex protein–protein and protein–DNA interactions during HR present a significant challenge for determining the molecular mechanism(s) of the process. This knowledge gap is largely because of the dynamic interactions between HR proteins and DNA which is difficult to capture by routine biochemical or structural biology methods. In recent years, single-molecule fluorescence microscopy has been a popular method in the field of HR to visualize these complex and dynamic interactions at high spatiotemporal resolution, revealing mechanistic insights of the process. In this review, we describe recent efforts that employ single-molecule fluorescence microscopy to investigate protein–protein and protein–DNA interactions operating on three key DNA-substrates: single-stranded DNA (ssDNA), double-stranded DNA (dsDNA), and four-way DNA called Holliday junction (HJ). We also outline the technological advances and several key insights revealed by these studies in terms of protein assembly on these DNA substrates and highlight the foreseeable promise of single-molecule fluorescence microscopy in advancing our understanding of homologous recombination

Sampling-based optimal kinodynamic planning with motion primitives

This paper proposes a novel sampling-based motion planner, which integrates in RRT* (Rapidly exploring Random Tree star) a database of pre-computed motion primitives to alleviate its computational load and allow for motion planning in a dynamic or partially known environment. The database is built by considering a set of initial and final state pairs in some grid space, and determining for each pair an optimal trajectory that is compatible with the system dynamics and constraints, while minimizing a cost. Nodes are progressively added to the tree {of feasible trajectories in the RRT* by extracting at random a sample in the gridded state space and selecting the best obstacle-free motion primitive in the database that joins it to an existing node. The tree is rewired if some nodes can be reached from the new sampled state through an obstacle-free motion primitive with lower cost. The computationally more intensive part of motion planning is thus moved to the preliminary offline phase of the database construction at the price of some performance degradation due to gridding. Grid resolution can be tuned so as to compromise between (sub)optimality and size of the database. The planner is shown to be asymptotically optimal as the grid resolution goes to zero and the number of sampled states grows to infinity