Asymmetric division of clonal muscle stem cells coordinates muscle regeneration in vivo.

Skeletal muscle is an example of a tissue that deploys a self-renewing stem cell, the satellite cell, to effect regeneration. Recent in vitro studies have highlighted a role for asymmetric divisions in renewing rare "immortal" stem cells and generating a clonal population of differentiation-competent myoblasts. However, this model currently lacks in vivo validation. We define a zebrafish muscle stem cell population analogous to the mammalian satellite cell and image the entire process of muscle regeneration from injury to fiber replacement in vivo. This analysis reveals complex interactions between satellite cells and both injured and uninjured fibers and provides in vivo evidence for the asymmetric division of satellite cells driving both self-renewal and regeneration via a clonally restricted progenitor pool.

MrGrid: a portable grid based molecular replacement pipeline.

BACKGROUND: The crystallographic determination of protein structures can be computationally demanding and for difficult cases can benefit from user-friendly interfaces to high-performance computing resources. Molecular replacement (MR) is a popular protein crystallographic technique that exploits the structural similarity between proteins that share some sequence similarity. But the need to trial permutations of search models, space group symmetries and other parameters makes MR time- and labour-intensive. However, MR calculations are embarrassingly parallel and thus ideally suited to distributed computing. In order to address this problem we have developed MrGrid, web-based software that allows multiple MR calculations to be executed across a grid of networked computers, allowing high-throughput MR. METHODOLOGY/PRINCIPAL FINDINGS: MrGrid is a portable web based application written in Java/JSP and Ruby, and taking advantage of Apple Xgrid technology. Designed to interface with a user defined Xgrid resource the package manages the distribution of multiple MR runs to the available nodes on the Xgrid. We evaluated MrGrid using 10 different protein test cases on a network of 13 computers, and achieved an average speed up factor of 5.69. CONCLUSIONS: MrGrid enables the user to retrieve and manage the results of tens to hundreds of MR calculations quickly and via a single web interface, as well as broadening the range of strategies that can be attempted. This high-throughput approach allows parameter sweeps to be performed in parallel, improving the chances of MR success.