The ATP-dependent molecular chaperone Hsp90 is required for the activation of a variety of client proteins involved in various cellular processes. Despite the abundance of known client proteins, functions of Hsp90 in the organismal context are not fully explored. In Caenorhabditis elegans, Hsp90 (DAF-21) has been implicated in the regulation of the stress-resistant dauer state, in chemosensing and in gonad formation. In a C. elegans strain carrying a DAF-21 mutation with a lower ATP turnover, we observed motility defects. Similarly, a reduction of DAF-21 levels in wild type nematodes leads to reduced motility and induction of the muscular stress response. Furthermore, aggregates of the myosin MYO-3 are visible in muscle cells, if DAF-21 is depleted, implying a role of Hsp90 in the maintenance of muscle cell functionality. Similar defects can also be observed upon knockdown of the Hsp90-cochaperone UNC-45. In life nematodes YFP-DAF-21 localizes to the I-band and the M-line of the muscular ultrastructure, but the protein is not stably attached there. The Hsp90-cofactor UNC-45-CFP contrarily can be found in all bands of the nematode muscle ultrastructure and stably associates with the UNC-54 containing A-band. Thus, despite the physical interaction between DAF-21 and UNC-45, apparently the two proteins are not always localized to the same muscular structures. While UNC-45 can stably bind to myofilaments in the muscular ultrastructure, Hsp90 (DAF-21) appears to participate in the maintenance of muscle structures as a transiently associated diffusible factor.

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Abstract. Proving programs terminating is a fundamental computer science challenge. Recent research has produced powerful tools that can check a wide range of programs for termination. The analog for probabilistic programs, namely termination with probability one ("almostsure termination"), is an equally important property for randomized algorithms and probabilistic protocols. We suggest a novel algorithm for proving almost-sure termination of probabilistic programs. Our algorithm exploits the power of state-of-the-art model checkers and termination provers for nonprobabilistic programs: it calls such tools within a refinement loop and thereby iteratively constructs a "terminating pattern", which is a set of terminating runs with probability one. We report on various case studies illustrating the effectiveness of our algorithm. As a further application, our algorithm can improve lower bounds on reachability probabilities.