Greatwall and Polo-like Kinase 1 Coordinate to Promote Checkpoint Recovery

Checkpoint recovery upon completion of DNA repair allows the cell to return to normal cell cycle progression and is thus a crucial process that determines cell fate after DNA damage. We previously studied this process in Xenopus egg extracts and established Greatwall (Gwl) as an important regulator. Here we show that preactivated Gwl kinase can promote checkpoint recovery independently of cyclin-dependent kinase 1 (Cdk1) or Plx1 (Xenopus polo-like kinase 1), whereas depletion of Gwl from extracts exhibits no synergy with that of Plx1 in delaying checkpoint recovery, suggesting a distinct but related relationship between Gwl and Plx1. In further revealing their functional relationship, we found mutual dependence for activation of Gwl and Plx1 during checkpoint recovery, as well as their direct association. We characterized the protein association in detail and recapitulated it in vitro with purified proteins, which suggests direct interaction. Interestingly, Gwl interaction with Plx1 and its phosphorylation by Plx1 both increase at the stage of checkpoint recovery. More importantly, Plx1-mediated phosphorylation renders Gwl more efficient in promoting checkpoint recovery, suggesting a functional involvement of such regulation in the recovery process. Finally, we report an indirect regulatory mechanism involving Aurora A that may account for Gwl-dependent regulation of Plx1 during checkpoint recovery. Our results thus reveal novel mechanisms underlying the involvement of Gwl in checkpoint recovery, in particular, its functional relationship with Plx1, a well characterized regulator of checkpoint recovery. Coordinated interplays between Plx1 and Gwl are required for reactivation of these kinases from the G2/M DNA damage checkpoint and efficient checkpoint recovery

Fanconi anemia cells with unrepaired DNA damage activate components of the checkpoint recovery process

International audienceBACKGROUND:The FA/BRCA pathway repairs DNA interstrand crosslinks. Mutations in this pathway cause Fanconi anemia (FA), a chromosome instability syndrome with bone marrow failure and cancer predisposition. Upon DNA damage, normal and FA cells inhibit the cell cycle progression, until the G2/M checkpoint is turned off by the checkpoint recovery, which becomes activated when the DNA damage has been repaired. Interestingly, highly damaged FA cells seem to override the G2/M checkpoint. In this study we explored with a Boolean network model and key experiments whether checkpoint recovery activation occurs in FA cells with extensive unrepaired DNA damage.METHODS:We performed synchronous/asynchronous simulations of the FA/BRCA pathway Boolean network model. FA-A and normal lymphoblastoid cell lines were used to study checkpoint and checkpoint recovery activation after DNA damage induction. The experimental approach included flow cytometry cell cycle analysis, cell division tracking, chromosome aberration analysis and gene expression analysis through qRT-PCR and western blot.RESULTS:Computational simulations suggested that in FA mutants checkpoint recovery activity inhibits the checkpoint components despite unrepaired DNA damage, a behavior that we did not observed in wild-type simulations. This result implies that FA cells would eventually reenter the cell cycle after a DNA damage induced G2/M checkpoint arrest, but before the damage has been fixed. We observed that FA-A cells activate the G2/M checkpoint and arrest in G2 phase, but eventually reach mitosis and divide with unrepaired DNA damage, thus resolving the initial checkpoint arrest. Based on our model result we look for ectopic activity of checkpoint recovery components. We found that checkpoint recovery components, such as PLK1, are expressed to a similar extent as normal undamaged cells do, even though FA-A cells harbor highly damaged DNA.CONCLUSIONS:Our results show that FA cells, despite extensive DNA damage, do not loss the capacity to express the transcriptional and protein components of checkpoint recovery that might eventually allow their division with unrepaired DNA damage. This might allow cell survival but increases the genomic instability inherent to FA individuals and promotes cancer

CRAFT: A library for easier application-level Checkpoint/Restart and Automatic Fault Tolerance

In order to efficiently use the future generations of supercomputers, fault tolerance and power consumption are two of the prime challenges anticipated by the High Performance Computing (HPC) community. Checkpoint/Restart (CR) has been and still is the most widely used technique to deal with hard failures. Application-level CR is the most effective CR technique in terms of overhead efficiency but it takes a lot of implementation effort. This work presents the implementation of our C++ based library CRAFT (Checkpoint-Restart and Automatic Fault Tolerance), which serves two purposes. First, it provides an extendable library that significantly eases the implementation of application-level checkpointing. The most basic and frequently used checkpoint data types are already part of CRAFT and can be directly used out of the box. The library can be easily extended to add more data types. As means of overhead reduction, the library offers a build-in asynchronous checkpointing mechanism and also supports the Scalable Checkpoint/Restart (SCR) library for node level checkpointing. Second, CRAFT provides an easier interface for User-Level Failure Mitigation (ULFM) based dynamic process recovery, which significantly reduces the complexity and effort of failure detection and communication recovery mechanism. By utilizing both functionalities together, applications can write application-level checkpoints and recover dynamically from process failures with very limited programming effort. This work presents the design and use of our library in detail. The associated overheads are thoroughly analyzed using several benchmarks

MATHEMATICAL MODELING REVEALS THAT G2/M CHECKPOINT OVERRIDE

Cell cycle checkpoints determine whether cells meet requirements to progress through the next stage. In response to DNA damage, how cells activate checkpoints have been well studied, but little is known about checkpoint deactivation (recovery), which directly impacts on cell fate. In tumor cells, the signaling network has been rewired due to epigenetic and genetic alterations, which result in resistance to the cell cycle control, and thus resistance to chemotherapy or radiation therapy. Therefore, it is critical to identify molecules required for checkpoint recovery or adaptation after DNA damage. To achieve this goal, we performed a multidisciplinary study combining reverse phase protein array (RPPA) data, molecular biology and mathematical modeling to systematically identify molecules required for DNA damage checkpoint recovery. The mTOR complex 1 (mTORC1) plays an essential role to regulate mitotic entry after irradiation. Inhibition of the mTOR pathway delayed G2/M checkpoint recovery, while TSC2-null cells with hyperactivity of mTORC1 exhibited the opposite results. Furthermore, our mechanistic study revealed that mTOR signaling pathway controls a transcriptional program of mitotic entry through regulating histone lysine demethylase KDM4B, which is required for the epigenetic regulation of key mitosis-related genes including CCNB1 and PLK1. Given accelerated G2/M checkpoint recovery in TSC2-null cells with mTORC1 hyperactivity, we postulated that further abrogation of the G2/M checkpoint may facilitate mitotic catastrophe and selectively kill cells. As we expected, TSC2-null cells were more sensitive to the WEE1 inhibitor, a negative regulator of mitotic entry, compared to wild-type cells. In summary, we reported a novel mechanism of the mTORC1 signaling in regulating a transcriptional program required for G2/M checkpoint recovery after DNA damage. This mechanism provided a therapeutic strategy for TSC patients with mTORC1 hyperactivity using the WEE1 inhibitor, which has a potential to be translated into clinical trials

Improving Performance of Iterative Methods by Lossy Checkponting

Iterative methods are commonly used approaches to solve large, sparse linear systems, which are fundamental operations for many modern scientific simulations. When the large-scale iterative methods are running with a large number of ranks in parallel, they have to checkpoint the dynamic variables periodically in case of unavoidable fail-stop errors, requiring fast I/O systems and large storage space. To this end, significantly reducing the checkpointing overhead is critical to improving the overall performance of iterative methods. Our contribution is fourfold. (1) We propose a novel lossy checkpointing scheme that can significantly improve the checkpointing performance of iterative methods by leveraging lossy compressors. (2) We formulate a lossy checkpointing performance model and derive theoretically an upper bound for the extra number of iterations caused by the distortion of data in lossy checkpoints, in order to guarantee the performance improvement under the lossy checkpointing scheme. (3) We analyze the impact of lossy checkpointing (i.e., extra number of iterations caused by lossy checkpointing files) for multiple types of iterative methods. (4)We evaluate the lossy checkpointing scheme with optimal checkpointing intervals on a high-performance computing environment with 2,048 cores, using a well-known scientific computation package PETSc and a state-of-the-art checkpoint/restart toolkit. Experiments show that our optimized lossy checkpointing scheme can significantly reduce the fault tolerance overhead for iterative methods by 23%~70% compared with traditional checkpointing and 20%~58% compared with lossless-compressed checkpointing, in the presence of system failures.Comment: 14 pages, 10 figures, HPDC'1

Implementing Performance Competitive Logical Recovery

New hardware platforms, e.g. cloud, multi-core, etc., have led to a reconsideration of database system architecture. Our Deuteronomy project separates transactional functionality from data management functionality, enabling a flexible response to exploiting new platforms. This separation requires, however, that recovery is described logically. In this paper, we extend current recovery methods to work in this logical setting. While this is straightforward in principle, performance is an issue. We show how ARIES style recovery optimizations can work for logical recovery where page information is not captured on the log. In side-by-side performance experiments using a common log, we compare logical recovery with a state-of-the art ARIES style recovery implementation and show that logical redo performance can be competitive.Comment: VLDB201