Riding out of the storm: How to deal with the complexity of grid and cloud management

Over the last decade, Grid computing paved the way for a new level of large scale distributed systems. This infrastructure made it possible to securely and reliably take advantage of widely separated computational resources that are part of several different organizations. Resources can be incorporated to the Grid, building a theoretical virtual supercomputer. In time, cloud computing emerged as a new type of large scale distributed system, inheriting and expanding the expertise and knowledge that have been obtained so far. Some of the main characteristics of Grids naturally evolved into clouds, others were modified and adapted and others were simply discarded or postponed. Regardless of these technical specifics, both Grids and clouds together can be considered as one of the most important advances in large scale distributed computing of the past ten years; however, this step in distributed computing has came along with a completely new level of complexity. Grid and cloud management mechanisms play a key role, and correct analysis and understanding of the system behavior are needed. Large scale distributed systems must be able to self-manage, incorporating autonomic features capable of controlling and optimizing all resources and services. Traditional distributed computing management mechanisms analyze each resource separately and adjust specific parameters of each one of them. When trying to adapt the same procedures to Grid and cloud computing, the vast complexity of these systems can make this task extremely complicated. But large scale distributed systems complexity could only be a matter of perspective. It could be possible to understand the Grid or cloud behavior as a single entity, instead of a set of resources. This abstraction could provide a different understanding of the system, describing large scale behavior and global events that probably would not be detected analyzing each resource separately. In this work we define a theoretical framework that combines both ideas, multiple resources and single entity, to develop large scale distributed systems management techniques aimed at system performance optimization, increased dependability and Quality of Service (QoS). The resulting synergy could be the key 350 J. Montes et al. to address the most important difficulties of Grid and cloud management

The Influence of Different Stresses on Glomalin Levels in an Arbuscular Mycorrhizal Fungus—Salinity Increases Glomalin Content

Glomalin is a glycoprotein produced by arbuscular mycorrhizal (AM) fungi, and the soil fraction containing glomalin is correlated with soil aggregation. Thus, factors potentially influencing glomalin production could be of relevance for this ecosystem process and for understanding AM fungal physiology. Previous work indicated that glomalin production in AM fungi may be a stress response, or related to suboptimal mycelium growth. We show here that environmental stress can enhance glomalin production in the mycelium of the AM fungus Glomus intraradices. We applied NaCl and glycerol in different intensities to the medium in which the fungus was grown in vitro, causing salinity stress and osmotic stress, respectively. As a third stress type, we simulated grazing on the extraradical hyphae of the fungus by mechanically injuring the mycelium by clipping. NaCl caused a strong increase, while the clipping treatment led to a marginally significant increase in glomalin production. Even though salinity stress includes osmotic stress, we found substantially different responses in glomalin production due to the NaCl and the glycerol treatment, as glycerol addition did not cause any response. Thus, our results indicate that glomalin is involved in inducible stress responses in AM fungi for salinity, and possibly grazing stress

Impaired Cellular Responses to Cytosolic DNA or Infection with Listeria monocytogenes and Vaccinia Virus in the Absence of the Murine LGP2 Protein

Innate immune signaling is crucial for detection of and the initial response to microbial pathogens. Evidence is provided indicating that LGP2, a DEXH box domain protein related to the RNA recognition receptors RIG-I and MDA5, participates in the cellular response to cytosolic double-stranded DNA (dsDNA). Analysis of embryonic fibroblasts and macrophages from mice harboring targeted disruption in the LGP2 gene reveals that LGP2 can act as a positive regulator of type I IFN and anti-microbial gene expression in response to transfected dsDNA. Results indicate that infection of LGP2-deficient mice with an intracellular bacterial pathogen, Listeria monocytogenes, leads to reduced levels of type I IFN and IL12, and allows increased bacterial growth in infected animals, resulting in greater colonization of both spleen and liver. Responses to infection with vaccinia virus, a dsDNA virus, are also suppressed in cells lacking LGP2, reinforcing the ability of LGP2 to act as a positive regulator of antiviral signaling. In vitro mechanistic studies indicate that purified LGP2 protein does not bind DNA but instead mediates these responses indirectly. Data suggest that LGP2 may be acting downstream of the intracellular RNA polymerase III pathway to activate anti-microbial signaling. Together, these findings demonstrate a regulatory role for LGP2 in the response to cytosolic DNA, an intracellular bacterial pathogen, and a DNA virus, and provide a plausible mechanistic hypothesis as the basis for this activity

Systematic identification of functional modules and cis-regulatory elements in Arabidopsis thaliana

<p>Abstract</p> <p>Background</p> <p>Several large-scale gene co-expression networks have been constructed successfully for predicting gene functional modules and cis-regulatory elements in Arabidopsis (<it>Arabidopsis thaliana</it>)<it>.</it> However, these networks are usually constructed and analyzed in an <it>ad hoc</it> manner. In this study, we propose a completely parameter-free and systematic method for constructing gene co-expression networks and predicting functional modules as well as cis-regulatory elements.</p> <p>Results</p> <p>Our novel method consists of an automated network construction algorithm, a parameter-free procedure to predict functional modules, and a strategy for finding known cis-regulatory elements that is suitable for consensus scanning without prior knowledge of the allowed extent of degeneracy of the motif. We apply the method to study a large collection of gene expression microarray data in Arabidopsis. We estimate that our co-expression network has ~94% of accuracy, and has topological properties similar to other biological networks, such as being scale-free and having a high clustering coefficient. Remarkably, among the ~300 predicted modules whose sizes are at least 20, 88% have at least one significantly enriched functions, including a few extremely significant ones (ribosome, <it>p</it> < 1E-300, photosynthetic membrane, <it>p</it> < 1.3E-137, proteasome complex, <it>p</it> < 5.9E-126). In addition, we are able to predict cis-regulatory elements for 66.7% of the modules, and the association between the enriched cis-regulatory elements and the enriched functional terms can often be confirmed by the literature. Overall, our results are much more significant than those reported by several previous studies on similar data sets. Finally, we utilize the co-expression network to dissect the promoters of 19 Arabidopsis genes involved in the metabolism and signaling of the important plant hormone gibberellin, and achieved promising results that reveal interesting insight into the biosynthesis and signaling of gibberellin.</p> <p>Conclusions</p> <p>The results show that our method is highly effective in finding functional modules from real microarray data. Our application on Arabidopsis leads to the discovery of the largest number of annotated Arabidopsis functional modules in the literature. Given the high statistical significance of functional enrichment and the agreement between cis-regulatory and functional annotations, we believe our Arabidopsis gene modules can be used to predict the functions of unknown genes in Arabidopsis, and to understand the regulatory mechanisms of many genes.</p

Type I Interferon Induction Is Detrimental during Infection with the Whipple's Disease Bacterium, Tropheryma whipplei

Macrophages are the first line of defense against pathogens. Upon infection macrophages usually produce high levels of proinflammatory mediators. However, macrophages can undergo an alternate polarization leading to a permissive state. In assessing global macrophage responses to the bacterial agent of Whipple's disease, Tropheryma whipplei, we found that T. whipplei induced M2 macrophage polarization which was compatible with bacterial replication. Surprisingly, this M2 polarization of infected macrophages was associated with apoptosis induction and a functional type I interferon (IFN) response, through IRF3 activation and STAT1 phosphorylation. Using macrophages from mice deficient for the type I IFN receptor, we found that this type I IFN response was required for T. whipplei-induced macrophage apoptosis in a JNK-dependent manner and was associated with the intracellular replication of T. whipplei independently of JNK. This study underscores the role of macrophage polarization in host responses and highlights the detrimental role of type I IFN during T. whipplei infection

Production of IFN-β during Listeria monocytogenes Infection Is Restricted to Monocyte/Macrophage Lineage

The family of type I interferons (IFN), which consists of several IFN-α and one IFN-β, are produced not only after stimulation by viruses, but also after infection with non-viral pathogens. In the course of bacterial infections, these cytokines could be beneficial or detrimental. IFN-β is the primary member of type I IFN that initiates a cascade of IFN-α production. Here we addressed the question which cells are responsible for IFN-β expression after infection with the intracellular pathogen Listeria monocytogenes by using a genetic approach. By means of newly established reporter mice, maximum of IFN-β expression was observed at 24 hours post infection in spleen and, surprisingly, 48 hours post infection in colonized cervical and inguinal lymph nodes. Colonization of lymph nodes was independent of the type I IFN signaling, as well as bacterial dose and strain. Using cell specific reporter function and conditional deletions we could define cells expressing LysM as the major IFN-β producers, with cells formerly defined as Tip-DCs being the highest. Neutrophilic granulocytes, dendritic cells and plasmacytoid dendritic cells did not significantly contribute to type I IFN production

Exon-Level Transcriptome Profiling in Murine Breast Cancer Reveals Splicing Changes Specific to Tumors with Different Metastatic Abilities

In breast cancer patients, tumor metastases at distant sites are the main cause of death. However, the molecular mechanisms of metastasis of breast cancer remain unclear. It is thought that changes occurring at the level of RNA processing contribute to cancer. Alternative splicing (AS) of pre-mRNA, a key post-transcriptional mechanism allowing for the production of distinct proteins from a single gene, affects over 90% of human genes. Such splicing events are responsible for generating mRNAs that encode protein isoforms that can have very different biological properties and functions. A well-studied example is the BCL-X gene, whose two major transcript isoforms produce two proteins having antagonistic functions: the short form (BCL-XS) promotes apoptosis while the long form (BCL-XL) is anti-apoptotic. Moreover, overexpression of BCL-XL has been reported to enhance the metastatic potential of breast tumor cells in patients

Profile of Central and Effector Memory T Cells in the Progression of Chronic Human Chagas Disease

Chagas disease is a parasitic infection caused by protozoan Trypanosoma cruzi that affects approximately 11 million people in Latin America. The involvement of the host's immune response on the development of severe forms of Chagas disease has not been fully elucidated. Studies on the immune response against T. cruzi infection show that the immunoregulatory mechanisms are necessary to prevent the deleterious effect of excessive immune response stimulation and consequently the fatal outcome of the disease. A recall response against parasite antigens observed in in vitro peripheral blood cell culture clearly demonstrates that memory response is generated during infection. Memory T cells are heterogeneous and differ in both the ability to migrate and exert their effector function. This heterogeneity is reflected in the definition of central (TCM) and effector memory (TEM) T cells. Our results suggest that a balance between regulatory and effectors T cells may be important for the progression and development of the disease. Furthermore, the high percentage of central memory CD4+ T cells in indeterminate patients after stimulation suggests that these cells may modulate host's inflammatory response by controlling cell migration to tissues and their effector role during chronic phase of the disease

Codivergence of Mycoviruses with Their Hosts

BACKGROUND: The associations between pathogens and their hosts are complex and can result from any combination of evolutionary events such as codivergence, switching, and duplication of the pathogen. Mycoviruses are RNA viruses which infect fungi and for which natural vectors are so far unknown. Thus, lateral transfer might be improbable and codivergence their dominant mode of evolution. Accordingly, mycoviruses are a suitable target for statistical tests of virus-host codivergence, but inference of mycovirus phylogenies might be difficult because of low sequence similarity even within families. METHODOLOGY: We analyzed here the evolutionary dynamics of all mycovirus families by comparing virus and host phylogenies. Additionally, we assessed the sensitivity of the co-phylogenetic tests to the settings for inferring virus trees from their genome sequences and approximate, taxonomy-based host trees. CONCLUSIONS: While sequence alignment filtering modes affected branch support, the overall results of the co-phylogenetic tests were significantly influenced only by the number of viruses sampled per family. The trees of the two largest families, Partitiviridae and Totiviridae, were significantly more similar to those of their hosts than expected by chance, and most individual host-virus links had a significant positive impact on the global fit, indicating that codivergence is the dominant mode of virus diversification. However, in this regard mycoviruses did not differ from closely related viruses sampled from non-fungus hosts. The remaining virus families were either dominated by other evolutionary modes or lacked an apparent overall pattern. As this negative result might be caused by insufficient taxon sampling, the most parsimonious hypothesis still is that host-parasite evolution is basically the same in all mycovirus families. This is the first study of mycovirus-host codivergence, and the results shed light not only on how mycovirus biology affects their co-phylogenetic relationships, but also on their presumable host range itself