Intergenerational Effect of Early Life Exposure to Permethrin: Changes in Global DNA Methylation and in Nurr1 Gene Expression.

Environmental exposure to pesticides during the early stages of development represents an important risk factor for the onset of neurodegenerative diseases in adult age. Neonatal exposure to Permethrin (PERM), a member of the family of synthetic pyrethroids, can induce a Parkinson-like disease and cause some alterations in striatum of rats, involving both genetic and epigenetic pathways. Through gene expression analysis and global DNA methylation assessment in both PERM-treated parents and their untreated offspring, we investigated on the prospective intergenerational effect of this pesticide. Thirty-three percent of progeny presents the same Nurr1 alteration as rats exposed to permethrin in early life. A decrease in global genome-wide DNA methylation was measured in mothers exposed in early life to permethrin as well as in their offspring, whereas untreated rats have a hypermethylated genomic DNA. Further studies are however needed to elucidate the molecular mechanisms, but, despite this, an intergenerational PERM-induced damage on progenies has been identified for the first time.

Blurring contact maps of thousands of proteins: what we can learn by reconstructing 3D structure.

BACKGROUND: The present knowledge of protein structures at atomic level derives from some 60,000 molecules. Yet the exponential ever growing set of hypothetical protein sequences comprises some 10 million chains and this makes the problem of protein structure prediction one of the challenging goals of bioinformatics. In this context, the protein representation with contact maps is an intermediate step of fold recognition and constitutes the input of contact map predictors. However contact map representations require fast and reliable methods to reconstruct the specific folding of the protein backbone. METHODS: In this paper, by adopting a GRID technology, our algorithm for 3D reconstruction FT-COMAR is benchmarked on a huge set of non redundant proteins (1716) taking random noise into consideration and this makes our computation the largest ever performed for the task at hand. RESULTS: We can observe the effects of introducing random noise on 3D reconstruction and derive some considerations useful for future implementations. The dimension of the protein set allows also statistical considerations after grouping per SCOP structural classes. CONCLUSIONS: All together our data indicate that the quality of 3D reconstruction is unaffected by deleting up to an average 75% of the real contacts while only few percentage of randomly generated contacts in place of non-contacts are sufficient to hamper 3D reconstruction.

A protein structure prediction service in the ProGenGrid system.

This paper describes a protein tertiary structure prediction service implemented in a Grid Environment. The service has been used for predicting the dicarboxylate carrier (DIC) of Saccharomyces cerevisiae by using the homology modelling approach. The visualization of the predicted model is made possible by using an interactive virtual reality environment based on X3D and Ajax3d technologies.

A grid-enabled protein secondary structure predictor.

We present an integrated Grid system for the prediction of protein secondary structures, based on the frequent automatic update of proteins in the training set. The predictor model is based on a feed-forward multilayer perceptron (MLP) neural network which is trained with the back-propagation algorithm; the design reuses existing legacy software and exploits novel grid components. The predictor takes into account the evolutionary information found in multiple sequence alignment (MSA); the information is obtained running an optimized parallel version of the PSI-BLAST tool, based on the MPI Master-Worker paradigm. The training set contains proteins of known structure. Using Grid technologies and efficient mechanisms for running the tools and extracting the data, the time needed to train the neural network is dramatically reduced, whereas the results are comparable to a set of well-known predictor tools.

A services oriented system for bioinformatics applications on the grid.

This paper describes the evolution of the main services of the ProGenGrid (Proteomics & Genomics Grid) system, a distributed and ubiquitous grid environment ("virtual laboratory"), based on Workflow and supporting the design, execution and monitoring of "in silico" experiments in bioinformatics.ProGenGrid is a Grid-based Problem Solving Environment that allows the composition of data sources and bioinformatics programs wrapped as Web Services (WS). The use of WS provides ease of use and fosters re-use. The resulting workflow of WS is then scheduled on the Grid, leveraging Grid-middleware services. In particular, ProGenGrid offers a modular bag of services and currently is focused on the biological simulation of two important bioinformatics problems: prediction of the secondary structure of proteins, and sequence alignment of proteins. Both services are based on an enhanced data access service.

ProGenGrid: a grid-enabled platform for bioinformatics.

In this paper we describe the ProGenGrid (Proteomics and Genomics Grid) system, developed at the CACT/ISUFI of the University of Lecce which aims at providing a virtual laboratory where e-scientists can simulate biological experiments, composing existing analysis and visualization tools, monitoring their execution, storing the intermediate and final output and finally, if needed, saving the model of the experiment for updating or reproducing it. The tools that we are considering are software components wrapped as Web Services and composed through a workflow. Since bioinformatics applications need to use high performance machines or a high number of workstations to reduce the computational time, we are exploiting a Grid infrastructure for interconnecting wide-spread tools and hardware resources. As an example, we are considering some algorithms and tools needed for drug design, providing them as services, through easy to use interfaces such as the Web and Web service interfaces built using the open source gSOAP Toolkit, whereas as Grid middleware we are using the Globus Toolkit 3.2, exploiting some protocols such as GSI and GridFTP.