Detecting significant features in modeling microRNA-target interactions

MicroRNAs (miRNAs) are small non-coding RNA molecules mediating the translational repression and degradation of target mRNAs in the cell. Mature miRNAs are used as a template by the RNA-induced silencing complex (RISC) to recognize the complementary mRNAs to be regulated. Up to 60% of human genes are putative targets of one or more miRNAs. Several prediction tools are available to suggest putative miRNA targets, however, only a small part of the interaction pairs has been validated by experimental approaches. The analysis of the expression profile of the RNA fraction immunoprecipitated (IP) with the RISC proteins is an established method to detect which genes are actually regulated by the RISC machinery. In fact, genes that result over-expressed in the IP sample with respect to the whole cell lysate RNA, are considered as involved in the RISC complex, then miRNA targets. Here, we aim to find the features useful to predict which genes are overexpressed in IP, i.e. miRNA targets, without actually performing the IP experiments. To this purpose, we compiled and analyzed a novel high throughput data set suitable to unravel the features involved in the miRNA regulatory activities. We analyzed IP samples obtained by the immunoprecipitation of two RISC proteins, AGO2 and GW182. The two proteins shows different behaviors, in terms of enriched genes and features characterizing the immunoprecipitated RNA fractio. Further analysis is needed to unravel the reason of such different behavior

Pro-invasive stimuli and the interacting protein Hsp70 favour the route of alpha-enolase to the cell surface

Cell surface expression of alpha-enolase, a glycolytic enzyme displaying moonlighting activities, has been shown to contribute to the motility and invasiveness of cancer cells through the protein non-enzymatic function of binding plasminogen and enhancing plasmin formation. Although a few recent records indicate the involvement of protein partners in the localization of alpha-enolase to the plasma membrane, the cellular mechanisms underlying surface exposure remain largely elusive. Searching for novel interactors and signalling pathways, we used low-metastatic breast cancer cells, a doxorubicin-resistant counterpart and a non-tumourigenic mammary epithelial cell line. Here, we demonstrate by a combination of experimental approaches that epidermal growth factor (EGF) exposure, like lipopolysaccharide (LPS) exposure, promotes the surface expression of alpha-enolase. We also establish Heat shock protein 70 (Hsp70), a multifunctional chaperone distributed in intracellular, plasma membrane and extracellular compartments, as a novel alpha-enolase interactor and demonstrate a functional involvement of Hsp70 in the surface localization of alpha-enolase. Our results contribute to shedding light on the control of surface expression of alpha-enolase in non-tumourigenic and cancer cells and suggest novel targets to counteract the metastatic potential of tumours

On the Multi-Language Construction

Modern software is no more developed in a single programming language. Instead, programmers tend to exploit cross-language interoperability mechanisms to combine code stemming from different languages, and thus yielding fully-fledged multi-language programs. Whilst this approach enables developers to benefit from the strengths of each single-language, on the other hand it complicates the semantics of such programs. Indeed, the resulting multi-language does not meet any of the semantics of the combined languages. In this paper, we broaden the boundary functions-based approach a la Matthews and Findler to propose an algebraic framework that provides a constructive mathematical notion of multi-language able to determine its semantics. The aim of this work is to overcome the lack of a formal method (resp., model) to design (resp., represent) a multi-language, regardless of the inherent nature of the underlying languages. We show that our construction ensures the uniqueness of the semantic function (i.e., the multi-language semantics induced by the combined languages) by proving the initiality of the term model (i.e., the abstract syntax of the multi-language) in its category

The PVT-1 oncogene is a Myc protein target that is overexpressed in transformed cells

The human PVT-1 gene is located on chromosome 8 telomeric to the c-Myc gene and it is frequently involved in the translocations occurring in variant Burkitt\u2019s lymphomas and murine plasmacytomas. It has been proposed that PVT-1 regulates c-Myc gene transcription over a long distance. To get new insights into the functional relationships between the two genes, we have investigated PVT-1 and c-Myc expression in normal human tissues and in transformed cells. Our findings indicate that PVT-1 expression is restricted to a relative low number of normal tissues compared to the wide distribution of c-Myc mRNA, whereas the gene is highly expressed in many transformed cell types including neuroblastoma cells that do not express c-Myc. Reporter gene assays were used to dissect the PVT-1 promoter and to identify the region responsible for the elevated expression observed in transformed cells. This region contains two putative binding sites for Myc proteins. The results of transfection experiments in RAT1-MycER cells and chromatin immunoprecipitation (ChIP) assays in proliferating and differentiated neuroblastoma cells indicate that PVT-1 is a downstream target of Myc proteins

Fast Fingerprints Classification only using the Directional Image

The classification phase is an important step of an automatic fingerprint identification system, where the goal is to restrict only to a subset of the whole database the search time. The proposed system classifies fingerprint images in four classes using only directional image information. This approach, unlike the literature approaches, uses the acquired fingerprint image without enhancement phases application. The system extracts only directional image and uses three concurrent decisional modules to classify the fingerprint. The proposed system has a high classification speed and a very low computational cost. The experimental results show a classification rate of 87.27%

The Kelch protein NS1-BP interacts with alpha-enolase/MBP-1 and is involved in c-Myc gene transcriptional control

Alpha-enolase is a key glycolytic enzyme that plays a functional role in several physiological processes depending on the cellular localization. The enzyme is mainly localized in the cytoplasm whereas an alternative translated form, named MBP-1, is predominantly nuclear. The MBP-1 protein has been characterized as a c-Myc promoter binding protein that negatively controls transcription. In the present study, we identified the kelch protein NS1-BP as one of the alpha-enolase/MBP-1 partners by using a yeast two-hybrid screening. Although NS1-BP has been originally described as a protein mainly localized in the nucleus, we provide evidence that NS1-BP also interacts with actin in human cells, as reported for most kelch-containing proteins. Here we showed that alpha-enolase and MBP-1 associate with NS1-BP in vitro and in vivo by GST pull-down assays and coimmunoprecipitation experiments; subsequent immunofluorescent staining confirmed colocalization of the proteins within the cells. Furthermore, functional analyses performed by cotransfection assays revealed that NS1-BP enhances the inhibitory effect exerted by MBP-1 on c-Myc promoter. In mammalian cells, the overexpression of both proteins resulted in an increased repression of basal c-Myc transcription and consistently affected the steady state levels of endogenous c-Myc mRNA. These findings further support the distinct roles of alpha-enolase and its MBP-1 variant in maintaining cell homeostasis. Moreover, our data suggest a novel function for NS1-BP in the control of cell proliferation. © 2007 Elsevier B.V. All rights reserved