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Abdelali Haoudi

Publications and source records attributed to Abdelali Haoudi.

15 recordsLinked to original sources
PubMed2006

Human LINE-1 retrotransposon induces DNA damage and apoptosis in cancer cells.

BACKGROUND: Long interspersed nuclear elements (LINEs), Alu and endogenous retroviruses (ERVs) make up some 45% of human DNA. LINE-1 also called L1, is the most common family of non-LTR retrotransposons in the human genome and comprises about 17% of the genome. L1 elements require the integration into chromosomal target sites using L1-encoded endonuclease which creates staggering DNA breaks allowing the newly transposed L1 copies to integrate into the genome. L1 expression and retrotransposition in cancer cells might cause transcriptional deregulation, insertional mutations, DNA breaks, and an increased frequency of recombinations, contributing to genome instability. There is however little evidence on the mechanism of L1-induced genetic instability and its impact on cancer cell growth and proliferation. RESULTS: We report that L1 has genome-destabilizing effects indicated by an accumulation of gamma-H2AX foci, an early response to DNA strand breaks, in association with an abnormal cell cycle progression through a G2/M accumulation and an induction of apoptosis in breast cancer cells. In addition, we found that adjuvant L1 activation may lead to supra-additive killing when combined with radiation by enhancing the radiation lethality through induction of apoptosis that we have detected through Bax activation. CONCLUSION: L1 retrotransposition is sensed as a DNA damaging event through the creation DNA breaks involving L1-encoded endonuclease. The apparent synergistic interaction between L1 activation and radiation can further be utilized for targeted induction of cancer cell death. Thus, the role of retrotransoposons in general, and of L1 in particular, in DNA damage and repair assumes larger significance both for the understanding of mutagenicity and, potentially, for the control of cell proliferation and apoptosis.

Journal Article↗
PubMed2006

RNA interference.

Explore the source record for details and available documents.

Editorial↗
PubMed2006

Bioinformatics and data mining in proteomics.

Proteomic studies involve the identification as well as qualitative and quantitative comparison of proteins expressed under different conditions, and elucidation of their properties and functions, usually in a large-scale, high-throughput format. The high dimensionality of data generated from these studies will require the development of improved bioinformatics tools and data-mining approaches for efficient and accurate data analysis of biological specimens from healthy and diseased individuals. Mining large proteomics data sets provides a better understanding of the complexities between the normal and abnormal cell proteome of various biological systems, including environmental hazards, infectious agents (bioterrorism) and cancers. This review will shed light on recent developments in bioinformatics and data-mining approaches, and their limitations when applied to proteomics data sets, in order to strengthen the interdependence between proteomic technologies and bioinformatics tools.

Computational Biology↗
PubMed2005

PDZ binding motif of HTLV-1 Tax promotes virus-mediated T-cell proliferation in vitro and persistence in vivo.

HTLV-1 cellular transformation and disease induction is dependent on expression of the viral Tax oncoprotein. PDZ is a modular protein interaction domain used in organizing signaling complexes in eukaryotic cells through recognition of a specific binding motif in partner proteins. Tax-1, but not Tax-2, contains a PDZ-binding domain motif (PBM) that promotes the interaction with several cellular PDZ proteins. Herein, we investigate the contribution of the Tax-1 PBM in HTLV-induced proliferation and immortalization of primary T cells in vitro and viral survival in an infectious rabbit animal model. We generated several HTLV-1 and HTLV-2 Tax viral mutants, including HTLV-1deltaPBM, HTLV-2+C22(+PBM), and HTLV-2+ C18(deltaPBM). All Tax mutants maintained the ability to significantly activate the CREB/ATF or NFkappaB signaling pathways. Microtiter proliferation assays revealed that the Tax-1 PBM significantly increases both HTLV-1- and HTLV-2-induced primary T-cell proliferation. In addition, Tax-1 PBM was responsible for the micronuclei induction activity of Tax-1 relative to that of Tax-2. Viral infection and persistence were severely attenuated in rabbits inoculated with HTLV-1deltaPBM. Our results provide the first direct evidence suggesting that PBM-mediated associations between Tax-1 and cellular proteins play a key role in HTLV-induced cell proliferation and genetic instability in vitro and facilitate viral persistence in vivo.

Amino Acid Motifs↗
PubMed2005

Functional clustering algorithm for high-dimensional proteomics data.

Clustering proteomics data is a challenging problem for any traditional clustering algorithm. Usually, the number of samples is largely smaller than the number of protein peaks. The use of a clustering algorithm which does not take into consideration the number of features of variables (here the number of peaks) is needed. An innovative hierarchical clustering algorithm may be a good approach. We propose here a new dissimilarity measure for the hierarchical clustering combined with a functional data analysis. We present a specific application of functional data analysis (FDA) to a high-throughput proteomics study. The high performance of the proposed algorithm is compared to two popular dissimilarity measures in the clustering of normal and human T-cell leukemia virus type 1 (HTLV-1)-infected patients samples.

Journal Article↗
PubMed2005

A novel approach for clustering proteomics data using Bayesian fast Fourier transform.

MOTIVATION: Bioinformatics clustering tools are useful at all levels of proteomic data analysis. Proteomics studies can provide a wealth of information and rapidly generate large quantities of data from the analysis of biological specimens. The high dimensionality of data generated from these studies requires the development of improved bioinformatics tools for efficient and accurate data analyses. For proteome profiling of a particular system or organism, a number of specialized software tools are needed. Indeed, significant advances in the informatics and software tools necessary to support the analysis and management of these massive amounts of data are needed. Clustering algorithms based on probabilistic and Bayesian models provide an alternative to heuristic algorithms. The number of clusters (diseased and non-diseased groups) is reduced to the choice of the number of components of a mixture of underlying probability. The Bayesian approach is a tool for including information from the data to the analysis. It offers an estimation of the uncertainties of the data and the parameters involved. RESULTS: We present novel algorithms that can organize, cluster and derive meaningful patterns of expression from large-scaled proteomics experiments. We processed raw data using a graphical-based algorithm by transforming it from a real space data-expression to a complex space data-expression using discrete Fourier transformation; then we used a thresholding approach to denoise and reduce the length of each spectrum. Bayesian clustering was applied to the reconstructed data. In comparison with several other algorithms used in this study including K-means, (Kohonen self-organizing map (SOM), and linear discriminant analysis, the Bayesian-Fourier model-based approach displayed superior performances consistently, in selecting the correct model and the number of clusters, thus providing a novel approach for accurate diagnosis of the disease. Using this approach, we were able to successfully denoise proteomic spectra and reach up to a 99% total reduction of the number of peaks compared to the original data. In addition, the Bayesian-based approach generated a better classification rate in comparison with other classification algorithms. This new finding will allow us to apply the Fourier transformation for the selection of the protein profile for each sample, and to develop a novel bioinformatic strategy based on Bayesian clustering for biomarker discovery and optimal diagnosis.

Algorithms↗
PubMed2004

Retrotransposition-Competent Human LINE-1 Induces Apoptosis in Cancer Cells With Intact p53.

Retrotransposition of human LINE-1 (L1) element, a major representative non-LTR retrotransposon in the human genome, is known to be a source of insertional mutagenesis. However, nothing is known about effects of L1 retrotransposition on cell growth and differentiation. To investigate the potential for such biological effects and the impact that human L1 retrotransposition has upon cancer cell growth, we examined a panel of human L1 transformed cell lines following a complete retrotransposition process. The results demonstrated that transposition of L1 leads to the activation of the p53-mediated apoptotic pathway in human cancer cells that possess a wild-type p53. In addition, we found that inactivation of p53 in cells, where L1 was undergoing retrotransposition, inhibited the induction of apoptosis. This suggests an association between active retrotransposition and a competent p53 response in which induction of apoptosis is a major outcome. These data are consistent with a model in which human retrotransposition is sensed by the cell as a "genetic damaging event" and that massive retrotransposition triggers signaling pathways resulting in apoptosis.

Journal Article↗
PubMed2003

Human T-cell leukemia virus-I tax oncoprotein functionally targets a subnuclear complex involved in cellular DNA damage-response.

The virally encoded oncoprotein Tax has been implicated in HTLV-1-mediated cellular transformation. The exact mechanism by which this protein contributes to the oncogenic process is not known. However, it has been hypothesized that Tax induces genomic instability via repression of cellular DNA repair. We examined the effect of de novo Tax expression upon the cell cycle, because appropriate activation of cell cycle checkpoints is essential to a robust damage-repair response. Upon induction of tax expression, Jurkat T-cells displayed a pronounced accumulation in G2/M that was reversible by caffeine. We examined the G2-specific checkpoint signaling response in these cells and found activation of the ATM/chk2-mediated pathway, whereas the ATR/chk1-mediated response was unaffected. Immunoprecipitation with anti-chk2 antibody results in co-precipitation of Tax demonstrating a direct interaction of Tax with a chk2-containing complex. We also show that Tax targets a discrete nuclear site and co-localizes with chk2 and not chk1. This nuclear site, previously identified as Tax Speckled Structures (TSS), also contains the early damage response factor 53BP1. The recruitment of 53BP1 to TSS is dependent upon ATM signaling and requires expression of Tax. Specifically, Tax expression induces redistribution of diffuse nuclear 53BP1 to the TSS foci. Taken together these data suggest that the TSS describe a unique nuclear site involved in DNA damage recognition, repair response, and cell cycle checkpoint activation. We suggest that association of Tax with this multifunctional subnuclear site results in disruption of a subset of the site-specific activities and contributes to cellular genomic instability.

Carrier Proteins↗
PubMed2003

The HTLV-1 tax oncoprotein attenuates DNA damage induced G1 arrest and enhances apoptosis in p53 null cells.

Transformation of cells by the human T cell leukemia virus type 1 occurs via mechanisms unique among oncogenic retroviruses. A prevailing hypothesis for HTLV-1-mediated cellular transformation is that expression of the viral transactivator, Tax, induces genomic instability. Tax-mediated failure in the cellular repair response is one possible mechanism for loss in genomic integrity. Here we have examined the in vivo repair response of Tax-expressing cells to determine the underlying defects that contribute to loss of genomic integrity. In these studies we examined the effects of de novo Tax-expression in naive "pre-neoplastic" REF52 cells. DNA-damage-induced p53 stabilization and concomitant transient stabilization of p21 were clearly evident in Tax-expressing cells. Likewise, the damage-induced apoptotic response of Tax-expressing cells was normal. However, the damage-induced G1 checkpoint was abrogated in either p53+ or p53- cellular backgrounds. Although nucleotide excision repair (NER) of asynchronous Tax-expressing cells was impaired, cell-cycle-independent assessment of NER in the global excision repair assay demonstrated comparable NER activity in Tax-expressing cells, suggesting that the failure of G1 checkpoint contributes to NER deficiency. Interestingly, we observed a dramatic increase in apoptosis and UV sensitivity of Tax-expressing p53-/- cells when compared to Tax-expressing p53+/+ cells. These data demonstrate that Tax-mediated cellular genomic instability arises from attenuation of cell-cycle checkpoint and imply a clonal dependence on p53 status separate from genomic integrity.

Apoptosis↗
PubMed2003

Postgenomics: Proteomics and Bioinformatics in Cancer Research.

Now that the human genome is completed, the characterization of the proteins encoded by the sequence remains a challenging task. The study of the complete protein complement of the genome, the "proteome," referred to as proteomics, will be essential if new therapeutic drugs and new disease biomarkers for early diagnosis are to be developed. Research efforts are already underway to develop the technology necessary to compare the specific protein profiles of diseased versus nondiseased states. These technologies provide a wealth of information and rapidly generate large quantities of data. Processing the large amounts of data will lead to useful predictive mathematical descriptions of biological systems which will permit rapid identification of novel therapeutic targets and identification of metabolic disorders. Here, we present an overview of the current status and future research approaches in defining the cancer cell's proteome in combination with different bioinformatics and computational biology tools toward a better understanding of health and disease.

Journal Article↗
PubMed2002

Telomere elongation (Tel), a new mutation in Drosophila melanogaster that produces long telomeres.

In most eukaryotes telomeres are extended by telomerase. Drosophila melanogaster, however, lacks telomerase, and telomere-specific non-LTR retrotransposons, HeT-A and TART, transpose specifically to chromosome ends. A Drosophila strain, Gaiano, that has long telomeres has been identified. We extracted the major Gaiano chromosomes into an Oregon-R genetic background and examined the resulting stocks after 60 generations. In situ hybridization using HeT-A and TART sequences showed that, in stocks carrying either the X or the second chromosome from Gaiano, only the Gaiano-derived chromosomes display long telomeres. However, in stocks carrying the Gaiano third chromosome, all telomeres are substantially elongated, indicating that the Gaiano chromosome 3 carries a factor that increases HeT-A and TART addition to the telomeres. We show that this factor, termed Telomere elongation (Tel), is dominant and localizes as a single unit to 69 on the genetic map. The long telomeres tend to associate with each other in both polytene and mitotic cells. These associations depend on telomere length rather than the presence of Tel. Associations between metaphase chromosomes are resolved during anaphase, suggesting that they are mediated by either proteinaceous links or DNA hydrogen bonding, rather than covalent DNA-DNA bonds.

Anaphase↗