Annotation des ARN non codants du génome de Candida albicans par méthode bioinformatique

La bio-informatique est un champ pluridisciplinaire qui utilise la biologie, l’informatique, la physique et les mathématiques pour résoudre des problèmes posés par la biologie. L’une des thématiques de la bio-informatique est l’analyse des séquences génomiques et la prédiction de gènes d’ARN non codants. Les ARN non codants sont des molécules d’ARN qui sont transcrites mais pas traduites en protéine et qui ont une fonction dans la cellule. Trouver des gènes d’ARN non codants par des techniques de biochimie et de biologie moléculaire est assez difficile et relativement coûteux. Ainsi, la prédiction des gènes d’ARNnc par des méthodes bio-informatiques est un enjeu important. Cette recherche décrit un travail d’analyse informatique pour chercher des nouveaux ARNnc chez le pathogène Candida albicans et d’une validation expérimentale. Nous avons utilisé comme stratégie une analyse informatique combinant plusieurs logiciels d’identification d’ARNnc. Nous avons validé un sous-ensemble des prédictions informatiques avec une expérience de puces à ADN couvrant 1979 régions du génome. Grace à cette expérience nous avons identifié 62 nouveaux transcrits chez Candida albicans. Ce travail aussi permit le développement d’une méthode d’analyse pour des puces à ADN de type tiling array. Ce travail présente également une tentation d’améliorer de la prédiction d’ARNnc avec une méthode se basant sur la recherche de motifs d’ARN dans les séquences.

Protein Microarray: "Theory" to "Real Practice"

Fueled by ever-growing genomic information and rapid developments of proteomics–the large scale analysis of proteins and mapping its functional role has become one of the most important disciplines for characterizing complex cell function. For building functional linkages between the biomolecules, and for providing insight into the mechanisms of biological processes, last decade witnessed the exploration of combinatorial and chip technology for the detection of bimolecules in a high throughput and spatially addressable fashion. Among the various techniques developed, the protein chip technology has been rapid. Recently we demonstrated a new platform called “Spacially addressable protein array” (SAPA) to profile the ligand receptor interactions. To optimize the platform, the present study investigated various parameters such as the surface chemistry and role of additives for achieving high density and high-throughput detection with minimal nonspecific protein adsorption. In summary the present poster will address some of the critical challenges in protein micro array technology and the process of fine tuning to achieve the optimum system for solving real biological problems.

No impact of malaria infection or immunisation on the expression of the immune GTPase GIMAP1 at the protein or mRNA levels (Article no. 53)

GIMAP (GTPase of the immunity-associated protein family) proteins are a family of putative GTPases believed to be regulators of cell death in lymphomyeloid cells. GIMAP1 was the first reported member of this gene family, identified as a gene up-regulated at the RNA level in the spleens of mice infected with the malarial parasite, Plasmodium chabaudi. Methods A monoclonal antibody against mouse GIMAP1 was developed and was used to analyse the expression of the endogenous protein in tissues of normal mice and in defined sub-populations of cells prepared from lymphoid tissues using flow cytometry. It was also used to assess the expression of GIMAP1 protein after infection and/or immunization of mice with P. chabaudi. Real-time PCR analysis was employed to measure the expression of GIMAP1 for comparison with the protein level analysis. Results GIMAP1 protein expression was detected in all lineages of lymphocytes (T, B, NK), in F4/80+ splenic macrophages and in some lymphoid cell lines. Additional evidence is presented suggesting that the strong expression by mature B cells of GIMAP1 and other GIMAP genes and proteins seen in mice may be a species-dependent characteristic. Unexpectedly, no increase was found in the expression of GIMAP1 in P. chabaudi infected mice at either the mRNA or protein level, and this remained so despite applying a number of variations to the protocol. Conclusion The model of up-regulation of GIMAP1 in response to infection/immunization with P. chabaudi is not a robustly reproducible experimental system. The GIMAP1 protein is widely expressed in lymphoid cells, with an interesting increase in expression in the later stages of B cell development. Alternative approaches will be required to define the functional role of this GTPase in immune cells.

Proteomic analysis of redox- and ErbB2-dependent changes in mammary luminal epithelial cells using cysteine- and lysine-labelling two-dimensional difference gel electrophoresis

Differential protein expression analysis based on modification of selected amino acids with labelling reagents has become the major method of choice for quantitative proteomics. One such methodology, two-dimensional difference gel electrophoresis (2-D DIGE), uses a matched set of fluorescent N-hydroxysuccinimidyl (NHS) ester cyanine dyes to label lysine residues in different samples which can be run simultaneously on the same gels. Here we report the use of iodoacetylated cyanine (ICy) dyes (for labelling of cysteine thiols, for 2-D DIGE-based redox proteomics. Characterisation of ICy dye labelling in relation to its stoichiometry, sensitivity and specificity is described, as well as comparison of ICy dye with NHS-Cy dye labelling and several protein staining methods. We have optimised conditions for labelling of nonreduced, denatured samples and report increased sensitivity for a subset of thiol-containing proteins, allowing accurate monitoring of redox-dependent thiol modifications and expression changes. Cysteine labelling was then combined with lysine labelling in a multiplex 2-D DIGE proteomic study of redox-dependent and ErbB2-dependent changes in epithelial cells exposed to oxidative stress. This study identifies differentially modified proteins involved in cellular redox regulation, protein folding, proliferative suppression, glycolysis and cytoskeletal organisation, revealing the complexity of the response to oxidative stress and the impact that overexpression of ErbB2 has on this response.

Proteomic analysis of redox- and ErbB2-dependent changes in mammary luminal epithelial cells using cysteine- and lysine-labelling two-dimensional difference gel electrophoresis

Differential protein expression analysis based on modification of selected amino acids with labelling reagents has become the major method of choice for quantitative proteomics. One such methodology, two-dimensional difference gel electrophoresis (2-D DIGE), uses a matched set of fluorescent N-hydroxysuccinimidyl (NHS) ester cyanine dyes to label lysine residues in different samples which can be run simultaneously on the same gels. Here we report the use of iodoacetylated cyanine (ICy) dyes (for labelling of cysteine thiols, for 2-D DIGE-based redox proteomics. Characterisation of ICy dye labelling in relation to its stoichiometry, sensitivity and specificity is described, as well as comparison of ICy dye with NHS-Cy dye labelling and several protein staining methods. We have optimised conditions for labelling of nonreduced, denatured samples and report increased sensitivity for a subset of thiol-containing proteins, allowing accurate monitoring of redox-dependent thiol modifications and expression changes, Cysteine labelling was then combined with lysine labelling in a multiplex 2-D DIGE proteomic study of redox-dependent and ErbB2-dependent changes in epithelial cells exposed to oxidative stress. This study identifies differentially modified proteins involved in cellular redox regulation, protein folding, proliferative suppression, glycolysis and cytoskeletal organisation, revealing the complexity of the response to oxidative stress and the impact that overexpression of ErbB2 has on this response.

Evaluation of peak-picking algorithms for protein mass spectrometry

Peak picking is an early key step in MS data analysis. We compare three commonly used approaches to peak picking and discuss their merits by means of statistical analysis. Methods investigated encompass signal-to-noise ratio, continuous wavelet transform, and a correlation-based approach using a Gaussian template. Functionality of the three methods is illustrated and discussed in a practical context using a mass spectral data set created with MALDI-TOF technology. Sensitivity and specificity are investigated using a manually defined reference set of peaks. As an additional criterion, the robustness of the three methods is assessed by a perturbation analysis and illustrated using ROC curves.

What are the baselines for protein fold recognition?

What constitutes a baseline level of success for protein fold recognition methods? As fold recognition benchmarks are often presented without any thought to the results that might be expected from a purely random set of predictions, an analysis of fold recognition baselines is long overdue. Given varying amounts of basic information about a protein—ranging from the length of the sequence to a knowledge of its secondary structure—to what extent can the fold be determined by intelligent guesswork? Can simple methods that make use of secondary structure information assign folds more accurately than purely random methods and could these methods be used to construct viable hierarchical classifications?

FunFOLDQA: a quality assessment tool for protein-ligand binding site residue predictions

The estimation of prediction quality is important because without quality measures, it is difficult to determine the usefulness of a prediction. Currently, methods for ligand binding site residue predictions are assessed in the function prediction category of the biennial Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiment, utilizing the Matthews Correlation Coefficient (MCC) and Binding-site Distance Test (BDT) metrics. However, the assessment of ligand binding site predictions using such metrics requires the availability of solved structures with bound ligands. Thus, we have developed a ligand binding site quality assessment tool, FunFOLDQA, which utilizes protein feature analysis to predict ligand binding site quality prior to the experimental solution of the protein structures and their ligand interactions. The FunFOLDQA feature scores were combined using: simple linear combinations, multiple linear regression and a neural network. The neural network produced significantly better results for correlations to both the MCC and BDT scores, according to Kendall’s τ, Spearman’s ρ and Pearson’s r correlation coefficients, when tested on both the CASP8 and CASP9 datasets. The neural network also produced the largest Area Under the Curve score (AUC) when Receiver Operator Characteristic (ROC) analysis was undertaken for the CASP8 dataset. Furthermore, the FunFOLDQA algorithm incorporating the neural network, is shown to add value to FunFOLD, when both methods are employed in combination. This results in a statistically significant improvement over all of the best server methods, the FunFOLD method (6.43%), and one of the top manual groups (FN293) tested on the CASP8 dataset. The FunFOLDQA method was also found to be competitive with the top server methods when tested on the CASP9 dataset. To the best of our knowledge, FunFOLDQA is the first attempt to develop a method that can be used to assess ligand binding site prediction quality, in the absence of experimental data.

Towards data warehousing and mining of protein unfolding simulation data

OBJECTIVES: The prediction of protein structure and the precise understanding of protein folding and unfolding processes remains one of the greatest challenges in structural biology and bioinformatics. Computer simulations based on molecular dynamics (MD) are at the forefront of the effort to gain a deeper understanding of these complex processes. Currently, these MD simulations are usually on the order of tens of nanoseconds, generate a large amount of conformational data and are computationally expensive. More and more groups run such simulations and generate a myriad of data, which raises new challenges in managing and analyzing these data. Because the vast range of proteins researchers want to study and simulate, the computational effort needed to generate data, the large data volumes involved, and the different types of analyses scientists need to perform, it is desirable to provide a public repository allowing researchers to pool and share protein unfolding data. METHODS: To adequately organize, manage, and analyze the data generated by unfolding simulation studies, we designed a data warehouse system that is embedded in a grid environment to facilitate the seamless sharing of available computer resources and thus enable many groups to share complex molecular dynamics simulations on a more regular basis. RESULTS: To gain insight into the conformational fluctuations and stability of the monomeric forms of the amyloidogenic protein transthyretin (TTR), molecular dynamics unfolding simulations of the monomer of human TTR have been conducted. Trajectory data and meta-data of the wild-type (WT) protein and the highly amyloidogenic variant L55P-TTR represent the test case for the data warehouse. CONCLUSIONS: Web and grid services, especially pre-defined data mining services that can run on or 'near' the data repository of the data warehouse, are likely to play a pivotal role in the analysis of molecular dynamics unfolding data.

The Gly482Ser genotype at the PPARGC1A gene and elevated blood pressure: a meta-analysis involving 13,949 individuals.

The protein encoded by the PPARGC1A gene is expressed at high levels in metabolically active tissues and is involved in the control of oxidative stress via reactive oxygen species detoxification. Several recent reports suggest that the PPARGC1A Gly482Ser (rs8192678) missense polymorphism may relate inversely with blood pressure. We used conventional meta-analysis methods to assess the association between Gly482Ser and systolic (SBP) or diastolic blood pressures (DBP) or hypertension in 13,949 individuals from 17 studies, of which 6,042 were previously unpublished observations. The studies comprised cohorts of white European, Asian, and American Indian adults, and adolescents from South America. Stratified analyses were conducted to control for population stratification. Pooled genotype frequencies were 0.47 (Gly482Gly), 0.42 (Gly482Ser), and 0.11 (Ser482Ser). We found no evidence of association between Gly482Ser and SBP [Gly482Gly: mean = 131.0 mmHg, 95% confidence interval (CI) = 130.5-131.5 mmHg; Gly482Ser mean = 133.1 mmHg, 95% CI = 132.6-133.6 mmHg; Ser482Ser: mean = 133.5 mmHg, 95% CI = 132.5-134.5 mmHg; P = 0.409] or DBP (Gly482Gly: mean = 80.3 mmHg, 95% CI = 80.0-80.6 mmHg; Gly482Ser mean = 81.5 mmHg, 95% CI = 81.2-81.8 mmHg; Ser482Ser: mean = 82.1 mmHg, 95% CI = 81.5-82.7 mmHg; P = 0.651). Contrary to previous reports, we did not observe significant effect modification by sex (SBP, P = 0.966; DBP, P = 0.715). We were also unable to confirm the previously reported association between the Ser482 allele and hypertension [odds ratio: 0.97, 95% CI = 0.87-1.08, P = 0.585]. These results were materially unchanged when analyses were focused on whites only. However, statistical evidence of gene-age interaction was apparent for DBP [Gly482Gly: 73.5 (72.8, 74.2), Gly482Ser: 77.0 (76.2, 77.8), Ser482Ser: 79.1 (77.4, 80.9), P = 4.20 x 10(-12)] and SBP [Gly482Gly: 121.4 (120.4, 122.5), Gly482Ser: 125.9 (124.6, 127.1), Ser482Ser: 129.2 (126.5, 131.9), P = 7.20 x 10(-12)] in individuals <50 yr (n = 2,511); these genetic effects were absent in those older than 50 yr (n = 5,088) (SBP, P = 0.41; DBP, P = 0.51). Our findings suggest that the PPARGC1A Ser482 allele may be associated with higher blood pressure, but this is only apparent in younger adults.

Implication of RNA-Binding Protein La in Proliferation, Migration and Invasion of Lymph Node-Metastasized Hypopharyngeal SCC Cells

The 5-year survival rate for oral cavity cancer is poorer than for breast, colon or prostate cancer, and has improved only slightly in the last three decades. Hence, new therapeutic strategies are urgently needed. Here we demonstrate by tissue micro array analysis for the first time that RNA-binding protein La is significantly overexpressed in oral squamous cell carcinoma (SCC). Within this study we therefore addressed the question whether siRNA-mediated depletion of the La protein may interfere with known tumor-promoting characteristics of head and neck SCC cells. Our studies demonstrate that the La protein promotes cell proliferation, migration and invasion of lymph node-metastasized hypopharyngeal SCC cells. We also reveal that La is required for the expression of beta-catenin as well as matrix metalloproteinase type 2 (MMP-2) within these cells. Taken together these data suggest a so far unknown function of the RNA-binding protein La in promoting tumor progression of head and neck SCC.

Molecular models of protein targets from Mycobacterium tuberculosis

Structural characterization of enzymes that belong to microbial metabolic pathways is very important for structure-based drug design since some of these proteins may be present in the bacterial genome, but absent in humans. Thus, metabolic pathways became potential targets for drug design. The motivation of this work is the fact that Mycobacterium tuberculosis is the cause of the deaths of millions of people in the world, so that the structural characterization of protein targets to propose new drugs has become essential. DBMODELING is a relational database, created to highlight the importance of methods of molecular modeling applied to the Mycobacterium tuberculosis genome with the aim of proposing protein-ligand docking analysis. There are currently more than 300 models for proteins from Mycobacterium tuberculosis genome in the database. The database contains a detailed description of the reaction catalyzed by each enzyme and their atomic coordinates. Information about structures, a tool for animated gif image, a table with a specification of the metabolic pathway, modeled protein, inputs used in modeling, and analysis methods used in this project are available in the database for download. The search tool can be used for reseachers to find specific pathways or enzymes.

Comportamento do implante contendo bone morphogenetic protein (bmp) associado ao plasma rico em plaquetas na reparação de fraturas orbitárias

Purpose: This study intends to evaluate BMP (Bone Morphogenetic Protein) implant and BMP implant plus PRP (Platelet Rich Plasma) in rabbit orbital fractures, searching for tissue reaction, by radiological and morfometrical analysis. Methods:Third six white rabbits were submitted to orbital floor fracture and distributed in three groups: G1, with rabbits receiving a plate containing decalcified bone matrix and BMP; G2, with rabbits receiving the implant with BMP wrapped by PRP; G3, the control group where it was made the fracture only. The animals were evaluated radiologically after surgery and at sacrifice time in 7, 30, 90 and 180th day after surgery. After sacrifice, a block containing the right orbital tissue was extracted and prepared to morphological and morphometrical analysis. Results: An intensive linfomononuclear inflammatory reaction was observed at 7th day in G1 e G2, witch decreased after the 30th day; mesenchimal cells, osteoblasts, new bone and progressive cavitation of the implant were also observed, besides signs of calcium deposition by radiological study. In the control group fibrosis at the site of fracture was identified only. Conclusion: BMP seemed a good orbital implant producing new bone at the implant site and correcting bone defect.There was not observed acceleration of osteoinduction when the implant was associated with PRP.

An Integrative Genomic and Transcriptomic Analysis Reveals Potential Targets Associated with Cell Proliferation in Uterine Leiomyomas

Background: Uterine Leiomyomas (ULs) are the most common benign tumours affecting women of reproductive age. ULs represent a major problem in public health, as they are the main indication for hysterectomy. Approximately 40-50% of ULs have non-random cytogenetic abnormalities, and half of ULs may have copy number alterations (CNAs). Gene expression microarrays studies have demonstrated that cell proliferation genes act in response to growth factors and steroids. However, only a few genes mapping to CNAs regions were found to be associated with ULs. Methodology: We applied an integrative analysis using genomic and transcriptomic data to identify the pathways and molecular markers associated with ULs. Fifty-one fresh frozen specimens were evaluated by array CGH (JISTIC) and gene expression microarrays (SAM). The CONEXIC algorithm was applied to integrate the data. Principal Findings: The integrated analysis identified the top 30 significant genes (P<0.01), which comprised genes associated with cancer, whereas the protein-protein interaction analysis indicated a strong association between FANCA and BRCA1. Functional in silico analysis revealed target molecules for drugs involved in cell proliferation, including FGFR1 and IGFBP5. Transcriptional and protein analyses showed that FGFR1 (P = 0.006 and P<0.01, respectively) and IGFBP5 (P = 0.0002 and P = 0.006, respectively) were up-regulated in the tumours when compared with the adjacent normal myometrium. Conclusions: The integrative genomic and transcriptomic approach indicated that FGFR1 and IGFBP5 amplification, as well as the consequent up-regulation of the protein products, plays an important role in the aetiology of ULs and thus provides data for potential drug therapies development to target genes associated with cellular proliferation in ULs. © 2013 Cirilo et al.

Post-receptor IGF1 insensitivity restricted to the MAPK pathway in a Silver-Russell syndrome patient with hypomethylation at the imprinting control region on chromosome 11

Background: Hypomethylation of the paternal imprinting center region 1 (ICR1) is the most frequent molecular cause of Silver-Russell syndrome (SRS). Clinical evidence suggests that patients with this epimutation have mild IGF1 insensitivity. Objective: To assess in vitro IGF1 action in fibroblast culture from a patient with SRS and IGF1 insensitivity. Methods: Fibroblast cultures from one patient with SRS due to ICR1 demethylation and controls were established. The SRS patient has severe growth failure, elevated IGF1 level, and poor growth rate during human recombinant GH treatment. IGF1 action was assessed by cell proliferation, AKT, and p42/44-MAPK phosphorylation. Gene expression was determined by real-time PCR. Results: Despite normal IGF1R sequence and expression, fibroblast proliferation induced by IGF1 was 50% lower in SRS fibroblasts in comparison with controls. IGF1 and insulin promoted a p42/44-MAPK activation in SRS fibroblasts 40 and 36%, respectively, lower than that in control fibroblasts. On the other hand, p42/44-MAPK activation induced by EGF stimulation was only slightly reduced (75% in SRS fibroblasts in comparison with control), suggesting a general impairment in MAPK pathway with a greater impairment of the stimulation induced by insulin and IGF1 than by EGF. A PCR array analysis disclosed a defect in MAPK pathway characterized by an increase in DUSP4 and MEF2C gene expressions in patient fibroblasts. Conclusion: A post-receptor IGF1 insensitivity was characterized in one patient with SRS and ICR1 hypomethylation. Although based on one unique severely affected patient, these results raise an intriguing mechanism to explain the postnatal growth impairment observed in SRS patients that needs confirmation in larger cohorts.