Structural Determinants of Specificity and Catalytic Mechanism in mammalian 25-kDa Thiamine Triphosphatase

in Biochimica et Biophysica Acta - General Subjects (in press)

Background: Thiamine triphosphate (ThTP) is present in most organisms and might be involved in intracellular signaling. In mammalian cells, the cytosolic ThTP level is controlled by a specific thiamine ... [more ▼]

Background: Thiamine triphosphate (ThTP) is present in most organisms and might be involved in intracellular signaling. In mammalian cells, the cytosolic ThTP level is controlled by a specific thiamine triphosphatase (ThTPase), belonging to the CYTH superfamily of proteins. CYTH proteins are present in all superkingdoms of life and act on various triphosphorylated substrates. Methods: Using crystallography, mass spectrometry and mutational analysis, we identified the key structural determinants of the high specificity and catalytic efficiency of mammalian ThTPase. Results: Triphosphate binding requires three conserved arginines while the catalytic mechanism relies on an unusual lysine-tyrosine dyad. By docking of the ThTP molecule in the active site, we found that Trp-53 should interact with the thiazole part of the substrate molecule, thus playing a key role in substrate recognition and specificity. Sea anemone and zebrafish CYTH proteins, which retain the corresponding Trp residue, are also specific ThTPases. Surprisingly, the whole chromosome region containing the ThTPase gene is lost in birds. Conclusion: The specificity for ThTP is linked to a stacking interaction between the thiazole heterocycle of thiamine and a tryptophan residue. The latter likely plays a key role in the secondary acquisition of ThTPase activity in early metazoan CYTH enzymes, in the lineage leading from cnidarians to mammals. General significance: We show that ThTPase activity is not restricted to mammals as previously thought but is an acquisition of early metazoans. This, and the identification of critically important residues, allows us to draw an evolutionary perspective of the CYTH family of proteins. [less ▲]

Phenotype Classification of Zebrafish Embryos by Supervised Learning

Poster (2011, December 08)

Phenotype Classification of Zebrafish Embryos by Supervised Learning

Conference (2011, September 02)

Zebrafish Skeleton Measurements using Image Analysis and Machine Learning Methods

Poster (2011, May 20)

The zebrafish is a model organism for biological studies on development and gene function. Our work aims at automating the detection of the cartilage skeleton and measuring several distances and angles to ... [more ▼]

The zebrafish is a model organism for biological studies on development and gene function. Our work aims at automating the detection of the cartilage skeleton and measuring several distances and angles to quantify its development following different experimental conditions. [less ▲]

Discovery and biochemical characterisation of four novel biomarkers for osteoarthritis.

in Annals of the Rheumatic Diseases (2011), 70(6), 1144-52

OBJECTIVE: Knee osteoarthritis (OA) is a heterogeneous, complex joint pathology of unknown aetiology. Biomarkers have been widely used to investigate OA but currently available biomarkers lack specificity ... [more ▼]

OBJECTIVE: Knee osteoarthritis (OA) is a heterogeneous, complex joint pathology of unknown aetiology. Biomarkers have been widely used to investigate OA but currently available biomarkers lack specificity and sensitivity. Therefore, novel biomarkers are needed to better understand the pathophysiological processes of OA initiation and progression. METHODS: Surface enhanced laser desorption/ionisation-time of flight-mass spectrometry proteomic technique was used to analyse protein expression levels in 284 serum samples from patients with knee OA classified according to Kellgren and Lawrence (K&L) score (0-4). OA serum samples were also compared to serum samples provided by healthy individuals (negative control subjects; NC; n=36) and rheumatoid arthritis (RA) patients (n=25). Proteins that gave similar signal in all K&L groups of OA patients were ignored, whereas proteins with increased or decreased levels of expression were selected for further studies. RESULTS: Two proteins were found to be expressed at higher levels in sera of OA patients at all four K&L scores compared to NC and RA, and were identified as V65 vitronectin fragment and C3fpeptide. Of the two remaining proteins, one showed increased expression (unknown protein at m/z of 3762) and the other (identified as connective tissue-activating peptide III protein) was decreased in K&L scores >2 subsets compared to NC, RA and K&L scores 0 or 1 subsets. CONCLUSION: The authors detected four unexpected biomarkers (V65 vitronectin fragment, C3f peptide, CTAP-III and m/z 3762 protein) that could be relevant in the pathophysiological process of OA as having significant correlation with parameters reflecting local inflammation and bone remodelling, as well as decrease in cartilage turnover. [less ▲]

Radar Classification based on Extra-Trees

(2010, May 24)

In this paper, we describe a new automatic target recognition algorithm for classifying SAR images based on the PiXiT im- age classifier. It uses randomized sub-windows extraction and extremely randomized ... [more ▼]

In this paper, we describe a new automatic target recognition algorithm for classifying SAR images based on the PiXiT im- age classifier. It uses randomized sub-windows extraction and extremely randomized trees (extra-trees). This approach re- quires very little pre-processing of the images, thereby lim- iting the computational load. It was successfully tested on an extended version of the public standard MSTAR database, that includes targets of interest, false targets, and background clutter. A misclassification rate of about three percent has been achieved. [less ▲]

Incremental Indexing and Distributed Image Search using Shared Randomized Vocabularies

in ACM Proceedings MIR 2010 (2010, March)

We present a cooperative framework for content-based image retrieval for the realistic setting where images are distributed across multiple cooperating servers. The proposed method is in line with bag-of ... [more ▼]

We present a cooperative framework for content-based image retrieval for the realistic setting where images are distributed across multiple cooperating servers. The proposed method is in line with bag-of-features approaches but uses fully data-independent, randomized structures, shared by the cooperating servers, to map image features to common visual words. A coherent, global image similarity measure (which is a kernel) is computed in a distributed fashion over visual words, by only requiring a small amount of data transfers between nodes. Our experiments on various image types show that this framework is a very promising step towards large-scale, distributed content-based image retrieval. [less ▲]

Biomedical Imaging Modality Classification Using Bags of Visual and Textual Terms with Extremely Randomized Trees: Report of ImageCLEF 2010 Experiments

in CLEF Notebook Papers/LABs/Workshops (2010)

In this paper we describe our experiments related to the ImageCLEF 2010 medical modality classification task using extremely randomized trees. Our best run combines bags of textual and visual features. It ... [more ▼]

In this paper we describe our experiments related to the ImageCLEF 2010 medical modality classification task using extremely randomized trees. Our best run combines bags of textual and visual features. It yields 90% recognition rate and ranks 6th among 45 runs (ranging from 94% downto 12%). [less ▲]

Fast Multi-Class Image Annotation with Random Subwindows and Multiple Output Randomized Trees

in Proc. International Conference on Computer Vision Theory and Applications (VISAPP) (2009, February)

This paper addresses image annotation, i.e. labelling pixels of an image with a class among a finite set of predefined classes. We propose a new method which extracts a sample of subwindows from a set of ... [more ▼]

This paper addresses image annotation, i.e. labelling pixels of an image with a class among a finite set of predefined classes. We propose a new method which extracts a sample of subwindows from a set of annotated images in order to train a subwindow annotation model by using the extremely randomized trees ensemble method appropriately extended to handle high-dimensional output spaces. The annotation of a pixel of an unseen image is done by aggregating the annotations of its subwindows containing this pixel. The proposed method is compared to a more basic approach predicting the class of a pixel from a single window centered on that pixel and to other state-of-the-art image annotation methods. In terms of accuracy, the proposed method significantly outperforms the basic method and shows good performances with respect to the state-of-the-art, while being more generic, conceptually simpler, and of higher computational efficiency than these latter. [less ▲]

Protéomique par SELDI-TOF-MS des maladies inflammatoires articulaires: identification des protéines S100 comme protéines d'intérêt

in Revue Médicale de Liège (2009), 64(Spec No), 29-35

Clinical proteomics is a technical approach studying the entire proteome expressed by cells, tissues or organs. It describes the dynamics of cell regulation by detecting molecular events related to ... [more ▼]

Clinical proteomics is a technical approach studying the entire proteome expressed by cells, tissues or organs. It describes the dynamics of cell regulation by detecting molecular events related to diseases development. Proteomic techniques focus mainly on identification of new biomarkers or new therapeutic targets. It is a multidisciplinary approach using medical, biological, bioanalytical and bioinformatics knowledges. A strong collaboration between these fields allowed SELDI-TOF-MS proteomics studies to be performed at the CHU and the University of Liege, in GIGA-Research facilities. The aim of these studies was driven along three main axes of research related to the identification of biomarkers specific to a studied pathology, to a common biological pathway and, finally, to a treatment response. [less ▲]