33 resultados para 060102 Bioinformatics


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In modern life- and medical-sciences major efforts are currently concentrated on creating artificial photoenzymes, consisting of light- oxygen-voltage-sensitive (LOV) domains fused to a target enzyme. Such protein constructs possess great potential for controlling the cell metabolism as well as gene function upon light stimulus. This has recently been impressively demonstrated by designing a novel artificial fusion protein, connecting the AsLOV2-Jα-photosensor from Avena sativa with the Rac1-GTPase (AsLOV2-Jα-Rac1), and by using it, to control the motility of cancer cells from the HeLa-line. Although tremendous progress has been achieved on the generation of such protein constructs, a detailed understanding of their signaling pathway after photoexcitation is still in its infancy. Here, we show through computer simulations of the AsLOV2-Jα-Rac1-photoenzyme that the early processes after formation of the Cys450-FMN-adduct involve the breakage of a H-bond between the carbonyl oxygen FMN-C4O and the amino group of Gln513, followed by a rotational reorientation of its sidechain. This initial event is followed by successive events including β-sheet tightening and transmission of torsional stress along the Iβ-sheet, which leads to the disruption of the Jα-helix from the N-terminal end. Finally, this process triggers the detachment of the AsLOV2-Jα-photosensor from the Rac1-GTPase, ultimately enabling the activation of Rac1 via binding of the effector protein PAK1.

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BACKGROUND: Despite recent algorithmic and conceptual progress, the stoichiometric network analysis of large metabolic models remains a computationally challenging problem. RESULTS: SNA is a interactive, high performance toolbox for analysing the possible steady state behaviour of metabolic networks by computing the generating and elementary vectors of their flux and conversions cones. It also supports analysing the steady states by linear programming. The toolbox is implemented mainly in Mathematica and returns numerically exact results. It is available under an open source license from: http://bioinformatics.org/project/?group_id=546. CONCLUSION: Thanks to its performance and modular design, SNA is demonstrably useful in analysing genome scale metabolic networks. Further, the integration into Mathematica provides a very flexible environment for the subsequent analysis and interpretation of the results.

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BACKGROUND: Pneumococcal meningitis is associated with high mortality (approximately 30%) and morbidity. Up to 50% of survivors are affected by neurological sequelae due to a wide spectrum of brain injury mainly affecting the cortex and hippocampus. Despite this significant disease burden, the genetic program that regulates the host response leading to brain damage as a consequence of bacterial meningitis is largely unknown.We used an infant rat model of pneumococcal meningitis to assess gene expression profiles in cortex and hippocampus at 22 and 44 hours after infection and in controls at 22 h after mock-infection with saline. To analyze the biological significance of the data generated by Affymetrix DNA microarrays, a bioinformatics pipeline was used combining (i) a literature-profiling algorithm to cluster genes based on the vocabulary of abstracts indexed in MEDLINE (NCBI) and (ii) the self-organizing map (SOM), a clustering technique based on covariance in gene expression kinetics. RESULTS: Among 598 genes differentially regulated (change factor > or = 1.5; p < or = 0.05), 77% were automatically assigned to one of 11 functional groups with 94% accuracy. SOM disclosed six patterns of expression kinetics. Genes associated with growth control/neuroplasticity, signal transduction, cell death/survival, cytoskeleton, and immunity were generally upregulated. In contrast, genes related to neurotransmission and lipid metabolism were transiently downregulated on the whole. The majority of the genes associated with ionic homeostasis, neurotransmission, signal transduction and lipid metabolism were differentially regulated specifically in the hippocampus. Of the cell death/survival genes found to be continuously upregulated only in hippocampus, the majority are pro-apoptotic, while those continuously upregulated only in cortex are anti-apoptotic. CONCLUSION: Temporal and spatial analysis of gene expression in experimental pneumococcal meningitis identified potential targets for therapy.

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PURPOSE: Identification of a novel rhodopsin mutation in a family with retinitis pigmentosa and comparison of the clinical phenotype to a known mutation at the same amino acid position. METHODS: Screening for mutations in rhodopsin was performed in 78 patients with retinitis pigmentosa. All exons and flanking intronic regions were amplified by PCR, sequenced, and compared to the reference sequence derived from the National Center for Biotechnology Information (NCBI, Bethesda, MD) database. Patients were characterized clinically according to the results of best corrected visual acuity testing (BCVA), slit lamp examination (SLE), funduscopy, Goldmann perimetry (GP), dark adaptometry (DA), and electroretinography (ERG). Structural analyses of the rhodopsin protein were performed with the Swiss-Pdb Viewer program available on-line (http://www.expasy.org.spdvbv/ provided in the public domain by Swiss Institute of Bioinformatics, Geneva, Switzerland). RESULTS: A novel rhodopsin mutation (Gly90Val) was identified in a Swiss family of three generations. The pedigree indicated autosomal dominant inheritance. No additional mutation was found in this family in other autosomal dominant genes. The BCVA of affected family members ranged from 20/25 to 20/20. Fundus examination showed fine pigment mottling in patients of the third generation and well-defined bone spicules in patients of the second generation. GP showed concentric constriction. DA demonstrated monophasic cone adaptation only. ERG revealed severely reduced rod and cone signals. The clinical picture is compatible with retinitis pigmentosa. A previously reported amino acid substitution at the same position in rhodopsin leads to a phenotype resembling night blindness in mutation carriers, whereas patients reported in the current study showed the classic retinitis pigmentosa phenotype. The effect of different amino acid substitutions on the three-dimensional structure of rhodopsin was analyzed by homology modeling. Distinct distortions of position 90 (shifts in amino acids 112 and 113) and additional hydrogen bonds were found. CONCLUSIONS: Different amino acid substitutions at position 90 of rhodopsin can lead to night blindness or retinitis pigmentosa. The data suggest that the property of the substituted amino acid distinguishes between the phenotypes.

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BACKGROUND: Gene expression analysis has emerged as a major biological research area, with real-time quantitative reverse transcription PCR (RT-QPCR) being one of the most accurate and widely used techniques for expression profiling of selected genes. In order to obtain results that are comparable across assays, a stable normalization strategy is required. In general, the normalization of PCR measurements between different samples uses one to several control genes (e.g. housekeeping genes), from which a baseline reference level is constructed. Thus, the choice of the control genes is of utmost importance, yet there is not a generally accepted standard technique for screening a large number of candidates and identifying the best ones. RESULTS: We propose a novel approach for scoring and ranking candidate genes for their suitability as control genes. Our approach relies on publicly available microarray data and allows the combination of multiple data sets originating from different platforms and/or representing different pathologies. The use of microarray data allows the screening of tens of thousands of genes, producing very comprehensive lists of candidates. We also provide two lists of candidate control genes: one which is breast cancer-specific and one with more general applicability. Two genes from the breast cancer list which had not been previously used as control genes are identified and validated by RT-QPCR. Open source R functions are available at http://www.isrec.isb-sib.ch/~vpopovic/research/ CONCLUSION: We proposed a new method for identifying candidate control genes for RT-QPCR which was able to rank thousands of genes according to some predefined suitability criteria and we applied it to the case of breast cancer. We also empirically showed that translating the results from microarray to PCR platform was achievable.

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BACKGROUND: The mollicute Mycoplasma conjunctivae is the etiological agent leading to infectious keratoconjunctivitis (IKC) in domestic sheep and wild caprinae. Although this pathogen is relatively benign for domestic animals treated by antibiotics, it can lead wild animals to blindness and death. This is a major cause of death in the protected species in the Alps (e.g., Capra ibex, Rupicapra rupicapra). METHODS: The genome was sequenced using a combined technique of GS-FLX (454) and Sanger sequencing, and annotated by an automatic pipeline that we designed using several tools interconnected via PERL scripts. The resulting annotations are stored in a MySQL database. RESULTS: The annotated sequence is deposited in the EMBL database (FM864216) and uploaded into the mollicutes database MolliGen http://cbi.labri.fr/outils/molligen/ allowing for comparative genomics. CONCLUSION: We show that our automatic pipeline allows for annotating a complete mycoplasma genome and present several examples of analysis in search for biological targets (e.g., pathogenic proteins).

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BACKGROUND Aeromonas salmonicida subsp. salmonicida, the etiologic agent of furunculosis, is a major pathogen of fisheries worldwide. Several virulence factors have been described, but the type-three secretion system (T3SS) is recognized as having a major effect on virulence by injecting effectors directly into fish cells. In this study we used high-throughput proteomics to display the differences between in vitro secretome of A. salmonicida wild-type (wt, hypervirulent, JF2267) and T3SS-deficient (isogenic ΔascV, extremely low-virulent, JF2747) strains in exponential and stationary phases of growth. RESULTS Results confirmed the secretion of effectors AopH, AexT, AopP and AopO via T3SS, and for the first time demonstrated the impact of T3SS in secretion of Ati2, AopN and ExsE that are known as effectors in other pathogens. Translocators, needle subunits, Ati1, and AscX were also secreted in supernatants (SNs) dependent on T3SS. AopH, Ati2, AexT, AopB and AopD were in the top seven most abundant excreted proteins. EF-G, EF-Tu, DnaK, HtpG, PNPase, PepN and MdeA were moderately secreted in wt SNs and predicted to be putative T3 effectors by bioinformatics. Pta and ASA_P5G088 were increased in wt SNs and T3-associated in other bacteria. Ten conserved cytoplasmic proteins were more abundant in wt SNs than in the ΔascV mutant, but without any clear association to a secretion system. T1-secreted proteins were predominantly found in wt SNs: OmpAI, OmpK40, DegQ, insulinase ASA_0716, hypothetical ASA_0852 and ASA_3619. Presence of T3SS components in pellets was clearly decreased by ascV deletion, while no impact was observed on T1- and T2SS. Our results demonstrated that the ΔascV mutant strain excreted well-described (VapA, AerA, AerB, GCAT, Pla1, PlaC, TagA, Ahe2, GbpA and enolase) and yet uncharacterized potential toxins, adhesins and enzymes as much as or even more than the wt strain. Other putative important virulence factors were not detected. CONCLUSIONS We demonstrated the whole in vitro secretome and T3SS repertoire of hypervirulent A. salmonicida. Several toxins, adhesins and enzymes that are not part of the T3SS secretome were secreted to a higher extent in the extremely low-virulent ΔascV mutant. All together, our results show the high importance of an intact T3SS to initiate the furunculosis and offer new information about the pathogenesis.

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Vector control is the mainstay of malaria control programmes. Successful vector control profoundly relies on accurate information on the target mosquito populations in order to choose the most appropriate intervention for a given mosquito species and to monitor its impact. An impediment to identify mosquito species is the existence of morphologically identical sibling species that play different roles in the transmission of pathogens and parasites. Currently PCR diagnostics are used to distinguish between sibling species. PCR based methods are, however, expensive, time-consuming and their development requires a priori DNA sequence information. Here, we evaluated an inexpensive molecular proteomics approach for Anopheles species: matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). MALDI-TOF MS is a well developed protein profiling tool for the identification of microorganisms but so far has received little attention as a diagnostic tool in entomology. We measured MS spectra from specimens of 32 laboratory colonies and 2 field populations representing 12 Anopheles species including the A. gambiae species complex. An important step in the study was the advancement and implementation of a bioinformatics approach improving the resolution over previously applied cluster analysis. Borrowing tools for linear discriminant analysis from genomics, MALDI-TOF MS accurately identified taxonomically closely related mosquito species, including the separation between the M and S molecular forms of A. gambiae sensu stricto. The approach also classifies specimens from different laboratory colonies; hence proving also very promising for its use in colony authentication as part of quality assurance in laboratory studies. While being exceptionally accurate and robust, MALDI-TOF MS has several advantages over other typing methods, including simple sample preparation and short processing time. As the method does not require DNA sequence information, data can also be reviewed at any later stage for diagnostic or functional patterns without the need for re-designing and re-processing biological material.

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In this paper, we propose novel methodologies for the automatic segmentation and recognition of multi-food images. The proposed methods implement the first modules of a carbohydrate counting and insulin advisory system for type 1 diabetic patients. Initially the plate is segmented using pyramidal mean-shift filtering and a region growing algorithm. Then each of the resulted segments is described by both color and texture features and classified by a support vector machine into one of six different major food classes. Finally, a modified version of the Huang and Dom evaluation index was proposed, addressing the particular needs of the food segmentation problem. The experimental results prove the effectiveness of the proposed method achieving a segmentation accuracy of 88.5% and recognition rate equal to 87%

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There is great demand for easily-accessible, user-friendly dietary self-management applications. Yet accurate, fully-automatic estimation of nutritional intake using computer vision methods remains an open research problem. One key element of this problem is the volume estimation, which can be computed from 3D models obtained using multi-view geometry. The paper presents a computational system for volume estimation based on the processing of two meal images. A 3D model of the served meal is reconstructed using the acquired images and the volume is computed from the shape. The algorithm was tested on food models (dummy foods) with known volume and on real served food. Volume accuracy was in the order of 90 %, while the total execution time was below 15 seconds per image pair. The proposed system combines simple and computational affordable methods for 3D reconstruction, remained stable throughout the experiments, operates in near real time, and places minimum constraints on users.

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FUS/TLS (fused in sarcoma/translocated in liposarcoma) is a ubiquitously expressed protein of the hnRNP family, that has been discovered as fused to transcription factors in several human sarcomas and found in protein aggregates in neurons of patients with an inherited form of Amyotrophic Lateral Sclerosis [Vance C. et al., 2009]. FUS is a 53 kDa nuclear protein that contains structural domains, such as a RNA Recognition Motif (RRM) and a zinc finger motif, that give to FUS the ability to bind to both RNA and DNA sequences. It has been implicated in a variety of cellular processes, such as pre-mRNA splicing, miRNA processing, gene expression control and transcriptional regulation [Fiesel FC. and Kahle PJ., 2011]. Moreover, some evidences link FUS to genome stability control and DNA damage response: mice lacking FUS are hypersensitive to ionizing radiation (IR) and show high levels of chromosome instability and, in response to double-strand breaks, FUS is phosphorylated by the protein kinase ATM [Kuroda M. et al., 2000; Hicks GG. et al., 2000; Gardiner M. et al., 2008]. Furthermore, preliminary results of mass spectrometric identification of FUS interacting proteins in HEK293 cells, expressing a recombinant flag-tagged FUS protein, highlighted the interactions with proteins involved in DNA damage response, such as DNA-PK, XRCC-5/-6, and ERCC-6, raising the possibilities that FUS is involved in this pathway, even though its role still needs to be clarified. This study aims to investigate the biological roles of FUS in human cells and in particular the putative role in DNA damage response through the characterization of the proteomic profile of the neuroblastoma cell line SH-SY5Y upon FUS inducible depletion, by a quantitative proteomic approach. The SH-SY5Y cell line that will be used in this study expresses, in presence of tetracycline, a shRNA that targets FUS mRNA, leading to FUS protein depletion (SH-SY5Y FUS iKD cells). To quantify changes in proteins expression levels a SILAC strategy (Stable Isotope Labeling by Amino acids in Cell culture) will be conducted on SH-SY5Y FUS iKD cells and a control SH-SY5Y cell line (that expresses a mock shRNA) and the relative changes in proteins levels will be evaluated after five and seven days upon FUS depletion, by nanoliquid chromatography coupled to tandem mass spectrometry (nLC-MS/MS) and bioinformatics analysis. Preliminary experiments demonstrated that the SH-SY5Y FUS iKD cells, when subjected to genotoxic stress (high dose of IR), upon inducible depletion of FUS, showed a increased phosphorylation of gH2AX with respect to control cells, suggesting an higher activation of the DNA damage response.

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AIM To characterize the subgingival microbiota within a cohort of adult males (n = 32) naïve to oral hygiene practices, and to compare the composition of bacterial taxa present in periodontal sites with various probing depths. MATERIAL AND METHODS Subgingival plaque samples were collected from single shallow pocket [pocket probing depth (PPD)≤3 mm] and deep pocket (PPD≥6 mm) sites from each subject. A polymerase chain reaction based strategy was used to construct a clone library of 16S ribosomal RNA (rRNA) genes for each site. The sequences of ca. 30-60 plasmid clones were determined for each site to identify resident taxa. Microbial composition was compared using a variety of statistical and bioinformatics approaches. RESULTS A total of 1887 cloned 16S rRNA gene sequences were analysed, which were assigned to 318 operational taxonomic units (98% identity cut-off). The subgingival microbiota was dominated by Firmicutes (69.8%), Proteobacteria (16.3%), and Fusobacteria (8.0%). The overall composition of microbial communities in shallow sites was significantly different from those within deep sites (∫-Libshuff, p < 0.001). CONCLUSIONS A taxonomically diverse subgingival microbiota was present within this cohort; however, the structures of the microbial communities present in the respective subjects exhibited limited variation. Deep and shallow sites contained notably different microbial compositions, but this was not correlated with the rate of periodontal progression.

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DNA testing is available for a growing number of hereditary diseases in neurology and other specialties. In addition to guiding breeding decisions, DNA tests are important tools in the diagnosis of diseases, particularly in conditions for which clinical signs are relatively nonspecific. DNA testing also can provide valuable insight into the risk of hereditary disease when decisions about treating comorbidities are being made. Advances in technology and bioinformatics will make broad screening for potential disease-causing mutations available soon. As DNA tests come into more common use, it is critical that clinicians understand the proper application and interpretation of these test results.