Search results for "proteomics."

showing 10 items of 523 documents

Combined omics approaches reveal distinct responses between light and heavy rare earth elements in Saccharomyces cerevisiae

2022

International audience; The rapid development of green energy sources and new medical technologies contributes to the increased exploitation of rare earth elements (REEs). They can be subdivided into light (LREEs) and heavy (HREEs) REEs. Mining, industrial processing, and end-use practices of REEs has led to elevated environmental concentrations and raises concerns about their toxicity to organisms and their impact on ecosystems. REE toxicity has been reported, but its precise underlying molecular effects have not been well described. Here, transcriptomic and proteomic approaches were combined to decipher the molecular responses of the model organism Saccharomyces cerevisiae to La (LREE) an…

Environmental EngineeringlanthanumKey genesHealth Toxicology and Mutagenesis[SDV]Life Sciences [q-bio]ved/biology.organism_classification_rank.speciesSaccharomyces cerevisiaeRare earthSaccharomyces cerevisiaeComputational biology010501 environmental sciences01 natural sciencesMiningTranscriptome03 medical and health sciencesHuman healthtranscriptomicsproteomicsLanthanidesHumansEnvironmental ChemistryModel organismWaste Management and DisposalEcosystem030304 developmental biology0105 earth and related environmental sciences0303 health sciencesbiologyved/biologyChemistryytterbiumbiology.organism_classificationPollutionREEs13. Climate action[SDE]Environmental Sciencescell wallMetals Rare EarthSignalling pathways
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Positioning Europe for the EPITRANSCRIPTOMICS challenge

2018

WOS: 000444092300018 PubMed ID: 29671387 The genetic alphabet consists of the four letters: C, A, G, and T in DNA and C,A,G, and U in RNA. Triplets of these four letters jointly encode 20 different amino acids out of which proteins of all organisms are built. This system is universal and is found in all kingdoms of life. However, bases in DNA and RNA can be chemically modified. In DNA, around 10 different modifications are known, and those have been studied intensively over the past 20years. Scientific studies on DNA modifications and proteins that recognize them gave rise to the large field of epigenetic and epigenomic research. The outcome of this intense research field is the discovery t…

Epigenomics0301 basic medicine[SDV]Life Sciences [q-bio]Gene ExpressionDetection of RNA ModificationEpigenesis GeneticTranscriptomechemistry.chemical_compoundEcologyEvolution & EthologyNeoplasmsRNA NeoplasmEuropean FundingComputingMilieux_MISCELLANEOUSRNA Neoplasm/geneticsEpitranscriptomicsEpigenomicsStem CellsDNA NeoplasmNeoplasms/genetics[SDV] Life Sciences [q-bio]EuropeGene Expression Regulation NeoplasticDetection of RNA modificationGenetics & GenomicsComputational biologyBiologyBiochemistry & ProteomicsENCODE03 medical and health sciencesEpigenomics/standardsEpitranscriptomicsModel systemsHumansEpigeneticsDatabase of ModificationDNA Neoplasm/geneticsMolecular BiologyComputational & Systems BiologyEuropean funding[SDV.GEN]Life Sciences [q-bio]/GeneticsGene Expression ProfilingFOS: Clinical medicineNeurosciencesModel SystemsRNACell Biology030104 developmental biologychemistryGene Expression Profiling/methodsAlphabetTranscriptomeDNARNA Biology
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Network pharmacology of cancer: From understanding of complex interactomes to the design of multi-target specific therapeutics from nature

2015

Despite massive investments in drug research and development, the significant decline in the number of new drugs approved or translated to clinical use raises the question, whether single targeted drug discovery is the right approach. To combat complex systemic diseases that harbour robust biological networks such as cancer, single target intervention is proved to be ineffective. In such cases, network pharmacology approaches are highly useful, because they differ from conventional drug discovery by addressing the ability of drugs to target numerous proteins or networks involved in a disease. Pleiotropic natural products are one of the promising strategies due to their multi-targeting and d…

EpigenomicsProteomics0301 basic medicineDrugmedia_common.quotation_subjectSystems biologyGene regulatory networkSynthetic lethalityDiseaseComputational biologyBiologyPharmacology03 medical and health sciencesNeoplasmsDrug DiscoveryBiomarkers TumormedicineAnimalsHumansMetabolomicsGene Regulatory NetworksMolecular Targeted TherapyProtein Interaction Mapsmedia_commonPharmacologyPlants MedicinalDrug discoveryGene Expression ProfilingSystems BiologyCancermedicine.diseaseAntineoplastic Agents PhytogenicGene Expression Regulation Neoplastic030104 developmental biologyBiological networkPhytotherapySignal TransductionPharmacological Research
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Fibroblast’s role in breast cancer: a proteomic approach

2008

Fibroblasts are the major mesenchymal cell types committed to the matrix formation and renewal. Moreover they are the main source of paracrine factors that influence the growth of epithelial cells of neighbouring tissues. For these properties they may be involved in tumourigenesis, either by remodelling the tumor-associated extracellular matrix (ECM), and by the production of paracrine factors that influence the growth of carcinoma cells. Studies on fibroblasts associated to carcinomas have documented their phenotypic modifications, including abnormal migratory behaviour in vitro and growth factors altered expression(Schor & Schor, 2001). In addition, fibroblasts often recruit inflammat…

Fibroblasts proteomics breast cancerfibroblast breast cancerSettore BIO/06 - Anatomia Comparata E Citologia
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Evaluating the Hypoxia Response of Ruffe and Flounder Gills by a Combined Proteome and Transcriptome Approach

2015

Hypoxia has gained ecological importance during the last decades, and it is the most dramatically increasing environmental factor in coastal areas and estuaries. The gills of fish are the prime target of hypoxia and other stresses. Here we have studied the impact of the exposure to hypoxia (1.5 mg O2/l for 48 h) on the protein expression of the gills of two estuarine fish species, the ruffe (Gymnocephalus cernua) and the European flounder (Platichthys flesus). First, we obtained the transcriptomes of mixed tissues (gills, heart and brain) from both species by Illumina next-generation sequencing. Then, the gill proteomes were investigated using two-dimensional gel electrophoresis and mass sp…

Fish ProteinsGillsProteomicsGillProteomelcsh:MedicineFlounderFlounderBiologyBioinformaticsFish ProteinsProteomicsTranscriptomeFish physiologyDatabases GeneticAnimalsEUROPEAN FLOUNDERHypoxialcsh:ScienceGeneticsMultidisciplinarylcsh:Rbiology.organism_classificationProteomelcsh:QTranscriptomeResearch ArticlePLOS ONE
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Insects’ potential: Understanding the functional role of their gut microbiome

2021

The study of insect-associated microbial communities is a field of great importance in agriculture, principally because of the role insects play as pests. In addition, there is a recent focus on the potential of the insect gut microbiome in areas such as biotechnology, given some microorganisms produce molecules with biotechnological and industrial applications, and also in biomedicine, since some bacteria and fungi are a reservoir of antibiotic resistance genes (ARGs). To date, most studies aiming to characterize the role of the gut microbiome of insects have been based on high-throughput sequencing of the 16S rRNA gene and/or metagenomics. However, recently functional approaches such as m…

Functional roleInsectaClinical BiochemistryPharmaceutical ScienceComputational biology01 natural sciencesAnalytical ChemistryMetabolomicsRNA Ribosomal 16SDrug DiscoveryAnimalsSpectroscopyBiomedicine010405 organic chemistrybusiness.industryChemistryMicrobiota010401 analytical chemistryGut microbiomeGastrointestinal Microbiome0104 chemical sciencesMetagenomicsMetaproteomicsMetagenomicsbusinessAntibiotic resistance genesJournal of Pharmaceutical and Biomedical Analysis
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Proteomic analysis of the photosystem I light-harvesting antenna in tomato (Lycopersicon esculentum).

2004

Until now, more genes of the light-harvesting antenna of higher-plant photosystem I (PSI) than proteins have been described. To improve our understanding of the composition of light-harvesting complex I (LHCI) of tomato (Lycopersicon esculentum), we combined one- and two-dimensional (1-D and 2-D, respectively) gel electrophoresis with immunoblotting and tandem mass spectrometry (MS/ MS). Separation of PSI with high-resolution 1-D gels allowed separation of five bands attributed to proteins of LHCI. Immunoblotting with monospecific antibodies and MS/MS analysis enabled the correct assignment of the four prominent bands to light-harvesting proteins Lhcal -4. The fifth band was recognized by o…

Gel electrophoresisGene isoformElectrophoresisProteomicsChromatographybiologyPhotosystem I Protein ComplexImmunoblottingMolecular Sequence DataLight-Harvesting Protein ComplexesContext (language use)Tandem mass spectrometrybiology.organism_classificationPhotosystem IBiochemistryLycopersiconMass SpectrometryIsoelectric pointBiochemistrySolanum lycopersicumSequence Analysis ProteinProtein IsoformsAmino Acid SequencePhotosystemBiochemistry
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Influence ofKi-ras-driven oncogenic transformation on the protein network of murine fibroblasts

2007

Ki-ras gene mutations that specifically occur in codons 12, 13 and 61 are involved in the carcinogenesis of acute myeloid leukemia, melanoma and different carcinomas. In order to define potential mutation-specific therapeutic targets, stable transfectants of NIH3T3 cells carrying different Ki-ras4B gene mutations were generated. Wild type Ki-ras transformants, mock transfectants and parental cells served as controls. These in vitro model systems were systematically analyzed for their protein expression pattern using two-dimensional gel electrophoresis followed by mass spectrometry and/or protein sequencing. Using this approach, a number of target molecules that are differentially but coordi…

Gel electrophoresismedicine.diagnostic_testWild typeFibroblastsBiologyGene mutationTransfectionmedicine.disease_causeProteomicsBiochemistryMolecular biologyMiceCell Transformation NeoplasticWestern blotHeat shock proteinNIH 3T3 Cellsras ProteinsmedicineAnimalsMitogen-Activated Protein KinasesCarcinogenesisMolecular BiologyGeneSignal TransductionPROTEOMICS
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p63 Isoforms Regulate Metabolism of Cancer Stem Cells

2014

p63 is an important regulator of epithelial development expressed in different variants containing (TA) or lacking (ΔN) the N-terminal transactivation domain. The different isoforms regulate stem-cell renewal and differentiation as well as cell senescence. Several studies indicate that p63 isoforms also play a role in cancer development; however, very little is known about the role played by p63 in regulating the cancer stem phenotype. Here we investigate the cellular signals regulated by TAp63 and ΔNp63 in a model of epithelial cancer stem cells. To this end, we used colon cancer stem cells, overexpressing either TAp63 or ΔNp63 isoforms, to carry out a proteomic study by chemical-labeling …

Gene isoformProteomicsProteomeRegulatorBiologyProteomicsBiochemistryTransactivationCancer stem cellmedicineHumansMetabolomicsProtein IsoformsProtein Interaction MapsSettore BIO/10 - BIOCHIMICAp63 colon cancer stem cells proteomics stable isotope dimethyl labeling glucose metabolismSettore BIO/12Tumor Suppressor ProteinsCancerGeneral Chemistrymedicine.diseasePhenotypePeptide FragmentsCell biologyIsotope LabelingNeoplastic Stem CellsStem cellSignal TransductionTranscription Factors
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MGFM: a novel tool for detection of tissue and cell specific marker genes from microarray gene expression data

2015

Background Identification of marker genes associated with a specific tissue/cell type is a fundamental challenge in genetic and cell research. Marker genes are of great importance for determining cell identity, and for understanding tissue specific gene function and the molecular mechanisms underlying complex diseases. Results We have developed a new bioinformatics tool called MGFM (Marker Gene Finder in Microarray data) to predict marker genes from microarray gene expression data. Marker genes are identified through the grouping of samples of the same type with similar marker gene expression levels. We verified our approach using two microarray data sets from the NCBI’s Gene Expression Omn…

Genetic MarkersCancer ResearchMicroarraysBiologyMarker genesWeb BrowserProteomicsMarker geneBioconductorGeneticsGeneGenetic Association StudiesGeneticsMicroarray analysis techniquesMethodology ArticleGene Expression ProfilingComputational BiologyReproducibility of Results3. Good healthGene expression profilingSamplesGene OntologyGenetic markerOrgan SpecificityDNA microarrayBiotechnologyBMC Genomics
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