Search results for "METAGENOMIC"

showing 10 items of 177 documents

The Generalist Inside the Specialist: Gut Bacterial Communities of Two Insect Species Feeding on Toxic Plants Are Dominated by Enterococcus sp.

2016

Some specialist insects feed on plants rich in secondary compounds, which pose a major selective pressure on both the phytophagous and the gut microbiota. However, microbial communities of toxic plant feeders are still poorly characterized. Here, we show the bacterial communities of the gut of two specialized Lepidoptera, Hyles euphorbiae and Brithys crini, which exclusively feed on latex-rich Euphorbia sp. and alkaloid-rich Pancratium maritimum, respectively. A metagenomic analysis based on high-throughput sequencing of the 16S rRNA gene revealed that the gut microbiota of both insects is dominated by the phylum Firmicutes, and especially by the common gut inhabitant Enterococcus sp. Staph…

0301 basic medicineMicrobiology (medical)media_common.quotation_subject030106 microbiologyInsectGut floraGeneralist and specialist speciesMicrobiologyMicrobiologyGut communities03 medical and health sciencesHyles euphorbiaeEnterococcus casseliflavusEnterococcus sp.Original Researchmedia_commonmetagenomicsLarvabiologysecondary metabolitesgut communitiesSecondary metabolitesfungiBiofilmbiology.organism_classificationLepidoptera030104 developmental biology: lepidopteraMetagenomicsBacteriaFrontiers in Microbiology
researchProduct

Neanderthal behaviour, diet, and disease inferred from ancient DNA in dental calculus

2017

Weyrich, Laura S. et al.

0301 basic medicineNeanderthalTime Factorsved/biology.organism_classification_rank.speciesneanderthal01 natural sciencesGenomeBelgiumWoolly rhinocerosCalculusDental CalculusHistory AncientNeanderthalsMultidisciplinarygeography.geographical_feature_categoryStomachCarnivoryMouflonIntestinesCavesHealthVegetarians010506 paleontologyMeatPan troglodytesBiologyMethanobrevibacter03 medical and health sciencesFood PreferencesCavebiology.animalAnimalsHumansDNA AncientSymbiosisancient DNAPerissodactyla0105 earth and related environmental sciencesgeographyMouthSheepved/biologyPenicilliumEnterocytozoonbiology.organism_classificationDietstomatognathic diseases030104 developmental biologyAncient DNAMetagenomicsSpainMethanobrevibacter oralisGenome Bacterial
researchProduct

Recommendations for the introduction of metagenomic high-throughput sequencing in clinical virology, part I: Wet lab procedure

2020

Metagenomic high-throughput sequencing (mHTS) is a hypothesis-free, universal pathogen detection technique for determination of the DNA/RNA sequences in a variety of sample types and infectious syndromes. mHTS is still in its early stages of translating into clinical application. To support the development, implementation and standardization of mHTS procedures for virus diagnostics, the European Society for Clinical Virology (ESCV) Network on Next-Generation Sequencing (ENNGS) has been established. The aim of ENNGS is to bring together professionals involved in mHTS for viral diagnostics to share methodologies and experiences, and to develop application recommendations. This manuscript aims…

0301 basic medicinePathogen detectionStandardizationComputer science030106 microbiologyRecommendationsINFLUENZA-A VIRUSDIAGNOSISVALIDATIONDNA sequencing03 medical and health sciences0302 clinical medicineSDG 3 - Good Health and Well-beingVirologyWet labViral metagenomics030212 general & internal medicine11832 Microbiology and virologyLaboratory methodsHigh-throughput sequencingQuality assessmentNetwork onHigh-Throughput Nucleotide SequencingDNAEFFICIENT TRANSLATIONData science3. Good healthInfectious DiseasesMetagenomicsVirusesNext-generation sequencing3111 BiomedicineMetagenomicsDEPLETIONMESSENGER-RNAClinical virologyPATHOGEN DETECTIONJournal of Clinical Virology
researchProduct

Oxidative stress in the oral cavity is driven by individualspecific bacterial communities

2018

The term “bacterial dysbiosis” is being used quite extensively in metagenomic studies, however, the identification of harmful bacteria often fails due to large overlap between the bacterial species found in healthy volunteers and patients. We hypothesized that the pathogenic oral bacteria are individual-specific and they correlate with oxidative stress markers in saliva which reflect the inflammatory processes in the oral cavity. Temporally direct and lagged correlations between the markers and bacterial taxa were computed individually for 26 volunteers who provided saliva samples during one month (21.2 ± 2.7 samples/volunteer, 551 samples in total). The volunteers’ microbiomes differed sig…

0301 basic medicineSalivaACID REACTING SUBSTANCES030106 microbiologyPhysiologyDiseasemedicine.disease_causeApplied Microbiology and BiotechnologyMicrobiologylcsh:Microbial ecologyArticle03 medical and health sciencesmedicineMicrobiomeGENE-EXPRESSIONTOTAL ANTIOXIDANT CAPACITYScience & TechnologyDENTAL-CARIESPLASMASTABILITYbiologybiology.organism_classificationmedicine.diseaseSALIVARY MARKERSSTREPTOCOCCUS-MUTANSStreptococcus mutansMICROBIOME030104 developmental biologyBiotechnology & Applied MicrobiologyMetagenomicslcsh:QR100-130Life Sciences & BiomedicineDysbiosisRESISTANCEBacteriaOxidative stressBiotechnology
researchProduct

Health and Disease Imprinted in the Time Variability of the Human Microbiome

2017

The human microbiota correlates closely with the health status of its host. This article analyzes the microbial composition of several subjects under different conditions over time spans that ranged from days to months. Using the Langevin equation as the basis of our mathematical framework to evaluate microbial temporal stability, we proved that stable microbiotas can be distinguished from unstable microbiotas. This initial step will help us to determine how temporal microbiota stability is related to a subject’s health status and to develop a more comprehensive framework that will provide greater insight into this complex system.

0301 basic medicineScaling lawPhysiologySystems biologyPopulationlcsh:QR1-502microbiomeDiseaseGut floraBiochemistryMicrobiologylcsh:MicrobiologyHost-Microbe Biology03 medical and health sciences0302 clinical medicineGeneticsMicrobiomeeducationMolecular BiologyEcology Evolution Behavior and Systematicseducation.field_of_studymetagenomicsbiologyHuman microbiomesystems biologystabilitybiology.organism_classificationEditor's PickQR1-502Computer Science Applications030104 developmental biologyEvolutionary biologyMetagenomicsModeling and Simulationecological modeling030217 neurology & neurosurgeryResearch ArticlemSystems
researchProduct

2019

With the rise of Next-Generation-Sequencing (NGS) methods, Micro-RNAs (miRNAs) have achieved an important position in the research landscape and have been found to present valuable diagnostic tools in various diseases such as multiple sclerosis or lung cancer. There is also emerging evidence that miRNAs play an important role in the pathogenesis of neurodegenerative diseases such as Alzheimer's disease (AD) or Parkinson's disease (PD). Apparently, these diseases come along with changes in miRNA expression patterns which led to attempts from researchers to use these small RNA species from several body fluids for a better diagnosis and in order to observe disease progression. Additionally, it…

0301 basic medicineSmall RNAbiologyGeneral NeuroscienceIn silicoNeurodegenerationDiseaseComputational biologyGut floramedicine.diseasebiology.organism_classification03 medical and health sciences030104 developmental biology0302 clinical medicineMetagenomicsmicroRNAmedicineMicrobiome030217 neurology & neurosurgeryFrontiers in Neuroscience
researchProduct

MetaCache: context-aware classification of metagenomic reads using minhashing.

2017

Abstract Motivation Metagenomic shotgun sequencing studies are becoming increasingly popular with prominent examples including the sequencing of human microbiomes and diverse environments. A fundamental computational problem in this context is read classification, i.e. the assignment of each read to a taxonomic label. Due to the large number of reads produced by modern high-throughput sequencing technologies and the rapidly increasing number of available reference genomes corresponding software tools suffer from either long runtimes, large memory requirements or low accuracy. Results We introduce MetaCache—a novel software for read classification using the big data technique minhashing. Our…

0301 basic medicineStatistics and ProbabilityComputer scienceSequence analysisContext (language use)BiochemistryGenome03 medical and health scienceschemistry.chemical_compound0302 clinical medicineRefSeqHumansMolecular BiologyInformation retrievalShotgun sequencingHigh-Throughput Nucleotide SequencingSequence Analysis DNAComputer Science ApplicationsComputational Mathematics030104 developmental biologyComputational Theory and MathematicschemistryMetagenomicsMetagenomics030217 neurology & neurosurgeryDNAAlgorithmsSoftwareReference genomeBioinformatics (Oxford, England)
researchProduct

AFS: identification and quantification of species composition by metagenomic sequencing

2017

Abstract Summary DNA-based methods to detect and quantify taxon composition in biological materials are often based on species-specific polymerase chain reaction, limited to detecting species targeted by the assay. Next-generation sequencing overcomes this drawback by untargeted shotgun sequencing of whole metagenomes at affordable cost. Here we present AFS, a software pipeline for quantification of species composition in food. AFS uses metagenomic shotgun sequencing and sequence read counting to infer species proportions. Using Illumina data from a reference sausage comprising four species, we reveal that AFS is independent of the sequencing assay and library preparation protocol. Cost-sav…

0301 basic medicineStatistics and ProbabilitySequence analysisLibrary preparationComputational biologyBiologyBioinformaticsBiochemistrylaw.invention03 medical and health sciences0404 agricultural biotechnologylawMolecular BiologyPolymerase chain reactionShotgun sequencingHigh-Throughput Nucleotide SequencingSequence Analysis DNA04 agricultural and veterinary sciencesAccession number (bioinformatics)040401 food scienceBiological materialsComputer Science ApplicationsComputational Mathematics030104 developmental biologyComputational Theory and MathematicsMetagenomicsFood MicrobiologyIdentification (biology)MetagenomicsSoftwareBioinformatics
researchProduct

Accelerating metagenomic read classification on CUDA-enabled GPUs.

2016

Metagenomic sequencing studies are becoming increasingly popular with prominent examples including the sequencing of human microbiomes and diverse environments. A fundamental computational problem in this context is read classification; i.e. the assignment of each read to a taxonomic label. Due to the large number of reads produced by modern high-throughput sequencing technologies and the rapidly increasing number of available reference genomes software tools for fast and accurate metagenomic read classification are urgently needed. We present cuCLARK, a read-level classifier for CUDA-enabled GPUs, based on the fast and accurate classification of metagenomic sequences using reduced k-mers (…

0301 basic medicineTheoretical computer scienceWorkstationGPUsComputer scienceContext (language use)CUDAParallel computingBiochemistryGenomelaw.invention03 medical and health sciencesCUDAUser-Computer Interface0302 clinical medicineStructural BiologylawTaxonomic assignmentHumansMicrobiomeMolecular BiologyInternetXeonApplied MathematicsHigh-Throughput Nucleotide SequencingSequence Analysis DNAExact k-mer matchingComputer Science Applications030104 developmental biologyTitan (supercomputer)Metagenomics030220 oncology & carcinogenesisMetagenomicsDNA microarraySoftwareBMC bioinformatics
researchProduct

Deep learning models for bacteria taxonomic classification of metagenomic data.

2018

Background An open challenge in translational bioinformatics is the analysis of sequenced metagenomes from various environmental samples. Of course, several studies demonstrated the 16S ribosomal RNA could be considered as a barcode for bacteria classification at the genus level, but till now it is hard to identify the correct composition of metagenomic data from RNA-seq short-read data. 16S short-read data are generated using two next generation sequencing technologies, i.e. whole genome shotgun (WGS) and amplicon (AMP); typically, the former is filtered to obtain short-reads belonging to a 16S shotgun (SG), whereas the latter take into account only some specific 16S hypervariable regions.…

0301 basic medicineTime FactorsDBNComputer scienceBiochemistryStructural BiologyRNA Ribosomal 16SDatabases Geneticlcsh:QH301-705.5Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazionibiologySettore INF/01 - InformaticaShotgun sequencingApplied MathematicsAmpliconClassificationComputer Science Applicationslcsh:R858-859.7DNA microarrayShotgunAlgorithmsCNN030106 microbiologyk-mer representationlcsh:Computer applications to medicine. Medical informaticsDNA sequencing03 medical and health sciencesMetagenomicDeep LearningMolecular BiologyBacteriaModels GeneticPhylumbusiness.industryDeep learningResearchReproducibility of ResultsPattern recognitionBiological classification16S ribosomal RNAbiology.organism_classificationAmpliconHypervariable region030104 developmental biologyTaxonlcsh:Biology (General)MetagenomicsMetagenomeArtificial intelligenceMetagenomicsNeural Networks ComputerbusinessClassifier (UML)BacteriaBMC bioinformatics
researchProduct