Academic literature on the topic 'Human metagenomic'
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Journal articles on the topic "Human metagenomic"
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Nalbantoglu, O. Ufuk. "Information Theoretic Metagenome Assembly Allows the Discovery of Disease Biomarkers in Human Microbiome." Entropy 23, no. 2 (February 2, 2021): 187. http://dx.doi.org/10.3390/e23020187.
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Quantitative metagenomics is an important field that has delivered successful microbiome biomarkers associated with host phenotypes. The current convention mainly depends on unsupervised assembly of metagenomic contigs with a possibility of leaving interesting genetic material unassembled. Additionally, biomarkers are commonly defined on the differential relative abundance of compositional or functional units. Accumulating evidence supports that microbial genetic variations are as important as the differential abundance content, implying the need for novel methods accounting for the genetic variations in metagenomics studies. We propose an information theoretic metagenome assembly algorithm, discovering genomic fragments with maximal self-information, defined by the empirical distributions of nucleotides across the phenotypes and quantified with the help of statistical tests. Our algorithm infers fragments populating the most informative genetic variants in a single contig, named supervariant fragments. Experiments on simulated metagenomes, as well as on a colorectal cancer and an atherosclerotic cardiovascular disease dataset consistently discovered sequences strongly associated with the disease phenotypes. Moreover, the discriminatory power of these putative biomarkers was mainly attributed to the genetic variations rather than relative abundance. Our results support that a focus on metagenomics methods considering microbiome population genetics might be useful in discovering disease biomarkers with a great potential of translating to molecular diagnostics and biotherapeutics applications.
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Filipic, Brankica, Katarina Novovic, David J. Studholme, Milka Malesevic, Nemanja Mirkovic, Milan Kojic, and Branko Jovcic. "Shotgun metagenomics reveals differences in antibiotic resistance genes among bacterial communities in Western Balkans glacial lakes sediments." Journal of Water and Health 18, no. 3 (May 21, 2020): 383–97. http://dx.doi.org/10.2166/wh.2020.227.
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Abstract Long-term overuse of antibiotics has driven the propagation and spreading of antibiotic resistance genes (ARGs) such as efflux pumps in the environment, which can be transferred to clinically relevant pathogens. This study explored the abundance and diversity of ARGs and mobile genetic elements within bacterial communities from sediments of three Western Balkans glacial lakes: Plav Lake (high impact of human population), Black Lake (medium impact of human population) and Donje Bare Lake (remote lake, minimal impact of human population) via shotgun metagenomics. Assembled metagenomic sequences revealed that Resistance-Nodulation-Division (RND) efflux pumps genes were most abundant in metagenome from the Plav Lake. The Integron Finder bioinformatics tool detected 38 clusters of attC sites lacking integron-integrases (CALIN) elements: 20 from Plav Lake, four from Black Lake and 14 from Donje Bare Lake. A complete integron sequence was recovered only from the assembled metagenome from Plav Lake. Plasmid contents within the metagenomes were similar, with proportions of contigs being plasmid-related: 1.73% for Plav Lake, 1.59% for Black Lake and 1.64% for Donje Bare Lake. The investigation showed that RNDs and mobile genetic elements content correlated with human population impact.
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Bai, Geng-Hao, Sheng-Chieh Lin, Yi-Hsiang Hsu, and Shih-Yen Chen. "The Human Virome: Viral Metagenomics, Relations with Human Diseases, and Therapeutic Applications." Viruses 14, no. 2 (January 28, 2022): 278. http://dx.doi.org/10.3390/v14020278.
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The human body is colonized by a wide range of microorganisms. The field of viromics has expanded since the first reports on the detection of viruses via metagenomic sequencing in 2002. With the continued development of reference materials and databases, viral metagenomic approaches have been used to explore known components of the virome and discover new viruses from various types of samples. The virome has attracted substantial interest since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic. Increasing numbers of studies and review articles have documented the diverse virome in various sites in the human body, as well as interactions between the human host and the virome with regard to health and disease. However, there have been few studies of direct causal relationships. Viral metagenomic analyses often lack standard references and are potentially subject to bias. Moreover, most virome-related review articles have focused on the gut virome and did not investigate the roles of the virome in other sites of the body in human disease. This review presents an overview of viral metagenomics, with updates regarding the relations between alterations in the human virome and the pathogenesis of human diseases, recent findings related to COVID-19, and therapeutic applications related to the human virome.
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Simon, Carola, and Rolf Daniel. "Metagenomic Analyses: Past and Future Trends." Applied and Environmental Microbiology 77, no. 4 (December 17, 2010): 1153–61. http://dx.doi.org/10.1128/aem.02345-10.
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ABSTRACTMetagenomics has revolutionized microbiology by paving the way for a cultivation-independent assessment and exploitation of microbial communities present in complex ecosystems. Metagenomics comprising construction and screening of metagenomic DNA libraries has proven to be a powerful tool to isolate new enzymes and drugs of industrial importance. So far, the majority of the metagenomically exploited habitats comprised temperate environments, such as soil and marine environments. Recently, metagenomes of extreme environments have also been used as sources of novel biocatalysts. The employment of next-generation sequencing techniques for metagenomics resulted in the generation of large sequence data sets derived from various environments, such as soil, the human body, and ocean water. Analyses of these data sets opened a window into the enormous taxonomic and functional diversity of environmental microbial communities. To assess the functional dynamics of microbial communities, metatranscriptomics and metaproteomics have been developed. The combination of DNA-based, mRNA-based, and protein-based analyses of microbial communities present in different environments is a way to elucidate the compositions, functions, and interactions of microbial communities and to link these to environmental processes.
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Zorrilla, Francisco, Filip Buric, Kiran R. Patil, and Aleksej Zelezniak. "metaGEM: reconstruction of genome scale metabolic models directly from metagenomes." Nucleic Acids Research 49, no. 21 (October 6, 2021): e126-e126. http://dx.doi.org/10.1093/nar/gkab815.
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Abstract Metagenomic analyses of microbial communities have revealed a large degree of interspecies and intraspecies genetic diversity through the reconstruction of metagenome assembled genomes (MAGs). Yet, metabolic modeling efforts mainly rely on reference genomes as the starting point for reconstruction and simulation of genome scale metabolic models (GEMs), neglecting the immense intra- and inter-species diversity present in microbial communities. Here, we present metaGEM (https://github.com/franciscozorrilla/metaGEM), an end-to-end pipeline enabling metabolic modeling of multi-species communities directly from metagenomes. The pipeline automates all steps from the extraction of context-specific prokaryotic GEMs from MAGs to community level flux balance analysis (FBA) simulations. To demonstrate the capabilities of metaGEM, we analyzed 483 samples spanning lab culture, human gut, plant-associated, soil, and ocean metagenomes, reconstructing over 14,000 GEMs. We show that GEMs reconstructed from metagenomes have fully represented metabolism comparable to isolated genomes. We demonstrate that metagenomic GEMs capture intraspecies metabolic diversity and identify potential differences in the progression of type 2 diabetes at the level of gut bacterial metabolic exchanges. Overall, metaGEM enables FBA-ready metabolic model reconstruction directly from metagenomes, provides a resource of metabolic models, and showcases community-level modeling of microbiomes associated with disease conditions allowing generation of mechanistic hypotheses.
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Kasmanas, Jonas Coelho, Alexander Bartholomäus, Felipe Borim Corrêa, Tamara Tal, Nico Jehmlich, Gunda Herberth, Martin von Bergen, Peter F. Stadler, André Carlos Ponce de Leon Ferreira de Carvalho, and Ulisses Nunes da Rocha. "HumanMetagenomeDB: a public repository of curated and standardized metadata for human metagenomes." Nucleic Acids Research 49, no. D1 (November 22, 2020): D743—D750. http://dx.doi.org/10.1093/nar/gkaa1031.
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Abstract Metagenomics became a standard strategy to comprehend the functional potential of microbial communities, including the human microbiome. Currently, the number of metagenomes in public repositories is increasing exponentially. The Sequence Read Archive (SRA) and the MG-RAST are the two main repositories for metagenomic data. These databases allow scientists to reanalyze samples and explore new hypotheses. However, mining samples from them can be a limiting factor, since the metadata available in these repositories is often misannotated, misleading, and decentralized, creating an overly complex environment for sample reanalysis. The main goal of the HumanMetagenomeDB is to simplify the identification and use of public human metagenomes of interest. HumanMetagenomeDB version 1.0 contains metadata of 69 822 metagenomes. We standardized 203 attributes, based on standardized ontologies, describing host characteristics (e.g. sex, age and body mass index), diagnosis information (e.g. cancer, Crohn's disease and Parkinson), location (e.g. country, longitude and latitude), sampling site (e.g. gut, lung and skin) and sequencing attributes (e.g. sequencing platform, average length and sequence quality). Further, HumanMetagenomeDB version 1.0 metagenomes encompass 58 countries, 9 main sample sites (i.e. body parts), 58 diagnoses and multiple ages, ranging from just born to 91 years old. The HumanMetagenomeDB is publicly available at https://webapp.ufz.de/hmgdb/.
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Nayfach, Stephen, David Páez-Espino, Lee Call, Soo Jen Low, Hila Sberro, Natalia N. Ivanova, Amy D. Proal, et al. "Metagenomic compendium of 189,680 DNA viruses from the human gut microbiome." Nature Microbiology 6, no. 7 (June 24, 2021): 960–70. http://dx.doi.org/10.1038/s41564-021-00928-6.
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AbstractBacteriophages have important roles in the ecology of the human gut microbiome but are under-represented in reference databases. To address this problem, we assembled the Metagenomic Gut Virus catalogue that comprises 189,680 viral genomes from 11,810 publicly available human stool metagenomes. Over 75% of genomes represent double-stranded DNA phages that infect members of the Bacteroidia and Clostridia classes. Based on sequence clustering we identified 54,118 candidate viral species, 92% of which were not found in existing databases. The Metagenomic Gut Virus catalogue improves detection of viruses in stool metagenomes and accounts for nearly 40% of CRISPR spacers found in human gut Bacteria and Archaea. We also produced a catalogue of 459,375 viral protein clusters to explore the functional potential of the gut virome. This revealed tens of thousands of diversity-generating retroelements, which use error-prone reverse transcription to mutate target genes and may be involved in the molecular arms race between phages and their bacterial hosts.
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Rahman, Mohammad Arifur, and Huzefa Rangwala. "IDMIL: an alignment-free Interpretable Deep Multiple Instance Learning (MIL) for predicting disease from whole-metagenomic data." Bioinformatics 36, Supplement_1 (July 1, 2020): i39—i47. http://dx.doi.org/10.1093/bioinformatics/btaa477.
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Abstract Motivation The human body hosts more microbial organisms than human cells. Analysis of this microbial diversity provides key insight into the role played by these microorganisms on human health. Metagenomics is the collective DNA sequencing of coexisting microbial organisms in an environmental sample or a host. This has several applications in precision medicine, agriculture, environmental science and forensics. State-of-the-art predictive models for phenotype predictions from metagenomic data rely on alignments, assembly, extensive pruning, taxonomic profiling and reference sequence databases. These processes are time consuming and they do not consider novel microbial sequences when aligned with the reference genome, limiting the potential of whole metagenomics. We formulate the problem of predicting human disease from whole-metagenomic data using Multiple Instance Learning (MIL), a popular supervised learning paradigm. Our proposed alignment-free approach provides higher accuracy in prediction by harnessing the capability of deep convolutional neural network (CNN) within a MIL framework and provides interpretability via neural attention mechanism. Results The MIL formulation combined with the hierarchical feature extraction capability of deep-CNN provides significantly better predictive performance compared to popular existing approaches. The attention mechanism allows for the identification of groups of sequences that are likely to be correlated to diseases providing the much-needed interpretation. Our proposed approach does not rely on alignment, assembly and reference sequence databases; making it fast and scalable for large-scale metagenomic data. We evaluate our method on well-known large-scale metagenomic studies and show that our proposed approach outperforms comparative state-of-the-art methods for disease prediction. Availability and implementation https://github.com/mrahma23/IDMIL.
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Jaiani, Ekaterine, Ia Kusradze, Tamar Kokashvili, Natia Geliashvili, Nino Janelidze, Adam Kotorashvili, Nato Kotaria, Archil Guchmanidze, Marina Tediashvili, and David Prangishvili. "Microbial Diversity and Phage–Host Interactions in the Georgian Coastal Area of the Black Sea Revealed by Whole Genome Metagenomic Sequencing." Marine Drugs 18, no. 11 (November 14, 2020): 558. http://dx.doi.org/10.3390/md18110558.
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Viruses have the greatest abundance and highest genetic diversity in marine ecosystems. The interactions between viruses and their hosts is one of the hot spots of marine ecology. Besides their important role in various ecosystems, viruses, especially bacteriophages and their gene pool, are of enormous interest for the development of new gene products with high innovation value. Various studies have been conducted in diverse ecosystems to understand microbial diversity and phage–host interactions; however, the Black Sea, especially the Eastern coastal area, remains among the least studied ecosystems in this regard. This study was aimed at to fill this gap by analyzing microbial diversity and bacteriophage–host interactions in the waters of Eastern Black Sea using a metagenomic approach. To this end, prokaryotic and viral metagenomic DNA from two sampling sites, Poti and Gonio, were sequenced on the Illumina Miseq platform and taxonomic and functional profiles of the metagenomes were obtained using various bioinformatics tools. Our metagenomics analyses allowed us to identify the microbial communities, with Proteobacteria, Cyanobacteria, Actinibacteria, and Firmicutes found to be the most dominant bacterial phyla and Synechococcus and Candidatus Pelagibacter phages found to be the most dominant viral groups in the Black Sea. As minor groups, putative phages specific to human pathogens were identified in the metagenomes. We also characterized interactions between the phages and prokaryotic communities by determining clustered regularly interspaced short palindromic repeats (CRISPR), prophage-like sequences, and integrase/excisionase sequences in the metagenomes, along with identification of putative horizontally transferred genes in the viral contigs. In addition, in the viral contig sequences related to peptidoglycan lytic activity were identified as well. This is the first study on phage and prokaryote diversity and their interactions in the Eastern coastal area of the Black Sea using a metagenomic approach.
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Liu, Michael Y., Paul Worden, Leigh G. Monahan, Matthew Z. DeMaere, Catherine M. Burke, Steven P. Djordjevic, Ian G. Charles, and Aaron E. Darling. "Evaluation of ddRADseq for reduced representation metagenome sequencing." PeerJ 5 (September 19, 2017): e3837. http://dx.doi.org/10.7717/peerj.3837.
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BackgroundProfiling of microbial communities via metagenomic shotgun sequencing has enabled researches to gain unprecedented insight into microbial community structure and the functional roles of community members. This study describes a method and basic analysis for a metagenomic adaptation of the double digest restriction site associated DNA sequencing (ddRADseq) protocol for reduced representation metagenome profiling.MethodsThis technique takes advantage of the sequence specificity of restriction endonucleases to construct an Illumina-compatible sequencing library containing DNA fragments that are between a pair of restriction sites located within close proximity. This results in a reduced sequencing library with coverage breadth that can be tuned by size selection. We assessed the performance of the metagenomic ddRADseq approach by applying the full method to human stool samples and generating sequence data.ResultsThe ddRADseq data yields a similar estimate of community taxonomic profile as obtained from shotgun metagenome sequencing of the same human stool samples. No obvious bias with respect to genomic G + C content and the estimated relative species abundance was detected.DiscussionAlthough ddRADseq does introduce some bias in taxonomic representation, the bias is likely to be small relative to DNA extraction bias. ddRADseq appears feasible and could have value as a tool for metagenome-wide association studies.
Dissertations / Theses on the topic "Human metagenomic"
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Rampelli, Simone <1985>. "Metagenomic trajectory of gut microbiome in the human lifespan." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amsdottorato.unibo.it/6333/1/Rampelli_thesis_2014.pdf.
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Co-evolving with the human host, gut microbiota establishes configurations, which vary under the pressure of inflammation, disease, ageing, diet and lifestyle.
In order to describe the multi-stability of the microbiome-host relationship, we studied specific tracts of the bacterial trajectory during the human lifespan and we characterized peculiar deviations from the hypothetical development, caused by disease, using molecular techniques, such as phylogenetic microarray and next-generation sequencing.
Firstly, we characterized the enterocyte-associated microbiota in breast-fed infants and adults, describing remarkable differences between the two groups of subjects. Successively, we investigated the impact of atopy on the development of the microbiome in Italian childrens, highlithing conspicuous deviations from the child-type microbiota of the Italian controls. To explore variation in the gut microbiota depending on geographical origins, which reflect different lifestyles, we compared the phylogenetic diversity of the intestinal microbiota of the Hadza hunter-gatherers of Tanzania and Italian adults. Additionally, we characterized the aged-type microbiome, describing the changes occurred in the metabolic potential of the gut microbiota of centenarians with respect to younger individuals, as a part of the pathophysiolology of the ageing process. Finally, we evaluated the impact of a probiotics intervention on the intestinal microbiota of elderly people, showing the repair of some age-related dysbioses. These studies contribute to elucidate several aspects of the intestinal microbiome development during the human lifespan, depicting the microbiota as an extremely plastic entity, capable of being reconfigured in response to different environmental factors and/or stressors of endogenous origin.
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Rampelli, Simone <1985>. "Metagenomic trajectory of gut microbiome in the human lifespan." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amsdottorato.unibo.it/6333/.
Full textAbstract:
Co-evolving with the human host, gut microbiota establishes configurations, which vary under the pressure of inflammation, disease, ageing, diet and lifestyle.
In order to describe the multi-stability of the microbiome-host relationship, we studied specific tracts of the bacterial trajectory during the human lifespan and we characterized peculiar deviations from the hypothetical development, caused by disease, using molecular techniques, such as phylogenetic microarray and next-generation sequencing.
Firstly, we characterized the enterocyte-associated microbiota in breast-fed infants and adults, describing remarkable differences between the two groups of subjects. Successively, we investigated the impact of atopy on the development of the microbiome in Italian childrens, highlithing conspicuous deviations from the child-type microbiota of the Italian controls. To explore variation in the gut microbiota depending on geographical origins, which reflect different lifestyles, we compared the phylogenetic diversity of the intestinal microbiota of the Hadza hunter-gatherers of Tanzania and Italian adults. Additionally, we characterized the aged-type microbiome, describing the changes occurred in the metabolic potential of the gut microbiota of centenarians with respect to younger individuals, as a part of the pathophysiolology of the ageing process. Finally, we evaluated the impact of a probiotics intervention on the intestinal microbiota of elderly people, showing the repair of some age-related dysbioses. These studies contribute to elucidate several aspects of the intestinal microbiome development during the human lifespan, depicting the microbiota as an extremely plastic entity, capable of being reconfigured in response to different environmental factors and/or stressors of endogenous origin.
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Huang, Kun. "Evolutionary analysis of the human microbiome using ancient metagenomic samples." Doctoral thesis, Università degli studi di Trento, 2021. http://hdl.handle.net/11572/318833.
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Studying the evolutionary history of human microbiome members is indispensable to understanding how our microbiota complexity has been shaped over time. While recent
decades have witnessed remarkable progress in investigation of the human microbiome within different evolutionary contexts, reconstructing a time-resolved divergence history for human microbiome members is still extremely challenging. Longitudinal metagenomics studies have shown the potential of addressing such challenges, but it is limited in tracking the evolutionary change in a short term. By contrast, leveraging the microbial genomic information preserved in the ancient metagenomic samples from the long past is emerging as a powerful strategy to study the long-established evolutionary history of the human microbiome. In this thesis, I aimed to devise a novel methodology that allows for efficiently reconstructing a time-resolved evolutionary history of human microbiome species using ancient metagenomic data. To this end, I firstly started from comparing four newly excavated paleofeces samples to a large body of contemporary metagenomic datasets. I observed that our human gut microbiota has diverged from its ancestral state in both microbial composition and metabolic pathways. This could be related to the change of lifestyle during human history. To better understand the divergence time of microbiome members, I secondly developed a novel computational pipeline which can precisely reconstruct and date strain-level phylogenies for microbiome species using carbon dated ancient metagenomic samples as calibration under Bayesian molecular clocking framework. The application of this tool has uncovered the unprecedented evolutionary diversity, in the context of geography and time period, of three Methanobrevibacter species from the human oral microbiome, and reconstructed a delicate time-resolved evolutionary history for common gut microbial species, such as Prevotella copri, Eubacterium rectale, Methanobrevibacter smithii and others mainly populating in the human gut microbiota. This approach promises that more underlying evolutionary history about the human microbiome will be unveiled in the foreseen future.
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Gaudin, Maxime. "Human RNA bait library depletion for human (viral) pathogen discovery using shotgun metagenomic sequencing." Thesis, Aix-Marseille, 2018. http://www.theses.fr/2018AIXM0697/document.
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La métagénomique virale est une approche prometteuse pour la détection et l’identification sans a priori de potentiels nouveaux pathogènes.Cependant, son utilisation reste encore marginale en raison de l’importante contamination des viromes par les séquences nucléiques de l’hôte.L'objectif de cette thèse était d’améliorer l’approche de métagénomique pour le diagnostic clinique de maladies infectieuses virales en augmentant le ratio de séquences pathogène/hôte par déplétion des acides nucléiques humains.Le premier chapitre consiste en une synthèse bibliographique des approches de métagénomique virale en recherche clinique et des challenges à relever dans ce domaine. Elle inclut également une revue sur les approches de capture/séquençage ciblées de certains pathogènes dans le domaine des maladies infectieuses humaines.Le deuxième chapitre propose une mise au point méthodologique permettant d’enrichir les métagénomes en séquences non-humaines basée sur l’hybridation et la capture de l’ensemble des acides nucléiques de l’hôte après hybridation avec des sondes ARN humaines biotinylées.Le troisième chapitre est divisé en deux sous-chapitres qui proposent l’application de ce protocole à la détection d’agents potentiellement impliqués (1) dans un cas fatal d’encéphalite et (2) dans un cas énigmatique d’endocardite infectieuse à hémoculture négative.Dans un quatrième chapitre, l’approche méthodologique que nous avons développée est discutée et les résultats sont replacés dans un contexte élargi d’émergence des maladies infectieuses et de lien de causalité entre l’agent détecté et la pathologie observéeViral metagenomics, which is based on the random shotgun sequencing of all viral genomes present in a sample, is a promising approach for blind detection and identification of potential new pathogens. Its use is however still marginal because of the large proportion of human nucleic sequences. In this context, this thesis work aims at improving the metagenomic approach for the clinical diagnosis of viral infectious diseases by increasing the ratio of pathogen-to-host sequences trough depletion of human nucleic acids from the samples. The first chapter of this thesis consists in a bibliographic synthesis of viral metagenomic approaches in clinical research and the challenges we faced in this field. This bibliographic overview also includes a review article on targeted-enrichment sequencing approaches for pathogen detection in the field of human infectious diseases. The second chapter proposes a methodological development allowing the enrichment of non-human sequences from metagenomes through hybridization and capture of human nucleic acids with biotinylated human RNA probes. The third chapter is divided into two sub-chapters that propose the application of this protocol to the detection of putative pathogens in (1) a fatal case of encephalitis and (2) an enigmatic case of blood-culture negative infectious endocarditis. The methodological approach developed during this work is finally discussed in a fourth chapter, which also replaces the results obtained in the broader context of emerging infectious diseases and validation of the causal link between the agent detected and the observed pathology
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Easton, S. "Functional and metagenomic analysis of the human tongue dorsum using phage display." Thesis, University College London (University of London), 2009. http://discovery.ucl.ac.uk/18512/.
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It is well established that mixed microbial communities contain organisms which have not been studied by conventional culture-based methods. In the human oral cavity this number is estimated at around 50%. Commensal bacteria develop and maintain an intimate relationship with human cells without triggering proinflammatory mechanisms and this study aims to explore this by searching for bacterial proteins which facilitate binding to the human tongue dorsum and wider oral cavity. Metagenomic DNA from the human tongue dorsum of 9 volunteers was extracted and a phage display library created, to our knowledge the first to incorporate metagenomic DNA. Phage display is an elegant molecular technique involving fusion of fragmented DNA to a phagemid coat protein, such that inserted DNA is encoded by the phage and displayed on the phage surface. The affinity selection technique panning, then exploited the natural affinity and specificity of the fusion proteins to identify bacterial binding proteins using, in this case, three ligands: IgA, Fibronectin and BSA. IgA is of special interest to this group as it interacts with bacterial proteins and is poised to respond to bacterial numbers in human secretions such as saliva. Proteins from panning were analysed in silico, however, the majority were discarded due to the presence of stop codons in the protein sequences. Remaining phagemid displaying fusion proteins of interest were assessed for function and binding assays carried out to confirm binding specificity. Due to the biased nature of phage display library production, a 16S rRNA gene analysis was also carried out in order to assess metagenomic DNA diversity prior to library construction. Because phage display was used successfully by colleagues with the genomes of single organisms, it was believed that including metagenomic DNA in a phage display library would cast a wide net over the tongue dorsum allowing capture of many more binding proteins occurring in this environment from a wide range of bacteria.
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Szczepanska, Anna. "Functional metagenomic analysis of carbohydrate degrading enzymes from the human gut microbiota." Thesis, University of East Anglia, 2011. https://ueaeprints.uea.ac.uk/47983/.
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The gut microbiota is a complex and diverse microbial community that is adapted to a carbohydrate-rich ecosystem. Plant cell wall components (cellulose, hemicelluloses and pectins), resistant starch and various oligosaccharides reach the colon by escaping digestion in the upper gastrointestinal tract. Fermentation of these dietary carbohydrates by the gut microbiota has well-recognised beneficial effects on host health. The microbial community in the human gut requires specific enzymes to efficiently degrade these carbohydrates. In this project, a culture-independent approach based on functional screening of genomic and metagenomic libraries using Escherichia coli and Lactococcus lactis as heterologous expression hosts, was used to isolate novel genes encoding glycoside hydrolase (GH) enzymes. The study identified several active GH enzymes involved in the breakdown of dietary polysaccharides such as starch, cellulose, xylan and β-glucan, recovered from the E. coli metagenomic library. The bioinformatic analysis of the insert from positive clones showed the presence of ORFs with the similarity to enzymes from GH families 13, 43 and 51 encoded by dominant bacterial genera from the human colon (Bacteroides sp., Roseburia sp., Ruminococcus sp.). A group of clones encoding potentially novel GH enzymes was also identified, emphasising the importance of functional-based study. One highly active clone was detected during screening of the L. lactis metagenomic library and showed fibrolytic activity on cellulose-, lichenanand xylan-containing plates. The insert contained a partial gene with the GH9 catalytic domain and identity to the protein from Coprococcus eutactus ART55/1. Further functional analysis established the fibrolytic activity of selected Coprococcus species. Moreover, several active clones were isolated from the Ruminococcus sp. 80/3 genomic library which encoded protein with the similarity to enzymes from GH families 2, 3 and 5. In this work, the traditional approach of expression in E. coli was complemented by using an alternative host – L. lactis. While this did not improve the screening efficiency in terms of number of recovered clones, differences in gene expression and protein export between E. coli and L. lactis were noted during this study which highlights the benefits of using different heterologous hosts in functional metagenomic approaches.
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Al-Jarbou, Ahmed. "Metagenomic analysis of the human mouth virus population and characterisation of two lytic viruses." Thesis, University of Leicester, 2009. http://hdl.handle.net/2381/8221.
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Viruses are biological agents that infect cellular organisms. Most viruses are bacteriophages, these are the most abundant biological entities on earth. Not much is known about virus diversity in the human mouth, including dental plaque, compared to other environments. A culture-independent based approach was tried using metagenomic analysis to characterize uncultured virus gene fragments in human dental plaque. The isolated viral genomes were amplified using a multiple displacement amplification method. Eighty, eleven and ten clones were sequenced from three volunteers, respectively. TBLASTX analysis showed that 44% of the sequences had significant identities to the GenBank databases. Of these 66% were viral; 12% human; 10% bacterial; 6% mobile and 6% eukarya. These sequences were sorted into six contigs and forty five single sequences. Four contigs and one single sequence were found to have a significant identity to a small region of a putative prophage in the Corynebcterium diphtheria genome. The gaps between these were filled by primer walking and PCR to give a continuous contig of 11554 bp. Two viruses A1 and A2 and their bacterial host were isolated from the human mouth. The 16S rRNA gene sequence of the host had a 99% identity to several Neisseria sp. The A1 virus was found to appear spontaneously on soft top agar plates, and might be a lysogenic virus. The A2 virus was a lytic virus. The two viruses have different morphological shapes. A1 has a varied isometric head size that ranges from 32 to 58 nm and no tail; it may belong to the Tectiviridae family. It has a linear dsDNA genome with a size between 12 kb and 23kb. A limited amount of the genome of the A1 virus was sequenced. The A2 virus has an icosohedral head with size of 60±3 nm and a sheathed rigid tail about 175 nm long with no detectable base plate or tail fibres. It can be classified into the order Caudovirales family Siphoviridae. The size of the A2 virus genome is estimated to be 35 to 40 kb. 31703 bp of unique sequence has been determined and sorted into three contigs and 14 single sequences. Further attempts at gap filling using primer walking and PCR were unsuccessful. It has a linear dsDNA genome, with a GC content of 49 mol%. A latent period of 25 min and a burst size of 25±2 particles were determined by a single step growth curve. Bioinformatic approaches were used to identify ORFs in the genome. A2 virion associated proteins were analysed by SDS–PAGE gel electrophoresis, and some proteins sequences were directly related to the translated genomic sequence.
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Tansirichaiya, Supathep. "Investigation of mobile genetic elements and antimicrobial resistance genes in human oral metagenomic DNA." Thesis, University College London (University of London), 2017. http://discovery.ucl.ac.uk/10041034/.
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Antibiotic resistance is currently one of the major global healthcare problems. Bacteria can become resistant by acquiring resistance genes from other bacteria. This process is usually facilitated by mobile genetic elements (MGEs), a type of DNA that can move from one site to another site within bacterial genome, and often between bacterial cells. The human oral cavity has been shown to harbour various antimicrobial resistance genes (ARGs). The aim of this research is to study the fundamental biology and the association between MGEs and ARGs present in human oral bacteria by both sequence and functional-based metagenomic assays. Using a PCR-based method, various genes predicted to confer antimicrobial resistance and other adaptive traits were identified on different MGEs (composite transposons, integrons and novel MGEs called translocatable units). This is the first report that showed ARGs in the human oral cavity were associated with these MGEs, especially in integron gene cassettes (GCs). Some of the integron gene cassettes were predicted to not contain any genes at all. They were predicted to have a regulatory function as a promoter, which could be important for the expression of other genes carried by integrons. Using an enzymatic reporter assay, it was proven that one of the functions of these GCs is as a promoter, which could allow bacteria to survive multiple stresses within the complex environment of the human oral cavity. Functional screening of a metagenomic library identified a clone that can confer resistance to two commonly used antiseptics agents. This was shown to be a result of UDP-glucose 4-epimerase enzyme derived from a common oral bacteria Veillonella parvula, which altered the cell’s surface charge to be more positive, presumably reducing the binding of positively charges antiseptics to the bacteria. To tackle the antibiotic resistance problems effectively, the understanding of the nature of MGEs is crucial. We have shown the presence of multiple novel MGEs, ARGs and a novel resistance mechanism. Those detected ARGs can be used for the surveillance and increase the understanding of MGEs in other environments.
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Temisak, Sasithon. "Assessing the accuracy of metagenomic analysis of microorganisms involved in human diseases using control materials." Thesis, St George's, University of London, 2015. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.703283.
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Metagenomics is the study of the collective genomes of the members of a microbial community. In contrast to conventional culture methods, sequence-based metagenomics exclusively relies on sequence analysis without culturing microorganisms. This approach has revolutionised our understanding of the complexity of microbiomes. As such, microbial profiling, particularly of microbiomes in humans that appear to play key roles in numerous disease phenotype, may provide information to help define associated underlying aetiological mechanisms. However, a number of available metagenomic approaches have different biases in the identification and quantification of the microbial composition, resulting in misinterpretation of the accrued data which subsequently affect conclusions. Therefore, the aim of this study was to interrogate sources of error in various methodologies in sequence-based metagenomic analysis. In this study, genomic DNA of common bacterial pathogens representative of both Gram-positive and Gram-negative organisms mixed at defined quantitative proportions were used as a standardised metagenomics control material (MCM) in order to assess the comparative accuracy of different approaches, i.e. 16S ribosomal RNA (rRNA) profiling and metagenomic shot~un-sequencing. Sources of bias in 16S rRNA including primer-template mismatches, primer design, and bioinformatics analytical tools were identified. Whole genome sequencing generated a high precision of microbial profiling. Bias was also observed due to DNA extraction protocol when the whole cell material (WCM) containing a bacteriologically quantitated range of bacteria was used. This study also suggested that the MCM provided the opportunity to develop species specific assays to detect multiple bacterial pathogens collected from the clinical samples by using high-throughput quantitative PCR (ht-qPCR). In conclusion, the methodology applied to microbial profiling analysis must consider sources of error and methods of standardisation such as those described here. Moreover, ht-qPCR demonstrated the value of a high-throughput bacterial detection technique for clinical diagnostic applications. This thesis has thus applied the principles of metrology to generate, characterise and evaluate whole organism and DNA based quantitative control materials as an essential pre-requisite for the precise and accurate biological interpretation of both 16S profiling and metagenomic analysis of human diseases.
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Ahiska, Bartu. "Reference-free identification of genetic variation in metagenomic sequence data using a probabilistic model." Thesis, University of Oxford, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.561121.
Full textAbstract:
Microorganisms are an indispensable part of our ecosystem, yet the natural metabolic and ecological diversity of these organisms is poorly understood due to a historical reliance of microbiology on laboratory grown cultures. The awareness that this diversity cannot be studied by laboratory isolation, together with recent advances in low cost scalable sequencing technology, have enabled the foundation of culture-independent microbiology, or metagenomics. The study of environmental microbial samples with metagenomics has led to many advances, but a number of technological and methodological challenges still remain. A potentially diverse set of taxa may be represented in anyone environmental sample. Existing tools for representing the genetic composition of such samples sequenced with short-read data, and tools for identifying variation amongst them, are still in their infancy. This thesis makes the case that a new framework based on a joint-genome graph can constitute a powerful tool for representing and manipulating the joint genomes of population samples. I present the development of a collection of methods, called SCRAPS, to construct these efficient graphs in small communities without the availability or bias of a reference genome. A key novelty is that genetic variation is identified from the data structure using a probabilistic algorithm that can provide a measure of the confidence in each call. SCRAPS is first tested on simulated short read data for accuracy and efficiency. At least 95% of non-repetitive small-scale genetic variation with a minor allele read depth greater than 10x is correctly identified; the number false positives per conserved nucleotide is consistently better than 1 part in 333 x 103. SCRAPS is then applied to artificially pooled experimental datasets. As part of this study, SCRAPS is used to identify genetic variation in an epidemiological 11 sample Neisseria meningitidis dataset collected from the African meningitis belt". In total 14,000 sites of genetic variation are identified from 48 million Illumina/Solexa reads. The results clearly show the genetic differences between two waves of infection that has plagued northern Ghana and Burkina Faso.
Books on the topic "Human metagenomic"
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Nelson, Karen E. Metagenomics of the human body. New York: Springer, 2011.
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Nelson, Karen E., ed. Metagenomics of the Human Body. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-7089-3.
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Nelson, Karen E. Metagenomics of the human body. New York: Springer, 2011.
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Epigenetics and human health: Linking hereditary, environmental, and nutritional aspects. Weinheim: Wiley-VCH, 2010.
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Probiotic bacteria and their effect on human health and well-being. Basel: Karger, 2013.
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Raffaetà, Roberta. Metagenomic Futures: How Microbiome Research Is Reconfiguring Health and What It Means to Be Human. Taylor & Francis Group, 2022.
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Raffaetà, Roberta. Metagenomic Futures: How Microbiome Research Is Reconfiguring Health and What It Means to Be Human. Taylor & Francis Group, 2022.
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Raffaetà, Roberta. Metagenomic Futures: How Microbiome Research Is Reconfiguring Health and What It Means to Be Human. Routledge, 2022.
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Raffaetà, Roberta. Metagenomic Futures: How Microbiome Research Is Reconfiguring Health and What It Means to Be Human. Routledge, Chapman & Hall, Incorporated, 2022.
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Raffaetà, Roberta. Metagenomic Futures: How Microbiome Research Is Reconfiguring Health and What It Means to Be Human. Taylor & Francis Group, 2022.
Find full textBook chapters on the topic "Human metagenomic"
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Bermúdez-Humarán, Luis G. "Metagenomic analysis of the human microbiome." In The Human Microbiota and Chronic Disease, 95–111. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2016. http://dx.doi.org/10.1002/9781118982907.ch6.
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Bhatia, Sonu, Vivek Tiwari, Neetu Sharma, Abhinashi Singh Sodhi, and Navneet Batra. "Metagenomic Insights of Human Oral Microbiome." In Genomic, Proteomics, and Biotechnology, 155–75. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003220831-10.
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Wang, Jun. "Human Gut Microbial Gene by Metagenomic Sequencing." In Encyclopedia of Metagenomics, 1–8. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6418-1_752-1.
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Wang, Jun. "Human Gut Microbial Genes by Metagenomic Sequencing." In Encyclopedia of Metagenomics, 265–71. Boston, MA: Springer US, 2015. http://dx.doi.org/10.1007/978-1-4899-7478-5_752.
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Li, Huiying. "Metagenomic Study, Human Skin Microbiome Associated with Acne, Project." In Encyclopedia of Metagenomics, 340–41. Boston, MA: Springer US, 2015. http://dx.doi.org/10.1007/978-1-4899-7475-4_532.
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Li, Huiying. "Metagenomic Study, Human Skin Microbiome Associated with Acne, Project." In Encyclopedia of Metagenomics, 1–2. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6418-1_532-4.
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Singh, Hemender, Indu Sharma, and Varun Sharma. "Epidemiological Perspectives of Human Health Through Metagenomic Research." In Metagenomics: Techniques, Applications, Challenges and Opportunities, 147–56. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6529-8_9.
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Schnabl, Bernd. "Metagenomic Applications and the Potential for Understanding Chronic Liver Disease." In Metagenomics of the Human Body, 277–95. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-7089-3_13.
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Jones, B. V., and C. G. M. Gahan. "Metagenomic Analysis of Bile Salt Hydrolases in the Human Gut Microbiome." In Encyclopedia of Metagenomics, 1–13. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6418-1_777-1.
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Jones, Brian V., and C. G. M. Gahan. "Metagenomic Analysis of Bile Salt Hydrolases in the Human Gut Microbiome." In Encyclopedia of Metagenomics, 402–14. Boston, MA: Springer US, 2015. http://dx.doi.org/10.1007/978-1-4899-7478-5_777.
Full textConference papers on the topic "Human metagenomic"
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Zhang, J., Q. Chen, Y. Qiu, W. Zeng, and X. Wei. "5 Cases of Talaromycosis in Human Immunodeficiency Virus-Uninfected Patients Early Diagnosed by Metagenomic Next-Generation Sequencing." In American Thoracic Society 2020 International Conference, May 15-20, 2020 - Philadelphia, PA. American Thoracic Society, 2020. http://dx.doi.org/10.1164/ajrccm-conference.2020.201.1_meetingabstracts.a5485.
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Qi, Xianghui, Lang Xu, Zexi Yang, Bokai Zhao, Xiu Wang, Jing Lin, Xu Wang, et al. "Cloning and analysis of xylose isomerase from metagenome." In International conference on Human Health and Medical Engineering. Southampton, UK: WIT Press, 2014. http://dx.doi.org/10.2495/hhme130211.
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Nuhamunada, Matin, Gregorius Altius Pratama, Setianing Wikanthi, Mohamad Khoirul Anam, R. Ludhang Pradhipta Rizki, and Nastiti Wijayanti. "Data Mining and Comparative Analysis of Human Skin Microbiome from EBI Metagenomics Database." In 2018 1st International Conference on Bioinformatics, Biotechnology, and Biomedical Engineering (BioMIC). IEEE, 2018. http://dx.doi.org/10.1109/biomic.2018.8610588.
Full textReports on the topic "Human metagenomic"
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Beckstrom-Sternberg, Stephen. Bioinformatic Tools for Metagenomic Analysis of Pathogen Backgrounds and Human Microbial Communities. Fort Belvoir, VA: Defense Technical Information Center, May 2010. http://dx.doi.org/10.21236/ada581677.
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Mizrahi, Itzhak, and Bryan A. White. Exploring the role of the rumen microbiota in determining the feed efficiency of dairy cows. United States Department of Agriculture, October 2011. http://dx.doi.org/10.32747/2011.7594403.bard.
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Expanding world hunger calls for increasing available food resources. Ruminants have the remarkable ability to convert human-indigestible plant biomass into human-digestible food products, due to a complex microbiome residing in the rumen compartment of their upper digestive tract. One way to tackle the problem of diminishing food resources is to increase the animals' energetic efficiency, i.e., the efficiency with which they convert energy from feed, thereby increasing food availability while lowering the environmental burden, as these animals would produce more and eat less. We hypothesize that the cow's feed efficiency is dependent on the taxonomic composition, coding capacity and activity of its reticulorumenmicrobiota. To test this hypothesis, three aims are defined: (1) Evaluation of the feed efficiency of 146 dairy cows and defining two groups representing the highest and lowest 25% using the Israeli group's unique facility; (2) Comparing these two groups for microbiota diversity, identity and coding capacity using next-generation sequencing and metagenomic approaches; (3) Comparing the reticulorumenmicrobiota metabolic activity parameters. We measured feed efficiency in 146 milking cows and analyzed the taxonomic composition, gene content, microbial activity and metabolomic composition of rumen microbiomes from the 78 most extreme animals. Lower richness of microbiome gene content and taxa was tightly linked to higher feed efficiency. Microbiome genes and species accurately predicted the animals' feed-efficiency phenotype. Specific enrichment of microbes and metabolic pathways in each of these microbiome groups resulted in increasing valuable metabolites and decreasing unusable ones such as methane in efficient animals. This ecological and mechanistic understanding of the rumen microbiome could lead to an increase in available food resources and environmentally friendly livestock agriculture.
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Mizrahi, Itzhak, and Bryan A. White. Uncovering rumen microbiome components shaping feed efficiency in dairy cows. United States Department of Agriculture, January 2015. http://dx.doi.org/10.32747/2015.7600020.bard.
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Ruminants provide human society with high quality food from non-human-edible resources, but their emissions negatively impact the environment via greenhouse gas production. The rumen and its resident microorganisms dictate both processes. The overall goal of this project was to determine whether a causal relationship exists between the rumen microbiome and the host animal's physiology, and if so, to isolate and examine the specific determinants that enable this causality. To this end, we divided the project into three specific parts: (1) determining the feed efficiency of 200 milking cows, (2) determining whether the feed- efficiency phenotype can be transferred by transplantation and (3) isolating and examining microbial consortia that can affect the feed-efficiency phenotype by their transplantation into germ-free ruminants. We finally included 1000 dairy cow metadata in our study that revealed a global core microbiome present in the rumen whose composition and abundance predicted many of the cows’ production phenotypes, including methane emission. Certain members of the core microbiome are heritable and have strong associations to cardinal rumen metabolites and fermentation products that govern the efficiency of milk production. These heritable core microbes therefore present primary targets for rumen manipulation towards sustainable and environmentally friendly agriculture. We then went beyond examining the metagenomic content, and asked whether microbes behave differently with relation to the host efficiency state. We sampled twelve animals with two extreme efficiency phenotypes, high efficiency and low efficiency where the first represents animals that maximize energy utilization from their feed whilst the later represents animals with very low utilization of the energy from their feed. Our analysis revealed differences in two host efficiency states in terms of the microbial expression profiles both with regards to protein identities and quantities. Another aim of the proposal was the cultivation of undescribed rumen microorganisms is one of the most important tasks in rumen microbiology. Our findings from phylogenetic analysis of cultured OTUs on the lower branches of the phylogenetic tree suggest that multifactorial traits govern cultivability. Interestingly, most of the cultured OTUs belonged to the rare rumen biosphere. These cultured OTUs could not be detected in the rumen microbiome, even when we surveyed it across 38 rumen microbiome samples. These findings add another unique dimension to the complexity of the rumen microbiome and suggest that a large number of different organisms can be cultured in a single cultivation effort. In the context of the grant, the establishment of ruminant germ-free facility was possible and preliminary experiments were successful, which open up the way for direct applications of the new concepts discovered here, prior to the larger scale implementation at the agricultural level.
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Haynes, Dr Edward, Chris Conyers, Dr Marc Kennedy, Roy Macarthur, Sam McGreig, and Dr John Walshaw. What is the Burden of Antimicrobial Resistance Genes in Selected Ready-to-Eat Foods? Food Standards Agency, November 2021. http://dx.doi.org/10.46756/sci.fsa.bsv485.
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This study was designed to get a broad estimate of the presence and the types of antimicrobial resistance genes across 52 simple ready-to-eat foods. It was also carried out to understand the benefits and drawbacks of using metagenomic sequencing, a fairly new technology, to study AMR genes. An antimicrobial is any substance that kills or inhibits the growth of microorganisms. It includes antibiotics which are used to treat bacterial infections in both humans and animals. Given the relevant selective pressures, the bacteria itself can change and find ways to survive the effects of an antimicrobials. This results in the bacteria becoming resistant to the ‘killing’ effects of antimicrobials and is known as ‘antimicrobial resistance’. The more we use antimicrobials and antibiotics and the way that we use them can increase the chance that bacteria will become resistant to antimicrobials. This is important as it can lead to infections that become more difficult to treat with drugs and poses a risk to the public health. T Addressing AMR is a national strategic priority for the UK Government which has led to the development of a new 20-year Vision for AMR and the 5-year National Action Plan (NAP), which runs until 2024. The NAP lays out how the UK will address the AMR challenge and takes a ‘One-Health’ approach which spans people, animals, agriculture, food and the environment. The NAP includes a specific section on the importance of better food safety to limit the contamination of foods and spread of AMR. This section emphasises the need to strengthen the evidence base for AMR and food safety through research, surveillance and promoting good practice across the food chain. The FSA is playing its part by continuing to fill evidence gaps on the role that food plays in AMR through the commissioning of research and surveillance. We are also promoting and improving UK food hygiene (‘4Cs’ messages) across the food chain that will help reduce exposure to AMR bacteria.