55 resultados para Miocene bacteria and mesofauna
Resumo:
The gut microbiota enhances the host's metabolic capacity for processing nutrients and drugs and modulate the activities of multiple pathways in a variety of organ systems. We have probed the systemic metabolic adaptation to gut colonization for 20 days following exposure of axenic mice (n = 35) to a typical environmental microbial background using high-resolution (1)H nuclear magnetic resonance (NMR) spectroscopy to analyze urine, plasma, liver, kidney, and colon (5 time points) metabolic profiles. Acquisition of the gut microbiota was associated with rapid increase in body weight (4%) over the first 5 days of colonization with parallel changes in multiple pathways in all compartments analyzed. The colonization process stimulated glycogenesis in the liver prior to triggering increases in hepatic triglyceride synthesis. These changes were associated with modifications of hepatic Cyp8b1 expression and the subsequent alteration of bile acid metabolites, including taurocholate and tauromuricholate, which are essential regulators of lipid absorption. Expression and activity of major drug-metabolizing enzymes (Cyp3a11 and Cyp2c29) were also significantly stimulated. Remarkably, statistical modeling of the interactions between hepatic metabolic profiles and microbial composition analyzed by 16S rRNA gene pyrosequencing revealed strong associations of the Coriobacteriaceae family with both the hepatic triglyceride, glucose, and glycogen levels and the metabolism of xenobiotics. These data demonstrate the importance of microbial activity in metabolic phenotype development, indicating that microbiota manipulation is a useful tool for beneficially modulating xenobiotic metabolism and pharmacokinetics in personalized health care. IMPORTANCE: Gut bacteria have been associated with various essential biological functions in humans such as energy harvest and regulation of blood pressure. Furthermore, gut microbial colonization occurs after birth in parallel with other critical processes such as immune and cognitive development. Thus, it is essential to understand the bidirectional interaction between the host metabolism and its symbionts. Here, we describe the first evidence of an in vivo association between a family of bacteria and hepatic lipid metabolism. These results provide new insights into the fundamental mechanisms that regulate host-gut microbiota interactions and are thus of wide interest to microbiological, nutrition, metabolic, systems biology, and pharmaceutical research communities. This work will also contribute to developing novel strategies in the alteration of host-gut microbiota relationships which can in turn beneficially modulate the host metabolism.
Resumo:
BipA is a novel member of the ribosome binding GTPase superfamily and is widely distributed in bacteria and plants. We report here that it regulates -multiple cell surface- and virulence-associated -components in the enteropathogenic Escherichia coli (EPEC) strain E2348/69. The regulated components include bacterial flagella, the espC pathogenicity island and a type III secretion system specified by the locus of enterocyte effacement (LEE). BipA positively regulated the espC and LEE gene clusters through transcriptional control of the LEE-encoded regulator, Ler. Additionally, it affected the pattern of proteolysis of intimin, a key LEE-encoded adhesin specified by the LEE. BipA control of the LEE operated independently of the previously characterized regulators Per, integration host factor and H-NS. In contrast, it negatively regulated the flagella-mediated motility of EPEC and in a Ler-independent manner. Our results indicate that the BipA GTPase functions high up in diverse regulatory cascades to co-ordinate the expression of key pathogenicity islands and other virulence-associated factors in E. coli.
Resumo:
This release of the Catalogue of Life contains contributions from 132 databases with information on 1,352,112 species, 114,069 infraspecific taxa and also includes 928,147 synonyms and 408,689 common names covering the following groups: Viruses • Viruses and Subviral agents from ICTV_MSL UPDATED! Bacteria and Archaea from BIOS Chromista • Chromistan fungi from Species Fungorum Protozoa • Major groups from ITIS Regional, • Ciliates from CilCat, • Polycystines from WoRMS Polycystina UPDATED!, • Protozoan fungi from Species Fungorum and Trichomycetes database • Slime moulds from Nomen.eumycetozoa.com Fungi • Various taxa in whole or in part from CABI Bioservices databases (Species Fungorum, Phyllachorales, Rhytismatales, Saccharomycetes and Zygomycetes databases) and from three other databases covering Xylariaceae, Glomeromycota, Trichomycetes, Dothideomycetes • Lichens from LIAS UPDATED! Plantae (Plants) • Mosses from MOST • Liverworts and hornworts from ELPT • Conifers from Conifer Database • Cycads and 6 flowering plant families from IOPI-GPC, and 99 families from WCSP • Plus individual flowering plants families from AnnonBase, Brassicaceae, ChenoBase, Droseraceae Database, EbenaBase, GCC UPDATED!, ILDIS UPDATED!, LecyPages, LHD, MELnet UPDATED!, RJB Geranium, Solanaceae Source, Umbellifers. Animalia (Animals) • Marine groups from URMO, ITIS Global, Hexacorals, ETI WBD (Euphausiacea), WoRMS: WoRMS Asteroidea UPDATED!, WoRMS Bochusacea UPDATED!, WoRMS Brachiopoda UPDATED!, WoRMS Brachypoda UPDATED!, WoRMS Brachyura UPDATED!, WoRMS Bryozoa UPDATED!, WoRMS Cestoda NEW!, WoRMS Chaetognatha UPDATED!, WoRMS Cumacea UPDATED!, WoRMS Echinoidea UPDATED!, WoRMS Gastrotricha NEW!, WoRMS Gnathostomulida NEW!, WoRMS Holothuroidea UPDATED!, WoRMS Hydrozoa UPDATED!, WoRMS Isopoda UPDATED!, WoRMS Leptostraca UPDATED!, WoRMS Monogenea NEW!, WoRMS Mystacocarida UPDATED!, WoRMS Myxozoa NEW!, WoRMS Nemertea UPDATED!, WoRMS Oligochaeta UPDATED!, WoRMS Ophiuroidea UPDATED!, WoRMS Phoronida UPDATED!, WoRMS Placozoa NEW!, WoRMS Polychaeta UPDATED!, WoRMS Polycystina UPDATED!, WoRMS Porifera UPDATED!, WoRMS Priapulida NEW!, WoRMS Proseriata and Kalyptorhynchia UPDATED!, WoRMS Remipedia UPDATED!, WoRMS Scaphopoda UPDATED!, WoRMS Tanaidacea UPDATED!, WoRMS Tantulocarida UPDATED!, WoRMS Thermosbaenacea UPDATED!, WoRMS Trematoda NEW!, WoRMS Xenoturbellida UPDATED! • Rotifers, mayflies, freshwater hairworms, planarians from FADA databases: FADA Rotifera UPDATED!, FADA Ephemeroptera NEW!, FADA Nematomorpha NEW! & FADA Turbellaria NEW! • Entoprocts, water bears from ITIS Global • Spiders, scorpions, ticks & mites from SpidCat via ITIS UPDATED!, SalticidDB , ITIS Global, TicksBase, SpmWeb BdelloideaBase UPDATED! & Mites GSDs: OlogamasidBase, PhytoseiidBase, RhodacaridBase & TenuipalpidBase • Diplopods, centipedes, pauropods and symphylans from SysMyr UPDATED! & ChiloBase • Dragonflies and damselflies from Odonata database • Stoneflies from PlecopteraSF UPDATED! • Cockroaches from BlattodeaSF UPDATED! • Praying mantids from MantodeaSF UPDATED! • Stick and leaf insects from PhasmidaSF UPDATED! • Grasshoppers, locusts, katydids and crickets from OrthopteraSF UPDATED! • Webspinners from EmbiopteraSF UPDATED! • Bark & parasitic lices from PsocodeaSF NEW! • Some groups of true bugs from ScaleNet, FLOW, COOL, Psyllist, AphidSF UPDATED! , MBB, 3i Cicadellinae, 3i Typhlocybinae, MOWD & CoreoideaSF NEW!• Twisted-wing parasites from Strepsiptera Database UPDATED! • Lacewings, antlions, owlflies, fishflies, dobsonflies & snakeflies from LDL Neuropterida • Some beetle groups from the Scarabs UPDATED!, TITAN, WTaxa & ITIS Global • Fleas from Parhost • Flies, mosquitoes, bots, midges and gnats from Systema Dipterorum, CCW & CIPA • Butterflies and moths from LepIndex UPDATED!, GloBIS (GART) UPDATED!, Tineidae NHM, World Gracillariidae • Bees & wasps from ITIS Bees, Taxapad Ichneumonoidea, UCD, ZOBODAT Vespoidea & HymIS Rhopalosomatidae NEW!• Molluscs from WoRMS Mollusca NEW!, FADA Bivalvia NEW!, MolluscaFW NEW! & AFD (Pulmonata) • Fishes from FishBase UPDATED! • Reptiles from TIGR Reptiles • Amphibians, birds and mammals from ITIS Global PLUS additional species of many groups from ITIS Regional, NZIB and CoL China NEW!
Resumo:
A model of species migration is presented which takes the form of a reaction-diffusion system. We consider special limits of this model in which we demonstrate the existence of travelling wave solutions. These solutions can be used to describe the migration of cells, bacteria, and some organisms. © 2000 Elsevier Science Ltd. All rights reserved.
Resumo:
Powered by advances in electron tomography, recent studies have extended our understanding of how viruses construct "replication factories" inside infected cells. Their function, however, remains an area of speculation with important implications for human health. It is clear from these studies that whatever their purpose, organelle structure is dynamic (M. Ulasli, M. H. Verheije, C. A. de Haan, and F. Reggiori, Cell. Microbiol. 12:844-861, 2010) and intricate (K. Knoops, M. Kikkert, S. H. Worm, J. C. Zevenhoven-Dobbe, Y. van der Meer, et al., PLOS Biol. 6:e226, 2008). But by concentrating on medically important viruses, these studies have failed to take advantage of the genetic variation inherent in a family of viruses that is as diverse as the archaea, bacteria, and eukaryotes combined (C. Lauber, J. J. Goeman, M. del Carmen Parquet, P. T. Nga, E. J. Snijder, et al., PLOS Pathog. 9:e1003500, 2013). In this climate, Maier et al. (H. J. Maier, P. C. Hawes, E. M. Cottam, J. Mantell, P. Verkade, et al., mBio 4:e00801-13, 2013) explored the replicative structures formed by an avian coronavirus that appears to have diverged at an early point in coronavirus evolution and shed light on controversial aspects of viral biology.
Resumo:
Selection can favour the evolution of individually costly dispersal if this alleviates competition between relatives. However, conditions that favour altruistic dispersal also mediate selection for other social behaviours, such as public goods cooperation, which in turn is likely to mediate dispersal evolution. Here, we investigate – both experimentally (using bacteria) and theoretically – how social habitat heterogeneity (i.e. the distribution of public goods cooperators and cheats) affects the evolution of dispersal. In addition to recovering the well-known theoretical result that the optimal level of dispersal increases with genetic relatedness of patch mates, we find both mathematically and experimentally that dispersal is always favoured when average patch occupancy is low, but when average patch occupancy is high, the presence of public goods cheats greatly alters selection for dispersal. Specifically, when public goods cheats are localized to the home patch, higher dispersal rates are favoured, but when cheats are present throughout available patches, lower dispersal rates are favoured. These results highlight the importance of other social traits in driving dispersal evolution.
Resumo:
Current feed evaluation systems for ruminants are too imprecise to describe diets in terms of their acidosis risk. The dynamic mechanistic model described herein arises from the integration of a lactic acid (La) metabolism module into an extant model of whole-rumen function. The model was evaluated using published data from cows and sheep fed a range of diets or infused with various doses of La. The model performed well in simulating peak rumen La concentrations (coefficient of determination = 0.96; root mean square prediction error = 16.96% of observed mean), although frequency of sampling for the published data prevented a comprehensive comparison of prediction of time to peak La accumulation. The model showed a tendency for increased La accumulation following feeding of diets rich in nonstructural carbohydrates, although less-soluble starch sources such as corn tended to limit rumen La concentration. Simulated La absorption from the rumen remained low throughout the feeding cycle. The competition between bacteria and protozoa for rumen La suggests a variable contribution of protozoa to total La utilization. However, the model was unable to simulate the effects of defaunation on rumen La metabolism, indicating a need for a more detailed description of protozoal metabolism. The model could form the basis of a feed evaluation system with regard to rumen La metabolism.
Resumo:
Retreating ice fronts (as a result of a warming climate) expose large expanses of deglaciated forefield, which become colonized by microbes and plants. There has been increasing interest in characterizing the biogeochemical development of these ecosystems using a chronosequence approach. Prior to the establishment of plants, microbes use autochthonously produced and allochthonously delivered nutrients for growth. The microbial community composition is largely made up of heterotrophic microbes (both bacteria and fungi), autotrophic microbes and nitrogen-fixing diazotrophs. Microbial activity is thought to be responsible for the initial build-up of labile nutrient pools, facilitating the growth of higher order plant life in developed soils. However, it is unclear to what extent these ecosystems rely on external sources of nutrients such as ancient carbon pools and periodic nitrogen deposition. Furthermore, the seasonal variation of chronosequence dynamics and the effect of winter are largely unexplored. Modelling this ecosystem will provide a quantitative evaluation of the key processes and could guide the focus of future research. Year-round datasets combined with novel metagenomic techniques will help answer some of the pressing questions in this relatively new but rapidly expanding field, which is of growing interest in the context of future large-scale ice retreat.
Resumo:
The aim of the present study was to investigate the effect of probiotic immobilization onto wheat grains, both wet and freeze dried, on the adhesion properties of the probiotic cells and make comparisons with wet and freeze dried free cells. Lactobacillus casei ATCC 393 and Lactobacillus plantarum NCIMB 8826 were used as model probiotic strains. The results showed satisfactory adhesion ability of free cells to a monolayer of Caco-2 cells (> 1000 CFU/100 Caco-2 cells for wet cells). Cell immobilization resulted in a significant decrease in adhesion, for both wet and freeze dried formulations, most likely because immobilized cells did not have direct access to the Caco-2 cells, but it still remained in adequate levels (> 100 CFU/100 Caco-2 cells for wet cells). No clear correlation could be observed between cell adhesion and the hydrophobicity of the bacterial cells, measured by the hexadecane adhesion assay. Most notably, immobilization enhanced the monolayer integrity of Caco-2 cells, demonstrated by a more than 2-fold increase in transepithelial electrical resistance (TEER) compared to free cells. SEM micrographs ascertained the adhesion of both immobilized and free cells to the brush border microvilli. Finally, the impact of the food matrix on the adhesion properties of probiotic bacteria and on the design of novel functional products is discussed.
Resumo:
Exposure to environmental chemicals has been linked to various health disorders, including obesity, type 2 diabetes, cancer and dysregulation of the immune and reproductive systems, whereas the gastrointestinal microbiota critically contributes to a variety of host metabolic and immune functions. We aimed to evaluate the bidirectional relationship between gut bacteria and environmental pollutants and to assess the toxicological relevance of the bacteria–xenobiotic interplay for the host. We examined studies using isolated bacteria, faecal or caecal suspensions—germ-free or antibiotic-treated animals—as well as animals reassociated with a microbiota exposed to environmental chemicals. The literature indicates that gut microbes have an extensive capacity to metabolise environmental chemicals that can be classified in five core enzymatic families (azoreductases, nitroreductases, β-glucuronidases, sulfatases and β-lyases) unequivocally involved in the metabolism of >30 environmental contaminants. There is clear evidence that bacteria-dependent metabolism of pollutants modulates the toxicity for the host. Conversely, environmental contaminants from various chemical families have been shown to alter the composition and/or the metabolic activity of the gastrointestinal bacteria, which may be an important factor contributing to shape an individual’s microbiotype. The physiological consequences of these alterations have not been studied in details but pollutant-induced alterations of the gut bacteria are likely to contribute to their toxicity. In conclusion, there is a body of evidence suggesting that gut microbiota are a major, yet underestimated element that must be considered to fully evaluate the toxicity of environmental contaminants.