165 resultados para Plant Size
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The mutualistic symbiosis involving Glomeromycota, a distinctive phylum of early diverging Fungi, is widely hypothesized to have promoted the evolution of land plants during the middle Paleozoic. These arbuscular mycorrhizal fungi (AMF) perform vital functions in the phosphorus cycle that are fundamental to sustainable crop plant productivity. The unusual biological features of AMF have long fascinated evolutionary biologists. The coenocytic hyphae host a community of hundreds of nuclei and reproduce clonally through large multinucleated spores. It has been suggested that the AMF maintain a stable assemblage of several different genomes during the life cycle, but this genomic organization has been questioned. Here we introduce the 153-Mb haploid genome of Rhizophagus irregularis and its repertoire of 28,232 genes. The observed low level of genome polymorphism (0.43 SNP per kb) is not consistent with the occurrence of multiple, highly diverged genomes. The expansion of mating-related genes suggests the existence of cryptic sex-related processes. A comparison of gene categories confirms that R. irregularis is close to the Mucoromycotina. The AMF obligate biotrophy is not explained by genome erosion or any related loss of metabolic complexity in central metabolism, but is marked by a lack of genes encoding plant cell wall-degrading enzymes and of genes involved in toxin and thiamine synthesis. A battery of mycorrhiza-induced secreted proteins is expressed in symbiotic tissues. The present comprehensive repertoire of R. irregularis genes provides a basis for future research on symbiosis-related mechanisms in Glomeromycota.
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Insects are an important and probably the most challenging pest to control in agriculture, in particular when they feed on belowground parts of plants. The application of synthetic pesticides is problematic owing to side effects on the environment, concerns for public health and the rapid development of resistance. Entomopathogenic bacteria, notably Bacillus thuringiensis and Photorhabdus/Xenorhabdus species, are promising alternatives to chemical insecticides, for they are able to efficiently kill insects and are considered to be environmentally sound and harmless to mammals. However, they have the handicap of showing limited environmental persistence or of depending on a nematode vector for insect infection. Intriguingly, certain strains of plant root-colonizing Pseudomonas bacteria display insect pathogenicity and thus could be formulated to extend the present range of bioinsecticides for protection of plants against root-feeding insects. These entomopathogenic pseudomonads belong to a group of plant-beneficial rhizobacteria that have the remarkable ability to suppress soil-borne plant pathogens, promote plant growth, and induce systemic plant defenses. Here we review for the first time the current knowledge about the occurrence and the molecular basis of insecticidal activity in pseudomonads with an emphasis on plant-beneficial and prominent pathogenic species. We discuss how this fascinating Pseudomonas trait may be exploited for novel root-based approaches to insect control in an integrated pest management framework.
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The complex ecology of free-living amoebae (FLA) and their role in spreading pathogenic microorganisms through water systems have recently raised considerable interest. In this study, we investigated the presence of FLA and amoebae-resisting bacteria (ARB) at various stages of a drinking water plant fed with river water. We isolated various amoebal species from the river and from several points within the plant, mostly at early steps of water treatment. Echinamoeba- and Hartmannella-related amoebae were mainly recovered in the drinking water plant whereas Acanthamoeba- and Naegleria-related amoebae were recovered from the river water and the sand filtration units. Some FLA isolates were recovered immediately after the ozonation step, thus suggesting resistance of these microorganisms to this disinfection procedure. A bacterial isolate related to Mycobacterium mucogenicum was recovered from an Echinamoeba-related amoeba isolated from ozone-treated water. Various other ARB were recovered using co-culture with axenic Acanthamoeba castellanii, including mycobacteria, legionella, Chlamydia-like organisms and various proteobacteria. Noteworthy, a new Parachlamydia acanthamoebae strain was recovered from river water and from granular activated carbon (GAC) biofilm. As amoebae mainly multiply in sand and GAC filters, optimization of filter backwash procedures probably offers a possibility to better control these protists and the risk associated with their intracellular hosts
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Fluctuations in ammonium (NH4+), measured as NH4-N loads using an ion-selective electrode installed at the inlet of a sewage treatment plant, showed a distinctive pattern which was associated to weekly (i.e., commuters) and seasonal (i.e., holidays) fluctuations of the population. Moreover, population size estimates based on NH4-N loads were lower compared to census data. Diurnal profiles of benzoylecgonine (BE) and 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (THC-COOH) were shown to be strongly correlated to NH4-N. Characteristic patterns, which reflect the prolonged nocturnal activity of people during the weekend, could be observed for BE, cocaine, and a major metabolite of MDMA (i.e., 4-hydroxy-3-methoxymethamphetamine). Additional 24 h composite samples were collected between February and September 2013. Per-capita loads (i.e., grams per day per 1000 inhabitants) were computed using census data and NH4-N measurements. Normalization with NH4-N did not modify the overall pattern, suggesting that the magnitude of fluctuations in the size of the population is negligible compared to those of illicit drug loads. Results show that fluctuations in the size of the population over longer periods of time or during major events can be monitored using NH4-N loads: either using raw NH4-N loads or population size estimates based on NH4-N loads, if information about site-specific NH4-N population equivalents is available.
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The peroxisome targeting signal (PTS) required for import of the rat acyl-CoA oxidase (AOX; EC 1.3.3.6) and the Candida tropicalis multifunctional protein (MFP) in plant peroxisomes was assessed in transgenic Arabidopsis thaliana (L.) Heynh. The native rat AOX accumulated in peroxisomes in A. thaliana cotyledons and targeting was dependent on the presence of the C-terminal tripeptide S-K-L. In contrast, the native C. tropicalis MFP, containing the consensus PTS sequence A-K-I was not targeted to plant peroxisomes. Modification of the carboxy terminus to the S-K-L tripeptide also failed to deliver the MFP to peroxisomes while addition of the last 34 amino acids of the Brassica napus isocitrate lyase, containing the terminal tripeptide S-R-M, enabled import of the fusion protein into peroxisomes. These results underline the influence of the amino acids adjacent to the terminal tripeptide of the C. tropicalis MFP on peroxisomal targeting, even in the context of a protein having a consensus PTS sequence S-K-L.
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PURPOSE: We determined the effect of entrance pupil size on retinal illumination. The influence of unilateral miosis on the magnitude of the pupil light reflex was studied to ascertain how a clinically significant anisocoria influences the relative afferent pupil defect (RAPD). METHODS: Miosis was induced by topical 1% pilocarpine in the right eye of 14 healthy subjects with normal eyes. The interocular difference in retinal illumination was assessed by computerized pupillometry from the stimulus response curve of the right and left eyes. The main outcome measure was the RAPD, determined by computerized pupillography, at baseline and after pilocarpine-induced anisocoria. RESULTS: Induced anisocoria produced a significant change in RAPD from baseline (mean = 1.60 dB in the miotic eye, P = 0.007). However, anisocoria correlated with RAPD only in subjects with darkly pigmented irides (Pearson correlation coefficient 0.793, P = 0.05). CONCLUSIONS: In darkly pigmented eyes, entrance pupil size significantly influenced the retinal illumination. However, retinal illumination of lightly pigmented eyes is relatively independent of entrance pupil size, presumably due to extrapupillary transmission of light through the iris and sclera. This has important implications in understanding the potential influence of anisocoria on the RAPD and also greater susceptibility of lightly pigmented eyes to light toxicity.
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Controlling external compound entrance is essential for plant survival. To set up an efficient and selective sorting of nutrients, free diffusion via the apoplast in vascular plants is blocked at the level of the endodermis. Although we have learned a lot about endodermal specification in the last years, information regarding its differentiation is still very limited. A differentiated endodermal cell can be defined by the presence of the "Casparian strip" (CS), a cell wall modification described first by Robert Caspary in 1865. While the anatomical description of CS in many vascular plants has been very detailed, we still lack molecular information about the establishment of the Casparian strips and their actual function in roots. The recent isolation of a novel protein family, the CASPs, that localizes precisely to a domain of the plasma membrane underneath the CS represents an excellent point of entry to explore CS function and formation. In addition, it has been shown that the endodermis contains transporters that are localized to either the central (stele-facing) or peripheral (soil-facing) plasma membranes. These features suggest that the endodermis functions as a polar plant epithelium.
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In mountainous regions, climate warming is expected to shift species' ranges to higher altitudes. Evidence for such shifts is still mostly from revisitations of historical sites. We present recent (2001 to 2008) changes in vascular plant species richness observed in a standardized monitoring network across Europe's major mountain ranges. Species have moved upslope on average. However, these shifts had opposite effects on the summit floras' species richness in boreal-temperate mountain regions (+3.9 species on average) and Mediterranean mountain regions (-1.4 species), probably because recent climatic trends have decreased the availability of water in the European south. Because Mediterranean mountains are particularly rich in endemic species, a continuation of these trends might shrink the European mountain flora, despite an average increase in summit species richness across the region.
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Much attention has been paid to the effects of climate change on species' range reductions and extinctions. There is however surprisingly little information on how climate change driven threat may impact the tree of life and result in loss of phylogenetic diversity (PD). Some plant families and mammalian orders reveal nonrandom extinction patterns, but many other plant families do not. Do these discrepancies reflect different speciation histories and does climate induced extinction result in the same discrepancies among different groups? Answers to these questions require representative taxon sampling. Here, we combine phylogenetic analyses, species distribution modeling, and climate change projections on two of the largest plant families in the Cape Floristic Region (Proteaceae and Restionaceae), as well as the second most diverse mammalian order in Southern Africa (Chiroptera), and an herbivorous insect genus (Platypleura) in the family Cicadidae to answer this question. We model current and future species distributions to assess species threat levels over the next 70years, and then compare projected with random PD survival. Results for these animal and plant clades reveal congruence. PD losses are not significantly higher under predicted extinction than under random extinction simulations. So far the evidence suggests that focusing resources on climate threatened species alone may not result in disproportionate benefits for the preservation of evolutionary history.
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Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. These networks--whose nodes can vary from tens to hundreds--are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which various graph metrics depend upon the network size. To this end, EEGs from 32 normal subjects were recorded and functional networks of three different sizes were extracted. A state-space based method was used to calculate cross-correlation matrices between different brain regions. These correlation matrices were used to construct binary adjacency connectomes, which were assessed with regards to a number of graph metrics such as clustering coefficient, modularity, efficiency, economic efficiency, and assortativity. We showed that the estimates of these metrics significantly differ depending on the network size. Larger networks had higher efficiency, higher assortativity and lower modularity compared to those with smaller size and the same density. These findings indicate that the network size should be considered in any comparison of networks across studies.
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Environmental gradients have been postulated to generate patterns of diversity and diet specialization, in which more stable environments, such as tropical regions, should promote higher diversity and specialization. Using field sampling and phylogenetic analyses of butterfly fauna over an entire alpine region, we show that butterfly specialization (measured as the mean phylogenetic distance between utilized host plants) decreases at higher elevations, alongside a decreasing gradient of plant diversity. Consistent with current hypotheses on the relationship between biodiversity and the strength of species interactions, we experimentally show that a higher level of generalization at high elevations is associated with lower levels of plant resistance: across 16 pairs of plant species, low-elevation plants were more resistant vis-à-vis their congeneric alpine relatives. Thus, the links between diversity, herbivore diet specialization, and plant resistance along an elevation gradient suggest a causal relationship analogous to that hypothesized along latitudinal gradients.
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Habitat suitability models, which relate species occurrences to environmental variables, are assumed to predict suitable conditions for a given species. If these models are reliable, they should relate to change in plant growth and function. In this paper, we ask the question whether habitat suitability models are able to predict variation in plant functional traits, often assumed to be a good surrogate for a species' overall health and vigour. Using a thorough sampling design, we show a tight link between variation in plant functional traits and habitat suitability for some species, but not for others. Our contrasting results pave the way towards a better understanding of how species cope with varying habitat conditions and demonstrate that habitat suitability models can provide meaningful descriptions of the functional niche in some cases, but not in others.
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Introduction: As part of the MicroArray Quality Control (MAQC)-II project, this analysis examines how the choice of univariate feature-selection methods and classification algorithms may influence the performance of genomic predictors under varying degrees of prediction difficulty represented by three clinically relevant endpoints. Methods: We used gene-expression data from 230 breast cancers (grouped into training and independent validation sets), and we examined 40 predictors (five univariate feature-selection methods combined with eight different classifiers) for each of the three endpoints. Their classification performance was estimated on the training set by using two different resampling methods and compared with the accuracy observed in the independent validation set. Results: A ranking of the three classification problems was obtained, and the performance of 120 models was estimated and assessed on an independent validation set. The bootstrapping estimates were closer to the validation performance than were the cross-validation estimates. The required sample size for each endpoint was estimated, and both gene-level and pathway-level analyses were performed on the obtained models. Conclusions: We showed that genomic predictor accuracy is determined largely by an interplay between sample size and classification difficulty. Variations on univariate feature-selection methods and choice of classification algorithm have only a modest impact on predictor performance, and several statistically equally good predictors can be developed for any given classification problem.