116 research outputs found

    Barley plasma membrane intrinsic proteins (PIP aquaporins) as water and CO2 transporters

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    We identified barley aquaporins and demonstrated that one, HvPIP2;1, transports water and CO2. Regarding water homeostasis in plants, regulations of aquaporin expression were observed in many plants under several environmental stresses. Under salt stress, a number of plasma membrane-type aquaporins were down-regulated, which can prevent continuous dehydration resulting in cell death. The leaves of transgenic rice plants that expressed the largest amount of HvPIP2;1 showed a 40% increase in internal CO2 conductance compared with leaves of wild-type rice plants. The rate of CO2 assimilation also increased in the transgenic plants. The goal of our plant aquaporin research is to determine the key aquaporin species responsible for water and CO2 transport, and to improve plant water relations, stress tolerance, CO2 uptake or assimilation, and plant productivity via molecular breeding of aquaporins.</p

    Revealing the Functional Neuroanatomy of Intrinsic Alertness Using fMRI: Methodological Peculiarities

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    Clinical observations and neuroimaging data revealed a right-hemisphere fronto-parietal-thalamic-brainstem network for intrinsic alertness, and additional left fronto-parietal activity during phasic alertness. The primary objective of this fMRI study was to map the functional neuroanatomy of intrinsic alertness as precisely as possible in healthy participants, using a novel assessment paradigm already employed in clinical settings. Both the paradigm and the experimental design were optimized to specifically assess intrinsic alertness, while at the same time controlling for sensory-motor processing. The present results suggest that the processing of intrinsic alertness is accompanied by increased activity within the brainstem, thalamus, anterior cingulate gyrus, right insula, and right parietal cortex. Additionally, we found increased activation in the left hemisphere around the middle frontal gyrus (BA 9), the insula, the supplementary motor area, and the cerebellum. Our results further suggest that rather minute aspects of the experimental design may induce aspects of phasic alertness, which in turn might lead to additional brain activation in left-frontal areas not normally involved in intrinsic alertness. Accordingly, left BA 9 activation may be related to co-activation of the phasic alertness network due to the switch between rest and task conditions functioning as an external warning cue triggering the phasic alertness network. Furthermore, activation of the intrinsic alertness network during fixation blocks due to enhanced expectancy shortly before the switch to the task block might, when subtracted from the task block, lead to diminished activation in the typical right hemisphere intrinsic alertness network. Thus, we cautiously suggest that – as a methodological artifact – left frontal activations might show up due to phasic alertness involvement and intrinsic alertness activations might be weakened due to contrasting with fixation blocks, when assessing the functional neuroanatomy of intrinsic alertness with a block design in fMRI studies

    Investigations into a putative role for the novel BRASSIKIN pseudokinases in compatible pollen-stigma interactions in Arabidopsis thaliana.

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    BACKGROUND: In the Brassicaceae, the early stages of compatible pollen-stigma interactions are tightly controlled with early checkpoints regulating pollen adhesion, hydration and germination, and pollen tube entry into the stigmatic surface. However, the early signalling events in the stigma which trigger these compatible interactions remain unknown. RESULTS: A set of stigma-expressed pseudokinase genes, termed BRASSIKINs (BKNs), were identified and found to be present in only core Brassicaceae genomes. In Arabidopsis thaliana Col-0, BKN1 displayed stigma-specific expression while the BKN2 gene was expressed in other tissues as well. CRISPR deletion mutations were generated for the two tandemly linked BKNs, and very mild hydration defects were observed for wild-type Col-0 pollen when placed on the bkn1/2 mutant stigmas. In further analyses, the predominant transcript for the stigma-specific BKN1 was found to have a premature stop codon in the Col-0 ecotype, but a survey of the 1001 Arabidopsis genomes uncovered three ecotypes that encoded a full-length BKN1 protein. Furthermore, phylogenetic analyses identified intact BKN1 orthologues in the closely related outcrossing Arabidopsis species, A. lyrata and A. halleri. Finally, the BKN pseudokinases were found to be plasma-membrane localized through the dual lipid modification of myristoylation and palmitoylation, and this localization would be consistent with a role in signaling complexes. CONCLUSION: In this study, we have characterized the novel Brassicaceae-specific family of BKN pseudokinase genes, and examined the function of BKN1 and BKN2 in the context of pollen-stigma interactions in A. thaliana Col-0. Additionally, premature stop codons were identified in the predicted stigma specific BKN1 gene in a number of the 1001 A. thaliana ecotype genomes, and this was in contrast to the out-crossing Arabidopsis species which carried intact copies of BKN1. Thus, understanding the function of BKN1 in other Brassicaceae species will be a key direction for future studies

    Microarray analysis and scale-free gene networks identify candidate regulators in drought-stressed roots of loblolly pine (P. taeda L.)

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    <p>Abstract</p> <p>Background</p> <p>Global transcriptional analysis of loblolly pine (<it>Pinus taeda </it>L.) is challenging due to limited molecular tools. PtGen2, a 26,496 feature cDNA microarray, was fabricated and used to assess drought-induced gene expression in loblolly pine propagule roots. Statistical analysis of differential expression and weighted gene correlation network analysis were used to identify drought-responsive genes and further characterize the molecular basis of drought tolerance in loblolly pine.</p> <p>Results</p> <p>Microarrays were used to interrogate root cDNA populations obtained from 12 genotype × treatment combinations (four genotypes, three watering regimes). Comparison of drought-stressed roots with roots from the control treatment identified 2445 genes displaying at least a 1.5-fold expression difference (false discovery rate = 0.01). Genes commonly associated with drought response in pine and other plant species, as well as a number of abiotic and biotic stress-related genes, were up-regulated in drought-stressed roots. Only 76 genes were identified as differentially expressed in drought-recovered roots, indicating that the transcript population can return to the pre-drought state within 48 hours. Gene correlation analysis predicts a scale-free network topology and identifies eleven co-expression modules that ranged in size from 34 to 938 members. Network topological parameters identified a number of central nodes (hubs) including those with significant homology (E-values ≀ 2 × 10<sup>-30</sup>) to 9-cis-epoxycarotenoid dioxygenase, zeatin O-glucosyltransferase, and ABA-responsive protein. Identified hubs also include genes that have been associated previously with osmotic stress, phytohormones, enzymes that detoxify reactive oxygen species, and several genes of unknown function.</p> <p>Conclusion</p> <p>PtGen2 was used to evaluate transcriptome responses in loblolly pine and was leveraged to identify 2445 differentially expressed genes responding to severe drought stress in roots. Many of the genes identified are known to be up-regulated in response to osmotic stress in pine and other plant species and encode proteins involved in both signal transduction and stress tolerance. Gene expression levels returned to control values within a 48-hour recovery period in all but 76 transcripts. Correlation network analysis indicates a scale-free network topology for the pine root transcriptome and identifies central nodes that may serve as drivers of drought-responsive transcriptome dynamics in the roots of loblolly pine.</p

    The Emergence of Emotions

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    Emotion is conscious experience. It is the affective aspect of consciousness. Emotion arises from sensory stimulation and is typically accompanied by physiological and behavioral changes in the body. Hence an emotion is a complex reaction pattern consisting of three components: a physiological component, a behavioral component, and an experiential (conscious) component. The reactions making up an emotion determine what the emotion will be recognized as. Three processes are involved in generating an emotion: (1) identification of the emotional significance of a sensory stimulus, (2) production of an affective state (emotion), and (3) regulation of the affective state. Two opposing systems in the brain (the reward and punishment systems) establish an affective value or valence (stimulus-reinforcement association) for sensory stimulation. This is process (1), the first step in the generation of an emotion. Development of stimulus-reinforcement associations (affective valence) serves as the basis for emotion expression (process 2), conditioned emotion learning acquisition and expression, memory consolidation, reinforcement-expectations, decision-making, coping responses, and social behavior. The amygdala is critical for the representation of stimulus-reinforcement associations (both reward and punishment-based) for these functions. Three distinct and separate architectural and functional areas of the prefrontal cortex (dorsolateral prefrontal cortex, orbitofrontal cortex, anterior cingulate cortex) are involved in the regulation of emotion (process 3). The regulation of emotion by the prefrontal cortex consists of a positive feedback interaction between the prefrontal cortex and the inferior parietal cortex resulting in the nonlinear emergence of emotion. This positive feedback and nonlinear emergence represents a type of working memory (focal attention) by which perception is reorganized and rerepresented, becoming explicit, functional, and conscious. The explicit emotion states arising may be involved in the production of voluntary new or novel intentional (adaptive) behavior, especially social behavior

    Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

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    In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field
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