58 research outputs found

    On the forced unilateral orientation number of a graph

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    AbstractA graph has a unilateral orientation if its edges can be oriented such that for every two vertices u and v there exists either a path from u to v or a path from v to u. If G is a graph with a unilateral orientation, then the forced unilateral orientation number of G is defined to be the minimum cardinality of a subset of the set of edges for which there is an assignment of directions that has a unique extension to a unilateral orientation of G. This paper gives a general lower bound for the forced unilateral orientation number and shows that the unilateral orientation number of a graph of size m, order n, and having edge connectivity 1 is equal to m − n + 2. A few other related problems are discussed

    The necrotrophic effector protein SnTox3 re-programs metabolism and elicits a strong defence response in susceptible wheat leaves

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    BACKGROUND: The fungus Stagonospora nodorum is a necrotrophic pathogen of wheat. It causes disease by secreting proteinaceous effectors which interact with proteins encoded by dominant susceptibility genes in the host. The outcome of these interactions results in necrosis, allowing the fungus to thrive on dead plant material. The mechanisms of these effectors though are poorly understood. In this study, we undertake a comprehensive transcriptomics, proteomic and metabolomic approach to understand how a susceptible wheat cultivar responds to exposure to the Stagonospora nodorum effector protein SnTox3. RESULTS: Microarray and proteomic studies revealed that SnTox3 strongly induced responses consistent with those previously associated with classical host defence pathways including the expression of pathogenicity-related proteins and the induction of cell death. Collapse of the photosynthetic machinery was also apparent at the transcriptional and translational level. SnTox3-infiltrated wheat leaves also showed a strong induction of enzymes involved in primary metabolism consistent with increases in hexoses, amino acids and organic acids as determined by primary metabolite profiling. Methionine and homocysteine metabolism was strongly induced upon exposure to SnTox3. Pathogenicity in the presence of homocysteine was inhibited confirming that the compound has a role in plant defence. Consistent with the strong defence responses observed, secondary metabolite profiling revealed the induction of several compounds associated with plant defence, including the phenylpropanoids chlorogenic acid and feruloylquinic acid, and the cyanogenic glucoside dhurrin. Serotonin did not accumulate subsequent to SnTox3 infiltration.CONCLUSIONS: These data support the theory that the SnTox3 effector protein elicits a host cell death response to facilitate the pathogen’s necrotrophic infection cycle. Our data also demonstrate that the mechanism of SnTox3 appears distinct from the previously characterised Stagonospora nodorum effector SnToxA. Collectively, this comprehensive analysis has advanced our understanding of necrotrophic effector biology and highlighted the complexity of effector-triggered susceptibility.BW, LAD and PSS would like to acknowledge the financial support of the Grains Research and Development Corporation (ANU00016) and the Australian Research Council (DP0986139)

    Transcript and protein profiling identify candidate gene sets of potential adaptive significance in New Zealand Pachycladon

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    <p>Abstract</p> <p>Background</p> <p>Transcript profiling of closely related species provides a means for identifying genes potentially important in species diversification. However, the predictive value of transcript profiling for inferring downstream-physiological processes has been unclear. In the present study we use shotgun proteomics to validate inferences from microarray studies regarding physiological differences in three <it>Pachycladon </it>species. We compare transcript and protein profiling and evaluate their predictive value for inferring glucosinolate chemotypes characteristic of these species.</p> <p>Results</p> <p>Evidence from heterologous microarrays and shotgun proteomics revealed differential expression of genes involved in glucosinolate hydrolysis (myrosinase-associated proteins) and biosynthesis (methylthioalkylmalate isomerase and dehydrogenase), the interconversion of carbon dioxide and bicarbonate (carbonic anhydrases), water use efficiency (ascorbate peroxidase, 2 cys peroxiredoxin, 20 kDa chloroplastic chaperonin, mitochondrial succinyl CoA ligase) and others (glutathione-S-transferase, serine racemase, vegetative storage proteins, genes related to translation and photosynthesis). Differences in glucosinolate hydrolysis products were directly confirmed. Overall, prediction of protein abundances from transcript profiles was stronger than prediction of transcript abundance from protein profiles. Protein profiles also proved to be more accurate predictors of glucosinolate profiles than transcript profiles. The similarity of species profiles for both transcripts and proteins reflected previously inferred phylogenetic relationships while glucosinolate chemotypes did not.</p> <p>Conclusions</p> <p>We have used transcript and protein profiling to predict physiological processes that evolved differently during diversification of three <it>Pachycladon </it>species. This approach has also identified candidate genes potentially important in adaptation, which are now the focus of ongoing study. Our results indicate that protein profiling provides a valuable tool for validating transcript profiles in studies of adaptive divergence.</p

    Amyloid β Induces Early Changes in the Ribosomal Machinery, Cytoskeletal Organization and Oxidative Phosphorylation in Retinal Photoreceptor Cells

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    Amyloid β (Aβ) accumulation and its aggregation is characteristic molecular feature of the development of Alzheimer’s disease (AD). More recently, Aβ has been suggested to be associated with retinal pathology associated with AD, glaucoma and drusen deposits in age related macular degeneration (AMD). In this study, we investigated the proteins and biochemical networks that are affected by Aβ in the 661 W photoreceptor cells in culture. Time and dose dependent effects of Aβ on the photoreceptor cells were determined utilizing tandem mass tag (TMT) labeling-based quantitative mass-spectrometric approach. Bioinformatic analysis of the data revealed concentration and time dependent effects of the Aβ peptide stimulation on various key biochemical pathways that might be involved in mediating the toxicity effects of the peptide. We identified increased Tau phosphorylation, GSK3β dysregulation and reduced cell viability in cells treated with Aβ in a dose and time dependent manner. This study has delineated for the first-time molecular networks in photoreceptor cells that are impacted early upon Aβ treatment and contrasted the findings with a longer-term treatment effect. Proteins associated with ribosomal machinery homeostasis, mitochondrial function and cytoskeletal organization were affected in the initial stages of Aβ exposure, which may provide key insights into AD effects on the photoreceptors and specific molecular changes induced by Aβ peptide

    Quantitative proteomic analysis of cabernet sauvignon grape cells exposed to thermal stresses reveals alterations in sugar and phenylpropanoid metabolism

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    Grapes (Vitis vinifera) are a valuable fruit crop and wine production is a major industry. Global warming and expanded range of cultivation will expose grapes to more temperature stresses in future. Our study investigated protein level responses to abiotic stresses, with particular reference to proteomic changes induced by the impact of four different temperature stress regimes, including both hot and cold temperatures, on cultured grape cells. Cabernet Sauvignon cell suspension cultures grown at 26°C were subjected to 14 h of exposure to 34 and 42°C for heat stress, and 18 and 10°C for cold stress. Cells from the five temperatures were harvested in biological triplicates and label-free quantitative shotgun proteomic analysis was performed. A total of 2042 non-redundant proteins were identified from the five temperature points. Fifty-five proteins were only detected in extreme heat stress conditions (42°C) and 53 proteins were only detected at extreme cold stress conditions (10°C). Gene Ontology (GO) annotations of differentially expressed proteins provided insights into the metabolic pathways that are involved in temperature stress in grape cells. Sugar metabolism displayed switching between alternative and classical pathways during temperature stresses. Additionally, nine proteins involved in the phenylpropanoid pathway were greatly increased in abundance at extreme cold stress, and were thus found to be cold-responsive proteins. All MS data have been deposited in the ProteomeXchange with identifier PXD000977 (http://proteomecentral.proteomexchange.org/dataset/PXD000977).13 page(s

    Differential metabolic response of cultured rice (Oryza sativa) cells exposed to high- And low-temperature stress

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    Global mean temperatures are expected to rise by 2–4.5°C by 2100, accompanied by an increase in frequency and amplitude of extreme temperature events. Greater climatic extremes and an expanded range of cultivation will expose rice to increasing stress in the future. Understanding gene expression in disparate thermal regimes is important for the engineering of cultivars with tolerance to nonoptimal temperatures. Our study investigated the proteomic responses of rice cell suspension cultures to sudden temperature changes. Cell cultures grown at 28°C were subjected to 3-day exposure to 12 or 20°C for low-temperature stress, and 36 or 44°C for high-temperature stress. Quantitative label-free shotgun proteomic analysis was performed on biological triplicates of each treatment. Over 1900 proteins were expressed in one or more temperature treatments, and, of these, more than 850 were found to be responsive to either of the temperature extremes. These temperature-responsive proteins included more than 300 proteins which were uniquely expressed at either 12 or 44°C. Our study also identified 40 novel stress–response proteins and observed that switching between the classical and the alternative pathways of sucrose metabolism occurs in response to extremes of temperature.19 page(s

    Differential regulation of aquaporins, small GTPases and V-ATPases proteins in rice leaves subjected to drought stress and recovery

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    Mechanisms of drought tolerance are complex, interacting, and polygenic. This paper describes patterns of gene expression at precise physiological stages of drought in 35-day-old seedlings of Oryza sativa cv. Nipponbare. Drought was imposed gradually for up to 15 days, causing abscisic acid levels to rise and growth to cease, and plants were then re-watered. Proteins were identified from leaf samples after moderate drought, extreme drought, and 3 and 6 days of re-watering. Label-free quantitative shotgun proteomics resulted in identification of 1548 non-redundant proteins. More proteins were down-regulated in early stages of drought but more were up-regulated as severe drought developed. After re-watering, there was notable down regulation, suggesting that stress-related proteins were being degraded. Proteins involved in signalling and transport became dominant as severe drought took hold but decreased again on re-watering. Most of the nine aquaporins identified were responsive to drought, with six decreasing rapidly in abundance as plants were re-watered. Nine G-proteins appeared in large amounts during severe drought and dramatically degraded once plants were re-watered. We speculate that water transport and drought signalling are critical elements of the overall response to drought in rice and might be the key to biotechnological approaches to drought tolerance.14 page(s

    Differential proteomic response of rice (Oryza sativa) leaves exposed to high- and low-temperature stress

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    Global mean surface temperature has been predicted to increase by 1.8-4°C within this century, accompanied by an increase in the magnitude and frequency of extreme temperature events. Developing rice cultivars better adapted to non-optimal temperatures is essential to increase rice yield in the future and, hence, understanding the molecular response of rice to temperature stress is necessary. In this study, we investigated the proteomic responses of leaves of 24-day-old rice seedlings to sudden temperature changes. Rice seedlings grown at 28/20°C (day/night) were subjected to 3-day exposure to 12/5°C or 20/12°C (day/night) for low-temperature stress, and 36/28°C or 44/36°C (day/night) for high-temperature stress, followed by quantitative label-free shotgun proteomic analysis on biological triplicates of each treatment. Out of over 1100 proteins identified in one or more temperature treatments, more than 400 were found to be responsive to temperature stress. Of these, 43, 126 and 47 proteins were exclusively found at 12/5, 20/12 and 44/36°C (day/night), respectively. Our results showed that a greater change occurs in the rice leaf proteome at 20/12°C (day/night) in comparison to other non-optimal temperature regimes. In addition, our study identified more than 20 novel stress-response proteins.12 page(s

    PloGO : plotting gene ontology annotation and abundance in multi-condition proteomics experiments

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    We describe the PloGO R package, a simple open-source tool for plotting gene ontology (GO) annotation and abundance information, which was developed to aid with the bioinformatics analysis of multi-condition label-free proteomics experiments using quantitation based on spectral counting. PloGO can incorporate abundance (raw spectral counts) or normalized spectral abundance factors (NSAF) data in addition to the GO annotation, as well as handle multiple files and allow for a targeted collection of GO categories of interest. Our main aims were to help identify interesting subsets of proteins for further analysis such as those arising from a protein data set partition based on the presence and absence or multiple pair-wise comparisons, as well as provide GO summaries that can be easily used in subsequent analyses. Though developed with label-free proteomics experiments in mind it is not specific to that approach and can be used for any multi-condition experiment for which GO information has been generated.5 page(s
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