501 research outputs found
Alimentary tract proteinases of the Southern corn rootworm (Diabrotica undecimpunctata howardi) and the potential of potato Kunitz proteinase inhibitors for larval control.
Proteolytic digestion by larval Diabrotica undecimpunctata howardi (Barber) (D.undecimpunctata) has been investigated with the aim of producing transgenic plants possessing enhanced resistance to this economically important crop pest. Biochemical characterisation in vitro by pH dependent hydrolysis and inhibition assays incorporating E-64, pepstatin A and soybean Kunitz trypsin inhibitor showed the majority of hydrolytic activity occurs at pH 5.5 and is performed by cysteine and aspartic endopeptidases. Cysteine and aspartic proteinase encoding clones were isolated from a larval alimentary tract cDNA library. Four cathepsin L-like cysteine proteinases and two cathepsin D-like aspartic proteinase cDNA clones were identified by codmg homology to known proteinase sequences. Analysis of primary and secondary sequence features revealed D. undecimpunctata aspartic proteinase 1 exhibits features associated with cathepsins E and is proposed to be a D. undecimpunctata cathepsm E-like aspartic proteinase.Cathepsin D-like aspartic proteinase inhibitors of the potato Kunitz protemase inhibitor (PKPI) family have been isolated by PCR and expressed employing the pET expression system (Novagen). In vitro assays demonstrated the inhibitory activity of PKPI-A and PKPl-B inhibitors against larval D. undecimpunctata alimentary tract proteolytic enzymes. To the authors knowledge this work represents the first reporting of the expression and purification of biologically active PKPI proteins. In vitro assays incorporating oryzacystatin I and PKPI proteins resulted in increased inhibition of proteolytic activity compared to single inhibitor and uninhibited control reactions. Inhibition assays provide evidence for the potential of a dual protemase inhibitor strategy to arrest protein hydrolysis by larval D. undecimpunctata, preventing essential amino acid absorption. Further research is necessary to characterise the properties of the digestive enzymes isolated in this work and the inhibitory spectrum of PKPI proteins. Transgenic crops expressing a combination of oryzacystatin and PKPI proteins would be predicted to show enhanced resistance to insect herbivores by virtue of digestive proteolysis inhibition
El SPC de UK Met Office MOGREPS
El Servicio Meteorológico británico, United Kingdom Met Office o, abreviadamente, Met Office disfruta, entre otros sistemas de predicción numérica, de un sistema de predicción por conjuntos (SPC) que abarca todas las escalas tanto espaciales como, por ende, temporales. El así llamado Met Office Global and Regional Ensemble
Prediction System, MOGREPS, es decir, SPC global y regional de Met Office, consta de una componente global y otra regional para generar información sobre la incertidumbre atmosférica, principalmente enfocado a las previsiones a corto plazo. El sistema está diseñado especialmente para ayudar en la predicción del desarrollo de tormentas rápidas, viento, lluvia, nieve y niebla
Met Office Weather Game Survey 2011
This dataset contains game play results and demographic data collected from participants in the 2011 Met Office weather game. The game was designed to determine the best methods of communicating uncertainty in rainfall and temperature forecasts, and to widen public engagement in uncertainty in weather forecasting.
Within the ‘ice-cream seller’ scenario of the game participants were asked to make decisions based on rainfall and temperature forecasts presented in different ways. The game was designed with a randomised structure to enable participants to experience being ‘lucky’ or ‘unlucky’ when the most likely forecast scenario did not occur.
The database contains the game play selections from over 8000 unique participants and the scores that they achieved in the game. Data were also collected on participant age, gender, location and educational attainment
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The Met Office weather game: investigating how different methods for presenting probabilistic weather forecasts influence decision-making
To inform the way probabilistic forecasts would be displayed on their website, the UK Met Office ran an online game as a mass participation experiment to highlight the best methods of communicating uncertainty in rainfall and temperature forecasts, and to widen public engagement in uncertainty in weather forecasting. The game used a hypothetical “ice-cream seller” scenario and a randomized structure to test decision-making ability using different methods of representing uncertainty and to enable participants to experience being “lucky” or “unlucky” when the most likely
forecast scenario did not occur.
Data were collected on participant age, gender, educational attainment, and previous experience of environmental modelling. The large number of participants (n > 8000) that played the game has led to the collation of a unique large dataset with which to compare the impact on the decision-making ability of different weather forecast presentation ormats. This analysis demonstrates that within the game the provision of information regarding forecast uncertainty greatly improved decision-making ability and did not cause confusion in situations where providing the uncertainty added no further information
On the use of Bayesian decision theory for issuing natural hazard warnings
This is the final version of the article. Available from the Royal Society via the DOI in this record.Warnings for natural hazards improve societal resilience and are a good example of decision-making under uncertainty. A warning system is only useful if well defined and thus understood by stakeholders. However, most operational warning systems are heuristic: not formally or transparently defined. Bayesian decision theory provides a framework for issuing warnings under uncertainty but has not been fully exploited. Here, a decision theoretic framework is proposed for hazard warnings. The framework allows any number of warning levels and future states of nature, and a mathematical model for constructing the necessary loss functions for both generic and specific end-users is described. The approach is illustrated using one-day ahead warnings of daily severe precipitation over the UK, and compared to the current decision tool used by the UK Met Office. A probability model is proposed to predict precipitation, given ensemble forecast information, and loss functions are constructed for two generic stakeholders: an end-user and a forecaster. Results show that the Met Office tool issues fewer high-level warnings compared with our system for the generic end-user, suggesting the former may not be suitable for risk averse end-users. In addition, raw ensemble forecasts are shown to be unreliable and result in higher losses from warnings.This work was supported by the Natural Environment Research Council (Consortium on Risk in the Environment: Diagnostics, Integration, Benchmarking, Learning and Elicitation (CREDIBLE); grant no. NE/J017043/1)
On the predictability of extremes: Does the butterfly effect ever decrease?
This is the peer reviewed version of the following article: Sterk, A. E., Stephenson, D. B., Holland, M. P. and Mylne, K. R. (2015), On the predictability of extremes: Does the butterfly effect ever decrease?. Quarterly Journal of the Royal Meteorological Society, which has been published in final form at http://dx.doi.org/10.1002/qj.2627. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving: http://olabout.wiley.com/WileyCDA/Section/id-820227.html#termsThis study investigates whether or not predictability always decreases for more extreme events. Predictability is measured by the Mean Squared Error (MSE), estimated here from the difference of pairs of ensemble forecasts, conditioned on one of the forecast variables (the 'pseudo-observation') exceeding a threshold. Using an exchangeable linear regression model for pairs of forecast variables, we show that the MSE can be decomposed into the sum of three terms: a threshold-independent constant, a mean term that always increases with threshold, and a variance term that can either increase, decrease, or stay constant with threshold. Using the generalised Pareto distribution to model wind speed excesses over a threshold, we show that MSE always increases with threshold at sufficiently high threshold. However, MSE can be a decreasing function of threshold at lower thresholds but only if the forecasts have finite upper bounds. The methods are illustrated by application to daily wind speed forecasts for London made using the 24 member Met Office Global and Regional Ensemble Prediction System from 1 January 2009 to 31 May 2011. For this example, the mean term increases faster than the variance term decreases with increasing threshold, and so predictability decreases for more extreme events.Engineering and Physical Sciences Research Council (EPSRC)Netherlands Organisation for Scientific Research (NWO
Protocol: A simple phenol-based method for 96-well extraction of high quality RNA from Arabidopsis
Background: Many experiments in modern plant molecular biology require the processing of large numbers of samples for a variety of applications from mutant screens to the analysis of natural variants. A severe bottleneck to many such analyses is the acquisition of good yields of high quality RNA suitable for use in sensitive downstream applications such as real time quantitative reverse-transcription-polymerase chain reaction (real time qRT-PCR). Although several commercial kits are available for high-throughput RNA extraction in 96-well format, only one non-kit method has been described in the literature using the commercial reagent TRIZOL.Results: We describe an unusual phenomenon when using TRIZOL reagent with young Arabidopsis seedlings. This prompted us to develop a high-throughput RNA extraction protocol (HTP96) adapted from a well established phenol:chloroform-LiCl method (P:C-L) that is cheap, reliable and requires no specialist equipment. With this protocol 192 high quality RNA samples can be prepared in 96-well format in three hours (less than 1 minute per sample) with less than 1% loss of samples. We demonstrate that the RNA derived from this protocol is of high quality and suitable for use in real time qRT-PCR assays.Conclusion: The development of the HTP96 protocol has vastly increased our sample throughput, allowing us to fully exploit the large sample capacity of modern real time qRT-PCR thermocyclers, now commonplace in many labs, and develop an effective high-throughput gene expression platform. We propose that the HTP96 protocol will significantly benefit any plant scientist with the task of obtaining hundreds of high quality RNA extractions
Modelling extreme concentration from a source in a turbulent flow over rough wall
The concentration fluctuations in passive plumes from an elevated and a groundlevel
source in a turbulent boundary layer over a rough wall were studied using
large eddy simulation and wind tunnel experiment. The predictions of statistics
up to second order moments were thereby validated. In addition, the trend of relative
fluctuations far downstream for a ground level source was estimated using
dimensional analysis. The techniques of extreme value theory were then applied
to predict extreme concentrations by modelling the upper tail of the probability
density function of the concentration time series by the Generalised Pareto Distribution.
Data obtained from both the simulations and experiments were analysed in
this manner. The predicted maximum concentration (?0) normalized by the local
mean concentration (Cm) or by the local r.m.s of concentration fluctuation (crms),
was extensively investigated. Values for ?0/Cm and ?0/crms as large as 50 and 20
respectively were found for the elevated source and 10 and 15 respectively for the
ground-level source
The Arabidopsis B3 domain protein VERNALIZATION1 is involved in processes essential for development with structural and mutational studies revealing its DNA binding surface
The B3 DNA-binding domain is a plant-specific domain found throughout the plant kingdom from the alga Chlamydomonas to grasses and flowering plants. Over 100 B3 domain-containing proteins are found in the model plant Arabidopsis thaliana, and one of these is critical for accelerating flowering in response to prolonged cold treatment, an epigenetic process called vernalization. Despite the specific phenotype of genetic vrn1 mutants, the VERNALIZATION1 (VRN1) protein localizes throughout the nucleus and shows sequence-nonspecific binding in vitro. In this work, we used a dominant repressor tag that overcomes genetic redundancy to show that VRN1 is involved in processes beyond vernalization that are essential for Arabidopsis development. To understand its sequence-nonspecific binding, we crystallized VRN1(208-341) and solved its crystal structure to 1.6 angstrom resolution using selenium/single-wavelength anomalous diffraction methods. The crystallized construct comprises the second VRN1 B3 domain and a preceding region conserved among VRN1 orthologs but absent in other B3 domains. We established the DNA-binding face using NMR and then mutated positively charged residues on this surface with a series of 16 Ala and Glu substitutions, ensuring that the protein fold was not disturbed using heteronuclear single quantum correlation NMR spectra. The triple mutant R249E/R289E/R296E was almost completely incapable of DNA binding in vitro. Thus, we have revealed that although VRN1 is sequence-nonspecific in DNA binding, it has a defined DNA-binding surface
Identification of candidates for cyclotide biosynthesis and cyclisation by expressed sequence tag analysis of Oldenlandia affinis
<p>Abstract</p> <p>Background</p> <p>Cyclotides are a family of circular peptides that exhibit a range of biological activities, including anti-bacterial, cytotoxic, anti-HIV activities, and are proposed to function in plant defence. Their high stability has motivated their development as scaffolds for the stabilisation of peptide drugs. <it>Oldenlandia affinis</it> is a member of the Rubiaceae (coffee) family from which 18 cyclotides have been sequenced to date, but the details of their processing from precursor proteins have only begun to be elucidated. To increase the speed at which genes involved in cyclotide biosynthesis and processing are being discovered, an expressed sequence tag (EST) project was initiated to survey the transcript profile of <it>O. affinis</it> and to propose some future directions of research on in vivo protein cyclisation.</p> <p>Results</p> <p>Using flow cytometry the holoploid genome size (1C-value) of <it>O. affinis </it>was estimated to be 4,210 - 4,284 Mbp, one of the largest genomes of the Rubiaceae family. High-quality ESTs were identified, 1,117 in total, from leaf cDNAs and assembled into 502 contigs, comprising 202 consensus sequences and 300 singletons. ESTs encoding the cyclotide precursors for kalata B1 (<it>Oak1</it>) and kalata B2 (<it>Oak4</it>) were among the 20 most abundant ESTs. In total, 31 ESTs encoded cyclotide precursors, representing a distinct commitment of 2.8% of the <it>O. affinis </it>transcriptome to cyclotide biosynthesis. The high expression levels of cyclotide precursor transcripts are consistent with the abundance of mature cyclic peptides in <it>O. affinis</it>. A new cyclotide precursor named <it>Oak5 </it>was isolated and represents the first cDNA for the bracelet class of cyclotides in <it>O. affinis</it>. Clones encoding enzymes potentially involved in processing cyclotides were also identified and include enzymes involved in oxidative folding and proteolytic processing.</p> <p>Conclusion</p> <p>The EST library generated in this study provides a valuable resource for the study of the cyclisation of plant peptides. Further analysis of the candidates for cyclotide processing discovered in this work will increase our understanding and aid in reconstructing cyclotide production using transgenic systems and will benefit their development in pharmaceutical applications and insect-resistant crop plants.</p
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