Towards a fair comparison of statistical and dynamical downscaling in the framework of the EURO-CORDEX initiative

Both statistical and dynamical downscaling methods are well established techniques to bridge the gap between the coarse information produced by global circulation models and the regional-to-local scales required by the climate change Impacts, Adaptation, and Vulnerability (IAV) communities. A number of studies have analyzed the relative merits of each technique by inter-comparing their performance in reproducing the observed climate, as given by a number of climatic indices (e.g. mean values, percentiles, spells). However, in this paper we stress that fair comparisons should be based on indices that are not affected by the calibration towards the observed climate used for some of the methods. We focus on precipitation (over continental Spain) and consider the output of eight Regional Climate Models (RCMs) from the EURO-CORDEX initiative at 0.44? resolution and five Statistical Downscaling Methods (SDMs) ?analog resampling, weather typing and generalized linear models? trained using the Spain044 observational gridded dataset on exactly the same RCM grid. The performance of these models is inter-compared in terms of several standard indices ?mean precipitation, 90th percentile on wet days, maximum precipitation amount and maximum number of consecutive dry days? taking into account the parameters involved in the SDM training phase. It is shown, that not only the directly affected indices should be carefully analyzed, but also those indirectly influenced (e.g. percentile-based indices for precipitation) which are more difficult to identify. We also analyze how simple transformations (e.g. linear scaling) could be applied to the outputs of the uncalibrated methods in order to put SDMs and RCMs on equal footing, and thus perform a fairer comparison.We acknowledge the World Climate Research Programme’s Working Group on Regional Climate, and theWorking Group on CoupledModelling, former coordinating body of CORDEX and responsible panel for CMIP5. We also thank the climate modeling groups (listed in Table 1 of this paper) for producing and making available their model output. We also acknowledge the Earth System Grid Federation infrastructure and AEMET and University of Cantabria for the Spain02 dataset (available at http: //www.meteo.unican.es/en/datasets/spain02). All the statistical downscaling experiments have been computed using theMeteoLab software (http://www.meteo.unican.es/software/meteolab), which is an open-source Matlab toolbox for statistical downscaling. This work has been partially supported by CORWES (CGL2010-22158-C02) and EXTREMBLES (CGL2010-21869) projects funded by the Spanish R&D programme. AC thanks the Spanish Ministry of Economy and Competitiveness for the funding provided within the FPI programme (BES-2011-047612 and EEBB-I-13-06354), JMG acknowledges the support from the SPECS project (FP7-ENV-2012-308378) and JF is grateful to the EUPORIAS project (FP7-ENV-2012-308291). We also thank three anonymous referees for their useful comments that helped to improve the original manuscript

Comparing correction methods of RCM outputs for improving crop impact projections in the Iberian Peninsula for 21st century

Assessment of climate change impacts on crops in regions of complex orography such as the Iberian Peninsula (IP) requires climate model output which is able to describe accurately the observed climate. The high resolution of output provided by Regional Climate Models (RCMs) is expected to be a suitable tool to describe regional and local climatic features, although their simulation results may still present biases. For these reasons, we compared several post-processing methods to correct or reduce the biases of RCM simulations from the ENSEMBLES project for the IP. The bias-corrected datasets were also evaluated in terms of their applicability and consequences in improving the results of a crop model to simulate maize growth and development at two IP locations, using this crop as a reference for summer cropping systems in the region. The use of bias-corrected climate runs improved crop phenology and yield simulation overall and reduced the inter-model variability and thus the uncertainty. The number of observational stations underlying each reference observational dataset used to correct the bias affected the correction performance. Although no single technique showed to be the best one, some methods proved to be more adequate for small initial biases, while others were useful when initial biases were so large as to prevent data application for impact studies. An initial evaluation of the climate data, the bias correction/reduction method and the consequences for impact assessment would be needed to design the most robust, reduced uncertainty ensemble for a specific combination of location, crop, and crop management

Gene expression analysis after receptor tyrosine kinase activation reveals new potential melanoma proteins

<p>Abstract</p> <p>Background</p> <p>Melanoma is an aggressive tumor with increasing incidence. To develop accurate prognostic markers and targeted therapies, changes leading to malignant transformation of melanocytes need to be understood. In the <it>Xiphophorus </it>melanoma model system, a mutated version of the EGF receptor Xmrk (<it>Xiphophorus </it>melanoma receptor kinase) triggers melanomagenesis. Cellular events downstream of Xmrk, such as the activation of Akt, Ras, B-Raf or Stat5, were also shown to play a role in human melanomagenesis. This makes the elucidation of Xmrk downstream targets a useful method for identifying processes involved in melanoma formation.</p> <p>Methods</p> <p>Here, we analyzed Xmrk-induced gene expression using a microarray approach. Several highly expressed genes were confirmed by realtime PCR, and pathways responsible for their induction were revealed using small molecule inhibitors. The expression of these genes was also monitored in human melanoma cell lines, and the target gene <it>FOSL1 </it>was knocked down by siRNA. Proliferation and migration of siRNA-treated melanoma cell lines were then investigated.</p> <p>Results</p> <p>Genes with the strongest upregulation after receptor activation were FOS-like antigen 1 (<it>Fosl1</it>), early growth response 1 (<it>Egr1</it>), osteopontin (<it>Opn</it>), insulin-like growth factor binding protein 3 (<it>Igfbp3</it>), dual-specificity phosphatase 4 (<it>Dusp4</it>), and tumor-associated antigen L6 (<it>Taal6</it>). Interestingly, most genes were blocked in presence of a SRC kinase inhibitor. Importantly, we found that <it>FOSL1</it>, <it>OPN</it>, <it>IGFBP3</it>, <it>DUSP4</it>, and <it>TAAL6 </it>also exhibited increased expression levels in human melanoma cell lines compared to human melanocytes. Knockdown of <it>FOSL1 </it>in human melanoma cell lines reduced their proliferation and migration.</p> <p>Conclusion</p> <p>Altogether, the data show that the receptor tyrosine kinase Xmrk is a useful tool in the identification of target genes that are commonly expressed in Xmrk-transgenic melanocytes and melanoma cell lines. The identified molecules constitute new possible molecular players in melanoma development. Specifically, a role of FOSL1 in melanomagenic processes is demonstrated. These data are the basis for future detailed analyses of the investigated target genes.</p

Coordinated Sumoylation and Ubiquitination Modulate EGF Induced EGR1 Expression and Stability

Abstract: Background: Human early growth response-1 (EGR1) is a member of the zing-finger family of transcription factors induced by a range of molecular and environmental stimuli including epidermal growth factor (EGF). In a recently published paper we demonstrated that integrin/EGFR cross-talk was required for Egr1 expression through activation of the Erk1/2 and PI3K/Akt/Forkhead pathways. EGR1 activity and stability can be influenced by many different post-translational modifications such as acetylation, phosphorylation, ubiquitination and the recently discovered sumoylation. The aim of this work was to assess the influence of sumoylation on EGF induced Egr1 expression and/or stability. Methods: We modulated the expression of proteins involved in the sumoylation process in ECV304 cells by transient transfection and evaluated Egr1 expression in response to EGF treatment at mRNA and protein levels. Results: We demonstrated that in ECV304 cells Egr1 was transiently induced upon EGF treatment and a fraction of the endogenous protein was sumoylated. Moreover, SUMO-1/Ubc9 over-expression stabilized EGF induced ERK1/2 phosphorylation and increased Egr1 gene transcription. Conversely, in SUMO-1/Ubc9 transfected cells, EGR1 protein levels were strongly reduced. Data obtained from protein expression and ubiquitination analysis, in the presence of the proteasome inhibitor MG132, suggested that upon EGF stimuli EGR1 sumoylation enhanced its turnover, increasing ubiquitination and proteasome mediated degradation. Conclusions: Here we demonstrate that SUMO-1 modification improving EGR1 ubiquitination is involved in the modulation of its stability upon EGF mediated induction

Conserved Expression Signatures between Medaka and Human Pigment Cell Tumors

Aberrations in gene expression are a hallmark of cancer cells. Differential tumor-specific transcript levels of single genes or whole sets of genes may be critical for the neoplastic phenotype and important for therapeutic considerations or useful as biomarkers. As an approach to filter out such relevant expression differences from the plethora of changes noted in global expression profiling studies, we searched for changes of gene expression levels that are conserved. Transcriptomes from massive parallel sequencing of different types of melanoma from medaka were generated and compared to microarray datasets from zebrafish and human melanoma. This revealed molecular conservation at various levels between fish models and human tumors providing a useful strategy for identifying expression signatures strongly associated with disease phenotypes and uncovering new melanoma molecules

A proteomic approach to investigating gene cluster expression and secondary metabolite functionality in Aspergillus fumigatus.

A combined proteomics and metabolomics approach was utilised to advance the identification and characterisation of secondary metabolites in Aspergillus fumigatus. Here, implementation of a shotgun proteomic strategy led to the identification of non-redundant mycelial proteins (n = 414) from A. fumigatus including proteins typically under-represented in 2-D proteome maps: proteins with multiple transmembrane regions, hydrophobic proteins and proteins with extremes of molecular mass and pI. Indirect identification of secondary metabolite cluster expression was also achieved, with proteins (n = 18) from LaeA-regulated clusters detected, including GliT encoded within the gliotoxin biosynthetic cluster. Biochemical analysis then revealed that gliotoxin significantly attenuates H2O2-induced oxidative stress in A. fumigatus (p>0.0001), confirming observations from proteomics data. A complementary 2-D/LC-MS/MS approach further elucidated significantly increased abundance (p<0.05) of proliferating cell nuclear antigen (PCNA), NADH-quinone oxidoreductase and the gliotoxin oxidoreductase GliT, along with significantly attenuated abundance (p<0.05) of a heat shock protein, an oxidative stress protein and an autolysis-associated chitinase, when gliotoxin and H2O2 were present, compared to H2O2 alone. Moreover, gliotoxin exposure significantly reduced the abundance of selected proteins (p<0.05) involved in de novo purine biosynthesis. Significantly elevated abundance (p<0.05) of a key enzyme, xanthine-guanine phosphoribosyl transferase Xpt1, utilised in purine salvage, was observed in the presence of H2O2 and gliotoxin. This work provides new insights into the A. fumigatus proteome and experimental strategies, plus mechanistic data pertaining to gliotoxin functionality in the organism

Bacteria Modulate the CD8+ T Cell Epitope Repertoire of Host Cytosol-Exposed Proteins to Manipulate the Host Immune Response

The main adaptive immune response to bacteria is mediated by B cells and CD4+ T-cells. However, some bacterial proteins reach the cytosol of host cells and are exposed to the host CD8+ T-cells response. Both gram-negative and gram-positive bacteria can translocate proteins to the cytosol through type III and IV secretion and ESX-1 systems, respectively. The translocated proteins are often essential for the bacterium survival. Once injected, these proteins can be degraded and presented on MHC-I molecules to CD8+ T-cells. The CD8+ T-cells, in turn, can induce cell death and destroy the bacteria's habitat. In viruses, escape mutations arise to avoid this detection. The accumulation of escape mutations in bacteria has never been systematically studied. We show for the first time that such mutations are systematically present in most bacteria tested. We combine multiple bioinformatic algorithms to compute CD8+ T-cell epitope libraries of bacteria with secretion systems that translocate proteins to the host cytosol. In all bacteria tested, proteins not translocated to the cytosol show no escape mutations in their CD8+ T-cell epitopes. However, proteins translocated to the cytosol show clear escape mutations and have low epitope densities for most tested HLA alleles. The low epitope densities suggest that bacteria, like viruses, are evolutionarily selected to ensure their survival in the presence of CD8+ T-cells. In contrast with most other translocated proteins examined, Pseudomonas aeruginosa's ExoU, which ultimately induces host cell death, was found to have high epitope density. This finding suggests a novel mechanism for the manipulation of CD8+ T-cells by pathogens. The ExoU effector may have evolved to maintain high epitope density enabling it to efficiently induce CD8+ T-cell mediated cell death. These results were tested using multiple epitope prediction algorithms, and were found to be consistent for most proteins tested

Substrate Specifity Profiling of the Aspergillus fumigatus Proteolytic Secretome Reveals Consensus Motifs with Predominance of Ile/Leu and Phe/Tyr

The filamentous fungus Aspergillus fumigatus (AF) can cause devastating infections in immunocompromised individuals. Early diagnosis improves patient outcomes but remains challenging because of the limitations of current methods. To augment the clinician's toolkit for rapid diagnosis of AF infections, we are investigating AF secreted proteases as novel diagnostic targets. The AF genome encodes up to 100 secreted proteases, but fewer than 15 of these enzymes have been characterized thus far. Given the large number of proteases in the genome, studies focused on individual enzymes may overlook potential diagnostic biomarkers.As an alternative, we employed a combinatorial library of internally quenched fluorogenic probes (IQFPs) to profile the global proteolytic secretome of an AF clinical isolate in vitro. Comparative protease activity profiling revealed 212 substrate sequences that were cleaved by AF secreted proteases but not by normal human serum. A central finding was that isoleucine, leucine, phenylalanine, and tyrosine predominated at each of the three variable positions of the library (44.1%, 59.1%, and 57.0%, respectively) among substrate sequences cleaved by AF secreted proteases. In contrast, fewer than 10% of the residues at each position of cleaved sequences were cationic or anionic. Consensus substrate motifs were cleaved by thermostable serine proteases that retained activity up to 50°C. Precise proteolytic cleavage sites were reliably determined by a simple, rapid mass spectrometry-based method, revealing predominantly non-prime side specificity. A comparison of the secreted protease activities of three AF clinical isolates revealed consistent protease substrate specificity fingerprints. However, secreted proteases of A. flavus, A. nidulans, and A. terreus strains exhibited striking differences in their proteolytic signatures.This report provides proof-of-principle for the use of protease substrate specificity profiling to define the proteolytic secretome of Aspergillus fumigatus. Expansion of this technique to protease secretion during infection could lead to development of novel approaches to fungal diagnosis