Extreme events representation in CMCC-CM2 standard and high-resolution general circulation models

The recent advancements in climate modeling partially build on the improvement of horizontal resolution in different components of the simulating system. A higher resolution is expected to provide a better representation of the climate variability, and in this work we are particularly interested in the potential improvements in representing extreme events of high temperature and precipitation. The two versions of the Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC-CM2) model used here adopt the highest horizontal resolutions available within the last family of the global coupled climate models developed at CMCC to participate in the Coupled Model Intercomparison Projects, Phase 6 (CMIP6) effort. The main aim of this study is to document the ability of the CMCC-CM2 models to represent the spatial distribution of extreme events of temperature and precipitation, under the historical period, comparing model results to observations, the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5), multi-source weighted-ensemble precipitation (MSWEP) and Climate Hazards Group infrared precipitation with station data (CHIRPS) observations. For a more detailed evaluation we use both 6-hourly and daily time series, to compute indices representative of intense and extreme conditions. In terms of mean climate, the two models are able to realistically reproduce the main patterns of temperature and precipitation. The high resolution version ( ∘ horizontal resolution) of the atmospheric model provides better results than the standard resolution one (1°), not only in terms of means but also in terms of intense and extreme events of temperature defined at daily and 6-hourly frequencies. This is also the case of average and intense precipitation. On the other hand the extreme precipitation is not improved by the adoption of a higher horizontal resolution

The Euro-Mediterranean Center on Climate Change (CMCC) decadal prediction system

Decadal climate predictions, obtained by constraining the initial condition of a dynamical model through a truthful estimate of the observed climate state, provide an accurate assessment of near-term climate change and are a useful tool to inform decision-makers on future climate-related risks. Here we present results from the CMIP6 (Coupled Model Intercomparison Project Phase 6) Decadal Climate Prediction Project (DCPP) decadal hindcasts produced with the operational CMCC (Euro-Mediterranean Center on Climate Change) decadal prediction system (DPS), based on the fully coupled CMCC-CM2-SR5 dynamical model. A 20-member suite of 10-year retrospective forecasts, initialized every year from 1960 to 2020, is performed using a full-field initialization strategy. The predictive skill for key variables is assessed and compared with theskill of an ensemble of non-initialized historical simulations so as toquantify the added value of the initialization. In particular, the CMCC DPS is able to skillfully reproduce past climate surface and subsurface temperature fluctuations over large parts of the globe. The North Atlantic Ocean is the region that benefits the most from initialization, with the largest skill enhancement occurring over the subpolar region compared to historical simulations. On the other hand, the predictive skill over the Pacific Ocean rapidly decays with forecast time, especially over the North Pacific. In terms of precipitation, the skill of the CMCC DPS is significantly higher than that of the historical simulations over a few specific regions, including the Sahel, northern Eurasia, and over western and central Europe. The Atlantic multidecadal variability is also skillfully predicted, and this likely contributes to the skill found over remote areas through downstream influence, circulation changes, and teleconnections. Considering the relatively small ensemble size, a remarkable prediction skill is also found for the North Atlantic Oscillation, with maximum correlations obtained in the 1-9 lead year range. Systematic errors also affect the forecast quality of the CMCC DPS,featuring a prominent cold bias over the Northern Hemisphere, which is notfound in the historical runs, suggesting that, in some areas, the adoptedfull-field initialization strategy likely perturbs the equilibrium state ofthe model climate quite significantly. The encouraging results obtained in this study indicate that climatevariability over land can be predictable over a multiyear range, andthey demonstrate that the CMCC DPS is a valuable addition to the currentgeneration of DPSs. This stresses the need to further explore the potentialof the near-term predictions, further improving future decadal systems andinitialization methods, with the aim to provide a reliable tool to inform decision-makers on how regional climate will evolve in the next decade

Interactome-Seq: A Protocol for Domainome Library Construction, Validation and Selection by Phage Display and Next Generation Sequencing

Folding reporters are proteins with easily identifiable phenotypes, such as antibiotic resistance, whose folding and function is compromised when fused to poorly folding proteins or random open reading frames. We have developed a strategy where, by using TEM-1 \u3b2-lactamase (the enzyme conferring ampicillin resistance) on a genomic scale, we can select collections of correctly folded protein domains from the coding portion of the DNA of any intronless genome. The protein fragments obtained by this approach, the so called "domainome", will be well expressed and soluble, making them suitable for structural/functional studies. By cloning and displaying the "domainome" directly in a phage display system, we have showed that it is possible to select specific protein domains with the desired binding properties (e.g., to other proteins or to antibodies), thus providing essential experimental information for gene annotation or antigen identification. The identification of the most enriched clones in a selected polyclonal population can be achieved by using novel next-generation sequencing technologies (NGS). For these reasons, we introduce deep sequencing analysis of the library itself and the selection outputs to provide complete information on diversity, abundance and precise mapping of each of the selected fragment. The protocols presented here show the key steps for library construction, characterization, and validation

Global mean climate and main patterns of variability in the CMCC-CM2 coupled model

Euro‐Mediterranean Centre on Climate Change coupled climate model (CMCC‐CM2) represents the new family of the global coupled climate models developed and used at CMCC. It is based on the atmospheric, land and sea ice components from the Community Earth System Model coupled with the global ocean model Nucleus for European Modeling of the Ocean. This study documents the model components, the coupling strategy, particularly for the oceanic, atmospheric, and sea ice components, and the overall model ability in reproducing the observed mean climate and main patterns of interannual variability. As a first step toward a more comprehensive, process‐oriented, validation of the model, this work analyzes a 200‐year simulation performed under constant forcing corresponding to present‐day climate conditions. In terms of mean climate, the model is able to realistically reproduce the main patterns of temperature, precipitation, and winds. Specifically, we report improvements in the representation of the sea surface temperature with respect to the previous version of the model. In terms of mean atmospheric circulation features, we notice a realistic simulation of upper tropospheric winds and midtroposphere geopotential eddies. The oceanic heat transport and the Atlantic meridional overturning circulation satisfactorily compare with present‐day observations and estimates from global ocean reanalyses. The sea ice patterns and associated seasonal variations are realistically reproduced in both hemispheres, with a better skill in winter. Main weaknesses of the simulated climate are related with the precipitation patterns, specifically in the tropical regions with large dry biases over the Amazon basin. Similarly, the seasonal precipitation associated with the monsoons, mostly over Asia, is weaker than observed. The main patterns of interannual variability in terms of dominant empirical orthogonal functions are faithfully reproduced, mostly in the Northern Hemisphere winter. In the tropics the main teleconnection patterns associated with El Niño–Southern Oscillation and with the Indian Ocean Dipole are also in good agreement with observations.Published4A. Oceanografia e climaJCR Journa

The Helicobacter pylori CagY Protein Drives Gastric Th1 and Th17 Inflammation and B Cell Proliferation in Gastric MALT Lymphoma

Background: the neoplastic B cells of the Helicobacter pylori-related low-grade gastric mucosa-associated lymphoid tissue (MALT) lymphoma proliferate in response to H. pylori, however, the nature of the H. pylori antigen responsible for proliferation is still unknown. The purpose of the study was to dissect whether CagY might be the H. pylori antigen able to drive B cell proliferation. Methods: the B cells and the clonal progeny of T cells from the gastric mucosa of five patients with MALT lymphoma were compared with those of T cell clones obtained from five H. pylori-infected patients with chronic gastritis. The T cell clones were assessed for their specificity to H. pylori CagY, cytokine profile and helper function for B cell proliferation. Results: 22 of 158 CD4(+) (13.9%) gastric clones from MALT lymphoma and three of 179 CD4(+) (1.7%) clones from chronic gastritis recognized CagY. CagY predominantly drives Interferon-gamma (IFN-gamma) and Interleukin-17 (IL-17) secretion by gastric CD4(+) T cells from H. pylori-infected patients with low-grade gastric MALT lymphoma. All MALT lymphoma-derived clones dose dependently increased their B cell help, whereas clones from chronic gastritis lost helper activity at T-to-B-cell ratios greater than 1. Conclusion: the results obtained indicate that CagY drives both B cell proliferation and T cell activation in gastric MALT lymphomas

Selecting soluble/foldable protein domains through single-gene or genomic ORF filtering: structure of the head domain of Burkholderia pseudomallei antigen BPSL2063

The 1.8\u2005\uc5 resolution crystal structure of a conserved domain of the potential Burkholderia pseudomallei antigen and trimeric autotransporter BPSL2063 is presented as a structural vaccinology target for melioidosis vaccine development. Since BPSL2063 (1090 amino acids) hosts only one conserved domain, and the expression/purification of the full-length protein proved to be problematic, a domain-filtering library was generated using \u3b2-lactamase as a reporter gene to select further BPSL2063 domains. As a result, two domains (D1 and D2) were identified and produced in soluble form in Escherichia coli. Furthermore, as a general tool, a genomic open reading frame-filtering library from the B. pseudomallei genome was also constructed to facilitate the selection of domain boundaries from the entire ORFeome. Such an approach allowed the selection of three potential protein antigens that were also produced in soluble form. The results imply the further development of ORF-filtering methods as a tool in protein-based research to improve the selection and production of soluble proteins or domains for downstream applications such as X-ray crystallography

InteractomeSeq: a web server for the identification and profiling of domains and epitopes from phage display and next generation sequencing data

High-Throughput Sequencing technologies are transforming many research fields, including the analysis of phage display libraries. The phage display technology coupled with deep sequencing was introduced more than a decade ago and holds the potential to circumvent the traditional laborious picking and testing of individual phage rescued clones. However, from a bioinformatics point of view, the analysis of this kind of data was always performed by adapting tools designed for other purposes, thus not considering the noise background typical of the 'interactome sequencing' approach and the heterogeneity of the data. InteractomeSeq is a web server allowing data analysis of protein domains ('domainome') or epitopes ('epitome') from either Eukaryotic or Prokaryotic genomic phage libraries generated and selected by following an Interactome sequencing approach. InteractomeSeq allows users to upload raw sequencing data and to obtain an accurate characterization of domainome/epitome profiles after setting the parameters required to tune the analysis. The release of this tool is relevant for the scientific and clinical community, because InteractomeSeq will fill an existing gap in the field of large-scale biomarkers profiling, reverse vaccinology, and structural/functional studies, thus contributing essential information for gene annotation or antigen identification. InteractomeSeq is freely available at https://InteractomeSeq.ba.itb.cnr.it/

Identification of novel proteins binding the AU-rich element of \u3b1-prothymosin mRNA through the selection of open reading frames (RIDome)

We describe here a platform for high-throughput protein expression and interaction analysis aimed at identifying the RNA-interacting domainome. This approach combines the selection of a phage library displaying "filtered" open reading frames with next-generation DNA sequencing. The method was validated using an RNA bait corresponding to the AU-rich element of \u3b1-prothymosin, an RNA motif that promotes mRNA stability and translation through its interaction with the RNA-binding protein ELAVL1. With this strategy, we not only confirmed known RNA-binding proteins that specifically interact with the target RNA (such as ELAVL1/HuR and RBM38) but also identified proteins not previously known to be ARE-binding (R3HDM2 and RALY). We propose this technology as a novel approach for studying the RNA-binding proteome

Quantification of the Arctic Sea ice‐driven atmospheric circulation variability in coordinated large ensemble simulations

A coordinated set of large ensemble atmosphere‐only simulations is used to investigate the impacts of observed Arctic sea ice‐driven variability (SIDV) on the atmospheric circulation during 1979–2014. The experimental protocol permits separating Arctic SIDV from internal variability and variability driven by other forcings including sea surface temperature and greenhouse gases. The geographic pattern of SIDV is consistent across seven participating models, but its magnitude strongly depends on ensemble size. Based on 130 members, winter SIDV is ~0.18 hPa2 for Arctic‐averaged sea level pressure (~1.5% of the total variance), and ~0.35 K2 for surface air temperature (~21%) at interannual and longer timescales. The results suggest that more than 100 (40) members are needed to separate Arctic SIDV from other components for dynamical (thermodynamical) variables, and insufficient ensemble size always leads to overestimation of SIDV. Nevertheless, SIDV is 0.75–1.5 times as large as the variability driven by other forcings over northern Eurasia and Arctic