176 research outputs found
Exploiting the Gal4/UAS System as Plant Orthogonal Molecular Toolbox to Control Reporter Expression in Arabidopsis Protoplasts
The ability of protein domains to fold independently from the rest of the polypeptide is the principle governing the generation of fusion proteins with customized functions. A clear example is the split transcription factor system based on the yeast GAL4 protein and its cognate UAS enhancer. The rare occurrence of the UAS element in the transcriptionally sensitive regions of the Arabidopsis genome makes this transcription factor an ideal orthogonal platform to control reporter induction. Moreover, heterodimeric transcriptional complexes can be generated by exploiting posttranslational modifications hampering or promoting the interaction between GAL4-fused transcriptional partners, whenever this leads to the reconstitution of a fully functional GAL4 factor. The assembly of multiple engineered proteins into a synthetic transcriptional complex requires preliminary testing, before its components can be stably introduced into the plant genome. Mesophyll protoplast transformation represents a fast and reliable technique to test and optimize synthetic regulatory modules. Remarkable properties are the possibility to transform different combinations of plasmids (co-transformation) and the physiological resemblance of these isolated cells with the original tissue. Here we describe an extensive protocol to produce and exploit Arabidopsis mesophyll protoplasts to investigate the transcriptional output of GAL4/UAS-based complexes that are sensitive to posttranslational protein modifications
Multi-time-scale hydroclimate dynamics of a regional watershed and links to large-scale atmospheric circulation:Application to the Seine river catchment, France
(IF 3.73; Q1)International audienceIn the present context of global changes, considerable efforts have been deployed by the hydrological scientific community to improve our understanding of the impacts of climate fluctuations on water resources. Both observational and modeling studies have been extensively employed to characterize hydrological changes and trends, assess the impact of climate variability or provide future scenarios of water resources. In the aim of a better understanding of hydrological changes, it is of crucial importance to determine how and to what extent trends and long-term oscillations detectable in hydrological variables are linked to global climate oscillations.In this work, we develop an approach associating correlation between large and local scales, empirical statistical downscaling and wavelet multiresolution decomposition of monthly precipitation and streamflow over the Seine river watershed, and the North Atlantic sea level pressure (SLP) in order to gain additional insights on the atmospheric patterns associated with the regional hydrology. We hypothesized that: (i) atmospheric patterns may change according to the different temporal wavelengths defining the variability of the signals; and (ii) definition of those hydrological/circulation relationships for each temporal wavelength may improve the determination of large-scale predictors of local variations.The results showed that the links between large and local scales were not necessarily constant according to time-scale (i.e. for the different frequencies characterizing the signals), resulting in changing spatial patterns across scales. This was then taken into account by developing an empirical statistical downscaling (ESD) modeling approach, which integrated discrete wavelet multiresolution analysis for reconstructing monthly regional hydrometeorological processes (predictand: precipitation and streamflow on the Seine river catchment) based on a large-scale predictor (SLP over the Euro-Atlantic sector). This approach basically consisted in three steps: 1 – decomposing large-scale climate and hydrological signals (SLP field, precipitation or streamflow) using discrete wavelet multiresolution analysis, 2 – generating a statistical downscaling model per time-scale, 3 – summing up all scale-dependent models in order to obtain a final reconstruction of the predictand. The results obtained revealed a significant improvement of the reconstructions for both precipitation and streamflow when using the multiresolution ESD model instead of basic ESD. In particular, the multiresolution ESD model handled very well the significant changes in variance through time observed in either precipitation or streamflow. For instance, the post-1980 period, which had been characterized by particularly high amplitudes in interannual-to-interdecadal variability associated with alternating flood and extremely low-flow/drought periods (e.g., winter/spring 2001, summer 2003), could not be reconstructed without integrating wavelet multiresolution analysis into the model. In accordance with previous studies, the wavelet components detected in SLP, precipitation and streamflow on interannual to interdecadal time-scales could be interpreted in terms of influence of the Gulf-Stream oceanic front on atmospheric circulation
Identification of novel plant cysteine oxidase inhibitors from a yeast chemical genetic screen
Hypoxic responses in plants involve Plant Cysteine Oxidases (PCOs). They catalyze the N-terminal cysteine oxidation of Ethylene Response Factors VII (ERF-VII) in an oxygen-dependent manner, leading to their degradation via the cysteine N-degron pathway (Cys-NDP) in normoxia. In hypoxia, PCO activity drops, leading to the stabilization of ERF-VIIs and subsequent hypoxic gene upregulation. Thus far, no chemicals have been described to specifically inhibit PCO enzymes. In this work, we devised an in vivo pipeline to discover Cys-NDP effector molecules. Budding yeast expressing AtPCO4 and plant-based ERF-VII reporters was deployed to screen a library of natural-like chemical scaffolds and was further combined with an Arabidopsis Cys-NDP reporter line. This strategy allowed us to identify three PCO inhibitors, two of which were shown to affect PCO activity in vitro. Application of these molecules to Arabidopsis seedlings led to an increase in ERF-VII stability, induction of anaerobic gene expression, and improvement of tolerance to anoxia. By combining a high-throughput heterologous platform and the plant model Arabidopsis, our synthetic pipeline provides a versatile system to study how the Cys-NDP is modulated. Its first application here led to the discovery of at least two hypoxia-mimicking molecules with the potential to impact plant tolerance to low oxygen stress
Dim artificial light at night alters gene expression rhythms and growth in a key seagrass species (Posidonia oceanica)
Artificial light at night (ALAN) is a globally spreading anthropogenic stressor, affecting more than 20% of coastal habitats. The alteration of the natural light/darkness cycle is expected to impact the physiology of organisms by acting on the complex circuits termed as circadian rhythms. Our understanding of the impact of ALAN on marine organisms is lagging behind that of terrestrial ones, and effects on marine primary producers are almost unexplored. Here, we investigated the molecular and physiological response of the Mediterranean seagrass, Posidonia oceanica (L.) Delile, as model to evaluate the effect of ALAN on seagrass populations established in shallow waters, by taking advantage of a decreasing gradient of dim nocturnal light intensity (from P. oceanica, including that of shorter blue wavelengths, through the ELF3–LUX1–ZTL regulatory network, and suggested that the daily perturbation of internal clock orthologs in seagrass might have caused the recruitment of PoSEND33 and PoPSBS genes to mitigate the repercussions of a nocturnal stress on photosynthesis during the day. A long-lasting impairment of gene fluctuations in sites characterised by ALAN could explain the reduced growth of the seagrass leaves when these were transferred into controlled conditions and without lighting during the night. Our results highlight the potential contribution of ALAN to the global loss of seagrass meadows, posing questions about key interactions with a variety of other human-related stressors in urban areas, in order to develop more efficient strategies to globally preserve these coastal foundation species
Novel uterine sarcoma preoperative diagnosis score predicts the need for surgery in patients presenting with a uterine mass
Hydrological droughts in the 21st century, hotspots and uncertainties from a global multimodel ensemble experiment
Increasing concentrations of greenhouse gases in the atmosphere are expected to modify the global water cycle with significant consequences for terrestrial hydrology. We assess the impact of climate change on hydrological droughts in a multimodel experiment including seven global impact models (GIMs) driven by biascorrected climate from five global climate models under four representative concentration pathways (RCPs). Drought severity is defined as the fraction of land under drought conditions. Results show a likely increase in the global severity of hydrological drought at the end of the 21st century, with systematically greater increases for RCPs describing stronger radiative forcings. Under RCP8.5, droughts exceeding 40% of analyzed land area are projected by nearly half of the simulations. This increase in drought severity has a strong signal-to-noise ratio at the global scale, and Southern Europe, the Middle East, the Southeast United States, Chile, and South West Australia are identified as possible hotspots for future water security issues. The uncertainty due to GIMs is greater than that from global climate models, particularly if including a GIM that accounts for the dynamic response of plants to CO2 and climate, as this model simulates little or no increase in drought frequency. Our study demonstrates that different representations of terrestrial water-cycle processes in GIMs are responsible for a much larger uncertainty in the response of hydrological drought to climate change than previously thought. When assessing the impact of climate change on hydrology, it is therefore critical to consider a diverse range of GIMs to better capture the uncertainty
Dim artificial light at night alters gene expression rhythms and growth in a key seagrass species (Posidonia oceanica)
Artificial light at night (ALAN) is a globally spreading anthropogenic stressor, affecting more than 20% of coastal habitats. The alteration of the natural light/darkness cycle is expected to impact the physiology of organisms by acting on the complex circuits termed as circadian rhythms. Our understanding of the impact of ALAN on marine organisms is lagging behind that of terrestrial ones, and effects on marine primary producers are almost unexplored. Here, we investigated the molecular and physiological response of the Mediterranean seagrass, Posidonia oceanica (L.) Delile, as model to evaluate the effect of ALAN on seagrass populations established in shallow waters, by taking advantage of a decreasing gradient of dim nocturnal light intensity (fro
Utility of bronchoalveolar lavage for COVID-19: a perspective from the Dragon consortium
Diagnosing COVID-19 and treating its complications remains a challenge. This review reflects the perspective of some of the Dragon (IMI 2-call 21, #101005122) research consortium collaborators on the utility of bronchoalveolar lavage (BAL) in COVID-19. BAL has been proposed as a potentially useful diagnostic tool to increase COVID-19 diagnosis sensitivity. In both critically ill and non-critically ill COVID-19 patients, BAL has a relevant role in detecting other infections or supporting alternative diagnoses and can change management decisions in up to two-thirds of patients. BAL is used to guide steroid and immunosuppressive treatment and to narrow or discontinue antibiotic treatment, reducing the use of unnecessary broad antibiotics. Moreover, cellular analysis and novel multi-omics techniques on BAL are of critical importance for understanding the microenvironment and interaction between epithelial cells and immunity, revealing novel potential prognostic and therapeutic targets. The BAL technique has been described as safe for both patients and healthcare workers in more than a thousand procedures reported to date in the literature. Based on these preliminary studies, we recognize that BAL is a feasible procedure in COVID-19 known or suspected cases, useful to properly guide patient management, and has great potential for research
Six-transmembrane epithelial antigen of the prostate and enhancer of zeste homolog 2 as immunotherapeutic targets for lung cancer
<p>Abstract</p> <p>Background</p> <p>T-cell based immunotherapy for lung cancer (LC) could be a promising and novel therapeutic approach. Six-transmembrane epithelial antigen of the prostate (STEAP) and the polycomb group protein enhancer of zeste homolog 2 (EZH2) are highly expressed in LC and since the expression of molecules in normal tissue is significantly lower as compared to tumor cells, these proteins are considered as potential tumor-associated antigens (TAAs) for developing T-cell based immunotherapy.</p> <p>Methods</p> <p>We assessed the capacity of predicted CD4 T-cell epitopes from STEAP and EZH2 to induce anti-tumor immune responses to LC cell lines.</p> <p>Results</p> <p>Out of several predicted epitopes, two synthetic peptides, STEAP<sub>281-296 </sub>and EZH2<sub>95-109</sub>, were effective in inducing CD4 T-cell responses that were restricted by HLA-DR1, DR15, or DR53 molecules, indicating that the peptides function as promiscuous T-cell epitopes. Moreover, STEAP<sub>281-296 </sub>and EZH2<sub>95-109</sub>-reactive T-cells could directly recognize STEAP or EZH2 expressing LC cells in an HLA-DR restricted manner. In addition, some STEAP-reactive T-cells responded to STEAP+ tumor cell lysates presented by autologous dendric cells. Most significantly, both of these peptides were capable of stimulating <it>in vitro </it>T-cell responses in patients with LC.</p> <p>Conclusions</p> <p>Peptides STEAP<sub>281-296 </sub>and EZH2<sub>95-109 </sub>function as strong CD4 T-cell epitopes that can elicit effective anti-tumor T-cell responses against STEAP or EZH2 expressing LC. These observations may facilitate the translation of T-cell based immunotherapy into the clinic for the treatment of LC.</p
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