AsrR Is an Oxidative Stress Sensing Regulator Modulating Enterococcus faecium Opportunistic Traits, Antimicrobial Resistance, and Pathogenicity

Oxidative stress serves as an important host/environmental signal that triggers a wide range of responses in microorganisms. Here, we identified an oxidative stress sensor and response regulator in the important multidrug-resistant nosocomial pathogen Enterococcus faecium belonging to the MarR family and called AsrR (antibiotic and stress response regulator). The AsrR regulator used cysteine oxidation to sense the hydrogen peroxide which results in its dissociation to promoter DNA. Transcriptome analysis showed that the AsrR regulon was composed of 181 genes, including representing functionally diverse groups involved in pathogenesis, antibiotic and antimicrobial peptide resistance, oxidative stress, and adaptive responses. Consistent with the upregulated expression of the pbp5 gene, encoding a low-affinity penicillin-binding protein, the asrR null mutant was found to be more resistant to \u3b2-lactam antibiotics. Deletion of asrR markedly decreased the bactericidal activity of ampicillin and vancomycin, which are both commonly used to treat infections due to enterococci, and also led to over-expression of two major adhesins, acm and ecbA, which resulted in enhanced in vitro adhesion to human intestinal cells. Additional pathogenic traits were also reinforced in the asrR null mutant including greater capacity than the parental strain to form biofilm in vitro and greater persistance in Galleria mellonella colonization and mouse systemic infection models. Despite overexpression of oxidative stress-response genes, deletion of asrR was associated with a decreased oxidative stress resistance in vitro, which correlated with a reduced resistance to phagocytic killing by murine macrophages. Interestingly, both strains showed similar amounts of intracellular reactive oxygen species. Finally, we observed a mutator phenotype and enhanced DNA transfer frequencies in the asrR deleted strain. These data indicate that AsrR plays a major role in antimicrobial resistance and adaptation for survival within the host, thereby contributes importantly to the opportunistic traits of E. faecium

Galaxy Training: A powerful framework for teaching!

There is an ongoing explosion of scientific datasets being generated, brought on by recent technological advances in many areas of the natural sciences. As a result, the life sciences have become increasingly computational in nature, and bioinformatics has taken on a central role in research studies. However, basic computational skills, data analysis, and stewardship are still rarely taught in life science educational programs, resulting in a skills gap in many of the researchers tasked with analysing these big datasets. In order to address this skills gap and empower researchers to perform their own data analyses, the Galaxy Training Network (GTN) has previously developed the Galaxy Training Platform (https://training.galaxyproject.org), an open access, community-driven framework for the collection of FAIR (Findable, Accessible, Interoperable, Reusable) training materials for data analysis utilizing the user-friendly Galaxy framework as its primary data analysis platform. Since its inception, this training platform has thrived, with the number of tutorials and contributors growing rapidly, and the range of topics extending beyond life sciences to include topics such as climatology, cheminformatics, and machine learning. While initially aimed at supporting researchers directly, the GTN framework has proven to be an invaluable resource for educators as well. We have focused our efforts in recent years on adding increased support for this growing community of instructors. New features have been added to facilitate the use of the materials in a classroom setting, simplifying the contribution flow for new materials, and have added a set of train-the-trainer lessons. Here, we present the latest developments in the GTN project, aimed at facilitating the use of the Galaxy Training materials by educators, and its usage in different learning environments

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

Transition et adaptation, analyse des modalités du changement de pratiques des acteurs de la pêche professionnelle: Programme TRANSIPECHE : Scénarios de transition écologique et sociale des pêches françaises

Les crises simultanées et successives (changement climatique, érosion de la biodiversité, Brexit, COVID, prix du gasoil…) imposent une transformation profonde et urgente du secteur de la pêche qui doit être accompagné vers la performance écologique et sociale. Un groupement de recherche s’est constitué à cette fin, sous la responsabilité scientifique et technique de plusieurs instituts de recherche (L’Institut Agro, AgroParisTech, EHESS-CNRS, Université Paris 2 Panthéon ASSAS) et en interaction avec des acteurs de la société civile (Atelier des jours à venir, association Bloom, Shift Project). Le groupement de recherche entend aborder la question des transitions de manière globale et interdisciplinaire, en intégrant autant les paramètres écologiques que ceux humains, notamment dans leurs dimensions sociales, culturelles, économiques. Les principaux objectifs du groupement sont de : • mieux connaitre les impacts des principales pêcheries ; • comprendre les leviers et les obstacles aux transitions dans le secteur de la pêche ; • proposer des schémas de transitions pour les plus impactantes d’entre elles en imaginant des formes opérationnelles d’accompagnement. Les activités de recherche du groupement sont organisées par axes thématiques. En partenariat avec AgroParisTech, le Pôle halieutique, mer et littoral de l’Institut Agro est plus spécifiquement en charge du programme « TRANSPECHE : Scénarios de transition écologique et sociale des pêches françaises », financé par la Fondation 2050. Ce programme vise à partager un constat, à identifier des scénarios, et à proposer une feuille de route concrète pour la transition des pêches impactantes vers une réduction drastique des émissions de CO2, vers des pratiques de pêche « écosystémiques » compatibles avec la préservation de la biodiversité marine et avec le maintien d’une pêche au service des sociétés humaines et des territoires côtiers. Le programme TRANSPECHE s’appuie, d’une part, sur un diagnostic quantitatif des performances écologiques, écologiques et sociales des flottilles françaises (Quemper et al., 2024), et d’autre part, sur un travail d’enquête mené auprès de pêcheurs engagés dans la transition avec l’objectif d’analyser les changements de pratiques des acteurs de la pêche professionnelle, leurs motivations, leurs modalités, mais aussi les freins et les leviers associés. C’est ce volet qui fait l’objet du présent rapport

Transition et adaptation, analyse des modalités du changement de pratiques des acteurs de la pêche professionnelle: Programme TRANSIPECHE : Scénarios de transition écologique et sociale des pêches françaises

Les crises simultanées et successives (changement climatique, érosion de la biodiversité, Brexit, COVID, prix du gasoil…) imposent une transformation profonde et urgente du secteur de la pêche qui doit être accompagné vers la performance écologique et sociale. Un groupement de recherche s’est constitué à cette fin, sous la responsabilité scientifique et technique de plusieurs instituts de recherche (L’Institut Agro, AgroParisTech, EHESS-CNRS, Université Paris 2 Panthéon ASSAS) et en interaction avec des acteurs de la société civile (Atelier des jours à venir, association Bloom, Shift Project). Le groupement de recherche entend aborder la question des transitions de manière globale et interdisciplinaire, en intégrant autant les paramètres écologiques que ceux humains, notamment dans leurs dimensions sociales, culturelles, économiques. Les principaux objectifs du groupement sont de : • mieux connaitre les impacts des principales pêcheries ; • comprendre les leviers et les obstacles aux transitions dans le secteur de la pêche ; • proposer des schémas de transitions pour les plus impactantes d’entre elles en imaginant des formes opérationnelles d’accompagnement. Les activités de recherche du groupement sont organisées par axes thématiques. En partenariat avec AgroParisTech, le Pôle halieutique, mer et littoral de l’Institut Agro est plus spécifiquement en charge du programme « TRANSPECHE : Scénarios de transition écologique et sociale des pêches françaises », financé par la Fondation 2050. Ce programme vise à partager un constat, à identifier des scénarios, et à proposer une feuille de route concrète pour la transition des pêches impactantes vers une réduction drastique des émissions de CO2, vers des pratiques de pêche « écosystémiques » compatibles avec la préservation de la biodiversité marine et avec le maintien d’une pêche au service des sociétés humaines et des territoires côtiers. Le programme TRANSPECHE s’appuie, d’une part, sur un diagnostic quantitatif des performances écologiques, écologiques et sociales des flottilles françaises (Quemper et al., 2024), et d’autre part, sur un travail d’enquête mené auprès de pêcheurs engagés dans la transition avec l’objectif d’analyser les changements de pratiques des acteurs de la pêche professionnelle, leurs motivations, leurs modalités, mais aussi les freins et les leviers associés. C’est ce volet qui fait l’objet du présent rapport

Transition and adaptation: An analysis of how professional fishermen change their practices

International audienceThe succession of crises in the French professional fishing sector raises the question of the sector's capacity to adapt to changes in its global environment, and of the possibilities for fishermen to change their practices. Through interviews with fishermen and representatives, 5 ideal types of individual transitions were described, as well as two examples of changes in the fisheries management system. Some changes can be characterised as adaptations following a shock, rather than real voluntary and planned transitions. Voluntary individual transitions do exist, however, initiated by a variable trigger factor, but they require a high degree of introspection about personal and professional expectations. These examples of transitions are made possible by the rare synchronisation of external events and various characteristics of the project owners and remain overall a niche phenomenon in the current situation. There is little scope for transition in the sector, mainly because of the difficulty of accessing production rights and the rigidity of management systems. To help the sector evolve and adapt to a changing macro-environment (organisational, environmental, societal, energy, etc.), transition levers can be mobilised at organisational, political, financial, technical, social and societal levels. The age structure of ships and people will probably be the mainstay of a major reconfiguration of the sector in the short term

Narrowing Uncertainties of Climate Projections using Data-driven Methods: the AMOC Case Study

International audienc

Narrowing Uncertainties of Climate Projections using Data-driven Methods: the AMOC Case Study

International audienc

Selecting and weighting dynamical models using data-driven approaches

In geosciences, multi-model ensembles are helpful to explore the robustness of a range of results. To obtain a synthetic and improved representation of the studied dynamic system, the models are usually weighted. The simplest method, namely the model democracy, gives equal weights to all models, while more advanced approaches base weights on agreement with available observations. Here, we focus on determining weights for various versions of an idealized model of Atlantic Meridional Overturning Circulation. This is done by assessing their performance against synthetic observations (generated from one of the model versions) within a data assimilation framework using EnKF. In contrast to traditional data assimilation, we implement data-driven forecasts using the analog method based on catalogs of short-term trajectories. This approach allows us to efficiently emulate the model's dynamics while keeping computational costs low. For each model version, we compute a local performance metric, known as the contextual model evidence, to compare observations and model forecasts. This metric, based on the innovation likelihood, is sensitive to differences in model dynamics and considers forecast and observation uncertainties. Finally, the weights are calculated using both model performance and model codependency, and then evaluated on climatologies of long-term simulations. Results show good performance in identifying numerical simulations that best replicate observed short-term variations. Additionally, it outperforms benchmark approaches such as model democracy or climatologies-based strategies when reconstructing missing distributions. These findings encourage the application of the proposed methodology to more complex datasets in the future, like climate simulations

Narrowing Uncertainties of Climate Projections using Data-driven Methods: the AMOC Case Study

International audienc