58 research outputs found
The QSL platform at LORIA
Colloque sans acte Ă diffusion restreinte. internationale.International audienceThe QSL project aims at the development of concepts, methods, techniques, and tools to increase the reliability and the quality of software intensive systems. Within this project, we are anticipating a platform of tools for validation and verification that ensures their availability, includes documentation and case studies, and eventually intends to foster the cooperation of different teams using different tools on common development projects
Anatomy of the bacitracin resistance network in <i>Bacillus subtilis</i>
Protection against antimicrobial peptides (AMPs) often involves the parallel production of multiple, well-characterized resistance determinants. So far, little is known about how these resistance modules interact and how they jointly protect the cell. Here, we studied the interdependence between different layers of the envelope stress response of Bacillus subtilis when challenged with the lipid II cycle-inhibiting AMP bacitracin. The underlying regulatory network orchestrates the production of the ABC transporter BceAB, the UPP phosphatase BcrCand the phage-shock proteins LiaIH. Our systems-level analysis reveals a clear hierarchy,allowing us to discriminate between primary (BceAB) and secondary (BcrC and LiaIH) layers ofbacitracin resistance. Deleting the primary layer provokes an enhanced induction of the secondary layer to partially compensate for this loss. This study reveals a direct role of LiaI H inbacitracin resistance, provides novel insights into the feedback regulation of the Lia system, anddemonstrates a pivotal role of BcrC in maintaining cell wall homeostasis. The compensatory regulation within the bacitracin network can also explain how gene expression noise propagates between resistance layers. We suggest that this active redundancy in the bacitracin resistance network of B. subtilis is a general principle to be found in many bacterial antibiotic resistance networks
Anatomy of the bacitracin resistance network in <i>Bacillus subtilis</i>
Protection against antimicrobial peptides (AMPs) often involves the parallel production of multiple, well-characterized resistance determinants. So far, little is known about how these resistance modules interact and how they jointly protect the cell. Here, we studied the interdependence between different layers of the envelope stress response of Bacillus subtilis when challenged with the lipid II cycle-inhibiting AMP bacitracin. The underlying regulatory network orchestrates the production of the ABC transporter BceAB, the UPP phosphatase BcrCand the phage-shock proteins LiaIH. Our systems-level analysis reveals a clear hierarchy,allowing us to discriminate between primary (BceAB) and secondary (BcrC and LiaIH) layers ofbacitracin resistance. Deleting the primary layer provokes an enhanced induction of the secondary layer to partially compensate for this loss. This study reveals a direct role of LiaI H inbacitracin resistance, provides novel insights into the feedback regulation of the Lia system, anddemonstrates a pivotal role of BcrC in maintaining cell wall homeostasis. The compensatory regulation within the bacitracin network can also explain how gene expression noise propagates between resistance layers. We suggest that this active redundancy in the bacitracin resistance network of B. subtilis is a general principle to be found in many bacterial antibiotic resistance networks
The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry
Background: The NORMAN Association (https://www.norman-.network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-.network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for "suspect screening" lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide.Results: The NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community (https:// zenodo.org/communities/norman-.sle), with a total of > 40,000 unique views, > 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the US EPA's CompTox Chemicals Dashboard (https://comptox. epa.gov/dashboard/), enabling further access to these lists, along with the additional functionality and calculated properties these resources offer. PubChem has also integrated significant annotation content from the NORMAN-SLE, including a classification browser (https://pubchem.ncbi.nlm.nih.gov/classification/#hid=101).Conclusions: The NORMAN-SLE offers a specialized service for hosting suspect screening lists of relevance for the environmental community in an open, FAIR manner that allows integration with other major chemical resources. These efforts foster the exchange of information between scientists and regulators, supporting the paradigm shift to the "one substance, one assessment" approach. New submissions are welcome via the contacts provided on the NORMAN-SLE website (https://www.norman-.network.com/nds/SLE/)
The NORMAN Suspect List Exchange (NORMAN-SLE): Facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry
Background: The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for “suspect screening” lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide. Results: The NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community (https://zenodo.org/communities/norman-sle), with a total of > 40,000 unique views, > 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the US EPA’s CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard/), enabling further access to these lists, along with the additional functionality and calculated properties these resources offer. PubChem has also integrated significant annotation content from the NORMAN-SLE, including a classification browser (https://pubchem.ncbi.nlm.nih.gov/classification/#hid=101). Conclusions: The NORMAN-SLE offers a specialized service for hosting suspect screening lists of relevance for the environmental community in an open, FAIR manner that allows integration with other major chemical resources. These efforts foster the exchange of information between scientists and regulators, supporting the paradigm shift to the “one substance, one assessment” approach. New submissions are welcome via the contacts provided on the NORMAN-SLE website (https://www.norman-network.com/nds/SLE/)
The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry
The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for "suspect screening" lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide.The NORMAN-SLE project has received funding from the NORMAN Association via its joint proposal of activities. HMT and ELS are supported by the Luxembourg National Research Fund (FNR) for project A18/BM/12341006. ELS, PC, SEH, HPHA, ZW acknowledge funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101036756, project ZeroPM: Zero pollution of persistent, mobile substances. The work of EEB, TC, QL, BAS, PAT, and JZ was supported by the National Center for Biotechnology Information of the National Library of Medicine (NLM), National Institutes of Health (NIH). JOB is the recipient of an NHMRC Emerging Leadership Fellowship (EL1 2009209). KVT and JOB acknowledge the support of the Australian Research Council (DP190102476). The Queensland Alliance for Environmental Health Sciences, The University of Queensland, gratefully acknowledges the financial support of the Queensland Department of Health. NR is supported by a Miguel Servet contract (CP19/00060) from the Instituto de Salud Carlos III, co-financed by the European Union through Fondo Europeo de Desarrollo Regional (FEDER). MM and TR gratefully acknowledge financial support by the German Ministry for Education and Research (BMBF, Bonn) through the project “Persistente mobile organische Chemikalien in der aquatischen Umwelt (PROTECT)” (FKz: 02WRS1495 A/B/E). LiB acknowledges funding through a Research Foundation Flanders (FWO) fellowship (11G1821N). JAP and JMcL acknowledge financial support from the NIH for CCSCompendium (S50 CCSCOMPEND) via grants NIH NIGMS R01GM092218 and NIH NCI 1R03CA222452-01, as well as the Vanderbilt Chemical Biology Interface training program (5T32GM065086-16), plus use of resources of the Center for Innovative Technology (CIT) at Vanderbilt University. TJ was (partly) supported by the Dutch Research Council (NWO), project number 15747. UFZ (TS, MaK, WB) received funding from SOLUTIONS project (European Union’s Seventh Framework Programme for research, technological development and demonstration under Grant Agreement No. 603437). TS, MaK, WB, JPA, RCHV, JJV, JeM and MHL acknowledge HBM4EU (European Union’s Horizon 2020 research and innovation programme under the grant agreement no. 733032). TS acknowledges funding from NFDI4Chem—Chemistry Consortium in the NFDI (supported by the DFG under project number 441958208). TS, MaK, WB and EMLJ acknowledge NaToxAq (European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 722493). S36 and S63 (HPHA, SEH, MN, IS) were funded by the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) Project No. (FKZ) 3716 67 416 0, updates to S36 (HPHA, SEH, MN, IS) by the German Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV) Project No. (FKZ) 3719 65 408 0. MiK acknowledges financial support from the EU Cohesion Funds within the project Monitoring and assessment of water body status (No. 310011A366 Phase III). The work related to S60 and S82 was funded by the Swiss Federal Office for the Environment (FOEN), KK and JH acknowledge the input of Kathrin Fenner’s group (Eawag) in compiling transformation products from European pesticides registration dossiers. DSW and YDF were supported by the Canadian Institutes of Health Research and Genome Canada. The work related to S49, S48 and S77 was funded by the MAVA foundation; for S77 also the Valery Foundation (KG, JaM, BG). DML acknowledges National Science Foundation Grant RUI-1306074. YL acknowledges the National Natural Science Foundation of China (Grant No. 22193051 and 21906177), and the Chinese Postdoctoral Science Foundation (Grant No. 2019M650863). WLC acknowledges research project 108C002871 supported by the Environmental Protection Administration, Executive Yuan, R.O.C. Taiwan (Taiwan EPA). JG acknowledges funding from the Swiss Federal Office for the Environment. AJW was funded by the U.S. Environmental Protection Agency. LuB, AC and FH acknowledge the financial support of the Generalitat Valenciana (Research Group of Excellence, Prometeo 2019/040). KN (S89) acknowledges the PhD fellowship through Marie Skłodowska-Curie grant agreement No. 859891 (MSCA-ETN). Exposome-Explorer (S34) was funded by the European Commission projects EXPOsOMICS FP7-KBBE-2012 [308610]; NutriTech FP7-KBBE-2011-5 [289511]; Joint Programming Initiative FOODBALL 2014–17. CP acknowledges grant RYC2020-028901-I funded by MCIN/AEI/1.0.13039/501100011033 and “ESF investing in your future”, and August T Larsson Guest Researcher Programme from the Swedish University of Agricultural Sciences. The work of ML, MaSe, SG, TL and WS creating and filling the STOFF-IDENT database (S2) mostly sponsored by the German Federal Ministry of Education and Research within the RiSKWa program (funding codes 02WRS1273 and 02WRS1354). XT acknowledges The National Food Institute, Technical University of Denmark. MaSch acknowledges funding by the RECETOX research infrastructure (the Czech Ministry of Education, Youth and Sports, LM2018121), the CETOCOEN PLUS project (CZ.02.1.01/0.0/0.0/15_003/0000469), and the CETOCOEN EXCELLENCE Teaming 2 project supported by the Czech ministry of Education, Youth and Sports (No CZ.02.1.01/0.0/0.0/17_043/0009632).Peer reviewe
<em>Bacillus anthracis</em> Purinriboschalter: Funktionelle Charakterisierung und Etablierung eines Selektionsverfahren fĂĽr neue Liganden
Riboswitches are structured RNA elements regulating the expression of downstream genes dependent on ligand binding. This thesis focusses on guanine riboswitches from the pathogenic bacterium Bacillus anthracis to investigate their activity and ligand selectivity. In addition, an in vivo reverse reporter gene system to analyze OFF riboswitches is presented. This system was used to establish a screening method for novel OFF-riboswitch ligands.Riboschalter sind strukturierte RNA-Elemente, die die Expression von nachgeschalteten Genen abhängig von der Ligandenbindung regulieren. Diese Arbeit befasst sich mit Guaninriboschaltern aus dem pathogenen Bakterium Bacillus anthracis und untersucht ihre Aktivität und Ligandenselektivität. Zusätzlich wird ein reverses in vivo Reportergensystem zur Analyse von OFF-Riboschaltern präsentiert. Dieses System wurde verwendet, um ein Selektionsverfahren für neue Liganden von OFF-Riboschaltern zu etablieren
Setting of French indoor air quality guidelines for chronic exposure to benzene
International audienceIndoor air quality guidelines (IAQGs) provide safe levels of indoor pollutant concentrations below which adverse health effects are not expected to occur in the general population, including susceptible groups. The development of French IAQGs has been on-going since 2005 in the framework of the National Environment and Health Action Plan (NEHAP, 2004-2008). According to toxicological and epidemiological data, benzene inhalation leads to acute and chronic effects. For long-term exposure, haematological effects and leukaemia have been observed in the Pliofilm cohort. Benzene is classified as carcinogenic for humans and its genotoxic effects have been demonstrated. Considering non carcinogenic effects and available toxicological reference values for benzene, the IAQG of 10 micro g.m-3 is proposed to protect the general population for long-term exposure. To protect from carcinogenic effects, the proposed IAQGs are based on WHO's potency slope factor: 2 and 0.2 micro g.m-3 respectively associated with an excess lifetime risk of 10-5 and 10-6
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