KDM6B drives epigenetic reprogramming associated with lymphoid stromal cell early commitment and immune properties

Mature lymphoid stromal cells (LSCs) are key organizers of immune responses within secondary lymphoid organs. Similarly, inflammation-driven tertiary lymphoid structures depend on immunofibroblasts producing lymphoid cytokines and chemokines. Recent studies have explored the origin and heterogeneity of LSC/immunofibroblasts, yet the molecular and epigenetic mechanisms involved in their commitment are still unknown. This study explored the transcriptomic and epigenetic reprogramming underlying LSC/immunofibroblast commitment. We identified the induction of lysine demethylase 6B (KDM6B) as the primary epigenetic driver of early immunofibroblast differentiation. In addition, we observed an enrichment for KDM6B gene signature in murine inflammatory fibroblasts and pathogenic stroma of patients with autoimmune diseases. Last, KDM6B was required for the acquisition of LSC/immunofibroblast functional properties, including the up-regulation of CCL2 and the resulting recruitment of monocytes. Overall, our results reveal epigenetic mechanisms that participate in the early commitment and immune properties of immunofibroblasts and support the use of epigenetic modifiers as fibroblast-targeting strategies in chronic inflammation

Periosteal Skeletal Stem Cells Can Migrate into the Bone Marrow and Support Hematopoietic Regeneration

International audienc

Sub-Cutaneous Administration of Rituximab Triggers a Pro-Phagocytic Phenotype of Monocytic Compartment in LowTumor Burden Follicular Lymphoma Patients Included in the Flirt Clinical Trial, a Lysa Study

International audienc

Workflow4Metabolomics: an international computing infrastructure for Metabolomics

Thursday 4th July - Talks I & TrainingsProteomics & Metabolomics. Moderator: P. JagtapThe Workflow4Metabolomics (W4M) project aims to develop full LC/MS, GC/MS, FIA/MS and NMR pipelines using Galaxy framework for dataanalysis including preprocessing, normalization, quality control, statistical analysis and annotation steps. Our current developments aim to provide a set of interactive visualization tools in order to make ease the results interpretations. The development of Shiny applications will allows interactions from graphical features and dataset filters with graphical outputs like chromatograms, RMN spectra, heatmaps or PCA. In parallel, one of the major issue of the metabolomic approach is the compounds identification. To facilitate this annotation step, tandem mass spectrometry (MS/MS) is able to provide informations about the compounds structure. For that reason, an MS/MS data processing workflow based on msPurity, and two identification tools, metFrag and Sirius-CSI: FingerID, will be available in W4M

Technological developments and opportunities with Workflow4Metabolomics

Technological developments and opportunities with Workflow4Metabolomics. European RFMF Metabomeeting 202

Developments and opportunities with Workflow4Metabolomics

International audienceMetabolomics data analysis is a complex, multistep process, constantly evolving with the development of new analytical technologies, mathematical methods, bioinformatics tools and databases. Workflow4Metabolomics[1] is a collaborative portal dedicated to metabolomics data processing, analysis and annotation for the Metabolomics community. In the latest version of W4M, the core team proposes new upgrades for LC-MS, GC-MS and NMR pipelines, including new preprocessing steps, as well as enhancement of statistical analysis and annotation tools. W4M aims to promote open science in Metabolomics and facilitate knowledge dissemination by providing community resources

Update on technological developments and opportunities with Workflow4Metabolomics

International audienceIntroductionMetabolomics data analysis is a complex and multistep process, which is constantly evolving with the development of new analytical technologies, mathematical methods, bioinformatics tools and databases. The Workflow4Metabolomics (W4M) infrastructure[1] provides tools in a single online web interface (through Galaxy[1]). During the last two years, W4M has evolved with new upgrades for LC-MS, LC-MSMS, GC-MS and NMR pipelines, including preprocessing, quality control, statistical analysis and annotation tools. W4M also proposes new community resources promoting open science in metabolomics.Technological and methodological innovationW4M major updates include: Specific Galaxy interactive tools with NMRPro[2] for NMR spectra visualization and Xseeker for visualization and annotation of LC-MSMS data (In collaboration with CHOPIN ANR project[3]); An improved MSMS pipeline; New annotation tools suite allowing connexion with PeakForest[4], a new spectral data manager infrastructure for laboratories; New functionalities regarding mixed model computation for repeated measure designs, and improvements in annotation of complex mixture bidimensional NMR spectra. New training resources through the Galaxy Training Network (GTN) are also proposed, and Training Infrastructure as a Service (TIass) is available through the new usegalaxy.fr host.Results and impactW4M’s improvements increase raw data input management and LC/GC-MS(MS) workflow efficiency. We highlight how current advances, along with community training as through the yearly international school Workflow4Experimenters, contribute to open data analysis practices worldwide. In addition the W4M organization on Github repository aims to review code, annotate tools and propose a showcase for contributors from the metabolomics community.References[1] Giacomoni F., Le Corguillé et al (2015). Workflow4Metabolomics: A collaborative research infrastructure for computational metabolomics. Bioinformatics 2015, May 1;31(9):1493-5. doi: 10.1093/bioinformatics/btu813[2] Mohamed A, Nguyen CH, Mamitsuka H. NMRPro: an integrated web component for interactive processing and visualization of NMR spectra. Bioinformatics. 2016 Jul 1;32(13):2067-8. doi: 10.1093/bioinformatics/btw102. Epub 2016 Feb 26. PMID: 27153725.[3] https://anr.fr/ProjetIA-16-RHUS-0007[4] Paulhe, N., Canlet, C., Damont, A. et al. PeakForest: a multi-platform digital infrastructure for interoperable metabolite spectral data and metadata management. Metabolomics 18, 40 (2022). doi: 10.1007/s11306-022-01899-3[5] Afgan E. et al. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update. Nucleic Acids Res. 2016 Jul 8;44(W1):W3-W10. doi: 10.1093/nar/gkw34

Update on technological developments and opportunities with Workflow4Metabolomics

International audienceIntroductionMetabolomics data analysis is a complex and multistep process, which is constantly evolving with the development of new analytical technologies, mathematical methods, bioinformatics tools and databases. The Workflow4Metabolomics (W4M) infrastructure[1] provides tools in a single online web interface (through Galaxy[1]). During the last two years, W4M has evolved with new upgrades for LC-MS, LC-MSMS, GC-MS and NMR pipelines, including preprocessing, quality control, statistical analysis and annotation tools. W4M also proposes new community resources promoting open science in metabolomics.Technological and methodological innovationW4M major updates include: Specific Galaxy interactive tools with NMRPro[2] for NMR spectra visualization and Xseeker for visualization and annotation of LC-MSMS data (In collaboration with CHOPIN ANR project[3]); An improved MSMS pipeline; New annotation tools suite allowing connexion with PeakForest[4], a new spectral data manager infrastructure for laboratories; New functionalities regarding mixed model computation for repeated measure designs, and improvements in annotation of complex mixture bidimensional NMR spectra. New training resources through the Galaxy Training Network (GTN) are also proposed, and Training Infrastructure as a Service (TIass) is available through the new usegalaxy.fr host.Results and impactW4M’s improvements increase raw data input management and LC/GC-MS(MS) workflow efficiency. We highlight how current advances, along with community training as through the yearly international school Workflow4Experimenters, contribute to open data analysis practices worldwide. In addition the W4M organization on Github repository aims to review code, annotate tools and propose a showcase for contributors from the metabolomics community.References[1] Giacomoni F., Le Corguillé et al (2015). Workflow4Metabolomics: A collaborative research infrastructure for computational metabolomics. Bioinformatics 2015, May 1;31(9):1493-5. doi: 10.1093/bioinformatics/btu813[2] Mohamed A, Nguyen CH, Mamitsuka H. NMRPro: an integrated web component for interactive processing and visualization of NMR spectra. Bioinformatics. 2016 Jul 1;32(13):2067-8. doi: 10.1093/bioinformatics/btw102. Epub 2016 Feb 26. PMID: 27153725.[3] https://anr.fr/ProjetIA-16-RHUS-0007[4] Paulhe, N., Canlet, C., Damont, A. et al. PeakForest: a multi-platform digital infrastructure for interoperable metabolite spectral data and metadata management. Metabolomics 18, 40 (2022). doi: 10.1007/s11306-022-01899-3[5] Afgan E. et al. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update. Nucleic Acids Res. 2016 Jul 8;44(W1):W3-W10. doi: 10.1093/nar/gkw34