Objectives Lipedema, a poorly understood chronic disease of adipose hyper-deposition, is often mistaken for obesity and causes significant impairment to mobility and quality-of-life. To identify molecular mechanisms underpinning lipedema, we employed comprehensive omics-based comparative analyses of whole tissue, adipocyte precursors (adipose-derived stem cells (ADSCs)), and adipocytes from patients with or without lipedema. Methods We compared whole-tissues, ADSCs, and adipocytes from body mass index–matched lipedema (n = 14) and unaffected (n = 10) patients using comprehensive global lipidomic and metabolomic analyses, transcriptional profiling, and functional assays. Results Transcriptional profiling revealed >4400 significant differences in lipedema tissue, with altered levels of mRNAs involved in critical signaling and cell function-regulating pathways (e.g., lipid metabolism and cell-cycle/proliferation). Functional assays showed accelerated ADSC proliferation and differentiation in lipedema. Profiling lipedema adipocytes revealed >900 changes in lipid composition and >600 differentially altered metabolites. Transcriptional profiling of lipedema ADSCs and non-lipedema ADSCs revealed significant differential expression of >3400 genes including some involved in extracellular matrix and cell-cycle/proliferation signaling pathways. One upregulated gene in lipedema ADSCs, Bub1, encodes a cell-cycle regulator, central to the kinetochore complex, which regulates several histone proteins involved in cell proliferation. Downstream signaling analysis of lipedema ADSCs demonstrated enhanced activation of histone H2A, a key cell proliferation driver and Bub1 target. Critically, hyperproliferation exhibited by lipedema ADSCs was inhibited by the small molecule Bub1 inhibitor 2OH-BNPP1 and by CRISPR/Cas9-mediated Bub1 gene depletion. Conclusion We found significant differences in gene expression, and lipid and metabolite profiles, in tissue, ADSCs, and adipocytes from lipedema patients compared to non-affected controls. Functional assays demonstrated that dysregulated Bub1 signaling drives increased proliferation of lipedema ADSCs, suggesting a potential mechanism for enhanced adipogenesis in lipedema. Importantly, our characterization of signaling networks driving lipedema identifies potential molecular targets, including Bub1, for novel lipedema therapeutics.
CloudStor SWAN (AARNet, 2022) is a research-focused web service for running analyses that is available to staff and students at many research institutes and Universities across Australia and New Zealand. In 2021, we used SWAN as a teaching tool in the master-level subject, Computational Genomics (COMP90016) at The University of Melbourne. This subject aims to teach students how to analyse large genomic datasets using best practices software tools, pipelines and student-written, custom code. Although CloudStor SWAN was not conceived as a teaching tool, we worked with their technical staff to tailor the service to our use case. This innovative use of existing research infrastructure allowed us to effectively transition the subject to remote learning. Students and staff could log in to the service using their existing University credentials, from anywhere in the world, without the use of a VPN. The ability to access the platform from a web browser allowed for a consistent computing environment for all students regardless of operating system, and without having to worry about software installations on local machines. This presented a significantly improved experience from the custom servers that had been used in the past. We used SWAN for weekly workshops during semester and for assessment in the form of assignments and an exam. It allowed us to format subject material in Jupyter notebooks where we could seamlessly integrate text, graphics and code. Additionally, assessed code questions can incorporate automatic marking and written submissions can be checked for plagiarism. SWAN also allowed us to introduce students to the UNIX command line, an important skillset that was not previously taught in the University of Melbourne Master of Science (Bioinformatics) program. From a student perspective, SWAN allowed for a practical skillset to be developed alongside theoretical knowledge from other aspects of the course. The platform was simple to learn and allowed students to focus on the subject content and the tasks asked of them, rather than on the interface. From a teacher’s perspective, having a unified platform allowed for a single set of clear instructions, improved troubleshooting and clearer management of tool versions and software dependencies. The use of Jupyter notebooks simplified lesson plans and assessments by integrating multiple elements into single documents. This element also made the lessons more easily sharable between colleagues and collaborators. Our integration of this technology into our tertiary teaching has served as a model for a similar use at a different Australian university. We hope to share the lessons learned from this subject, the advantages of using CloudStor SWAN in a teaching environment for both staff and students and provide some advice for others who may want to adapt it to fit their own teaching needs. Presentation link: https://youtu.be/8tutCO1hd9c References AARNet. (2022). CloudStor: Access, store, share and work with your data in one place. https://www.aarnet.edu.au/network-and-services/cloud-services/cloudstor
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