Search bioRxiv⌕ Search

bioRxiv · 10.1101/2024.02.15.577777

Trajectory analysis of hepatic stellate cell differentiation reveals metabolic regulation of cell commitment and fibrosis

Abstract

Defining the trajectory of cells during differentiation and disease offers the possibility to understand the mechanisms driving cell fate and identity. However, trajectories of human cells are largely unexplored. By investigating the proteome trajectory of iPSCs differentiation to hepatic stellate cells (dHSCs), we identified RORA as a key transcription factor governing the metabolic reprogramming of HSCs necessary for HSCs commitment, identity, and activation. Using RORA deficient iPSCs and pharmacologic interventions, we showed that RORA is required for mesoderm differentiation and prevents dHSCs activation by reducing the high energetic state of the cells. While RORA knockout mice had enhanced fibrosis, RORA agonists rescued multi- organ fibrosis in in vivo models. RORA expression was consistently found to be negatively correlated with liver fibrosis and HSCs activation markers in patients with liver disease. This study reveals that RORA regulates cell metabolic plasticity, crucial for mesoderm differentiation, pericyte quiescence, and fibrosis, influencing cell commitment and disease mechanisms. SummaryThis study describes the trajectory of induced pluripotent stem cells (iPSCs) differentiation to hepatic stellate cells (dHSCs). We identify RAR-related orphan receptor alpha (RORA) as a transcription factor essential for mesoderm commitment and dHSCs identity and fibrogenic activation by regulating metabolic plasticity.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Martinez Garcia de la Torre, R. A., Vallverdu, J., Xu, Z., Arino, S., Aguilar-Bravo, B., Ruiz Blazquez, P., Fernandez Fernandez, M., Navarro-Gascon, A., Blasco-Roset, A., Sanchez--Fernandez-de-Landa, P., Pera Garcia, J., Romero-Moya, D., Ayuso Garcia, P., Martinez Sanchez, C., Zanatto, L., Sererols, L., Cantallops Vila, P., Antoine, B., Azkargorta, M., Lozano, J. J., Martinez-Chantar, M. L., Giorgetti, A., Elortza, F., Planavila, A., Varela, M., Woodhoo, A., Zorzano, A., Graupera, I., Moles, A., Coll, M., Affo, S., Sancho-Bru, P.. 2024-02-17. Trajectory analysis of hepatic stellate cell differentiation reveals metabolic regulation of cell commitment and fibrosis. https://doi.org/10.1101/2024.02.15.577777

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Differential requirement for the Ire1 luminal domain in Candida albicans drug susceptibility and pathogenicity

The opportunistic human pathogen Candida albicans depends on the unfolded protein response (UPR) for cell wall integrity, antifungal tolerance, filamentous growth, and virulence. The UPR is driven by the conserved transmembrane sensor Ire1, which is activated either by misfolded proteins through its luminal domain or by lipid bilayer stress (LBS) through its transmembrane domain. In budding yeast, these two activation modes deploy divergent transcriptional programs. Whether the requirement for these two input domains is separable in C. albicans, where the cell membrane and cell wall are themselves the targets of major antifungal drug classes, remains unknown. Here, we engineered a C. albicans strain expressing Ire1 lacking an intact luminal domain (ire1{Delta}LD), which no longer detects proteotoxic stress. The ire1{Delta}LD strain grew in the presence of the azole antifungals fluconazole and miconazole but was highly sensitive to heat shock, cell wall stress, and the echinocandin caspofungin. It was also unable to sustain filamentous growth and showed reduced virulence in a Caenorhabditis elegans infection model. RNA sequencing revealed only modest changes to the steady-state transcriptome of ire1{Delta}LD cells. Together, these findings define a differential requirement for the input domains of C. albicans Ire1, uncoupling growth under azole-induced membrane stress from the cell wall, thermal, and virulence-associated outputs that depend on proteotoxic sensing, a distinction that could inform antifungal strategies targeting the UPR.

cell biology↗

Nucleosome Core Allostery Governs Chromatin Recognition and Cell Fate

Nucleosomes regulate chromatin folding, accessibility, and factor recruitment. Current models primarily attribute these functions to histone tail modifications, while the core is largely viewed as a structural scaffold. Yet subtle changes within the nucleosome core can produce profound functional consequences, and the mechanisms underlying these effects remain unclear. Here, we describe nucleosome core allostery as a fundamental principle of chromatin regulation that amplifies the impact of minimal nucleosome variations. Leveraging natural differences between H2A.Z variants, we show that the nucleosome core encodes distinct conformational dynamics that propagate allosterically, thereby controlling nucleosome accessibility and recognition by chromatin factors. As a result, a single buried amino acid substitution alone is sufficient to reprogram nucleosome dynamics and bias cell identity. Our findings establish the nucleosome core as an allosteric regulatory module and provide a generalizable framework for how subtle variation within nucleosomes is amplified into diverse biological outcomes in development and disease.

cell biology↗

A Novel Open-Source CellProfiler Pipeline for Automated, User-Friendly Hierarchical and K-Means Clustering of Microglial Morphology

Microglia represent a highly dynamic and heterogeneous cell type that is critically implicated in states of health and pathology. Microglial morphological subgroups have been identified that correspond to functional characteristics determining health-related outcomes. The identification of states based on morphological characteristics will therefore provide invaluable insights into the microglia-specific functional mechanisms driving treatment effects. The application of clustering analyses enables the detection of groupings within samples reflecting differences in morphological features. Here we propose the application of three custom-created modules to be used within the open-source software CellProfiler. These modules enable the automated detection of clusters present within the sample of microglia, as well as the assessment of the abundance of these clusters across conditions. The application of the analysis is conducted in a highly user-friendly manner, with a user interface integrated into the pipeline, enabling the performance of the analysis with only minimal user input. The workflow thereby includes the conduction of an outlier assessment, followed by hierarchical clustering and k-means clustering and the generation of interactive graphs to determine the number of microglia states present in the sample. Bar plots displaying the abundance of the microglia states across conditions included in the sample will be created. This approach will facilitate faster and more comparable detection of microglial morphological clusters across studies.

cell biology↗