Nutrient-sensing plays a crucial role in maintaining cellular energy and metabolic homeostasis. Perturbations in sensing pathways are associated with a wide variety of pathologies, especially metabolic diseases. Very little is understood about sensing fluctuations in nutrients and how this information is integrated into physiological and metabolic adaptation that could further affect cell-fate decisions during differentiation in Dictyostelium discoideum (henceafter, Dictyostelium). Glucose is the primary metabolic fuel among all nutrients. Carbohydrates, lipids and proteins ultimately breakdown into glucose, which is further used for providing energy. The maintenance of optimum glucose levels is important for efficient cell-survival. Glucose is not only a nutrient, but also a signaling molecule influencing cell growth and differentiation in Dictyostelium. Modulation of endogenous glucose levels either by varying exogenous glucose levels or genetic overexpression or deletion of genes involved in glucose signaling lead to changes in endogenous metabolite levels such as ADP/ATP ratio, NAD /NADH ratio, cAMP and ROS levels which further influence cell-fate decisions. Here, we show that AMPKα and Sir2D are components of glucose-signaling pathway in Dictyostelium which adjust cell metabolism interdependently in response to nutrient-status and promote cell-fate decisions.
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http://dx.doi.org/10.1002/cbf.3892 | DOI Listing |
Biotechnol Bioeng
January 2025
Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
Human pluripotent stem cells (hPSCs) can be differentiated in vitro to an increasing number of mature cell types, presenting significant promise for addressing a wide range of diseases and studying human development. One approach to further enhance stem cell differentiation methods would be to coordinate multiple inducible gene or protein switches to operate simultaneously within the same cell, with minimal cross-interference, to precisely regulate a network of lineage-specifying transcription factors (TFs) to guide cell fate decisions. Therefore, in this study, we designed and tested various mammalian gene and protein switches responsive to clinically safe small-molecule inhibitors of viral proteases.
View Article and Find Full Text PDFEpigenetics Chromatin
January 2025
Univ Lyon, Université Lyon 1, INSERM, Stem Cell and Brain Research Institute U1208, INRAE USC 1361, Bron, F-69500, France.
Post-translational modifications of histone H3 on lysine 9, specifically acetylation (H3K9ac) and tri-methylation (H3K9me3), play a critical role in regulating chromatin accessibility. However, the role of these modifications in lineage segregation in the mammalian blastocyst remains poorly understood. We demonstrate that di- and tri-methylation marks, H3K9me2 and H3K9me3, decrease during cavitation and expansion of the rabbit blastocyst.
View Article and Find Full Text PDFReprod Sci
January 2025
Service de Médecine Et Biologie de La Reproduction, Hôpital Mère Et Enfant, CHU de Nantes, 38 Boulevard Jean Monnet, Nantes, France.
Vitrification has revolutionized embryo cryopreservation, but represents a significant workload in the IVF lab. We evaluated here an ultrafast blastocyst warming procedure in order to improve workflow while maintaining clinical outcome. We first evaluated the expression of main markers of lineage specification in a subset of blastocysts donated to research warmed with ultrafast protocol.
View Article and Find Full Text PDFMethods Mol Biol
January 2025
Life Science Institute, University of Michigan, Ann Arbor, MI, USA.
Cell lineage analysis is primarily undertaken to understand cell fate specification and diversification along a cell lineage tree. Built with dual repressible markers, twin-spot mosaic analysis with repressible cell markers (MARCM) labels the two daughter cells made by a common precursor in distinct colors. The power of twin-spot MARCM to systematically subdivide complex lineages is exemplified in studies of Drosophila neural stem-cell lineages.
View Article and Find Full Text PDFMethods Mol Biol
January 2025
Ecole Polytechnique Fédérale de Lausanne, School of Life Sciences, Institute of Bioengineering, Lausanne, Switzerland.
Gene expression memory-based lineage inference (GEMLI) is a computational tool allowing to predict cell lineages solely from single-cell RNA-sequencing (scRNA-seq) datasets and is publicly available as an R package on GitHub. GEMLI is based on the occurrence of gene expression memory, i.e.
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