Controlling low rates of cell differentiation through noise and ultrahigh feedback

Abstract

Mammalian tissue size is maintained by slow replacement of de-differentiating and dying cells. For adipocytes, key regulators of glucose and lipid metabolism, the renewal rate is only 10% per year. We used computational modeling, quantitative mass spectrometry, and single-cell microscopy to show that cell-to-cell variability, or noise, in protein abundance acts within a network of more than six positive feedbacks to permit pre-adipocytes to differentiate at very low rates. This reconciles two fundamental opposing requirements: High cell-to-cell signal variability is needed to generate very low differentiation rates, whereas low signal variability is needed to prevent differentiated cells from de-differentiating. Higher eukaryotes can thus control low rates of near irreversible cell fate decisions through a balancing act between noise and ultrahigh feedback connectivity.

Adipose Tissue–Derived Stem Cells From Obese Subjects Contribute to Inflammation and Reduced Insulin Response in Adipocytes Through Differential Regulation of the Th1/Th17 Balance and Monocyte Activation

“…Such plasticity, associated with lifestyle changes in nutrition and physical activity in the population worldwide, has led to the current epidemics of obesity (28). Although differentiated adipocytes constitute the major part of the AT mass, precursor ASCs represent five cells for each differentiated adipocyte (29). Infiltrating immune cells are also present within AT and contribute to the inflammatory state observed in obesity (3).…”

Simultaneous Metabolite, Protein, Lipid Extraction (SIMPLEX): A Combinatorial Multimolecular Omics Approach for Systems Biology

“…Considering that probably only about 10% of all existing metabolites are known (51), here we utilized a targeted approach for me- tabolites involved into central metabolic functions such as amino acid, nucleotides, and nucleosides metabolism (Table S4). We were able to detect intracellular metabolites such as nucleosides, nucleotides and analogues (23), organic acids and derivatives (11), amino acids and derivatives (25), redox cofactors, and others (11), as well as carbohydrates and conjugates (5), thus providing access to metabolites at the systems level.…”

“…Taken together, this renders the present work as the most comprehensive study describing the effect of PPARG activation on a cellular system to date. In addition to already known PPARG downstream targets such as platelet glycoprotein 4 (CD36), fatty acid-binding protein (FABP4), solute carrier family 2, facilitated glucose transporter member 4 (GLUT4), and phosphatidate phosphatase LPIN1 (LIPIN1) (11,56), we identified several so far undescribed targets, including focal adhesion proteins alpha-actinin-1 (ACTN1), zyxin (ZYX), serine/threonine-protein phosphatase PP1-beta catalytic subunit (PPP1CB), myosin regulatory light polypeptide 9 (MYL9) and proteins involved in lipid synthesis (Table S6). Notably, the strongest regulations were observed for the following protein groups: (i) glycerolipid and glycerophospholipid metabolism, (ii) PPAR signaling, (iii) glycolysis/gluconeogeneses, (iv) pentosephosphate pathway, (v) insulin signaling, and (vi) focal adhesion.…”

“…Fat cell differentiation, known as adipogenesis, is controlled by a complex interconnected system with PPARG as the master regulator of this system. During adipogenesis, high initial levels of glucocorticoids, cAMP and PPARG ligand trigger differentiation, leading to an increased PPARG and CCAAT/ enhancer-binding protein alpha (CEBPA) protein expression level as well as to an elevated insulin sensitivity (11)(12)(13).…”

Computational analysis of signaling patterns in single cells

“…It is known that populations of hematopoetic stem cells and retinal progenitor cells show extensive intrinsic molecular heterogeneity [70]. Furthermore, there is increasing evidence that single cell dynamics are relevant to normal growth and development in vivo [71]. Live-cell time-lapse microscopy of single molecule dynamics in cells transitioning from multi-potency to lineage commitment could resolve the kinetics of molecular events involved in cell fate specification [72].…”