Control of mammalian cell differentiation by feedback and noise

Mary N. Teruel, Stanford University

10/3/2018

12:00pm - 1:00pm

Location: 106, Stanley Hall

Mammalian tissue size is maintained by slow replacement of damaged, de-differentiating, and dying cells. For adipocytes, key regulators of glucose and lipid metabolism, the renewal rate is only 10% per year1. Using computational modeling, quantitative mass spectrometry, and single-cell microscopy, we showed 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 so that differentiation rates can be kept very low and low signal variability 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 ultra-high feedback connectivity2,3,4.

We have since explored how the differentiation network functions in the physiological context where hormone inputs are known to oscillate. Intriguingly, we found that a circadian signaling code is critical for restricting the rate of fat cell differentiation. Dysregulation of the circadian pattern of glucocorticoid oscillations by irregular feeding and sleep cycles, by long-term hormone treatment, or during metabolic diseases, have all been shown to cause obesity. By using live, single-cell imaging of the key adipogenic transcription factors CEBPB and PPARG, endogenously tagged with fluorescent proteins, we show that pulsatile circadian hormone stimuli are rejected by the adipocyte differentiation control system, leading to very low adipocyte differentiation rates5. In striking contrast, equally strong persistent signals trigger maximal differentiation. We identify a network that combines fast and slow positive feedback loops as a unique regulatory motif that selectively suppresses differentiation for circadian pulse patterns. Furthermore, we confirm in mice that flattening of daily glucocorticoid oscillations significantly increases the mass of subcutaneous and visceral fat pads. Together, our study provides a molecular mechanism for why stress, Cushing's disease, and other conditions for which glucocorticoid secretion loses its pulsatility may lead to obesity.

References:
1. Spalding KL et al. Dynamics of fat cell turnover in humans. (2008). Nature 453, 783–787.
2. Ahrends R,…, & Teruel MN. (2014). Controlling low rates of cell differentiation through noise and ultrahigh feedback. Science 344, 1384–1389.
3. Park BO, Ahrends R. & Teruel MN. (2012). Consecutive positive feedback loops create a bistable switch that controls preadipocyte-to-adipocyte conversion. Cell Reports 2, 976–990.
4. Kovary KM,…., & Teruel MN. (2018). Expression variation impairs analog and enables binary signaling control. Mol Syst Biol. May 14;14(5):e7997.
5. Bahrami-Nejad Z*, Zhao ML*, ..., & Teruel MN. (2018). A transcriptional circuit filters oscillating circadian hormonal inputs to regulate fat cell differentiation. Cell Metabolism Apr 3, 27(4):854-868.e8. *equal contribution

  • Sponsor:

    Bioengineering (BioE)
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