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Accurate Encoding and Decoding by Single Cells: Amplitude Versus Frequency Modulation

Author

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  • Gabriele Micali
  • Gerardo Aquino
  • David M Richards
  • Robert G Endres

Abstract

Cells sense external concentrations and, via biochemical signaling, respond by regulating the expression of target proteins. Both in signaling networks and gene regulation there are two main mechanisms by which the concentration can be encoded internally: amplitude modulation (AM), where the absolute concentration of an internal signaling molecule encodes the stimulus, and frequency modulation (FM), where the period between successive bursts represents the stimulus. Although both mechanisms have been observed in biological systems, the question of when it is beneficial for cells to use either AM or FM is largely unanswered. Here, we first consider a simple model for a single receptor (or ion channel), which can either signal continuously whenever a ligand is bound, or produce a burst in signaling molecule upon receptor binding. We find that bursty signaling is more accurate than continuous signaling only for sufficiently fast dynamics. This suggests that modulation based on bursts may be more common in signaling networks than in gene regulation. We then extend our model to multiple receptors, where continuous and bursty signaling are equivalent to AM and FM respectively, finding that AM is always more accurate. This implies that the reason some cells use FM is related to factors other than accuracy, such as the ability to coordinate expression of multiple genes or to implement threshold crossing mechanisms.Author Summary: Signals, and hence information, can generally be transmitted either by amplitude (AM) or frequency (FM) modulation, as used, for example, in the transmission of radio waves since the 1930s. Both types of modulation are known to play a role in biology with AM conventionally associated with signaling and gene expression, and FM used to reliably transmit electrical signals over large distances between neurons. Surprisingly, FM was recently also observed in gene regulation, making their roles less distinct than previously thought. Although the engineering advantages and disadvantages of AM and FM are well understood, the equivalent question in biological systems is still largely unsolved. Here, we propose a simple model of signaling by receptors (or ion channels) with subsequent gene regulation, thus implementing both AM and FM in different types of biological pathways. We then compare the accuracy in the production of target proteins. We find that FM can be more accurate than AM only for a single receptor with fast signaling, whereas AM is more accurate in slow gene regulation and with signaling by multiple receptors. Finally, we propose possible reasons that cells use FM despite the potential decrease in accuracy.

Suggested Citation

  • Gabriele Micali & Gerardo Aquino & David M Richards & Robert G Endres, 2015. "Accurate Encoding and Decoding by Single Cells: Amplitude Versus Frequency Modulation," PLOS Computational Biology, Public Library of Science, vol. 11(6), pages 1-21, June.
  • Handle: RePEc:plo:pcbi00:1004222
    DOI: 10.1371/journal.pcbi.1004222
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    References listed on IDEAS

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    1. Richard C. Yu & C. Gustavo Pesce & Alejandro Colman-Lerner & Larry Lok & David Pincus & Eduard Serra & Mark Holl & Kirsten Benjamin & Andrew Gordon & Roger Brent, 2008. "Negative feedback that improves information transmission in yeast signalling," Nature, Nature, vol. 456(7223), pages 755-761, December.
    2. Avigdor Eldar & Michael B. Elowitz, 2010. "Functional roles for noise in genetic circuits," Nature, Nature, vol. 467(7312), pages 167-173, September.
    3. U. Alon & M. G. Surette & N. Barkai & S. Leibler, 1999. "Robustness in bacterial chemotaxis," Nature, Nature, vol. 397(6715), pages 168-171, January.
    4. Ricardo E. Dolmetsch & Keli Xu & Richard S. Lewis, 1998. "Calcium oscillations increase the efficiency and specificity of gene expression," Nature, Nature, vol. 392(6679), pages 933-936, April.
    5. Joseph R. Arron & Monte M. Winslow & Alberto Polleri & Ching-Pin Chang & Hai Wu & Xin Gao & Joel R. Neilson & Lei Chen & Jeremy J. Heit & Seung K. Kim & Nobuyuki Yamasaki & Tsuyoshi Miyakawa & Uta Fra, 2006. "NFAT dysregulation by increased dosage of DSCR1 and DYRK1A on chromosome 21," Nature, Nature, vol. 441(7093), pages 595-600, June.
    6. Long Cai & Chiraj K. Dalal & Michael B. Elowitz, 2008. "Frequency-modulated nuclear localization bursts coordinate gene regulation," Nature, Nature, vol. 455(7212), pages 485-490, September.
    7. Jing Kang & Bing Xu & Ye Yao & Wei Lin & Conor Hennessy & Peter Fraser & Jianfeng Feng, 2011. "A Dynamical Model Reveals Gene Co-Localizations in Nucleus," PLOS Computational Biology, Public Library of Science, vol. 7(7), pages 1-16, July.
    8. N. Barkai & S. Leibler, 1997. "Robustness in simple biochemical networks," Nature, Nature, vol. 387(6636), pages 913-917, June.
    9. Michael J. Berridge, 1997. "The AM and FM of calcium signalling," Nature, Nature, vol. 386(6627), pages 759-760, April.
    10. Savaş Tay & Jacob J. Hughey & Timothy K. Lee & Tomasz Lipniacki & Stephen R. Quake & Markus W. Covert, 2010. "Single-cell NF-κB dynamics reveal digital activation and analogue information processing," Nature, Nature, vol. 466(7303), pages 267-271, July.
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    2. Nick E Phillips & Cerys Manning & Nancy Papalopulu & Magnus Rattray, 2017. "Identifying stochastic oscillations in single-cell live imaging time series using Gaussian processes," PLOS Computational Biology, Public Library of Science, vol. 13(5), pages 1-30, May.

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