1. Bas JHM Rosier
  2. Tom FA de Greef  Is a corresponding author
  1. Eindhoven University of Technology, The Netherlands

Ever since it was discovered that the level of calcium ions inside a cell can oscillate (Woods et al., 1986), biologists have been intrigued by the periodic nature of many cellular signals. While we are slowly starting to grasp the many and varied roles that these periodic oscillations play in cellular communication, an open question remains: how are networks of genes able to generate sustained oscillations? Now, in eLife, Sebastian Maerkl and co-workers – including Henrike Niederholtmeyer and Zachary Sun as joint first authors – report that they have used a synthetic biology approach to reveal how simple gene circuits can produce robust oscillations in cells (Niederholtmeyer et al., 2015).

Initially, it was argued that periodic oscillations in the level of calcium ions and other cellular components had no role in signaling, but decades of research has revealed that periodic signals are better at relaying information than non-periodic signals (Rapp, 1987; Behar and Hoffman, 2010; Purvis and Lahav, 2013; Levine et al., 2013). Both types of signal can encode information in the size (amplitude) of the signal, but the frequency and phase of periodic signals can also encode information. As a result, periodic signals may be able to regulate complex cell processes more precisely than non-periodic signals. Importantly, recent advances in single-cell analysis and optogenetics have resulted in numerous in-depth studies that reveal how critical events, such as the determination of cell fate and multicellular communication, are controlled by periodic signals (the review by Sonnen and Auleha, 2014 describes other examples).

Mathematical analysis shows that an essential element of an oscillating circuit is an inhibitory feedback loop: if the activity of one gene in such a feedback loop increases, it activates other genes in the circuit that ultimately inhibit it (Rapp, 1987; Novak and Tyson, 2008; Purcell et al., 2010). This feedback loop needs to have an in-built time delay to enable the activities of the genes in the circuit to fluctuate in regular cycles.

The rise of synthetic biology has made it possible to design and construct synthetic networks in living cells that perform a specific role. In an early example of this, researchers at Princeton reported that they had constructed an oscillatory gene network in E. coli based on a cyclic network of three genes called the repressilator (Elowitz and Leibler, 2000; Figure 1). Theory predicts that the repressilator and other ring oscillators that have an odd number of genes (nodes) should be capable of producing sustained oscillations. However, since designing, building and testing new gene networks in living cells is a lengthy process, ring oscillators with more than three nodes have not been reported.

Synthetic gene networks containing three, four and five genes.

The genes in each circuit (top) are translated into protein products, with each protein product repressing the activity of another gene in the network (as indicated by the arrows). Theory predicts that cyclic networks of genes display oscillatory behavior when the number of nodes in the network is odd. Niederholtmeyer et al. found that a circuit consisting of three genes gave rise to well-defined oscillations with a period of up to 8 hr, and that a circuit containing five genes oscillated with a period of 19 hours. In contrast, and in line with theoretical predictions, a network consisting of four nodes did not oscillate: instead it reached a steady state where the activity of all the genes was constant over time.

Now Maerkl and co-workers – who are based at the École Polytechnique Fédérale de Lausanne and the California Institute of Technology – have made ring architectures containing three, four and five genes (Figure 1). They built their prototype genetic circuits in a cell-free system by combining microfluidic flow reactors with extracts from E. coli bacteria (Niederholtmeyer et al, 2013; Noireaux et al., 2003). The major advantage of this approach is that it significantly decreases the time taken for each design-build-test cycle because it removes the need for various laborious tasks, such as molecular cloning and collecting measurements from individual cells.

Using this strategy Niederholtmeyer, Sun et al. were able to confirm the prediction that oscillators with three or five nodes are able to generate oscillations, whereas oscillators with four nodes are not. The period of the five-node oscillator is about twice as long as the three-node oscillator, indicating that cells can tune the periodicity of signals by increasing the complexity of their genetic circuits. Next, the researchers transferred their prototyped designs to living E. coli cells and showed that the oscillation period in cells matched the oscillation period in the cell-free systems. This is an important result as it shows that cell-free systems can be used to accurately capture the behavior of cells, which paves the way for researchers to use synthetic biology approaches in cell-free systems to explore the complex regulatory mechanisms that operate inside cells (van Roekel et al., 2015). The latest work should also greatly speed up the construction of complex new gene networks in bacteria, which could have applications in biofuel production, medical diagnosis and experiments to explore the ways that cells process information.

References

    1. Niederholtmeyer H
    2. Stepanova V
    3. Maerkl SJ
    (2013) Implementation of cell-free biological networks at steady state
    Proceedings of the National Academy of Sciences of the United States of America 110:15985–15990.
    https://doi.org/10.1073/pnas.1311166110
    1. Noireaux V
    2. Bar-Ziv R
    3. Libchaber A
    (2003) Principles of cell-free genetic circuit assembly
    Proceedings of the National Academy of Sciences of the United States of America 100:12672–12677.
    https://doi.org/10.1073/pnas.2135496100

Article and author information

Author details

  1. Bas JHM Rosier

    Department of Biomedical Engineering and Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, The Netherlands
    Competing interests
    The authors declare that no competing interests exist.
  2. Tom FA de Greef

    Department of Biomedical Engineering and Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, The Netherlands
    For correspondence
    t.f.a.d.greef@tue.nl
    Competing interests
    The authors declare that no competing interests exist.

Publication history

  1. Version of Record published: December 10, 2015 (version 1)

Copyright

© 2015, Rosier et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 7,095
    views
  • 634
    downloads
  • 11
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Bas JHM Rosier
  2. Tom FA de Greef
(2015)
Synthetic Biology: How to make an oscillator
eLife 4:e12260.
https://doi.org/10.7554/eLife.12260
  1. Further reading

Further reading

    1. Biochemistry and Chemical Biology
    Daljit Sangar, Elizabeth Hill ... Jan Bieschke
    Research Article

    Prions replicate via the autocatalytic conversion of cellular prion protein (PrPC) into fibrillar assemblies of misfolded PrP. While this process has been extensively studied in vivo and in vitro, non-physiological reaction conditions of fibril formation in vitro have precluded the identification and mechanistic analysis of cellular proteins, which may alter PrP self-assembly and prion replication. Here, we have developed a fibril formation assay for recombinant murine and human PrP (23-231) under near-native conditions (NAA) to study the effect of cellular proteins, which may be risk factors or potential therapeutic targets in prion disease. Genetic screening suggests that variants that increase syntaxin-6 expression in the brain (gene: STX6) are risk factors for sporadic Creutzfeldt-Jakob disease (CJD). Analysis of the protein in NAA revealed, counterintuitively, that syntaxin-6 is a potent inhibitor of PrP fibril formation. It significantly delayed the lag phase of fibril formation at highly sub-stoichiometric molar ratios. However, when assessing toxicity of different aggregation time points to primary neurons, syntaxin-6 prolonged the presence of neurotoxic PrP species. Electron microscopy and super-resolution fluorescence microscopy revealed that, instead of highly ordered fibrils, in the presence of syntaxin-6 PrP formed less-ordered aggregates containing syntaxin-6. These data strongly suggest that the protein can directly alter the initial phase of PrP self-assembly and, uniquely, can act as an 'anti-chaperone', which promotes toxic aggregation intermediates by inhibiting fibril formation.

    1. Biochemistry and Chemical Biology
    2. Cell Biology
    Birol Cabukusta, Shalom Borst Pauwels ... Jacques Neefjes
    Research Article

    Numerous lipids are heterogeneously distributed among organelles. Most lipid trafficking between organelles is achieved by a group of lipid transfer proteins (LTPs) that carry lipids using their hydrophobic cavities. The human genome encodes many intracellular LTPs responsible for lipid trafficking and the function of many LTPs in defining cellular lipid levels and distributions is unclear. Here, we created a gene knockout library targeting 90 intracellular LTPs and performed whole-cell lipidomics analysis. This analysis confirmed known lipid disturbances and identified new ones caused by the loss of LTPs. Among these, we found major sphingolipid imbalances in ORP9 and ORP11 knockout cells, two proteins of previously unknown function in sphingolipid metabolism. ORP9 and ORP11 form a heterodimer to localize at the ER-trans-Golgi membrane contact sites, where the dimer exchanges phosphatidylserine (PS) for phosphatidylinositol-4-phosphate (PI(4)P) between the two organelles. Consequently, loss of either protein causes phospholipid imbalances in the Golgi apparatus that result in lowered sphingomyelin synthesis at this organelle. Overall, our LTP knockout library toolbox identifies various proteins in control of cellular lipid levels, including the ORP9-ORP11 heterodimer, which exchanges PS and PI(4)P at the ER-Golgi membrane contact site as a critical step in sphingomyelin synthesis in the Golgi apparatus.