Polyphasic feedback enables tunable cellular timers

Collective oscillatory signaling in Dictyosteliumdiscoideum acts as a developmental timer initiated by weak coupling of a noisy pulsatile signal

Oscillatory phenomena play widespread roles in the control of biological systems. In D. discoideum, oscillatory cyclic adenosine monophosphate (cAMP) signaling drives collective behavior and induces a temporal developmental gene expression program. How collective cAMP oscillations emerge or how they encode temporal transcriptional information is still poorly understood. To address this, we identified a transcription factor required for the initiation of collective behavior. Hbx5 activity is cAMP dependent and provides a sensitive single-cell readout for cAMP signaling. Extensive stochastic pulsatile cAMP signaling is found to precede collective oscillations. Stochastic signaling induces Hbx5-dependent transcriptional feedback, which enhances signal sensitivity and cell-cell coupling. This results in the emergence of synchronized collective oscillations, which subsequently activates the GtaC transcription factor and triggers shifts in developmental gene expression. Our results suggest this temporal coordination is encoded by changes in the amplitude of cAMP oscillations and differential sensitivity of these transcription factors to the cAMP-regulated kinase ErkB.

Scalable control of developmental timetables by epigenetic switching networks

During development, progenitor cells follow timetables for differentiation that span many cell generations. These developmental timetables are robustly encoded by the embryo, yet scalably adjustable by evolution, facilitating variation in organism size and form. Epigenetic switches, involving rate-limiting activation steps at regulatory gene loci, control gene activation timing in diverse contexts, and could profoundly impact the dynamics of gene regulatory networks controlling developmental lineage specification. Here, we develop a mathematical framework to model regulatory networks with genes controlled by epigenetic switches. Using this framework, we show that such epigenetic switching networks uphold developmental timetables that robustly span many cell generations, and enable the generation of differentiated cells in precisely defined numbers and fractions. Changes to epigenetic switching networks can readily alter the timing of developmental events within a timetable, or alter the overall speed at which timetables unfold, enabling scalable control over differentiated population sizes. With their robust, yet flexibly adjustable nature, epigenetic switching networks could represent central targets on which evolution acts to manufacture diversity in organism size and form.

A tunable population timer in multicellular consortia

Processing time-dependent information requires cells to quantify the duration of past regulatory events and program the time span of future signals. At the single-cell level, timer mechanisms can be implemented with genetic circuits. However, such systems are difficult to implement in single cells due to saturation in molecular components and stochasticity in the limited intracellular space. In contrast, multicellular implementations outsource some of the components of information-processing circuits to the extracellular space, potentially escaping these constraints. Here, we develop a theoretical framework, based on trilinear coordinate representation, to study the collective behavior of populations composed of three cell types under stationary conditions. This framework reveals that distributing different processes (in our case the production, detection and degradation of a time-encoding signal) across distinct strains enables the implementation of a multicellular timer. Our analysis also shows that the circuit can be easily tunable by varying the cellular composition of the consortium.

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We propose a chemical wire architecture for distributed biological computation

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Our model predicts how input signals can be restored or modulated in the output

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Chemical wires can store temporal information and the system can act as a timer

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Digital periodic input signals can be filtered by altering the strain ratios

Rhythmicity and waves in the cortex of single cells

Emergence of dynamic patterns in the form of oscillations and waves on the cortex of single cells is a fascinating and enigmatic phenomenon. Here we outline various theoretical frameworks used to model pattern formation with the goal of reducing complex, heterogeneous patterns into key parameters that are biologically tractable. We also review progress made in recent years on the quantitative and molecular definitions of these terms, which we believe have begun to transform single-cell dynamic patterns from a purely observational and descriptive subject to more mechanistic studies. Specifically, we focus on the nature of local excitable and oscillation events, their spatial couplings leading to propagating waves and the role of active membrane. Instead of arguing for their functional importance, we prefer to consider such patterns as basic properties of dynamic systems. We discuss how knowledge of these patterns could be used to dissect the structure of cellular organization and how the network-centric view could help define cellular functions as transitions between different dynamical states. Last, we speculate on how these patterns could encode temporal and spatial information.

This article is part of the theme issue ‘Self-organization in cell biology’.

What does time mean in development?

Biology is dynamic. Timescales range from frenetic sub-second ion fluxes and enzymatic reactions to the glacial millions of years of evolutionary change. Falling somewhere in the middle of this range are the processes we usually study in development: cell division and differentiation, gene expression, cell-cell signalling, and morphogenesis. But what sets the tempo and manages the order of developmental events? Are the order and tempo different between species? How is the sequence of multiple events coordinated? Here, we discuss the importance of time for developing embryos, highlighting the necessity for global as well as cell-autonomous control. New reagents and tools in imaging and genomic engineering, combined with in vitro culture, are beginning to offer fresh perspectives and molecular insight into the origin and mechanisms of developmental time.

Identifying stochastic oscillations in single-cell live imaging time series using Gaussian processes

Multiple biological processes are driven by oscillatory gene expression at different time scales. Pulsatile dynamics are thought to be widespread, and single-cell live imaging of gene expression has lead to a surge of dynamic, possibly oscillatory, data for different gene networks. However, the regulation of gene expression at the level of an individual cell involves reactions between finite numbers of molecules, and this can result in inherent randomness in expression dynamics, which blurs the boundaries between aperiodic fluctuations and noisy oscillators. This underlies a new challenge to the experimentalist because neither intuition nor pre-existing methods work well for identifying oscillatory activity in noisy biological time series. Thus, there is an acute need for an objective statistical method for classifying whether an experimentally derived noisy time series is periodic. Here, we present a new data analysis method that combines mechanistic stochastic modelling with the powerful methods of non-parametric regression with Gaussian processes. Our method can distinguish oscillatory gene expression from random fluctuations of non-oscillatory expression in single-cell time series, despite peak-to-peak variability in period and amplitude of single-cell oscillations. We show that our method outperforms the Lomb-Scargle periodogram in successfully classifying cells as oscillatory or non-oscillatory in data simulated from a simple genetic oscillator model and in experimental data. Analysis of bioluminescent live-cell imaging shows a significantly greater number of oscillatory cells when luciferase is driven by a Hes1 promoter (10/19), which has previously been reported to oscillate, than the constitutive MoMuLV 5’ LTR (MMLV) promoter (0/25). The method can be applied to data from any gene network to both quantify the proportion of oscillating cells within a population and to measure the period and quality of oscillations. It is publicly available as a MATLAB package.

Technological advances now allow us to observe gene expression in real-time at a single-cell level. In a wide variety of biological contexts this new data has revealed that gene expression is highly dynamic and possibly oscillatory. It is thought that periodic gene expression may be useful for keeping track of time and space, as well as transmitting information about signalling cues. Classifying a time series as periodic from single cell data is difficult because it is necessary to distinguish whether peaks and troughs are generated from an underlying oscillator or whether they are aperiodic fluctuations. To this end, we present a novel tool to classify live-cell data as oscillatory or non-oscillatory that accounts for inherent biological noise. We first demonstrate that the method outperforms a competing scheme in classifying computationally simulated single-cell data, and we subsequently analyse live-cell imaging time series. Our method is able to successfully detect oscillations in a known genetic oscillator, but it classifies data from a constitutively expressed gene as aperiodic. The method forms a basis for discovering new gene expression oscillators and quantifying how oscillatory activity alters in response to changes in cell fate and environmental or genetic perturbations.

Coordination of cell decisions and promotion of phenotypic diversity in B. subtilis via pulsed behavior of the phosphorelay

The phosphorelay of Bacillus subtilis, a kinase cascade that activates master regulator Spo0A ~ P in response to starvation signals, is the core of a large network controlling the cell's decision to differentiate into sporulation and other phenotypes. This article reviews recent advances in understanding the origins and purposes of the complex dynamical behavior of the phosphorelay, which pulses with peaks of activity coordinated with the cell cycle. The transient imbalance in the expression of two critical genes caused by their strategic placement at opposing ends of the chromosome proved to be the key for this pulsed behavior. Feedback control loops in the phosphorelay use these pulses to implement a timer mechanism, which creates several windows of opportunity for phenotypic transitions over multiple generations. This strategy allows the cell to coordinate multiple differentiation programs in a decision process that fosters phenotypic diversity and adapts to current conditions.

Intrinsic regulation of FIC-domain AMP-transferases by oligomerization and automodification

Filamentation induced by cyclic AMP (FIC)-domain enzymes catalyze adenylylation or other posttranslational modifications of target proteins to control their function. Recently, we have shown that Fic enzymes are autoinhibited by an α-helix (αinh) that partly obstructs the active site. For the single-domain class III Fic proteins, the αinh is located at the C terminus and its deletion relieves autoinhibition. However, it has remained unclear how activation occurs naturally. Here, we show by structural, biophysical, and enzymatic analyses combined with in vivo data that the class III Fic protein NmFic from Neisseria meningitidis gets autoadenylylated in cis, thereby autonomously relieving autoinhibition and thus allowing subsequent adenylylation of its target, the DNA gyrase subunit GyrB. Furthermore, we show that NmFic activation is antagonized by tetramerization. The combination of autoadenylylation and tetramerization results in nonmonotonic concentration dependence of NmFic activity and a pronounced lag phase in the progress of target adenylylation. Bioinformatic analyses indicate that this elaborate dual-control mechanism is conserved throughout class III Fic proteins.

Temporal and evolutionary dynamics of two-component signaling pathways

Bacteria sense and respond to numerous environmental signals through two-component signaling pathways. Typically, a given stimulus will activate a sensor histidine kinase to autophosphorylate and then phosphotransfer to a cognate response regulator, which can mount an appropriate response. Although these signaling pathways often appear to be simple switches, they can also orchestrate surprisingly sophisticated and complex responses. These temporal dynamics arise from several key regulatory features, including the bifunctionality of histidine kinases as well as positive and negative feedback loops. Two-component signaling pathways are also dynamic on evolutionary time-scales, expanding dramatically in many species through gene duplication and divergence. Here, we review recent work probing the temporal and evolutionary dynamics of two-component signaling systems.