Bet-hedging and variability in plant development: seed germination and beyond.

When future conditions are unpredictable, bet-hedging strategies can be advantageous. This can involve isogenic individuals producing different phenotypes, under the same environmental conditions. Ecological studies provide evidence that variability in seed germination time has been selected for as a bet-hedging strategy. We demonstrate how variability in germination time found in Arabidopsis could function as a bet-hedging strategy in the face of unpredictable lethal stresses. Despite a body of knowledge on how the degree of seed dormancy versus germination is controlled, relatively little is known about how differences between isogenic seeds in a batch are generated. We review proposed mechanisms for generating variability in germination time and the current limitations and new possibilities for testing the model predictions. We then look beyond germination to the role of variability in seedling and adult plant growth and review new technologies for quantification of noisy gene expression dynamics. We discuss evidence for phenotypic variability in plant traits beyond germination being under genetic control and propose that variability in stress response gene expression could function as a bet-hedging strategy. We discuss open questions about how noisy gene expression could lead to between-plant heterogeneity in gene expression and phenotypes. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.

The σB alternative sigma factor circuit modulates noise to generate different types of pulsing dynamics.

Single-cell approaches are revealing a high degree of heterogeneity, or noise, in gene expression in isogenic bacteria. How gene circuits modulate this noise in gene expression to generate robust output dynamics is unclear. Here we use the Bacillus subtilis alternative sigma factor σB as a model system for understanding the role of noise in generating circuit output dynamics. σB controls the general stress response in B. subtilis and is activated by a range of energy and environmental stresses. Recent single-cell studies have revealed that the circuit can generate two distinct outputs, stochastic pulsing and a single pulse response, but the conditions under which each response is generated are under debate. We implement a stochastic mathematical model of the σB circuit to investigate this and find that the system's core circuit can generate both response types. This is despite one response (stochastic pulsing) being stochastic in nature, and the other (single response pulse) being deterministic. We demonstrate that the main determinant for whichever response is generated is the degree with which the input pathway activates the core circuit, although the noise properties of the input pathway also biases the system towards one or the other type of output. Thus, our work shows how stochastic modelling can reveal the mechanisms behind non-intuitive gene circuit output dynamics.

Spatially specific mechanisms and functions of the plant circadian clock.

Like many organisms, plants have evolved a genetic network, the circadian clock, to coordinate processes with day/night cycles. In plants, the clock is a pervasive regulator of development and modulates many aspects of physiology. Clock-regulated processes range from the correct timing of growth and cell division to interactions with the root microbiome. Recently developed techniques, such as single-cell time-lapse microscopy and single-cell RNA-seq, are beginning to revolutionize our understanding of this clock regulation, revealing a surprising degree of organ, tissue, and cell-type specificity. In this review, we highlight recent advances in our spatial view of the clock across the plant, both in terms of how it is regulated and how it regulates a diversity of output processes. We outline how understanding these spatially specific functions will help reveal the range of ways that the clock provides a fitness benefit for the plant.

A spatial model of the plant circadian clock reveals design principles for coordinated timing.

Individual plant cells possess a genetic network, the circadian clock, that times internal processes to the day-night cycle. Mathematical models of the clock are typically either "whole-plant" that ignore tissue or cell type-specific clock behavior, or "phase-only" that do not include molecular components. To address the complex spatial coordination observed in experiments, here we implemented a clock network model on a template of a seedling. In our model, the sensitivity to light varies across the plant, and cells communicate their timing via local or long-distance sharing of clock components, causing their rhythms to couple. We found that both varied light sensitivity and long-distance coupling could generate period differences between organs, while local coupling was required to generate the spatial waves of clock gene expression observed experimentally. We then examined our model under noisy light-dark cycles and found that local coupling minimized timing errors caused by the noise while allowing each plant region to maintain a different clock phase. Thus, local sensitivity to environmental inputs combined with local coupling enables flexible yet robust circadian timing.

High Spatial Resolution Luciferase Imaging of the Arabidopsis thaliana Circadian Clock.

The A. thaliana circadian clock is an example of a gene network that generates rich temporal and spatial dynamics. Bioluminescent imaging has proven a powerful method to help dissect the genetic mechanisms that generate oscillations of gene expression over the course of the day. However, its use for the study of spatial regulation is often limited by resolution. Here, we describe a modified luciferase imaging method for the study of the Arabidopsis circadian clock across the plant at sub-tissue-level resolution.

Cut the noise or couple up: Coordinating circadian and synthetic clocks.

Circadian clocks are important to much of life on Earth and are of inherent interest to humanity, implicated in fields ranging from agriculture and ecology to developmental biology and medicine. New techniques show that it is not simply the presence of clocks, but coordination between them that is critical for complex physiological processes across the kingdoms of life. Recent years have also seen impressive advances in synthetic biology to the point where parallels can be drawn between synthetic biological and circadian oscillators. This review will emphasize theoretical and experimental studies that have revealed a fascinating dichotomy of coupling and heterogeneity among circadian clocks. We will also consolidate the fields of chronobiology and synthetic biology, discussing key design principles of their respective oscillators.

Tunable phenotypic variability through an autoregulatory alternative sigma factor circuit.

Genetically identical individuals in bacterial populations can display significant phenotypic variability. This variability can be functional, for example by allowing a fraction of stress prepared cells to survive an otherwise lethal stress. The optimal fraction of stress prepared cells depends on environmental conditions. However, how bacterial populations modulate their level of phenotypic variability remains unclear. Here we show that the alternative sigma factor σV circuit in Bacillus subtilis generates functional phenotypic variability that can be tuned by stress level, environmental history and genetic perturbations. Using single-cell time-lapse microscopy and microfluidics, we find the fraction of cells that immediately activate σV under lysozyme stress depends on stress level and on a transcriptional memory of previous stress. Iteration between model and experiment reveals that this tunability can be explained by the autoregulatory feedback structure of the sigV operon. As predicted by the model, genetic perturbations to the operon also modulate the response variability. The conserved sigma-anti-sigma autoregulation motif is thus a simple mechanism for bacterial populations to modulate their heterogeneity based on their environment.

An ABA-GA bistable switch can account for natural variation in the variability of Arabidopsis seed germination time.

Genetically identical plants growing in the same conditions can display heterogeneous phenotypes. Here we use Arabidopsis seed germination time as a model system to examine phenotypic variability and its underlying mechanisms. We show extensive variation in seed germination time variability between Arabidopsis accessions and use a multiparent recombinant inbred population to identify two genetic loci involved in this trait. Both loci include genes implicated in modulating abscisic acid (ABA) sensitivity. Mutually antagonistic regulation between ABA, which represses germination, and gibberellic acid (GA), which promotes germination, underlies the decision to germinate and can act as a bistable switch. A simple stochastic model of the ABA-GA network shows that modulating ABA sensitivity can generate the range of germination time distributions we observe experimentally. We validate the model by testing its predictions on the effects of exogenous hormone addition. Our work provides a foundation for understanding the mechanism and functional role of phenotypic variability in germination time.

Interpretation of morphogen gradients by a synthetic bistable circuit.

During development, cells gain positional information through the interpretation of dynamic morphogen gradients. A proposed mechanism for interpreting opposing morphogen gradients is mutual inhibition of downstream transcription factors, but isolating the role of this specific motif within a natural network remains a challenge. Here, we engineer a synthetic morphogen-induced mutual inhibition circuit in E. coli populations and show that mutual inhibition alone is sufficient to produce stable domains of gene expression in response to dynamic morphogen gradients, provided the spatial average of the morphogens falls within the region of bistability at the single cell level. When we add sender devices, the resulting patterning circuit produces theoretically predicted self-organised gene expression domains in response to a single gradient. We develop computational models of our synthetic circuits parameterised to timecourse fluorescence data, providing both a theoretical and experimental framework for engineering morphogen-induced spatial patterning in cell populations.

Does Gene Expression Noise Play a Functional Role in Plants?

Gene expression in individual cells can be surprisingly noisy. In unicellular organisms this noise can be functional; for example, by allowing a subfraction of the population to prepare for environmental stress. The role of gene expression noise in multicellular organisms has, however, remained unclear. In this review, we discuss how new techniques are revealing an unexpected level of variability in gene expression between and within genetically identical plants. We describe recent progress as well as speculate on the function of transcriptional noise as a mechanism for generating functional phenotypic diversity in plants.

Stochastic pulsing of gene expression enables the generation of spatial patterns in Bacillus subtilis biofilms.

Stochastic pulsing of gene expression can generate phenotypic diversity in a genetically identical population of cells, but it is unclear whether it has a role in the development of multicellular systems. Here, we show how stochastic pulsing of gene expression enables spatial patterns to form in a model multicellular system, Bacillus subtilis bacterial biofilms. We use quantitative microscopy and time-lapse imaging to observe pulses in the activity of the general stress response sigma factor σB in individual cells during biofilm development. Both σB and sporulation activity increase in a gradient, peaking at the top of the biofilm, even though σB represses sporulation. As predicted by a simple mathematical model, increasing σB expression shifts the peak of sporulation to the middle of the biofilm. Our results demonstrate how stochastic pulsing of gene expression can play a key role in pattern formation during biofilm development.

Serum CXCL13 levels are associated with lymphoma risk and lymphoma occurrence in primary Sjögren's syndrome.

Primary Sjögren's syndrome (pSS) is an autoimmune disease characterised by an increased risk for non-Hodgkin lymphoma (NHL) development. Ectopic germinal centre (GC) in the salivary gland is associated with increased NHL risk in pSS, and the chemokine CXCL13 is implicated in B-cell migration and GC formation. Serum CXCL13 concentrations were quantified by ELISA in 48 healthy individuals, 273 pSS patients without NHL (pSS-nonL), and 38 pSS patients with NHL (pSS-NHL+) from the United Kingdom Primary Sjögren's Syndrome Registry cohort. PSS-nonL patients were stratified into low risk (LR), moderate risk (MR) and high risk (HR) groups according to the lymphoma risk score proposed by Fragkioudaki et al. Differences in serum CXCL13 levels among groups were analysed using the Wilcoxon method. Also, changes in serum CXCL13 over a time period of at least 1 year and a median 4 years were assessed for 200 pSS-nonL and 8 pSS-NHL+ patients. In addition, associations of serum CXCL13 with B-cell and inflammatory markers were investigated by correlation analyses and logistic regression. Serum CXCL13 levels were higher in all pSS groups compared to controls (p < 0.0001), and in pSS-NHL+ compared to pSS-nonL patients (p = 0.0204). LR patients had lower CXCL13 levels than MR patients (p < 0.0001) and pSS-NHL+ patients (p = 0.0008). CXCL13 levels remained stable over the study period for all pSS groups. CXCL13 was associated (p < 0.0005) with Immunoglobulin G (IgG), B-cell activating factor, ß2 microglobulin, combined free light chains, κ and λ light chains, anti-Ro/SSA, anti-La/SSB, and erythrocyte sedimentation rate. IgG and C3 controlled for age and gender were significantly associated with NHL risk in pSS. Serum CXCL13 levels were elevated in pSS-NHL+ and MR patients compared to LR patients and remained stable over time. Further study is required to investigate the role of CXCL13 in pSS-associated NHL risk.

Co-expression Networks From Gene Expression Variability Between Genetically Identical Seedlings Can Reveal Novel Regulatory Relationships.

Co-expression networks are a powerful tool to understand gene regulation. They have been used to identify new regulation and function of genes involved in plant development and their response to the environment. Up to now, co-expression networks have been inferred using transcriptomes generated on plants experiencing genetic or environmental perturbation, or from expression time series. We propose a new approach by showing that co-expression networks can be constructed in the absence of genetic and environmental perturbation, for plants at the same developmental stage. For this, we used transcriptomes that were generated from genetically identical individual plants that were grown under the same conditions and for the same amount of time. Twelve time points were used to cover the 24-h light/dark cycle. We used variability in gene expression between individual plants of the same time point to infer a co-expression network. We show that this network is biologically relevant and use it to suggest new gene functions and to identify new targets for the transcriptional regulators GI, PIF4, and PRR5. Moreover, we find different co-regulation in this network based on changes in expression between individual plants, compared to the usual approach requiring environmental perturbation. Our work shows that gene co-expression networks can be identified using variability in gene expression between individual plants, without the need for genetic or environmental perturbations. It will allow further exploration of gene regulation in contexts with subtle differences between plants, which could be closer to what individual plants in a population might face in the wild.

The circadian clock coordinates plant development through specificity at the tissue and cellular level.

The circadian clock is a genetic circuit that allows organisms to anticipate daily events caused by the rotation of the Earth. The plant clock regulates physiology at multiple scales, from cell division to ecosystem-scale interactions. It is becoming clear that rather than being a single perfectly synchronised timer throughout the plant, the clock can be sensitive to different cues, run at different speeds, and drive distinct processes in different cell types and tissues. This flexibility may help the plant clock to regulate such a range of developmental and physiological processes. In this review, using examples from the literature, we describe how the clock regulates development at multiple scales and discuss how the clock might allow local flexibility in regulation whilst remaining coordinated across the plant.

Coordinated circadian timing through the integration of local inputs in Arabidopsis thaliana.

Individual plant cells have a genetic circuit, the circadian clock, that times key processes to the day-night cycle. These clocks are aligned to the day-night cycle by multiple environmental signals that vary across the plant. How does the plant integrate clock rhythms, both within and between organs, to ensure coordinated timing? To address this question, we examined the clock at the sub-tissue level across Arabidopsis thaliana seedlings under multiple environmental conditions and genetic backgrounds. Our results show that the clock runs at different speeds (periods) in each organ, which causes the clock to peak at different times across the plant in both constant environmental conditions and light-dark (LD) cycles. Closer examination reveals that spatial waves of clock gene expression propagate both within and between organs. Using a combination of modeling and experiment, we reveal that these spatial waves are the result of the period differences between organs and local coupling, rather than long-distance signaling. With further experiments we show that the endogenous period differences, and thus the spatial waves, can be generated by the organ specificity of inputs into the clock. We demonstrate this by modulating periods using light and metabolic signals, as well as with genetic perturbations. Our results reveal that plant clocks can be set locally by organ-specific inputs but coordinated globally via spatial waves of clock gene expression.

Widespread inter-individual gene expression variability in Arabidopsis thaliana.

A fundamental question in biology is how gene expression is regulated to give rise to a phenotype. However, transcriptional variability is rarely considered although it could influence the relationship between genotype and phenotype. It is known in unicellular organisms that gene expression is often noisy rather than uniform, and this has been proposed to be beneficial when environmental conditions are unpredictable. However, little is known about inter-individual transcriptional variability in multicellular organisms. Using transcriptomic approaches, we analysed gene expression variability between individual Arabidopsis thaliana plants growing in identical conditions over a 24-h time course. We identified hundreds of genes that exhibit high inter-individual variability and found that many are involved in environmental responses, with different classes of genes variable between the day and night. We also identified factors that might facilitate gene expression variability, such as gene length, the number of transcription factors regulating the genes and the chromatin environment. These results shed new light on the impact of transcriptional variability in gene expression regulation in plants.

Reducing the complexity of mathematical models for the plant circadian clock by distributed delays.

A major bottleneck in the modelling of biological networks is the parameter explosion problem - the exponential increase in the number of parameters that need to be optimised to data as the size of the model increases. Here, we address this problem in the context of the plant circadian clock by applying the method of distributed delays. We show that using this approach, the system architecture can be simplified efficiently - reducing the number of parameters - whilst still preserving the core mechanistic dynamics of the gene regulatory network. Compared to models with discrete time-delays, which are governed by functional differential equations, the distributed delay models can be converted into sets of equivalent ordinary differential equations, enabling the use of standard methods for numerical integration, and for stability and bifurcation analyses. We demonstrate the efficiency of our modelling approach by applying it to three exemplar mathematical models of the Arabidopsis circadian clock of varying complexity, obtaining significant reductions in complexity in each case. Moreover, we revise one of the most up-to-date Arabidopsis models, updating the regulation of the PRR9 and PRR7 genes by LHY in accordance with recent experimental data. The revised model more accurately reproduces the LHY-induction experiments of core clock genes, compared with the original model. Our work thus shows that the method of distributed delays facilitates the optimisation and reformulation of genetic network models.

Escherichia coli can survive stress by noisy growth modulation.

Gene expression can be noisy, as can the growth of single cells. Such cell-to-cell variation has been implicated in survival strategies for bacterial populations. However, it remains unclear how single cells couple gene expression with growth to implement these strategies. Here, we show how noisy expression of a key stress-response regulator, RpoS, allows E. coli to modulate its growth dynamics to survive future adverse environments. We reveal a dynamic positive feedback loop between RpoS and growth rate that produces multi-generation RpoS pulses. We do so experimentally using single-cell, time-lapse microscopy and microfluidics and theoretically with a stochastic model. Next, we demonstrate that E. coli prepares for sudden stress by entering prolonged periods of slow growth mediated by RpoS. This dynamic phenotype is captured by the RpoS-growth feedback model. Our synthesis of noisy gene expression, growth, and survival paves the way for further exploration of functional phenotypic variability.

Cell size control driven by the circadian clock and environment in cyanobacteria.

How cells maintain their size has been extensively studied under constant conditions. In the wild, however, cells rarely experience constant environments. Here, we examine how the 24-h circadian clock and environmental cycles modulate cell size control and division timings in the cyanobacterium Synechococcus elongatus using single-cell time-lapse microscopy. Under constant light, wild-type cells follow an apparent sizer-like principle. Closer inspection reveals that the clock generates two subpopulations, with cells born in the subjective day following different division rules from cells born in subjective night. A stochastic model explains how this behavior emerges from the interaction of cell size control with the clock. We demonstrate that the clock continuously modulates the probability of cell division throughout day and night, rather than solely applying an on-off gate to division, as previously proposed. Iterating between modeling and experiments, we go on to identify an effective coupling of the division rate to time of day through the combined effects of the environment and the clock on cell division. Under naturally graded light-dark cycles, this coupling narrows the time window of cell divisions and shifts divisions away from when light levels are low and cell growth is reduced. Our analysis allows us to disentangle, and predict the effects of, the complex interactions between the environment, clock, and cell size control.