Prediction of photoperiodic regulators from quantitative gene circuit models.

Photoperiod sensors allow physiological adaptation to the changing seasons. The prevalent hypothesis is that day length perception is mediated through coupling of an endogenous rhythm with an external light signal. Sufficient molecular data are available to test this quantitatively in plants, though not yet in mammals. In Arabidopsis, the clock-regulated genes CONSTANS (CO) and FLAVIN, KELCH, F-BOX (FKF1) and their light-sensitive proteins are thought to form an external coincidence sensor. Here, we model the integration of light and timing information by CO, its target gene FLOWERING LOCUS T (FT), and the circadian clock. Among other predictions, our models show that FKF1 activates FT. We demonstrate experimentally that this effect is independent of the known activation of CO by FKF1, thus we locate a major, novel controller of photoperiodism. External coincidence is part of a complex photoperiod sensor: modeling makes this complexity explicit and may thus contribute to crop improvement.

The Circadian Clock Gene Circuit Controls Protein and Phosphoprotein Rhythms in Arabidopsis thaliana.

Twenty-four-hour, circadian rhythms control many eukaryotic mRNA levels, whereas the levels of their more stable proteins are not expected to reflect the RNA rhythms, emphasizing the need to test the circadian regulation of protein abundance and modification. Here we present circadian proteomic and phosphoproteomic time series from Arabidopsis thaliana plants under constant light conditions, estimating that just 0.4% of quantified proteins but a much larger proportion of quantified phospho-sites were rhythmic. Approximately half of the rhythmic phospho-sites were most phosphorylated at subjective dawn, a pattern we term the "phospho-dawn." Members of the SnRK/CDPK family of protein kinases are candidate regulators. A CCA1-overexpressing line that disables the clock gene circuit lacked most circadian protein phosphorylation. However, the few phospho-sites that fluctuated despite CCA1-overexpression still tended to peak in abundance close to subjective dawn, suggesting that the canonical clock mechanism is necessary for most but perhaps not all protein phosphorylation rhythms. To test the potential functional relevance of our datasets, we conducted phosphomimetic experiments using the bifunctional enzyme fructose-6-phosphate-2-kinase/phosphatase (F2KP), as an example. The rhythmic phosphorylation of diverse protein targets is controlled by the clock gene circuit, implicating posttranslational mechanisms in the transmission of circadian timing information in plants.

A phospho-dawn of protein modification anticipates light onset in the picoeukaryote Ostreococcus tauri.

Diel regulation of protein levels and protein modification had been less studied than transcript rhythms. Here, we compare transcriptome data under light-dark cycles with partial proteome and phosphoproteome data, assayed using shotgun MS, from the alga Ostreococcus tauri, the smallest free-living eukaryote. A total of 10% of quantified proteins but two-thirds of phosphoproteins were rhythmic. Mathematical modelling showed that light-stimulated protein synthesis can account for the observed clustering of protein peaks in the daytime. Prompted by night-peaking and apparently dark-stable proteins, we also tested cultures under prolonged darkness, where the proteome changed less than under the diel cycle. Among the dark-stable proteins were prasinophyte-specific sequences that were also reported to accumulate when O. tauri formed lipid droplets. In the phosphoproteome, 39% of rhythmic phospho-sites reached peak levels just before dawn. This anticipatory phosphorylation suggests that a clock-regulated phospho-dawn prepares green cells for daytime functions. Acid-directed and proline-directed protein phosphorylation sites were regulated in antiphase, implicating the clock-related casein kinases 1 and 2 in phase-specific regulation, alternating with the CMGC protein kinase family. Understanding the dynamic phosphoprotein network should be facilitated by the minimal kinome and proteome of O. tauri. The data are available from ProteomeXchange, with identifiers PXD001734, PXD001735, and PXD002909.

Photoperiodic control of the Arabidopsis proteome reveals a translational coincidence mechanism.

Plants respond to seasonal cues such as the photoperiod, to adapt to current conditions and to prepare for environmental changes in the season to come. To assess photoperiodic responses at the protein level, we quantified the proteome of the model plant Arabidopsis thaliana by mass spectrometry across four photoperiods. This revealed coordinated changes of abundance in proteins of photosynthesis, primary and secondary metabolism, including pigment biosynthesis, consistent with higher metabolic activity in long photoperiods. Higher translation rates in the day than the night likely contribute to these changes, via an interaction with rhythmic changes in RNA abundance. Photoperiodic control of protein levels might be greatest only if high translation rates coincide with high transcript levels in some photoperiods. We term this proposed mechanism "translational coincidence", mathematically model its components, and demonstrate its effect on the Arabidopsis proteome. Datasets from a green alga and a cyanobacterium suggest that translational coincidence contributes to seasonal control of the proteome in many phototrophic organisms. This may explain why many transcripts but not their cognate proteins exhibit diurnal rhythms.

Multiple circadian clock outputs regulate diel turnover of carbon and nitrogen reserves.

Plants accumulate reserves in the daytime to support growth at night. Circadian regulation of diel reserve turnover was investigated by profiling starch, sugars, glucose 6-phosphate, organic acids, and amino acids during a light-dark cycle and after transfer to continuous light in Arabidopsis wild types and in mutants lacking dawn (lhy cca1), morning (prr7 prr9), dusk (toc1, gi), or evening (elf3) clock components. The metabolite time series were integrated with published time series for circadian clock transcripts to identify circadian outputs that regulate central metabolism. (a) Starch accumulation was slower in elf3 and prr7 prr9. It is proposed that ELF3 positively regulates starch accumulation. (b) Reducing sugars were high early in the T-cycle in elf3, revealing that ELF3 negatively regulates sucrose recycling. (c) The pattern of starch mobilization was modified in all five mutants. A model is proposed in which dawn and dusk/evening components interact to pace degradation to anticipated dawn. (d) An endogenous oscillation of glucose 6-phosphate revealed that the clock buffers metabolism against the large influx of carbon from photosynthesis. (e) Low levels of organic and amino acids in lhy cca1 and high levels in prr7 prr9 provide evidence that the dawn components positively regulate the accumulation of amino acid reserves.

A multi-model framework for the Arabidopsis life cycle.

Linking our understanding of biological processes at different scales is a major conceptual challenge in biology and aggravated by differences in research methods. Modelling can be a useful approach to consolidating our understanding across traditional research domains. The laboratory model species Arabidopsis is very widely used to study plant growth processes and has also been tested more recently in ecophysiology and population genetics. However, approaches from crop modelling that might link these domains are rarely applied to Arabidopsis. Here, we combine plant growth models with phenology models from ecophysiology, using the agent-based modelling language Chromar. We introduce a simpler Framework Model of vegetative growth for Arabidopsis, FM-lite. By extending this model to include inflorescence and fruit growth and seed dormancy, we present a whole-life-cycle, multi-model FM-life, which allows us to simulate at the population level in various genotype × environment scenarios. Environmental effects on plant growth distinguish between the simulated life history strategies that were compatible with previously described Arabidopsis phenology. Our results simulate reproductive success that is founded on the broad range of physiological processes familiar from crop models and suggest an approach to simulating evolution directly in future.

Practical steps to digital organism models, from laboratory model species to 'Crops in silico.

A recent initiative named 'Crops in silico' proposes that multi-scale models 'have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts' in plant science, particularly directed to crop species. To that end, the group called for 'a paradigm shift in plant modelling, from largely isolated efforts to a connected community'. 'Wet' (experimental) research has been especially productive in plant science, since the adoption of Arabidopsis thaliana as a laboratory model species allowed the emergence of an Arabidopsis research community. Parts of this community invested in 'dry' (theoretical) research, under the rubric of Systems Biology. Our past research combined concepts from Systems Biology and crop modelling. Here we outline the approaches that seem most relevant to connected, 'digital organism' initiatives. We illustrate the scale of experimental research required, by collecting the kinetic parameter values that are required for a quantitative, dynamic model of a gene regulatory network. By comparison with the Systems Biology Markup Language (SBML) community, we note computational resources and community structures that will help to realize the potential for plant Systems Biology to connect with a broader crop science community.

Circadian clock components control daily growth activities by modulating cytokinin levels and cell division-associated gene expression in Populus trees.

Trees are carbon dioxide sinks and major producers of terrestrial biomass with distinct seasonal growth patterns. Circadian clocks enable the coordination of physiological and biochemical temporal activities, optimally regulating multiple traits including growth. To dissect the clock's role in growth, we analysed Populus tremula × P. tremuloides trees with impaired clock function due to down-regulation of central clock components. late elongated hypocotyl (lhy-10) trees, in which expression of LHY1 and LHY2 is reduced by RNAi, have a short free-running period and show disrupted temporal regulation of gene expression and reduced growth, producing 30-40% less biomass than wild-type trees. Genes important in growth regulation were expressed with an earlier phase in lhy-10, and CYCLIN D3 expression was misaligned and arrhythmic. Levels of cytokinins were lower in lhy-10 trees, which also showed a change in the time of peak expression of genes associated with cell division and growth. However, auxin levels were not altered in lhy-10 trees, and the size of the lignification zone in the stem showed a relative increase. The reduced growth rate and anatomical features of lhy-10 trees were mainly caused by misregulation of cell division, which may have resulted from impaired clock function.

Peroxiredoxins are conserved markers of circadian rhythms.

Cellular life emerged ∼3.7 billion years ago. With scant exception, terrestrial organisms have evolved under predictable daily cycles owing to the Earth's rotation. The advantage conferred on organisms that anticipate such environmental cycles has driven the evolution of endogenous circadian rhythms that tune internal physiology to external conditions. The molecular phylogeny of mechanisms driving these rhythms has been difficult to dissect because identified clock genes and proteins are not conserved across the domains of life: Bacteria, Archaea and Eukaryota. Here we show that oxidation-reduction cycles of peroxiredoxin proteins constitute a universal marker for circadian rhythms in all domains of life, by characterizing their oscillations in a variety of model organisms. Furthermore, we explore the interconnectivity between these metabolic cycles and transcription-translation feedback loops of the clockwork in each system. Our results suggest an intimate co-evolution of cellular timekeeping with redox homeostatic mechanisms after the Great Oxidation Event ∼2.5 billion years ago.

Circadian rhythms persist without transcription in a eukaryote.

Circadian rhythms are ubiquitous in eukaryotes, and coordinate numerous aspects of behaviour, physiology and metabolism, from sleep/wake cycles in mammals to growth and photosynthesis in plants. This daily timekeeping is thought to be driven by transcriptional-translational feedback loops, whereby rhythmic expression of 'clock' gene products regulates the expression of associated genes in approximately 24-hour cycles. The specific transcriptional components differ between phylogenetic kingdoms. The unicellular pico-eukaryotic alga Ostreococcus tauri possesses a naturally minimized clock, which includes many features that are shared with plants, such as a central negative feedback loop that involves the morning-expressed CCA1 and evening-expressed TOC1 genes. Given that recent observations in animals and plants have revealed prominent post-translational contributions to timekeeping, a reappraisal of the transcriptional contribution to oscillator function is overdue. Here we show that non-transcriptional mechanisms are sufficient to sustain circadian timekeeping in the eukaryotic lineage, although they normally function in conjunction with transcriptional components. We identify oxidation of peroxiredoxin proteins as a transcription-independent rhythmic biomarker, which is also rhythmic in mammals. Moreover we show that pharmacological modulators of the mammalian clock mechanism have the same effects on rhythms in Ostreococcus. Post-translational mechanisms, and at least one rhythmic marker, seem to be better conserved than transcriptional clock regulators. It is plausible that the oldest oscillator components are non-transcriptional in nature, as in cyanobacteria, and are conserved across kingdoms.

Multiscale digital Arabidopsis predicts individual organ and whole-organism growth.

Understanding how dynamic molecular networks affect whole-organism physiology, analogous to mapping genotype to phenotype, remains a key challenge in biology. Quantitative models that represent processes at multiple scales and link understanding from several research domains can help to tackle this problem. Such integrated models are more common in crop science and ecophysiology than in the research communities that elucidate molecular networks. Several laboratories have modeled particular aspects of growth in Arabidopsis thaliana, but it was unclear whether these existing models could productively be combined. We test this approach by constructing a multiscale model of Arabidopsis rosette growth. Four existing models were integrated with minimal parameter modification (leaf water content and one flowering parameter used measured data). The resulting framework model links genetic regulation and biochemical dynamics to events at the organ and whole-plant levels, helping to understand the combined effects of endogenous and environmental regulators on Arabidopsis growth. The framework model was validated and tested with metabolic, physiological, and biomass data from two laboratories, for five photoperiods, three accessions, and a transgenic line, highlighting the plasticity of plant growth strategies. The model was extended to include stochastic development. Model simulations gave insight into the developmental control of leaf production and provided a quantitative explanation for the pleiotropic developmental phenotype caused by overexpression of miR156, which was an open question. Modular, multiscale models, assembling knowledge from systems biology to ecophysiology, will help to understand and to engineer plant behavior from the genome to the field.

Non-transcriptional oscillators in circadian timekeeping.

Circadian clocks have evolved as an adaptation to life on a rotating planet, and orchestrate rhythmic changes in physiology to match the time of day. For decades, cellular circadian rhythms were considered to solely result from feedback between the products of rhythmically expressed genes. These transcriptional/translational feedback loops (TTFLs) have been ubiquitously studied, and explain the majority of circadian outputs. In recent years, however, non-transcriptional processes were shown to be major contributors to circadian rhythmicity. These key findings have profound implications on our understanding of the evolution and mechanistic basis of cellular circadian timekeeping. This review summarises and discusses these results and the experimental and theoretical evidence of a possible relation between non-transcriptional oscillator (NTO) mechanisms and TTFL oscillations.

A Bayesian approach for structure learning in oscillating regulatory networks.

MOTIVATION: Oscillations lie at the core of many biological processes, from the cell cycle, to circadian oscillations and developmental processes. Time-keeping mechanisms are essential to enable organisms to adapt to varying conditions in environmental cycles, from day/night to seasonal. Transcriptional regulatory networks are one of the mechanisms behind these biological oscillations. However, while identifying cyclically expressed genes from time series measurements is relatively easy, determining the structure of the interaction network underpinning the oscillation is a far more challenging problem. RESULTS: Here, we explicitly leverage the oscillatory nature of the transcriptional signals and present a method for reconstructing network interactions tailored to this special but important class of genetic circuits. Our method is based on projecting the signal onto a set of oscillatory basis functions using a Discrete Fourier Transform. We build a Bayesian Hierarchical model within a frequency domain linear model in order to enforce sparsity and incorporate prior knowledge about the network structure. Experiments on real and simulated data show that the method can lead to substantial improvements over competing approaches if the oscillatory assumption is met, and remains competitive also in cases it is not. AVAILABILITY: DSS, experiment scripts and data are available at http://homepages.inf.ed.ac.uk/gsanguin/DSS.zip. CONTACT: d.trejo-banos@sms.ed.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Linked circadian outputs control elongation growth and flowering in response to photoperiod and temperature.

Clock-regulated pathways coordinate the response of many developmental processes to changes in photoperiod and temperature. We model two of the best-understood clock output pathways in Arabidopsis, which control key regulators of flowering and elongation growth. In flowering, the model predicted regulatory links from the clock to cycling DOF factor 1 (CDF1) and flavin-binding, KELCH repeat, F-box 1 (FKF1) transcription. Physical interaction data support these links, which create threefold feed-forward motifs from two clock components to the floral regulator FT. In hypocotyl growth, the model described clock-regulated transcription of phytochrome-interacting factor 4 and 5 (PIF4, PIF5), interacting with post-translational regulation of PIF proteins by phytochrome B (phyB) and other light-activated pathways. The model predicted bimodal and end-of-day PIF activity profiles that are observed across hundreds of PIF-regulated target genes. In the response to temperature, warmth-enhanced PIF4 activity explained the observed hypocotyl growth dynamics but additional, temperature-dependent regulators were implicated in the flowering response. Integrating these two pathways with the clock model highlights the molecular mechanisms that coordinate plant development across changing conditions.

Organ specificity in the plant circadian system is explained by different light inputs to the shoot and root clocks.

Circadian clocks allow the temporal compartmentalization of biological processes. In Arabidopsis, circadian rhythms display organ specificity but the underlying molecular causes have not been identified. We investigated the mechanisms responsible for the similarities and differences between the clocks of mature shoots and roots in constant conditions and in light : dark cycles. We developed an imaging system to monitor clock gene expression in shoots and light- or dark-grown roots, modified a recent mathematical model of the Arabidopsis clock and used this to simulate our new data. We showed that the shoot and root circadian clocks have different rhythmic properties (period and amplitude) and respond differently to light quality. The root clock was entrained by direct exposure to low-intensity light, even in antiphase to the illumination of shoots. Differences between the clocks were more pronounced in conditions where light was present than in constant darkness, and persisted in the presence of sucrose. We simulated the data successfully by modifying those parameters of a clock model that are related to light inputs. We conclude that differences and similarities between the shoot and root clocks can largely be explained by organ-specific light inputs. This provides mechanistic insight into the developing field of organ-specific clocks.

Photoperiod-dependent changes in the phase of core clock transcripts and global transcriptional outputs at dawn and dusk in Arabidopsis.

Plants use the circadian clock to sense photoperiod length. Seasonal responses like flowering are triggered at a critical photoperiod when a light-sensitive clock output coincides with light or darkness. However, many metabolic processes, like starch turnover, and growth respond progressively to photoperiod duration. We first tested the photoperiod response of 10 core clock genes and two output genes. qRT-PCR analyses of transcript abundance under 6, 8, 12 and 18 h photoperiods revealed 1-4 h earlier peak times under short photoperiods and detailed changes like rising PRR7 expression before dawn. Clock models recapitulated most of these changes. We explored the consequences for global gene expression by performing transcript profiling in 4, 6, 8, 12 and 18 h photoperiods. There were major changes in transcript abundance at dawn, which were as large as those between dawn and dusk in a given photoperiod. Contributing factors included altered timing of the clock relative to dawn, light signalling and changes in carbon availability at night as a result of clock-dependent regulation of starch degradation. Their interaction facilitates coordinated transcriptional regulation of key processes like starch turnover, anthocyanin, flavonoid and glucosinolate biosynthesis and protein synthesis and underpins the response of metabolism and growth to photoperiod.

Plants in silico: why, why now and what?--an integrative platform for plant systems biology research.

A paradigm shift is needed and timely in moving plant modelling from largely isolated efforts to a connected community endeavour that can take full advantage of advances in computer science and in mechanistic understanding of plant processes. Plants in silico (Psi) envisions a digital representation of layered dynamic modules, linking from gene networks and metabolic pathways through to cellular organization, tissue, organ and whole plant development, together with resource capture and use efficiency in dynamic competitive environments, ultimately allowing a mechanistically rich simulation of the plant or of a community of plants in silico. The concept is to integrate models or modules from different layers of organization spanning from genome to phenome to ecosystem in a modular framework allowing the use of modules of varying mechanistic detail representing the same biological process. Developments in high-performance computing, functional knowledge of plants, the internet and open-source version controlled software make achieving the concept realistic. Open source will enhance collaboration and move towards testing and consensus on quantitative theoretical frameworks. Importantly, Psi provides a quantitative knowledge framework where the implications of a discovery at one level, for example, single gene function or developmental response, can be examined at the whole plant or even crop and natural ecosystem levels.

HIGH EXPRESSION OF OSMOTICALLY RESPONSIVE GENES1 is required for circadian periodicity through the promotion of nucleo-cytoplasmic mRNA export in Arabidopsis.

Cold acclimation has been shown to be attenuated by the degradation of the INDUCER OF CBF EXPRESSION1 protein by the E3 ubiquitin ligase HIGH EXPRESSION OF OSMOTICALLY RESPONSIVE GENES1 (HOS1). However, recent work has suggested that HOS1 may have a wider range of roles in plants than previously appreciated. Here, we show that hos1 mutants are affected in circadian clock function, exhibiting a long-period phenotype in a wide range of temperature and light environments. We demonstrate that hos1 mutants accumulate polyadenylated mRNA in the nucleus and that the circadian defect in hos1 is shared by multiple mutants with aberrant mRNA export, but not in a mutant attenuated in nucleo-cytoplasmic transport of microRNAs. As revealed by RNA sequencing, hos1 exhibits gross changes to the transcriptome with genes in multiple functional categories being affected. In addition, we show that hos1 and other previously described mutants with altered mRNA export affect cold signaling in a similar manner. Our data support a model in which altered mRNA export is important for the manifestation of hos1 circadian clock defects and suggest that HOS1 may indirectly affect cold signaling through disruption of the circadian clock.

Bridging the gap between omics and earth system science to better understand how environmental change impacts marine microbes.

The advent of genomic-, transcriptomic- and proteomic-based approaches has revolutionized our ability to describe marine microbial communities, including biogeography, metabolic potential and diversity, mechanisms of adaptation, and phylogeny and evolutionary history. New interdisciplinary approaches are needed to move from this descriptive level to improved quantitative, process-level understanding of the roles of marine microbes in biogeochemical cycles and of the impact of environmental change on the marine microbial ecosystem. Linking studies at levels from the genome to the organism, to ecological strategies and organism and ecosystem response, requires new modelling approaches. Key to this will be a fundamental shift in modelling scale that represents micro-organisms from the level of their macromolecular components. This will enable contact with omics data sets and allow acclimation and adaptive response at the phenotype level (i.e. traits) to be simulated as a combination of fitness maximization and evolutionary constraints. This way forward will build on ecological approaches that identify key organism traits and systems biology approaches that integrate traditional physiological measurements with new insights from omics. It will rely on developing an improved understanding of ecophysiology to understand quantitatively environmental controls on microbial growth strategies. It will also incorporate results from experimental evolution studies in the representation of adaptation. The resulting ecosystem-level models can then evaluate our level of understanding of controls on ecosystem structure and function, highlight major gaps in understanding and help prioritize areas for future research programs. Ultimately, this grand synthesis should improve predictive capability of the ecosystem response to multiple environmental drivers.

Label-free quantitative analysis of the casein kinase 2-responsive phosphoproteome of the marine minimal model species Ostreococcus tauri.

Casein kinase 2 (CK2) is a protein kinase that phosphorylates a plethora of cellular target proteins involved in processes including DNA repair, cell cycle control, and circadian timekeeping. CK2 is functionally conserved across eukaryotes, although the substrate proteins identified in a range of complex tissues are often different. The marine alga Ostreococcus tauri is a unicellular eukaryotic model organism ideally suited to efficiently study generic roles of CK2 in the cellular circadian clock. Overexpression of CK2 leads to a slow circadian rhythm, verifying functional conservation of CK2 in timekeeping. The proteome was analysed in wild-type and CK2-overexpressing algae at dawn and dusk, revealing that differential abundance of the global proteome across the day is largely unaffected by overexpression. However, CK2 activity contributed more strongly to timekeeping at dusk than at dawn. The phosphoproteome of a CK2 overexpression line and cells treated with CK2 inhibitor was therefore analysed and compared to control cells at dusk. We report an extensive catalogue of 447 unique CK2-responsive differential phosphopeptide motifs to inform future studies into CK2 activity in the circadian clock of more complex tissues. All MS data have been deposited in the ProteomeXchange with identifier PXD000975 (http://proteomecentral.proteomexchange.org/dataset/PXD000975).