SKF96365 modulates activity of CatSper channels in human sperm.

Exposure of human sperm to progesterone (P4) activates cation channel of sperm (CatSper) channels, inducing an intracellular Ca2+ concentration ([Ca2+]i) transient followed by repetitive [Ca2+]i activity (oscillations), which are believed to be functionally important. We investigated the potential significance of store-operated Ca2+-entry in these oscillations using the inhibitor SKF96365 (30 µM; SKF). Following pre-treatment of human sperm with 3 µM P4, exposure to SKF doubled the proportion of oscillating cells (P = 0.00004). In non-pre-treated cells, SKF had an effect similar to P4, inducing a [Ca2+]i transient in >80% of cells which was followed by oscillations in ≈50% of cells. The CatSper blocker RU1968 (11 µM) inhibited the SKF-induced [Ca2+]i increase and reversibly arrested [Ca2+]i oscillations. Using whole-cell patch clamp, we observed that SKF enhanced CatSper currents by 100% within 30 s, but amplitude then decayed to levels below control over the next minute. When cells were stimulated with P4, CatSper currents were stably increased (by 200%). Application of SKF then returned current amplitude to control level or less. When sperm were prepared in medium lacking bovine serum albumin (BSA), both P4 and SKF induced a [Ca2+]i transient in >95% of cells but the ability of SKF to induce oscillations was greatly reduced (P = 0.0009). We conclude that SKF, similar to a range of small organic molecules, activates CatSper channels, but that a secondary blocking action also occurs, which was detected only during patch-clamp recording. The failure of SKF to induce oscillations when cells were prepared without BSA emphasizes that the drug does not fully mimic the actions of P4.

Multiplexing information flow through dynamic signalling systems.

We consider how a signalling system can act as an information hub by multiplexing information arising from multiple signals. We formally define multiplexing, mathematically characterise which systems can multiplex and how well they can do it. While the results of this paper are theoretical, to motivate the idea of multiplexing, we provide experimental evidence that tentatively suggests that the NF-κB transcription factor can multiplex information about changes in multiple signals. We believe that our theoretical results may resolve the apparent paradox of how a system like NF-κB that regulates cell fate and inflammatory signalling in response to diverse stimuli can appear to have the low information carrying capacity suggested by recent studies on scalar signals. In carrying out our study, we introduce new methods for the analysis of large, nonlinear stochastic dynamic models, and develop computational algorithms that facilitate the calculation of fundamental constructs of information theory such as Kullback-Leibler divergences and sensitivity matrices, and link these methods to a new theory about multiplexing information. We show that many current models such as those of the NF-κB system cannot multiplex effectively and provide models that overcome this limitation using post-transcriptional modifications.

[Ca2+]i signalling in sperm--making the most of what you've got.

Thanks to a worrying decrease in male fertility, understanding how sperm 'work' is a matter both of interest and great importance. Sperm of all animals detect various environmental cues. The 'behavioural' and physiological responses of sperm must be specific, appropriate and correctly timed. Strangely, in a cell with few organelles and minimal cytoplasmic volume, internal Ca(2+) concentration, [Ca(2+)](i), regulates almost all these activities. How does such a simple cell achieve this - and is it as simple as it seems?

Dynamic analysis of stochastic transcription cycles.

In individual mammalian cells the expression of some genes such as prolactin is highly variable over time and has been suggested to occur in stochastic pulses. To investigate the origins of this behavior and to understand its functional relevance, we quantitatively analyzed this variability using new mathematical tools that allowed us to reconstruct dynamic transcription rates of different reporter genes controlled by identical promoters in the same living cell. Quantitative microscopic analysis of two reporter genes, firefly luciferase and destabilized EGFP, was used to analyze the dynamics of prolactin promoter-directed gene expression in living individual clonal and primary pituitary cells over periods of up to 25 h. We quantified the time-dependence and cyclicity of the transcription pulses and estimated the length and variation of active and inactive transcription phases. We showed an average cycle period of approximately 11 h and demonstrated that while the measured time distribution of active phases agreed with commonly accepted models of transcription, the inactive phases were differently distributed and showed strong memory, with a refractory period of transcriptional inactivation close to 3 h. Cycles in transcription occurred at two distinct prolactin-promoter controlled reporter genes in the same individual clonal or primary cells. However, the timing of the cycles was independent and out-of-phase. For the first time, we have analyzed transcription dynamics from two equivalent loci in real-time in single cells. In unstimulated conditions, cells showed independent transcription dynamics at each locus. A key result from these analyses was the evidence for a minimum refractory period in the inactive-phase of transcription. The response to acute signals and the result of manipulation of histone acetylation was consistent with the hypothesis that this refractory period corresponded to a phase of chromatin remodeling which significantly increased the cyclicity. Stochastically timed bursts of transcription in an apparently random subset of cells in a tissue may thus produce an overall coordinated but heterogeneous phenotype capable of acute responses to stimuli.

Wnt signaling in estrogen-induced lactotroph proliferation.

Prolactinomas are the most common type of functioning pituitary adenoma in humans, but the control of lactotroph proliferation remains unclear. Here, using microarray analysis, we show that estrogen treatment increased expression of Wnt4 mRNA in adult Fischer rat pituitary tissue. Dual immunofluorescence analysis revealed that Wnt4 expression was not confined to lactotrophs, but that it was expressed in all anterior pituitary cell types. Estradiol induced proliferation in the somatolactotroph GH3 cell line, in parallel with Wnt4 mRNA and protein induction. A reporter gene assay for TCF- and LEF-dependent transcription revealed that there was no activation of the canonical Wnt pathway in GH3 cells upon stimulation with Wnt-conditioned culture medium or coexpression of constitutively active mutant ß-catenin. Expression of ß-catenin in both GH3 cells and normal rat anterior pituitary cells was restricted to the cell membrane and was unaltered by treatment with estradiol, with no nuclear ß-catenin being detected under any of the conditions tested. We show for the first time that Wnt4 affects non-canonical signaling in the pituitary by inhibiting Ca(2+) oscillations in GH3 cells, although the downstream effects are as yet unknown. In summary, Wnt4 is expressed in the adult pituitary gland, and its expression is increased by estrogen exposure, suggesting that its involvement in adult tissue plasticity is likely to involve ß-catenin-independent signaling pathways.

Pulsatile patterns of pituitary hormone gene expression change during development.

Important questions in biology have emerged recently concerning the timing of transcription in living cells. Studies on clonal cell lines have shown that transcription is often pulsatile and stochastic, with implications for cellular differentiation. Currently, information regarding transcriptional activity at cellular resolution within a physiological context remains limited. To investigate single-cell transcriptional activity in real-time in living tissue we used bioluminescence imaging of pituitary tissue from transgenic rats in which luciferase gene expression is driven by a pituitary hormone gene promoter. We studied fetal and neonatal pituitary tissue to assess whether dynamic patterns of transcription change during tissue development. We show that gene expression in single cells is highly pulsatile at the time endocrine cells first appear but becomes stabilised as the tissue develops in early neonatal life. This stabilised transcription pattern might depend upon tissue architecture or paracrine signalling, as isolated cells, generated from enzymatic dispersion of the tissue, display pulsatile luminescence. Nascent cells in embryonic tissue also showed coordinated transcription activity over short distances further indicating that cellular context is important for transcription activity. Overall, our data show that cells alter their patterns of gene expression according to their context and developmental stage, with important implications for cellular differentiation.

Population robustness arising from cellular heterogeneity.

Heterogeneity between individual cells is a common feature of dynamic cellular processes, including signaling, transcription, and cell fate; yet the overall tissue level physiological phenotype needs to be carefully controlled to avoid fluctuations. Here we show that in the NF-kappaB signaling system, the precise timing of a dual-delayed negative feedback motif [involving stochastic transcription of inhibitor kappaB (IkappaB)-alpha and -epsilon] is optimized to induce heterogeneous timing of NF-kappaB oscillations between individual cells. We suggest that this dual-delayed negative feedback motif enables NF-kappaB signaling to generate robust single cell oscillations by reducing sensitivity to key parameter perturbations. Simultaneously, enhanced cell heterogeneity may represent a mechanism that controls the overall coordination and stability of cell population responses by decreasing temporal fluctuations of paracrine signaling. It has often been thought that dynamic biological systems may have evolved to maximize robustness through cell-to-cell coordination and homogeneity. Our analyses suggest in contrast, that this cellular variation might be advantageous and subject to evolutionary selection. Alternative types of therapy could perhaps be designed to modulate this cellular heterogeneity.

Dynamic organisation of prolactin gene expression in living pituitary tissue.

Gene expression in living cells is highly dynamic, but temporal patterns of gene expression in intact tissues are largely unknown. The mammalian pituitary gland comprises several intermingled cell types, organised as interdigitated networks that interact functionally to generate co-ordinated hormone secretion. Live-cell imaging was used to quantify patterns of reporter gene expression in dispersed lactotrophic cells or intact pituitary tissue from bacterial artificial chromosome (BAC) transgenic rats in which a large prolactin genomic fragment directed expression of luciferase or destabilised enhanced green fluorescent protein (d2EGFP). Prolactin promoter activity in transgenic pituitaries varied with time across different regions of the gland. Although amplitude of transcriptional responses differed, all regions of the gland displayed similar overall patterns of reporter gene expression over a 50-hour period, implying overall co-ordination of cellular behaviour. By contrast, enzymatically dispersed pituitary cell cultures showed unsynchronised fluctuations of promoter activity amongst different cells, suggesting that transcriptional patterns were constrained by tissue architecture. Short-term, high resolution, single cell analyses in prolactin-d2EGFP transgenic pituitary slice preparations showed varying transcriptional patterns with little correlation between adjacent cells. Together, these data suggest that pituitary tissue comprises a series of cell ensembles, which individually display a variety of patterns of short-term stochastic behaviour, but together yield long-range and long-term coordinated behaviour.

Physiological levels of TNFalpha stimulation induce stochastic dynamics of NF-kappaB responses in single living cells.

Nuclear factor kappa B (NF-kappaB) signalling is activated by cellular stress and inflammation and regulates cytokine expression. We applied single-cell imaging to investigate dynamic responses to different doses of tumour necrosis factor alpha (TNFalpha). Lower doses activated fewer cells and those responding showed an increasingly variable delay in the initial NF-kappaB nuclear translocation and associated IkappaBalpha degradation. Robust 100 minute nuclear:cytoplasmic NF-kappaB oscillations were observed over a wide range of TNFalpha concentrations. The result is supported by computational analyses, which identified a limit cycle in the system with a stable 100 minute period over a range of stimuli, and indicated no co-operativity in the pathway activation. These results suggest that a stochastic threshold controls functional all-or-nothing responses in individual cells. Deterministic and stochastic models simulated the experimentally observed activation threshold and gave rise to new predictions about the structure of the system and open the way for better mechanistic understanding of physiological TNFalpha activation of inflammatory responses in cells and tissues.

Calcium dynamics and chromatin remodelling underlie heterogeneity in prolactin transcription.

Pituitary cells have been reported to show spontaneous calcium oscillations and dynamic transcription cycles. To study both processes in the same living cell in real time, we used rat pituitary GH3 cells stably expressing human prolactin-luciferase or prolactin-EGFP reporter gene constructs loaded with a fluorescent calcium indicator and measured activity using single-cell time-lapse microscopy. We observed heterogeneity between clonal cells in the calcium activity and prolactin transcription in unstimulated conditions. There was a significant correlation between cells displaying spontaneous calcium spikes and cells showing spontaneous bursts in prolactin expression. Notably, cells showing no basal calcium activity showed low prolactin expression but elicited a significantly greater transcriptional response to BayK8644 compared to cells showing basal calcium activity. This suggested the presence of two subsets of cells within the population at any one time. Fluorescence-activated cell sorting was used to sort cells into two populations based on the expression level of prolactin-EGFP however, the bimodal pattern of expression was restored within 26 h. Chromatin immunoprecipitation showed that these sorted populations were distinct due to the extent of histone acetylation. We suggest that maintenance of a heterogeneous bimodal population is a fundamental characteristic of this cell type and that calcium activation and histone acetylation, at least in part, drive prolactin transcriptional competence.

Transcription Factor Pit-1 Affects Transcriptional Timing in the Dual-Promoter Human Prolactin Gene.

Gene transcription occurs in short bursts interspersed with silent periods, and these kinetics can be altered by promoter structure. The effect of alternate promoter architecture on transcription bursting is not known. We studied the human prolactin (hPRL) gene that contains 2 promoters, a pituitary-specific promoter that requires the transcription factor Pit-1 and displays dramatic transcriptional bursting activity and an alternate upstream promoter that is active in nonpituitary tissues. We studied large hPRL genomic fragments with luciferase reporters, and used bacterial artificial chromosome recombineering to manipulate critical promoter regions. Stochastic switch mathematical modelling of single-cell time-lapse luminescence image data revealed that the Pit-1-dependent promoter showed longer, higher-amplitude transcriptional bursts. Knockdown studies confirmed that the presence of Pit-1 stabilized and prolonged periods of active transcription. Pit-1 therefore plays an active role in establishing the timing of transcription cycles, in addition to its cell-specific functions.

Real-time visualization of human prolactin alternate promoter usage in vivo using a double-transgenic rat model.

We have generated a humanized double-reporter transgenic rat for whole-body in vivo imaging of endocrine gene expression, using the human prolactin (PRL) gene locus as a physiologically important endocrine model system. The approach combines the advantages of bacterial artificial chromosome recombineering to report appropriate regulation of gene expression by distant elements, with double reporter activity for the study of highly dynamic promoter regulation in vivo and ex vivo. We show first that this rat transgenic model allows quantitative in vivo imaging of gene expression in the pituitary gland, allowing the study of pulsatile dynamic activity of the PRL promoter in normal endocrine cells in different physiological states. Using the dual reporters in combination, dramatic and unexpected changes in PRL expression were observed after inflammatory challenge. Expression of PRL was shown by RT-PCR to be driven by activation of the alternative upstream extrapituitary promoter and flow cytometry analysis pointed at diverse immune cells expressing the reporter gene. These studies demonstrate the effective use of this type of model for molecular physiology and illustrate the potential for providing novel insight into human gene expression using a heterologous system.

Bayesian inference of biochemical kinetic parameters using the linear noise approximation.

BACKGROUND: Fluorescent and luminescent gene reporters allow us to dynamically quantify changes in molecular species concentration over time on the single cell level. The mathematical modeling of their interaction through multivariate dynamical models requires the development of effective statistical methods to calibrate such models against available data. Given the prevalence of stochasticity and noise in biochemical systems inference for stochastic models is of special interest. In this paper we present a simple and computationally efficient algorithm for the estimation of biochemical kinetic parameters from gene reporter data. RESULTS: We use the linear noise approximation to model biochemical reactions through a stochastic dynamic model which essentially approximates a diffusion model by an ordinary differential equation model with an appropriately defined noise process. An explicit formula for the likelihood function can be derived allowing for computationally efficient parameter estimation. The proposed algorithm is embedded in a Bayesian framework and inference is performed using Markov chain Monte Carlo. CONCLUSION: The major advantage of the method is that in contrast to the more established diffusion approximation based methods the computationally costly methods of data augmentation are not necessary. Our approach also allows for unobserved variables and measurement error. The application of the method to both simulated and experimental data shows that the proposed methodology provides a useful alternative to diffusion approximation based methods.

Reconstruction of transcriptional dynamics from gene reporter data using differential equations.

MOTIVATION: Promoter-driven reporter genes, notably luciferase and green fluorescent protein, provide a tool for the generation of a vast array of time-course data sets from living cells and organisms. The aim of this study is to introduce a modeling framework based on stochastic differential equations (SDEs) and ordinary differential equations (ODEs) that addresses the problem of reconstructing transcription time-course profiles and associated degradation rates. The dynamical model is embedded into a Bayesian framework and inference is performed using Markov chain Monte Carlo algorithms. RESULTS: We present three case studies where the methodology is used to reconstruct unobserved transcription profiles and to estimate associated degradation rates. We discuss advantages and limits of fitting either SDEs ODEs and address the problem of parameter identifiability when model variables are unobserved. We also suggest functional forms, such as on/off switches and stimulus response functions to model transcriptional dynamics and present results of fitting these to experimental data.

Spatio-temporal protein dynamics in single living cells.

The development and application of single cell optical imaging has identified dynamic and oscillatory signalling processes in individual cells. This requires single cell analyses since the processes may otherwise be masked by the population average. These oscillations range in timing from seconds/minutes (e.g. calcium) to minutes/hours (e.g. NF-kappaB, Notch/Wnt and p53) and hours/days (e.g. circadian clock and cell cycle). Quantitative live cell measurement of the protein processes underlying these complex networks will allow characterisation of the core mechanisms that drive these signalling pathways and control cell function. Ultimately, such studies can be applied to develop predictive models of whole tissues and organisms.

Asymmetry between Activation and Deactivation during a Transcriptional Pulse.

Transcription in eukaryotic cells occurs in gene-specific bursts or pulses of activity. Recent studies identified a spectrum of transcriptionally active "on-states," interspersed with periods of inactivity, but these "off-states" and the process of transcriptional deactivation are poorly understood. To examine what occurs during deactivation, we investigate the dynamics of switching between variable rates. We measured live single-cell expression of luciferase reporters from human growth hormone or human prolactin promoters in a pituitary cell line. Subsequently, we applied a statistical variable-rate model of transcription, validated by single-molecule FISH, to estimate switching between transcriptional rates. Under the assumption that transcription can switch to any rate at any time, we found that transcriptional activation occurs predominantly as a single switch, whereas deactivation occurs with graded, stepwise decreases in transcription rate. Experimentally altering cAMP signalling with forskolin or chromatin remodelling with histone deacetylase inhibitor modifies the duration of defined transcriptional states. Our findings reveal transcriptional activation and deactivation as mechanistically independent, asymmetrical processes.

Tumor necrosis factor-alpha activates the human prolactin gene promoter via nuclear factor-kappaB signaling.

Pituitary function has been shown to be regulated by an increasing number of intrapituitary factors, including cytokines. Here we show that the important cytokine TNF-alpha activates prolactin gene transcription in pituitary GH3 cells stably expressing luciferase under control of 5 kb of the human prolactin promoter. Similar regulation of the endogenous rat prolactin gene by TNF-alpha in GH3 cells was confirmed using real-time PCR. Luminescence microscopy revealed heterogeneous dynamic response patterns of promoter activity in individual cells. In GH3 cells treated with TNF-alpha, Western blot analysis showed rapid inhibitory protein kappaB (IkappaBalpha) degradation and phosphorylation of p65. Confocal microscopy of cells expressing fluorescence-labeled p65 and IkappaBalpha fusion proteins showed transient cytoplasmic-nuclear translocation and subsequent oscillations in p65 localization and confirmed IkappaBalpha degradation. This was associated with increased nuclear factor kappaB (NF-kappaB)-mediated transcription from an NF-kappaB-responsive luciferase reporter construct. Disruption of NF-kappaB signaling by expression of dominant-negative variants of IkappaB kinases or truncated IkappaBalpha abolished TNF-alpha activation of the prolactin promoter, suggesting that this effect was mediated by NF-kappaB. TNF-alpha signaling was found to interact with other endocrine signals to regulate prolactin gene expression and is likely to be a major paracrine modulator of lactotroph function.

Dynamic NF-κB and E2F interactions control the priority and timing of inflammatory signalling and cell proliferation.

Dynamic cellular systems reprogram gene expression to ensure appropriate cellular fate responses to specific extracellular cues. Here we demonstrate that the dynamics of Nuclear Factor kappa B (NF-κB) signalling and the cell cycle are prioritised differently depending on the timing of an inflammatory signal. Using iterative experimental and computational analyses, we show physical and functional interactions between NF-κB and the E2 Factor 1 (E2F-1) and E2 Factor 4 (E2F-4) cell cycle regulators. These interactions modulate the NF-κB response. In S-phase, the NF-κB response was delayed or repressed, while cell cycle progression was unimpeded. By contrast, activation of NF-κB at the G1/S boundary resulted in a longer cell cycle and more synchronous initial NF-κB responses between cells. These data identify new mechanisms by which the cellular response to stress is differentially controlled at different stages of the cell cycle.

Signal transduction controls heterogeneous NF-κB dynamics and target gene expression through cytokine-specific refractory states.

Cells respond dynamically to pulsatile cytokine stimulation. Here we report that single, or well-spaced pulses of TNFα (>100 min apart) give a high probability of NF-κB activation. However, fewer cells respond to shorter pulse intervals (<100 min) suggesting a heterogeneous refractory state. This refractory state is established in the signal transduction network downstream of TNFR and upstream of IKK, and depends on the level of the NF-κB system negative feedback protein A20. If a second pulse within the refractory phase is IL-1ß instead of TNFα, all of the cells respond. This suggests a mechanism by which two cytokines can synergistically activate an inflammatory response. Gene expression analyses show strong correlation between the cellular dynamic response and NF-κB-dependent target gene activation. These data suggest that refractory states in the NF-κB system constitute an inherent design motif of the inflammatory response and we suggest that this may avoid harmful homogenous cellular activation.

Peritonitis activates transcription of the human prolactin locus in myeloid cells in a humanized transgenic rat model.

Prolactin (PRL) is mainly expressed in the pituitary in rodents, whereas in humans, expression is observed in many extrapituitary sites, including lymphocytes. Due to the lack of adequate experimental models, the function of locally produced PRL in the immune system is largely unknown. Using transgenic rats that express luciferase under the control of extensive human PRL regulatory regions, we characterized immune cell responses to thioglycollate (TG)-induced peritonitis. Resident populations of myeloid cells in the peritoneal cavity of untreated rats expressed barely detectable levels of luciferase. In contrast, during TG-induced peritonitis, cell-specific expression in both neutrophils and monocytes/macrophages in peritoneal exudates increased dramatically. Elevated luciferase expression was also detectable in peripheral blood and bone marrow CD11b(+) cells. Ex vivo stimulation of primary myeloid cells showed activation of the human extrapituitary promoter by TNF-α, lipopolysaccharide, or TG. These findings were confirmed in human peripheral blood monocytes, showing that the transgenic rat provided a faithful model for the human gene. Thus, the resolution of an inflammatory response is associated with dramatic activation of the PRL gene promoter in the myeloid lineage.