Real-time imaging of gene promoter activity using an adenoviral reporter construct demonstrates transcriptional dynamics in normal anterior pituitary cells

A model of gene expression based on random dynamical systems reveals modularity properties of gene regulatory networks

Here we propose a new approach to modeling gene expression based on the theory of random dynamical systems (RDS) that provides a general coupling prescription between the nodes of any given regulatory network given the dynamics of each node is modeled by a RDS. The main virtues of this approach are the following: (i) it provides a natural way to obtain arbitrarily large networks by coupling together simple basic pieces, thus revealing the modularity of regulatory networks; (ii) the assumptions about the stochastic processes used in the modeling are fairly general, in the sense that the only requirement is stationarity; (iii) there is a well developed mathematical theory, which is a blend of smooth dynamical systems theory, ergodic theory and stochastic analysis that allows one to extract relevant dynamical and statistical information without solving the system; (iv) one may obtain the classical rate equations form the corresponding stochastic version by averaging the dynamic random variables (small noise limit). It is important to emphasize that unlike the deterministic case, where coupling two equations is a trivial matter, coupling two RDS is non-trivial, specially in our case, where the coupling is performed between a state variable of one gene and the switching stochastic process of another gene and, hence, it is not a priori true that the resulting coupled system will satisfy the definition of a random dynamical system. We shall provide the necessary arguments that ensure that our coupling prescription does indeed furnish a coupled regulatory network of random dynamical systems. Finally, the fact that classical rate equations are the small noise limit of our stochastic model ensures that any validation or prediction made on the basis of the classical theory is also a validation or prediction of our model. We illustrate our framework with some simple examples of single-gene system and network motifs.

MR molecular imaging of tumours using ferritin heavy chain reporter gene expression mediated by the hTERT promoter

Objectives

Using the human telomerase reverse transcriptase (hTERT) promoter and the modified ferritin heavy chain (Fth) reporter gene, reporter gene expression for MRI was examined in telomerase positive and negative tumour cells and xenografts.

Methods

Activity of the reporter gene expression vector Lenti-hTERT-Fth1-3FLAG-Puro was compared to constitutive CMV-driven expression and to the untransfected parental control in five tumour cell lines: A549, SKOV3, 293T, U2OS and HPDLF. In vitro, transfected cells were evaluated for FLAG-tagged protein expression, iron accumulation and transverse relaxation. In vivo, tumours transduced by lentiviral vector injection were imaged using T2*WI. Changes in tumour signal intensity were validated by histology.

Results

Only telomerase positive tumour cells expressed FLAG-tagged Fth and displayed an increase in R2* above the parental control, with a corresponding change in T2*WI. In addition, only telomerase positive tumours, transduced by injection of the reporter gene expression construct, exhibited a change in signal intensity on T2*WI. Tumour histology verified the expression of FLAG-tagged Fth and iron accumulation in telomerase positive tissue.

Conclusion

Reporter gene expression for MRI, using the Fth reporter and the hTERT promoter, may be a useful strategy for the non-invasive diagnosis of many types of cancer.

Key points

• Modified heavy chain of ferritin can serve as an MR reporter gene

• hTERT promoter can direct the expression of reporter gene in cancer cells

• MR reporter imaging mediated by hTERT promoter can be used for cancer diagnosis

Role of Estrogen Response Element in the Human Prolactin Gene: Transcriptional Response and Timing

The use of bacterial artificial chromosome (BAC) reporter constructs in molecular physiology enables the inclusion of large sections of flanking DNA, likely to contain regulatory elements and enhancers regions that contribute to the transcriptional output of a gene. Using BAC recombineering, we have manipulated a 160-kb human prolactin luciferase (hPRL-Luc) BAC construct and mutated the previously defined proximal estrogen response element (ERE) located -1189 bp relative to the transcription start site, to assess its involvement in the estrogen responsiveness of the entire hPRL locus. We found that GH3 cell lines stably expressing Luc under control of the ERE-mutated hPRL promoter (ERE-Mut) displayed a dramatically reduced transcriptional response to 17β-estradiol (E2) treatment compared with cells expressing Luc from the wild-type (WT) ERE hPRL-Luc promoter (ERE-WT). The -1189 ERE controls not only the response to E2 treatment but also the acute transcriptional response to TNFα, which was abolished in ERE-Mut cells. ERE-WT cells displayed a biphasic transcriptional response after TNFα treatment, the acute phase of which was blocked after treatment with the estrogen receptor antagonist 4-hydroxy-tamoxifen. Unexpectedly, we show the oscillatory characteristics of hPRL promoter activity in individual living cells were unaffected by disruption of this crucial response element, real-time bioluminescence imaging showed that transcription cycles were maintained, with similar cycle lengths, in ERE-WT and ERE-Mut cells. These data suggest the -1189 ERE is the dominant response element involved in the hPRL transcriptional response to both E2 and TNFα and, crucially, that cycles of hPRL promoter activity are independent of estrogen receptor binding.

New researches and application progress of commonly used optical molecular imaging technology

Optical molecular imaging, a new medical imaging technique, is developed based on genomics, proteomics and modern optical imaging technique, characterized by non-invasiveness, non-radiativity, high cost-effectiveness, high resolution, high sensitivity and simple operation in comparison with conventional imaging modalities. Currently, it has become one of the most widely used molecular imaging techniques and has been applied in gene expression regulation and activity detection, biological development and cytological detection, drug research and development, pathogenesis research, pharmaceutical effect evaluation and therapeutic effect evaluation, and so forth, This paper will review the latest researches and application progresses of commonly used optical molecular imaging techniques such as bioluminescence imaging and fluorescence molecular imaging.

The prolactin gene: a paradigm of tissue-specific gene regulation with complex temporal transcription dynamics

Transcription of numerous mammalian genes is highly pulsatile, with bursts of expression occurring with variable duration and frequency. The presence of this stochastic or 'noisy' expression pattern has been relatively unexplored in tissue systems. The prolactin gene provides a model of tissue-specific gene regulation resulting in pulsatile transcription dynamics in both cell lines and endocrine tissues. In most cell culture models, prolactin transcription appears to be highly variable between cells, with differences in transcription pulse duration and frequency. This apparently stochastic transcription is constrained by a transcriptional refractory period, which may be related to cycles of chromatin remodelling. We propose that prolactin transcription dynamics result from the summation of oscillatory cellular inputs and by regulation through chromatin remodelling cycles. Observations of transcription dynamics in cells within pituitary tissue show reduced transcriptional heterogeneity and can be grouped into a small number of distinct patterns. Thus, it appears that the tissue environment is able to reduce transcriptional noise to enable coordinated tissue responses to environmental change. We review the current knowledge on the complex tissue-specific regulation of the prolactin gene in pituitary and extra-pituitary sites, highlighting differences between humans and rodent experimental animal models. Within this context, we describe the transcription dynamics of prolactin gene expression and how this may relate to specific processes occurring within the cell.

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.

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.

Circadian timekeeping and multiple timescale neuroendocrine rhythms

The hormones secreted by the anterior pituitary gland regulate major functions such as reproduction, as well as body growth and metabolism. Their efficiency of action highly depends on their temporal profile of release in the blood stream. This review summarises the recent evidence suggesting that the circadian clock genes that pace our daily rhythms may also contribute to the regulation of pituitary pulsatility, even in the non 24-h range. This inter-relation between molecular circadian oscillators and endocrine rhythmicities is discussed in light of the longstanding literature that has considered the involvement of the central circadian pacemaker located within the suprachiasmatic nuclei. Other arguments that suggest a role for circadian clock genes outside the suprachiasmatic nuclei are also presented, with a special emphasis on endocrine pituitary cells and hypothalamic neuroendocrine neurones that directly pace pituitary secretion rates.

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.

Single live-cell imaging for systems biology

Understanding how mammalian cells function requires a dynamic perspective. However, owing to the complexity of signalling networks, these non-linear systems can easily elude human intuition. The central aim of systems biology is to improve our understanding of the temporal complexity of cell signalling pathways, using a combination of experimental and computational approaches. Live-cell imaging and computational modelling are compatible techniques which allow quantitative analysis of cell signalling pathway dynamics. Non-invasive imaging techniques, based on the use of various luciferases and fluorescent proteins, trace cellular events such as gene expression, protein-protein interactions and protein localization in cells. By employing a number of markers in a single assay, multiple parameters can be measured simultaneously in the same cell. Following acquisition using specialized microscopy, analysis of multi-parameter time-lapse images facilitates the identification of important qualitative and quantitative relationships-linking intracellular signalling, gene expression and cell fate.

A physiological model of a circannual oscillator

Recent evidence based on studies in hypothalamo-pituitary disconnected Soay sheep suggests that the generation of circannual rhythms may be local to specific tissues or physiological systems. Now, the authors present a physiological model of a circannual rhythm generator centered in the pituitary gland based on the interaction between melatonin-responsive cells in the pars tuberalis that act to decode photoperiod, and lactotroph cells of the adjacent pars distalis that secrete prolactin. The model produces a self-sustained, circannual rhythm in endocrine output that the authors explore by mathematical modeling. The circannual oscillation requires a delayed negative feedback mechanism. The authors highlight specific features of the pituitary dynamics as a guide to future research on circannual rhythms.

Deterministic and stochastic models of NFkappaB pathway

In the article, we discuss the state of art and perspectives in deterministic and stochastic models of NFkappaB regulatory module. The NFkappaB is a transcription factor controlling various immune responses including inflammation and apoptosis. It is tightly regulated by at least two negative feedback loops involving IkappaBalpha and A20. This mode of regulation results in nucleus-to-cytoplasm oscillations in NFkappaB localization, which induce subsequent waves of NFkappaB responsive genes. Single cell experiments carried by several groups provided comprehensive evidence that stochastic effects play an important role in NFkappaB regulation. From modeling point of view, living cells might be considered noisy or stochastic biochemical reactors. In eukaryotic cells, in which the number of protein or mRNA molecules is relatively large, stochastic effects primarily originate in regulation of gene activity. Transcriptional activity of a gene can be initiated by trans-activator molecules binding to the specific regulatory site(s) in the target gene. The stochastic event of gene activation is amplified by transcription and translation, since it results in a burst of mRNA molecules, and each copy of mRNA then serves as a template for numerous protein molecules. Another potential source of variability can be receptors activation. At low-dose stimulation, important in cell-to-cell signaling, the number of active receptors can be low enough to introduce substantial noise to downstream signaling. Stochastic modeling confirms the large variability in cell responses and shows that no cell behaves like an "average" cell. This high cell-to-cell variability can be one of the weapons of the immune defense. Such non-deterministic defense may be harder to overcome by relatively simple programs coded in viruses and other pathogens.

Modeling stochasticity in gene regulation: characterization in the terms of the underlying distribution function

Intrinsic stochasticity plays an essential role in gene regulation because of a small number of involved molecules of DNA, mRNA and protein of a given species. To better understand this phenomenon, small gene regulatory systems are mathematically modeled as systems of coupled chemical reactions, but the existing exact description utilizing a Chapman-Kolmogorov equation or simulation algorithms is limited and inefficient. The present work considers a much more efficient yet accurate modeling approach, which allows analyzing stochasticity in the system in the terms of the underlying distribution function. We depart from the analysis of a single gene regulatory module to find that the mRNA and protein variance is decomposable into additive terms resulting from respective sources of stochasticity. This variance decomposition is asserted by constructing two approximations to the exact stochastic description: First, the continuous approximation, which considers only the stochasticity due to the intermittent gene activity. Second, the mixed approximation, which in addition attributes stochasticity to the mRNA transcription/decay process. Considered approximations yield systems of first order partial differential equations for the underlying distribution function, which can be efficiently solved using developed numerical methods. Single cell simulations and numerical two-dimensional mRNA-protein stationary distribution functions are presented to confirm accuracy of approximating models.

An adenoviral vector for probing promoter activity in primary immune cells

Functional analysis of the DNA regulatory regions that control gene expression has largely been performed through transient transfection of promoter-reporter constructs into transformed cells. However, transformed cells are often poor models of primary cells. To directly analyze DNA regulatory regions in primary cells, we generated a novel adenoviral luciferase reporter vector, pShuttle-luciferase-GFP (pSLUG) that contains a promoterless luciferase cassette (with an upstream cloning site) for probing promoter activity, and a GFP expression cassette that allows for the identification of transduced cells. Recombinant adenoviruses generated from this vector can transduce a wide range of primary immune cells with high efficiency, including human macrophages, dendritic cells and T cells; and mouse T cells transgenic for the coxsackie and adenoviral receptor (CAR). In primary T cells, we show inducible nuclear factor of activated T cells (NF-AT) activity using a recombinant pSLUG adenovirus containing a consensus NF-AT promoter. We further show inducible IL-12/23 p40 promoter activity in primary macrophages and dendritic cells using a recombinant pSLUG adenovirus containing the proximal human IL-12/23 p40 promoter. The pSLUG system promises to be a powerful tool for the analysis of DNA regulatory regions in diverse types of primary immune cells.

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.

Transcriptional stochasticity in gene expression

Due to the small number of copies of molecular species involved, such as DNA, mRNA and regulatory proteins, gene expression is a stochastic phenomenon. In eukaryotic cells, the stochastic effects primarily originate in regulation of gene activity. Transcription can be initiated by a single transcription factor binding to a specific regulatory site in the target gene. Stochasticity of transcription factor binding and dissociation is then amplified by transcription and translation, since target gene activation results in a burst of mRNA molecules, and each mRNA copy serves as a template for translating numerous protein molecules. In the present paper, we explore a mathematical approach to stochastic modeling. In this approach, the ordinary differential equations with a stochastic component for mRNA and protein levels in a single cells yield a system of first-order partial differential equations (PDEs) for two-dimensional probability density functions (pdf). We consider the following examples: Regulation of a single auto-repressing gene, and regulation of a system of two mutual repressors and of an activator-repressor system. The resulting PDEs are approximated by a system of many ordinary equations, which are then numerically solved.

Bioluminescence imaging in living organisms

Luciferase enzymes catalyze the emission of light from a substrate -- a phenomenon known as bioluminescence -- and have been employed as reporters of many biological functions. Luminescent reporters are much dimmer than fluorescent reporters, and therefore provide relatively modest spatial and temporal resolution. Yet, they are generally more sensitive and less toxic, making them particularly useful for long-term longitudinal studies of living cells, tissues and whole animals. Bioluminescence imaging has proven useful for detecting protein-protein interactions, for tracking cells in vivo, and for monitoring the transcriptional and post-transcriptional regulation of specific genes. Recent applications have included longitudinal monitoring of tumor progression in vivo, and monitoring circadian rhythms with single-cell resolution.

Pulses of prolactin promoter activity depend on a noncanonical E-box that can bind the circadian proteins CLOCK and BMAL1

Recent findings from our laboratory and those of others demonstrated that prolactin gene expression (PRL-GE) oscillates in single living mammotropes, but little information is available on the molecular processes that contribute to this phenomenon. To elucidate the source of this activity, we generated a series of constructs containing decreasing lengths of the PRL promoter fused to a luciferase reporter gene. These constructs were injected into single cells and assayed for photonic activity. We found pulse activity with all plasmids tested, even with the smallest promoter fragment of 331 bp. Sequence analysis of this fragment identified two potential E-boxes (elements known to bind CLOCK and BMAL1 circadian proteins). Furthermore, RT-PCR of PRL cells (pituitary, MMQ, and GH(3)) revealed expression of clock and bmal1 as well as five other clock genes (per1, per2, cry1, cry2, and tim), suggesting that the circadian system may function in PRL cells. Next, we mutated the core sequences of both E-boxes within the 2.5-kb PRL promoter and found that only mutation of the E-box133 completely abolished PRL-GE pulses. EMSAs revealed that CLOCK and BMAL1 were able to bind to the E-box133 site in vitro. Our results demonstrate that PRL-GE pulses are dependent on a specific E-box binding site in the PRL promoter. Moreover, the indication that CLOCK/BMAL1 can bind to this site suggests that these circadian proteins, either alone or in conjunction with other factors, may regulate intermittent PRL promoter activity in mammotropes, perhaps by acting as a temporal switch for the on/off expression of PRL.