Karen Featherstone

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.

Plasma Bile Acids Are Associated with Energy Expenditure and Thyroid Function in Humans

BACKGROUND/AIMS Animal studies implicate a role of bile acids (BA) in thyroid-regulated energy expenditure (EE) via activation of the TGR-5/adenylate cyclase/deiodinase type 2 pathway. Here we investigated these possible associations in humans. METHODS EE, BA, and thyroid hormone status were assessed in 10 healthy subjects and eight patients with liver cirrhosis at baseline and after oral nutrition. In cirrhosis, blood was additionally sampled from the mesenteric vein and the radial artery. RESULTS At baseline, BA and EE related positively (r = 0.648, P = 0.048 in healthy subjects; r = 0.833, P = 0.010 in cirrhosis; r = 0.556, P =0.017 in all), with the highest correlation with deoxycholic acid levels. The respiratory quotient associated negatively to baseline BA (all, r = -0.639, P = 0.004). Postprandially, serum TSH decreased in both groups (P < 0.05 each). In cirrhosis, the decrease of TSH after 60 min correlated to the meal-stimulated BA increase (r = -0.762, P = 0.028). To assess the mechanism involved, we studied a single human TSHoma and TαT1 mouse thyrotrope cells. In TSHoma cells, TGR-5 was predominantly expressed cytoplasmically, and in vitro stimulation with BA did not substantially alter cAMP or deiodinase type 2. CONCLUSIONS Our data support a role of BA in human energy metabolism and in thyroid hormone control. Even though no convincing response to BA was demonstrated in TSHoma and TαT1 cells, the TSH decrease after a nutritional challenge suggests an interaction of BA on the set point of the thyroid axis.

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.

Spatially coordinated dynamic gene transcription in living pituitary tissue

Transcription at individual genes in single cells is often pulsatile and stochastic. A key question emerges regarding how this behaviour contributes to tissue phenotype, but it has been a challenge to quantitatively analyse this in living cells over time, as opposed to studying snap-shots of gene expression state. We have used imaging of reporter gene expression to track transcription in living pituitary tissue. We integrated live-cell imaging data with statistical modelling for quantitative real-time estimation of the timing of switching between transcriptional states across a whole tissue. Multiple levels of transcription rate were identified, indicating that gene expression is not a simple binary ‘on-off’ process. Immature tissue displayed shorter durations of high-expressing states than the adult. In adult pituitary tissue, direct cell contacts involving gap junctions allowed local spatial coordination of prolactin gene expression. Our findings identify how heterogeneous transcriptional dynamics of single cells may contribute to overall tissue behaviour. DOI: http://dx.doi.org/10.7554/eLife.08494.001

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 β-catenin. Expression of β-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 β-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 Ca2+ 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 β-catenin-independent signaling pathways.

A stochastic transcriptional switch model for single cell imaging data

Gene expression is made up of inherently stochastic processes within single cells and can be modeled through stochastic reaction networks (SRNs). In particular, SRNs capture the features of intrinsic variability arising from intracellular biochemical processes. We extend current models for gene expression to allow the transcriptional process within an SRN to follow a random step or switch function which may be estimated using reversible jump Markov chain Monte Carlo (MCMC). This stochastic switch model provides a generic framework to capture many different dynamic features observed in single cell gene expression. Inference for such SRNs is challenging due to the intractability of the transition densities. We derive a model-specific birth–death approximation and study its use for inference in comparison with the linear noise approximation where both approximations are considered within the unifying framework of state-space models. The methodology is applied to synthetic as well as experimental single cell imaging data measuring expression of the human prolactin gene in pituitary cells.

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.

Asymmetry between activation and deactivation during a transcriptional pulse

Summary 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.

E18_5 Pituitary Data1

GFP fluorescence measured from single cells in embryonic day18.5 pituitary tissue and subsequent modelling of transcription activity using a stochastic switch model.

Adult Pituitary Trypsin Treated Data2

GFP fluorescence measured from single cells in adult pituitary tissue treated with trypsin for 2hrs prior to confocal imaging. Compare to Adult Pituitary Trypsin Untreated Data2.