Dynamic Changes in Prolactin Promoter Activation in Individual Living Lactotrophic Cells

Takasuka, Naomi; White, Michael R. H.; Wood, Christopher D.; Robertson, W. R.; Davis, John R.

doi:10.1210/endo.139.3.5826

Cited by 71 publications

(28 citation statements)

References 13 publications

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“…The PT tissue was subsequently used in a coculture assay. Coculture assays used a rat pituitary (GH 3 ) cell line stably transfected with 5 kb of the human prolactin promoter coupled to the firefly luciferase gene (hPRL-Luc-GH 3 ), which has been characterized (23). hPRL-Luc-GH 3 cells were seeded in 24-well culture plates at a density of 5 ϫ 10 4 cells per well and cultured for 3 days in serum-free culture medium.…”

Section: Cell Culture and Assay Of Tuberalin Secretionmentioning

confidence: 99%

Evidence for an endogenous per1 ‐ and ICER ‐independent seasonal timer in the hamster pituitary gland

et al. 2003

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Most mammals use changing annual day-length cycles to regulate pineal melatonin secretion and thereby drive many physiological rhythms including reproduction, metabolism, immune function, and pelage. Prolonged exposure to short winter day lengths results in refractoriness, a spontaneous reversion to long-day physiological status. Despite its critical role in the timing of seasonal rhythms, refractoriness remains poorly understood. The aim of this study was therefore to describe cellular and molecular mechanisms driving the seasonal secretion of a key hormone, prolactin, in refractory Syrian hamsters. We used recently developed single cell hybridization and reporter assays to show that this process is initiated by timed reactivation of endocrine signaling from the pars tuberalis (PT) region of the pituitary gland, a well-defined melatonin target site, causing renewed activation of prolactin gene expression. This timed signaling is independent of per1 clock gene expression in the suprachiasmatic nuclei and PT and of melatonin secretion, which continue to track day length. Within the PT, there is also a continued short day-like profile of ICER expression, suggesting that the change in hormone secretion is independent of cAMP signaling. Our data thus identify the PT as a key anatomical structure involved in endogenous seasonal timing mechanisms, which breaks from prevailing day length-induced gene expression.

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Section: Cell Culture and Assay Of Tuberalin Secretionmentioning

confidence: 99%

Evidence for an endogenous per1 ‐ and ICER ‐independent seasonal timer in the hamster pituitary gland

et al. 2003

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“…They observed directly that the HIV-1-LTR and cytomegalovirus promoters shuttle on and off in individual cells. Subsequently, Takasuka et al 22 used the same approach to study the regulation of the prolactin promoter in individual cells from a cloned pituitary cell line. Again, a profound variation without obvious pattern was observed between individual cells responding to stimuli that activate promoter activity.…”

Section: The Digital Process Of Transcription Initiation Transcriptiomentioning

confidence: 99%

Probability in transcriptional regulation and its implications for leukocyte differentiation and inducible gene expression

Hume

2000

Blood

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The phenotype of individual hematopoietic cells, like all other differentiated mammalian cells, is determined by selective transcription of a subset of the genes encoded within the genome. This overview summarizes the recent evidence that transcriptional regulation at the level of individual cells is best described in terms of the regulation of the probability of transcription rather than the rate. In this model, heterogeneous gene expression among populations of cells arises by chance, and the degree of heterogeneity is a function of the stability of the mRNA and protein products of individual genes. The probabilistic nature of transcriptional regulation provides one explanation for stochastic phenomena, such as stem cell lineage commitment, and monoallelic expression of inducible genes, such as lymphokines and cytokines.

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“…The model proposed here is based on the assumption that the gene promoters, in the time-scale at the order of half-life of the mRNA, are not in a statistical equilibrium. This assumption is supported by a growing number of experiments on single-cell gene expression, showing cell-to-cell heterogeneity in mRNA levels, fluctuations of which are too large to be explained only by the effects of finiteness of number of mRNAs [64,65]. The analytical framework introduced here can be compared with experimental data, since it is possible to tabulate some measurable parameter values from data sets and identify common genetic regulatory elements in genes with similar noise behaviors.…”

Section: Discussionmentioning

confidence: 96%

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

Antoneli

Ferreira

Briones

2016

Mathematical Biosciences

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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.

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Dynamic Changes in Prolactin Promoter Activation in Individual Living Lactotrophic Cells

Cited by 71 publications

References 13 publications

Evidence for an endogenous per1 ‐ and ICER ‐independent seasonal timer in the hamster pituitary gland

Evidence for an endogenous per1 ‐ and ICER ‐independent seasonal timer in the hamster pituitary gland

Probability in transcriptional regulation and its implications for leukocyte differentiation and inducible gene expression

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

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