Dynamic Patterns of Growth Hormone Gene Transcription in Individual Living Pituitary Cells

A. J. Norris, J. A. Stirland, D. W. McFerran, Z. C. Seymour, D. G. Spiller, A. S. I. Loudon, M. R. H. White and J. R. E. Davis

Endocrine Sciences Research Group, Faculty of Medicine (A.J.N., D.W.M., J.R.E.D.), and School of Biological Sciences (J.A.S., A.S.I.L.), University of Manchester, Manchester M13 9PT, United Kingdom; and School of Biological Sciences (D.W.M., Z.C.S., D.G.S., M.R.H.W.), University of Liverpool, Liverpool L69 7ZB, United Kingdom

Address all correspondence and requests for reprints to: Dr. M. R. H. White, School of Biological Sciences, Life Sciences Building, University of Liverpool, Crown Street, Liverpool, L69 7ZB, United Kingdom. E-mail: mwhite{at}liv.ac.uk; or to Professor J. R. E. Davis, Endocrine Sciences Research Group, School of Medicine, University of Manchester, Stopford Building, Manchester M13 9PT, United Kingdom. E-mail: julian.davis{at}man.ac.uk.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Real-time imaging of the GH gene promoter linked to luciferase in living pituitary cells has revealed surprising heterogeneity and variety of dynamic patterns of gene expression. Cells treated with either forskolin or thyroid hormone generated a consistent and characteristic temporal response from cell populations, but detailed analysis of individual cells revealed different patterns. Approximately 25–26% of cells displayed no response, 25–33% of cells exhibited a sustained progressive rise in luciferase activity, and 41–50% showed a transient phasic, or oscillatory response, after given stimuli. In cells treated consecutively with the two stimuli, the population response to the second stimulus was augmented. Single-cell analysis revealed that this was partly due to an increased number of cells responding, but also that the prevalence of response patterns changed: cells that responded to an initial stimulus were more likely to respond subsequently in a progressive sustained manner. In conclusion, these studies have indicated that GH promoter activity in individual living pituitary cells is unstable and possibly stochastic, with dynamic variations from hour to hour. The prevalence of different temporal patterns of response to hormonal stimulation among a population of cells is altered by the endocrine history of those cells.


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
THE USE OF real-time imaging of bioluminescence as a measure of luciferase reporter gene activation has recently allowed the dynamics of transcription in living cells to be studied in real time (1, 2, 3, 4, 5, 6). The short half-life of firefly luciferase compared with previous markers of transcription activity such as mRNA analysis and the chloramphenicol acetyl transferase reporter gene has allowed surprisingly rapid changes in transcription rates to be observed in living individual cells. We and others have found that the apparently stable transcription rate in a population of pituitary cells represents the overall sum of dynamically variable patterns of promoter activity among the individual cells (7, 8, 9). The activity of the prolactin (PRL) promoter in single pituitary cells shows dramatic fluctuations from hour to hour in both resting and hormonally stimulated cells (8). Previous in situ hybridization and hemolytic plaque assay studies of GH production indicated that both mRNA accumulation and peptide production are heterogeneous among individual clonal pituitary somatotroph cells, some of which appeared to behave as high-producers, and others as lowproducers (10, 11, 12). Our data on the PRL promoter suggested that this transcriptional heterogeneity among pituitary cells is not a fixed phenomenon but is subject to dynamic variation, and occurs not only in clonal cell lines but also in normal pituitary cells microinjected with luciferase reporter genes (7). We have observed a similar result in primary pituitary cells using luciferase reporters in recombinant adenovirus vectors (our unpublished data).

Temporal patterns of hormone gene transcription in individual pituitary cells are known to be susceptible to modification by extracellular signals. For instance, cells cultured continuously in the presence of serum exhibit heterogeneous periodic fluctuations in activity among individual cells, with different subpopulations of cells displaying different periodicities (13). Cells exposed only to a brief pulse of serum, however, switched to a pattern of persistent synchronized, homogeneous oscillations in PRL promoter activity in nearly all cells among the overall population (13). These surprising data suggested that there is an underlying potential for endogenous rhythmicity in gene promoter activation, with an oscillatory transcriptional response to physiological signals that can be synchronized. Parallel independent studies have shown similar spontaneous periodic oscillations in PRL promoter activation in individual normal lactotroph cells, albeit with shorter periods (14).

Temporal control of pituitary GH secretion depends both on acute changes in peptide storage and release and also on changes in hormone synthesis that reflect transcriptional regulation by a variety of factors. The molecular mechanisms of GH transcriptional control are increasingly well understood, in terms of the structure and function of the GH gene promoter and the role of the far-upstream locus control region (15, 16). Here, we report the first detailed analysis of the temporal patterns of GH promoter activity in real time in living pituitary cells. We have found that GH gene transcription is unstable, and we have defined temporal patterns of transcriptional responses to cAMP and thyroid hormone (T3) stimulation. The prevalence of these different patterns within a population is altered by the endocrine history of the cells, and this implies that the transcriptional pattern of individual cells is plastic.


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Real-Time Transcriptional Responses of Human GH-luciferase (hGH-luc) Cells to Stimulation by Forskolin or T3
Rat pituitary GH3 cells were transfected with a hGH-luc plasmid in which the hGH promoter (-496/+1bp) directed expression of the firefly luciferase gene. A series of stably transfected cell lines was obtained after rounds of G418 selection and ring cloning. Twenty-six of 30 clones that were investigated by luminometry of bulk cell lysates showed significant responses to stimulation with forskolin, T3, and dexamethasone (results not shown). Results are presented from detailed real time imaging studies of luciferase reporter gene expression of one of these lines, hGH-luc-YX30, but similar results were obtained using additional clones.

GH promoter activity in hGH-luc-YX30 cells was increased by stimulation with forskolin, acting through the cAMP signaling pathway and by thyroid hormone (T3), acting through a nuclear hormone receptor, as shown by quantification of serial luminescence images from populations of cells treated for more than 20 h (Fig. 1Go). We have termed these "population response" data to distinguish them from results obtained from individual cell analysis. Cells responded to continuous forskolin treatment with a transient 1.5-fold increase in luciferase expression, falling to basal levels by 5 h, and remaining stable thereafter. Stimulation with T3, in contrast, produced a sustained induction of GH promoter activity lasting up to 24 h.



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Figure 1. Quantitation of Real-Time Imaging of a Population of Stably Transfected hGH-luc-YX30 Pituitary Cells to Stimulation with Forskolin or T3 (Population Response)

Clonal rat pituitary cells stably transfected with the hGH-luciferase reporter gene construct (YX30 cells) were cultured on cover slips on the microscope stage, and luciferin substrate was added 17 h before addition of stimulus. Forskolin (5 µM) or thyroid hormone (T3, 7.5 nM) was added at 0 h. Photon counts over the whole field of approximately 150 cells were collected over 30-min periods at hourly intervals for 24 h. Fold induction was calculated by dividing the actual count by the basal level at time zero, before stimulation. Forskolin stimulation produced a transient response, whereas T3 produced a sustained response. The figure shows data from 10 h after addition of luciferin by which time point stable baseline luciferase activity had been attained; error bars represent the SEM of three independent experiments.

 
Characterization of Individual Cell Transcriptional Responses
Although stimulation of hGH-luc cells with either forskolin or T3 generated clear responses from populations of cells, microscopic analysis of the responses of GH promoter activity in individual cells among the overall population revealed strikingly varied patterns. Three characteristic response profiles could be distinguished, as illustrated in Figs. 2Go and 3Go. Some cells displayed clearly detectable levels of luminescence, above the background levels of the imaging system at baseline, yet showed no response to stimulation; others displayed a gradual progressive increase in luciferase activity; and a third group of cells responded with brief phasic bursts of luciferase activity. To analyze these patterns of transcriptional response further, quantitative criteria were applied. Two parameters were used to define cell type: 1) the area under the curve (AUC) of the luminescence signal over time, and 2) the presence of significant peaks as determined by Cluster analysis (17). For the Cluster analysis, a peak response was defined as more than 12 photons/30 min integration (i.e. above normal background levels of {approx}4 photons/30 min plus 2 SD) above basal levels, to prevent detection of variation that reflected simply a variation in background activity. Thus nonresponsive cells were defined as having an AUC of less than 250 photon counts over 30 h of imaging, and no detectable peaks by Cluster analysis; progressive responses were defined as having an AUC of more than 350 photon counts over 30 h of imaging, and no more than one peak by Cluster analysis; phasic responses were defined by an AUC of less than 350 photons/30 h with two or more significant peaks by Cluster analysis (Figs. 2Go and 3Go). A combination of AUC and cluster analysis is necessary to define the dynamic phasic patterns detected using the real-time imaging protocols (Fig. 2Go). When responses of pituitary hGH-luc cells to T3 stimulation were categorized according to these criteria, approximately 26 ± 6.5% of cells were unresponsive, 33 ± 5.7% displayed sustained progressive responses, and 41 ± 9.3% displayed phasic responses (Fig. 4Go). This distribution in response phenotype remained constant in six individual experiments using T3 as the stimulus. In cells stimulated with forskolin, no response was seen in 25 ± 5.1%, progressive responses in 25 ± 7.2%, phasic responses in 50% ± 6.8% [n = 6 individual experiments, P < 0.001, {chi}2 analysis given the null hypothesis that T3 and forskolin generate the same distribution of patterns (Fig. 4Go)]. Stimulation with T3 produced a higher proportion of cells showing a progressive response; therefore, the difference in population response to T3 and forskolin may be explained by the different response patterns between individual cells within the population.



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Figure 2. Definition of Single-Cell Response Patterns

Three characteristic patterns in the cellular response were defined by analysis of the AUC and Cluster peak analysis (see Materials and Methods). AUC data were generated for cultured YX30 cells treated with either forskolin or T3, as shown in Fig. 1Go, and plotted against response profiles as defined in the text. Data represent photon counts from single cell areas, pooled from 150 cells per treatment, gathered from three replicate experiments. Boxes represent the interquartile range, the bold horizontal line represents the median, and the error bars represent the smallest and largest values. Outlying points appear as circles, i.e. points greater than 1.5 box lengths from the end of the box. Representative images of these data are shown in Fig. 3Go.

 


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Figure 3. Luminescence Images of hGH-luc Pituitary Cells to Illustrate Different Temporal Patterns of Response

Pituitary hGH-luc cells were incubated as before and treated with T3 for 24 h in the presence of 1 mM luciferin substrate. Panel A shows a bright-field image of cells with a luminescence image of the same cells in the presence of luciferin: three individual cell areas have been marked, and the same field of cells imaged at hourly intervals as before. Luminescence images are shown for 6–12 h, to indicate the response of the cells to T3 (7.5 nM) given at time 0 h. Panel B illustrates the three different patterns of individual cell response to T3, using the three highlighted cells as examples (enlargements inset), tracked during the experiment. The graphs show the photon counts obtained from these individual cell areas. The horizontal line on the graph represents background count for untreated cells, and the variance of the data is indicated by dotted lines (see Materials and Methods). The stars represent significant peaks as detected by the Cluster peak detection algorithm. Panel B1 shows a cell with no response, B2 shows a cell with a progressive response, and B3 shows a phasic response.

 


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Figure 4. Prevalence of Individual Cell Response Patterns

Pituitary hGH-luc YX30 cells were incubated with forskolin (5 µM) or T3 (7.5 nM) as shown in Figs. 1Go and 2Go, and the prevalence of different patterns among the individual cells is shown as a proportion of the total number of cells studied. Data represent the mean ± SD derived from pooled single-cell measurements from a total population of 150 individual cells in three separate experiments per treatment that gave similar results. A significant difference in the distribution of cell phenotype between forskolin and T3 treatment was observed on analysis by {chi}2 analysis (* represents P < 0.001).

 
Changing Patterns of Transcriptional Response by Consecutive Stimulation
We next investigated the contribution of individual cells to the overall response, and whether sequential stimulation by two consecutive signals might alter the recruitment of cells to a responsive population, or alter the nature or prevalence of different patterns of transcriptional response.

Population Responses
In establishing a consecutive stimulation protocol, hGH-luc cells were first treated with 5 µM forskolin for 8 h, transferred to control serum-free medium for 2 h, and then retreated with forskolin at the same concentration for an additional 20 h. Two distinct inductions in GH promoter activity were observed in the overall population of cells. Population responses to the second forskolin stimulus were similar (P = 0.06) in amplitude and duration to the first response (Fig. 5AGo). In the next series of experiments, cells were treated first with forskolin, followed by a second stimulation with T3 (Fig. 5BGo); the T3 response was significantly increased, compared with T3-stimulated cells that had not been pretreated with forskolin (T3 stimulus alone). This augmentation in response occurred even though the transient response to forskolin had apparently concluded. Reversal of the order of stimulation (initial stimulation by T3 followed by forskolin) produced a similar effect, with a significantly amplified rise in the population response to the second stimulus compared with cells that were not pretreated (Fig. 5CGo). T3 stimulation followed by a second T3 stimulus could not be performed as the response to T3 was sustained beyond the duration of the experiment and a doseresponse phenomenon could not be excluded.



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Figure 5. Effect of Consecutive Stimuli on Real-Time Transcriptional Responses in Living hGH-luc Pituitary Cells

A, Cells were incubated on the camera stage in the presence of luciferin (1 mM) for 15 h before stimulation experiments starting at 0 h. Forskolin (5 µM) was added from 0–8 h, the stimulus removed by medium change for 2 h, and stimulation repeated from 10–30 h. The amplitude of the second response was not statistically different from the first response (P = 0.06, independent sample t test). B, Using the same experimental protocol, cells were exposed first to forskolin (5 µM) (triangles), and then to T3 (7.5 nM) (diamonds). Even though the transient transcriptional response to initial forskolin exposure is completed by 8 h, there is an augmentation of the subsequent response to T3, compared with T3-stimulated cells that were not exposed to initial forskolin stimulation (squares) (P < 0.039, ANOVA). C, Using the same protocol as in panel B, but reversing the order of the two stimuli, a similar augmentation of response to forskolin is observed after T3 pre-treatment (triangles), compared with forskolin-stimulated cells without prior exposure to T3 (circles). Results are shown as means ± SD of luminescence data from three independent experiments for each treatment paradigm.

 
Patterns of Single Cell Transcriptional Responses: Recruitment of Responsive Cells
The individual cell luminescence responses within the overall populations were analyzed. Initial stimulation of hGH-luc cells by T3 alone generated significant responses (i.e. a 2-fold induction above baseline) in 51% of the cells; similarly, 50% of cells responded within 8 h to an initial stimulation by forskolin alone (Fig. 6Go). The proportion of cells responding to either T3 or forskolin was increased to approximately 80% when cells had been prestimulated, irrespective of the order of stimulation (P = 0.006). This indicates that the increase in the population response was facilitated by recruitment of cells to a responsive population, rather than purely a graded increase in transcription rate. In support of this idea, further analysis of cells treated with T3 alone revealed that of the 50% of cells judged to be initially nonresponsive (within 0–8 h after stimulation), a proportion went on to display late responses at 8–30 h in the presence of T3: 16% showed a delayed progressive response, and 33% a delayed phasic response, during the latter 8–30 h of observation.



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Figure 6. Recruitment of Cells to a Transcriptionally Responsive Population by Consecutive Stimulation

The percentage of individual hGH-luc cells displaying a significant transcriptional response to either forskolin or T3 was increased within the overall population by consecutive stimulation when compared with the responses to either single initial stimulus, using the experimental paradigm shown in Fig. 5Go. Results shown are mean ± SD of luminescence data from at least 50 cells from three independent experiments for each treatment sequence. A forskolin response here is defined by detection of a significant peak with Cluster detection algorithm; T3 response is defined by a 2-fold induction above basal stimulation. Significance was calculated using a paired t test. **, P = 0.006.

 
Temporal patterns of individual cellular transcriptional responses to the second stimulus were then analyzed according to whether or not they had displayed a response to the first stimulus. Patterns of hGH-luc transcriptional response were analyzed using the criteria for the progressive or phasic responses, as above. Among those cells exhibiting no response to the first stimulus, forskolin, similar proportions of cells displayed the three defined response patterns on subsequent T3 stimulation (no response, 25%; progressive response, 33%; phasic response, 41%). In contrast, those cells that did initially show a response to forskolin were more likely to respond to subsequent T3 treatment, and also more likely to display a progressive response to T3 (62% vs. 33%, P < 0.005; Fig. 7Go). These effects of consecutive stimulation were similar regardless of the order of the respective stimuli; thus, initial treatment with T3 had similar effects on subsequent patterns of response to forskolin, i.e. an increase in the number of progressive responders in those cells originally responsive to T3 (64% vs. 35%, P < 0.005, Fig. 7Go). The data from these consecutive stimulation experiments revealed that both the likelihood of a transcriptional response to a second stimulus, and the temporal nature of that response, were altered by responsiveness to the first stimulus, irrespective of the nature or order of that stimulus.



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Figure 7. Temporal Patterns of Single-Cell Responsiveness Depend on Responsiveness to Earlier Stimulation

Pituitary hGH-luc cells were treated with consecutive stimuli, as shown in Fig. 5Go, and results were analyzed to relate real-time patterns of transcriptional response in individual living cells to their overall responsiveness or nonresponsiveness to prior stimulation (as defined in Fig. 6Go). A, Cells treated with forskolin followed by T3. Upper panel shows cells that did not respond to the first stimulus (forskolin), and the temporal response profile of these cells (as defined in Fig. 3Go) on addition of a second stimulus (T3) is shown to the right. Similar proportions of cells displayed the three defined patterns of transcriptional response to the second stimulus. Lower panel, Cells that did respond to a first stimulus (forskolin) were more likely to respond in an ordered progressive manner (62 ± 4.4%) to the second stimulus (T3) compared with cells that did not respond to the first stimulus (33 ± 6.4%, **, P < 0.005) and were less likely to display no response. Data shown are mean ± SD, n = 3 independent experiments, derived from analyses of 150 individual cells. B, Cells treated with T3 followed by forskolin. Data are shown in the same format as panel A. Cells that responded to T3 were more likely to display a progressive response to forskolin (64 ± 2.5% vs. 35 ± 6.2%, **, P < 0.005).

 

    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
This study demonstrates, for the first time, dynamic patterns of hGH promoter activity over long periods in individual living pituitary cells. By using clonal stably transfected cell lines, we have been able to study the contribution of all of the cells within a given population. Our findings indicate widely differing patterns of GH gene expression among individual living cells in response to stimulation, with marked heterogeneity of responses within a clonal population. Furthermore, we have found that the prevalence of different temporal patterns of transcriptional activation depends on the previous history of responsiveness of the cells.

Use of microscopic luminescence imaging of luciferase reporter gene activity allows dynamic monitoring of transcription in real time in individual living pituitary cells. The short half-life of the luciferase reporter gene (50 min) compared with other markers such as chloramphenicol acetyl transferase or green fluorescent protein has allowed hour-to-hour variation in response to be documented. In situ hybridization studies first showed that subpopulations of cells can be low or high producers of pituitary hormones such as GH (12). Earlier studies using both stably transfected GH3 pituitary cell lines and microinjected normal pituitary cells have shown that transcription from the PRL promoter is unstable in individual cells, with rapid and unsynchronized fluctuations in gene expression from hour to hour (7, 8, 14).

In the present study, we have addressed the regulation of a related pituitary gene, GH, whose expression, like PRL, requires the Pit-1 transcription factor (15, 16). We focused our attention on temporal response patterns using two activators of transcription, one stimulating the cAMP signaling pathway, and the other acting via a nuclear hormone receptor. Regulation of GH expression depends on a complex interaction of intracellular signaling pathways. cAMP regulates GH production and is modulated in somatotrophic cells by dopamine, somatostatin, and GHRH. The cAMP signal pathway is thought to involve protein kinase A activation of various targets including Pit-1, cAMP response element binding protein (CREB), activating transcription factor 1, and CREB binding protein (18, 19, 20). T3 has been shown to be a strong activator of the rat GH promoter (21), although studies in rat pituitary GC cells suggested that the hGH promoter was negatively regulated by T3 (22, 23). In our studies using GH3 cells, significant stimulation of hGH promoter was achieved with T3. A stimulatory effect of T3 on hGH gene expression has been previously shown in a human pituitary cell line (24), and therefore hGH promoter regulation by T3 may be dependent on cell type. In addition, a study in nonpituitary cell lines showed important interaction between signal systems in that forskolin-dependent activation of the rat GH promoter with Pit-1 coexpression only occurred in the presence of the T3 receptor (25).

In our real-time analysis, population responses of GH promoter activity in pituitary cells to the two stimuli were slightly different, as forskolin stimulation generated a transient transcriptional response lasting about 5 h, whereas T3 stimulation produced a prolonged stable increase in reporter gene activity. However, these patterns concealed surprisingly different responses of individual cells within the overall population, which when quantified revealed that dynamic patterns of GH promoter activity in individual cells can be classified into three discernible categories, and that these patterns varied in different conditions. The consecutive stimulation paradigm showed that an initial stimulus augmented the transcriptional response to a second stimulation. This effect of the initial stimulus on the subsequent response could be observed even when an initial transient transcriptional response appeared to have terminated (see Fig. 5AGo). This augmentation appeared to be partly due to a significant increase in the number of responsive cells within the population, indicating a recruitment process, and implying that individual cells have a given probability of responding to a stimulus, which could be modified by initial priming. The nature of this phenomenon is unclear, and it is hard to distinguish priming from synergy between different signaling mechanisms. However, analysis of early and late responsiveness to T3 suggested that a proportion of initially unresponsive cells could display late responses with continuing presence of the stimulus. Thus, priming cells with an initial stimulus may allow changes in chromatin structure facilitating transcription factor access such that response to a second stimulus, or to prolonged stimulation, is enhanced by the presence of a stable transcription complex.

Quantitative analysis of the individual cell data obtained from the consecutive stimulation experiments also revealed differences in the prevalence of the three patterns of single-cell transcriptional response that we had defined. We studied this according to whether or not cells had responded to an initial stimulation: thus, of those cells that failed to respond to the first stimulation, similar proportions displayed each of the three patterns (no-response, progressive response, or phasic response). However, those cells that had responded to the first stimulation behaved differently, with a much higher percentage showing a progressive response, and fewer cells failing to respond or showing phasic responses. Thus, it appeared that an initial responsiveness increased the probability of a sustained progressive response pattern after a second stimulus. The mechanisms underlying these differences are not yet clear but are consistent with the recruitment hypothesis and some form of transcriptional priming, perhaps due to changes in chromatin structure.

Frawley et al. (26) first demonstrated real-time measurement of GH gene expression using luciferase reporter gene imaging in microinjected normal rat pituitary cells, although that early work did not report detailed longitudinal quantitative analysis. Similar heterogeneity and dynamic fluctuations in PRL promoter activity have been noted by the same group in microinjected pituitary cells and related to intracellular signaling (7, 14, 27). In addition, adenoviral transfection of luciferase reporter genes in primary cultures of normal pituitary cells has confirmed similar transcriptional patterns (our unpublished data). Therefore the transcriptional heterogeneity that we have described is observed in both cell lines and normal pituitary cells and probably represents inherent instability in the transcription complex, which can be observed using both integrated and episomal reporter constructs, and with both the GH and PRL genes. Stably transfected cell lines have the important advantage that a clonal population of genetically identical cells can be studied, with relatively low copy number of the target gene incorporated into the genome of each cell. Southern blot analysis of our pituitary GH3-based stable cell lines has indicated copy number of approximately 10 or less (our unpublished data). Our experience in using such cell lines has shown no evidence to suggest methylation or gene suppression in these cell lines up to 20 passages. In principle the insertion site of the construct in clonal cells may affect results, but in this work we found similar patterns in a second cell line (YX33), and since 87% of our clones responded to the stimuli, it is likely that T3 and cAMP responsiveness is itself independent of insertion site.

The fluctuations that we have observed in reporter gene expression in single cells are substantial and well above the basal level of the instrument and its natural variance. Thus, we believe that these signals are biologically significant and not artefacts of a barely detected low signal distribution. A possible source of variation that could give rise to natural deviations is photon shot noise, the uncertainty of photon arrival in a given time when there is a low signal. Since photon shot noise is estimated by the square root of the average signal, we believe that the phasic oscillations that we see lie significantly above this level (see Materials and Methods). In addition, our definition of phasic responses cannot be explained by a threshold effect of studying weak cell signals, as there was no significant difference in signal amplitude between the peaks of phasic and progressive responders. An example of this is shown in Fig. 3Go in which for both cells 2 and 3 the peak signal is approximately 80 photons from a 30-min integration.

Signal duration and pattern may be an important determinant of transcriptional regulation and may offer a mechanism facilitating both acute and longer-term responsiveness of endocrine cells to hormonal stimuli (13). The reason behind this phenomenon is not clear: efforts to relate intracellular signaling pathway activation to pituitary gene expression have so far relied on measurements of calcium concentration followed by sequential luciferase reporter gene expression (27), but future simultaneous measurements of both parameters, and of other signaling cascades such as cAMP-protein kinase A, would be valuable to discern the temporal relationships more clearly. Inherent instability in transcription complexes may facilitate rapid changes in transcription phenotype in individual cells (29, 30, 31). Recently, it has been recognized that recruitment and release of nuclear hormone receptors and coactivators to chromatin is a highly dynamic process (32, 33) that relates to transcription rate.

In principle, gene enhancers may increase either the probability of a single transcription unit being active: in a stochastic or binary model, genes are either on or off. Alternatively, they might alter the rate of gene transcription: in a rate or graded model, enhancers would modulate a continuous range of transcriptional activity (30, 34, 35). Either a stochastic or a graded function may be affected in different ways by changing patterns of hormonal stimuli. Important recent evidence from studies in yeast (36, 37) suggests that a given promoter can, in fact, adopt either binary or graded behavior according to the nature of the signal pathway, but the physiological function and significance of these phenomena in mammalian cells are unknown. In the case of pituitary hormone genes, the transcription of which changes both acutely and chronically in response to a range of physiological states and signals, our data indicate that the timing of external signals has important and previously unsuspected effects on transcriptional response. In summary, the data presented in this paper indicate the new information that can be obtained about behavior of individual cells within populations, using real-time quantitative reporter gene imaging. The timing and coordination of transcriptional responses to different signal duration may represent an important mechanism for endocrine regulation.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Cell Culture and Development of Stable Cell Lines
Rat pituitary GH3 cells were cotransfected with a hGH promoter (-496/+1) linked to a firefly luciferase reporter gene (38) (kindly supplied by Dr. P. A. Cattini, Manitoba, Canada), together with a pSV2-neo vector (kindly supplied by Dr. D. W. Ray, Manchester, UK). The nonliposomal transfection reagent FuGene 6 (Roche Molecular Biochemicals, Indianapolis, IN) was used under serum-free conditions. Cells were then grown in DMEM (containing phenol red) supplemented with 10% fetal calf serum (FCS) and pyruvate/glutamine (Life Technologies Inc., Paisley, UK). Neomycin-resistant, stable clones were selected and ring cloned using 400 µg/ml G418 (Life Technologies, Inc.). A series of cloned cell lines were isolated and then tested for responsiveness to stimuli including forskolin, T3, and dexamethasone (all from Sigma-Aldrich Corp. Ltd., Dorset, UK). Cell lysates were prepared and luciferase activity measured using a Berthold-Lumat LB9501 luminometer, and cell lines that demonstrated reproducible responses were selected for further microscopic study (data not shown). Cell lines hGH-luc-YX30 and hGH-luc-YX33 were both studied in detail. The results with YX30 are reported here, but the findings with YX33 were essentially similar. Cells were maintained in DMEM, containing 10% FCS, and 100 µg G418 for up to 15 wk with negligible decline in luciferase activity. Cells were therefore studied up to passage 18.

Imaging of Individual Living Pituitary Cells
hGH-Luc-YX30 (105) cells were seeded onto 35-mm cover slip dishes (MatTek Corp., Ashland, MA) and cultured in 10% FCS for 10 h before transfer to DMEM, plus 0.25% BSA medium (serum-free medium) for a further 24 h before imaging. Luciferin (final concentration, 1 mM; Bio-Synth, Inc., Staad, Switzerland) was added at the start of the experiment, and the cells were transferred to an Axiovert-135TV microscope (Carl Zeiss, Welwyn Garden City, UK). The heated stage was maintained at 37 C in a humidified chamber with 5% CO2-95% air in a completely darkened room. Bright field images to allow localization of the cells were taken using differential interference contrast. Luminescence images were obtained using a x10, 0.5 numerical aperture dry objective and captured using a photon counting charge coupled device camera (C2400-40, Hamamatsu Photonics, Enfield, UK). Sequential images were taken hourly, and each was integrated over 30 min. Slice images are used for pictorial display: these were generated using Hamamatsu Argus-50 photon counting software and processed using a 3 x 3 neighborhood matrix (weighted 2 for the central pixel and 1 for surrounding pixels) to provide a moving average over the image (Hamamatsu Photonics software). This smoothes the image by removing sharp changes and eliminates noise. Center-of-gravity images were used for quantification, and represent direct photon counts acquired over a field of cells (typically 100–200 cells) or over single-cell areas defined from the differential interference contrast bright field images. Hormonal stimulation of cells commenced 15 h after addition of luciferin by which time luciferase activity had fallen to a steady baseline (8, 13, 21). Forskolin and T3 were used at final concentrations of 5 µM and 7.5 nM (5 ng/ml), respectively, and a luciferin concentration of 1 mM was used throughout all experiments.

Data Analysis
Total photon counts for the whole population and individual cell areas were integrated over 30 min at hourly intervals. An individual cell area of 477 pixels was used for analysis. Data were analyzed using the Cluster peak detection algorithm (17) to detect significant peaks [>12 (background + 2 SD)] in luciferase activity and calculate the AUC.

A key issue in luminescence imaging studies is the need to minimize unnecessary background light and to carefully quantify the signal-noise levels from the cells. Background light in our system was removed by the use of a light-tight darkroom to house the microscope and camera. Other background noise arises from natural variation in the dark count recorded by the camera in the absence of any signal. The average dark count and the SD that corresponded to the dark count were recorded. This noise contribution was found to be the same either in the absence of cells, or in the absence of luciferin, or using cells not expressing luciferase (data not shown). For quantification of luminescence in these studies, the average instrument dark count (corrected for the number of pixels being used) was subtracted from the luminescence signal. This means that the recorded luminescence signal could then be directly related to the level of noise in the system. In cells emitting luminescence, there is another important source of noise, which is photon shot noise. This represents the uncertainty of photon arrival in a given time when there is a low signal, as discussed above. The variance of the data was calculated by the formula: variance = {surd}[(total count) + (SDbackground) (2), as described previously (8). The variance is shown by the dotted lines on individual cell profiles. Individual cellular transcriptional responses to stimulation over 30-h periods were categorized into three distinct groups to allow analysis, as described in Results. Further data analysis was performed with Excel and SPSS statistics package (SPSS, Inc., Chicago, IL), using independent sample t test, {chi}2 tests, and ANOVA.


    ACKNOWLEDGMENTS
 
We would like to record our gratitude for conversations with the late Dr. Steve Frawley, who pioneered the development of novel approaches to understanding gene expression and hormone secretion in living endocrine tissues. We also thank Dr. P. A. Cattini (Manitoba, Canada) for the GH-Luc plasmid, Dr. D. W. Ray (Manchester, UK) for advice and discussion, Hamamatsu Photonics (Welwyn Garden City, UK), and Carl Zeiss (Welwyn Garden City). Thanks also to Jo Soden (Manchester, UK) for her technical help, and to the two reviewers for their constructive criticism of the original manuscript.


    FOOTNOTES
 
This work was supported by the Wellcome Trust who provided a clinical fellowship (to A.J.N.); the University of Manchester School of Medicine Endowments Fund; the Biotechnology and Biological Sciences Research Council and Medical Research Council; and the Society for Endocrinology for a Prize Ph.D. studentship (to D.W.M.).

Abbreviations: AUC, Area under the curve; FCS, fetal calf serum; hGH, human GH; PRL, prolactin.

Received for publication June 10, 2002. Accepted for publication November 5, 2002.


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 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
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