Physiol Genomics 21: 14–33, 2005.
First published December 28, 2004; doi:10.1152/physiolgenomics.00099.2004.
Gene expression profiles in HEK-293 cells with low or high
store-operated calcium entry: can regulatory as well as
regulated genes be identified?
Tatiana K. Zagranichnaya, Xiaoyan Wu, Arpad M. Danos, and Mitchel L. Villereal
Department of Neurobiology, Pharmacology and Physiology, The University of Chicago, Chicago, Illinois
Submitted 23 April 2004; accepted in final form 22 December 2004
cDNA microarray; fluorescence-activated cell sorting analysis; thapsigargin; insulin receptor substrate-2; small interfering RNA; realtime PCR; canonical transient receptor potential protein-1
utilize Ca2⫹ as a second
messenger to initiate downstream physiological processes (4,
5, 8, 54). Activation of these receptors generally results in a
biphasic Ca2⫹ response involving an initial release of internal
Ca2⫹ stores, followed by Ca2⫹ entry through receptor-operated
or capacitative Ca2⫹ entry channels (43), also called storeoperated channels (SOCs). Although progress has been made
in identifying proteins that assemble to form SOCs, little is
known about the downstream physiological consequences of
Ca2⫹ entry via these channels. Recent studies have indicated
that activation of store-operated Ca2⫹ entry (SOCE), via depletion of stores with inhibitors of sarco(endo)plasmic reticuMANY PLASMA MEMBRANE RECEPTORS
Article published online before print. See web site for date of publication
(http://physiolgenomics.physiology.org).
Address for reprint requests and other correspondence: M. L. Villereal,
Dept. of Neurobiology, Pharmacology and Physiology, The Univ. of Chicago,
947 E. 58th St., Chicago, IL 60637 (E-mail: [email protected]).
14
lum Ca2⫹-ATPase pumps, can lead to the regulation of a
handful of specifically monitored genes such as Nur77 (33),
c-fos and grp78 (23), and pip92 (10); however, these studies do
not provide an insight into how widespread the involvement of
SOCE is in regulating mRNA levels. Several recent investigations have utilized cDNA microarrays to broaden the range of
mRNA expression that can be monitored. One such study in T
lymphocytes utilized cDNA microarrays (representing 7,396
cDNA clones) to investigate the gene regulation in response to
ionomycin and phorbol ester treatment of control cells, or cells
thought to have a defect in SOCE (18). Although this study
greatly advanced our understanding of the role of SOCE in
regulating gene expression, there are several reasons that
additional studies are required. First, a significantly larger
number of genes are represented on more recent cDNA microarrays, allowing a fuller description of the expression profile. Second, the lymphocyte is a specialized cell in which
induced gene expression is heavily directed toward producing
cytokines to regulate the population of immune cells, and
therefore the expression profile is possibly quite different from
the gene expression profile elicited in other types of cells.
Third, while ionomycin and phorbol ester approximate a physiological stimulus in lymphocytes, an ionomycin stimulus in
most other cell types fully depletes the endoplasmic reticulum
(ER) stores to the point of blocking ER protein processing,
resulting in the activation of the ER stress response and
ultimately activation of apoptosis. The peripheral effects of
fully depleting internal Ca2⫹ stores can be seen in a gene
expression profiling study of RBL-2H3 mast cells stimulated
with 2,5-di(tert-butyl)-1,4-hydroquinone (DTBHQ), another
inhibitor of the ER Ca2⫹-ATPase, where DTBHQ upregulated
many more stress-inducible genes than cross-linking of IgE
receptors, a more physiological stimulus (38). Therefore, the
gene expression profiles produced by thapsigargin and ionomycin may vary significantly from those produced by activation of SOCE by receptor agonists. Another recent study
utilized cDNA arrays (Atlas 1.2 mouse array from Clontech,
which represents 1,200 genes) to demonstrate that inhibition of
serum-stimulated 3T3 cells with SKF-96365, an inhibitor of
SOCs, leads to the upregulation, or downregulation, of 29
genes (27). However, the interpretation of these SKF-96365
experiments is complicated by the lack of specificity of this
reagent. Recent papers report SKF-96365 inhibition of Na⫹
channels (26), K⫹ channels (49), maitotoxin-induced Ca2⫹
entry (14, 51), and facilitation of nicotinic receptor desensitization (25) in addition to the more widely recognized inhibition
of SOCs. One recent study used SKF-96365 to distinguish
between receptor-operated channels (ROCs) and SOCs, but as
an inhibitor of ROCs, not SOCs (36). Given the limitations of
1094-8341/05 $8.00 Copyright © 2005 the American Physiological Society
Downloaded from http://physiolgenomics.physiology.org/ by 10.220.32.247 on June 17, 2017
Zagranichnaya, Tatiana K., Xiaoyan Wu, Arpad M. Danos,
and Mitchel L. Villereal. Gene expression profiles in HEK-293 cells
with low or high store-operated calcium entry: can regulatory as well
as regulated genes be identified?. Physiol Genomics 21: 14–33, 2005.
First published December 28, 2004; doi:10.1152/physiolgenomics.
00099.2004.—Gene expression profiles were generated using cDNA
microarray technology for clones of human embryonic kidney (HEK)293 cells selected to have either high or low levels of store-operated
Ca2⫹ entry (SOCE). For five high clones, three low clones, and
control HEK-293 cells, duplicate Affymetrix U133A human gene
arrays were run after extraction of total RNA from cells growing in
the presence of serum. Of the ⬃22,000 genes represented on the
microarray, 58 genes had readings at least twofold higher, while 32
genes had readings at least twofold lower, in all five high SOCE
clones compared with control HEK-293 cells. In the low SOCE
clones, 92 genes had readings at least twofold higher, while 58 genes
had readings at least twofold lower, than in HEK-293 cells. Microarray results were confirmed for 18 selected genes by real-time RT-PCR
analysis; for six of those genes, predicted changes in the low SOCE
clone were confirmed by an alternative method, monitoring mRNA
levels in HEK-293 with SOCE decreased by expression of small
interfering (si)RNA to canonical transient receptor potential protein-1.
Genes regulated by SOCE are involved in signal transduction, transcription, apoptosis, metabolism, and membrane transport. These data
provide insight into the physiological role of SOCE. In addition, a
potential regulator of SOCE, insulin receptor substrate (IRS)-2, has
been identified. A reduction of IRS-2 levels by siRNA methods in two
high clones dramatically reduced SOCE, whereas overexpression of
IRS-2 in a low SOCE clone elevated SOCE.
GENE EXPRESSION PROFILES IN CLONES WITH LOW AND HIGH SOCE
15
experiment. On the next morning, cells were washed twice with
HEPES-buffered HBSS, loaded for 30 min with 5 ␮M fura-2 AM in
HBSS supplemented with 1 mg/ml BSA ⫹ 0.025% Pluronic F-127,
and then unloaded in HBSS for another 30 min. The coverslips were
mounted as the bottom of a chamber, and cells in the chamber were
perfused via an eight-channel syringe system. A suction pipette
maintained a constant volume of solution (⬃0.5 ml) in the chamber.
An InCyt IM2 dual-wavelength fluorescence imaging system (Intracellular Imaging, Cincinnati, OH) was used to measure [Ca2⫹]i during
the experiment, as previously described (57). In short, Ba2⫹ influx
was measured before (to determine leak flux) and after (to determine
total flux) store depletion by thapsigargin. SOCE was defined as the
difference between total and leak Ba2⫹ influxes. Nominally Ca2⫹-free
HBSS was prepared by stirring Ca2⫹-free, Mg2⫹-free, and HCO⫺
3 free HBSS with Chelex-100 beads. After the Chelex-100 beads were
filtered out, MgCl2 was added to a final concentration of 1 mM.
MATERIALS AND METHODS
The five high SOCE clones, three low SOCE clones, and HEK-293
cells (to serve as the general control population) were plated onto
15-cm plates 1 day before RNA purification. Two separate experiments were run. In the first experiment, microarrays were run on
duplicate samples from five high clones (H1, H15, H24, H36, and
H39), one low clone (L3), and the HEK control cells. In the second
experiment, microarrays were run on duplicate samples from two low
clones (L28 and L29), one high clone (H36), and the HEK control
cells. Cells were taken from their growth medium, and total RNA was
immediately purified. The quality of the RNA was evaluated by
agarose gel electrophoresis. A quantity in excess of 20 ␮g of RNA
from each clone (duplicate sample) was submitted to our Functional
Genomics Core Facility for microarray analysis. To confirm the
integrity of the RNA, samples were applied on an Agilent 2100
Bioanalyzer (Agilent Technologies, Palo Alto, CA), and the purity
and the concentration were determined with a GeneSpec III (Miraibio). The target preparation protocol followed the Affymetrix
GeneChip Expression Analysis Manual (Santa Clara, CA). Briefly, 10
␮g of total RNA were used to synthesize double-stranded cDNA
using the Superscript Choice System (Life Technologies). First-strand
cDNA synthesis was primed with a T7-(dT24) oligonucleotide. From
the phase-log gel-purified cDNA, biotin-labeled antisense cRNA was
synthesized with BioArray High Yield RNA Transcript Labeling Kit
(Enzo Diagnostics, Farmingdale, NY). After precipitation with 4 M
lithium chloride, 12 ␮g of fragmented cRNA were hybridized to
human 133A arrays for 16 h at 45°C and 60 rpm in an Affymetrix
Hybridization Oven 640. The arrays were washed and stained with
streptavidin phycoerythrin in Affymetrix Fluidics Station 400, using
the Affymetrix GeneChip protocol, and then scanned using the Affymetrix Agilent GeneArray Scanner. The acquisition and initial
quantification of array images were performed using the Affymetrix
Microarray Suite Version 5.0 (MAS 5.0) with the default analytic
parameters. Complete microarray expression data are available at the
National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database (GEO submissions GSE1309, GSM21234–
21235, GSM21258–21264, GSM21378–21382, GSM21385, GSM21391,
GSM21393–21396, GSM21400–21401) at http://www.ncbi.nlm.nih.gov/
geo. Subsequent data analyses were performed by our laboratory.
The Functional Genomics Core provided us with two types of data
output, each contained in a separate Excel file. The first file contained
normalized fluorescence values and an absolute call for presence or
Materials
Fura-2 free acid, fura-2 AM, indo-1, and Pluronic F-127 were
purchased from Molecular Probes; thapsigargin was purchased from
LC Laboratory. Cyclopiazonic acid (CPA) was purchased from Calbiochem. Hanks’ balanced salt solution (HBSS); Ca2⫹-free, Mg2⫹free, and HCO⫺
3 -free HBSS; DMEM; penicillin-streptomycin, Lglutamine, and trypsin-EDTA were purchased from Life Technologies
(GIBCO BRL). Chelex-100 came from Bio-Rad.
Cell Culture
HEK-293 cells were cultured in DMEM supplemented with 10%
FBS, 50 U/ml penicillin, 50 ␮g/ml streptomycin, and 2 mM glutamine. Cells were grown in an incubator at 37°C with humidified 5%
CO2 and 95% air.
Cell Sorting and Clone Selection
HEK-293 cells were grown to confluency on 15-cm plates, and then
the cells were loaded with Fluo-3 and Fura Red. In the absence of
Ca2⫹, cells were stimulated with 10 ␮M CPA for 10 min to deplete
intracellular Ca2⫹ stores. Cells were then removed from the dish by
rinsing in EDTA medium, transferred to a 50-ml sterile centrifuge
tube, and washed with nominally Ca2⫹-free HBSS. After sufficient
time for the return of cytosolic Ca2⫹ to basal levels, intracellular Ca2⫹
concentration ([Ca2⫹]i) was measured by fluorescence-activated cell
sorting (FACS) before and after the addition of 1.8 mM Ca2⫹. The
sorted population of cells with high SOCE (or low SOCE) was plated
on six-well plates and grown until individual cell clones were visible.
Cell clones were then selected and expanded into clonal cell lines.
Thirty-one high SOCE clonal cell lines and twenty-four low SOCE
clonal cell lines were generated and tested to confirm that they were
high or low in SOCE by monitoring thapsigargin-stimulated Ba2⫹
entry. Five high SOCE clones and three low SOCE clones were
selected for use on the basis of their level of SOCE and low Ba2⫹ leak
influx before thapsigargin stimulation.
Ca2⫹ Imaging
[Ca2⫹]i was measured in cells loaded with the fluorescent indicator
fura-2. Cells were plated onto 25-mm coverslips 1 day before the
Physiol Genomics • VOL
21 •
Total RNA Isolation
Total RNA was isolated from HEK-293 cells and clones by use of
the RNeasy Mini Kit (Qiagen) and treated with DNase I (Invitrogen).
The RNA sample was additionally purified by ethanol precipitation,
and its concentration was determined by measuring absorbance at
260 nm.
cDNA Microarray Analysis
www.physiolgenomics.org
Downloaded from http://physiolgenomics.physiology.org/ by 10.220.32.247 on June 17, 2017
the previous investigations into the role of SOCE in regulating
mRNA levels, we decided to take an alternative approach to
investigate this question.
Previously, we reported that a clonal variation of SOCE
exists in the human embryonic kidney (HEK)-293 cell population (2). In the current study, we took advantage of that clonal
variation and selected HEK-293 cell clones that varied in their
levels of SOCE. We used these clonal populations to investigate the effect of low or high levels of SOCE on the gene
expression profile for cells maintained in their normal growth
environment. The mRNA expression profiles for the various
clones were evaluated by utilizing Affymetrix cDNA microarrays. Comparisons of mRNA profiles of five clones high in
SOCE, the parent HEK-293 cell population, and three clones
low in SOCE provide valuable information about which genes
are regulated by changes in SOCE for cells in their normal
growth environment. In addition, this study provides important
information on potential upstream regulators of SOCE, as
evidenced by our results demonstrating that reduction of the
elevated insulin receptor substrate (IRS)-2 levels in two high
SOCE clones by small interfering (si)RNA methods, or overexpression of IRS-2 in a low SOCE clone, alters their levels of
SOCE.
16
GENE EXPRESSION PROFILES IN CLONES WITH LOW AND HIGH SOCE
PCR Primers
PCR primers for the genes chosen for real-time RT-PCR were
designed based on published sequences in GenBank.
RT-PCR
First-strand cDNA was prepared from 1 ␮g of total RNA, using
SuperScript III RNase H⫺ RT (Invitrogen) and 1 ␮g of oligo(dT). The
mRNA samples were denatured at 65°C for 5 min. Reverse transcription was performed at 50°C for 55 min and was stopped by heating
samples at 75°C for 10 min.
Quantitative Real-Time RT-PCR
Real-time PCR was performed on the ABI Prism 7700 Sequence
Detection System using SYBR7 Green PCR Core Reagents (Applied
Biosystems) and cDNA synthesized as described above. PCR was
performed using the kit protocol in a 25-␮l reaction volume. The
integrity of the RT-PCR products was confirmed by melting-curve
analysis. Melting curves for each primer pair showed one specific
1
The Supplemental Material for this article (Supplemental Tables S1–S4) is
available online at http://physiolgenomics.physiology.org/cgi/content/full/
0099.2004/DC1.
Physiol Genomics • VOL
21 •
signal. The amount of PCR products in parental HEK-293 cells or in
clones H36 and L28 was calculated in reference to the individual
calibration curves based on cDNA obtained from parental HEK-293
cells.
Western Blotting
Cells were grown on 10-cm dishes under the conditions described
above. Cells were lysed in modified radioimmunoprecipitation (RIPA)
buffer (10 mM Tris䡠HCl, pH 7.5, 500 mM NaCl, 0.1% SDS, 1%
NP-40, 1% Na-deoxycholate, 2 mM EDTA, 2 mM Na2VO4, 2 mM
Na4P2O7, 2 mM NaF). The lysates were clarified by centrifugation,
and protein concentration was measured by a bicinchoninic acid
(BCA) kit (Pierce). Total protein extract (50 ␮g) was applied on 8%
SDS-PAGE (16 cm ⫻ 16 cm gels) and run overnight. The proteins
were transferred onto an Immobilon-P membrane (Millipore), and the
uniformity of protein transfer for all the lanes was evaluated by
reversibly staining with BLOT-Fast-Stain (Geno Technology). After
1 h of blocking, membranes were treated with monoclonal anti-IRS-2
antibodies (Upstate) at a dilution of 1:1,000. Membranes were washed
4⫻ 10 min with Tris-buffered saline containing 0.1% Tween 20
(TBS-T), incubated for 30 min at room temperature with secondary
anti-mouse antibody (1:10,000 in TBS-T), washed under the same
conditions, and developed with SuperSignal West Pico Chemiluminescent Substrate (Pierce) for a suitable time so as not to saturate the
film. The films were digitized on a flatbed scanner, and the relative
spot intensities were determined in Photoshop 6.0. The images were
inverted, the bands were outlined, and the average gray level and
number of pixels in the spot were obtained from the histogram
function. The product of the average gray level value and the number
of pixels was used to represent the integrated signal in the band. Each
Western blot was repeated at least three times using different cell
lysates.
siRNA Constructs
For human IRS-2 (GenBank no. AF073310), potential siRNA
target sites (19 nucleotides in length) were chosen. The location of the
selected IRS-2 gene sequence is 573–591. The potential target sites
were compared with the human genome database by using BLAST
(http://www.ncbi.nlm.nih.gov/BLAST), and any target sequences
with homology to other coding sequences were eliminated from
consideration. Hairpin siRNA template oligonucleotide design was
done by entering siRNA target sequences into the web-based insert
design tool at the following address: http://www.ambion.com/
techlib/misc/psilencer_converter.html. Then, two complementary
oligonucleotides (forward 5⬘-GATCCCGCCTCAACAACAACAACAACTTCAAGAGAGTTGTTGTTGTTGTTGAGGTTTTTTGGAAA-3⬘ and reverse 5⬘-AGCTTTTCCAAAAAACCTCAACAACAACAACAACTCTCTTGAAGTTGTTGTTGTTGTTGAGGCGG-3⬘)
were synthesized, annealed, and ligated into the linearized pSilencer
3.1 H1 neo vector (Ambion). All procedures were performed as
directed by the manufacturer’s instruction manual (Ambion). The
inserts were sequenced to confirm that there were no unwanted
mutations.
Transfection
Cells were grown in 75-cm2 flasks to 60% confluency and transfected by use of PerFectin Transfection reagent (Gene Therapy Systems). For transient transfection experiments (IRS-2 overexpression),
cells were used 48 h after transfection. For stable transfection experiments (siRNA expression), cells were transfected and later treated
with 400 ␮g/ml G418. Cells that survived after 2 wk were collected,
and this population of cells was used for future experiments.
www.physiolgenomics.org
Downloaded from http://physiolgenomics.physiology.org/ by 10.220.32.247 on June 17, 2017
absence of a transcript (see Supplemental Table S1; available at the
Physiological Genomics web site)1. The calls were present (P), absent
(A), or marginal (M) to reflect whether the particular gene was
expressed on the basis of a complex algorithm that weighs the number
of matched vs. mismatched probes that are positive for a particular
gene. Supplemental Table S2 contained comparative data; for each
gene, a ratio of the normalized fluorescence value for each experimental case (each high or low clone) vs. the normalized fluorescence
value for its HEK cell control was calculated. In the absolute data set,
all genes with fluorescence values less than 200, both in the control
HEK samples and in the high or low clones, were identified; this list
of genes was matched against the Excel file containing the comparative data, and those genes were eliminated from further consideration. From this modified comparative file, a new Excel file was
generated that contained the comparative data for only the five high
SOCE clones. With duplicate values for each clone being individually
compared with the duplicate values for the control (HEK cells), four
comparative ratios for each clone were generated, each accompanied
by an identifier for increase (I), decrease (D), or no significant change
(NC). A Countif routine was run within Excel to total the number of
I or D identifiers present within a given row (for a given gene). Thus,
if the Countif routine gave a value of 20 Is for a given row, this would
mean that this gene increased in all four comparisons for each of the
five high clones. The file was then sorted based on the value within the
“Countif column,” and all genes containing a “Countif value” above
16 were selected and pasted into a new file. A Countif value of 16
almost always meant that the gene had increased for all four comparisons in four of the five clones. This data set was then sorted based on
the ratio values in one of the high clone columns. Any gene with a
value above 1 or below ⫺1 (values were based on a log2 scale, so a
ratio ⬎1 meant the level had increased at least 2-fold) for at least 16
of the 20 comparisons was selected and pasted into a new file. Each
of these genes was then checked against the data for the low clone
(L3) run in this experiment, and genes were maintained on the list
only if their low clone levels either did not change dramatically or
changed in the opposite direction seen in the high clones.
For the low clones, we report the genes from the second experiment
(see Supplemental Tables S3 and S4) that change in both the L28 and
L29 clones compared with the HEK control cells, but either do not
dramatically change or change in the opposite direction in the high
clone (H36) run in this experiment.
GENE EXPRESSION PROFILES IN CLONES WITH LOW AND HIGH SOCE
RESULTS
Selection of HEK-293 Cell Clones That Have Low or High
Levels of SOCE
established. The aspiration of the sample was interrupted to
add Ca2⫹, and then the aspiration was resumed. The data in
Fig. 1A show that there is no significant change in [Ca2⫹]i
when Ca2⫹ is added back to control cells. Another aliquot of
cells was incubated for 10 min in 10 ␮M CPA in Ca2⫹-free
HBSS, and the cells were removed from the dish. The data in
Fig. 1B illustrate that, after depletion of internal Ca2⫹ stores,
the addition of external Ca2⫹ resulted in a dramatic elevation
of [Ca2⫹]i. A series of similar experiments was run, and the
cells were sorted on the basis of the sorting profile shown in
Fig. 1C. Cells in the low end of the profile, and in other runs
the cells in the high end of the profile, were collected in sterile
centrifuge tubes. This provided us with two populations of
cells, one enriched for cells with low levels of CPA-stimulated
Fig. 1. Fluorescence-activated cell sorting (FACS) of human embryonic kidney (HEK)-293 cells based on Ca2⫹ entry levels. HEK-293 cells were grown to
confluency on 15-cm plates. Cells were loaded with Fluo-3 and Fura Red, removed from the dish by rinsing in EDTA medium, transferred to a 50-ml tube, and
washed in Ca2⫹-free HBSS. Cells were aspirated by FACS and excited at 488 nM, and the emission was monitored at 530 and 585 nM. The ratio of 530-to-585
nM emission intensity (FL1/FL2) was recorded as a measure of the Ca2⫹ level, the aspiration was interrupted to add 1.8 mM Ca2⫹, and the aspiration was
resumed (A). In a parallel experiment, cells were stimulated with 10 ␮M cyclopiazonic acid (CPA) in Ca2⫹-free HBSS for 10 min before their removal from
the dish. The cells were then treated as described above (B). Ca2⫹ entry into CPA-treated cells was initiated, and then the cells were sorted by FACS. A typical
sorting profile is shown to illustrate the fractions collected for either low store-operated Ca2⫹ entry (SOCE) cells or high SOCE cells (C).
Physiol Genomics • VOL
21 •
www.physiolgenomics.org
Downloaded from http://physiolgenomics.physiology.org/ by 10.220.32.247 on June 17, 2017
In a previous study, we reported that HEK-293 cells plated
at clonal density demonstrate considerable clone-to-clone variation of SOCE (2). This clonal variation was utilized to select
cell populations that had either high or low levels of SOCE. To
screen for clones on a high throughput basis, HEK-293 cells
were grown on 15-cm plates, loaded with Fluo-3 and Fura Red,
and removed from their plates in EDTA-containing medium.
They were washed by centrifugation and resuspended in Ca2⫹free HBSS. An aliquot of these cells was aspirated into the
FACS machine, and a baseline for intracellular Ca2⫹ was
17
18
GENE EXPRESSION PROFILES IN CLONES WITH LOW AND HIGH SOCE
Physiol Genomics • VOL
21 •
Fig. 2. SOCE in selected HEK cell clones. Subpopulations of HEK-293 cells
selected by FACS were plated at clonal density, and macroscopic clones were
selected and expanded to produce monoclonal lines. Top: high or low levels of
SOCE were confirmed in each clone by monitoring thapsigargin-stimulated
Ba2⫹ entry. In the absence of Ca2⫹, 2 mM Ba2⫹ was added to Ca2⫹-free HBSS
to measure the rate of Ba2⫹ leak. After switching to Ca2⫹-free medium, Ca2⫹
stores were released by adding 1 ␮M thapsigargin. After Ca2⫹ returned to
basal levels, 2 mM Ba2⫹ was added. SOCE was determined by subtracting
initial Ba2⫹ leak influx from the thapsigargin-stimulated Ba2⫹ influx. Compared with HEK control cells, 5 clones (H1, H15, H24, H36, H39) have
significantly (P ⬍ 0.01) higher SOCE levels and 3 clones (L3, L28, L29) have
significantly (P ⬍ 0.0005) lower SOCE levels. B: SOCE was measured in a
high K⫹ medium (133 mM K⫹, with K⫹ above 5.4 mM being added as a
replacement for Na⫹). Compared with the HEK control, all 5 high SOCE
clones had significantly higher SOCE levels (P ⬍ 0.05) and all 3 low SOCE
clones had significantly lower SOCE levels (P ⬍ 0.05). The no. of coverslips
tested for SOCE is shown in parenthesis, with each determination being the
average response of ⬃800 cells.
in cytoplasmic Ca2⫹ buffering capacity would be expected to
produce clonal variations in the Ca2⫹ transients in response to
thapsigargin.
These data extend our earlier report on clonal variation of
SOCE (2) by demonstrating that, when individual cell clones
are selected and grown into populations of cells, the various
cell populations maintain their elevated or decreased level of
SOCE. The successful generation of multiple clonal lines with
high or low SOCE promises to be useful in evaluating the
physiological roles of SOCE. Experiments can be performed to
investigate the physiological consequences of having elevated
or decreased levels of SOCE in the absence of pharmacological
interventions. Our initial investigations in this direction were to
assess the effect of elevated or decreased SOCE on gene
expression profiles in HEK cells. One should note at this point
www.physiolgenomics.org
Downloaded from http://physiolgenomics.physiology.org/ by 10.220.32.247 on June 17, 2017
Ca2⫹ entry and one enriched for cells with high levels of
CPA-stimulated Ca2⫹ entry.
These populations of cells were plated onto six-well plates at
clonal densities, and the cells were fed on a regular basis until
individual macroscopic cell clones could be observed. Individual cell clones were selected and grown up for analysis of
SOCE on a Ca2⫹ imaging rig. Thirty-one potentially high
SOCE clones were harvested and rescreened to confirm high
levels of SOCE. Because the initial high throughput screen was
on the basis of changes in cytosolic Ca2⫹ levels, it seemed
possible that some clones were selected because they had low
Ca2⫹ pump rates rather than high levels of SOCE. Thus, for the
second screen, thapsigargin-stimulated Ba2⫹ entry was monitored, as Ba2⫹ is not pumped by the Ca2⫹-ATPases (29, 48),
and therefore observed changes would result from changes in
entry rates. An initial incubation in HBSS allowed a baseline to
be established, and then cells were incubated in Ca2⫹-free
HBSS ⫹ 2 mM Ba2⫹ to measure the Ba2⫹ leak before store
depletion. The cells were then incubated in Ca2⫹-free HBSS,
and 1 ␮M thapsigargin was added to deplete intracellular
stores. After the return of the cytosolic Ca2⫹ to basal levels,
Ba2⫹ was added, and the slope of Ba2⫹ entry was measured.
The SOCE is defined as the difference between the Ba2⫹ entry
after thapsigargin stimulation and the Ba2⫹ leak entry before
thapsigargin stimulation. This approach has been used in several of our previous papers, and time courses for Ca2⫹ release
and Ba2⫹ influx can be viewed there (3, 50, 57). Because we
were interested in clones with high SOCE, we discarded clones
with high leak rates, regardless of whether they also had high
thapsigargin-stimulated Ba2⫹ entry.
Of the 31 potentially high clones rescreened by image
analysis, 13 clones appeared to be authentic high SOCE clones.
Of the 24 potentially low clones rescreened by image analysis,
5 clones appeared to be authentic low SOCE clones. On the
basis of their low basal Ba2⫹ leaks, we selected five high
clones and three low clones to utilize in cDNA microarray
experiments (Fig. 2, top). Ba2⫹ uptake rates were as follows:
HEK-293 ⫽ 0.00061 ⫾ 0.00005 min⫺1 (n ⫽ 20); H1 ⫽
0.00098 ⫾ 0.00012 min⫺1 (n ⫽ 18); H24 ⫽ 0.00106 ⫾
0.00009 min⫺1 (n ⫽ 19); H39 ⫽ 0.00097 ⫾ 0.00011 min⫺1
(n ⫽ 10); H15 ⫽ 0.00095 ⫾ 0.00010 min⫺1 (n ⫽ 11); H36 ⫽
0.00107 ⫾ 0.00011 min⫺1 (n ⫽ 16); L3 ⫽ 0.00039 ⫾ 0.00002
min⫺1 (n ⫽ 7); L28 ⫽ 0.00034 ⫾ 0.00003 min⫺1 (n ⫽ 10);
L29 ⫽ 0.00034 ⫾ 0.00004 min⫺1 (n ⫽ 9). To assure that the
variation in SOCE between clones was not simply due to
variations in membrane potential, similar experiments were
performed in a high-potassium medium to depolarize the membrane potential. As seen in Fig. 2, bottom, although the magnitude of the SOCE was reduced in all clones, membrane
depolarization did not normalize the differences in SOCE
between the various clones and the parent HEK-293 cell
population. An analysis of the Ca2⫹ transients (area under the
curve) in response to thapsigargin and the Ba2⫹ leak fluxes
indicated that there were no statistically significant differences
in these parameters between the clones and the parent HEK293 cells (data not shown). This indicates that the clonal
variations in thapsigargin-stimulated Ba2⫹ entry were not the
result of clonal variations in cell volumes or cytoplasmic Ca2⫹
buffering capacities. Changes in cell volume or buffering
capacity would be expected to alter Ba2⫹ leak fluxes as well as
thapsigargin-stimulated Ba2⫹ flux. Likewise, clonal variations
GENE EXPRESSION PROFILES IN CLONES WITH LOW AND HIGH SOCE
Gene Expression Profiles in High and Low SOCE Clones
The quantity of total RNA purified was determined by
absorbance measurements, and the quality of the RNA was
checked by running several micrograms of RNA on gel electrophoresis. A second check on the RNA quality was performed at our Functional Genomics Core Facility. For each
sample, at least two cDNA microarrays were run, but for the
control HEK-293 cells and the H36 clone, four cDNA microarrays were run. In Fig. 4A, an example of the quality of the
technical replication of the microarray assay is shown; the
fluorescent signals from one duplicate sample of the H1 clone
are plotted on the x-axis vs. the fluorescence signals from the
other duplicate sample of the H1 clone on the y-axis. This plot
demonstrates that there is good replication between the duplicate microarrays run in these experiments. This is especially
Fig. 3. Serum-stimulated Ca2⫹ entry in the high and low SOCE clones. Cells
from different clones were plated on coverslips 24 h before the experiment, and
serum-stimulated Ba2⫹ entry was monitored in each clone. In the absence of
Ca2⫹, 2 mM Ba2⫹ was added to Ca2⫹-free HBSS to measure the rate of Ba2⫹
leak. After switching to Ca2⫹-free medium, Ca2⫹ stores were released by
adding 0.5% FBS. After Ca2⫹ returned to basal levels, 2 mM Ba2⫹ was added
in Ca2⫹-free medium containing 0.5% FBS. The serum-stimulated Ba2⫹ entry
was determined by subtracting initial Ba2⫹ leak influx from the Ba2⫹ influx
measured after serum treatment. Compared with the HEK control, all 5 high
SOCE clones had significantly higher serum-stimulated Ba2⫹ entry levels (P ⬍
0.03) and all 3 low SOCE clones had significantly lower serum-stimulated
Ba2⫹ entry levels (P ⬍ 0.03). The no. of coverslips tested is shown in
parenthesis, with each determination being the average response of ⬃800 cells.
Physiol Genomics • VOL
21 •
true for those genes with a signal in excess of 100 on the
fluorescence scale; there are few points with signals ⬎100 that
fall above the line indicating a greater than twofold change in
gene expression level.
In Fig. 4B, the data for one replicate of the high clone H1 is
plotted against the data for one replicate of the control HEK293 cells. This plot stands in dramatic contrast to the plot
illustrating the excellent technical replication. There are many
more genes with signals above 100 that fall in the region
indicating a greater than twofold change in expression level.
There also are several genes with expression levels above 100
that fall above the line indicating a ⬎10-fold change in expression level. These results suggest that there will be reproducible changes in expression levels in the clones with elevated
levels of SOCE.
In Fig. 4C, we have plotted the data for one replicate of the
L3 clone vs. the data for one replicate of the parent HEK-293
cells. This plot also looks quite different from the plot demonstrating the quality of technical replication. There are a
larger number of genes with a signal above 100 that fall in the
region of the plot that indicates a greater than twofold change
in gene expression. These results suggest that there may be a
significant number of genes that increase in cells that have low
levels of SOCE.
Finally, in Fig. 4D, we have plotted one replicate of the L3
clone vs. one replicate of the H24 clone. Compared with Fig.
4B, there are many more genes within the region representing
changes in level of gene expression between 2-fold and 10fold. This suggests that there may be a number of genes that
increase in cells having high SOCE levels and also decrease in
cells having low levels of SOCE.
Changes in Gene Expression in Clones with High Levels
of SOCE
We report all genes that change their expression level by at
least twofold in at least four of the five high clones and that, in
the low clone, do not undergo a change in the same direction.
We chose to report the four-of-five category of genes because
it was felt that two classes of interesting genes might be present
in this category. Some genes would be in this category because
changes were above threshold in four of five genes and slightly
below threshold in the fifth clone. For example, if, for a
particular gene, the ratios (on the log2 scale) were 1.1, 1.2, 1.2,
1.1, and 0.9 for the five high clones, we would consider it to be
an interesting gene. We were also interested in the much
smaller subclass of genes where the change was dramatic in
four of the five clones but did not change, or changed in the
opposite direction, in the fifth clone. Our prediction was that
genes regulated downstream of SOCE would change comparably in five of five high clones. We also theorized that some
genes that are elevated might be responsible for the elevated
SOCE. Three obvious theories to explain the elevated SOCE
would be an increase in channel proteins, an increase in a
positive channel regulator, or a decrease in a negative channel
regulator; it is not necessary for all high clones to have the
same underlying mechanism for the elevated SOCE. We hypothesized that we possibly could identify an elevated positive
regulator as being the underlying mechanism responsible for
the elevated SOCE in some of the high clones. Thus the lack of
response of a gene in one of five clones would suggest that it
www.physiolgenomics.org
Downloaded from http://physiolgenomics.physiology.org/ by 10.220.32.247 on June 17, 2017
that more of the clones from the high SOCE selection than
from the low SOCE selection were confirmed by Ba2⫹ imaging
experiments. This is likely the result of the steeper shape of the
distribution curve at the low end vs. the high end of the sorting
profile (Fig. 1C).
Because we wanted to investigate the effect of low or high
SOCE levels on gene expression under normal physiological
conditions, we harvested logarithmically growing cells directly
from their growth medium (DMEM ⫹ 10% FBS) for the
subsequent RNA purification. Previous studies have reported
that various growth factors stimulate SOCE (32, 34, 59),
suggesting that an increase or decrease in SOCE should be
reflected in a change in Ca2⫹ entry for cells growing in serum.
The data in Fig. 3 confirm that serum-stimulated Ca2⫹ entry is
higher in the five high SOCE clones than in HEK-293 cells and
is lower in the low SOCE clones (all statistically significant,
P ⬍ 0.03).
19
20
GENE EXPRESSION PROFILES IN CLONES WITH LOW AND HIGH SOCE
is not Ca2⫹ regulated and is not the underlying cause for
elevated SOCE in that particular clone, but could be the cause
for the elevated SOCE in the other four clones. This is only one
of a number of potential scenarios one can use to explain
elevated SOCE levels in the high clones, but it serves to
explain our rationale for wanting to examine genes that respond in four of five clones. Thus we have reported genes that
changed above the twofold threshold in at least four of five
high clones.
Identifying genes that changed expression levels by at least
twofold in at least four of the five high clones involved two
different sorts of the comparative data file. We initially ran a
Countif routine to determine the number of I (significant
increase) parameters on each row (each row representing all of
the 20 comparisons for a single gene). For each gene with 16
or more Is, we determined that they had all presents (P) in the
absolute file and that they achieved a value of 200. Thus genes
that started with a value below 200 in HEK cells but increased
above 200 in the high clones were counted. Genes that increased dramatically in the low clone for this experiment were
excluded. The genes that fit these criteria are listed in Table 1.
After determining which genes increased in the high SOCE
clones, we then ran a Countif routine to determine the number
of D (significant decrease) parameters on each row. For each
Physiol Genomics • VOL
21 •
gene with 16 or more Ds, we determined that they achieved a
value of 200. Thus genes that started with a value above 200 in
HEK cells but dropped below 200 in the high clones were
counted. Genes that decreased dramatically in the low clone for
this experiment were excluded. The genes that fit these criteria
are listed in Table 2.
Changes in Gene Expression in Clones with Low Levels
of SOCE
As discussed in MATERIALS AND METHODS, we wanted to pull
out those genes that changed expression levels by at least
twofold in the low SOCE clones compared with the parental
HEK cells. This involved two different sorts of the comparative data file for the second set of microarrays. We initially ran
a Countif routine to determine the number of I (significant
increase) parameters present on each row (each row representing all of the 8 comparisons for a single gene). For each gene
with eight Is, we determined that they had all presents (P) in
the absolute file and that they achieved a value of 200. Thus
genes that started with a value below 200 in HEK cells but
increased above 200 in the low clones were counted. Genes
that increased dramatically in the high clone for this experiwww.physiolgenomics.org
Downloaded from http://physiolgenomics.physiology.org/ by 10.220.32.247 on June 17, 2017
Fig. 4. Microarray data for HEK clones with
high or low SOCE. Representative scatter
plots are shown for the microarray experiments comparing gene expression profiles of
HEK cells, high SOCE clones, and low
SOCE clones. Green data points represent
those genes for which the absolute fluorescence measurements fell below the threshold
of 200. Red points represent the genes for
which the fluorescence was above 200 for
both measurements. A: gene-by-gene comparison of the fluorescence values obtained
from the 2 duplicate chips run for the H1
clone. This comparison is shown to indicate
the quality of the technical replication of the
data. B: gene-by-gene comparison of the fluorescence values obtained from 1 chip run
for the H1 clone (high SOCE) and 1 chip run
for the HEK control. C: gene-by-gene comparison of the fluorescence values obtained
from 1 chip run for the L3 clone (low SOCE)
and 1 chip run for the HEK control. D:
gene-by-gene comparison of the fluorescence values obtained from 1 chip run for the
H24 clone (high SOCE) and 1 chip run for
the L3 clone (low SOCE).
21
GENE EXPRESSION PROFILES IN CLONES WITH LOW AND HIGH SOCE
Table 1. List of genes that are upregulated in the high SOCE clones
Name of Gene
GenBank Accession No.
Function
5.5
4.5
4.3
4.2
4.1
3.9
3.8
3.8
3.6
3.3
3.3
3.2
3.1
3.1
3.0
3.0
2.9
2.8
2.8
2.7
2.7
2.6
2.6
2.6
2.5
2.5
2.5
2.5
2.4
2.4
2.4
2.4
2.4
2.4
2.3
2.3
ATPase, class 1, type 8B, member 1 (ATP 1B8)
nucleoporin 210 (NUP210)
zinc finger protein 347
BANP homolog, SMAR1 homolog
solute carrier family 35, member E1 (SLC35E1)
weakly similar to UBIQUITIN-LIKE PROTEIN DSK2
ubiquitin-specific protease 34 (USP34)
dihydrolipoamide branched-chain transacylase (DBT)
phosphoinositol 3-phosphate-binding protein-2
G2 and S-phase expressed 1 (GTSE-1)
acylsphingosine amidohydrolase (acid ceramidase)-like
similar to DNA-directed RNA polymerase 1 (135 kDa)
interferon-stimulated protein, 15 kDa (ISG15)
immunoglobulin superfamily member WM78
CASP8 and FADD-like apoptosis regulator (FLAME-1)
poly(rC)-binding protein 2
DNA cross-link repair 1C (DCLRE1C)
GPI deacylase (PGAP1)
BRCA2 region
H2B histone family, member Q (H2BFQ)
leucine-rich repeat (in FLII) interacting protein 1
insulin receptor substrate 2
RNA binding protein; AT-rich element binding factor (SRM300)
LIM domain-containing preferred translocation partner in lipoma
retinoblastoma-associated factor 600
ASH1 (absent, small, or homeotic)-like
carnitine palmitoyltransferase I
leukocyte-associated Ig-like receptor 2 (LAIR2), transcript variant 1
ribosomal protein L38
fibroblast growth factor 13 (FGF-13)
complement component C4A
sodium channel, voltage-gated, type X, alpha polypeptide (SCN10A)
pan-hematopoietic expression (PHEMX)
activin A receptor, type 1B (ACVR1B), transcript variant 2
tel related Ets factor (TREF)
PTPNS (protein tyrosine phosphatase, non-receptor type substrate)
family pseudogene
heat shock 70-kDa protein 1A (HSPA1A)
splicing factor, arginineserine-rich 11 (SFRS11)
acid-inducible phosphoprotein (OA48-18)
zinc finger protein 198 (ZNF198)
ribosomal protein S3A
elongation factor 1-alpha 1 (EF-1-alpha-1)
ribosomal protein L39
tRNA isopentenylpyrophosphate transferase
ribosomal protein S3A (RPS3A)
cytochrome c oxidase subunit VIIa polypeptide 2 (liver) (COX7A2)
ribosomal protein S18 (RPS18)
NM_005603
NM_024923
AK024789
AL049250
NM_024881
AK023354
NM_014709
NM_001918
BC000969
BC006325
AW276646
NM_019014
NM_005101
AF181660
AF009616
AW103422
NM_022487
NM_024989
U50529
NM_003528
AF130054
AF073310
NM_016333
BF221852
AB007931
NM_018489
U62733
NM_002288
AW303136
NM_004114
K02403
NM_006514
NM_005705
NM_020327
AF147782
AL109809
cation transport
major component of the nuclear pore complex
DNA binding
unknown
metabolism
signal transduction
signal transduction
protein binding, metabolism
signal transduction
signal transduction
metabolism
DNA binding
inmmune response
inmmune response
apoptosis inhibitor activity
DNA binding
DNA repairing
catalytic activity
unknown
DNA binding
transcriptional repressor activity
signal transduction
RNA BINDING
function unknown
ubiquitin cycle, metabolism
DNA binding
fatty acid beta-oxidation, transport
unknown
structural constituent of ribosome
signal transduction
complement activation, classic pathway
cation transport, calcium ion binding
cell-cell signaling
protein serine/threonine kinase
regulation of transcription
signal transduction
NM_005345
NM_004768
NM_006107
NM_003453
AI925635
AL515273
BC001019
BE964125
NM_001006
NM_001865
NM_022551
heat shock protein activity
RNA binding
RNA splicing
regulation of transcription, DNA dependent
protein biosynthesis
translational elongation
RNA binding
translation
structural constituent of ribosome
electron transfer
structural constituent of ribosome
2.2
2.2
2.2
2.2
2.1
2.0
2.0
2.0
2.0
2.0
2.0
Fold change is the average fold increase for the high store-operated Ca2⫹ entry (SOCE) clones. Although some genes have multiple representation on the
microarray chip, only the set with the highest fold change is shown.
ment were excluded. The genes that fit these criteria are listed
in Table 3.
After determining which genes increased in the low SOCE
clones, we then ran a Countif routine to determine the number
of D (significant decrease) parameters present on each row. For
each gene with eight Ds, we determined that they achieved a
value of 200. Thus genes that started with a value above 200 in
HEK cells but dropped below 200 in the low clones were
counted. Genes that decreased dramatically in the high clone
for this experiment were excluded. The genes that fit these
criteria are listed in Table 4.
Confirmation of Gene Changes by Real-Time PCR
High SOCE clones. To evaluate the ability of the gene
microarray to reveal changes in gene expression levels, we
Physiol Genomics • VOL
21 •
ran real-time PCR assays on a select number of genes that
changed in either the low or high SOCE clones. The data in
Fig. 5 show a comparison between the microarray results
and the quantitative PCR (Q-PCR) results for several genes
that increased their level of expression in the high clones.
The responses for dihydrolipoamide branched-chain
transacylase (DBT) match very well between the microarray
and Q-PCR results; both methods show no change in the low
clones but a dramatic elevation in the high clones. The data
for ATPase, class 1, type 8B, member 1 (ATP1B8) show an
example of a gene that responds in both the low and high
clones, by being dramatically higher in the high clones and
significantly lower in the low clones. Fibroblast growth
factor (FGF)-13 represents a case where the microarray data
reveal a trend in directions (i.e., low in low clones and high
www.physiolgenomics.org
Downloaded from http://physiolgenomics.physiology.org/ by 10.220.32.247 on June 17, 2017
Fold Change
22
GENE EXPRESSION PROFILES IN CLONES WITH LOW AND HIGH SOCE
Table 2. List of genes that are downregulated in the high SOCE clones
Fold Change
Name of Gene
Function
response to stress
regulation of transcription, DNA dependent
protein binding
metabolism
DNA binding
metabolism
membrane
metabolism
mitosis
immune response
malate dehydrogenase (decarboxylating)
activity
RNA binding
intracellular protein transport
heat shock protein activity
intracellular signaling cascade
magnesium ion binding
L-serine catabolism
carbohydrate metabolism
nucleic acid binding
unknown
collagen component of hyaline cartilage
metabolism
calcium ion binding
glycerol-3-phosphate metabolism
glycerol-3-phosphate metabolism
negative regulation of cell cycle
electron transport
rRNA processing
signal transduction
unknown
DNA binding
intracellular signaling cascade
intracellular
protein domain-specific binding
cell cycle arrest
nucleic acid binding
synaptic junction
protein folding
transport
intracellular protein transport
regulation of cell cycle
receptor activity
metabolism
energy pathways
calcium ion binding, response to stress
tumor antigen
metabolism
protein domain-specific binding
electron transport
rRNA processing
bardet-biedl syndrome related
mitochondrial translocation
transport
DNA recombination
regulation of cell cycle
nucleus
intracellular protein transport
glycolysis
metabolism
ubiquitin-dependent protein catabolism
metabolism
signal transduction
protein amino acid dephosphorylation
regulation of transcription
regulation of transcription, DNA dependent
⫺7.3
⫺7.2
⫺6.0
⫺6.0
⫺5.9
⫺5.8
⫺5.7
⫺5.5
⫺5.4
⫺5.3
⫺5.2
stress-induced-phosphoprotein
zinc finger protein 6 (CMPX1) (ZNF6)
Cbpp300-interacting transactivator, (CITED2)
galactokinase 1
interleukin enhancer binding factor 3, 90 kDa
ATP citrate lyase
brain cell membrane protein 1
similar to aldehyde dehydrogenase 5
MAD1 (mitotic arrest deficient, yeast, homolog)-like 1
interferon, gamma-inducible protein 16
mitochondrial NAD(P)⫹ dependent malic enzyme
AL553320
NM_021998
NM_006079
BG474736
BG032366
U18197
AL136550
BC001619
NM_003550
BG256677
M55905
⫺5.2
⫺5.2
⫺5.1
⫺4.8
⫺4.8
⫺4.8
⫺4.7
⫺4.7
⫺4.5
⫺4.4
⫺4.3
⫺4.3
⫺4.3
⫺4.3
⫺4.2
⫺4.2
⫺4.1
⫺4.1
⫺4.1
⫺4.0
⫺4.0
⫺4.0
⫺3.9
⫺3.9
⫺3.8
⫺3.8
⫺3.8
⫺3.7
⫺3.6
⫺3.6
⫺3.6
⫺3.5
⫺3.4
⫺3.4
⫺3.4
⫺3.3
⫺3.3
⫺3.3
⫺3.3
⫺3.2
⫺3.2
⫺3.2
⫺3.1
⫺3.1
⫺3.1
⫺3.0
⫺3.0
⫺3.0
⫺3.0
⫺3.0
⫺3.0
⫺3.0
⫺3.0
⫺3.0
poly(a) polymerase alpha
Sec23 (S. cerevisiae) homolog A (SEC23A)
endoplasmin precursor (GRP94)
guanine nucleotide binding protein (G protein)
methionine adenosyltransferase II, alpha (MAT2A)
serine hydroxymethyltransferase
partial GK gene for glycerol kinase, exon 1
squamous cell carcinoma antigen
leucine rich repeat and fibronectin type III domain containing 4
collagen, type IX, alpha 3 (COL9A3)
phosphoserine aminotransferase (PSA)
calmodulin
glycerol kinase
glycerol kinase, testis specific 1
DNA mismatch repair protein MSH6
squalene epoxidase
similar to putative dimethyladenosine transferase
G protein-coupled receptor 50 (GPR50)
WD-repeat protein 18
smarce 1-related protein
protein-tyrosine phosphatase, non-receptor type 11
fibronectin type 3 and spry domain-containing protein
epsilon 14-3-3 protein
v-myc avian myelocytomatosis viral oncogene homolog (MYC)
NS1-associated protein 1
vesicle-associated membrane protein 3 (cellubrevin) (VAMP3)
FK506-binding protein 1A (12 kDa)
ATP-binding cassette, sub-family F (GCN20), member 2
ADP-ribosylation factor 1
transcription factor E2F-5
putative G protein-coupled receptor GPCR41
very-long-chain acyl-CoA synthetase homolog 2 (VLCS-H2)
nicotinamide nucleotide transhydrogenase (NNT)
endoplasmin precursor (94-kDa glucose-regulated protein)
tumor protein D52
similar to glycerol kinase
14-3-3 protein, zeta polypeptide
thioredoxin-related transmembrane protein (TMX)
exosome complex exonuclease rrp4
bardet-biedl syndrome 4 protein
mitochondrial import inner membrane translocase subunit tim23
lacental folate transporter (hFOLT1)
translin
dyskeratosis congenita 1, dyskerin (DKC1)
block of proliferation 1
RAB1, member RAS oncogene family (RAB1)
phosphoglycerate kinase
M2 mitochondrial autoantigen dihydrolipoamide acetyltransferase
ubiquitin-conjugating enzyme E2G 1 (homologous to C. elegans UBC7)
phosphoglycerate kinase 1 (PGK1)
ubiquitin-conjugating enzyme E2G 1 (homologous to C. elegans UBC7)
acid phosphatase 1. soluble
RNase P protein subunit p25 (Rpp25)
structure-specific recognition protein 1
AI670847
NM_006364
AK025862
NM_022446
NM_005911
L23928
AJ252550
AW173076
NM_024036
NM_001853
NM_021154
AI653730
X68285
X78713
D89646
BF979497
BC002841
NM_004224
BC001648
AF288679
AF119855
NM_024333
U28936
NM_002467
AI472757
NM_004781
BC005147
NM_005692
AA580004
U15642
AK021918
NM_012254
NM_012343
AI582238
BG389015
AA292874
U28964
NM_030755
NM_014285
AI813772
NM_006327
U15939
NM_004622
AJ010395
BG491842
NM_004161
S81916
J03866
BC002775
NM_000291
BC002775
NM_004300
NM_017793
BE795648
Continued
Physiol Genomics • VOL
21 •
www.physiolgenomics.org
Downloaded from http://physiolgenomics.physiology.org/ by 10.220.32.247 on June 17, 2017
GenBank Accession No.
23
GENE EXPRESSION PROFILES IN CLONES WITH LOW AND HIGH SOCE
Table 2.—Continued
Fold Change
⫺2.9
⫺2.9
⫺2.9
Name of Gene
GenBank Accession No.
Function
protein folding
intracellular protein transport
metabolism
AF067173
AD000092
NM_016567
BF342707
AW665024
BE256479
X75296
D13988
BC003360
X96588
AA670344
NM_002860
sex determination
pathogenesis
regulation of CDK activity
processing factor
kinase
protein folding
embryogenesis and morphogenesis
nonselective vesicle transport
RNA binding
signal transduction
cytoskeleton
metabolism
NM_006254
NM_007085
⫺2.6
⫺2.6
⫺2.6
⫺2.5
⫺2.5
⫺2.5
⫺2.5
⫺2.5
⫺2.5
⫺2.5
⫺2.4
⫺2.4
⫺2.4
⫺2.4
⫺2.4
⫺2.3
colon cancer, nonpolyposis type 1 (hMSH2)
cyclophilin D
sorting nexin 2 (SNX2)
progesterone-induced blocking factor 1 (PIBF1)
splicing factor, arginineserine-rich 3 (SFRS3)
BAG-family molecular chaperone regulator-2
myosin 1D
ARP2 (actin-related protein 2, yeast) homolog
HSPC274 protein
signal recognition particle 72 kDa
phosphoribosyl pyrophosphate amidotransferase
protein-coupled receptor kinase 6
gpi-anchored protein P137 (P137GP1)
possible global transcription activator SNF2L4
X-prolyl aminopeptidase (aminopeptidase P)-like (XPNPEPL)
proto-oncogene tyrosine-protein kinase FYN
U04045
NM_005038
AF043453
NM_006346
NM_003017
AF095192
AA621962
BE566290
NM_014145
AV702627
AI457120
BG423052
NM_005898
AI744900
NM_006523
S74774
⫺2.3
⫺2.3
⫺2.3
replication protein A1 (70-kDa) (RPA1)
programmed cell death 4 (PDCD4)
protein tyrosine phosphatase, receptor type, F
NM_002945
NM_014456
AI762627
⫺2.3
⫺2.2
⫺2.2
⫺2.2
⫺2.2
⫺2.1
⫺2.1
⫺2.1
⫺2.1
⫺2.0
septin 2 (NEDD5 protein homolog)
CGI-70 protein
ADAMTS-1 precursor
phosphoribosyl pyrophosphate synthetase 1 (PRPS1)
Fas apoptotic inhibitory molecule (FAIM)
3,2-trans-enoyl-CoA isomerase, mitochondrial precursor
calmodulin-dependent calcineurin a subunit, alpha isoform
programmed cell death 8 (apoptosis-inducing factor) (PDCD8)
septin 10 isoform 1
phosphatidylcholine 2-acylhydrolase (cPLA2)
AI191427
NM_016017
AK023795
NM_002764
NM_018147
BC002746
AA911231
NM_004208
BF966021
M68874
⫺2.0
multifunctional protein ADE2
NM_006452
intracellular signaling cascade
autoantigen associated with rheumatoid
arthritis
tumor antigen
protein folding
protein transport
blocking factor
mRNA splicing
protein folding, apoptosis regulator
calmodulin binding, actin binding
structural constituent of cytoskeleton
transmembrane proteins
ribonucleoprotein complex
glutamine metabolism
signal transduction
integral to plasma membrane
DNA binding
proteolysis and peptidolysis
calcium ion transport, intracellular signaling
cascade
DNA recombination
apoptosis
protein tyrosine phosphatase signaling
pathway
cell cycle
unknown
extracellular matrix
purine base metabolism
apoptosis
metabolism
calcium ion binding, calmodulin binding
apoptosis
cell cycle
calcium-dependent cytosolic phospholipase
A2
purine base biosynthesis
⫺2.9
⫺2.9
⫺2.8
⫺2.8
⫺2.8
⫺2.8
⫺2.8
⫺2.8
⫺2.8
⫺2.8
⫺2.7
⫺2.7
Fold change is the average fold decrease for the high SOCE clones. Although some genes have multiple representation on the microarray chip, only the set
with the highest fold change is shown.
in high clones), but the Q-PCR shows a more dramatic
elevation in the high clones than was predicted by the
microarray.
The data in Fig. 6 are a comparison between microarray
results and Q-PCR results for several genes the expression of
which decreases in the high clones and increases in the low
clones. The Q-PCR results for glutaminyl peptide cyclotransferase (QPCT) agree quantitatively with the microarray results
showing dramatic decreases in expression in the high clone and
dramatic increases in expression in the low clone. For G
Physiol Genomics • VOL
21 •
protein-coupled receptor (GPR)50 and 14-3-3 epsilon, there is
good qualitative agreement between the microarray data and
the Q-PCR data, with the observed decrease of GPR50 expression measured in high clones being less dramatic than predicted by the microarray assay, but the increase in the low
clone being more dramatic than predicted. For 14-3-3 epsilon,
the Q-PCR data showed a more dramatic decrease in the high
clone and a more dramatic increase in the low clone.
Low SOCE clones. The data in Fig. 7 show a comparison
between the microarray results and the Q-PCR results for
www.physiolgenomics.org
Downloaded from http://physiolgenomics.physiology.org/ by 10.220.32.247 on June 17, 2017
NM_005729
NM_003794
BG472176
⫺2.6
⫺2.6
peptidylprolyl isomerase F (cyclophilin F) (PPIF)
sorting nexin 4 (SNX4)
hydroxyacyl-CoA dehydrogenase3-ketoacyl-CoA thiolaseenoyl-CoA
hydratase (trifunctional protein), alpha subunit
mago-nashi (Drosophila) homolog, proliferation associated
phenylalanyl-trna synthetase alpha chain
cdk inhibitor p21 binding protein (TOK-1)
pre-mRNA processing factor 31 homolog
protein tyrosine kinase 9
heat shock 60-kDa protein 1 (chaperonin)
TUP1-like enhancer of split gene 1 (TUPLE1)
GDP dissociation inhibitor 2 beta
DEADH (Asp-Glu-Ala-AspHis) box polypeptide 18 (Myc regulated)
H-RYK receptor tyrosine kinase
villin 2 (ezrin)
pyrroline-5-carboxylate synthetase (glutamate gamma-semialdehyde
synthetase) (PYCS)
protein kinase C, delta (PRKCD)
follistatin-like 1 (FSTL1)
24
GENE EXPRESSION PROFILES IN CLONES WITH LOW AND HIGH SOCE
Table 3. List of genes that are upregulated in the low SOCE clones
Fold Change
12.3
9.9
9.6
8.6
8.1
7.9
7.6
7.3
7.0
Name of Gene
GenBank Accession No.
U82671
NM_005794
U10691
AK000345
NM_004988
BC005254
NM_001035
NM_018181
NM_000393
6.7
5.9
5.5
5.3
5.1
5.1
4.4
4.2
4.1
4.0
4.0
3.3
3.2
3.2
3.0
2.8
2.8
2.7
2.7
2.6
2.6
2.6
2.5
2.5
glutaminyl peptide cyclotransferase (glutaminyl cyclase) (QPCT)
melanoma antigen, family C, 1 (MAGEC1)
interferon induced transmembrane protein 3 (1-8U)
cystatin A (stefin A) (CSTA)
60S acidic ribosomal protein 1 (RPLP1)-LIKE gene
SH2 domain protein 1A, Duncan’s disease (DSHP)
transmembrane phosphatase with tensin homology (TPTE)
lectomedin-3 (LEC3)
hematopoietic cell-specific Lyn substrate 1 (HCLS1)
Cbpp300-interacting transactivator 1 (CITED1)
cytolysis inhibitor (CLI)
diaphanous (Drosophila, homolog) 2 (DIAPH2)
signal sequence receptor, gamma (SSR3)
butyrylcholinesterase (BCHE)
kinesin family member 5B (KIF5B)
glycine receptor beta subunit precursor (GLRB)
fumarate hydratase
f-box and leucine-rich repeat protein 7
imogen 38 (IMOGN38)
cyclin T2 (CCNT2)
epidermal growth factor receptor pathway substrate 8
lysyl oxidase-like 1 (LOXL1)
G protein-coupled receptor 50 (GPR50)
putative endothelin receptor type B-like protein
NM_012413
NM_005462
BF338947
NM_005213
NM_014253.1
AL022718
NM_013315
AF307080
NM_005335
NM_004143
M25915
NM_007309
NM_007107
NM_000055
NM_004521
AF094754
AA669797
AU145127
NM_005830
BE674119
NM_022772
NM_005576
NM_004224
U87460
2.5
2.5
2.5
2.4
2.4
2.3
2.3
2.3
2.3
2.3
2.3
2.3
2.1
Rab3 GTPase-activating protein (Rab3-GAP)
fucosyltransferase 4 [alpha (1,3) fucosyltransferase, myeloid-specific]
NTF2-related export protein NXT1 (NXT1)
MAB-21 (C. elegans)-LIKE 1 (MAB21L1)
transcription factor ELYS
kelch (Drosophila)-like 2 (Mayven) (KLHL2)
nucleosome assembly protein 1-like 3
zinc finger mynd domain containing protein 1
solute carrier family 25 member 15 (SLC25A15)
steroid-5-alpha-reductase, alpha polypeptide 1
cysteine-rich motor neuron 1
steroid sulfatase (microsomal), arylsulfatase C, isozyme S
jerky (mouse) homolog-like (JRKL)
AK022494
AF305083
AK023289
NM_005584
AL080144
NM_007246
NM_004538
NM_022743
NM_014252
NM_001047
BG546884
AI122754
NM_003772
2.1
2.1
2.1
2.1
2.0
2.0
2.0
2.0
non-metastatic 5 (NME5)
protocadherin 17 (PCDH17)
androgen-regulated short-chain dehydrogenasereductase 1
core-binding factor, runt domain, alpha subunit 2 cyclin D-related
R3H domain containing protein (R3HDM)
Similar to aspartyl-tRNA synthetase
transcription factor B2, mitochondrial
regulator of chromosome condensation (RCC1) and BTB (POZ)
domain containing protein 1
nel (chicken)-like 2 (NELL2)
nuclear receptor interacting protein 1 (NRIP1)
NM_003551
NM_014459
AF167438
NM_004349
NM_015361
BC000629
NM_022366
NM_018191
methylmalonate-semialdehyde dehydrogenase
translin (TSN)
Dmx-like 1 (DMXL1)
heart and neural crest derivatives expressed 1 (HAND1)
mineralocorticoid receptor (MR)
non-ocogenic Rho GTPase-specific GTP exchange factor
(proto-LBC)
AW612403
AI659180
NM_005509
NM_004821
NM_000901
AF127481
2.0
2.0
1.9
1.9
1.9
1.8
1.8
1.8
NM_006159
NM_003489
melanoma associated
carbohydrate metabolism
melanoma associated
carbohydrate metabolism
plasma membrane
heterophilic cell adhesion
signal transduction
signal transduction
extracellular matrix structural
constituent
protein modification
melanoma associated
immune response
cysteine protease inhibitor
translation
Duncan’s disease associated
signal transduction
neuropeptide signaling pathway
intracellular signaling cascade
regulation of transcription
apoptosis
cytokinesis
signal sequence binding
serine esterase
kinesin complex
synaptic transmission
negative regulation of cell cycle
unknown
structural constituent of ribosome
cell cycle
unknown
protein modification
signal transduction
G protein-coupled receptor protein
signaling pathway
signal transduction
gene expression regulation
intracellular protein transport
embryogenesis and morphogenesis
regulation of transcription
intracellular protein transport
chromatin assembly complex
unknown
amino acid metabolism
cell-cell signaling
regulation of cell growth
metabolism
central nervous system
development
anti-apoptosis
cell-cell connections in the brain
metabolism
regulation of transcription
nucleic acid binding
protein complex assembly
rRNA modification
protein binding
cell adhesion calcium ion binding
modulates transcriptional activity
of the estrogen receptor
metabolism
DNA recombination
superfamily of WD repeat proteins
development
signal transduction
signal transduction
Fold change is the average fold increase for the low SOCE clones. Although some genes have multiple representation on the microarray chip, only the set
with the highest fold change is shown.
Physiol Genomics • VOL
21 •
www.physiolgenomics.org
Downloaded from http://physiolgenomics.physiology.org/ by 10.220.32.247 on June 17, 2017
melanoma antigen family A2a (MAGEA2A)
alcohol dehydrogenase family member (HEP27)
melanoma-associated antigen 6 (MAGE-6 antigen)
dehydrogenase/reductase sdr family member 2
melanoma antigen, family A, 1 (MAGEA1)
C-type (calcium dependent, carbohydrate-recognition domain) lectin
ryanodine receptor 2 (cardiac) (RYR2)
zinc finger protein 532 (ZNF532)
collagen, type V, alpha 2 (COL5A2)
Function
25
GENE EXPRESSION PROFILES IN CLONES WITH LOW AND HIGH SOCE
Table 4. List of genes that are downregulated in the low SOCE clones
Name of Gene
GenBank Accession No.
⫺9.9
⫺7.0
⫺6.8
⫺6.6
⫺6.5
⫺6.3
⫺6.0
⫺5.9
⫺5.9
⫺5.5
bone morphogenetic protein 2 (BMP-2)
lymphotoxin beta receptor [TNFR superfamily, member 3 (LTBR)]
zinc finger protein 22 (KOX15)
tribbles homolog 2 (TRB2)
iroquois homeobox protein 4 (IRX4)
BarH-like homeobox 1 (BARX1)
putative zinc finger protein NY-REN-34 antigen
calcitonin-related polypeptide, beta
insulin receptor substrate 2 (IRS-2)
ras-related C3 botulinum toxin substrate 3 (RAC3)
AA583044
NM_002342
AA744771
NM_021643
NM_016358
NM_021570
BF055474
AA747379
BF700086
NM_005052
⫺5.3
⫺4.4
homeobox protein SIX2
solute carrier family 2 (facilitated glucose transporter), member 3
(SLC2A3)
adipose differentiation-related protein
protein AFIQ
adrenoleukodystrophy protein (ALDP)
homeobox protein MSX-2
myo-inositol 1-phosphate synthase A1
meningioma (disrupted in balanced translocation) 1 (MN1)
major histocompatibility complex, class II, DP beta 1 (HLADPB1)
sine oculis homeobox (Drosophila) homolog 2 (SIX2)
glutamate decarboxylase 1 (brain, 67 kDa) (GAD1), transcript
variant GAD25
transforming growth factor, beta 1 (TGF beta 1)
secreted protein, acidic, cysteine-rich (osteonectin) (SPARC)
NaH antiporter (APNH1)
transcription factor AP-2 alpha (activating enhancer-binding
protein 2 alpha) (TFAP2A)
Jagged2 (JAG2)
AF332197
NM_006931
cell growth and/or maintenance
signal transduction, apoptosis
regulation of transcription
protein amino acid phosphorylation
regulation of transcription
development
regulation of transcription
signal transduction
signal transduction
small GTPase-mediated signal
transduction
development
carbohydrate metabolism
BC005127
BC006471
NM_000033
D31771
AL137749
NM_002430
NM_002121
lipid particle
cell growth and/or maintenance
transport
skeletal development
phospholipid biosynthesis
negative regulation of cell cycle
immune responce
NM_016932
NM_013445
development
amino acid metabolism
BC000125
NM_003118
M81768
NM_003220
growth factor
calcium ion binding, collagen binding
sodium ion transport
signal transduction, development
AF029778
cell cycle, calcium ion binding, Notch
binding
heme oxidation
development
⫺4.3
⫺4.1
⫺4.0
⫺3.9
⫺3.7
⫺3.5
⫺3.4
⫺3.2
⫺3.0
⫺2.9
⫺2.9
⫺2.8
⫺2.8
⫺2.7
⫺2.6
⫺2.6
NM_002133
NM_002167
⫺2.6
⫺2.6
⫺2.6
heme oxygenase (decycling) 1 (HMOX1)
inhibitor of DNA binding 3, dominant negative helix-loop-helix
protein (ID3)
TED protein (TED)
butyrate response factor 2 (EGF-response factor 2)
type VI collagen alpha 2 chain precursor (COL6A2)
⫺2.5
⫺2.5
⫺2.5
⫺2.3
⫺2.2
⫺2.2
chromobox homolog 4 (Drosophila Pc class) (CBX4)
protein kinase, cAMP-dependent, catalytic, beta (PRKACB)
T-box transcription factor TBX1
retinol-binding protein 1, cellular (RBP1)
tyrosine protein kinase (CAK)
collagen, type IV, alpha 2
NM_003655
NM_002731
AF012130
NM_002899
L20817
AA909035
⫺2.2
⫺2.2
fibroblast growth factor 13 (FGF13)
nuclear factor of activated T-cells, cytoplasmic, calcineurindependent 1
frizzled 7 precursor (frizzled-7) (FZ-7)
major centromere autoantigen B
homcobox B6 (HOXB6)
phosphatidylinositol 3-kinase catalytic subunit p110 delta
zinc finger protein 282
phosphofructokinase, platelet (PFKP)
type IV collagen alpha (2) chain
NM_004114
U08015
⫺2.2
⫺2.2
⫺2.1
⫺2.1
⫺2.1
⫺2.1
⫺2.1
⫺2.0
⫺2.0
⫺2.0
⫺2.0
⫺2.0
⫺2.0
NM_015686
AI356398
AY029208
NM_003507
AL109804
NM_018952
U86453
AW130128
NM_002627
X05610
UDP-N-acetyl-alpha-D-galactosamine:polypeptide Nacetylgalactosaminyltransferase 6 (GalNAc-T6)
putative MAPK activating protein PM20,PM21
high-mobility group (nonhistone chromosomal) protein 17-like 3
MAD (mothers against decapentaplegic, Drosophila) homolog 7
(MADH7)
nuclear receptor binding protein (NRBP)
SHC (Src homology 2 domain-containing) transforming protein 1
Function
integral to membrane
cell proliferation
extracellular matrix organization and
biogenesis
apoptosis inhibitor
signal transduction
heart development
vitamin A metabolism
cell adhesion
extracellular matrix structural
constituent
growth factor
transcription factor
NM_007210
frizzled signaling pathway
satellite DNA binding
development
signal transduction
regulation of transcription
glycolysis
extracellular matrix structural
constituent
synthesis of oncofetal fibronectin
BG171020
BC001282
NM_005904
signal transduction
DNA binding
response to stress
NM_013392
AI809967
signal transduction
intracellular signaling cascade
Fold change is the average fold decrease for the low SOCE cloned. Although some genes have multiple representation on the microarray chip, only the set
with the highest fold change is shown.
Physiol Genomics • VOL
21 •
www.physiolgenomics.org
Downloaded from http://physiolgenomics.physiology.org/ by 10.220.32.247 on June 17, 2017
Fold Change
26
GENE EXPRESSION PROFILES IN CLONES WITH LOW AND HIGH SOCE
several genes that have a decreased expression level in the low
clones. The responses for bone morphogenetic protein
(BMP)-2 and lymphotoxin ␤-receptor (LTBR) match very well
between the microarray and the Q-PCR results, with BMP-2
showing no significant change in the high clones but a dramatic
decrease in the low clones, while LTBR shows a dramatic
decrease in the low clones and a dramatic increase in the high
clones. The data for ras-related C3 botulinum toxin substrate-3
(RAC3) show an example of a gene that responds in the low
clones as predicted by the microarray data, but the Q-PCR
picks up a significant elevation (note break in y-axis scale) in
the high clones that was missed in the microarray assay.
The data in Fig. 8 are a comparison between microarray
results and Q-PCR results for several genes the expression of
which increases dramatically in the low clones. Diaphanous
protein homolog 2 (DIAPH2) and C-type lectin show little
change in the high clones in both the microarray and the
Q-PCR assay but show dramatic increases in gene expression
in the low clones. Ribosomal protein, large, P1 (RPLP1)-like
shows good agreement between the microarray and the Q-PCR
results in the low clone and qualitative agreement in the high
clone (i.e., there is a small increase in the high clones relative
to the large change observed for the low clone).
Because fewer clones were analyzed for the low SOCE
condition than for the high SOCE condition, the confidence
level for gene changes associated with low SOCE was somewhat less than that for those associated with high SOCE. To
confirm that a decrease in SOCE is causative for the changes in
gene expression in the low SOCE clones, SOCE was reduced
by an alternate method and select genes were assayed by
real-time RT-PCR methods. Recently, our laboratory has demonstrated that a reduction of canonical transient receptor potential (TRPC)1 protein levels by siRNA techniques leads to a
65% reduction in SOCE in HEK-293 cells (unpublished observation), a result consistent with that observed after reduction
of TRPC1 levels in cultured hippocampal cells (58). The data
in Fig. 9 show that changes in gene expression, predicted by
the microarray results for the low SOCE clones, can be confirmed in HEK-293 cells in which SOCE is reduced by 65%
due to the expression of siRNA specific for TRPC1. Thus, for
six test genes [cyclin T2 (CCNT2), melanoma antigen A1
(MAGEA1), rab3-GTPase-activating protein (rab3-GAP), Rho
exchange factor (proto-LBC), meningioma (MN1), and zinc
finger protein 22 (KOX15)], the changes in mRNA expression
levels associated with decreased SOCE in the low clones were
duplicated when SOCE was reduced by expressing siRNA
specific for TRPC1.
Could Some of These Genes Be Regulators of SOCE?
It is possible that some of the signaling molecules that are
present on the list of genes in Tables 1–4 could be responsible
for the difference in SOCE between the high or low clones.
The task is to distinguish those genes that are downstream
from, and regulated by, an elevated Ca2⫹ signal from those that
are upstream of, and perhaps causative for, an elevated SOCE.
Fig. 6. Q-PCR confirmation for selected
genes whose expression levels decreased in
the high SOCE clones and increased in the
low SOCE clones. Expression levels measured in the microarray assay for glutaminyl
peptide cyclotransferase (QPCT), G proteincoupled receptor (GPR)50, and 14-3-3 epsilon in control, low SOCE clones, and high
SOCE clones are shown at left. Microarray
results for these 3 genes were confirmed by
Q-PCR, and the data are shown at right. As
indicated, the microarray and Q-PCR
showed qualitative agreement, but in some
instances the Q-PCR assay demonstrated
more dramatic changes than the microarray
assay predicted.
Physiol Genomics • VOL
21 •
www.physiolgenomics.org
Downloaded from http://physiolgenomics.physiology.org/ by 10.220.32.247 on June 17, 2017
Fig. 5. Quantitative (Q)-PCR confirmation for
selected genes whose expression levels increase in high SOCE clones. Expression levels
measured in the microarray assay for dihydrolipoamide branched-chain transacylase (DBT),
ATP1B8, and fibroblast growth factor
(FGF)-13 in control, low SOCE clones, and
high SOCE clones are shown at left. Microarray results for these 3 genes were confirmed by
Q-PCR, and the data are shown at right. As
indicated, the increases in gene expression in
the high SOCE clones predicted by the microarray assay for DBT, ATP1B8, and FGF-13
were confirmed by the real-time PCR assay. In
some cases, the Q-PCR assay demonstrated
more dramatic changes than were predicted by
the microarray assay (e.g., the decrease in
ATP1B8 in the low SOCE clones).
GENE EXPRESSION PROFILES IN CLONES WITH LOW AND HIGH SOCE
27
As discussed earlier, it seemed that some insight might be
gained by looking at genes that were elevated in four of five of
the clones. One gene that fell into this category, and is a
well-known signaling molecule, is IRS-2. Western blot data
indicate that IRS-2 protein levels are high in four of the five
clones compared with the levels in HEK cells (data not shown).
The data in Fig. 10A illustrate the difference in protein levels
among control HEK cells, L3 cells, and H36 cells. This
compares favorably with the differences in mRNA levels
predicted by the microarray assay (Fig. 10B). We wanted to
investigate whether reducing the high level of IRS-2 in the H36
clone would effect the level of SOCE. Thus we designed
constructs that, upon stable expression in cells, would express
hairpin siRNA specific for IRS-2. We stably transfected H36
cells with this siRNA construct and mixed all of the surviving
cells (in excess of 200 surviving clones) to eliminate possible
effects from clonal selection. We monitored the level of IRS-2
protein by Western blotting and found IRS-2 levels in the H36
clone to be reduced to approximately the level observed in
control HEK-293 cells (Fig. 11A). Protein expression was
reduced by ⬃80%, averaged over three experiments (Fig.
11B).
Next, we investigated whether a reduction in IRS-2 levels in
H36 cells could alter the level of SOCE. We observed that
reducing IRS-2 levels in the H36 cells led to a 60% reduction
in leak-corrected, thapsigargin-stimulated Ba2⫹ entry (Fig.
11C). Parallel experiments in the H24 clone gave similar
results (data not shown). Complementary studies were per-
formed in which IRS-2 was overexpressed in a low SOCE
clone. The results in Fig. 12 show that overexpression of IRS-2
in L29 cells resulted in a dramatic increase in SOCE. These
data suggest that IRS-2 does play a role in determining the
level of SOCE in these cells. Although much work is required
to determine where IRS-2 might be positioned in the signaling
pathway that regulates SOCE, the observed results do indicate
that it will be important to investigate some of the other
signaling molecules that appear in Tables 1–4 for their potential role as regulators of SOCE.
DISCUSSION
Implications of the Microarray Results
The results from the microarray experiments using cell
clones with differing levels of SOCE indicate that the level of
SOCE has a profound effect on the gene expression profile in
HEK-293 cells. The investigation of five high SOCE clones vs.
three low SOCE clones provides a higher level of confidence in
the cDNA microarray results associated with an increase in
SOCE than in the results associated with a reduction of SOCE.
However, the case for the association between low SOCE and
changes in gene profile is greatly strengthened by a supporting
set of experiments using an alternative method to decrease
SOCE. Real-time RT-PCR was used to confirm changes in
mRNA levels for a select number of genes predicted to respond
to a decrease in SOCE in HEK-293 cells expressing TRPC1
siRNA to reduce SOCE by 65% (unpublished observation).
Fig. 8. Q-PCR confirmation for selected
genes whose expression levels increased in
low SOCE clones. Expression levels measured in the microarray assay for diaphanous
protein homolog 2 (DIAPH2), C-type lectin,
and ribosomal protein, large, P1 (RPLP1) in
control, low SOCE clones, and high SOCE
clones are shown at left. Microarray results
for these 3 genes were confirmed by Q-PCR,
and the data are shown at right. As indicated,
the increases in gene expression in the low
SOCE clones predicted by the microarray
assay for DIAPH2, C-type lectin, and RPLP1
were confirmed by real-time PCR assay.
Physiol Genomics • VOL
21 •
www.physiolgenomics.org
Downloaded from http://physiolgenomics.physiology.org/ by 10.220.32.247 on June 17, 2017
Fig. 7. Q-PCR confirmation for selected
genes whose expression levels decreased in
low SOCE clones. Expression levels measured in the microarray assay for bone morphogenetic protein (BMP)-2, lymphotoxin
␤-receptor (LTBR), and ras-related C3 botulinum toxin substrate 3 (RAC3) in control,
low SOCE clones, and high SOCE clones
are shown at left. Microarray results for
these 3 genes were confirmed by Q-PCR,
and the data are shown at right. As indicated,
the decreases in gene expression in the low
SOCE clones predicted by the microarray
assay for BMP-2, LTBR, and RAC3 were
confirmed by the real-time PCR assay, as
was the increased LTBR expression in the
high SOCE clones.
28
GENE EXPRESSION PROFILES IN CLONES WITH LOW AND HIGH SOCE
This led to changes in gene expression for these six selected
genes in line with predictions from the cDNA microarray
results in the low SOCE clones.
The types of genes affected by changes in SOCE cover a
wide range on the functional spectrum, including signal transduction molecules, transcription factors, regulators of apoptosis, metabolic enzymes, cytoskeletal elements, and membrane
transporters. Although it is obviously impossible to discuss all
Fig. 10. Elevated endogenous insulin receptor substrate (IRS)-2 protein expression in high SOCE clone. Cells (HEK control, L3 clone, and H36 clone)
were grown on dishes as described in MATERIALS AND METHODS. A: Western
blot analysis. Cells were lysed in modified radioimmunoprecipitation (RIPA)
buffer, and Western blots were performed using monoclonal anti-IRS-2 antibody (1:1,000 dilution) and anti-mouse antibody (1:10,000 dilution) as the
secondary antibody. Western blots were repeated at least 3 times, using
different cell lysates. B: microarray analysis. Data represent average fold
changes in IRS-2 gene expression calculated for HEK control, L3, and H36
cells.
Physiol Genomics • VOL
21 •
of the implications that can be drawn from a complete review
of Tables 1–4, it is worthwhile to discuss several important
points.
Changes in the level of SOCE have a significant impact on
several genes that are related to cell cycle or cell proliferation.
There is extensive literature describing changes in Ca2⫹ levels
during proliferation and at specific points within the cell cycle,
as well as reports that imposed changes in intracellular Ca2⫹
levels can block the cell cycle at specific points. (4, 54) Thus
the genes listed below could serve as an important focus for
future investigations to clarify the role of Ca2⫹ in regulating
cell cycle and proliferation.
1) In HEK cell clones with high levels of SOCE, the G2 and
S phase expressed-1 (GTSE-1) gene expression is upregulated.
Murine GTSE-1 was cloned as a p53-inducible gene (11), and
it, as well as its human homolog, have been demonstrated to be
cell cycle regulated (37). The product of GTSE-1, which
localizes to microtubules, has been reported to delay G2/M
progression and to negatively regulate p53 function and p53dependent apoptosis (11). Given the previously described
changes in Ca2⫹ within the cell cycle and the reported effects
of Ca2⫹ on G2/M progression, it will be important to determine
whether GTSE-1 plays any role in cell cycle regulation attributed to changes in cytosolic Ca2⫹.
2) Cyclin T2 is another example of a cell cycle- or proliferation-related gene that is regulated by SOCE (upregulated in
the low clones). This protein is found complexed to cyclindependent kinase (CDK)9, which is known to phosphorylate
the protein product of the retinoblastoma gene (15). Although
the kinase activity of CDK9 does not appear to be cell cycle
dependent, there is recent evidence that it can be involved in
controlling cell growth and/or cell viability (13). Other studies
point to a role for CDK9 in differentiation, and, given the role
of Ca2⫹ in differentiation, it would be important to investigate
possible Ca2⫹-mediated changes in cyclin T2 in differentiating
cells (15).
3) MAD1L1, the human homolog of the yeast mitotic
checkpoint gene MAD1 (16, 28), is also regulated by SOCE.
MAD1L1 mRNA was observed to decrease in cells with high
SOCE. Although the precise function of MAD1L1 in the
www.physiolgenomics.org
Downloaded from http://physiolgenomics.physiology.org/ by 10.220.32.247 on June 17, 2017
Fig. 9. Comparison of expression levels for select genes in low SOCE clones vs. cells in which SOCE is suppressed by expression of small interfering (si)RNA
to TRPC1. Expression levels for MN1, KOX15, CCNT2, Rab3-GAP, Proto-LBC, and MAGEA1 genes were compared by the real-time RT-PCR method in 3
cell lines: HEK-293 cells, L29 cells, and siTRPC1 cells (HEK-293 cells stably expressing siRNA to TRPC1). A: expression levels of 2 genes (MN1 and KOX15)
are confirmed to be downregulated in L29 cells, as predicted by the microarray data (Table 4). They are also downregulated when SOCE is suppressed by siRNA
to TRPC1. B: expression levels of 4 genes (CCNT2, Rab3-GAP, proto-LBC, and MAGEA1) are confirmed to be upregulated in L29 cells, as predicted by the
microarray results (Table 3). They are also upregulated when SOCE is suppressed by siRNA to TRPC1.
GENE EXPRESSION PROFILES IN CLONES WITH LOW AND HIGH SOCE
mitotic spindle checkpoint remains unknown, this again would
be an interesting protein to explore in terms of the role of Ca2⫹
in regulating cell cycle.
4) In the high clones, a decrease in the expression of a cdk
inhibitor p21 binding protein (TOK-1) was observed. A
p21(Cip1/Waf1/Sdi1) protein is thought to negatively regulate
the cell cycle by inhibiting kinase activity of a variety of
cyclin-dependent kinases. TOK-1 is expressed at the G1/S
boundary of the cell cycle and is thus thought to be a new type
of CDK2 modulator (42). An investigation of whether TOK-1
plays a role in the Ca2⫹-mediated regulation of cell cycle is
warranted.
Changes in the level of SOCE have a significant impact on
several genes that are related to various disease states. 1) The
most striking observation in this regard is the large number of
melanoma-associated genes the expression levels of which are
increased when SOCE is decreased. In the low SOCE clones,
Physiol Genomics • VOL
21 •
an increase in gene expression was observed for melanoma
antigen family members MAGEA1, MAGEA2A, MAGEC1,
and MAGE6. The melanoma antigen genes were initially
identified in melanomas and were subsequently found to have
an expression pattern almost exclusively confined to tumors
(39). Given that distribution pattern and our finding that four
family members are upregulated in cells with low SOCE, it
would be important to investigate whether changes, especially
decreases, in SOCE levels occur in melanomas or other types
of tumors.
2) The tumor protein D52 is another cancer-associated gene
the expression of which is changed in cell clones with modified
SOCE. Its expression level is decreased in the high SOCE
clones. This gene was discovered in a differential screening of
a breast carcinoma cDNA library; subsequent studies showed
that this gene is overexpressed in ⬃40% of breast carcinomas (9).
3) The dyskeratosis congenita 1 gene is downregulated in
clones with high SOCE. The X-linked form of this disease,
which results in skin and bone marrow failure, is due to
mutations in the dyskerin gene. The dyskerin protein is a
component of small nucleolar ribonuclear protein particles as
well as the telomerase complex (35). The gene or genes
involved in the recessive forms of the disease still remain
unknown, so the regulation of dyskerin gene expression by
SOCE should be of interest to those who study this particular
disease.
4) Finally, the gene DSHP [Src homology (SH)2 domain
protein-1A; Duncan’s disease] is upregulated in clones with
low SOCE. DSHP encodes a single SH2 domain protein that is
mutated in some patients with X-linked lymphoproliferative
syndrome. Because DSHP is upregulated late in the immune
Fig. 12. Overexpression of IRS-2 on SOCE. L29 cells (low SOCE) were
transiently cotransfected with pcDNA3.1EYFP vector and pSMVhis-IRS2 as
described in MATERIALS AND METHODS. L29 cells transiently cotransfected with
pcDNA3.1EYFP and pSMVhis were used as a control (Mock). Cells were
circled based on their EYFP fluorescence when excited at 500 nM. SOCE was
determined as described in Fig. 2. Cells overexpressing IRS-2 had significantly
higher SOCE levels than did their controls (*P ⬍ 0.0001). The no. of cells
assayed is shown in parenthesis.
www.physiolgenomics.org
Downloaded from http://physiolgenomics.physiology.org/ by 10.220.32.247 on June 17, 2017
Fig. 11. Effect of suppressing IRS-2 protein levels on SOCE in H36 cells. H36
cells were stably transfected with pSilencer siIRS-2 as described in MATERIALS
AND METHODS. A: representative Western blots for H36 cells expressing
siIRS-2 compared with HEK control cells and H36 cells. In these experiments,
samples of 50 ␮g of total protein extract were applied to individual lanes. B:
protein expression in H36 cells stably transfected with siIRS-2 compared with
H36 cells. Data from 3 independent experiments were averaged. Western blots
were quantitated based on the relative spot intensities and are plotted as percent
control. *Significantly different from H36 control (P ⫽ 0.005). C: SOCE in
H36 cells stably transfected with siIRS-2 compared with H36 cells. SOCE was
determined as described in Fig. 2. As indicated, SOCE was inhibited by ⬃60%
in siIRS-2-transfected cells compared with their controls. *Significantly different from H36 control (P ⫽ 0.005). The no. of coverslips tested for SOCE
is shown in parenthesis, with each determination being the average response of
⬃800 cells.
29
30
GENE EXPRESSION PROFILES IN CLONES WITH LOW AND HIGH SOCE
Physiol Genomics • VOL
21 •
2) The programmed cell death 4 (PDCD4) gene was observed to decrease in clones having high levels of SOCE. This
gene was first discovered as one that is upregulated after
initiation of apoptosis in a number of different cell types, and
recent evidence suggests that PDCD4 may function as a tumor
suppressor gene (30). A recent paper (19) described the upregulation of PDCD4 in HEK-293 cells that were transfected
with the fas ligand gene. However, with other apoptotic signals, PDCD4 can be unaffected or even downregulated (40,
41), indicating that we do not fully understand the role of this
molecule in apoptosis.
3) The apoptosis-inducing factor (AIF, PDCD8) gene was
also observed to decrease in clones with high levels of SOCE.
AIF is expressed in both normal cells and a variety of cancer
cells. The mature protein is confined to the mitochondrial
intermembrane space, but in response to apoptosis-inducing
conditions, it is released to the cytosol to act by a caspaseindependent process to promote nuclear chromatin condensation and DNA fragmentation (12).
4) The Fas apoptotic inhibitory molecule (FAIM) is also
downregulated in cells with high levels of SOCE. This gene
was cloned by differential display comparing Fas-resistant and
Fas-sensitive primary murine B lymphocytes. FAIM is evolutionarily conserved and expressed in a wide range of tissues,
suggesting that its gene product plays a key physiological role.
It will be interesting to investigate why this apoptotic inhibitory molecule is downregulated along with the cell death genes
(listed above) when SOCE is increased.
A number of enzymes involved in metabolism are represented in the list of genes in Tables 1–4. These include
enzymes involved in carbohydrate metabolism such as galactokinase 1, glycerol kinase, phosphoglycerate kinase, solute
carrier family 2, phosphofructokinase, dehydrogenase/reductase SDR family member, and HEP27; enzymes involved in
amino acid metabolism such as serine hydroxymethyltransferase, phosphoserine aminotransferase, pyrroline-5-carboxylate synthetase, phosphoribosyl pyrophosphate amidotransferase, and glutamate decarboxylase 1; and enzymes involved
in lipid metabolism such as very-long-chain acyl-CoA synthetase homolog 2, hydroxyacyl-CoA dehydrogenase, 3,2trans-enoyl-CoA isomerase, dehydrocholesterol reductase, steroid sulfatase, and androgen-regulated short-chain dehydrogenase/reductase.
Changes in the level of SOCE had a dramatic effect on a
number of signaling molecules. These include protein kinases,
protein phosphatases, and transcription factors. We will only
discuss a subset of these, some of which have been demonstrated in other studies to be regulated by SOCE and some that
are of interest to investigate as potential regulators of SOCE.
A number of signaling genes whose levels of expression
were altered in our studies were also found to be Ca2⫹
regulated in other studies linking gene expression to SOCE
(18, 27). These include calcineurin, cAMP-dependent protein
kinase catalytic-␤, FLAME-1, c-myc, frizzled homolog 7, Sine
oculis homeobox homolog 2 (SIX2), and TGF-␤1. The number
of genes the expression of which is modified in the low SOCE
clones (150 genes either increasing or decreasing) is not out of
line with the number of genes proposed to respond to a
decrease in SOCE in the T lymphocyte study (18) mentioned
www.physiolgenomics.org
Downloaded from http://physiolgenomics.physiology.org/ by 10.220.32.247 on June 17, 2017
response, this form of immunodeficiency differs from most
others, where the mutations occur in a signaling molecule that
is hard wired into the signaling complex (47). Thus it will be
of great interest to determine whether changes in levels of
SOCE can play a role in Duncan’s disease.
Changes in the level of SOCE alter the expression levels of
several hormones, cytokines, and growth factors in HEK-293
cells. 1) In the cells with low levels of SOCE, a decreased
expression of BMP-2, a member of the transforming growth
factor (TGF)-␤ superfamily of polypeptide signaling molecules, was observed. Although BMPs were first discovered for
their osteogenic effects (56), they were later found to be
expressed in a wide range of vertebrate embryonic structures
(24) and to be involved in dorsal-ventral axis specifications
(21). Mice having null mutations in BMP-2 die early in
embryogenesis (62). In early reports, BMP-2 expression was
found to be controlled by both retinoic acid and cAMP (44),
but in recent studies in limb bud mesechymal cells, BMP-2
gene expression was increased by ionomycin and suppressed
by the calcineurin inhibitor cyclosporine A (53). These results,
coupled to our observation of a reduction of BMP-2 expression
in low SOCE clones, suggest that further study into the role of
store-operated channels in regulating BMP-2 would be important.
2) Another member of the TGF-␤ superfamily found to be
decreased in the clones with low SOCE is TGF-␤1. The TGF-␤
compounds have three well-characterized biological activities.
They inhibit growth in most cells except for chondrocytes and
osteoblasts, in which they stimulate growth. They have an
immunosuppressive effect by inhibiting T and B lymphocytes.
They also stimulate the deposition of collagens, fibronectin,
and proteoglycans (7). Additional studies will be required to
determine the importance of the downregulation of TGF-␤1
levels in HEK cells that have low levels of SOCE.
3) The level of gene expression for FGF-13 was also found
to be decreased in clones with low levels of SOCE. FGF-13 is
a member of the large family of FGFs that were originally
found to stimulate growth (20). They are now known to
regulate differentiation and a number of other physiological
functions in a wide variety of cells. They play an important
physiological role in development, maintenance of tissues, and
wound repair and have been postulated to play a pathophysiological role in arthritis, tumor proliferation, and arteriosclerosis. Because little is known about the regulation of gene
expression for this recently discovered FGF family member
(22), our observation that SOCE plays a role in regulating
FGF-13 mRNA levels is an important contribution to this area.
Changes in the level of SOCE in HEK cells had an effect on
a number of genes related to apoptosis. Given the rich, but
confusing, literature on the role of Ca2⫹ in apoptosis, there
should be considerable interest in apoptotic genes regulated by
SOCE.
1) The expression of Fas-associated death domain (FADD)like apoptosis regulator (FLAME-1) was observed to increase
in clones with high SOCE. FLAME-1, which contains FADD
death effector domain homology regions, can be recruited to
the Fas receptor complex, where it inhibits Fas/TNF receptor
(TNFR)-induced apoptosis, possibly by acting as a dominantnegative inhibitor (52).
GENE EXPRESSION PROFILES IN CLONES WITH LOW AND HIGH SOCE
Physiol Genomics • VOL
21 •
by SOCE. The fact that these profiles were determined for cells
under normal growth conditions (presence of serum), and in
the absence of pharmacological interventions, allows a more
accurate determination of the physiological importance of
store-operated channels. These results will be particularly useful in evaluating the role of SOCE in regulating genes involved
in cell proliferation and cell cycle. In addition to providing a
more physiological measure of the genes regulated downstream of SOCE, these studies provide several candidate genes
to investigate for their potential role in regulating store-operated channels. One of these, IRS-2, shows real promise as a
regulator of SOCE based on the inhibition of SOCE in H36
cells observed after suppression of IRS-2 levels by siRNA
techniques, and the increase in SOCE observed when IRS-2 is
overexpressed in a clone low in SOCE. Future studies can
investigate how IRS-2 might fit in with other proposed mechanisms for regulation of SOCE and explore the role of some of
the other potential regulators of SOCE.
ACKNOWLEDGMENTS
We acknowledge the generous assistance that Dr. Xinmin Li from our
Functional Genomics Core Facility provided in the analysis of the gene
microarray data. The IRS-2 expression construct was generously provided by
Dr. Xiao Jian Sun, Medicine Department, University of Chicago.
GRANTS
This work was supported by National Institute of General Medical Sciences
Grant GM-54500 and a supplemental grant for microarray analysis (GM54500-05S1) (to M. L. Villereal).
REFERENCES
1. Babnigg G, Bowersox SR, and Villereal ML. The role of pp60c-src in
the regulation of calcium entry via store-operated calcium channels. J Biol
Chem 272: 29434–29437, 1997.
2. Babnigg G, Heller B, and Villereal ML. Cell-to-cell variation in storeoperated calcium entry in HEK-293 cells and its impact on the interpretation of data from stable clones expressing exogenous calcium channels.
Cell Calcium 27: 61–73, 2000.
3. Babnigg G, Zagranichnaya T, Wu X, and Villereal ML. Differential
tyrosine phosphorylation of plasma membrane Ca2⫹-ATPase and regulation of calcium pump activity by carbachol and bradykinin. J Biol Chem
278: 14872–14882, 2003.
4. Berridge MJ. Calcium signalling and cell proliferation. Bioessays 17:
491–500, 1995.
5. Berridge MJ. The versatility and complexity of calcium signalling.
Novartis Found Symp 239: 52–64, 2001.
6. Bird GS and Putney JW Jr. Inhibition of thapsigargin-induced calcium
entry by microinjected guanine nucleotide analogues. Evidence for the
involvement of a small G-protein in capacitative calcium entry. J Biol
Chem 268: 21486–21488, 1993.
7. Blumenfeld I and Livne E. The role of transforming growth factor
(TGF)-␤, insulin-like growth factor (IGF)-1, and interleukin (IL)-1 in
osteoarthritis and aging of joints. Exp Gerontol 34: 821–829, 1999.
8. Bootman MD, Berridge MJ, and Roderick HL. Calcium signalling:
more messengers, more channels, more complexity. Curr Biol 12: R563–
R565, 2002.
9. Byrne JA, Tomasetto C, Garnier JM, Rouyer N, Mattei MG, Bellocq
JP, Rio MC, and Basset P. A screening method to identify genes
commonly overexpressed in carcinomas and the identification of a novel
complementary DNA sequence. Cancer Res 55: 2896–2903, 1995.
10. Chung KC, Sung JY, Ahn W, Rhim H, Oh TH, Lee MG, and Ahn YS.
Intracellular calcium mobilization induces immediate early gene pip92 via
Src and mitogen-activated protein kinase in immortalized hippocampal
cells. J Biol Chem 276: 2132–2138, 2001.
www.physiolgenomics.org
Downloaded from http://physiolgenomics.physiology.org/ by 10.220.32.247 on June 17, 2017
earlier (111 genes either increasing or decreasing), especially
when one considers that the cDNA microarray used for our
study had significantly more genes represented. Although there
are a few genes in common between our study and the
lymphocyte study, for the most part, SOCE appears to regulate
different populations of genes in the two cell types, a possibility that we considered at the outset of the investigation (see
INTRODUCTION). Compared with the data from the fibroblast
study (27), the 150 genes regulated by a decrease in SOCE are
much higher than the 29 genes seen to change. However, the
microarray used in that study only represented 1,200 cDNA
clones compared with the 22,000 cDNA clones represented on
the Affymetrix microarray.
1) Our initial hypothesis was that some of the signaling
genes that are high or low in the clones with high or low SOCE
might be setting the levels of SOCE rather than responding to
alterations in SOCE. This hypothesis was further supported by
the observation that there were not significant changes in levels
of TRPC genes in the high or low clones. Our results showing
that expression of IRS-2 is high in four of five high clones and
that expression of siRNA specific for IRS-2 inhibits SOCE in
H36 cells, together with the observation that overexpression of
IRS-2 in L29 cells elevates SOCE, support the hypothesis that
IRS-2 may be involved in the SOCE signaling pathway.
Because IRS-2 is clearly not causative for the high SOCE
levels in the H1 clone, it is worthwhile to discuss what other
signaling molecules listed in Tables 1–4 should be investigated
as potential regulators of SOCE. Previous studies based on
microinjection of GTP␥S (6, 17), microinjection of Clostridium C3 transferase, or overexpression of wild-type rho (60)
suggested that small-molecular-weight G proteins might be
involved in regulating SOCE. Thus it will be important to
further investigate the following genes on our lists: Rab3
GTPase-activating protein, ras-related C3 botulinum toxin substrate 3 (RAC3), rho GDP dissociation inhibitor (GDI)-␣, and
Rab1.
2) Previous data from our laboratory (1, 31) and from
several other laboratories (45, 46, 55) suggest that there is a
tyrosine phosphorylation step involved in regulating SOCE.
Thus it will be important to investigate those molecules on our
list that mediate changes in protein tyrosine phosphorylation
levels or that interact with tyrosine phosphorylated proteins.
These include the following: protein tyrosine kinase 9, H-Ryk
receptor tyrosine kinase, protein tyrosine phosphatase receptor
type F, CAK tyrosine protein kinase, protein tyrosine phosphatase nonreceptor type 4 (PTPN4), and SH2 domain protein 1A
(DSHP).
It is possible that some of the genes upregulated in high
SOCE may serve as negative regulators of SOCE, thereby
preventing cells from achieving even higher levels of SOCE.
Alternatively, it is possible that some of the genes upregulated
in the low clones may serve to prevent the SOCE from falling
to lower levels.
In summary, the selection of HEK-293 cell clones with high
or low levels of SOCE, and the suppression of SOCE levels by
the expression of siRNA specific for TRPC1, has enabled us to
begin asking important questions concerning the physiological
role of SOCE. The gene expression profiles for these cells have
allowed us to gain important information about genes regulated
31
32
GENE EXPRESSION PROFILES IN CLONES WITH LOW AND HIGH SOCE
Physiol Genomics • VOL
21 •
33. Liu W, Youn HD, and Liu JO. Thapsigargin-induced apoptosis involves
Cabin1-MEF2-mediated induction of Nur77. Eur J Immunol 31: 1757–
1764, 2001.
34. Ma R and Sansom SC. Epidermal growth factor activates store-operated
calcium channels in human glomerular mesangial cells. J Am Soc Nephrol
12: 47–53, 2001.
35. Marrone A and Mason PJ. Dyskeratosis congenita. Cell Mol Life Sci 60:
507–517, 2003.
36. Moneer Z and Taylor CW. Reciprocal regulation of capacitative and
non-capacitative Ca2⫹ entry in A7r5 vascular smooth muscle cells: only
the latter operates during receptor activation. Biochem J 362: 13–21, 2002.
37. Monte M, Collavin L, Lazarevic D, Utrera R, Dragani TA, and
Schneider C. Cloning, chromosome mapping and functional characterization of a human homologue of murine gtse-1 (B99) gene. Gene 254:
229–236, 2000.
38. Nakamura R, Ishida S, Ozawa S, Saito Y, Okunuki H, Teshima R, and
Sawada J. Gene expression profiling of Ca2⫹-ATPase inhibitor DTBHQ
and antigen-stimulated RBL-2H3 mast cells. Inflamm Res 51: 611–618,
2002.
39. Ohman Forslund K and Nordqvist K. The melanoma antigen genes—
any clues to their functions in normal tissues? Exp Cell Res 265: 185–194,
2001.
40. Onishi Y, Hashimoto S, and Kizaki H. Cloning of the TIS gene
suppressed by topoisomerase inhibitors. Gene 215: 453–459, 1998.
41. Onishi Y and Kizaki H. Molecular cloning of the genes suppressed in
RVC lymphoma cells by topoisomerase inhibitors. Biochem Biophys Res
Commun 228: 7–13, 1996.
42. Ono T, Kitaura H, Ugai H, Murata T, Yokoyama KK, Iguchi-Ariga
SM, and Ariga H. TOK-1, a novel p21Cip1-binding protein that cooperatively enhances p21-dependent inhibitory activity toward CDK2 kinase. J Biol Chem 275: 31145–31154, 2000.
43. Putney JW Jr. A model for receptor-regulated calcium entry. Cell
Calcium 7: 1–12, 1986.
44. Rogers MB, Rosen V, Wozney JM, and Gudas LJ. Bone morphogenetic
proteins-2 and -4 are involved in the retinoic acid-induced differentiation
of embryonal carcinoma cells. Mol Biol Cell 3: 189–196, 1992.
45. Rosado JA, Graves D, and Sage SO. Tyrosine kinases activate storemediated Ca2⫹ entry in human platelets through the reorganization of the
actin cytoskeleton. Biochem J 351: 429–437, 2000.
46. Sargeant P, Farndale RW, and Sage SO. ADP- and thapsigargin-evoked
Ca2⫹ entry and protein-tyrosine phosphorylation are inhibited by the
tyrosine kinase inhibitors genistein and methyl-2,5-dihydroxycinnamate in
fura-2-loaded human platelets. J Biol Chem 268: 18151–18156, 1993.
47. Satterthwaite AB, Rawlings DJ, and Witte ON. DSHP: a “power bar”
for sustained immune responses? Proc Natl Acad Sci USA 95: 13355–
13357, 1998.
48. Schilling WP, Rajan L, and Strobl-Jager E. Characterization of the
bradykinin-stimulated calcium influx pathway of cultured vascular endothelial cells. Saturability, selectivity, and kinetics. J Biol Chem 264:
12838–12848, 1989.
49. Schwarz G, Droogmans G, and Nilius B. Multiple effects of SK&F
96365 on ionic currents and intracellular calcium in human endothelial
cells. Cell Calcium 15: 45–54, 1994.
50. Shalabi A, Zamudio F, Wu X, Scaloni A, Possani LD, and Villereal
ML. Tetrapandins, a new class of scorpion toxins that specifically inhibit
store-operated calcium entry in human embryonic kidney-293 cells. J Biol
Chem 279: 1040–1049, 2004.
51. Soergel DG, Yasumoto T, Daly JW, and Gusovsky F. Maitotoxin
effects are blocked by SK&F 96365, an inhibitor of receptor-mediated
calcium entry. Mol Pharmacol 41: 487–493, 1992.
52. Srinivasula SM, Ahmad M, Ottilie S, Bullrich F, Banks S, Wang Y,
Fernandes-Alnemri T, Croce CM, Litwack G, Tomaselli KJ, Armstrong RC, and Alnemri ES. FLAME-1, a novel FADD-like anti-apoptotic molecule that regulates Fas/TNFR1-induced apoptosis. J Biol Chem
272: 18542–18545, 1997.
53. Tomita M, Reinhold MI, Molkentin JD, and Naski MC. Calcineurin
and NFAT4 induce chondrogenesis. J Biol Chem 277: 42214–42218,
2002.
54. Villereal ML and Byron KL. Calcium signals in growth factor signal
transduction. Rev Physiol Biochem Pharmacol 119: 67–121, 1992.
www.physiolgenomics.org
Downloaded from http://physiolgenomics.physiology.org/ by 10.220.32.247 on June 17, 2017
11. Collavin L, Monte M, Verardo R, Pfleger C, and Schneider C.
Cell-cycle regulation of the p53-inducible gene B99. FEBS Lett 481:
57–62, 2000.
12. Daugas E, Nochy D, Ravagnan L, Loeffler M, Susin SA, Zamzami N,
and Kroemer G. Apoptosis-inducing factor (AIF): a ubiquitous mitochondrial oxidoreductase involved in apoptosis. FEBS Lett 476: 118–123,
2000.
13. de Falco G and Giordano A. CDK9 (PITALRE): a multifunctional
cdc2-related kinase. J Cell Physiol 177: 501–506, 1998.
14. de la Rosa LA, Alfonso A, Vilarino N, Vieytes MR, Yasumoto T, and
Botana LM. Maitotoxin-induced calcium entry in human lymphocytes:
modulation by yessotoxin, Ca(2⫹) channel blockers and kinases. Cell
Signal 13: 711–716, 2001.
15. De Luca A, De Falco M, Baldi A, and Paggi MG. Cyclin T: three forms
for different roles in physiological and pathological functions. J Cell
Physiol 194: 101–107, 2003.
16. Elledge SJ. Cell cycle checkpoints: preventing an identity crisis. Science
274: 1664–1672, 1996.
17. Fasolato C, Hoth M, and Penner R. A GTP-dependent step in the
activation mechanism of capacitative calcium influx. J Biol Chem 268:
20737–20740, 1993.
18. Feske S, Giltnane J, Dolmetsch R, Staudt LM, and Rao A. Gene
regulation mediated by calcium signals in T lymphocytes. Nat Immun 2:
316–324, 2001.
19. Goke A, Goke R, Knolle A, Trusheim H, Schmidt H, Wilmen A,
Carmody R, Goke B, and Chen YH. DUG is a novel homologue of
translation initiation factor 4G that binds eIF4A. Biochem Biophys Res
Commun 297: 78–82, 2002.
20. Gospodarowicz D, Jones KL, and Sato G. Purification of a growth factor
for ovarian cells from bovine pituitary glands. Proc Natl Acad Sci USA 71:
2295–2299, 1974.
21. Graff JM. Embryonic patterning: to BMP or not to BMP, that is the
question. Cell 89: 171–174, 1997.
22. Greene JM, Li YL, Yourey PA, Gruber J, Carter KC, Shell BK,
Dillon PA, Florence C, Duan DR, Blunt A, Ornitz DM, Ruben SM,
and Alderson RF. Identification and characterization of a novel member
of the fibroblast growth factor family. Eur J Neurosci 10: 1911–1925,
1998.
23. He H, McColl K, and Distelhorst CW. Involvement of c-Fos in signaling
grp78 induction following ER calcium release. Oncogene 19: 5936–5943,
2000.
24. Hogan BL. Bone morphogenetic proteins: multifunctional regulators of
vertebrate development. Genes Dev 10: 1580–1594, 1996.
25. Hong SJ and Chang CC. Facilitation of nicotinic receptor desensitization
at mouse motor endplate by a receptor-operated Ca2⫹ channel blocker,
SK&F 96365. Eur J Pharmacol 265: 35–42, 1994.
26. Hong SJ, Lin WW, and Chang CC. Inhibition of the sodium channel by
SK&F 96365, an inhibitor of the receptor-operated calcium channel, in
mouse diaphragm. J Biomed Sci 1: 172–178, 1994.
27. Jenkins RE, Hawley SR, Promwikorn W, Brown J, Hamlett J, and
Pennington SR. Regulation of growth factor-induced gene expression by
calcium signalling: integrated mRNA and protein expression analysis.
Proteomics 1: 1092–1104, 2001.
28. Jin DY, Spencer F, and Jeang KT. Human T cell leukemia virus type 1
oncoprotein Tax targets the human mitotic checkpoint protein MAD1. Cell
93: 81–91, 1998.
29. Kwan CY and Putney JW Jr. Uptake and intracellular sequestration of
divalent cations in resting and methacholine-stimulated mouse lacrimal
acinar cells. Dissociation by Sr2⫹ and Ba2⫹ of agonist-stimulated divalent
cation entry from the refilling of the agonist-sensitive intracellular pool.
J Biol Chem 265: 678–684, 1990.
30. Lankat-Buttgereit B and Goke R. Programmed cell death protein 4
(pdcd4): a novel target for antineoplastic therapy? Biol Cell 95: 515–519,
2003.
31. Lee KM, Toscas K, and Villereal ML. Inhibition of bradykinin- and
thapsigargin-induced Ca2⫹ entry by tyrosine kinase inhibitors. J Biol
Chem 268: 9945–9948, 1993.
32. Li WP, Tsiokas L, Sansom SC, and Ma R. Epidermal growth factor
activates store-operated Ca2⫹ channels through an inositol 1,4,5-trisphosphate-independent pathway in human glomerular mesangial cells. J Biol
Chem 279: 4570–4577, 2004.
GENE EXPRESSION PROFILES IN CLONES WITH LOW AND HIGH SOCE
55. Vostal JG, Jackson WL, and Shulman NR. Cytosolic and stored
calcium antagonistically control tyrosine phosphorylation of specific
platelet proteins. J Biol Chem 266: 16911–16916, 1991.
56. Wozney JM, Rosen V, Celeste AJ, Mitsock LM, Whitters MJ, Kriz
RW, Hewick RM, and Wang EA. Novel regulators of bone formation:
molecular clones and activities. Science 242: 1528–1534, 1988.
57. Wu X, Babnigg G, Zagranichnaya T, and Villereal ML. The role of
endogenous human Trp4 in regulating carbachol-induced calcium oscillations in HEK-293 cells. J Biol Chem 277: 13597–13608, 2002.
58. Wu X, Zagranichnaya TK, Gurda GT, Eves EM, and Villereal ML. A
TRPC1/TRPC3-mediated increase in store-operated calcium entry is re-
33
quired for differentiation of H19-7 hippocampal neuronal cells. J Biol
Chem 279: 43392–43402, 2004.
59. Yang H, Sun X, Wang Z, Ning G, Zhang F, Kong J, Lu L, and
Reinach PS. EGF stimulates growth by enhancing capacitative calcium
entry in corneal epithelial cells. J Membr Biol 194: 47–58, 2003.
60. Yao Y, Ferrer-Montiel AV, Montal M, and Tsien RY. Activation of
store-operated Ca2⫹ current in Xenopus oocytes requires SNAP-25 but not
a diffusible messenger. Cell 98: 475–485, 1999.
62. Zhang H and Bradley A. Mice deficient for BMP2 are nonviable and
have defects in amnion/chorion and cardiac development. Development
122: 2977–2986, 1996.
Downloaded from http://physiolgenomics.physiology.org/ by 10.220.32.247 on June 17, 2017
Physiol Genomics • VOL
21 •
www.physiolgenomics.org