Original Article Open Access
Copyright ©2010 Baishideng Publishing Group Co., Limited. All rights reserved.
World J Stem Cells. Dec 26, 2010; 2(6): 127-140
Published online Dec 26, 2010. doi: 10.4252/wjsc.v2.i6.127
Gene targeting and Calcium handling efficiencies in mouse embryonic stem cell lines
Solomon Mamo, Julianna Kobolak, Andras Dinnyes, Genetic Reprogramming Group, Agricultural Biotechnology Center, Szent-Gyorgyi Albert ut. 4, H-2100 Gödöllő, Hungary
Solomon Mamo, Lyons Research Farm, University College Dublin, Newcastle, Co Dublin, Ireland
Istvan Borbíró, Tamás Bíró, Department of Physiology, Research Center for Molecular Medicine, Medical and Health Science Center, University of Debrecen, Nagyerdei krt. 98, H-4032 Debrecen, Hungary; Abiol Ltd., Nagyerdei krt. 98, H-4032 Debrecen, Hungary
Istvan Bock, BioTalentum Ltd., Aulich l. 26, Gödöllő, Hungary
Andras Dinnyes, Molecular Animal Biotechnology Laboratory, Szent Istvan University, Páter K. u. 1, H-2103 Gödöllő, Hungary
Author contributions: Mamo S participated in the experimental design, coordinated molecular biology activities, performed real time PCR and microarray analysis, interpretation of the data and was the primary author of the manuscript; Kobolak J conceived the experiment, performed the stem cell culture, Southern blot, and participated in manuscript preparation; Borbíró I performed the Ca2+ assay measurement; Bíró T performed Ca2+ assay data analysis and participated in manuscript preparation; Bock I performed the real time PCR experiment and data analysis for the various Ca2+ receptors; Dinnyes A supervised the study design, execution, analysis, and approved the final version.
Supported by EU FP6 (TEAMOHOLIC “MEXT-CT-2003-509582”, “MEDRAT” LSHG-CT-2006-518240, “CLONET” MRTN-CT-2006-035468), EU FP7 (“PartnErS” PIAPGA-2008-218205; “Plurisys” HEALTH-F4-2009-223485; “RESOLVE” FP7-HEALTH-F4-2008-202047), NKFP_07_1-ES2HEART-HU (OM-00202-2007), Hungarian-Chinese NKTH TET, No. CN-56/2007 and “Plurabit” NKTH TET-09-1-2010-0007
Correspondence to: Andras Dinnyes, PhD, DSc, Professor, Molecular Animal Biotechnology Laboratory, Szent Istvan University, Páter K. u. 1, H-2103 Gödöllő, Hungary. andrasdinnyes@yahoo.com
Telephone: +36-20-5109632 Fax: +36-28-526151
Received: March 24, 2010
Revised: October 5, 2010
Accepted: October 12, 2010
Published online: December 26, 2010


AIM: To compare gene targeting efficiencies, expression profiles, and Ca2+ handling potentials in two widely used mouse embryonic stem cell lines.

METHODS: The two widely used mouse embryonic stem cell lines, R1 and HM-1, were cultured and maintained on Mitomycin C treated mouse embryonic fibroblast feeder cell layers, following standard culture procedures. Cells were incubated with primary and secondary antibodies before fluorescence activated cell sorting analysis to compare known pluripotency markers. Moreover, cells were harvested by trypsinization and transfected with a kinase-inactive murine Tyk2 targeting construct, following the BioRad and Amaxa transfection procedures. Subsequently, the cells were cultured and neomycin-resistant cells were picked after 13 d of selection. Surviving clones were screened twice by polymerase chain reaction (PCR) and finally confirmed by Southern blot analysis before comparison. Global gene expression profiles of more than 20 400 probes were also compared and significantly regulated genes were confirmed by real time PCR analysis. Calcium handling potentials of these cell lines were also compared using various agonists.

RESULTS: We found significant differences in transfection efficiencies of the two cell lines (91% ± 6.1% vs 75% ± 4.2%, P = 0.01). Differences in the targeting efficiencies were also significant whether the Amaxa or BioRad platforms were used for comparison. We did not observe significant differences in the levels of many known pluripotency markers. However, our genome-wide expression analysis using more than 20 400 spotted cDNA arrays identified 55 differentially regulated transcripts (P < 0.05) implicated in various important biological processes, including binding molecular functions (particularly Ca2+ binding roles). Subsequently, we measured Ca2+ signals in these cell lines in response to various calcium agonists, both in high and low Ca2+ solutions, and found significant differences (P < 0.05) in the regulation of Ca2+ homeostasis between the investigated cell lines. Then we further compared the detection and expression of various membrane and intracellular Ca2+ receptors and similarly found significant (P < 0.05) variations in a number of calcium receptors between these cell lines.

CONCLUSION: Results of this study emphasize the importance of considering intrinsic cellular variations, during selection of cell lines for experiments and interpretations of experimental results.

Key Words: Embryonic stem cells, Microarray, Calcium, Agonists, Transfection, Cell culture, Pluripotency, Gene targeting


Embryonic stem cells (ESCs) are derived from the inner cell mass of the developing blastocyst with a retained potential to self-renew and to differentiate into diverse cell lineages[1,2]. Currently mouse ESCs are used in various research applications, including gene targeting, which involves the transfer of a designed alteration in an exogenous DNA sequence to the cognate DNA sequence in the living cell genome via homologous recombination[3]. Generation of knockout mouse models by targeted disruption of essential genes provides useful insights into genes that regulate development and allows investigators to dissect molecular developmental mechanisms[3,4]. In an effort to understand the therapeutic applications of stem cells, mouse models have been created for a number of human genetic diseases, and gene targeting in stem cells has also been common practice. The various methods of gene transfer technology and comparative efficiencies were described elsewhere[5-7]. However, most studies have focused mainly on comparing the efficiency of different gene delivery techniques, parameters or phenotypes of the offspring carrying the mutant gene. In the earlier studies, cell line differences were seldom described, although some reports acknowledged the existence of differences[8].

Despite the similarities observed in the expression of some classical pluripotent stem cell markers, such as Pou5f1 (formerly Oct4), Nanog and alkaline phosphatase (ALP)[8,9] variations were also evident between ESCs of different species[10-12], somatic SCs of different tissue types[13,14] and distinct ESC lines derived from the same species[9]. Previous studies using different mouse ESC lines have shown variations in growth performance and in some other phenotypes[9,15]. Undoubtedly, these studies have made significant contributions in advancing the field by unravelling the effects of various factors on the phenotype and performance of the cells. Better understanding is required to harness cellular potency, as it is fundamental in biology and also critical for future therapeutic uses of stem cells[16]. The HM-1 and R1 ESCs are two ESC lines of the same mouse strain (strain 129, but different sublines) that are widely used to decipher ESC biology and various applications.

We transfected these ESCs with the non-isogenic DNA construct and compared the efficiencies of homologous recombination. The significant differences observed during this initial targeting efficiency comparison lead us, subsequently, to compare the genome-wide gene expression profiles of these ESCs, in order to further compare the intracellular calcium handling potentials and expression of calcium receptors. Calcium, an intracellular second messenger, is known to be a growth-regulating divalent cation[17], and a ubiquitous intracellular signal responsible for controlling numerous cellular processes[18]. Here we demonstrate significant differences in the gene targeting efficiency, the gene expression profiles, and the intracellular Ca2+ handling potentials of these embryonic stem cell lines. The results of the current study reveal significant variations in the examined parameters, and underscore the importance of understanding cellular variations (efficiency) for better results in gene targeting and other in vitro culture applications of the cells.


Materials for the cell culture, sample preparation and hybridizations, unless otherwise indicated were purchased from Invitrogen (Carlsbad, USA), whilst nerve growth factor (NGF), epidermal growth factor (EGF), and caffeine were obtained from the same source (Invitrogen). Other materials for Ca2+ measurement and real time polymerase chain reaction (PCR) analysis, unless otherwise indicated, were purchased from Sigma-Aldrich Chem. Inc. (St. Louis, USA).

Embryonic stem cells and culture conditions

The R1[19] mouse ESC, at passage 9, was kindly provided by Mount Sinai Hospital and Samuel Lunenfeld Research Institute, Canada. The mouse HM-1[20] ESC, at passage 19, was kindly provided by Roslin Institute, UK. The genetic backgrounds of both ESC lines are described in Table 1, while their developmental potentials were earlier tested and confirmed by production of chimeras with germline transmission[21,22]. These ESC lines were further cultured and maintained on Mitomycin C treated (10 μg/mL Mitomycin C in standard ESC medium for 150 min) mouse embryonic fibroblast (MEF) feeder cell layers. Cells were grown in standard ESC medium changed daily [high glucose DMEM supplemented with 0.1 mmol/L 2-mercaptoethanol (Sigma-Aldrich), fetal bovine serum (15% v/v; HyClone, Logan, USA), 1000 U/mL ESGRO-LIF (CHEMICON International, Temecula, USA) and antibiotics (Penicillin: 50 U/mL, Streptomycin: 50 μg/mL)]. When in culture, the cells were routinely maintained at 37°C in humidified air containing 5% CO2 in an incubator and passaged every other day. For RNA preparation, 2 × 106 cells/mL were lysed in RLT buffer (Qiagen, Düsseldorf, Germany) and frozen in multiple vials prior to further experiments.

Table 1 Some characteristics of R1 and HM-1 embryonic stem cells and fluorescence activated cell sorting analysis.
Cell lineR1HM-1
Genetic background(129X1/SvJ x 129S1/Sv) F1 (+/p+tyr-cKitlSl-J/+)1129/Ola2
Culture conditionsDMEM3 + 15%FBS + 1000 U ESGRO mLIFDMEM3 + 15%FBS + 1000 U ESGRO mLIF
Cell doubling (in our hands)14-16 h12-14 h
Germline competence4++
In vitro differentiation to form three germ layers5++
Karyotype (FISH)XY (often XO)XY more stabile
Euploidy (hoechst staining)78% ± 4.4%71% ± 5.3%
Telomerase (PCR)++
FACS analysis (mean ± SE)
Pou5f1 (FACS)90.6% ± 5.8%88.8% ± 5.7%
Nanog (FACS)72.5% ± 6.2%68.7% ± 2.8%
SSEA-1 (FACS)58.8% ± 4.1%65.1% ± 3.1%
Sox2 (FACS)97.4% ± 1.2%98.8% ± 0.2%
ALP (enzyme assay)++
Fluorescence activated cell sorting and pluripotency markers analysis

In preparation for fluorescence activated cell sorting (FACS), cells were dissociated with cell dissociation buffer (Invitrogen), washed and fixed with 4% PFA (Paraformaldehyde) for 15 min. Following fixation, the cells were permeabilized with 0.1% Triton-X 100, and 0.1% BSA-containing (Bovine serum albumin) PBS (Phosphate buffered saline). In order to check the existence of some classical pluripotency marker genes [Pou5f1 (Oct4), Nanog, Sox-2, and Fut4 (SSEA-1)], cells were incubated with primary antibodies [(mouse polyclonal Oct4 (1:200), goat polyclonal nanog (1:200) and goat polyclonal Sox-2 (1:200), Santa Cruz Biotechnology, Santa Cruz, USA); mouse monoclonal SSEA-1 (1:100), MC-480, Developmental Studies Hybridoma Bank, Iowa City, USA)] at 37°C for 2 h. ESCs were incubated with fluorescent secondary antibodies [anti-mouse IgM-Cy3 (1:200); anti-mouse IgG-FITC (1:200), anti-goat IgG-Cy3 (1:200), and anti-goat IgG-Cy5 (1:200), respectively, from JacksonImmuno Research Laboratories, West Grove, USA] for 1 h at room temperature. Nuclei were counterstained with bisbenzamide (Hoechst 333258, Sigma). Cells were washed, pelleted and resuspended in 1 mL PBS, and analyzed within 12 h, with FACS-CALIBUR flow cytometer (Becton Dickinson, Franklin Lakes, USA) using its own software.

Embryonic stem cells transfection

To transfect R1 and HM-1 ESCs and compare the homologous recombination efficiency, a kinase-inactive murine Tyk2 targeting construct was kindly provided by Dr. Mathias Mueller (Institute of Animal Breeding and Genetics, Veterinary University of Vienna, Vienna, Austria) and used with intact cells. The construct was made from mouse C57B1/6 strain DNA, and thus non-isogenic for both R1 and HM-1 ESC lines which derived from 129 mouse sub strains. For transfection, cells were harvested by trypsinization (5 min in 0.25% trypsin-EDTA solution) before following the established procedures of the Bio-Rad (Bio-Rad laboratories, Hercules, USA) or Amaxa (Amaxa Biosystems, Cologne, Germany) transfection systems. Briefly, for the Bio-Rad system, 3 × 107 cells with 10-μg linearized vector were resuspended in 0.8 mL of electroporation buffer [in mmol/L; 20 HEPES (pH 7.0), 137 NaCl, 5 KCl, 0.7 NaHPO4, 6 glucose, and 0.1 of 2-mercaptoethanol] and electroporated with a single pulse (240 V and 500 μF), using Gene pulser II (Bio-Rad) in a 4-mm cuvette. After electroporation, cells were incubated at room temperature for 10 min before plating. Similarly, for the nucleofection of cells using the Amaxa system, 3 × 106 cells and 5-μg linearized vector were resuspended in 100 μL nucleofector solution (mouse ES cell nucleofector Kit, Amaxa), and three different Amaxa programs (A23, A24 and A30) were compared for the efficiency. As a control, 5 μg EGFP (Enhanced Green Fluorescent Protein) plasmid DNA (Amaxa) was used with the same electroporation and nucleofection (program A23) protocols, as well for the homologous recombination assays.

Following electroporation or nucleofection, cells were plated onto antibiotic-free, mitotically inactivated neomycin-resistant MEF feeder layers, in ESC culture medium. Neomycin selection was started 24 h post-electroporation or nucleofection, by applying 200 μg/mL of G418 (Sigma) in culture medium and neomycin-resistant cells were picked after 13 d of selection. Surviving clones were screened twice by PCR and correct targeting was further confirmed by Southern blot analysis of the genomic DNA. Finally, the results of different transfection systems and programs were compared for the percentage of positive clones (for the construct), after neomycin selection.

Southern blot analysis and PCR positive clone selection

To confirm the PCR positive clones for homologous recombination, Southern blot hybridization was carried out with DIG system (Roche Applied Science, Basel, Switzerland) by following the manufacturer’s protocol. Briefly, 20 μg genomic DNA from individual drug-selected colonies was digested with BamHI (Invitrogen), and screened on 1% agarose gel. Gels were blotted on Hybond-N+ membrane (GE Healthcare Bio-Sciences, Uppsala, Sweden) overnight in 20 × SSC buffer (Sigma). As a probe, the 472 bp long PCR fragments were labeled with DIG-11-dUTP using the PCR DIG Probe Synthesis Kit (Roche), and hybridized to the membrane at 45°C overnight in the DIG Easy Hyb solution (Roche). Detection was performed using the DIG Wash and Block Buffer Set (Roche). Dig labeled probe was detected with Anti-Digoxigenin-AP Fab fragment (Roche) and visualized with NBT/BCIP Solution (Roche).

Microfluorimetric measurements of intracellular calcium signaling ([Ca2+]i)

For this experiment, adenosine 5′-triphosphate (ATP), bradykinin, histamine, thapsigargin, nerve growth factor (NGF), epidermal growth factor (EGF), and caffeine were used. Cells were seeded in 96-well black-well/clear-bottom plates (Greiner Bio-One, Frickenhausen, Germany) at a density of 40 000 cells per well in ESC medium and cultured at 37°C for 24-48 h. The cells were incubated with medium containing the cytoplasmic calcium indicator 2 μmol/L Fluo-4 AM (Invitrogen) at 37°C for 40 min. Then cells were washed four times with and finally cultured in Hank’s solution (in mmol/L; 136.8 NaCl, 5.4 KCl, 0.34 Na2HPO4, 0.44 KH2PO4, 0.81 MgSO4, 1.26 CaCl2, 5.56 glucose, 4.17 NaHCO3, pH 7.2) containing 1% bovine serum albumin and 2.5 mmol/L Probenecid for 30 min at 37°C. The plates were then placed to a FlexStation II384 fluorimetric image plate reader (FLIPR, Molecular Devices, Sunnyvale, USA), and changes in [Ca2+]i (reflected by changes in fluorescence; lEX = 494 nm, lEM = 516 nm) of the above Hank’s medium was recorded. Ca-responses were also measured in low Ca (0.6 mmol/L) Hank’s solution. When calculating dose-response curves[23] data were fitted to the Hill equation: B/Bmax = [X]n/([EC50]n + [X]n).

Where B is the actual fluorescence value, Bmax is the theoretical maximum of B, × is the ligand in question, and n is the Hill coefficient.

Experiments were performed in quadruplets and the average values (mean ± SE) were used for calculations. When applicable, data were analyzed using a two-tailed un-paired t-test and P < 0.05 values were regarded as significant differences.

Microarray hybridization and functional data analyses

To examine the transcriptional profiles and identify differentially regulated genes with major biological and molecular functional differences that may serve to explain the variations, a cDNA array containing about 20 400 probes on a glass-surface was used. Total RNA was isolated using an RNeasy Midi kit (Qiagen), and samples used for real time PCR were additionally on-column treated with RNase-Free DNase I (Qiagen), following the manufacturer’s instructions. For hybridization, 15 μg of total RNA from each ESC sample was labeled either with Cy3 or Cy5 fluorescent dyes, and the dyes were swapped during the hybridization. All procedures of microarray processing were carried out as described in earlier studies[24,25].

The hybridized slides were scanned and MIAME-compliant gene expression data were submitted to the Gene Expression Omnibus (GEO) database (GSE 7173). A full description of the DNA-chip platform is available from the same database (GPL 3697). Similar to the earlier studies, genes were ranked according to the lowest absolute ratio of signal intensities regardless of reproducible up- or down-regulation. The false discovery rate among the top ranked and reproducibly regulated genes was calculated by random permutations of genes and expression ratios. For further functional characterizations, the resulting lists of regulated genes were imported into the Expression Analysis Systematic Explorer (EASE) and the Database for Annotation, Visualization, and Integrated Discovery softwares (DAVID)[26,27]. These software tools systematically mine the functional information associated with the generated microarray data[28], and analyze for overrepresentation in the gene ontology (GO) biological process, molecular function and cellular component. However, it is important to note that overrepresentation does not refer to the abundance of gene expression but rather describes a class of genes that have similar functions, regardless of their expression level[27].

Real time PCR analysis and data validation

For validation of the results, independent samples of these ESCs were prepared from the same passage aliquots. Equal amounts of total RNA from each sample were reverse transcribed to cDNA, and real time PCR was used for validation. Gene specific primers for a subset of differentially regulated genes from the microarray analysis, additional primers for various membrane and intracellular receptors involved in Ca2+ homeostasis and two reference genes were designed. The details of cDNA synthesis, real-time PCR and analysis procedures were as described earlier[29].

FACS analysis and pluripotency markers

First we determined the proportion of cells expressing the main pluripotency marker genes Pou5f1, Nanog, Fut4 and Sox-2 in mouse R1 and HM-1 ESCs based on FACS (Fluorescent Activated Cell Sorting) analysis. The results revealed the expression of these classical pluripotency marker genes in both cell lines. As shown in Table 1, the average percentages of positive cells were comparable with no significant difference in the levels of Pou5f1, Nanog, Fut4 and Sox-2 between R1 and HM-1 ESCs. The detected comparable profiles, in the percentage of positive cells, confirmed pluripotency of the two ESCs used for the study and gave us confidence in the subsequent results derived from the analysis.

Transfection and targeting efficiencies

To examine the potentials of R1 and HM-1 mouse ESCs for gene targeting and generation of genetically modified mice, we compared the efficiency of homologous recombination in these ESCs using the same non-isogenic targeting construct. The targeting efficiency was calculated by the ratio of positive clones (homologous recombined clones), confirmed by Southern blot analysis, to the total number of screened clones. The results of analysis revealed significant differences between these cell lines (R1 vs HM-1), transfection platforms (Amaxa vs Bio-Rad) and Amaxa program numbers (A23, A24 and A30).

Furthermore, major variations in the efficiency of the two ESC lines were also observed with the different Amaxa programs. Using program A23 of Amaxa, there was no significant difference, in the percentage of positive clones, between the R1 (2.5%) and HM-1 (2.4%) ESCs. However, based on the Southern blot confirmed positive clones formation efficiency from program A24 of Amaxa, the R1 ESCs outperformed the HM-1 (4.7% vs 2.4%). Similarly, when comparing the percentage of positive clones from program A30 of Amaxa, the R1 ESCs performed best (6.0%), while HM-1 ESCs had no positive clones at all, indicating another major difference between the two ESC lines. Similar comparison was also made with Bio-Rad system, and the results revealed better performances of R1 ESCs compared to HM-1 (2.0% vs 1.3%). However, the latter difference was not statistically significant.

Moreover, the numbers of PCR positive clones obtained from Bio-Rad system were significantly (P < 0.05) reduced during Southern blot confirmation analysis, while more than 90% of similar clones from the Amaxa system were further confirmed, indicating higher incidence of false positives in the former. The transfection efficiency of both ESCs was also compared using BioRad system. The results of transient transfection was significantly better for R1 (P < 0.01) than for HM-1 ESCs (Table 2).

Table 2 Comparative targeting efficiencies of R1 and HM-1 mouse embryonic stem cells.
ParametersCell line (passage number)
R1 (p12)
HM-1 (p21)
Electroporation programA231A241A301A231A241A301
Cell number3 × 1063 × 1073 × 1063 × 107
DNA concentration (μg)510510
Number of selected clones12019216835683616816824384744
Positive clones after 1st PCR screen3101115395401524
Percentage (%)
Positive clones after 2nd PCR screen3101115395401524
Homologous recombination confirmed by Southern blot analysis
Clone number3910729440514
Efficiency (%)2.54.7623.52.42.401.31.9
Transfection efficiency
TransientNo data on Amaxa system91% ± 6.1%No data on Amaxa system75% ± 4.2%
StableNo data on Amaxa system34% ± 2.9%No data on Amaxa system25% ± 5.3%
Gene expression profiles and reproducibility analysis

We compared the genome-wide expression profiles of the two ESCs, using microarrays to examine the possible causes of variations observed in targeting efficiency. During analysis, genes were ranked according to the lowest ratio of expression (HM-1/R1) in four independent chip hybridization experiments, and the ranking was independent of consistent up- or down-regulation. However, the vast majority of the top selected genes were reproducibly regulated in all four hybridization experiments. Following consideration of the reproducibility analysis and the estimation of false positive genes, the significant analysis resulted in the selection of 55 differentially regulated genes. Only 8 transcripts were up-regulated, while 47 transcripts were down-regulated in the HM-1 compared to R1 ESCs (Table 3).

Table 3 Differentially regulated transcripts between R1 and HM-1 embryonic stem cells.
Lion IDGene symbolGene nameLocus IDUnigene IDReference sequenceFold change
Chrom location
Up regulated in HM-1 compared to the R1 embryonic stem cells
MG-4-li7Rps15aRibosomal protein S15a267019Mm.288212NM_1706691.441.50.087 F1
MG-3-6b3HSPa9aHeat shock protein 9a15526Mm.209419NM_0104811.41.480.0518 15cM
MG-14-78c20B930046C15RikRIKEN cDNA B930046C15Rik gene544998Mm.327147XM_9870631.391.530.114 A1
MG-13-43a6Lefty1Left right determination factor13590Mm.378911NM_0100941.331.50.141 F
MG-3-1 1116LOC544988Hypothetical protein LOC544988544988Mm.350858NM_0010247121.291.40.0814 A1
MG-3-32g7Nsmce1Non.SMC element 1 homolog67711Mm.4467NM_0263301.281.430.17 F3
MG-11-2g16Glo1Glyoxylase 1109801Mm.261984NM_0253741.261.330.0517 16.0 cM
Down regulated in HM-1 compared to the R1 embryonic stem cells
MG-15-102f2Dab2Disabled homolog 2 drosophila13132Mm.240830NM_0010087021.992.130.1315 6.7cM
MG-12-140m7Spink3Serine protease inhibitor Kazal-type 3 precursor20730Mm.272NM_0092581.922.10.1418 B3
MG-3-251i14Sparcsecreted acidic cystein rich glycoprotein20692Mm.291442NM_0092421.862.050.1311 29.9 cM
MG-15-55i8AmotAngiomotin27494Mm.100068NM_1533191.761.90.14X F2
MG-8-118g22Krt2-8Keratin complex 2 basic gene 816691Mm.358618NM_0311701.751.930.1315 58.86cM
MG-13-5n3CryabCrystallin, α B12955Mm.178NM_0099641.71.780.19 29.0cM
MG-15-261m9BC024814cDNA sequence BC024814239706Mm.214953NM_1462471.691.880.1516 A1
MG-8-17b12Prph1Peripherin 119132Mm.2477NM_0136391.661.980.2515 55.5 cM
Table 3b. cont.Gpc4Glypican-4 precursor (K-glypican)14735Mm.1528NM_0081501.622.10.37X 16.0 cM
MG-13-91a5Serpinh1Serine (Cystein) proteinase inhibitor, clade H, member 112406Mm.22708NM_0098251.561.630.057 E1
MG-14-101o20CtgfConnective tissue growth factor precursor14219Mm.1810NM_0102171.561.730.110 17 cM
MG-12-197o17PodxlPodocalyxin like protein 1 precursor27205Mm.89918NM_0137231.461.580.156 10.0 cM
MG-6-75c23Lamc1Laminin gamma 1226519Mm.1249NM_0106831.451.50.081 81.1 cM
MG-8-118f19Anxa2Annexin 212306Mm.238343NM_0075851.451.50.089 37.0 cM
MG-16-54i39630046K23RikRIKEN cDNA 9630046K23 gene224143Mm.284366NM_1723801.441.580.1316 B3
MG-6-2i22Timp2tissue inhibitor of metalloproteinase 221858Mm.206505NM_0115941.421.50.0811 72.0 cM
MG-13-1c9S100a10Calpactin I light chain20194Mm.1NM_0091121.411.480.053 41.7 cM
MG-14-79j4Lhfp12Lipoma HMGIC fusion partner-like 2, mRNA218454Mm.316553NM_1725891.411.580.2113 C3-D1
MG-3-38p22CtslCathepsin L precursor13039Mm.930NM_0099841.381.630.1513 30.0 cM
MG-3-91d9Kcnh2Potassium voltage-gated channel, sub family H (eagralated), member 216511Mm.6539AC1130551.381.530.15
MG-3-45k24GsnGelsoin227753Mm.21109NM_1461201.371.480.152 24.5 cM
MG-6-31m16Clec21C-type lectin domain family, member 1381758Mm.349066XM_3557531.371.406 B1
MG-3-171n1Iap1-3Intracisternal A particles, Eya 1 linked15601AF0975461.351.50.081 10.4 cM
MG-3-85d19SfrsiSplicing factor, arginine/serine-rich (ASF/SFZ)Mm.45645CR5181311.342.050.8911
MG-12-195b2Timp3Metalloproteinase inhibitor 3 precursor (TIMP3) tissue inhibitor21859Mm.4871NM_0115951.331.450.1310 47.0 cM
MG-14-58h24Col8a1Procollagen type VIII, α 112837Mm.370175BC0582811.331.450.116 C1.1
MG-3-23b6Tpm1Tropomyosin 1 α22003Mm.121878M224791.321.380.059 40.0 cM
MG-13-1k15S100a4S100 calcium binding protein A420198Mm.3925BC0512141.311.450.133 43.6 cM
Table 3b. cont.S100a1S100 calcium binding protein A120193Mm.24662NM_0113091.311.350.063 43.6 cM
MG-68-98m4CtszCathepsin Z precursor64138Mm.156919NM_0223251.311.40.082 103.5 cM
MG-13-117j9AhnakAHNAK nucleoprotein (desmoyokin), mRNA66395Mm.203866BC0068921.291.40.0819 A
MG-15-217f23A930026I22RikRIKEN cDNA A930026I22 gene77970Mm.259790BX6323871.281.380.0519 C3
MG-6-30n6S100a6S100 calcium binding protein A6 (Calcyclin)20200Mm.100144NM_0113131.281.450.13 43.6 cM
MG-6-30o19Clstn3calsyntenin 3232370Mm.193701NM_1535081.281.350.066 F2
MG-6-31b18Camkk2Calcium/calmodulin-dependent protein kinase kinase 2 β207565Mm.289237NM_1453581.281.305 F
MG-12-3f11S100gS100 calcium binding protein G12309Mm.6891NM_0097891.271.30X F4
MG-6-1g19My16myosin, light polypeptide 6, alkali, smooth muscle and non-muscle17904Mm.337074NM_0108601.271.350.0610
MG-6-31b244933433P14RikRIKEN cDNA 4933433P14 gene66787Mm.248019BC0314941.271.40.0812 E
MG-12-42l4Cotl1Coactosin-like 1 (Dictyostelium)72042Mm.141741XM_4892501.261.450.138 E1
MG-3-254m20A430065p19Riken A430065P19 gene329421Mm.99648NM_1773761.261.450.132 C2
MG-3-37p2Qscn6Quiescin Q6104009Mm.27035NM_0010249451.261.380.051 G3
MG-6-31h10Map3k11mitogen activated protein kinase kinase kinase 1126403Mm.185020NM-0220121.261.330.0519 0.5 cM
MG-6-82c15DbpD site albumin promoter binding protein13170Mm.378235NM_0169741.261.307 23.0 cM
MG-8-17n2Stard9START domain containing 9211824Mm.246506XM_6198011.261.380.052 F1
MG-14-95h3Ggta1Glycoprotein galactosyltransferase α 114594Mm.281124NM_0102831.251.380.152 25.0 cM
Functional classifications of the differentially regulated genes

To search for important biological clusters that may serve to explain the functional roles of differentially regulated genes, we used the overrepresentation analysis modules of EASE and classified them according to gene ontology (GO) annotation. Despite the multiple roles played by some genes, the analysis revealed five major biological processes. In general, 27% of the regulated genes were annotated with morphogenesis and development, and 22% with organogenesis. Most of the differentially expressed ESTs and some other genes, which together account for 24% of regulated ones were not classified. Those genes that are overrepresented in response to abiotic stimulus and temperature constitute 13% and 5% of the differentially regulated genes, respectively (Figure 1A).

Figure 1
Figure 1 Overrepresentation analysis of the differentially regulated genes between R1 and HM-1 embryonic stem cells. Panels represent analysis results based on (A, 1: Morphogenesis and development, 15, 27%; 2: Organogenesis, 12, 22%; 3: Temperature response, 3, 5%; 4: Response to abiotic stimulus, 7, 13%; 5: Miscellaneous, 5, 9%; 6: Unclassified, 13, 24%) GO biological process, (B, 1: Calcium ion binding, 14, 24%; 2: Heat shock protein activity, 3, 5%; 3: Protein binding, 14, 24%; 4: Structural molecule activity, 9, 16%; 5: Unclassified, 13, 22%; 6: Enzyme regulator activity, 5, 9%) GO molecular function, (C, 1: Extracellular matrix, 17, 31%; 2: Basement membrane, 4, 7%; 3: Unclassified, 13, 24%; 4: Muscle fiber, 3, 5%; 5: Miscellaneous, 18, 33%) GO cellular components.

To examine the existence of specific molecular roles that can be related to the variations, the molecular functions of these genes were also analyzed. The majority of classified transcripts possess molecular binding functions with protein binding and calcium ion binding in equal proportions (24% each). The molecular functions of about 22% of the transcripts were not known. The remaining regulated genes were annotated as structural molecules (16%) and regulators of enzyme activity (9%) (Figure 1B). Moreover, the cellular localizations of the differentially expressed genes were also examined. 31% of the differentially regulated transcripts were overrepresented in the extracellular region. The cellular localizations of about a quarter (24%) of genes were not known with the rest annotated to different cellular locations (Figure 1C).

Validation of the microarray results with real time PCR analysis

We used real time PCR as an independent analysis tool to investigate a subset of the differentially regulated genes and validate the results of microarray analysis. Primer sequences and product sizes are listed in Table 4. The examined subset of genes include Ca2+ binding cluster genes such as Camkk2 and S100 family (S100a4, S100a6, and S100a10) genes and some other up- and down regulated transcripts (Figure 2). The results of the real time PCR analysis fully confirmed the trends and patterns of expression observed during microarray analysis with minor ratio variations, compared to the microarray results.

Figure 2
Figure 2 Relative expression analysis results of real time polymerase chain reaction for subsets of genes in R1 and HM-1 embryonic stem cells. Independently prepared samples were compared to validate the results of microarray. The analysis of real time polymerase chain reaction results supports the earlier microarray results with minor ration variations.
Table 4 Primer sequences and polymerase chain reaction conditions of genes selected for real time polymerase chain reaction assays.
Gene symbolGene namePrimer sequence (5' to 3')Product size (bp)Annealing T°
S100a4S100 calcium binding protein A4For-TCAAGCTGAACAAGACAGAGC13156
S100a6S100 calcium binding protein A6For-TCCACAAGTACTCTGGCAAGG13856
S100a10S100 calcium binding protein A10For-AGCTCTTCCAAGGACTGCTG13860
Camkk2Calcium/calmodulin-dependent protein kinase kinase2, βFor-GTCACACCACGTCTCCATTAC14456
Tpm1Tropomyosin 1 αFor-ATGCCCGTGTTCCTTAAAGC15759
SparcSecreted acidic cystein rich glycoproteinFor-ATCCCCATGGAACATTGCAC12259
TrhThyrotropin releasing hormoneFor-GGTTCTTCCACGCCTCCTAAG13559
Lefty1Left right determination factor 1For-GCAAACCAAGGACAGAATCCC10859
P2rx1Purinergic receptor P2X, ligand-gated ion channel 1For-GTCTCCAGGCTTCAACTTC15656
P2rx2Purinergic receptor P2X, ligand-gated ion channel 2For-GTAGAGCAAGCAGGAGAGA8960
P2rx3Purinergic receptor P2X, ligand-gated ion channel 3For-CCCGCTAAGACCTGAATCT14260
P2rx4Purinergic receptor P2X, ligand-gated ion channel 4For-CTGTGTGACGTCATAGTCC8560
P2rx5Purinergic receptor P2X, ligand-gated ion channel 5For-GCTTTCTTCTGTGACCTG9960
P2rx6Purinergic receptor P2X, ligand-gated ion channel 6For-CCCAAAGACGACTACCAA8660
P2rx7Purinergic receptor P2X, ligand-gated ion channel 7For-GGAAGTTAACCGTTCCTG9860
P2ry1Purinergic receptor P2Y, G-protein coupled 1For-GGTCTAGCAAGTCTCAACAG12160
P2ry2Purinergic receptor P2Y, G-protein coupled 2For-CCAAGCATGGAGAGGAGT15660
P2ry4Purinergic receptor P2Y, G-protein coupled 4For-ACTAACTGCAGGCAGAGG17060
P2ry5Purinergic receptor P2Y, G-protein coupled 5For-CATGTACCCGATCACTCTC13660
P2ry6Purinergic receptor P2Y, G-protein coupled 6For-GAGTTCTGCGTGTGTGTG17260
P2ry10Purinergic receptor P2Y, G-protein coupled 10For-GACATTTGGTATGCAGGCAAG8256
P2ry12Purinergic receptor P2Y, G-protein coupled 12For-TGCTGAGGTGCTCAAACTCTAC8456
P2ry13Purinergic receptor P2Y, G-protein coupled 13For-AACAGAGCACCAGAAGAGAG11960
P2ry14Purinergic receptor P2Y, G-protein coupled 14For-CACAAAGAGTCAGACGGAAGG9660
Bdkrb1Bradykinin receptor, β 1For-AGTCGTCCCTGATCTGAA8556
Bdkrb2Bradykinin receptor, β 2For-CACGCAGATCAGTTCCTAC9960
Hrh1Histamine receptor H1For-GGGCTACATCAACTCCAC15360
Hrh2Histamine receptor H2For-CCTCTCCTTCCTCTCTATTC11060
Hrh3Histamine receptor H3For-ACAGTCAGCAGGAGGGAGAG13556
Hrh4Histamine receptor H4For-CTTGGAAGAACAGCACGAAC10656
Ryr1Ryanodine receptor 1, skeletal muscleFor-ACTTTGTACCCTGTCCTGTG13260
Ryr2Ryanodine receptor 2, cardiac muscleFor-GGATGAATGTCTCACTGTCC14760
Ryr3Ryanodine receptor 3For-CAGGTATCTTGGAGGTCTTG11160
Itpr1Inositol 1,4,5-triphosphate receptor 1For-GGTTGATGACCGTTGTGTTG12160
Itpr2Inositol 1,4,5-triphosphate receptor 2For-GTGAGGATGGCATAGAAAG16560
Itpr3Inositol 1,4,5-triphosphate receptor 3For-GGCTTCATCAGCACTTTGG9660
H2afzH2A histone family, member ZFor-ACAGCGCAGCCATCCTGGAGTA20260
PpiaPeptidylprolyl isomerase AFor-CGCGTCTCCTTCGAGCTGTTTG15060
Intracellular Ca2+ handling and homeostasis

Because of the significant variations observed during molecular function analysis (for the calcium binding proteins) we further examined the calcium handling potentials of these ESCs. A previous study[30] described the functional existence of multiple Ca2+ signaling pathways on ES-D3 mouse ESCs. Therefore, we compared the characteristics of intracellular Ca2+ handling potentials of R1 and HM-1 ESCs in high Ca2+ solutions (i.e. 1.8 mmol/L), using various agonists and FLIPR (FlexStation II384 fluorimetric image plate reader). First, we tested the effect of ATP, a well-known activator of P2 purinergic receptors[31], on the responsiveness of the cells. The application of ATP (0.01-100 μmol/L) resulted in very similar, dose-dependent elevations of [Ca2+]i in both ESCs, with comparable EC50 values (Figure 3A). We also examined the performances in high and low Ca solutions. In HM-1 ESCs, the suppression of extracellular calcium concentration [Ca2+]e did not modify the responsiveness of the cells to ATP (Figure 4A). In contrast, in R1 ESCs, 200 μmol/L ATP induced a significantly smaller elevation of [Ca2+]i in low-Ca2+ solution than under high-Ca2+ conditions (Figure 4A). Similarly, the responsiveness of the two cell types to bradykinin (0.02-20 μmol/L), an agonist of metabotropic bradykinin receptors[32], was very similar (Figure 3B). In addition, when the [Ca2+]e was decreased, both cell types responded with significantly smaller Ca-transients to high (20 μmol/L) concentrations of bradykinin (Figure 4B).

Figure 3
Figure 3 Comparison of agonist-induced changes in [Ca2+]i in mouse R1 and HM-1 embryonic stem cells. The plates were placed into a FlexStation II384 (FLIPR) to monitor cell fluorescence (lEX = 494 nmol/L, lEM = 516 nmol/L, FU, fluorescence units) before and after the addition of various concentrations of agents in high-Ca (1.8 mmol/L) Hank’s medium. A: ATP; B: Bradykinin; C: Histamine; D: Caffeine; E: Thapsigargin.
Figure 4
Figure 4 Comparison of agonist-induced changes of [Ca2+]i in high- and low-Ca solutions. Cell fluorescence was monitored before and after addition of agents in high-Ca (1.8 mmol/L) and low-Ca (0.6 mmol/L) Hank’s medium. Panels summarize effects of (A) 200 mmol/L ATP (B), 20 mmol/L Bradykinin (C), 100 mmol/L Histamine (D) 20 mmol/L Thapsigargin. Asterisks mark significant (P < 0.05) differences.

We then investigated the effect of histamine, another agent which activates metabotropic G-protein-coupled receptor pathways[30,33]. Histamine (0.01-100 μmol/L) induced markedly different Ca2+ release response patterns in the two cell types (Figure 3C). Namely, although the EC50 values were comparable, the amplitudes of the maximal histamine-evoked [Ca2+]i elevations (Bmax values) of R1 ESCs were more than two-fold higher than those measured on HM-1 ESCs. Importantly, however, the responsiveness of both cell types was strongly dependent on the [Ca2+]e since we observed only minimal [Ca2+]i elevation upon histamine (100 μmol/L) administration in low-Ca solutions (Figure 4C). Previous studies have also shown that certain tyrosine kinase coupled (metabotropic) receptors may also modulate [Ca2+]i[34]. Therefore, we also investigated the effect of two growth factors, NGF and EGF, on Ca-homeostasis of the cells. We found that none of the agonists modified [Ca2+]i in either cell type (data not shown).

Functional intracellular Ca2+ stores may possess various Ca2+ release channels[18,35,36]. To investigate the presence of ryanodine receptors (RyRs), we employed caffeine (0.002-20 mmol/L), an activator of RyRs[30,37]. In high-Ca solution, R1 ESCs did not respond to caffeine (up to 20 mmol/L) (Figure 3D). However, under similar conditions, higher doses of caffeine (2-20 mmol/L) markedly (P < 0.05) elevated [Ca2+]i in HM-1 ESCs (Figure 3D). As expected, the response of HM-1 ESCs to caffeine (20 mmol/L) was not affected by the suppression of [Ca2+]e (data not shown). Finally, we investigated the Ca2+ content of the intracellular stores using thapsigargin, an inhibitor of the Ca2+ pump[30,38]. Thapsigargin (0.002-20 μmol/L) effectively elevated [Ca2+]i in a dose-dependent manner in both cells types in high-Ca solution (Figure 3E). However, importantly, the maximal Ca2+ response was remarkably greater in R1 than in HM-1 ESCs. Furthermore, as expected, we found that suppression of [Ca2+]e did not modify the amplitude of [Ca2+]i elevations evoked by 20 μmol/L thapsigargin (Figure 4D).

Expression profiles of membrane and intracellular receptors involved in Ca-homeostasis

Since cell type-dependence was also observed when measuring the efficiency of the above agents in elevating [Ca2+]i in R1 and HM-1 cells (Figure 3), it can be postulated that the receptor-mediated signaling mechanisms (including Ca-handling) are different in the different ESCs. In order to investigate this hypothesis, we performed a large number of experiments to identify the expression patterns of those receptors which either (1) function as molecular targets of the above agents that modulate [Ca2+]i and the targeting efficiency; or (2) participate in the intracellular Ca-handling of the cells. For this we used qPCR (quantitative real time PCR) to measure and compare the expression of various receptors. Primer sequences and product sizes are listed in Table 4.

Indeed, as shown in Figure 5, qPCR analysis of gene expression levels of various surface membrane receptors (i.e. ionotropic P2X purinoreceptors; metabotropic P2Y purinoreceptors; metabotropic Bradykinin (B) receptor; metabotropic histamine (H) receptors) as well as of intracellular Ca-release channel receptors (i.e. ryanodine receptors; IP3 receptors) revealed that, as expected, HM-1 and R1 ESCs express markedly different patterns of receptors/molecules that participate in the regulation of Ca-homeostasis of these cells. The variations in the levels for most of the receptors was significant (P < 0.05) between these cell lines, as shown in Figure 5. Generally, the analysis revealed that the detection and expression intensity of these receptors was cell line dependent. This correlates well with our earlier observations and, thus, may contribute to the performance of these ESC lines.

Figure 5
Figure 5 Differential expression of genes encoding surface membrane and intracellular receptors involved in the regulation of Ca-homeostasis of R1 and HM-1 embryonic stem cells. Independently prepared samples were used to measure the expression of various receptors by real time polymerase chain reaction and relative expression levels were presented. aRepresent genes significantly (P < 0.05) up regulated; cRepresent genes significantly (P < 0.05) down regulated in HM-1 compared to R1 embryonic stem cells.

Extensive molecular analysis was suggested as a prerequisite for the elucidation of the complex and interrelated processes that occur in biological systems[39]. In this study, we examined the gene targeting efficiency, the gene expression profiles and the Ca2+ homeostasis of two mouse embryonic stem cell lines, and found significant differences between them.

A number of research papers[40-42] have addressed the different aspects of DNA transfer and subsequent efficiency. A maximum DNA transfer of homologous targeting vectors with electroporation/transfection into the cytoplasm of 7%, with only 4.5% reaching the nucleus, and further degradation of this fraction (in both cytoplasm and the nucleus) was described earlier[40]. To understand the causes of this and to increase the efficiency, different studies[3,8], have examined the effects of various factors, including contents of the medium, time of adding DNA and other ingredients, sizes of various molecules, DNA concentration, temperature, type of the construct, and extent of homology. One of these studies[42] examined the effects of various concentration gradients of calcium, phosphate solutions and other parameters on the kinetics and reproducibility of precipitate formation during transfection. Our study with one of its objectives to examine the inherent Ca2+ handling potentials of the transfected cells is complementary and fills a knowledge gap.

As these ESCs were derived from the mouse strain129, the use of a non-isogenic DNA construct (C57B1/6) has enabled us to compare these ESCs under identical conditions. In our study, the targeting efficiency of 1.3% to 2% with BioRad and 2.4% to 6% with Amaxa systems is comparable to the previously reported values with non-isogenic mouse DNA constructs[8,43]. In line with our results, better performance using nucleofection was also reported by other studies[7,44]. Generally, R1 ESCs outperformed HM-1 ESCs in targeting efficiency irrespective of the transfection system and program types. Although details of the different Amaxa program packages (A23, A24, and A30) and the contents of the reagents are not known, we assume the existence of factors that elicited differential cellular responses. For the same program and conditions used in parallel, the two ESCs responded differently.

Following observation of the variations in targeting efficiencies, we then compared the global gene expression profiles using microarrays. Considering the genetic background from which the lines were derived, similar culture conditions, stringency of our filtering procedures and to avoid the possibility of missing informative genes with subtle differences, we decided to use at least 1.25 fold changes as bottom line for significance. The overrepresentation analysis in the biological process and in the molecular functions pointed to some functional roles of differentially regulated genes. The GO biological process defines the broad biological goals that are accompanied by ordered assemblies of molecular functions[28]. We focused mainly on the genes with the binding molecular functions, as they constituted the major categories of annotation for the differentially regulated genes (Figure 1B). Earlier studies[45,46] in different cell types have indicated the buffering capacity of calcium binding proteins in rendering the cells tolerant to the calcium load. Thus, the lower performances of HM-1 ESCs during transfection may be linked to a lower intrinsic potential. Comparison of these ESCs in high and low Ca+2 solutions confirmed this difference. Using the examined agonists, while no significant differences were observed in lower Ca+2 solutions, significant differences were observed in high Ca+2 solution comparisons (Figure 4). In order to further test the above observations, we used a range of agonists and examined the calcium handling potentials of these ESCs both in high and low calcium solutions (Figure 4). Evaluation of the effects of various agents, known as key regulators of intracellular homeostasis, revealed marked differences in the Ca-handling potentials of R1 and HM-1 ESCs. ATP is a well-known activator of P2 purinergic receptors[30,31]. Among these receptors, P2X purinoreceptors function as ionotropic ligand-gated with a marked permeability to calcium. P2Y metabotropic G-protein coupled purinoreceptors, however, initiate a phospholipase-C (PLC)-mediated intracellular signaling pathway which, eventually, results in the liberation of Ca2+ from the intracellular stores by acting on inositol-1,4,5-trisphosphate receptors (InsP3Rs), i.e. Ca2+ release channels[18,30,31,35,36]. Our FLIPR (FlexStation II384 fluorimetric image plate reader) experiments revealed that whereas R1 and HM-1 ESCs responded very similarly in high-Ca solution, the ATP responsiveness of R1 ESCs but, importantly not of HM-1 cells, was significantly lower in low-Ca solution. These findings strongly suggest that in HM-1 ESCs, the elevated [Ca2+]i originated exclusively from the intracellular stores whereas in R1 ESCs, a significant part of the Ca elevation was due to Ca-influx from the extracellular space.

Bradykinin activates metabotropic bradykinin receptors[32] which are similar to P2Y metabotropic purinoreceptors and were shown to initiate the G-protein - PLC - InsP3R intracellular signaling pathway to release Ca2+ from the intracellular stores[18,35,36]. Therefore, it was unexpected to observe the bradykinin-induced Ca-transients, similar for both ESCs, that showed a reasonable dependence on the [Ca2+]e. These intriguing findings suggest that the initiation of the bradykinin receptor-coupled signaling pathway, which apparently does exist in both ESC types, also results in an opening of a plasma membrane channel population, which is permeable for calcium. Such mechanisms were previously described in various cell types such as vascular endothelial cells and corneal epithelial cells[47,48]. Similar responses were observed in both cell types when histamine, the endogenous agonist of metabotropic histamine receptors (most of which also functioning via the G-protein - PLC - InsP3R -Ca-release pathway), was investigated[30,33]. An even more pronounced suppression of the amplitude of the histamine-evoked Ca-transients was measured in low-Ca medium suggesting that, intriguingly, most of the calcium originated from the extracellular space via Ca-permeable channels (similar to previous findings on other cell types)[47,49]. Moreover, we also found that R1 ESCs responded with much greater [Ca2+]i elevations in response to histamine than HM-1 ESCs.

The above data have unambiguously demonstrated that both ESCs possess functional InsP3R-mediated Ca-release mechanisms. In contrast, we found that only HM-1 ESCs responded with [Ca2+]i elevations to caffeine application. However, it was intriguing to observe (especially in light of the above data with caffeine) that thapsigargin, an inhibitor of the Ca2+ pump[30,38], was able to induce a markedly higher [Ca2+]i elevation in R1 than in HM-1 ESCs. These data may indicate that the content of the (thapsigargin-sensitive) Ca-pools is much greater in R1 than in the other ESCs.

Finally, it is important to note that none of the agonists (NGF and EGF) of tyrosine kinase coupled (metabotropic) receptor pathways, caused changes in [Ca2+]i suggesting the lack of functional tyrosine kinase receptor coupled signaling in R1 and HM-1 ESCs.

Taken together, our experiments revealed significant differences in the regulation of Ca2+ homeostasis of R1 and HM-1 ESCs and suggested that these differences may contribute to the different targeting efficiencies of the two cell types as measured in various functional in vivo and in vitro assays. The various agents differentially modulated the performances of these cell lines. These findings suggest that other components of the receptor-mediated signaling pathways may also differ in the various ESCs and hence may also play roles in determining the functional characteristics of the cells. Indeed, a series of gene expression analyses revealed that R1 and HM-1 ESCs exhibit markedly different expression patterns of genes encoding various surface membrane and intracellular receptors involved in the regulation of Ca-homeostasis of the cells. Hence, when a given agent is administered to different mouse ESCs, the activation of different receptor patterns (expressed on these cells) may induce differential elevation of [Ca2+]i as well as initiation of distinct receptor-mediated intracellular signaling mechanisms. Collectively, this results in differential cellular effects (e.g. transfection efficiency) in the different cell types.

In summary, our study revealed some similarities and significant differences in targeting efficiency, Ca2+ homeostasis, and gene expression profiles between R1 and HM-1 ESCs. Despite the variations between the technique (Bio-Rad vs Amaxa) and program types (A23, A24 and A30) used, the cells with better potential (R1) performed better. Thus, our findings emphasize the significance of inherent cellular potentials for increased targeting efficiency, and are in line with the results of some previous studies[9,13,12,15,50] that have also acknowledged contributions of cellular differences to the experimental outcomes. The knowledge of intrinsic cellular differences in Ca2+ signals and their possible impacts on the targeting efficiency are significant inputs towards filling the current knowledge gap. A similar recent study[9,51] described the existence of marked variations in the differentiation propensity of the different human ESC lines. Differences in their potential may reflect the underlying genetic variations of the embryos from which the lines were derived, some other differences in the initial culture, and/or an interaction of the two factors. However, understanding these variations contributes to the selection of better performing cell lines for realizing the potentials of the ESCs for various applications. The approach of combining molecular profiles and in vitro culture performance will give better insight into the different cell lines. This is increasingly important for the characterization of human ESC lines before therapeutic use.


Generation of knockout mouse models by targeted disruption of essential genes provides useful insights into genes that regulate development and allows investigators to dissect molecular developmental mechanisms. In an effort to understand the therapeutic applications of stem cells, mouse models have been created for a number of human genetic diseases, and gene targeting in stem cells has also been common practice. However, most studies have focused mainly on comparing the efficiency of different gene delivery techniques, parameters or phenotypes of the offspring carrying the mutant gene, but not the efficiency of different cell lines.

Research frontiers

Previous studies have acknowledged the existence of similarities and differences in the performances of different stem cell lines. In the area of improving the therapeutic applications of stem cells, the research hotspot is to increase the technical efficiencies of various genetic modifications and transfers in embryonic stem cells, in order to increase the chances of getting more colonies with required genetic information and recombination efficiency.

Innovations and breakthroughs

Currently mouse embryonic stem cells are used in various research applications, including gene targeting, with designed alterations in an exogenous DNA sequence and transfer to the DNA sequence in the living cell genome via homologous recombination. However, the procedures are laborious and performance of various stem cells differ markedly. Despite the acknowledged existence of variations among the different stem cell lines, most studies have focused mainly on comparing the efficiency of different gene delivery techniques, parameters or phenotypes of the offspring carrying the mutant gene. In the present study, the authors compare the two widely known mouse embryonic stem cell lines and show how the intrinsic qualities of these cells can affect the gene targeting performances and calcium handling potentials of these stem cells.


Results of this study emphasize the importance of considering intrinsic cellular variations, during selection of cell lines for experiments and interpretation of experimental results.


Embryonic stem cells: Embryonic stem cells are cells derived from the inner cell mass of the developing blastocyst with a retained potential to self-renew and to differentiate into diverse cell lineages; gene targeting: Gene targeting is the transfer of designed alteration in an exogenous DNA sequence to the cognate DNA sequence in the living cell genome via homologous recombination; calcium homeostasis: Calcium homeostasis is the mechanism by which the body maintains adequate calcium levels.

Peer review

The manuscript entitled “Gene targeting and Ca2+ handling efficiencies in mouse embryonic stem cell lines” raises important questions to the scientific community and emphasizes the importance of considering intrinsic cellular variations during selection of cell lines for experiments and interpretations of experimental results. The novelty relies on Calcium handling efficiencies.


Peer reviewers: Regina Coeli dos S Goldenberg, PhD, Carlos Chagas Filho Biophysics Institute, Federal University of Rio de Janeiro, Av Carlos Chagas Filho no 373, Prédio do CCS , Bloco G, Sala 53, Cidade Universitária, Ilha do Fundão 21941-902, Rio de Janeiro, RJ, Brazil; Alain Chapel, PhD, SRBE DRPH, IRSN, BP17, 926262 Far, France; Naiara Zoccal Saraiva, DVM, MSc, FCAV-UNESP-Jaboticabal, Via de Acesso Prof. Paulo Donato Castellane, s/n, CEP 14884-900, Jaboticabal, SP, Brazil

S- Editor Wang JL L- Editor Hughes D E- Editor Ma WH

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