All cells were cultured at 37°C and 5% CO₂ in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 5% fetal bovine serum, 1% penicillin/streptomycin and 0.25 μg/mL amphotericin B. HEK293 WT, IP₃R TKO and IP₃R1 rescue cells were the kind gift of Dr. David Yule (Alzayady et al., 2016; Arige et al., 2022). WT and and IP₃R TKO HeLa cells were a kind gift of Katsuhiko Mikoshiba (Ando et al., 2018). All experiments were conducted with a normal level of extracellular Ca²⁺ (2.5 mM).

2 × 10⁵ cells were plated in 12-well dishes and grown to 70%–80% confluency. The reporter constructs used were as follows: pGL3-NFAT luciferase, Addgene #17870; pGL3-3xAP1, Addgene #40342; pGL4.29-CRE, Promega #E8471; pGL4.32-NFkb-RE, Promega #E8491. Cells were transfected with 1ug DNA/well of reporter gene-luciferase and 0.2 ug/well of Renilla luciferase (a kind gift of Dr. Makarand Risbud) using Lipofectamine 3000 (ThermoFisher Scientific). After 24 h, cells were subjected to various treatments for 4 h and then lysed with 1X Firefly Luciferase assay buffer (Biotium Corporation). A Luciferase Assay Kit 2.0 (Biotium Corporation) was used to measure firefly and Renilla luciferase activity on a Synergy Neo2 (Biotek) plate reader.

To prepare lysates, cells incubated in DMEM were washed in PBS and lysed in a 0.25 mL of WB buffer containing 1% Triton X-100, 50 mM Tris/HCl pH 7.8, 150 mM NaCl, 2 mM sodium orthovanadate, 10 mM sodium pyrophosphate, 20 mM NaF, and a 1x dilution of a complete protease inhibitor mixture (Roche Diagnostics). The lysates were centrifuged at 12,000 ×g for 10 min. The supernatants were denatured in SDS sample buffer. Lysates were boiled at 100°C for 5 min, then stored at −20°C until use. Unless otherwise noted, 40 µg of protein were run at 100V for 90min on 10% polyacrylamide gels and transferred at 100V for 60 min onto nitrocellulose membranes. Polyvinylidene difluoride membranes were used in the specific case of LC3 immunoblotting. Membranes were blocked in TBST supplemented with 5% BSA for 1 h at room temperature. Following 3 × 15 min washes in TBST, the primary Ab was added for 16 h at 4°C. All Abs were used at a dilution of 1:1000 and were obtained from Cell Signaling. Membranes were developed using ECL reagent (ThermoFisher). When necessary membranes were stripped using a buffer containing SDS (2% w/v), Tris (62.5 mM; pH6.8) and β-mercaptoethanol (100 mM).

2 × 10⁵ cells were plated in 60 mm dishes, incubated at 37°C, and grown to 70%–80% confluency. Cells were transfected with either PKCδ siRNA, non-targeted negative control siRNA, or Cy3 fluorescent positive control siRNA (OriGene Technologies Inc., Rockville, MD) using a Lipofectamine RNAiMAX kit (Thermo Fisher Scientific) then incubated at 37°C for 48 h.

RNA was isolated using Direct-zol RNA Miniprep kit (Zymo Research, cat no. R2052) according to manufacturer’s instructions and yielded samples with RIN values > 7. Poly-A RNA sequencing library was prepared following Illumina’s Tru-Seq-standard-mRNA sample preparation protocol. Poly(A) tail-containing mRNAs were purified using oligo-(dT) magnetic beads with two rounds of purification. After purification, poly(A) RNA was fragmented using divalent cation buffer in elevated temperature. Paired-ended sequencing was performed on Illumina’s NovaSeq 6000 sequencing system. Reads were processed to remove adapter contamination, verified for sequence quality, and then assembled and mapped to the human genome. All library construction, sequencing and data processing was performed by LC Sciences, Houston, TX. The differentially expressed mRNAs were selected with log2 (fold change) > 1 or log2 (fold change) <-1 and with statistical significance (adjusted p-value <0.05) by R package edgeR (Robinson et al., 2010).

The volcano plots were drawn using the ‘Volcano plots’ feature in the toolbox of the Galaxy web site (https://usegalaxy.eu/). Visualization of pathway enrichment of genes using the KEGG compendium of pathways was supplied by LC Sciences. Manual curation of differentially expressed genes (DEG) was done with the following data sets: calcium signaling (Hortenhuber et al., 2017)(https://www.uhlenlab.org/cagedb/), transcription factors (Lambert et al., 2018)(http://humantfs.ccbr.utoronto.ca/allTFs.php) and MitoCarta3 (Rath et al., 2021) (https://personal.broadinstitute.org/scalvo/MitoCarta3.0/human.mitocarta3.0.html). Data sets of target genes for the transcription factor NFAT, CREB, AP-1 and NF-Kb were downloaded from the Harmonizome web site (https://maayanlab.cloud/Harmonizome/).Gene Set Enrichment Analysis (GSEA) (Subramanian et al., 2005) was performed by GSEA software (v 4.1.0) using the Hallmark gene set documented in the MSigDB-C5 (v 7.3).

Cells were seeded at 5 × 10⁵ cell/well on a six-well plate and grown overnight at 37°C. After treatment, total RNA was purified using a Direct-zol RNA Microprep kit (Zymo Research, cat no. R2052) according to manufacturer’s instructions. Genomic DNA was eliminated by on-column digestion with DNaseI. RNA quality and quantity were measured using a NanoDrop. A total of 200 ng RNA was reverse transcribed using 1 µL reverse transciptase (200U/mL, APEXbio, cat. no. K1071). qPCR reactions were performed in triplicate using HotStart 2X SYBR qPCR Master Mix, APEXbio, cat. no. K1070) according to the manufacturer’s instructions on a QuantStudio5 (Applied Biosystems). Relative gene expression was normalized using either GAPDH or Actin as a housekeeping gene. The sequences of the primers used are given below:

Extracellular H₂O₂ was measured using Amplex Red reagent (ThermoFisher; A12222). 5 × 10⁵ cells/well were seeded on black, clear bottom 96-well plates and grown in DMEM overnight. Medium was aspirated from all wells and replaced with 100 µL Amplex red assay buffer (HBSS, 10 µM Amplex Red, 0.4U/mL horseradish peroxidase). Fluorescence was measured every 5 min for 1 h using a Synergy Neo2 plate reader (Biotek Instruments) set at Ex 535 nm and Em 590 nm. After 1 h, wells were aspirated, cells were lysed using 50 µL WB buffer and assayed for protein. Absolute values were estimated from a H₂O₂ standard curve. Mitochondrial superoxide (O₂ ^•─) was measured using a MitoSOX Red mitochondrial superoxide indicator (ThermoFisher; M36005). 5 × 10⁵ cells/well were seeded on black, clear bottom 96-well plates and grown in DMEM overnight. Medium was aspirated from all wells and replaced with 150 µL MitoSOX assay buffer (HBSS, 1 µM MitoSOX Red reagent, 5 mM glucose, 1 mM sodium pyruvate). Fluorescence was measured immediately and every 20 min for 1 h using a Synergy Neo2 plate reader (Biotek Instruments) set at Ex 510 nm and Em 595 nm. After 1h, wells were aspirated, cells were lysed using 50 µL WB buffer and assayed for protein. Intracellular H₂O₂ was assessed using cells transiently transfected with cytosol-targeted pCS2+HyPer7-NES (Addgene #136467). Fluorescence ratios Ex490/Ex405 nm and Em 535 were obtained every 30 s for 30 min using the Synergy Neo2 plate reader. At the end of the experiment, sequential additions of dithiothreitol (DTT) were made to establish the Ex490/405 nm minimum value representing fully reduced probe. Subsequently, sequential H₂O₂ (200 µM) washes were performed until a stable Ex490/Ex405 nm maximum ratio was achieved representing a fully oxidized probe. Results are presented as (R-R_DTT)/(R_H2O2-R_DTT).Glutathione peroxidase was assayed with 1ug cell lysate in 96 clear well plates using an assay buffer containing 6 mM GSH, 1.25 mM NADPH and 500U glutathione reductase. After mixing, 100 µL 7 mM H₂O₂ was added and the absorbance of NADPH read at 340 nm using a Synergy Neo2 plate reader every 10 s for 5 min. Rates of NADPH oxidation/mg protein were calculated from linear regions of the graphs.

Epifluorescence imaging of GSSG:GSH was carried in cells transiently transfected with cytosol and mitochondrial matrix-targeted Grx1roGFP2 (PMC8455442) Lipofectamine 3000 (ThermoFisher L300000) according to manufacturer’s instructions. 24–36 h post transfection, cells were pre-incubated in HBSS supplemented with 2% BSA. For imaging, cells were washed and transferred to a similar solution containing 0.25% BSA. Imaging was carried out using a back-illuminated electron multiplying charge-coupled device (EMCCD) camera (EvolveEM 512 × 512 pixel. Photometrics), mounted to an Olympus IX70 inverted microscope equipped with a Sutter DG4 light source. Fluorescence excitation was achieved with a custom dichroic derived from Chroma #59022 modified to enhance short wavelength excitation and bandpass filters specific to fluorophores. Grx1roGFP2 was imaged with dual excitation of 402/15 & 485/15 nm. Analysis was carried out using the FIJI variant of ImageJ (NIH, version 1.52). Images were subject to background subtraction and registration (MultiStackreg plugin, registration matrices applied equally to all wavelengths). GSSG:GSH was calculated using formula (R-Rmin)/(Rmax-Rmin) where Rmin & Rmax values were obtained via complete reduction (DTT) and oxidation (H₂O₂) of Grx1roGFP at the end of each experiment. Excitation frequencies in Grx1roGFP2 are reversed, short wavelength/long wavelength to ensure that oxidation of both Grx1roGFP2 and HyPer7 causes an increase in ratio.

Unless otherwise noted, the data are expressed as means ± SEM of three independent experiments, each performed in technical triplicate. With the exception of Figure 4, statistics were evaluated by comparing two data groups using an unpaired t-test with p < 0.05 as the standard criteria for significance. GraphPad Prism 8.0 (GraphPad Software, San Diego, CA, United States) was used to generate plots and to perform statistical analysis.

To investigate the impact of Ca²⁺ signal loss on transcription, we began by looking at the activation of the well-established Ca²⁺-dependent transcription factor NFAT using a luciferase reporter assay. We expressed the effect of treatments as a fold-activation over the baseline of WT cells, after normalization for transfection efficiency using Renilla luciferase activity. However, a 50%–70% increase in baseline NFAT activity was noted in both HEK293 and HeLa TKO cells (Figures 1A,C). HEK293 cells express endogenous M3 muscarinic receptors (Luo et al., 2008) and stimulation with carbachol (Cch) caused a 3.5-fold increase in NFAT activity in WT cells, but had no further stimulatory effect above the baseline of TKO cells (Figure 1A). Activation of endogenous histamine receptors in HeLa cells showed a 2-fold activation of NFAT in WT cells which is lost in TKO cells (Figure 1C). These observations are in line with published data showing loss of NFAT stimulation by B-cell receptor activation in DT40 TKO cells (Sugawara et al., 1997), and reduced NFAT activation in HEK293A cells after siRNA knockdown of type 2 IP₃Rs (Arguin et al., 2010). As a control to verify that NFAT was still responsive to Ca²⁺ in TKO cells, we tested the effect of the Ca²⁺ ionophore ionomycin which had comparable effects to agonists in both WT HEK293 and HeLa cells. However, ionophore elicited an unexpectedly large increase (∼13-fold activation) in NFAT activity in the HEK293 TKO cells (Figure 1A). An increased NFAT response to thapsigargin-induced elevation of cytosolic Ca²⁺ was also observed in HEK293 TKO cells (Figure 1B). Previous studies have shown equivalent responses of [Ca²⁺]_c to ionomycin and thapsigargin in HEK293 TKO cells (Bittremieux et al., 2017; Yue et al., 2020; Young et al., 2022; Chakraborty et al., 2023). The hypersensitivity to ionomycin was not observed in the HeLa TKO model. These results suggest that one adaptation to a loss of Ca²⁺ signaling in HEK293 TKO cells is an increased Ca²⁺ sensitivity of the calcineurin (CaN) -mediated dephosphorylation of NFAT. Immunosuppressive drugs (e.g., cyclosporine A or FK506) are known to block NFAT activation by inhibition of calcineurin activity (Mattila et al., 1990). To test for the involvement of CaN we pretreated the cells with cyclosporine A (CsA) which blocked the ionomycin responses in both WT and TKO HEK 293 cells and eliminated the baseline differences seen in the TKO cells (Figure 1A). The enhanced sensitivity of TKO cells to thapsigargin was also inhibited by CsA (Figure 1B). Many possible mechanisms may underlie the altered Ca²⁺ sensitivity of CaN regulation in HEK293 TKO cells, including a slower export of NFAT from the nucleus or altered levels of endogenous CaN inhibitors such as RCAN1 (Macian, 2005). We found decreased levels of RCAN1 in HEK293 TKO cells but not in HeLa TKO cells (Figure 1D), which would be consistent with hypersensitivity to ionomycin being confined to HEK293 cells. Another reason for the lack of Ca²⁺ hypersensitivity could be related to HeLa cells having a different complement of NFAT isoforms than HEK293 cells (Bekker-Jensen et al., 2017), since each isoform also shows differential regulation and kinetics of nuclear translocation (Kar and Parekh, 2015; Yoast et al., 2020).

Many NFAT-dependent target genes are also stimulated by the AP-1 transcription factor, which in turn is activated by PKC signaling (Hogan et al., 2003). The cooperative binding of NFAT and AP-1 to adjacent promoter sites results in synergistic activation of NFAT gene targets when cells are simultaneously stimulated by Ca²⁺ and PKC activation (Macian et al., 2001). A pan PKC activator, phorbol 12-myristate 13-acetate (PMA), caused a ∼70% activation of NFAT in the HEK293 WT or TKO cell line (Figure 1A). Combination treatment of PMA and ionomycin elicited synergistic responses in WT and TKO cells. However, the PMA/ionomycin treatment caused a larger increase in the TKO cells (45-fold versus 12-fold in WT cells). A synergistic activation by PMA/ionomycin was seen in the HeLa WT line (Figure 1C). However, in HeLa TKO cells, PMA alone caused a large NFAT activation which was not further stimulated when combined with ionomycin (Figure 1C).

Next, we investigated cAMP response element binding protein (CREB), another well studied Ca²⁺-sensitive transcription factor (Steven et al., 2020). Using a CRE-luciferase reporter assay to monitor the activity of CREB, we observed baseline increases in both HEK293 and HeLa TKO cells (Figures 2A,B). Unlike NFAT, CREB luciferase activity was still stimulated by agonists in TKO cells of both cell types. The addition of ionomycin to the WT cells had a smaller effect than agonist on CREB-luciferase activity. However, ionomycin promoted a marked increase in CREB reporter activity (>10-fold) in HEK293 TKO cells. CsA blocked the effects of ionomycin and eliminated the baseline increase in CREB reporter activity seen in the TKO cells (Figure 2A). The supersensitivity to ionophore was not observed in HeLa TKO cells which were actually less sensitive to ionophore compared to WT cells (Figure 2B). The selective effect of ionomycin resembles that seen with NFAT luciferase in HEK293 cells (Figure 1A) and may have the same underlying mechanism. It is known that CaN can activate CREB by dephosphorylation and nuclear translocation of CRTC2, a transcriptional coactivator of CREB (Screaton et al., 2004). Thus, decreased levels of RCAN1 could play the same role in altering the Ca²⁺ responsiveness of CREB in a manner similar to NFAT. The different ionophore response in HeLa cells may be due to the lack of RCAN1 changes, but it should be noted that the regulation of CRTC2 is also different in HeLa cells since they lack an upstream kinase (LKB1) needed to maintain phosphorylation of CRTC2 (Katoh et al., 2006). In a previously published study on HEK293A cells it was shown that optimal responses of CREB to Ca²⁺ mobilizing hormone requires the addition of vasoactive intestinal peptide (VIP), a cAMP-elevating stimulus (Arguin et al., 2010). Treatment with VIP alone or in combination with ionophore caused a very large activation of CREB in both cell lines which was not significantly different in the TKO cells (Figures 2A,B).

A primary phosphorylation site in CREB is at ser-133 which enhances recruitment of the co-activator CBP/p300 and increases transcriptional activity (Johannessen et al., 2004). To confirm the data obtained with CREB reporter assays, we immunoblotted for p-CREB (ser-133) after 10min agonist treatment in HEK293 (Figure 2C) and HeLa (Figure 2D) cells and increased CREB phosphorylation in both WT and TKO cells, with agonist effects being significantly larger in the TKO cell lines (Figures 2C,D). Ca²⁺-modulation of CREB is exerted through phosphorylation by specific isoforms of two protein kinase families, Ca²⁺/calmodulin-dependent protein kinase (CaMK) and PKC (Dewenter et al., 2017; Steven et al., 2020). To investigate the possible role of PKC in maintaining CREB phosphorylation in TKO cells, we used a pan-PKC inhibitor, Ro-31–8220 (Nixon et al., 1992). The inhibitor did not block agonist-stimulated pCREB in WT HEK293 or HeLa cells suggesting that PKC is not a major factor controlling CREB phosphorylation in WT cells. However, the pan-PKC inhibitor decreased phosphorylation in both TKO cell lines (Figures 2C,D). In order to identify the isoform of PKC that may be involved in maintaining CREB activation in TKO cells we used an siRNA knockdown approach. The obvious candidates are the novel Ca²⁺-insensitive isoforms, of which PKCδ and PKCε are both expressed in HEK293 and HeLa cells (Rimessi et al., 2007; Kim et al., 2016). HEK293 WT and TKO cells expressed similar basal levels of total PKCδ and treatment with siRNA resulted in >90% knockdown in both cell lines. (Figure 2E). Knockdown of PKCδ had no effect on agonist stimulated CREB phosphorylation in HEK293 WT cells but caused a 50% reduction of pCREB in TKO cells (Figure 2F). In HeLa cells, expression levels of basal PKCδ in TKO cells was only 25% of that seen in WT cells (Figure 2G). The mechanism(s) involved were not further explored but it is known that PKCδ is targeted for degradation by phosphorylation and ubiquitination (Srivastava et al., 2002). Treatment with siRNA reduced PKCδ in HeLa WT and TKO cells but resulted in significantly reduced pCREB only in TKO cells (Figure 2H). The poor quality of our PKCε antibodies precluded further investigation of the contribution of this isoform. Overall, these data indicate that CREB activation is maintained in TKO cells, in part, by an increased reliance on Ca²⁺-insensitive PKC isoforms.

AP-1 is a transcription factor composed of homo- and heterodimers of members of the fos, jun, Maf and ATF families. These proteins are categorized as “immediate early genes” that are normally present at low amounts in quiescent cells and are induced in response to activation of signaling pathways, such as Ca²⁺ mobilization or the activation of PKC. Initially, we examined the activity of AP-1 in WT and TKO cells using luciferase promoter assays (Figure 3). The results show that agonists only weakly stimulated AP-1 activity (<20%) in the WT HEK293 (Figure 3A) but increased AP-1 activity in WT HeLa cells (Figure 3B) by ∼2-fold. Both TKO cell lines had elevated baseline AP-1 activities, which could not be further increased by agonists. AP-1 activity in HEK293 cells was not responsive to ionomycin but was stimulated by PMA. This is in line with the known sensitivity of AP-1 to activation by PKC (Karin et al., 1997). Although PMA treatment of TKO cells gave an apparent smaller fold activation in both cell types, the absolute levels of AP-1 activity were comparable when the elevated baselines were taken into account. The combined treatment with PMA and ionomycin produced a synergistic activation in both WT and TKO HEK293 cells but not in HeLa cells. The elevated baselines of AP-1, NFAT and CREB reporter activities could be suppressed in HEK293 TKO cells stably rescued with the human IP₃R1 isoform (Supplementary Figure S1).

The protein expression levels of four AP-1 members (c-fos, fosB, c-jun, junB) were examined by immunoblotting of control and agonist-stimulated HEK293 WT and TKO cells (Figures 3C–G). Significant levels of c-fos, c-jun and junB were detected at baseline even in serum-deprived HEK293 cells. In the case of c-fos, basal levels were comparable in WT and TKO cells and carbachol treatment increased c-fos similarly in both cell lines, although higher concentrations of carbachol were required in TKO cells (Figure 3C). By contrast, baseline fosB was not detectable in WT or TKO cells and was increased by carbachol treatment only in WT cells (Figure 3D). Two bands were detected for fosB with both bands showing the same changes. Based on its molecular weight, the lower band likely corresponds to the molecular weight of the established splice variant fosB2 (also known as delta fosB) (Nakabeppu and Nathans, 1991). c-Jun (Figure 3E) and JunB (Figure 3F) behaved similarly, with protein levels increasing in response to carbachol in WT cells. However, baseline levels of both proteins were elevated in TKO cells and could not be further stimulated by carbachol treatment. Changes in the levels of these AP-1 proteins in WT and TKO HeLa cells are shown in Supplementary Figure S3. c-Fos and JunB in HeLa cells behaved in a manner similar to c-jun and JunB in HEK cells. Notably, baseline levels were increased in TKO cells and could not be further stimulated by histamine. The histamine response of c-jun was decreased in TKO cells and FosB was not expressed in HeLa cells under any experimental conditions (not shown). The results indicate that some members of the AP-1 family are more highly expressed at baseline in TKO cells and this could underlie the constitutive activation of AP-1 activity seen under these conditions.

The activation of ERK1/2, p38 and Jnk MAP kinase cascades lie upstream of the AP-1 and CREB pathways. The consensus of studies suggests that while Ca²⁺ signals are not essential, they can regulate these pathways. For example, Ca²⁺ elevation in primary cortical neurons (Rosen et al., 1994; Agell et al., 2002), fibroblasts (Chao et al., 1994) and HeLa cells (Kupzig et al., 2005) activates the Ras/Raf/ERK1/2 pathway. Similarly, there have been many studies which report the involvement of a Ca²⁺ signal in the activation of p38 and Jnk (Enslen et al., 1996) pathways. We have examined the carbachol-mediated activation of Jnk and ERK1/2 in HEK293 TKO cells (Supplementary Figure S3). In the case of Jnk, a 54 kDa species was phosphorylated in response to carbachol stimulation in both WT and TKO cells (Supplementary Figures SA–C). However, a higher baseline level and more rapid kinetics of p-Jnk formation were evident in the TKO cells. Similarly, the ERK1/2 pathway was activated robustly by carbachol in both WT and TKO cells (Supplementary Figures S3D, E).

Multiple mechanisms have been identified for the Ca²⁺ regulation of NFκb activity including activation of PKC (Berry et al., 2018). A NFκb luciferase promoter showed a higher basal activity in HEK293 TKO cells but was insensitive to carbachol or ionophore in either WT or TKO cells (Supplementary Figures S3F, E). As expected PMA was a potent stimulus for NFκb promoter activity but the combination of ionophore and PMA was less effective, particularly in TKO cells (Supplementary Figure S3). HeLa WT and TKO cells showed several differences from HEK293 cells including similar baseline activity and less pronounced sensitivity to PMA (Supplementary Figure S3G). In contrast to lymphocytes, the NFκb pathway appears relatively insensitive to Ca²⁺ changes even in WT HEK293 and HeLa cells.

Increased ROS levels regulate the basal activity of many transcription factors including NFAT (Vaeth and Feske, 2018; Peng et al., 2021), AP-1 (Abate et al., 1990), NFκb (Morgan and Liu, 2011) and CREB (Ichiki et al., 2003). In addition, the activity of specific signaling proteins, e.g., Jnk are altered by ROS (Aggarwal et al., 2019). Therefore, we examined if ROS production is altered in the IP₃R TKO cells. Initially, we measured the production of extracellular H₂O₂ using a peroxidase/amplex red assay. The results showed increased H₂O₂ release in both HEK293 and HeLa TKO cells under basal conditions (Figures 4A,B). As a positive control we treated cells with antimycin A (AA) which blocks electron flow at complex III and stimulates production of superoxide (O₂ ^•─) (Quinlan et al., 2011) that can be enzymatically converted to H₂O₂ by superoxide dismutase (SOD). Both WT and TKO cells showed a stimulation of H₂O₂ when treated with AA (Figures 4A,B). Further inhibition of the, ETC with the combination of AA and rotenone blocks electron entry to the, ETC and acts as a negative control. In both HEK293 and HeLa TKO cells the AA and rotenone cocktail was insufficient to block H₂O₂ release. However, in both HEK293 and HeLa the AA and rotenone cocktail did not eliminate the difference between WT and TKO cells suggesting an, ETC independent source of H₂O₂ in TKO cells. We employed diphenyleneiodonium (DPI) as an isoform insensitive inhibitor of NADPH oxidase (NOX) complex assembly. In both HEK and HeLa, NOX inhibition had a more pronounced effect in TKO cells vs. WT. It should be noted that NOX expression is regulated by some of the transcription factors shown to be increased in TKO cells (e.g., AP-1 and NFκB (Manea et al., 2015)) and NOX activity can be increased by PKCδ (Kim et al., 2011). As predicted, inhibition of catalase activity with 3-aminotriazole (3-AT) increased H₂O₂ release in both HEK and HeLa TKO cells (Figures 4A,B). Inhibition of H₂O₂ metabolism could also contribute to the elevation of H₂O₂ in TKO cells. However, direct measurements of the catalytic activity of glutathione peroxidase showed a small decrease that was confined to HEK293 TKO cells only (Supplementary Figure S4A).

We attempted to quantitate O₂ ^•─ generation directly using the mitochondrial targeted probe MitoSox (Murphy et al., 2022). These results showed that O₂ ^•─ levels are decreased under basal and AA-treated conditions in both HEK293 and HeLa TKO cells (Figures 4C,D). The result would be consistent with an increased conversion of O₂ ^•─ to H₂O₂ by SOD in TKO cells. Indeed, levels of the cytosolic (SOD1) and the mitochondrial (SOD2) isoforms were increased in HEK293 TKO cells (Figures 4E,F,H). However, only the mitochondrial SOD2 isoform was elevated in HeLa TKO cells (Figures 4E,F). Catalase protein levels were also elevated in both cell types (Figure 4G). The presence of altered handling of ROS in TKO cells was further confirmed by using two additional approaches. The first was to monitor the redox status of glutathione in the cytosol and mitochondrial compartments using the genetically targeted Grx1-roGFP2 probe (Gutscher et al., 2008). The results showed the cytosolic glutathione pool was more reduced in the TKO cells but the mitochondrial pool was not affected (Supplementary Figure S4B). The second approach was to use HyPer7-an ultra-sensitive, pH independent, H₂O₂ probe targeted to the cytosol (Pak et al., 2020). Using additions of H₂O₂ and DTT to provide maximum and minimum values, the HyPer7 probe confirmed that HEK293 TKO cells maintained a higher baseline production of H₂O₂ (Supplementary Figure S4C) and that AA was able to further increase the signal in both WT and TKO cells. Some of the functional effects of ROS on gene transcription are mediated by the transcription factor Nrf2 which translocates to the nucleus and binds antioxidant response elements (ARE) in the promoters of genes coding for antioxidant enzymes (including catalase and SOD’s) (Ma, 2013). Measurement of luciferase promoter activity indicates that basal activity of Nrf2/ARE was increased in both HEK293 and HeLa TKO cells, consistent with enhanced ROS generation (Figure 4I).

To gain a broader understanding of global baseline transcriptional changes resulting from knockout of IP₃ receptors, we carried out RNAseq analysis on unstimulated WT and TKO cell models in both HEK293 and HeLa lines. For HEK293 cells a total of 58,825 gene transcripts were measured and 828 genes were identified as being differentially expressed (DEG) by edgeR analysis using a criteria of ∣log₂ fold change∣>1 and p-value < 0.05. These genes are depicted on a volcano plot in Figure 5A with the top 30 genes having highest statistical significance (false discovery rate p-value < 0.01) being colored and labeled. In order to determine if there were changes in groups of genes with related biological function, we also compared the DEGs to online curated gene sets encoding Ca²⁺ signaling components, transcription factors or mitochondrial proteins (Figure 5B). Six cell surface receptors coupled to phospholipase-C activation are in the Ca²⁺ signaling list but the biological relevance of these changes are likely to be complicated since some are upregulated (e.g., HTR2C, CCKBR) and others downregulated (e.g., EGFR, P2RY11). Six cation channels are also in the list including several members of the TRP family. This includes TRPC6, which can be directly stimulated by diacylglycerol, and is known to be involved in NFAT activation in the heart (Kuwahara et al., 2006). All these channels, with one exception (KCNN3), were upregulated in the TKO cells. In the case of transcription factors, the list included 8 immediate early genes (underlined), all of which were downregulated under basal conditions. Only a few genes encoding mitochondrial proteins were altered. In many cases, such as acyl CoA synthetases (ACSL6, ACSL1) or respiratory complexes (NDUFA6, SCO2) the changes were in opposite directions. Transcripts for MICU2 were also decreased in TKO cells but previous studies have shown that the levels of protein were not altered (Katona et al., 2022). The over representation of DEGs in specific KEGG pathways was assessed in Figure 5C. The top 20 hits included several signaling pathways, such as phospholipase D, MAPK, and VEGF. Of particular interest, the NFκB signaling pathway was highlighted as being significantly enriched in the TKO cells which is in line with results from the NFκb luciferase reporter assays. Focal adhesion was also a highlighted KEGG pathway. Although not specifically investigated in this study, others have reported decreased motility of IP₃R TKO HEK293 cells (Yue et al., 2020).

To look for cell type dependent and independent changes, we repeated the RNAseq analysis in HeLa WT and TKO cell models (Figure 6). For HeLa cells a total of 60,613 gene transcripts were measured and 310 genes were identified as being differentially expressed (DEG) by edgeR analysis using the same threshold criteria as used for HEK293 cells. Based on this the number of DEGs are significantly lower in HeLa cells (37.4%). These genes are depicted on a volcano plot in Figure 6A with the top 30 genes being identified as in Figure 5A. A feature that is apparent is that many more genes are downregulated than upregulated in HeLa cells, whereas the opposite is true for HEK293 cells. The distribution of the HeLa DEGs within the curated gene sets of Ca²⁺ signaling, transcription factors or mitochondrial proteins are shown in Figure 6B. As expected, a lower number of genes are found in each category than seen for HEK293 cells. The over-representation analysis also showed no overlap in the 2 cell types with a lower number of HeLa DEGs in each KEGG gene set (Figure 6C). At the single gene level with the significance criteria used, there were only 18 genes changed in common between the HEK293 and HeLa data sets (Figure 7). To avoid focusing on individual genes, or DEG lists based on thresholds, we utilized gene set enrichment analysis (GSEA) which uses all the genes in the RNAseq data set to look for concerted changes in biological pathways. This analysis, using the Hallmark gene set from the Molecular Signatures data base, is shown for HEK293 (Figure 7C) and HeLa cells (Figure 7D). More pathways were enriched than de-enriched in HEK293 cells than in HeLa cells, in line with our previous analysis of individual genes. Ten common pathways were altered in the same direction in both cell types under basal conditions. This included KRAS signaling, TNF-alpha signaling via NF-Kb, Interferon responses, Notch signaling, hypoxia and the p53 pathway. However, there were also changes in pathways that were unique or changed in opposite directions in both cell types.It is possible that the changes in the common pathways may underlie the common changes in phenotypes observed in the two TKO cell lines–notably, increased baseline transcription factor activity, altered PKC regulation and elevated ROS levels. However, the relationships between the common pathways and common phenotypes are likely to be complex. For example, PKCδ is both a downstream effector of KRAS (Symonds et al., 2011) and KRAS can itself be regulated by PKC phosphorylation (Bivona et al., 2006). KRAP (a regulator of KRAS) is proposed to be a binding partner of IP₃Rs (Thillaiappan et al., 2021; Vorontsova et al., 2022) and loss of IP₃Rs could alter KRAS signaling by this mechanism. Similarly, p53 can both be regulated by ROS and alter levels of antioxidant enzymes (Liu et al., 2008). Further work is needed to determine the relative importance of the common pathways for the survival of IP₃R TKO cells.

Our focus in this study was on transcriptional changes that may result from the loss of Ca²⁺ signaling in the IP₃R TKO cells. In particular, we have concentrated on the known Ca²⁺ dependent transcription factors, e.g., NFAT, CREB, AP-1 and NFκb. Therefore, we wanted to know the contribution of target genes of these transcription factors to the RNAseq data sets. To do this we employed a publicly available transcription factor target gene data base (Harmonizome (Rouillard et al., 2016)). Of the 828 DEGs in HEK293 cells, 135 genes (16.3%) were NFAT2 targets, 26 (3.1%) were CREB targets, 587 (70.1%) were AP-1 targets and 96 (11.6%) were NF-kB targets. For the 310 DEGs in HeLa cells we identified 47 genes (15.2%) as NFAT2 targets, 6 genes (1.9%) as CREB targets, 207 (66.7%) as AP-1 targets and 33 genes (10.6%) as NF-kB targets. Thus, AP-1 and NFAT were the most affected of the three transcription factors measured in TKO cells. Despite the differences in overall number of DEGs between HEK293 and HeLa cells, the percentage of altered NFAT, CREB, AP-1 and NFκB target genes were similar in both cell lines. It is important to emphasize that the RNAseq data set were obtained from unstimulated cells. NFAT and AP-1 family members can bind cooperatively to adjacent promoter sites and PKC is a known activator of AP-1 (Karin et al., 1997). This raises the possibility that, although the absence of Ca²⁺ signaling in TKO cells may impair the activation of NFAT, the higher basal activity of NFAT, together with the activation of Ca²⁺ -independent PKC isoforms may be sufficient to allow agonists to turn on NFAT target genes. The redundancy of transcription factor activation makes it difficult to test this hypothesis with target genes that are exclusively NFAT responsive. RT-qPCR measurements were made of two representative NFAT target genes (COX2 (Pont et al., 2012), IRS2 (Demozay et al., 2011)) and ETS1, which is a transcription factor that interacts with NFAT (Naito et al., 1998; Tsao et al., 2013). None of the selected genes showed agonist-mediated increases over a 6 h period in HEK293 or HeLa cells (Supplementary Figure S5). PMA stimulated the expression of COX2 and ETS1 in both WT HEK293 and HeLa cells (Supplementary Figures S5A–D). The PMA response of COX2 was further increased in TKO cells in both cell lines, but for ETS1 was increased only in HeLa TKO cells. Baseline IRS2 mRNA levels were strongly suppressed in HEK293 TKO cells and to a lesser extent in HeLa TKO cells. This confirms findings from RNAseq data (Figure 5). Previous microarray studies on clones of HEK293 cells with high and low store-operated Ca²⁺ entry (SOCE) identified IRS2 as a putative regulator of SOCE (Zagranichnaya et al., 2005), but a mechanistic and functional link between loss of IP₃R-mediated Ca²⁺ fluxes and IRS2 remains to be established.