ITPKA Antibody

What is ITPKA and what biological functions does it serve?

ITPKA (Inositol-trisphosphate 3-kinase A) is an enzyme that catalyzes the phosphorylation of 1D-myo-inositol 1,4,5-trisphosphate (InsP3) into 1D-myo-inositol 1,3,4,5-tetrakisphosphate. This reaction plays a crucial role in regulating calcium homeostasis in cells . In mammals, ITPKA is predominantly expressed in principal neurons of the forebrain and in cerebellar Purkinje neurons, as well as in testis tissue . It is expressed relatively late in postnatal brain development, suggesting a role in mature neuronal function rather than in early development .

At the functional level, ITPKA is significantly involved in hippocampal long-term potentiation (LTP), with knockout studies showing enhanced LTP in the CA1 region but decreased LTP in the CA3 region of the hippocampus, resulting in memory deficits . The primary molecular role of ITPKA involves attenuating InsP3-mediated calcium responses, thus fine-tuning calcium signaling in neurons .

Why are ITPKA antibodies important for neuroscience research?

ITPKA antibodies serve as crucial tools for investigating calcium signaling mechanisms in neuronal systems. Since ITPKA is predominantly expressed in principal neurons of the forebrain and cerebellar Purkinje neurons, antibodies targeting this protein allow researchers to track specific neuronal populations and their functional states .

From a methodological perspective, these antibodies enable scientists to detect ITPKA protein expression in multiple experimental contexts. For instance, immunohistochemistry using ITPKA antibodies helps visualize the protein's distribution in brain tissue sections, including human cerebral cortex and mouse hypothalamus . Western blot applications assist in quantifying ITPKA expression levels, particularly important when comparing normal versus pathological states . Additionally, immunofluorescence techniques with ITPKA antibodies provide insights into the protein's subcellular localization in neuronal cells, helping to elucidate its functional interactions with other signaling molecules .

What tissue distribution pattern does ITPKA show, and how can antibodies help map this?

ITPKA exhibits a distinct tissue distribution pattern that can be effectively mapped using appropriate antibodies. The enzyme is predominantly expressed in the principal neurons of the forebrain and in cerebellar Purkinje neurons . It is also expressed in testis tissue . Notably, ITPKA expression follows a developmental pattern, appearing relatively late in postnatal brain development .

Antibodies can map this distribution through various techniques. Immunohistochemistry on paraffin-embedded (IHC-P) tissue sections can visualize ITPKA in different brain regions, as demonstrated with antibodies like ab251867 that have been validated for both human and mouse brain tissues . Such immunostaining reveals ITPKA's neuronal-specific localization pattern. Western blotting with ITPKA antibodies can quantitatively compare expression levels across different brain regions or developmental stages, with validated antibodies showing a predicted band size of approximately 51 kDa in human cerebral cortex tissue lysates . For subcellular localization studies, immunocytochemistry/immunofluorescence (ICC/IF) techniques using ITPKA antibodies have successfully demonstrated the protein's distribution within neuronal cells, as exemplified by studies in U-251 MG human brain glioma cell lines .

What validation methods should be employed before using an ITPKA antibody in research?

Before employing an ITPKA antibody in research, several validation methods should be implemented to ensure specificity and reliability. First, Western blot analysis should be performed to confirm that the antibody detects a protein of the expected molecular weight (approximately 51 kDa for ITPKA) . The presence of a single, clear band at this size suggests antibody specificity, while multiple bands may indicate cross-reactivity with other proteins.

Second, immunohistochemistry validation should include positive controls using tissues known to express ITPKA, such as human cerebral cortex or mouse hypothalamus . Negative controls should also be included by either omitting the primary antibody or using tissues where ITPKA is not expressed. Third, for functional validation, researchers should consider knockdown or knockout experiments. By reducing ITPKA expression through techniques like shRNA (as demonstrated in H1299 cells with the targeting sequence 5′-CCUUGUGUGCUCGACUGCA-3′), the specificity of the antibody can be confirmed if the signal diminishes proportionally to the knockdown efficiency .

Additionally, recombinant protein or peptide blocking experiments can be valuable. Pre-incubating the antibody with the immunogen (for example, recombinant fragment within Human Inositol-trisphosphate 3-kinase A aa 300-400) should abolish the signal if the antibody is specific . Finally, cross-validation using multiple antibodies targeting different epitopes of ITPKA can provide further confidence in the specificity of detection.

What are the optimal fixation and antigen retrieval methods for ITPKA immunostaining?

Optimal fixation and antigen retrieval methods for ITPKA immunostaining depend on the specific application and tissue type. For immunocytochemistry/immunofluorescence (ICC/IF), paraformaldehyde (PFA) fixation followed by Triton X-100 permeabilization has been successfully employed, as demonstrated in U-251 MG human brain glioma cell line studies . This method preserves cellular architecture while allowing antibody access to intracellular ITPKA.

Since ITPKA is known to be highly susceptible to proteolysis during purification , inclusion of protease inhibitors during tissue collection and processing is critical. Early biochemical studies showed that ITPKA purified from brain runs on gels as a ladder of multiple catalytically active bands between 53 kD and about 30 kD, indicating significant proteolysis . Inclusion of calpain inhibitors in buffers during tissue processing can reduce this protein degradation and improve immunostaining results.

How should researchers optimize Western blotting protocols for ITPKA detection?

Optimizing Western blotting protocols for ITPKA detection requires careful consideration of several factors. First, sample preparation is critical - since ITPKA is highly susceptible to proteolysis , researchers should include protease inhibitor cocktails in lysis buffers during protein extraction. RIPA lysis buffer supplemented with protease inhibitors has been successfully used for ITPKA detection .

Protein separation should be performed on 12% SDS-PAGE gels, which provide appropriate resolution in the 50-55 kDa range where ITPKA is expected (predicted band size: 51 kDa) . For transfer, a semi-dry transfer system with PVDF membranes often yields optimal results for ITPKA detection. When blocking, 5% non-fat dry milk or BSA in TBS-T (Tris-buffered saline with 0.1% Tween-20) for 1 hour at room temperature is typically effective.

For primary antibody incubation, validated ITPKA antibodies should be diluted appropriately - for example, ab251867 has been effectively used at 0.04 μg/ml concentration . Overnight incubation at 4°C generally yields optimal results. For detection, HRP-conjugated secondary antibodies specific to the primary antibody host species (e.g., anti-rabbit for ab251867) should be used . Enhanced chemiluminescence (ECL) detection systems provide good sensitivity for ITPKA visualization.

To control for loading and specificity, researchers should include appropriate loading controls (e.g., GAPDH, β-actin) and consider positive controls (tissues known to express ITPKA, such as cerebral cortex) and negative controls (tissues with minimal ITPKA expression) .

How can ITPKA antibodies be utilized in co-immunoprecipitation studies to identify protein interaction partners?

ITPKA antibodies can be effectively employed in co-immunoprecipitation (co-IP) studies to identify and confirm protein interaction partners. This approach has successfully revealed the interaction between ITPKA and Drebrin 1 (DBN1) in lung adenocarcinoma research . To implement co-IP for ITPKA interaction studies, researchers should first prepare cell or tissue lysates using gentle lysis buffers that preserve protein-protein interactions, supplemented with protease inhibitor cocktails to prevent degradation .

The experimental procedure includes several critical steps: first, pre-clearing the lysate with protein A/G beads to reduce non-specific binding; second, incubating the pre-cleared lysate with ITPKA antibody to form antibody-protein complexes; third, adding protein A/G beads to capture these complexes; and finally, washing the beads thoroughly before eluting bound proteins for analysis . Validation requires performing reciprocal co-IP experiments, as demonstrated in the ITPKA-DBN1 interaction studies where proteins pulled down by anti-ITPKA antibody were detected by DBN1 antibody, and conversely, proteins pulled down by anti-DBN1 antibody were detected by ITPKA antibody .

Including appropriate controls is essential: using non-specific IgG from the same species as the primary antibody serves as a negative control (as exemplified by the use of rabbit IgG as control for ITPKA pull-down) , while input samples (pre-IP lysate) confirm the presence of target proteins before immunoprecipitation. For ITPKA interaction studies, GAPDH detection in immunoprecipitates can serve as a negative control for specificity, as demonstrated in published protocols .

What role does ITPKA play in cancer progression and how can antibodies help elucidate this function?

ITPKA plays a significant role in cancer progression, particularly in lung adenocarcinoma (LUAD), where it functions as an oncogene. Research utilizing ITPKA antibodies has revealed that ITPKA is over-expressed in LUAD tissues compared to normal lung tissues, with significantly higher expression in lymph node-positive and more aggressive T-stage LUAD tissues . This overexpression correlates with worse prognosis, suggesting ITPKA as a potential prognostic biomarker .

ITPKA antibodies have helped elucidate the molecular mechanism behind ITPKA's oncogenic function. Immunohistochemical analysis of tissue microarrays using ITPKA antibodies has demonstrated that ITPKA expression levels serve as an independent survival marker in LUAD patients . Additionally, co-immunoprecipitation studies with ITPKA antibodies have identified Drebrin 1 (DBN1) as an interaction partner that contributes to ITPKA's oncogenic function .

The transcriptional regulation of ITPKA has also been investigated using antibodies. ChIP-qPCR experiments using TFAP2A antibodies have confirmed that the transcription factor TFAP2A binds to the ITPKA promoter and regulates its expression . Western blot analysis with ITPKA antibodies following TFAP2A knockdown showed decreased ITPKA expression, establishing the TFAP2A-ITPKA regulatory axis .

Functionally, ITPKA promotes epithelial-mesenchymal transition (EMT) in cancer cells. Western blot analysis with antibodies against EMT markers (N-cadherin, E-cadherin, Vimentin) in cells with ITPKA knockdown has demonstrated ITPKA's role in this cancer progression mechanism . This data is summarized in the following relationship:

How can ChIP-qPCR with transcription factor antibodies help understand ITPKA regulation?

Chromatin Immunoprecipitation followed by quantitative PCR (ChIP-qPCR) with transcription factor antibodies has proven invaluable for understanding ITPKA regulation. This technique has specifically revealed that TFAP2A acts as an upstream transcription factor for ITPKA by binding to its promoter region . The methodology involves several critical steps optimized for ITPKA regulatory studies.

First, cells expressing ITPKA (such as H1299 lung cancer cells) are fixed with formaldehyde to cross-link DNA and associated proteins, preserving the in vivo interactions between transcription factors and the ITPKA promoter . Next, chromatin is fragmented through sonication to yield DNA fragments of appropriate size (typically 200-500 bp) for immunoprecipitation. The fragmented chromatin is then immunoprecipitated using antibodies against suspected transcription factors, such as TFAP2A in LUAD studies .

For ITPKA regulatory studies, appropriate controls are essential: rabbit IgG serves as a negative control to assess non-specific binding, while H3K4me3 pull-down can function as a positive control (with EIF4A2 sequence detection) to confirm successful ChIP procedure . After immunoprecipitation, cross-links are reversed, and the enriched DNA is purified for qPCR analysis.

The qPCR analysis targets specific regions of the ITPKA promoter containing putative transcription factor binding sites. For TFAP2A binding to the ITPKA promoter, three independent ChIP-Seq datasets (GSM2817666, GSM1081381, and GSM588928) have confirmed a clear peak at the core promoter region . When designing primers for ITPKA promoter analysis, researchers should focus on these validated binding regions.

For data analysis, enrichment is calculated relative to the IgG pull-down control using the formula 2^-(CtTarget - CtIgG) . A significant enrichment of ITPKA promoter DNA fragments in TFAP2A antibody pull-down compared to IgG control confirms direct binding of TFAP2A to the ITPKA promoter .

What are common challenges in ITPKA antibody-based experiments and how can they be addressed?

Several common challenges arise when working with ITPKA antibodies, each requiring specific troubleshooting approaches. One major challenge is ITPKA's susceptibility to proteolysis during sample preparation. Early biochemical studies demonstrated that ITPKA purified from brain typically appears as multiple bands between 53 kDa and 30 kDa due to proteolytic degradation . This issue can be addressed by incorporating calpain inhibitors and comprehensive protease inhibitor cocktails in all extraction buffers . Additionally, keeping samples consistently cold and processing them rapidly minimizes degradation.

Another challenge is potential cross-reactivity with other inositol trisphosphate kinase isoforms (ITPKB and ITPKC), which share sequence homology with ITPKA. To address this, researchers should select antibodies raised against unique regions of ITPKA and validate specificity through Western blot analysis in tissues expressing different ITPK isoforms. Incorporating appropriate positive controls (tissues known to express ITPKA, such as cerebral cortex) and negative controls (tissues with minimal ITPKA expression) helps confirm antibody specificity .

In immunohistochemistry applications, background staining or weak signal intensity may occur. Background can be reduced by optimizing blocking conditions (e.g., extending blocking time or using different blocking agents like BSA or serum) and diluting primary antibodies appropriately. For enhanced signal detection, amplification systems such as tyramide signal amplification or polymer-based detection systems can be employed, particularly when studying tissues with moderate ITPKA expression levels.

For ChIP-qPCR experiments investigating ITPKA regulation, challenges include low enrichment signals. This can be addressed by optimizing sonication conditions to generate appropriate DNA fragment sizes (200-500 bp), increasing antibody amounts or incubation times, and using validated positive controls like H3K4me3 pull-down .

How should researchers interpret variations in ITPKA expression patterns across different neural tissues?

Interpreting variations in ITPKA expression patterns across different neural tissues requires careful consideration of both biological factors and methodological limitations. ITPKA shows cell-type specificity, being predominantly expressed in principal neurons of the forebrain and cerebellar Purkinje neurons . Therefore, variations between brain regions may reflect the relative abundance of these neuronal populations rather than global expression differences.

Researchers should note that ITPKA expression follows a developmental timeline, appearing relatively late in postnatal brain development . This temporal pattern means that expression levels in developing versus mature neural tissues may differ significantly. When comparing expression across age groups, researchers should account for these developmental changes rather than interpreting them solely as experimental variations.

Interestingly, there are species differences in ITPKA expression patterns. While most studies report ITPKA primarily in forebrain and cerebellar neurons in rodents, human microarray data suggest substantial ITPKA expression in gray matter regions that lack ITPKA expression in rodents . This indicates that a subset of neurons may express ITPKA in humans but not in rodents, highlighting the importance of species-specific validation when interpreting antibody staining patterns.

From a methodological perspective, researchers should be aware that ITPKA detection is influenced by antibody sensitivity and specificity. Variations in staining intensity may sometimes reflect differences in epitope accessibility rather than true expression level differences. To address this, multiple detection methods (e.g., immunohistochemistry, Western blot, and in situ hybridization) should be used to corroborate expression patterns. Additionally, quantification methods should be standardized when comparing expression levels across neural tissues, using appropriate housekeeping genes or loading controls specific to neuronal populations.

What controls should be included when studying ITPKA phosphorylation status and enzymatic activity?

When studying ITPKA phosphorylation status and enzymatic activity, a comprehensive set of controls should be included to ensure reliable and interpretable results. First, positive and negative phosphorylation controls are essential. Since ITPKA is a substrate for both cAMP-dependent protein kinase A (PKA) and protein kinase C (PKC) in vitro , samples treated with PKA or PKC activators (e.g., forskolin for PKA, phorbol esters for PKC) can serve as positive controls for phosphorylated ITPKA. Conversely, samples treated with specific PKA or PKC inhibitors can function as negative controls.

Phosphorylation site-specific controls are also critical. Researchers should include ITPKA mutants where known phosphorylation sites have been altered (e.g., serine-to-alanine mutations) to validate the specificity of phospho-specific antibodies. For enzymatic activity assays, researchers should include kinase-dead ITPKA mutants (with mutations in the catalytic domain) to distinguish between ITPKA-specific activity and background phosphorylation.

When measuring ITPKA's enzymatic activity (phosphorylation of InsP3 to InsP4), appropriate substrate controls are necessary. These include no-substrate controls to establish baseline measurements and substrate saturation controls to ensure the assay operates within the linear range. Additionally, specific inhibitors of ITPKA activity can be used as negative controls.

Time-course controls help establish the kinetics of ITPKA phosphorylation and activity. These involve measuring phosphorylation status and enzymatic activity at multiple time points after stimulation, providing insights into the temporal regulation of ITPKA.

Finally, for in vivo studies, ITPKA knockout or knockdown models serve as essential negative controls. The absence of ITPKA protein or activity in these models confirms the specificity of detection methods. For instance, shRNA targeting ITPKA with the sequence 5′-CCUUGUGUGCUCGACUGCA-3′ has been validated for effective knockdown in cell culture models .

How is ITPKA implicated in diseases beyond cancer, and what research techniques are emerging to study these connections?

While ITPKA's role in cancer (particularly lung adenocarcinoma) has been well-documented, emerging evidence suggests its involvement in various other pathological conditions. In neurological disorders, ITPKA's critical function in calcium homeostasis and its predominant expression in principal neurons of the forebrain and cerebellar Purkinje neurons implicate it in disorders affecting synaptic plasticity . The enhanced long-term potentiation (LTP) in CA1 and decreased LTP in CA3 regions observed in ITPKA knockout mice suggest potential roles in learning and memory disorders .

In immunological disorders, connections are beginning to emerge. Although ITPKA itself is not highly expressed in immune cells (unlike its isoform ITPKB), its role in calcium signaling pathways suggests potential indirect effects on immune function . Interestingly, mutations in the related ITPKC gene have been linked to Kawasaki disease, an autoimmune condition, suggesting that perturbations in this enzyme family can contribute to immune dysregulation .

Emerging research techniques to study these disease connections include:

• Single-cell transcriptomics and proteomics, which allow for precise mapping of ITPKA expression in specific cell populations within heterogeneous tissues, providing insights into cell-type-specific roles in disease states.

• CRISPR-Cas9 genome editing for creating precise ITPKA mutations or conditional knockouts in disease-relevant tissues, enabling the study of ITPKA function in specific pathological contexts.

• Advanced calcium imaging techniques combined with ITPKA manipulation, allowing real-time visualization of how ITPKA affects calcium dynamics in relevant cell types during disease processes.

• Phosphoproteomics approaches to identify downstream targets of ITPKA-mediated signaling in different disease contexts, revealing potential disease-specific signaling networks.

• Patient-derived organoid models incorporating ITPKA antibody-based imaging to study the protein's expression and function in three-dimensional tissue contexts that better recapitulate human disease conditions.

What are the latest developments in understanding ITPKA's role in epithelial-mesenchymal transition (EMT) and metastasis?

Recent research has uncovered ITPKA's significant role in epithelial-mesenchymal transition (EMT) and metastasis, particularly in lung adenocarcinoma (LUAD). ITPKA has been identified as a downstream effector of TFAP2A, a transcription factor previously implicated in EMT . Through detailed molecular studies, researchers have established that TFAP2A directly binds to the ITPKA promoter region, as confirmed by ChIP-Seq data from three independent datasets (GSM2817666, GSM1081381, and GSM588928) .

The functional relationship between ITPKA and EMT has been demonstrated through knockdown experiments. When TFAP2A (the upstream regulator of ITPKA) is knocked down in H1299 lung cancer cells, there is a significant reduction in ITPKA expression, accompanied by reduced levels of mesenchymal markers N-cadherin and Vimentin, and increased expression of the epithelial marker E-cadherin . This indicates that the TFAP2A-ITPKA axis promotes EMT, a critical process in cancer metastasis.

Importantly, rescue experiments have provided further evidence for ITPKA's role in EMT. When ITPKA is overexpressed in TFAP2A-knockdown H1299 cells, it partially rescues the EMT phenotype, confirming that ITPKA is a key mediator of TFAP2A's pro-EMT effects .

Clinical studies have strengthened the connection between ITPKA and metastasis. Analysis of LUAD tissue microarrays revealed that high ITPKA expression correlates significantly with lymph node positivity (p=0.02), as shown in the following data table:

This clinical correlation, combined with the mechanistic insights from molecular studies, establishes ITPKA as an important contributor to the metastatic process .

How can researchers integrate computational predictions with antibody-based validation to advance ITPKA research?

Integrating computational predictions with antibody-based validation offers a powerful approach to advancing ITPKA research. This hybrid methodology combines in silico analysis with experimental verification, enhancing both efficiency and reliability in investigating ITPKA's functions, interactions, and regulatory mechanisms.

For identifying protein interaction partners, researchers can first employ computational approaches such as protein-protein interaction (PPI) prediction algorithms or structural docking simulations to generate hypotheses about potential ITPKA binding partners. These computational predictions can then be validated experimentally using co-immunoprecipitation with ITPKA antibodies, as demonstrated in the identification of the ITPKA-DBN1 interaction. This approach was successfully employed in lung adenocarcinoma research, where mass spectrometric data initially suggested a potential interaction between ITPKA and Drebrin 1, which was subsequently confirmed through antibody-based co-immunoprecipitation experiments .

For transcriptional regulation studies, researchers can integrate computational transcription factor binding site predictions with experimental ChIP-qPCR validation. Computational analysis of the ITPKA promoter region identified an AP2 motif, suggesting potential regulation by TFAP2A . This prediction was then experimentally validated through ChIP-Seq and ChIP-qPCR using TFAP2A antibodies, confirming direct binding of TFAP2A to the ITPKA promoter .

Regarding post-translational modifications, computational algorithms can predict potential phosphorylation sites in ITPKA, which can then be verified using phospho-specific antibodies. Since ITPKA is known to be a substrate for both PKA and PKC , computational prediction of specific phosphorylation sites followed by site-directed mutagenesis and antibody-based detection can elucidate the functional consequences of these modifications.

For advancing clinical applications, researchers can integrate computational analysis of large-scale genomic data (such as TCGA datasets) with antibody-based validation in patient samples. This approach has already proven valuable in LUAD research, where computational analysis of TCGA data identified ITPKA overexpression in tumors, which was subsequently validated through immunohistochemistry with ITPKA antibodies in patient-derived tissue microarrays .