PTGIS Antibody, HRP conjugated

What is PTGIS and why is it an important research target?

PTGIS (Prostaglandin I2 Synthase), also known as Prostacyclin Synthase, is a critical enzyme in the arachidonic acid metabolism pathway that catalyzes the conversion of prostaglandin H2 to prostacyclin (PGI2). It plays significant roles in vascular homeostasis, inflammation, and diverse pathological processes including fibrosis and cancer progression.

What experimental applications are validated for PTGIS antibodies?

PTGIS antibodies have been validated for multiple research applications with methodological considerations for each:

When selecting a PTGIS antibody, researchers should verify validation for their specific application and target species reactivity, as PTGIS antibodies are available with reactivity against human, mouse, rat, and bovine targets .

What are the key differences between unconjugated and HRP-conjugated PTGIS antibodies?

While unconjugated PTGIS antibodies require a secondary detection system, HRP-conjugated variants offer direct detection capabilities with several methodological implications:

• Detection workflow: HRP-conjugated antibodies eliminate the need for secondary antibody incubation, reducing protocol time by approximately 1-2 hours and minimizing potential cross-reactivity issues.

• Sensitivity considerations: Direct HRP conjugation may provide lower sensitivity than amplified detection systems using unconjugated primary antibodies, particularly for low-abundance PTGIS detection.

• Experimental flexibility: Unconjugated antibodies offer greater flexibility for multiplexing and signal amplification strategies but require additional optimization steps.

• Background concerns: HRP-conjugated antibodies might exhibit higher background in some tissues due to endogenous peroxidase activity, requiring effective blocking steps using hydrogen peroxide treatment (typically 0.3% for 15 minutes) .

The selection between conjugated and unconjugated formats should be determined by experimental requirements, target abundance, and tissue-specific considerations.

What is the recommended protocol for Western blot detection of PTGIS?

Based on validated research methodologies, the following protocol has been optimized for PTGIS detection by Western blot:

• Extract total protein using RIPA lysis buffer containing 1% PMSF protease inhibitor

• Determine protein concentration using BCA assay

• Load 20-50μg protein per lane on 10% SDS-PAGE gel

• Transfer to PVDF membrane (optimal for PTGIS detection)

• Block with 5% skim milk for 3 hours at room temperature

• Incubate with primary PTGIS antibody (1:1000 dilution) overnight at 4°C

• Wash three times with TBST, 5 minutes per wash

• For unconjugated antibodies: incubate with HRP-labeled secondary antibody (typically goat anti-rabbit IgG) for 1 hour at room temperature
  For HRP-conjugated antibodies: proceed directly to detection step

• Wash three times with TBST, 5 minutes each

• Visualize using ECL detection and capture images with appropriate imaging system

• Quantify relative expression using software such as Image J

For validation, β-actin is typically used as a loading control, and results should be normalized to this reference protein.

What immunohistochemistry protocol is recommended for PTGIS detection in tissue sections?

The following protocol has been validated for PTGIS detection in paraffin-embedded tissue sections:

• Fix tissues in 10% neutral buffered formalin solution and embed in paraffin

• Section tissues at 4-5μm thickness

• Dewax slides in xylene and rehydrate through gradient alcohol series

• Perform antigen retrieval by microwaving in citric buffer for 15 minutes

• Treat with 0.3% hydrogen peroxide for 15 minutes to block endogenous peroxidase activity

• Block non-specific binding with 5% BSA for 30-60 minutes at room temperature

• Incubate with PTGIS primary antibody (1:50 dilution recommended) overnight at 4°C

• Rinse sections and incubate with biotinylated secondary antibody for 60 minutes at room temperature
  (For HRP-conjugated antibodies, this step may be skipped)

• Visualize using 3,3-diaminobenzidine tetrahydrochloride (DAB) staining

• Counterstain with hematoxylin, dehydrate, and mount with appropriate mounting medium

PTGIS typically shows cytoplasmic localization, with expression patterns varying significantly between normal and pathological tissues.

How should samples be prepared for optimal PTGIS detection?

Sample preparation is critical for reliable PTGIS detection across different experimental platforms:

• Cell lysates for Western blotting:

  • Harvest cells at 80-90% confluence

  • Lyse using RIPA buffer containing protease inhibitors

  • Perform brief sonication (3-5 pulses at medium intensity) to ensure complete membrane disruption

  • Centrifuge at 14,000g for 15 minutes at 4°C to remove cellular debris

  • Store extracted proteins at -80°C with minimal freeze-thaw cycles

• Tissue samples for immunohistochemistry:

  • Fix tissues immediately after collection in 10% neutral buffered formalin for 24-48 hours

  • Process and embed in paraffin following standard protocols

  • For frozen sections, embed in OCT compound and snap-freeze in liquid nitrogen

  • Use freshly cut sections for optimal antigen preservation

• RNA extraction for PTGIS expression analysis:

  • Extract total RNA using TRIzol or equivalent reagent

  • Ensure RNA integrity by electrophoresis or Bioanalyzer analysis (RIN > 7)

  • Perform reverse transcription using validated protocols

  • For RT-qPCR, use PTGIS-specific primers:
    Forward: 5'-ACTGTTGCTGCTGCTGCTACTG-3'
    Reverse: 5'-GAGGAAGATGGCATAGGCATGGAAG-3'

Standardized sample preparation protocols minimize experimental variability and improve reproducibility of PTGIS detection across different research settings.

What are common causes of non-specific binding when using PTGIS antibodies?

Non-specific binding is a common challenge in PTGIS antibody applications. The following methodological approaches can address specific causes:

• High background in Western blot:

  • Increase blocking time (5% milk or BSA for 3+ hours)

  • Optimize primary antibody concentration (perform titration experiments)

  • Increase washing frequency (5-6 times) and duration (10 minutes each)

  • Use freshly prepared buffers and reagents

  • For HRP-conjugated antibodies, ensure complete blocking of endogenous peroxidase activity

• Cross-reactivity issues:

  • Verify antibody specificity against the intended region of PTGIS (peptide competition assays)

  • Select antibodies targeting unique epitopes (such as those targeting amino acids 210-238 from the central region of human PTGIS)

  • Include appropriate negative controls (isotype controls, secondary-only controls)

  • For tissue work, include antigen-negative tissues as controls

• Inconsistent results between experiments:

  • Standardize protein loading (20-50μg recommended)

  • Use purified antibodies (protein A column purification followed by peptide affinity purification has shown optimal results)

  • Maintain consistent incubation times and temperatures

  • Implement quality control procedures for all reagents

Proper experimental design with appropriate controls is essential for distinguishing specific PTGIS signal from background or cross-reactivity artifacts.

How can PTGIS antibody specificity be validated in experimental settings?

Rigorous validation of PTGIS antibody specificity is crucial for research reliability. The following validation approaches are recommended:

• Peptide competition assay:

  • Pre-incubate antibody with excess immunizing peptide (5-10x molar excess)

  • Run parallel Western blots with blocked and unblocked antibody

  • Specific bands should disappear in the peptide-blocked sample

• Genetic manipulation validation:

  • Overexpress PTGIS using plasmid transfection (pEX-2-PTGIS has been validated)

  • Knockdown PTGIS using siRNA or CRISPR-Cas9

  • Verify band intensity changes corresponding to genetic manipulation

• Multi-antibody validation:

  • Test multiple antibodies targeting different PTGIS epitopes

  • Compare detection patterns across antibodies

  • Consistent results across different antibodies provide stronger validation

• Cross-species reactivity assessment:

  • Test antibody against PTGIS from different species when cross-reactivity is claimed

  • Verify conservation of the target epitope sequence across species

  • Document species-specific molecular weight variations

These validation approaches provide critical evidence that the observed signal is specific to PTGIS rather than resulting from antibody cross-reactivity or experimental artifacts.

How can PTGIS antibodies be utilized in studying the tumor microenvironment?

PTGIS has emerged as a significant factor in tumor microenvironment studies, with methodological approaches focusing on immune cell interactions:

• Dual immunostaining protocols:

  • Perform multiplexed immunofluorescence with PTGIS antibody and markers for tumor-associated macrophages (CD68, CD163)

  • Include markers for regulatory T cells (FOXP3, CD25) based on observed correlations

  • Implement spectral unmixing for accurate signal separation

  • Analyze cellular co-localization and spatial relationships

• Correlation analysis with immune infiltrates:

  • Quantify PTGIS expression in tumor tissues using validated antibodies

  • Measure infiltration of immune cell populations using established markers:

    • Macrophages: CD68, CD163 (M2)

    • T cells: CD4, CD8, FOXP3

    • Neutrophils: CD66b, MPO

    • Dendritic cells: CD11c, CD83

  • Analyze correlation coefficients between PTGIS expression and immune cell densities

• Functional studies in tumor models:

  • Manipulate PTGIS expression in cancer cell lines using overexpression or knockdown approaches

  • Co-culture with immune cells to assess effects on polarization and function

  • Measure cytokine/chemokine production in response to altered PTGIS expression

Research has demonstrated significant correlations between PTGIS expression and infiltrating immune cells, particularly macrophages (r = 0.638, P = 1.12e-43 in gastric cancer), CD4+ T cells (r = 0.477, P = 3.63e-22), and dendritic cells (r = 0.443, P = 2.68e-19) , suggesting PTGIS may influence immune cell recruitment and function within the tumor microenvironment.

What approaches are recommended for studying PTGIS in relation to cell proliferation and apoptosis?

Investigating PTGIS's role in cellular proliferation and apoptosis requires integrated methodological approaches:

• Cell cycle analysis following PTGIS manipulation:

  • Transfect cells with PTGIS expression plasmids (e.g., pEX-2-PTGIS)

  • Perform flow cytometric analysis with propidium iodide staining

  • Quantify cell distribution across G0/G1, S, and G2/M phases

  • Research has shown PTGIS overexpression induces G0/G1 arrest in certain cell types

• Proliferation marker analysis:

  • Following PTGIS manipulation, assess proliferation markers using validated antibodies:

    • C-myc (1:1000 dilution recommended)

    • Cyclin D1 (1:1000 dilution recommended)

  • Quantify changes in protein expression by Western blot

  • Correlate with functional proliferation assays (CCK8, MTT, or BrdU incorporation)

• Apoptosis assessment protocols:

  • Perform Annexin-V/PI staining followed by flow cytometric analysis

  • Quantify apoptotic cell percentages following PTGIS manipulation

  • Assess apoptotic pathway activation through:

    • Bax/Bcl-2 ratio determination

    • Cleaved-caspase 3 levels measurement

    • PARP cleavage detection

Research has demonstrated that PTGIS overexpression significantly increases the Bax/Bcl-2 ratio and cleaved-caspase 3 levels in certain cell types, confirming its pro-apoptotic effects in specific cellular contexts .

How can researchers investigate the epigenetic regulation of PTGIS expression?

PTGIS expression is subject to epigenetic regulation, particularly DNA methylation, which can be studied through several methodological approaches:

• Methylation-specific PCR (MSP) analysis:

  • Extract genomic DNA from cells or tissues

  • Perform bisulfite conversion (converting unmethylated cytosines to uracils)

  • Design primers specific for methylated and unmethylated PTGIS promoter regions

  • Analyze methylation status through PCR amplification patterns

• DNA methyltransferase (DNMT) analysis:

  • Assess expression levels of DNMTs (DNMT1, DNMT3a, DNMT3b) by Western blotting

  • Correlate DNMT expression with PTGIS promoter methylation status

  • Implement DNMT inhibitor treatments (e.g., 5-azacytidine) to assess rescue of PTGIS expression

• Chromatin immunoprecipitation (ChIP) assays:

  • Use antibodies against histone modifications associated with active (H3K4me3) or repressed (H3K27me3) chromatin

  • Precipitate DNA-protein complexes and perform qPCR with PTGIS promoter-specific primers

  • Correlate histone modification patterns with PTGIS expression levels

Research has identified PTGIS promoter hypermethylation in several disease models, including CCl4-induced liver fibrosis , making these epigenetic approaches particularly valuable for understanding PTGIS regulation in pathological contexts.

How should contradictory PTGIS expression data across different cancer types be analyzed?

PTGIS expression shows complex patterns across cancer types, requiring specialized analytical approaches:

• Cancer type-specific analysis framework:

  • Separate analyses by cancer type rather than pooling diverse tumors

  • Document tissue-specific PTGIS expression patterns in normal tissues as baselines

  • Consider tissue-specific cut-off values for "high" versus "low" expression

  • Account for tumor heterogeneity through multiple sampling approaches

• Prognostic value assessment methodology:

  • Implement survival analysis using Kaplan-Meier curves stratified by PTGIS expression

  • Calculate hazard ratios using Cox proportional hazards models

  • Perform multivariate analysis adjusting for clinical covariates

  • Report tissue-specific prognostic implications (adverse in lung, ovarian, and gastric cancers)

• Tumor microenvironment context integration:

  • Correlate PTGIS expression with tumor purity measurements

  • Assess relationship with specific immune cell populations across cancer types

  • Document cancer-specific correlation patterns with infiltrating immune cells

  • Consider the influence of tumor purity on gene expression analysis

What statistical approaches are recommended for analyzing correlations between PTGIS and immune infiltrates?

Analyzing relationships between PTGIS expression and immune cell infiltration requires rigorous statistical methodologies:

These statistical approaches provide a framework for rigorous analysis of PTGIS's relationship with the immune microenvironment, informing its potential role in immunomodulation and therapeutic targeting.